Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Chin, Alexander W.; Mavris, Dimitri N.

2016-01-01

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

Application of super-twisting observers to the estimation of state and unknown inputs in an anaerobic digestion system.

PubMed

Sbarciog, M; Moreno, J A; Vande Wouwer, A

2014-01-01

This paper presents the estimation of the unknown states and inputs of an anaerobic digestion system characterized by a two-step reaction model. The estimation is based on the measurement of the two substrate concentrations and of the outflow rate of biogas and relies on the use of an observer, consisting of three parts. The first is a generalized super-twisting observer, which estimates a linear combination of the two input concentrations. The second is an asymptotic observer, which provides one of the two biomass concentrations, whereas the third is a super-twisting observer for one of the input concentrations and the second biomass concentration.

Estimation of the uncertainty of analyte concentration from the measurement uncertainty.

PubMed

Brown, Simon; Cooke, Delwyn G; Blackwell, Leonard F

2015-09-01

Ligand-binding assays, such as immunoassays, are usually analysed using standard curves based on the four-parameter and five-parameter logistic models. An estimate of the uncertainty of an analyte concentration obtained from such curves is needed for confidence intervals or precision profiles. Using a numerical simulation approach, it is shown that the uncertainty of the analyte concentration estimate becomes significant at the extremes of the concentration range and that this is affected significantly by the steepness of the standard curve. We also provide expressions for the coefficient of variation of the analyte concentration estimate from which confidence intervals and the precision profile can be obtained. Using three examples, we show that the expressions perform well.

A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model

NASA Astrophysics Data System (ADS)

Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kue-Young; Jun, Seong-Chun; Choung, Sungwook; Yun, Seong-Taek; Oh, Junho; Kim, Hyun-Jun

2017-11-01

In this study, a data-driven method for predicting CO2 leaks and associated concentrations from geological CO2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems.

Probabilistic Reverse dOsimetry Estimating Exposure Distribution (PROcEED)

EPA Pesticide Factsheets

PROcEED is a web-based application used to conduct probabilistic reverse dosimetry calculations.The tool is used for estimating a distribution of exposure concentrations likely to have produced biomarker concentrations measured in a population.

Methods for estimating expected blood alcohol concentration.

DOT National Transportation Integrated Search

1980-12-01

Estimates of blood alcohol concentration (BAC) typically are based on the amount of alcohol consumed per pound body weight. This method fails to consider food intake and body composition, which significantly affect BAC. A laboratory experiment was co...

Methods for estimating expected blood alcohol concentration

DOT National Transportation Integrated Search

1980-08-01

Estimates of blood alcohol concentration (BAC) typically are based on the amount of alcohol consumed per pound bodyweight. This method fails to consider either food intake or body composition, factors which significantly affect BAC. A laboratory expe...

Concentrations, loads, and yields of total phosphorus, total nitrogen, and suspended sediment and bacteria concentrations in the Wister Lake Basin, Oklahoma and Arkansas, 2011-13

USGS Publications Warehouse

Buck, Stephanie D.

2014-01-01

The Poteau Valley Improvement Authority uses Wister Lake in southeastern Oklahoma as a public water supply. Total phosphorus, total nitrogen, and suspended sediments from agricultural runoff and discharges from wastewater treatment plants and other sources have degraded water quality in the lake. As lake-water quality has degraded, water-treatment cost, chemical usage, and sludge production have increased for the Poteau Valley Improvement Authority. The U.S. Geological Survey (USGS), in cooperation with the Poteau Valley Improvement Authority, investigated and summarized concentrations of total phosphorus, total nitrogen, suspended sediment, and bacteria (Escherichia coli and Enterococcus sp.) in surface water flowing to Wister Lake. Estimates of total phosphorus, total nitrogen, and suspended sediment loads, yields, and flow-weighted mean concentrations of total phosphorus and total nitrogen concentrations were made for the Wister Lake Basin for a 3-year period from October 2010 through September 2013. Data from water samples collected at fixed time increments during base-flow conditions and during runoff conditions at the Poteau River at Loving, Okla. (USGS station 07247015), the Poteau River near Heavener, Okla. (USGS station 07247350), and the Fourche Maline near Leflore, Okla. (USGS station 07247650), water-quality stations were used to evaluate water quality over the range of streamflows in the basin. These data also were collected to estimate annual constituent loads and yields by using regression models. At the Poteau River stations, total phosphorus, total nitrogen, and suspended sediment concentrations in surface-water samples were significantly larger in samples collected during runoff conditions than in samples collected during base-flow conditions. At the Fourche Maline station, in contrast, concentrations of these constituents in water samples collected during runoff conditions were not significantly larger than concentrations during base-flow conditions. Flow-weighted mean total phosphorus concentrations at all three stations from 2011 to 2013 were several times larger than the Oklahoma State Standard for Scenic Rivers (0.037 milligrams per liter [mg/L]), with the largest flow-weighted phosphorus concentrations typically being measured at the Poteau River at Loving, Okla., station. Flow-weighted mean total nitrogen concentrations did not vary substantially between the Poteau River stations and the Fourche Maline near Leflore, Okla., station. At all of the sampled water-quality stations, bacteria (Escherichia coli and Enterococcus sp.) concentrations were substantially larger in water samples collected during runoff conditions than in water samples collected during base-flow conditions from 2011 to 2013. Estimated annual loads of total phosphorus, total nitrogen, and suspended sediment in the Poteau River stations during runoff conditions ranged from 82 to 98 percent of the total annual loads of those constituents. Estimated annual loads of total phosphorus, total nitrogen, and suspended sediment in the Fourche Maline during runoff conditions ranged from 86 to nearly 100 percent of the total annual loads. Estimated seasonal total phosphorus loads generally were smallest during base-flow and runoff conditions in autumn. Estimated seasonal total phosphorus loads during base-flow conditions tended to be largest in winter and during runoff conditions tended to be largest in the spring. Estimated seasonal total nitrogen loads tended to be smallest in autumn during base-flow and runoff conditions and largest in winter during runoff conditions. Estimated seasonal suspended sediment loads tended to be smallest during base-flow conditions in the summer and smallest during runoff conditions in the autumn. The largest estimated seasonal suspended sediment loads during runoff conditions typically were in the spring. The estimated mean annual total phosphorus yield was largest at the Poteau River at Loving, Okla., water-quality station. The estimated mean annual total phosphorus yield was largest during base flow at the Poteau River at Loving, Okla., water-quality station and at both of the Poteau River water-quality stations during runoff conditions. The estimated mean annual total nitrogen yields were largest at the Poteau River water-quality stations. Estimated mean annual total nitrogen yields were largest during base-flow and runoff conditions at the Poteau River at Loving, Okla., water-quality station. The estimated mean annual suspended sediment yield was largest at the Poteau River near Heavener, Okla., water-quality station during base-flow and runoff conditions. Flow-weighted mean concentrations indicated that total phosphorus inputs from the Poteau River Basin in the Wister Lake Basin were larger than from the Fourche Maline Basin. Flow-weighted mean concentrations of total nitrogen did not vary spatially in a consistent manner. The Poteau River and the Fourche Maline contributed estimated annual total phosphorus loads of 137 to 278 tons per year (tons/yr) to Wister Lake. Between 89 and 95 percent of the annual total phosphorus loads were transported to Wister Lake during runoff conditions. The Poteau River and the Fourche Maline contributed estimated annual total nitrogen loads of 657 to 1,294 tons/yr, with 86 to 94 percent of the annual total nitrogen loads being transported to Wister Lake during runoff conditions. The Poteau River and the Fourche Maline contributed estimated annual total suspended sediment loads of 110,919 to 234,637 tons/yr, with 94 to 99 percent of the annual suspended sediment loads being transported to Wister Lake during runoff conditions. Most of the total phosphorus and suspended sediment were delivered to Wister Lake during runoff conditions in the spring. The majority of the total nitrogen was delivered to Wister Lake during runoff conditions in winter.

Estimating the capacity value of concentrating solar power plants: A case study of the southwestern United States

DOE PAGES

Madaeni, Seyed Hossein; Sioshansi, Ramteen; Denholm, Paul

2012-01-27

Here, we estimate the capacity value of concentrating solar power (CSP) plants without thermal energy storage in the southwestern U.S. Our results show that CSP plants have capacity values that are between 45% and 95% of maximum capacity, depending on their location and configuration. We also examine the sensitivity of the capacity value of CSP to a number of factors and show that capacity factor-based methods can provide reasonable approximations of reliability-based estimates.

A Comparison of Turbidity-Based and Streamflow-Based Estimates of Suspended-Sediment Concentrations in Three Chesapeake Bay Tributaries

USGS Publications Warehouse

Jastram, John D.; Moyer, Douglas; Hyer, Kenneth

2009-01-01

Fluvial transport of sediment into the Chesapeake Bay estuary is a persistent water-quality issue with major implications for the overall health of the bay ecosystem. Accurately and precisely estimating the suspended-sediment concentrations (SSC) and loads that are delivered to the bay, however, remains challenging. Although manual sampling of SSC produces an accurate series of point-in-time measurements, robust extrapolation to unmeasured periods (especially highflow periods) has proven to be difficult. Sediment concentrations typically have been estimated using regression relations between individual SSC values and associated streamflow values; however, suspended-sediment transport during storm events is extremely variable, and it is often difficult to relate a unique SSC to a given streamflow. With this limitation for estimating SSC, innovative approaches for generating detailed records of suspended-sediment transport are needed. One effective method for improved suspended-sediment determination involves the continuous monitoring of turbidity as a surrogate for SSC. Turbidity measurements are theoretically well correlated to SSC because turbidity represents a measure of water clarity that is directly influenced by suspended sediments; thus, turbidity-based estimation models typically are effective tools for generating SSC data. The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency Chesapeake Bay Program and Virginia Department of Environmental Quality, initiated continuous turbidity monitoring on three major tributaries of the bay - the James, Rappahannock, and North Fork Shenandoah Rivers - to evaluate the use of turbidity as a sediment surrogate in rivers that deliver sediment to the bay. Results of this surrogate approach were compared to the traditionally applied streamflow-based approach for estimating SSC. Additionally, evaluation and comparison of these two approaches were conducted for nutrient estimations. Results demonstrate that the application of turbidity-based estimation models provides an improved method for generating a continuous record of SSC, relative to the classical approach that uses streamflow as a surrogate for SSC. Turbidity-based estimates of SSC were found to be more accurate and precise than SSC estimates from streamflow-based approaches. The turbidity-based SSC estimation models explained 92 to 98 percent of the variability in SSC, while streamflow-based models explained 74 to 88 percent of the variability in SSC. Furthermore, the mean absolute error of turbidity-based SSC estimates was 50 to 87 percent less than the corresponding values from the streamflow-based models. Statistically significant differences were detected between the distributions of residual errors and estimates from the two approaches, indicating that the turbidity-based approach yields estimates of SSC with greater precision than the streamflow-based approach. Similar improvements were identified for turbidity-based estimates of total phosphorus, which is strongly related to turbidity because total phosphorus occurs predominantly in particulate form. Total nitrogen estimation models based on turbidity and streamflow generated estimates of similar quality, with the turbidity-based models providing slight improvements in the quality of estimations. This result is attributed to the understanding that nitrogen transport is dominated by dissolved forms that relate less directly to streamflow and turbidity. Improvements in concentration estimation resulted in improved estimates of load. Turbidity-based suspended-sediment loads estimated for the James River at Cartersville, VA, monitoring station exhibited tighter confidence interval bounds and a coefficient of variation of 12 percent, compared with a coefficient of variation of 38 percent for the streamflow-based load.

Evaluation of concentrations of pharmaceuticals detected in sewage influents in Japan by using annual shipping and sales data.

PubMed

Azuma, Takashi; Nakada, Norihide; Yamashita, Naoyuki; Tanaka, Hiroaki

2015-11-01

A year-round monitoring survey of sewage flowing into sewage treatment plants located in urban Japan was conducted by targeting seven representative pharmaceutical components-atenolol (ATL), ciprofloxacin (CFX), clarithromycin (CTM), diclofenac (DCF), diltiazem (DTZ), disopyramide (DSP), and sulpiride (SPR)-detected in the river environment. For each of these components, two types of predicted concentration were estimated on the basis of two types of data (the shipping volume and sales volume of each component). The measured concentration of each component obtained through the survey and the two types of estimated predicted concentration of each component were then compared. The correspondence ratio between the predicted concentration estimated from the shipping volume of the component and the measured concentration (predicted concentration/measured concentration) was, for ATL, 3.1; CFX, 1.4; CTM, 1.4; DCF, 0.2; DTZ, 0.9; DSP, 11.6; and SPR, 1.1. The correspondence ratio between the predicted concentration estimated from the sales volume of the component and the measured concentration was, for ATL, 0.5; CFX, 1.1; CTM, 0.8; DCF, 0.1; DTZ, 0.2; DSP, 0.7; and SPR, 0.8. Although a generally corresponding trend was seen regardless of whether the prediction was based on shipping volume or sales volume, the predicted concentrations estimated from the shipping volumes of all components expect DSP were found, to our knowledge for the first time in Japan, to correspond better than those based on sales volumes to the measured concentrations. These findings should help to improve the prediction accuracy of concentrations of pharmaceutical components in river waters. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effects of Blood-Alcohol Concentration (BAC) Feedback on BAC Estimates Over Time

ERIC Educational Resources Information Center

Bullers, Susan; Ennis, Melissa

2006-01-01

This study examines the effects of self-tested blood alcohol concentration (BAC) feedback, from personal hand-held breathalyzers, on the accuracy of BAC estimation. Using an e-mail prompted web-based questionnaire, 19 participants were asked to report both BAC estimates and subsequently measured BAC levels over the course of 27 days. Results from…

Gas-hydrate concentration estimated from P- and S-wave velocities at the Mallik 2L-38 research well, Mackenzie Delta, Canada

NASA Astrophysics Data System (ADS)

Carcione, José M.; Gei, Davide

2004-05-01

We estimate the concentration of gas hydrate at the Mallik 2L-38 research site using P- and S-wave velocities obtained from well logging and vertical seismic profiles (VSP). The theoretical velocities are obtained from a generalization of Gassmann's modulus to three phases (rock frame, gas hydrate and fluid). The dry-rock moduli are estimated from the log profiles, in sections where the rock is assumed to be fully saturated with water. We obtain hydrate concentrations up to 75%, average values of 37% and 21% from the VSP P- and S-wave velocities, respectively, and 60% and 57% from the sonic-log P- and S-wave velocities, respectively. The above averages are similar to estimations obtained from hydrate dissociation modeling and Archie methods. The estimations based on the P-wave velocities are more reliable than those based on the S-wave velocities.

Estimation of phytoplankton production from space: current status and future potential of satellite remote sensing.

PubMed

Joint; Groom

2000-07-30

A new generation of ocean colour satellites is now operational, with frequent observation of the global ocean. This paper reviews the potential to estimate marine primary production from satellite images. The procedures involved in retrieving estimates of phytoplankton biomass, as pigment concentrations, are discussed. Algorithms are applied to SeaWiFS ocean colour data to indicate seasonal variations in phytoplankton biomass in the Celtic Sea, on the continental shelf to the south west of the UK. Algorithms to estimate primary production rates from chlorophyll concentration are compared and the advantages and disadvantage discussed. The simplest algorithms utilise correlations between chlorophyll concentration and production rate and one equation is used to estimate daily primary production rates for the western English Channel and Celtic Sea; these estimates compare favourably with published values. Primary production for the central Celtic Sea in the period April to September inclusive is estimated from SeaWiFS data to be 102 gC m(-2) in 1998 and 93 gC m(-2) in 1999; published estimates, based on in situ incubations, are ca. 80 gC m(-2). The satellite data demonstrate large variations in primary production between 1998 and 1999, with a significant increase in late summer in 1998 which did not occur in 1999. Errors are quantified for the estimation of primary production from simple algorithms based on satellite-derived chlorophyll concentration. These data show the potential to obtain better estimates of marine primary production than are possible with ship-based methods, with the ability to detect short-lived phytoplankton blooms. In addition, the potential to estimate new production from satellite data is discussed.

A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model.

PubMed

Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kue-Young; Jun, Seong-Chun; Choung, Sungwook; Yun, Seong-Taek; Oh, Junho; Kim, Hyun-Jun

2017-11-01

In this study, a data-driven method for predicting CO 2 leaks and associated concentrations from geological CO 2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO 2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO 2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO 2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative cancer risk assessment for ethylene oxide inhalation in occupational settings.

PubMed

Valdez-Flores, Ciriaco; Sielken, Robert L; Teta, M Jane

2011-10-01

The estimated occupational ethylene oxide (EO) exposure concentrations corresponding to specified extra risks are calculated for lymphoid mortality as the most appropriate endpoint, despite the lack of a statistically significant exposure-response relationship. These estimated concentrations are for occupational exposures--40 years of occupational inhalation exposure to EO from age 20 to age 60 years. The estimated occupational inhalation exposure concentrations (ppm) corresponding to specified extra risks of lymphoid mortality to age 70 years in a population of male and female EO workers are based on Cox proportional hazards models of the most recent updated epidemiology cohort mortality studies of EO workers and a standard life-table calculation. An occupational exposure at an inhalation concentration of 2.77 ppm EO is estimated to result in an extra risk of lymphoid mortality of 4 in 10,000 (0.0004) in the combined worker population of men and women from the two studies. The corresponding estimated concentration decreases slightly to 2.27 ppm when based on only the men in the updated cohorts combined. The difference in these estimates reflects the difference between combining all of the available data or focusing on only the men and excluding the women who did not show an increase in lymphoid mortality with EO inhalation exposure. The results of sensitivity analyses using other mortality endpoints (all lymphohematopoietic tissue cancers, leukemia) support the choice of lymphoid tumor mortality for estimation of extra risk.

Bruise chromophore concentrations over time

NASA Astrophysics Data System (ADS)

Duckworth, Mark G.; Caspall, Jayme J.; Mappus, Rudolph L., IV; Kong, Linghua; Yi, Dingrong; Sprigle, Stephen H.

2008-03-01

During investigations of potential child and elder abuse, clinicians and forensic practitioners are often asked to offer opinions about the age of a bruise. A commonality between existing methods of bruise aging is analysis of bruise color or estimation of chromophore concentration. Relative chromophore concentration is an underlying factor that determines bruise color. We investigate a method of chromophore concentration estimation that can be employed in a handheld imaging spectrometer with a small number of wavelengths. The method, based on absorbance properties defined by Beer-Lambert's law, allows estimation of differential chromophore concentration between bruised and normal skin. Absorption coefficient data for each chromophore are required to make the estimation. Two different sources of this data are used in the analysis- generated using Independent Component Analysis and taken from published values. Differential concentration values over time, generated using both sources, show correlation to published models of bruise color change over time and total chromophore concentration over time.

Estimating Risk from Ambient Concentrations of Acrolein across the United States

PubMed Central

Woodruff, Tracey J.; Wells, Ellen M.; Holt, Elizabeth W.; Burgin, Deborah E.; Axelrad, Daniel A.

2007-01-01

Background Estimated ambient concentrations of acrolein, a hazardous air pollutant, are greater than the U.S. Environmental Protection Agency (EPA) reference concentration throughout the United States, making it a concern for human health. However, there is no method for assessing the extent of risk under the U.S. EPA noncancer risk assessment framework. Objectives We estimated excess risks from ambient concentrations of acrolein based on dose–response modeling of a study in rats with a relationship between acrolein and residual volume/total lung capacity ratio (RV/TLC) and specific compliance (sCL), markers for altered lung function. Methods Based on existing literature, we defined values above the 90th percentile for controls as “adverse.” We estimated the increase over baseline response that would occur in the human population from estimated ambient concentrations of acrolein, taken from the U.S. EPA’s National-Scale Air Toxics Assessment for 1999, after standard animal-to-human conversions and extrapolating to doses below the experimental data. Results The estimated median additional number of adverse sCL outcomes across the United States was approximately 2.5 cases per 1,000 people. The estimated range of additional outcomes from the 5th to the 95th percentile of acrolein concentration levels across census tracts was 0.28–14 cases per 1,000. For RV/TLC, the median additional outcome was 0.002 per 1,000, and the additional outcome at the 95th percentile was 0.13 per 1,000. Conclusions Although there are uncertainties in estimating human risks from animal data, this analysis demonstrates a method for estimating health risks for noncancer effects and suggests that acrolein could be associated with decreased respiratory function in the United States. PMID:17431491

Binational arsenic exposure survey: methodology and estimated arsenic intake from drinking water and urinary arsenic concentrations.

PubMed

Roberge, Jason; O'Rourke, Mary Kay; Meza-Montenegro, Maria Mercedes; Gutiérrez-Millán, Luis Enrique; Burgess, Jefferey L; Harris, Robin B

2012-04-01

The Binational Arsenic Exposure Survey (BAsES) was designed to evaluate probable arsenic exposures in selected areas of southern Arizona and northern Mexico, two regions with known elevated levels of arsenic in groundwater reserves. This paper describes the methodology of BAsES and the relationship between estimated arsenic intake from beverages and arsenic output in urine. Households from eight communities were selected for their varying groundwater arsenic concentrations in Arizona, USA and Sonora, Mexico. Adults responded to questionnaires and provided dietary information. A first morning urine void and water from all household drinking sources were collected. Associations between urinary arsenic concentration (total, organic, inorganic) and estimated level of arsenic consumed from water and other beverages were evaluated through crude associations and by random effects models. Median estimated total arsenic intake from beverages among participants from Arizona communities ranged from 1.7 to 14.1 µg/day compared to 0.6 to 3.4 µg/day among those from Mexico communities. In contrast, median urinary inorganic arsenic concentrations were greatest among participants from Hermosillo, Mexico (6.2 µg/L) whereas a high of 2.0 µg/L was found among participants from Ajo, Arizona. Estimated arsenic intake from drinking water was associated with urinary total arsenic concentration (p < 0.001), urinary inorganic arsenic concentration (p < 0.001), and urinary sum of species (p < 0.001). Urinary arsenic concentrations increased between 7% and 12% for each one percent increase in arsenic consumed from drinking water. Variability in arsenic intake from beverages and urinary arsenic output yielded counter intuitive results. Estimated intake of arsenic from all beverages was greatest among Arizonans yet participants in Mexico had higher urinary total and inorganic arsenic concentrations. Other contributors to urinary arsenic concentrations should be evaluated.

Binational Arsenic Exposure Survey: Methodology and Estimated Arsenic Intake from Drinking Water and Urinary Arsenic Concentrations

PubMed Central

Roberge, Jason; O’Rourke, Mary Kay; Meza-Montenegro, Maria Mercedes; Gutiérrez-Millán, Luis Enrique; Burgess, Jefferey L.; Harris, Robin B.

2012-01-01

The Binational Arsenic Exposure Survey (BAsES) was designed to evaluate probable arsenic exposures in selected areas of southern Arizona and northern Mexico, two regions with known elevated levels of arsenic in groundwater reserves. This paper describes the methodology of BAsES and the relationship between estimated arsenic intake from beverages and arsenic output in urine. Households from eight communities were selected for their varying groundwater arsenic concentrations in Arizona, USA and Sonora, Mexico. Adults responded to questionnaires and provided dietary information. A first morning urine void and water from all household drinking sources were collected. Associations between urinary arsenic concentration (total, organic, inorganic) and estimated level of arsenic consumed from water and other beverages were evaluated through crude associations and by random effects models. Median estimated total arsenic intake from beverages among participants from Arizona communities ranged from 1.7 to 14.1 µg/day compared to 0.6 to 3.4 µg/day among those from Mexico communities. In contrast, median urinary inorganic arsenic concentrations were greatest among participants from Hermosillo, Mexico (6.2 µg/L) whereas a high of 2.0 µg/L was found among participants from Ajo, Arizona. Estimated arsenic intake from drinking water was associated with urinary total arsenic concentration (p < 0.001), urinary inorganic arsenic concentration (p < 0.001), and urinary sum of species (p < 0.001). Urinary arsenic concentrations increased between 7% and 12% for each one percent increase in arsenic consumed from drinking water. Variability in arsenic intake from beverages and urinary arsenic output yielded counter intuitive results. Estimated intake of arsenic from all beverages was greatest among Arizonans yet participants in Mexico had higher urinary total and inorganic arsenic concentrations. Other contributors to urinary arsenic concentrations should be evaluated. PMID:22690182

Aquatic concentrations of chemical analytes compared to ecotoxicity estimates

USGS Publications Warehouse

Kostich, Mitchell S.; Flick, Robert W.; Angela L. Batt,; Mash, Heath E.; Boone, J. Scott; Furlong, Edward T.; Kolpin, Dana W.; Glassmeyer, Susan T.

2017-01-01

We describe screening level estimates of potential aquatic toxicity posed by 227 chemical analytes that were measured in 25 ambient water samples collected as part of a joint USGS/USEPA drinking water plant study. Measured concentrations were compared to biological effect concentration (EC) estimates, including USEPA aquatic life criteria, effective plasma concentrations of pharmaceuticals, published toxicity data summarized in the USEPA ECOTOX database, and chemical structure-based predictions. Potential dietary exposures were estimated using a generic 3-tiered food web accumulation scenario. For many analytes, few or no measured effect data were found, and for some analytes, reporting limits exceeded EC estimates, limiting the scope of conclusions. Results suggest occasional occurrence above ECs for copper, aluminum, strontium, lead, uranium, and nitrate. Sparse effect data for manganese, antimony, and vanadium suggest that these analytes may occur above ECs, but additional effect data would be desirable to corroborate EC estimates. These conclusions were not affected by bioaccumulation estimates. No organic analyte concentrations were found to exceed EC estimates, but ten analytes had concentrations in excess of 1/10th of their respective EC: triclocarban, norverapamil, progesterone, atrazine, metolachlor, triclosan, para-nonylphenol, ibuprofen, venlafaxine, and amitriptyline, suggesting more detailed characterization of these analytes.

Aquatic concentrations of chemical analytes compared to ecotoxicity estimates.

PubMed

Kostich, Mitchell S; Flick, Robert W; Batt, Angela L; Mash, Heath E; Boone, J Scott; Furlong, Edward T; Kolpin, Dana W; Glassmeyer, Susan T

2017-02-01

We describe screening level estimates of potential aquatic toxicity posed by 227 chemical analytes that were measured in 25 ambient water samples collected as part of a joint USGS/USEPA drinking water plant study. Measured concentrations were compared to biological effect concentration (EC) estimates, including USEPA aquatic life criteria, effective plasma concentrations of pharmaceuticals, published toxicity data summarized in the USEPA ECOTOX database, and chemical structure-based predictions. Potential dietary exposures were estimated using a generic 3-tiered food web accumulation scenario. For many analytes, few or no measured effect data were found, and for some analytes, reporting limits exceeded EC estimates, limiting the scope of conclusions. Results suggest occasional occurrence above ECs for copper, aluminum, strontium, lead, uranium, and nitrate. Sparse effect data for manganese, antimony, and vanadium suggest that these analytes may occur above ECs, but additional effect data would be desirable to corroborate EC estimates. These conclusions were not affected by bioaccumulation estimates. No organic analyte concentrations were found to exceed EC estimates, but ten analytes had concentrations in excess of 1/10th of their respective EC: triclocarban, norverapamil, progesterone, atrazine, metolachlor, triclosan, para-nonylphenol, ibuprofen, venlafaxine, and amitriptyline, suggesting more detailed characterization of these analytes. Published by Elsevier B.V.

Estimation of time-variable fast flow path chemical concentrations for application in tracer-based hydrograph separation analyses

USGS Publications Warehouse

Kronholm, Scott C.; Capel, Paul D.

2016-01-01

Mixing models are a commonly used method for hydrograph separation, but can be hindered by the subjective choice of the end-member tracer concentrations. This work tests a new variant of mixing model that uses high-frequency measures of two tracers and streamflow to separate total streamflow into water from slowflow and fastflow sources. The ratio between the concentrations of the two tracers is used to create a time-variable estimate of the concentration of each tracer in the fastflow end-member. Multiple synthetic data sets, and data from two hydrologically diverse streams, are used to test the performance and limitations of the new model (two-tracer ratio-based mixing model: TRaMM). When applied to the synthetic streams under many different scenarios, the TRaMM produces results that were reasonable approximations of the actual values of fastflow discharge (±0.1% of maximum fastflow) and fastflow tracer concentrations (±9.5% and ±16% of maximum fastflow nitrate concentration and specific conductance, respectively). With real stream data, the TRaMM produces high-frequency estimates of slowflow and fastflow discharge that align with expectations for each stream based on their respective hydrologic settings. The use of two tracers with the TRaMM provides an innovative and objective approach for estimating high-frequency fastflow concentrations and contributions of fastflow water to the stream. This provides useful information for tracking chemical movement to streams and allows for better selection and implementation of water quality management strategies.

Assessing Methods for Mapping 2D Field Concentrations of CO2 Over Large Spatial Areas for Monitoring Time Varying Fluctuations

NASA Astrophysics Data System (ADS)

Zaccheo, T. S.; Pernini, T.; Botos, C.; Dobler, J. T.; Blume, N.; Braun, M.; Levine, Z. H.; Pintar, A. L.

2014-12-01

This work presents a methodology for constructing 2D estimates of CO2 field concentrations from integrated open path measurements of CO2 concentrations. It provides a description of the methodology, an assessment based on simulated data and results from preliminary field trials. The Greenhouse gas Laser Imaging Tomography Experiment (GreenLITE) system, currently under development by Exelis and AER, consists of a set of laser-based transceivers and a number of retro-reflectors coupled with a cloud-based compute environment to enable real-time monitoring of integrated CO2 path concentrations, and provides 2D maps of estimated concentrations over an extended area of interest. The GreenLITE transceiver-reflector pairs provide laser absorption spectroscopy (LAS) measurements of differential absorption due to CO2 along intersecting chords within the field of interest. These differential absorption values for the intersecting chords of horizontal path are not only used to construct estimated values of integrated concentration, but also employed in an optimal estimation technique to derive 2D maps of underlying concentration fields. This optimal estimation technique combines these sparse data with in situ measurements of wind speed/direction and an analytic plume model to provide tomographic-like reconstruction of the field of interest. This work provides an assessment of this reconstruction method and preliminary results from the Fall 2014 testing at the Zero Emissions Research and Technology (ZERT) site in Bozeman, Montana. This work is funded in part under the GreenLITE program developed under a cooperative agreement between Exelis and the National Energy and Technology Laboratory (NETL) under the Department of Energy (DOE), contract # DE-FE0012574. Atmospheric and Environmental Research, Inc. is a major partner in this development.

Application of spectral decomposition algorithm for mapping water quality in a turbid lake (Lake Kasumigaura, Japan) from Landsat TM data

NASA Astrophysics Data System (ADS)

Oyama, Youichi; Matsushita, Bunkei; Fukushima, Takehiko; Matsushige, Kazuo; Imai, Akio

The remote sensing of Case 2 water has been far less successful than that of Case 1 water, due mainly to the complex interactions among optically active substances (e.g., phytoplankton, suspended sediments, colored dissolved organic matter, and water) in the former. To address this problem, we developed a spectral decomposition algorithm (SDA), based on a spectral linear mixture modeling approach. Through a tank experiment, we found that the SDA-based models were superior to conventional empirical models (e.g. using single band, band ratio, or arithmetic calculation of band) for accurate estimates of water quality parameters. In this paper, we develop a method for applying the SDA to Landsat-5 TM data on Lake Kasumigaura, a eutrophic lake in Japan characterized by high concentrations of suspended sediment, for mapping chlorophyll-a (Chl-a) and non-phytoplankton suspended sediment (NPSS) distributions. The results show that the SDA-based estimation model can be obtained by a tank experiment. Moreover, by combining this estimation model with satellite-SRSs (standard reflectance spectra: i.e., spectral end-members) derived from bio-optical modeling, we can directly apply the model to a satellite image. The same SDA-based estimation model for Chl-a concentration was applied to two Landsat-5 TM images, one acquired in April 1994 and the other in February 2006. The average Chl-a estimation error between the two was 9.9%, a result that indicates the potential robustness of the SDA-based estimation model. The average estimation error of NPSS concentration from the 2006 Landsat-5 TM image was 15.9%. The key point for successfully applying the SDA-based estimation model to satellite data is the method used to obtain a suitable satellite-SRS for each end-member.

Do fossil plants signal palaeoatmospheric carbon dioxide concentration in the geological past?

PubMed Central

McElwain, J. C.

1998-01-01

Fossil, subfossil, and herbarium leaves have been shown to provide a morphological signal of the atmospheric carbon dioxide environment in which they developed by means of their stomatal density and index. An inverse relationship between stomatal density/index and atmospheric carbon dioxide concentration has been documented for all the studies to date concerning fossil and subfossil material. Furthermore, this relationship has been demonstrated experimentally by growing plants under elevated and reducedcarbon dioxide concentrations. To date, the mechanism that controls the stomatal density response to atmospheric carbon dioxide concentration remains unknown. However, stomatal parameters of fossil plants have been successfully used as a proxy indicator of palaeo-carbon dioxide levels. This paper presents new estimates of palaeo-atmospheric carbon dioxide concentrations for the Middle Eocene (Lutetian), based on the stomatal ratios of fossil Lauraceae species from Bournemouth in England. Estimates of atmospheric carbon dioxide concentrations derived from stomatal data from plants of the Early Devonian, Late Carboniferous, Early Permian and Middle Jurassic ages are reviewed in the light of new data. Semi-quantitative palaeo-carbon dioxide estimates based on the stomatal ratio (a ratio of the stomatal index of a fossil plant to that of a selected nearest living equivalent) have in the past relied on the use of a Carboniferous standard. The application of a new standard based on the present-day carbon dioxide level is reported here for comparison. The resultant ranges of palaeo-carbon dioxide estimates made from standardized fossil stomatal ratio data are in good agreement with both carbon isotopic data from terrestrial and marine sources and long-term carbon cycle modelling estimates for all the time periods studied. These data indicate elevated atmospheric carbon dioxide concentrations during the Early Devonian, Middle Jurassic and Middle Eocene, and reduced concentrations during the Late Carboniferous and Early Permian. Such data are important in demonstrating the long-term responses of plants to changing carbon dioxide concentrations and in contributing to the database needed for general circulation model climatic analogues.

Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors

NASA Technical Reports Server (NTRS)

Van Donkelaar, Aaron; Martin, Randall V.; Brauer, Michael; Hsu, N. Christina; Kahn, Ralph A.; Levy, Robert C.; Lyapustin, Alexei; Sayer, Andrew M.; Winker, David M.

2016-01-01

We estimated global fine particulate matter (PM(sub 2.5)) concentrations using information from satellite-, simulation- and monitor-based sources by applying a Geographically Weighted Regression (GWR) to global geophysically-based satellite-derived PM(sub 2.5) estimates. Aerosol optical depth from multiple satellite products (MISR, MODIS Dark Target, MODIS and SeaWiFS Deep Blue, and MODIS MAIAC) was combined with simulation (GEOS-Chem) based upon their relative uncertainties as determined using ground-based sun photometer (AERONET) observations for 1998-2014. The GWR predictors included simulated aerosol composition and land use information. The resultant PM(sub 2.5) estimates were highly consistent (R(sup 2) equals 0.81) with out-of-sample cross-validated PM(sub 2.5) concentrations from monitors. The global population-weighted annual average PM(sub 2.5) concentrations were 3-fold higher than the 10 micrograms per cubic meter WHO guideline, driven by exposures in Asian and African regions. Estimates in regions with high contributions from mineral dust were associated with higher uncertainty, resulting from both sparse ground-based monitoring, and challenging conditions for retrieval and simulation. This approach demonstrates that the addition of even sparse ground-based measurements to more globally continuous PM(sub 2.5) data sources can yield valuable improvements to PM(sub 2.5) characterization on a global scale.

Phosphorus Concentrations, Loads, and Yields in the Illinois River Basin, Arkansas and Oklahoma, 2000-2004

USGS Publications Warehouse

Tortorelli, Robert L.; Pickup, Barbara E.

2006-01-01

The Illinois River and tributaries, Flint Creek and Baron Fork, are designated scenic rivers in Oklahoma. Recent phosphorus levels in streams in the basin have resulted in the growth of excess algae, which have limited the aesthetic benefits of water bodies in the basin, especially the Illinois River and Lake Tenkiller. The Oklahoma Water Resources Board has established a standard for total phosphorus not to exceed the 30-day geometric mean concentration of 0.037 milligram per liter in Oklahoma Scenic Rivers. The U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, conducted an investigation to summarize phosphorus concentrations and provide estimates of phosphorus loads, yields, and flow-weighted concentrations in the Illinois River and tributaries from January 2000 through December 2004. Data from water-quality samples collected from 2000 to 2004 were used to summarize phosphorus concentrations and estimate phosphorus loads, yields, and mean flow-weighted concentrations in the Illinois River basin for three 3-year periods - 2000-2002, 2001-2003, and 2002-2004, to update a previous report that used data from water-quality samples from 1997 to 2001. This report provides information needed to advance knowledge of the regional hydrologic system and understanding of hydrologic processes, and provides hydrologic data and results useful to multiple parties for interstate compacts. Phosphorus concentrations in the Illinois River basin were significantly greater in runoff samples than in base-flow samples. Phosphorus concentrations generally decreased with increasing base flow, from dilution, and decreased in the downstream direction in the Illinois River from the Watts to Tahlequah stations. Phosphorus concentrations generally increased with runoff, possibly because of phosphorus resuspension, stream bank erosion, and the addition of phosphorus from nonpoint sources. Estimated mean annual phosphorus loads were greater at the Illinois River stations than at Flint Creek and Baron Fork. Annual total loads in the Illinois River from Watts to Tahlequah, increased slightly for the period 2000-2002 and decreased slightly for the periods 2001-2003 and 2002-2004. Estimated mean annual base-flow loads at stations on the Illinois River were about 11 to 20 times greater than base-flow loads at the station on Baron Fork and 4 to 10 times greater than base-flow loads at the station on Flint Creek. Estimated mean annual runoff loads ranged from 68 to 96 percent of the estimated mean annual total phosphorus loads from 2000-2004. Estimated mean seasonal base-flow loads were generally greatest in spring (March through May) and were least in fall (September through November). Estimated mean seasonal runoff loads generally were greatest in summer (June through August) for the period 2000-2002, but were greatest in winter (December through February) for the period 2001-2003, and greatest in spring for the period 2002-2004. Estimated mean total yields of phosphorus ranged from 192 to 811 pounds per year per square mile, with greatest yields being reported for Illinois River near Watts (576 to 811 pounds per year per square mile), and the least yields being reported for Baron Fork at Eldon for the periods 2000-2002 and 2001-2003 (501 and 192 pounds per year per square mile) and for Illinois River near Tahlequah for the period 2002-2004 (370 pounds per year per square mile). Estimated mean flow-weighted concentrations were more than 10 times greater than the median (0.022 milligram per liter) and were consistently greater than the 75th percentile of flow-weighted phosphorus concentrations in samples collected at relatively undeveloped basins of the United States (0.037 milligram per liter). In addition, flow-weighted phosphorus concentrations in 2000-2002 at all Illinois River stations and at Flint Creek near Kansas were equal to or greater than the 75th percentile of all National Water-Quality Assessment Program station

Aquatic concentrations of chemical analytes compared to ...

EPA Pesticide Factsheets

We describe screening level estimates of potential aquatic toxicity posed by 227 chemical analytes that were measured in 25 ambient water samples collected as part of a joint USGS/USEPA drinking water plant study. Measured concentrations were compared to biological effect concentration (EC) estimates, including USEPA aquatic life criteria, effective plasma concentrations of pharmaceuticals, published toxicity data summarized in the USEPA ECOTOX database, and chemical structure-based predictions. Potential dietary exposures were estimated using a generic 3-tiered food web accumulation scenario. For many analytes, few or no measured effect data were found, and for some analytes, reporting limits exceeded EC estimates, limiting the scope of conclusions. Results suggest occasional occurrence above ECs for copper, aluminum, strontium, lead, uranium, and nitrate. Sparse effect data for manganese, antimony, and vanadium suggest that these analytes may occur above ECs, but additional effect data would be desirable to corroborate EC estimates. These conclusions were not affected by bioaccumulation estimates. No organic analyte concentrations were found to exceed EC estimates, but ten analytes had concentrations in excess of 1/10th of their respective EC: triclocarban, norverapamil, progesterone, atrazine, metolachlor, triclosan, para-nonylphenol, ibuprofen, venlafaxine, and amitriptyline, suggesting more detailed characterization of these analytes. Purpose: to provide sc

Analysis of hyperspectral data for estimation of temperate forest canopy nitrogen concentration: comparison between an airborne (AVIRIS) and a spaceborne (Hyperion) sensor

Treesearch

Marie-Louise Smith; Mary E. Martin; Lucie Plourde; Scott V. Ollinger

2003-01-01

Field studies among diverse biomes demonstrate that mass-based nitrogen concentration at leaf and canopy scales is strongly related to carbon uptake and cycling. Combined field and airborne imaging spectrometry studies demonstrate the capacity for accurate empirical estimation of forest canopy N concentration and other biochemical constituents at scales from forest...

ESTIMATING THE EXPOSURE POINT CONCENTRATION TERM USING PROUCL, VERSION 3.0

EPA Science Inventory

In superfund and RCRA Projects of the U.S. EPA, cleanup, exposure, and risk assessment decisions are often made based upon the mean concentrations of the contaminants of potential concern (COPC). A 95% upper confidence limit (UCL) of the population mean is used to estimate the e...

Quantitative measurement of protein digestion in simulated gastric fluid.

PubMed

Herman, Rod A; Korjagin, Valerie A; Schafer, Barry W

2005-04-01

The digestibility of novel proteins in simulated gastric fluid is considered to be an indicator of reduced risk of allergenic potential in food, and estimates of digestibility for transgenic proteins expressed in crops are required for making a human-health risk assessment by regulatory authorities. The estimation of first-order rate constants for digestion under conditions of low substrate concentration was explored for two protein substrates (azocoll and DQ-ovalbumin). Data conformed to first-order kinetics, and half-lives were relatively insensitive to significant variations in both substrate and pepsin concentration when high purity pepsin preparations were used. Estimation of digestion efficiency using densitometric measurements of relative protein concentration based on SDS-PAGE corroborated digestion estimates based on measurements of dye or fluorescence release from the labeled substrates. The suitability of first-order rate constants for estimating the efficiency of the pepsin digestion of novel proteins is discussed. Results further support a kinetic approach as appropriate for comparing the digestibility of proteins in simulated gastric fluid.

Blood flow estimation in gastroscopic true-color images

NASA Astrophysics Data System (ADS)

Jacoby, Raffael S.; Herpers, Rainer; Zwiebel, Franz M.; Englmeier, Karl-Hans

1995-05-01

The assessment of blood flow in the gastrointestinal mucosa might be an important factor for the diagnosis and treatment of several diseases such as ulcers, gastritis, colitis, or early cancer. The quantity of blood flow is roughly estimated by computing the spatial hemoglobin distribution in the mucosa. The presented method enables a practical realization by calculating approximately the hemoglobin concentration based on a spectrophotometric analysis of endoscopic true-color images, which are recorded during routine examinations. A system model based on the reflectance spectroscopic law of Kubelka-Munk is derived which enables an estimation of the hemoglobin concentration by means of the color values of the images. Additionally, a transformation of the color values is developed in order to improve the luminance independence. Applying this transformation and estimating the hemoglobin concentration for each pixel of interest, the hemoglobin distribution can be computed. The obtained results are mostly independent of luminance. An initial validation of the presented method is performed by a quantitative estimation of the reproducibility.

Discrete wavelength selection for the optical readout of a metamaterial biosensing system for glucose concentration estimation via a support vector regression model.

PubMed

Teutsch, T; Mesch, M; Giessen, H; Tarin, C

2015-01-01

In this contribution, a method to select discrete wavelengths that allow an accurate estimation of the glucose concentration in a biosensing system based on metamaterials is presented. The sensing concept is adapted to the particular application of ophthalmic glucose sensing by covering the metamaterial with a glucose-sensitive hydrogel and the sensor readout is performed optically. Due to the fact that in a mobile context a spectrometer is not suitable, few discrete wavelengths must be selected to estimate the glucose concentration. The developed selection methods are based on nonlinear support vector regression (SVR) models. Two selection methods are compared and it is shown that wavelengths selected by a sequential forward feature selection algorithm achieves an estimation improvement. The presented method can be easily applied to different metamaterial layouts and hydrogel configurations.

Hierarchical Bayesian Model Averaging for Non-Uniqueness and Uncertainty Analysis of Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Fijani, E.; Chitsazan, N.; Nadiri, A.; Tsai, F. T.; Asghari Moghaddam, A.

2012-12-01

Artificial Neural Networks (ANNs) have been widely used to estimate concentration of chemicals in groundwater systems. However, estimation uncertainty is rarely discussed in the literature. Uncertainty in ANN output stems from three sources: ANN inputs, ANN parameters (weights and biases), and ANN structures. Uncertainty in ANN inputs may come from input data selection and/or input data error. ANN parameters are naturally uncertain because they are maximum-likelihood estimated. ANN structure is also uncertain because there is no unique ANN model given a specific case. Therefore, multiple plausible AI models are generally resulted for a study. One might ask why good models have to be ignored in favor of the best model in traditional estimation. What is the ANN estimation variance? How do the variances from different ANN models accumulate to the total estimation variance? To answer these questions we propose a Hierarchical Bayesian Model Averaging (HBMA) framework. Instead of choosing one ANN model (the best ANN model) for estimation, HBMA averages outputs of all plausible ANN models. The model weights are based on the evidence of data. Therefore, the HBMA avoids overconfidence on the single best ANN model. In addition, HBMA is able to analyze uncertainty propagation through aggregation of ANN models in a hierarchy framework. This method is applied for estimation of fluoride concentration in the Poldasht plain and the Bazargan plain in Iran. Unusually high fluoride concentration in the Poldasht and Bazargan plains has caused negative effects on the public health. Management of this anomaly requires estimation of fluoride concentration distribution in the area. The results show that the HBMA provides a knowledge-decision-based framework that facilitates analyzing and quantifying ANN estimation uncertainties from different sources. In addition HBMA allows comparative evaluation of the realizations for each source of uncertainty by segregating the uncertainty sources in a hierarchical framework. Fluoride concentration estimation using the HBMA method shows better agreement to the observation data in the test step because they are not based on a single model with a non-dominate weights.

In Silico Estimation of Skin Concentration Following the Dermal Exposure to Chemicals.

PubMed

Hatanaka, Tomomi; Yoshida, Shun; Kadhum, Wesam R; Todo, Hiroaki; Sugibayashi, Kenji

2015-12-01

To develop an in silico method based on Fick's law of diffusion to estimate the skin concentration following dermal exposure to chemicals with a wide range of lipophilicity. Permeation experiments of various chemicals were performed through rat and porcine skin. Permeation parameters, namely, permeability coefficient and partition coefficient, were obtained by the fitting of data to two-layered and one-layered diffusion models for whole and stripped skin. The mean skin concentration of chemicals during steady-state permeation was calculated using the permeation parameters and compared with the observed values. All permeation profiles could be described by the diffusion models. The estimated skin concentrations of chemicals using permeation parameters were close to the observed levels and most data fell within the 95% confidence interval for complete prediction. The permeability coefficient and partition coefficient for stripped skin were almost constant, being independent of the permeant's lipophilicity. Skin concentration following dermal exposure to various chemicals can be accurately estimated based on Fick's law of diffusion. This method should become a useful tool to assess the efficacy of topically applied drugs and cosmetic ingredients, as well as the risk of chemicals likely to cause skin disorders and diseases.

A simple linear model for estimating ozone AOT40 at forest sites from raw passive sampling data.

PubMed

Ferretti, Marco; Cristofolini, Fabiana; Cristofori, Antonella; Gerosa, Giacomo; Gottardini, Elena

2012-08-01

A rapid, empirical method is described for estimating weekly AOT40 from ozone concentrations measured with passive samplers at forest sites. The method is based on linear regression and was developed after three years of measurements in Trentino (northern Italy). It was tested against an independent set of data from passive sampler sites across Italy. It provides good weekly estimates compared with those measured by conventional monitors (0.85 ≤R(2)≤ 0.970; 97 ≤ RMSE ≤ 302). Estimates obtained using passive sampling at forest sites are comparable to those obtained by another estimation method based on modelling hourly concentrations (R(2) = 0.94; 131 ≤ RMSE ≤ 351). Regression coefficients of passive sampling are similar to those obtained with conventional monitors at forest sites. Testing against an independent dataset generated by passive sampling provided similar results (0.86 ≤R(2)≤ 0.99; 65 ≤ RMSE ≤ 478). Errors tend to accumulate when weekly AOT40 estimates are summed to obtain the total AOT40 over the May-July period, and the median deviation between the two estimation methods based on passive sampling is 11%. The method proposed does not require any assumptions, complex calculation or modelling technique, and can be useful when other estimation methods are not feasible, either in principle or in practice. However, the method is not useful when estimates of hourly concentrations are of interest.

Pollutant exposures from natural gas cooking burners: a simulation-based assessment for Southern California.

PubMed

Logue, Jennifer M; Klepeis, Neil E; Lobscheid, Agnes B; Singer, Brett C

2014-01-01

Residential natural gas cooking burners (NGCBs) can emit substantial quantities of pollutants, and they are typically used without venting range hoods. We quantified pollutant concentrations and occupant exposures resulting from NGCB use in California homes. A mass-balance model was applied to estimate time-dependent pollutant concentrations throughout homes in Southern California and the exposure concentrations experienced by individual occupants. We estimated nitrogen dioxide (NO2), carbon monoxide (CO), and formaldehyde (HCHO) concentrations for 1 week each in summer and winter for a representative sample of Southern California homes. The model simulated pollutant emissions from NGCBs as well as NO2 and CO entry from outdoors, dilution throughout the home, and removal by ventilation and deposition. Residence characteristics and outdoor concentrations of NO2 and CO were obtained from available databases. We inferred ventilation rates, occupancy patterns, and burner use from household characteristics. We also explored proximity to the burner(s) and the benefits of using venting range hoods. Replicate model executions using independently generated sets of stochastic variable values yielded estimated pollutant concentration distributions with geometric means varying by <10%. The simulation model estimated that-in homes using NGCBs without coincident use of venting range hoods-62%, 9%, and 53% of occupants are routinely exposed to NO2, CO, and HCHO levels that exceed acute health-based standards and guidelines. NGCB use increased the sample median of the highest simulated 1-hr indoor concentrations by 100, 3,000, and 20 ppb for NO2, CO, and HCHO, respectively. Reducing pollutant exposures from NGCBs should be a public health priority. Simulation results suggest that regular use of even moderately effective venting range hoods would dramatically reduce the percentage of homes in which concentrations exceed health-based standards.

Estimation of sport fish harvest for risk and hazard assessment of environmental contaminants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poston, T.M.; Strenge, D.L.

1989-01-01

Consumption of contaminated fish flesh can be a significant route of human exposure to hazardous chemicals. Estimation of exposure resulting from the consumption of fish requires knowledge of fish consumption and contaminant levels in the edible portion of fish. Realistic figures of sport fish harvest are needed to estimate consumption. Estimates of freshwater sport fish harvest were developed from a review of 72 articles and reports. Descriptive statistics based on fishing pressure were derived from harvest data for four distinct groups of freshwater sport fish in three water types: streams, lakes, and reservoirs. Regression equations were developed to relate harvestmore » to surface area fished where data bases were sufficiently large. Other aspects of estimating human exposure to contaminants in fish flesh that are discussed include use of bioaccumulation factors for trace metals and organic compounds. Using the bioaccumulation factor and the concentration of contaminants in water as variables in the exposure equation may also lead to less precise estimates of tissue concentration. For instance, muscle levels of contaminants may not increase proportionately with increases in water concentrations, leading to overestimation of risk. In addition, estimates of water concentration may be variable or expressed in a manner that does not truly represent biological availability of the contaminant. These factors are discussed. 45 refs., 1 fig., 7 tabs.« less

SEASONAL AND REGIONAL VARIATIONS OF PRIMARY AND SECONDARY ORGANIC AEROSOLS OVER THE CONTINENTAL UNITED STATES: OBSERVATION-BASED ESTIMATES AND MODEL EVALUATION

EPA Science Inventory

Due to the lack of an analytical technique for directly quantifying the atmospheric concentrations of primary (OC_pri) and secondary (OC_sec) organic carbon aerosols, different indirect methods have been developed to estimate their concentrations. In this stu...

Impact of planetary boundary layer turbulence on model climate and tracer transport

NASA Astrophysics Data System (ADS)

McGrath-Spangler, E. L.; Molod, A.; Ott, L. E.; Pawson, S.

2014-12-01

Planetary boundary layer (PBL) processes are important for weather, climate, and tracer transport and concentration. One measure of the strength of these processes is the PBL depth. However, no single PBL depth definition exists and several studies have found that the estimated depth can vary substantially based on the definition used. In the Goddard Earth Observing System (GEOS-5) atmospheric general circulation model, the PBL depth is particularly important because it is used to calculate the turbulent length scale that is used in the estimation of turbulent mixing. This study analyzes the impact of using three different PBL depth definitions in this calculation. Two definitions are based on the scalar eddy diffusion coefficient and the third is based on the bulk Richardson number. Over land, the bulk Richardson number definition estimates shallower nocturnal PBLs than the other estimates while over water this definition generally produces deeper PBLs. The near surface wind velocity, temperature, and specific humidity responses to the change in turbulence are spatially and temporally heterogeneous, resulting in changes to tracer transport and concentrations. Near surface wind speed increases in the bulk Richardson number experiment cause Saharan dust increases on the order of 1 × 10-4 kg m-2 downwind over the Atlantic Ocean. Carbon monoxide (CO) surface concentrations are modified over Africa during boreal summer, producing differences on the order of 20 ppb, due to the model's treatment of emissions from biomass burning. While differences in carbon dioxide (CO2) are small in the time mean, instantaneous differences are on the order of 10 ppm and these are especially prevalent at high latitude during boreal winter. Understanding the sensitivity of trace gas and aerosol concentration estimates to PBL depth is important for studies seeking to calculate surface fluxes based on near-surface concentrations and to studies projecting future concentrations.

Impact of planetary boundary layer turbulence on model climate and tracer transport

NASA Astrophysics Data System (ADS)

McGrath-Spangler, E. L.; Molod, A.; Ott, L. E.; Pawson, S.

2015-07-01

Planetary boundary layer (PBL) processes are important for weather, climate, and tracer transport and concentration. One measure of the strength of these processes is the PBL depth. However, no single PBL depth definition exists and several studies have found that the estimated depth can vary substantially based on the definition used. In the Goddard Earth Observing System (GEOS-5) atmospheric general circulation model, the PBL depth is particularly important because it is used to calculate the turbulent length scale that is used in the estimation of turbulent mixing. This study analyzes the impact of using three different PBL depth definitions in this calculation. Two definitions are based on the scalar eddy diffusion coefficient and the third is based on the bulk Richardson number. Over land, the bulk Richardson number definition estimates shallower nocturnal PBLs than the other estimates while over water this definition generally produces deeper PBLs. The near-surface wind velocity, temperature, and specific humidity responses to the change in turbulence are spatially and temporally heterogeneous, resulting in changes to tracer transport and concentrations. Near-surface wind speed increases in the bulk Richardson number experiment cause Saharan dust increases on the order of 1 × 10-4 kg m-2 downwind over the Atlantic Ocean. Carbon monoxide (CO) surface concentrations are modified over Africa during boreal summer, producing differences on the order of 20 ppb, due to the model's treatment of emissions from biomass burning. While differences in carbon dioxide (CO2) are small in the time mean, instantaneous differences are on the order of 10 ppm and these are especially prevalent at high latitude during boreal winter. Understanding the sensitivity of trace gas and aerosol concentration estimates to PBL depth is important for studies seeking to calculate surface fluxes based on near-surface concentrations and for studies projecting future concentrations.

Model methodology for estimating pesticide concentration extremes based on sparse monitoring data

USGS Publications Warehouse

Vecchia, Aldo V.

2018-03-22

This report describes a new methodology for using sparse (weekly or less frequent observations) and potentially highly censored pesticide monitoring data to simulate daily pesticide concentrations and associated quantities used for acute and chronic exposure assessments, such as the annual maximum daily concentration. The new methodology is based on a statistical model that expresses log-transformed daily pesticide concentration in terms of a seasonal wave, flow-related variability, long-term trend, and serially correlated errors. Methods are described for estimating the model parameters, generating conditional simulations of daily pesticide concentration given sparse (weekly or less frequent) and potentially highly censored observations, and estimating concentration extremes based on the conditional simulations. The model can be applied to datasets with as few as 3 years of record, as few as 30 total observations, and as few as 10 uncensored observations. The model was applied to atrazine, carbaryl, chlorpyrifos, and fipronil data for U.S. Geological Survey pesticide sampling sites with sufficient data for applying the model. A total of 112 sites were analyzed for atrazine, 38 for carbaryl, 34 for chlorpyrifos, and 33 for fipronil. The results are summarized in this report; and, R functions, described in this report and provided in an accompanying model archive, can be used to fit the model parameters and generate conditional simulations of daily concentrations for use in investigations involving pesticide exposure risk and uncertainty.

Fractional kalman filter to estimate the concentration of air pollution

NASA Astrophysics Data System (ADS)

Vita Oktaviana, Yessy; Apriliani, Erna; Khusnul Arif, Didik

2018-04-01

Air pollution problem gives important effect in quality environment and quality of human’s life. Air pollution can be caused by nature sources or human activities. Pollutant for example Ozone, a harmful gas formed by NOx and volatile organic compounds (VOCs) emitted from various sources. The air pollution problem can be modeled by TAPM-CTM (The Air Pollution Model with Chemical Transport Model). The model shows concentration of pollutant in the air. Therefore, it is important to estimate concentration of air pollutant. Estimation method can be used for forecast pollutant concentration in future and keep stability of air quality. In this research, an algorithm is developed, based on Fractional Kalman Filter to solve the model of air pollution’s problem. The model will be discretized first and then it will be estimated by the method. The result shows that estimation of Fractional Kalman Filter has better accuracy than estimation of Kalman Filter. The accuracy was tested by applying RMSE (Root Mean Square Error).

Estimating Likelihood of Fetal In Vivo Interactions Using In ...

EPA Pesticide Factsheets

Tox21/ToxCast efforts provide in vitro concentration-response data for thousands of compounds. Predicting whether chemical-biological interactions observed in vitro will occur in vivo is challenging. We hypothesize that using a modified model from the FDA guidance for drug interaction studies, Cmax/AC50 (i.e., maximal in vivo blood concentration over the half-maximal in in vitro activity concentration), will give a useful approximation for concentrations where in vivo interactions are likely. Further, for doses where maternal blood concentrations are likely to elicit an interaction (Cmax/AC50>0.1), where do the compounds accumulate in fetal tissues? In order to estimate these doses based on Tox21 data, in silico parameters of chemical fraction unbound in plasma and intrinsic hepatic clearance were estimated from ADMET predictor (Simulations-Plus Inc.) and used in the HTTK R-package to obtain Cmax values from a physiologically-based toxicokinetics model. In silico estimated Cmax values predicted in vivo human Cmax with median absolute error of 0.81 for 93 chemicals, giving confidence in the R-package and in silico estimates. A case example evaluating Cmax/AC50 values for peroxisome proliferator-activated receptor gamma (PPARγ) and glucocorticoid receptor revealed known compounds (glitazones and corticosteroids, respectively) highest on the list at pharmacological doses. Doses required to elicit likely interactions across all Tox21/ToxCast assays were compared to

PAH volatilization following application of coal-tar-based pavement sealant

USGS Publications Warehouse

Van Metre, Peter C.; Majewski, Michael S.; Mahler, Barbara J.; Foreman, William T.; Braun, Christopher L.; Wilson, Jennifer T.; Burbank, Teresa L.

2012-01-01

Coal-tar-based pavement sealants, a major source of PAHs to urban water bodies, have recently been identified as a source of volatile PAHs to the atmosphere. We tracked the volatilization of PAHs for 1 year after application of a coal-tar-based pavement sealant by measuring gas-phase PAH concentrations above the pavement surface and solid-phase PAH concentrations in sealant scraped from the surface. Gas-phase concentrations at two heights (0.03 and 1.28 m) and wind speed were used to estimate volatilization flux. The sum of the concentrations of eight frequently detected PAHs (ΣPAH8) in the 0.03-m sample 1.6 h after application (297,000 ng m-3) was about 5000 times greater than that previously reported for the same height above unsealed parking lots (66 ng m-3). Flux at 1.6 h after application was estimated at 45,000 μg m-2 h-1 and decreased rapidly during the 45 days after application to 160 μg m-2 h-1. Loss of PAHs from the adhered sealant also was rapid, with about a 50% decrease in solid-phase ΣPAH8 concentration over the 45 days after application. There was general agreement, given the uncertainties, in the estimated mass of ΣPAH8 lost to the atmosphere on the basis of air sampling (2–3 g m-2) and adhered sealant sampling (6 g m-2) during the first 16 days after application, translating to a loss to the atmosphere of one-quarter to one-half of the PAHs in the sealcoat product. Combining the estimated mass of ΣPAH8 released to the atmosphere with a national-use estimate of coal-tar-based sealant suggests that PAH emissions from new coal-tar-based sealcoat applications each year (~1000 Mg) are larger than annual vehicle emissions of PAHs for the United States.

Methods for estimating heterocyclic amine concentrations in cooked meats in the US diet.

PubMed

Keating, G A; Bogen, K T

2001-01-01

Heterocyclic amines (HAs) are formed in numerous cooked foods commonly consumed in the diet. A method was developed to estimate dietary HA levels using HA concentrations in experimentally cooked meats reported in the literature and meat consumption data obtained from a national dietary survey. Cooking variables (meat internal temperature and weight loss, surface temperature and time) were used to develop relationships for estimating total HA concentrations in six meat types. Concentrations of five individual HAs were estimated for specific meat type/cooking method combinations based on linear regression of total and individual HA values obtained from the literature. Using these relationships, total and individual HA concentrations were estimated for 21 meat type/cooking method combinations at four meat doneness levels. Reported consumption of the 21 meat type/cooking method combinations was obtained from a national dietary survey and the age-specific daily HA intake calculated using the estimated HA concentrations (ng/g) and reported meat intakes. Estimated mean daily total HA intakes for children (to age 15 years) and adults (30+ years) were 11 and 7.0 ng/kg/day, respectively, with 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) estimated to comprise approximately 65% of each intake. Pan-fried meats were the largest source of HA in the diet and chicken the largest source of HAs among the different meat types.

Refractometric total protein concentrations in icteric serum from dogs.

PubMed

Gupta, Aradhana; Stockham, Steven L

2014-01-01

To determine whether high serum bilirubin concentrations interfere with the measurement of serum total protein concentration by refractometry and to assess potential biases among refractometer measurements. Evaluation study. Sera from 2 healthy Greyhounds. Bilirubin was dissolved in 0.1M NaOH, and the resulting solution was mixed with sera from 2 dogs from which food had been withheld to achieve various bilirubin concentrations up to 40 mg/dL. Refractometric total protein concentrations were estimated with 3 clinical refractometers. A biochemical analyzer was used to measure biuret assay-based total protein and bilirubin concentrations with spectrophotometric assays. No interference with refractometric measurement of total protein concentrations was detected with bilirubin concentrations up to 41.5 mg/dL. Biases in refractometric total protein concentrations were detected and were related to the conversion of refractive index values to total protein concentrations. Hyperbilirubinemia did not interfere with the refractometric estimation of serum total protein concentration. The agreement among total protein concentrations estimated by 3 refractometers was dependent on the method of conversion of refractive index to total protein concentration and was independent of hyperbilirubinemia.

Adaptive and Personalized Plasma Insulin Concentration Estimation for Artificial Pancreas Systems.

PubMed

Hajizadeh, Iman; Rashid, Mudassir; Samadi, Sediqeh; Feng, Jianyuan; Sevil, Mert; Hobbs, Nicole; Lazaro, Caterina; Maloney, Zacharie; Brandt, Rachel; Yu, Xia; Turksoy, Kamuran; Littlejohn, Elizabeth; Cengiz, Eda; Cinar, Ali

2018-05-01

The artificial pancreas (AP) system, a technology that automatically administers exogenous insulin in people with type 1 diabetes mellitus (T1DM) to regulate their blood glucose concentrations, necessitates the estimation of the amount of active insulin already present in the body to avoid overdosing. An adaptive and personalized plasma insulin concentration (PIC) estimator is designed in this work to accurately quantify the insulin present in the bloodstream. The proposed PIC estimation approach incorporates Hovorka's glucose-insulin model with the unscented Kalman filtering algorithm. Methods for the personalized initialization of the time-varying model parameters to individual patients for improved estimator convergence are developed. Data from 20 three-days-long closed-loop clinical experiments conducted involving subjects with T1DM are used to evaluate the proposed PIC estimation approach. The proposed methods are applied to the clinical data containing significant disturbances, such as unannounced meals and exercise, and the results demonstrate the accurate real-time estimation of the PIC with the root mean square error of 7.15 and 9.25 mU/L for the optimization-based fitted parameters and partial least squares regression-based testing parameters, respectively. The accurate real-time estimation of PIC will benefit the AP systems by preventing overdelivery of insulin when significant insulin is present in the bloodstream.

Comparison of 3 estimation methods of mycophenolic acid AUC based on a limited sampling strategy in renal transplant patients.

PubMed

Hulin, Anne; Blanchet, Benoît; Audard, Vincent; Barau, Caroline; Furlan, Valérie; Durrbach, Antoine; Taïeb, Fabrice; Lang, Philippe; Grimbert, Philippe; Tod, Michel

2009-04-01

A significant relationship between mycophenolic acid (MPA) area under the plasma concentration-time curve (AUC) and the risk for rejection has been reported. Based on 3 concentration measurements, 3 approaches have been proposed for the estimation of MPA AUC, involving either a multilinear regression approach model (MLRA) or a Bayesian estimation using either gamma absorption or zero-order absorption population models. The aim of the study was to compare the 3 approaches for the estimation of MPA AUC in 150 renal transplant patients treated with mycophenolate mofetil and tacrolimus. The population parameters were determined in 77 patients (learning study). The AUC estimation methods were compared in the learning population and in 73 patients from another center (validation study). In the latter study, the reference AUCs were estimated by the trapezoidal rule on 8 measurements. MPA concentrations were measured by liquid chromatography. The gamma absorption model gave the best fit. In the learning study, the AUCs estimated by both Bayesian methods were very similar, whereas the multilinear approach was highly correlated but yielded estimates about 20% lower than Bayesian methods. This resulted in dosing recommendations differing by 250 mg/12 h or more in 27% of cases. In the validation study, AUC estimates based on the Bayesian method with gamma absorption model and multilinear regression approach model were, respectively, 12% higher and 7% lower than the reference values. To conclude, the bicompartmental model with gamma absorption rate gave the best fit. The 3 AUC estimation methods are highly correlated but not concordant. For a given patient, the same estimation method should always be used.

Development of a dome Fresnel lens/gallium arsenide photovoltaic concentrator for space applications

NASA Technical Reports Server (NTRS)

O'Neill, Mark J.; Piszczor, Michael F.

1987-01-01

A novel photovoltaic concentrator system is currently being developed. Phase I of the program, completed in late 1986, produced a conceptual design for the concentrator system, including an array weight and performance estimates based on optical, electrical, and thermal analyses. Phase II of the program, just underway, concerns the fabrication and testing of prototype concentrator panels of the design. The concentrator system uses dome Fresnel lenses for optical concentration; gallium arsenide concentrator cells for power generation; prismatic cell covers to eliminate gridline obscuration losses; a backplane radiator for heat rejection; and a honeycomb structure for the deployable panel assembly. The conceptual design of the system, its anticipated performance, and its estimated weight are reported.

STRONTIUM-90 LIQUID CONCENTRATION SOLUBILITY CORRELATION IN THE HANFORD TANK WASTE OPERATIONS SIMULATOR

DOE Office of Scientific and Technical Information (OSTI.GOV)

HOHL, T.; PLACE, D.; WITTMAN, R.

2004-08-05

A new correlation was developed to estimate the concentration of strontium-90 in a waste solution based on total organic carbon. This correlation replaces the strontium-90 wash factors, and when applied in the Hanford Tank Waste Operations Simulator, significantly reduced the estimated quantity of strontium-90 in the delivered low-activity waste feed. This is thought to be a more realistic estimate of strontium-90 than using the wash-factor method.

Developing a semi-analytical algorithm to estimate particulate organic carbon (POC) levels in inland eutrophic turbid water based on MERIS images: A case study of Lake Taihu

NASA Astrophysics Data System (ADS)

Lyu, Heng; Wang, Yannan; Jin, Qi; Shi, Lei; Li, Yunmei; Wang, Qiao

2017-10-01

Particulate organic carbon (POC) plays an important role in the carbon cycle in water due to its biological pump process. In the open ocean, algorithms can accurately estimate the surface POC concentration. However, no suitable POC-estimation algorithm based on MERIS bands is available for inland turbid eutrophic water. A total of 228 field samples were collected from Lake Taihu in different seasons between 2013 and 2015. At each site, the optical parameters and water quality were analyzed. Using in situ data, it was found that POC-estimation algorithms developed for the open ocean and coastal waters using remote sensing reflectance were not suitable for inland turbid eutrophic water. The organic suspended matter (OSM) concentration was found to be the best indicator of the POC concentration, and POC has an exponential relationship with the OSM concentration. Through an analysis of the POC concentration and optical parameters, it was found that the absorption peak of total suspended matter (TSM) at 665 nm was the optimum parameter to estimate POC. As a result, MERIS band 7, MERIS band 10 and MERIS band 12 were used to derive the absorption coefficient of TSM at 665 nm, and then, a semi-analytical algorithm was used to estimate the POC concentration for inland turbid eutrophic water. An accuracy assessment showed that the developed semi-analytical algorithm could be successfully applied with a MAPE of 31.82% and RMSE of 2.68 mg/L. The developed algorithm was successfully applied to a MERIS image, and two full-resolution MERIS images, acquired on August 13, 2010, and December 7, 2010, were used to map the POC spatial distribution in Lake Taihu in summer and winter.

Variation in the iodine concentrations of foods: considerations for dietary assessment1234

PubMed Central

Carriquiry, Alicia L; Spungen, Judith H; Murphy, Suzanne P; Pehrsson, Pamela R; Dwyer, Johanna T; Juan, WenYen; Wirtz, Mark S

2016-01-01

Background: Food-composition tables typically give measured nutrient concentrations in foods as a single summary value, often the mean, without providing information as to the shape of the distribution. Objective: Our objective was to explore how the statistical approach chosen to describe the iodine concentrations of foods affects the proportion of the population identified as having either insufficient or excessive iodine intakes. Design: We used food intake data reported by the 2009−2010 NHANES and measured iodine concentrations of Total Diet Study (TDS) foods from 4 US regions sampled in 2004–2011. We created 4 data sets, each by using a different summary statistic (median, mean, and 10th and 90th percentiles), to represent the iodine concentration distribution of each TDS food. We estimated the iodine concentration distribution of each food consumed by NHANES participants as the 4 iodine concentration summary statistics of a similar TDS food and used these, along with NHANES food intake data, to develop 4 estimates of each participant’s iodine intake on each survey day. Using the 4 estimates in turn, we calculated 4 usual iodine intakes for each sex- and age-specific subgroup. We then compared these to guideline values and developed 4 estimates of the proportions of each subgroup with deficient and excessive usual iodine intakes. Results: In general, the distribution of iodine intakes was poorly characterized when food iodine concentrations were expressed as mean values. In addition, mean values predicted lower prevalences of iodine deficiency than did median values. For example, in women aged 19–50 y, the estimated prevalence of iodine deficiency was 25% when based on median food iodine concentrations but only 5.8% when based on mean values. Conclusion: For nutrients such as iodine with highly variable concentrations in important food sources, we recommend that food-composition tables provide useful variability information, including the mean, SD, and median. PMID:27534633

Variation in the iodine concentrations of foods: considerations for dietary assessment.

PubMed

Carriquiry, Alicia L; Spungen, Judith H; Murphy, Suzanne P; Pehrsson, Pamela R; Dwyer, Johanna T; Juan, WenYen; Wirtz, Mark S

2016-09-01

Food-composition tables typically give measured nutrient concentrations in foods as a single summary value, often the mean, without providing information as to the shape of the distribution. Our objective was to explore how the statistical approach chosen to describe the iodine concentrations of foods affects the proportion of the population identified as having either insufficient or excessive iodine intakes. We used food intake data reported by the 2009-2010 NHANES and measured iodine concentrations of Total Diet Study (TDS) foods from 4 US regions sampled in 2004-2011. We created 4 data sets, each by using a different summary statistic (median, mean, and 10th and 90th percentiles), to represent the iodine concentration distribution of each TDS food. We estimated the iodine concentration distribution of each food consumed by NHANES participants as the 4 iodine concentration summary statistics of a similar TDS food and used these, along with NHANES food intake data, to develop 4 estimates of each participant's iodine intake on each survey day. Using the 4 estimates in turn, we calculated 4 usual iodine intakes for each sex- and age-specific subgroup. We then compared these to guideline values and developed 4 estimates of the proportions of each subgroup with deficient and excessive usual iodine intakes. In general, the distribution of iodine intakes was poorly characterized when food iodine concentrations were expressed as mean values. In addition, mean values predicted lower prevalences of iodine deficiency than did median values. For example, in women aged 19-50 y, the estimated prevalence of iodine deficiency was 25% when based on median food iodine concentrations but only 5.8% when based on mean values. For nutrients such as iodine with highly variable concentrations in important food sources, we recommend that food-composition tables provide useful variability information, including the mean, SD, and median. © 2016 American Society for Nutrition.

Childhood Estimates of Glomerular Filtration Rate Based on Creatinine and Cystatin C: Importance of Body Composition.

PubMed

Miliku, Kozeta; Bakker, Hanneke; Dorresteijn, Eiske M; Cransberg, Karlien; Franco, Oscar H; Felix, Janine F; Jaddoe, Vincent W V

2017-01-01

Creatinine and cystatin C concentrations are commonly used to estimate glomerular filtration rate (eGFR) in clinical practice and epidemiological studies. To estimate the influence of different body composition measures on eGFR from creatinine and cystatin C blood concentrations, we compared the associations of different anthropometric and body composition measures with eGFR derived from creatinine (eGFRcreat) and cystatin C (eGFRcystC) blood concentrations. In a population-based cohort study among 4,305 children aged 6.0 years (95% range 5.7-8.0), we measured weight and height and calculated body mass index (BMI) and body surface area (BSA), and lean and fat mass using dual-energy X-ray absorptiometry. At the same age, we measured creatinine and cystatin C blood concentrations and estimated the GFR. Correlation between eGFR based on creatinine and cystatin C concentrations was r = 0.40 (p value <0.01). Higher BMI was associated with lower eGFRcystC but not with eGFRcreat. Higher BSA was associated with higher eGFRcreat and lower eGFRcystC (p value <0.05). Lean and fat mass percentages were associated with eGFRcreat but not with eGFRcystC. Our findings suggest that both eGFRcreat and eGFRcystC are influenced by BMI and BSA. eGFRcreat is more strongly influenced by body composition than eGFRcystC. © 2017 S. Karger AG, Basel.

Microbial risk assessment of drinking water based on hydrodynamic modelling of pathogen concentrations in source water.

PubMed

Sokolova, Ekaterina; Petterson, Susan R; Dienus, Olaf; Nyström, Fredrik; Lindgren, Per-Eric; Pettersson, Thomas J R

2015-09-01

Norovirus contamination of drinking water sources is an important cause of waterborne disease outbreaks. Knowledge on pathogen concentrations in source water is needed to assess the ability of a drinking water treatment plant (DWTP) to provide safe drinking water. However, pathogen enumeration in source water samples is often not sufficient to describe the source water quality. In this study, the norovirus concentrations were characterised at the contamination source, i.e. in sewage discharges. Then, the transport of norovirus within the water source (the river Göta älv in Sweden) under different loading conditions was simulated using a hydrodynamic model. Based on the estimated concentrations in source water, the required reduction of norovirus at the DWTP was calculated using quantitative microbial risk assessment (QMRA). The required reduction was compared with the estimated treatment performance at the DWTP. The average estimated concentration in source water varied between 4.8×10(2) and 7.5×10(3) genome equivalents L(-1); and the average required reduction by treatment was between 7.6 and 8.8 Log10. The treatment performance at the DWTP was estimated to be adequate to deal with all tested loading conditions, but was heavily dependent on chlorine disinfection, with the risk of poor reduction by conventional treatment and slow sand filtration. To our knowledge, this is the first article to employ discharge-based QMRA, combined with hydrodynamic modelling, in the context of drinking water. Copyright © 2015 Elsevier B.V. All rights reserved.

[Considerations when using creatinine as a measure of kidney function].

PubMed

Drion, I Iefke; Fokkert, M J Marion; Bilo, H J G Henk

2013-01-01

Reported serum creatinine concentrations can sometimes vary considerably, even when the renal function does less so or even not. This variation is partly due to true changes in actual serum concentration, and partly due to interferences in the measurement technique, thus not reflecting a true change in concentration. Increased or decreased endogenous creatinine production, ingested creatinine sources through meat eating or certain creatine formulations, and interference by either browning of chromogenic substances in Jaffe measurement techniques or promotors and inhibitors of enzymatic reaction methods do play a role. Reliable serum creatinine measurements are needed for renal function estimating equations. In screening circumstances and daily practice, chronic kidney disease staging is based on these estimated glomerular filtration rate values. Given the possible influences on reported serum creatinine concentrations, it is important for health care workers to remain critical when interpreting outcomes of renal function estimating equations and to not see every reported result based on an equation as a true reflection of renal function.

Impact analysis of traffic-related air pollution based on real-time traffic and basic meteorological information.

PubMed

Pan, Long; Yao, Enjian; Yang, Yang

2016-12-01

With the rapid development of urbanization and motorization in China, traffic-related air pollution has become a major component of air pollution which constantly jeopardizes public health. This study proposes an integrated framework for estimating the concentration of traffic-related air pollution with real-time traffic and basic meteorological information and also for further evaluating the impact of traffic-related air pollution. First, based on the vehicle emission factor models sensitive to traffic status, traffic emissions are calculated according to the real-time link-based average traffic speed, traffic volume, and vehicular fleet composition. Then, based on differences in meteorological conditions, traffic pollution sources are divided into line sources and point sources, and the corresponding methods to determine the dynamic affecting areas are also proposed. Subsequently, with basic meteorological data, Gaussian dispersion model and puff integration model are applied respectively to estimate the concentration of traffic-related air pollution. Finally, the proposed estimating framework is applied to calculate the distribution of CO concentration in the main area of Beijing, and the population exposure is also calculated to evaluate the impact of traffic-related air pollution on public health. Results show that there is a certain correlation between traffic indicators (i.e., traffic speed and traffic intensity) of the affecting area and traffic-related CO concentration of the target grid, which indicates the methods to determine the affecting areas are reliable. Furthermore, the reliability of the proposed estimating framework is verified by comparing the predicted and the observed ambient CO concentration. In addition, results also show that the traffic-related CO concentration is higher in morning and evening peak hours, and has a heavier impact on public health within the Fourth Ring Road of Beijing due to higher population density and higher CO concentration under calm wind condition in this area. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chemical-specific screening criteria for interpretation of biomonitoring data for volatile organic compounds (VOCs)--application of steady-state PBPK model solutions.

PubMed

Aylward, Lesa L; Kirman, Chris R; Blount, Ben C; Hays, Sean M

2010-10-01

The National Health and Nutrition Examination Survey (NHANES) generates population-representative biomonitoring data for many chemicals including volatile organic compounds (VOCs) in blood. However, no health or risk-based screening values are available to evaluate these data from a health safety perspective or to use in prioritizing among chemicals for possible risk management actions. We gathered existing risk assessment-based chronic exposure reference values such as reference doses (RfDs), reference concentrations (RfCs), tolerable daily intakes (TDIs), cancer slope factors, etc. and key pharmacokinetic model parameters for 47 VOCs. Using steady-state solutions to a generic physiologically-based pharmacokinetic (PBPK) model structure, we estimated chemical-specific steady-state venous blood concentrations across chemicals associated with unit oral and inhalation exposure rates and with chronic exposure at the identified exposure reference values. The geometric means of the slopes relating modeled steady-state blood concentrations to steady-state exposure to a unit oral dose or unit inhalation concentration among 38 compounds with available pharmacokinetic parameters were 12.0 microg/L per mg/kg-d (geometric standard deviation [GSD] of 3.2) and 3.2 microg/L per mg/m(3) (GSD=1.7), respectively. Chemical-specific blood concentration screening values based on non-cancer reference values for both oral and inhalation exposure range from 0.0005 to 100 microg/L; blood concentrations associated with cancer risk-specific doses at the 1E-05 risk level ranged from 5E-06 to 6E-02 microg/L. The distribution of modeled steady-state blood concentrations associated with unit exposure levels across VOCs may provide a basis for estimating blood concentration screening values for VOCs that lack chemical-specific pharmacokinetic data. The screening blood concentrations presented here provide a tool for risk assessment-based evaluation of population biomonitoring data for VOCs and are most appropriately applied to central tendency estimates for such datasets. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Estimating Water Supply Arsenic Levels in the New England Bladder Cancer Study

PubMed Central

Freeman, Laura E. Beane; Lubin, Jay H.; Airola, Matthew S.; Baris, Dalsu; Ayotte, Joseph D.; Taylor, Anne; Paulu, Chris; Karagas, Margaret R.; Colt, Joanne; Ward, Mary H.; Huang, An-Tsun; Bress, William; Cherala, Sai; Silverman, Debra T.; Cantor, Kenneth P.

2011-01-01

Background: Ingestion of inorganic arsenic in drinking water is recognized as a cause of bladder cancer when levels are relatively high (≥ 150 µg/L). The epidemiologic evidence is less clear at the low-to-moderate concentrations typically observed in the United States. Accurate retrospective exposure assessment over a long time period is a major challenge in conducting epidemiologic studies of environmental factors and diseases with long latency, such as cancer. Objective: We estimated arsenic concentrations in the water supplies of 2,611 participants in a population-based case–control study in northern New England. Methods: Estimates covered the lifetimes of most study participants and were based on a combination of arsenic measurements at the homes of the participants and statistical modeling of arsenic concentrations in the water supply of both past and current homes. We assigned a residential water supply arsenic concentration for 165,138 (95%) of the total 173,361 lifetime exposure years (EYs) and a workplace water supply arsenic level for 85,195 EYs (86% of reported occupational years). Results: Three methods accounted for 93% of the residential estimates of arsenic concentration: direct measurement of water samples (27%; median, 0.3 µg/L; range, 0.1–11.5), statistical models of water utility measurement data (49%; median, 0.4 µg/L; range, 0.3–3.3), and statistical models of arsenic concentrations in wells using aquifers in New England (17%; median, 1.6 µg/L; range, 0.6–22.4). Conclusions: We used a different validation procedure for each of the three methods, and found our estimated levels to be comparable with available measured concentrations. This methodology allowed us to calculate potential drinking water exposure over long periods. PMID:21421449

Estimating water supply arsenic levels in the New England bladder cancer study

USGS Publications Warehouse

Nuckols, J.R.; Beane, Freeman L.E.; Lubin, J.H.; Airola, M.S.; Baris, D.; Ayotte, J.D.; Taylor, A.; Paulu, C.; Karagas, M.R.; Colt, J.; Ward, M.H.; Huang, A.-T.; Bress, W.; Cherala, S.; Silverman, D.T.; Cantor, K.P.

2011-01-01

Background: Ingestion of inorganic arsenic in drinking water is recognized as a cause of bladder cancer when levels are relatively high (??? 150 ??g/L). The epidemiologic evidence is less clear at the low-to-moderate concentrations typically observed in the United States. Accurate retrospective exposure assessment over a long time period is a major challenge in conducting epidemiologic studies of environmental factors and diseases with long latency, such as cancer. Objective: We estimated arsenic concentrations in the water supplies of 2,611 participants in a population-based case-control study in northern New England. Methods: Estimates covered the lifetimes of most study participants and were based on a combination of arsenic measurements at the homes of the participants and statistical modeling of arsenic concentrations in the water supply of both past and current homes. We assigned a residential water supply arsenic concentration for 165,138 (95%) of the total 173,361 lifetime exposure years (EYs) and a workplace water supply arsenic level for 85,195 EYs (86% of reported occupational years). Results: Three methods accounted for 93% of the residential estimates of arsenic concentration: direct measurement of water samples (27%; median, 0.3 ??g/L; range, 0.1-11.5), statistical models of water utility measurement data (49%; median, 0.4 ??g/L; range, 0.3-3.3), and statistical models of arsenic concentrations in wells using aquifers in New England (17%; median, 1.6 ??g/L; range, 0.6-22.4). Conclusions: We used a different validation procedure for each of the three methods, and found our estimated levels to be comparable with available measured concentrations. This methodology allowed us to calculate potential drinking water exposure over long periods.

A biology-driven receptor model for daily pollen allergy risk in Korea based on Weibull probability density function

NASA Astrophysics Data System (ADS)

Kim, Kyu Rang; Kim, Mijin; Choe, Ho-Seong; Han, Mae Ja; Lee, Hye-Rim; Oh, Jae-Won; Kim, Baek-Jo

2017-02-01

Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.

A biology-driven receptor model for daily pollen allergy risk in Korea based on Weibull probability density function.

PubMed

Kim, Kyu Rang; Kim, Mijin; Choe, Ho-Seong; Han, Mae Ja; Lee, Hye-Rim; Oh, Jae-Won; Kim, Baek-Jo

2017-02-01

Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.

Assessing Interval Estimation Methods for Hill Model ...

EPA Pesticide Factsheets

The Hill model of concentration-response is ubiquitous in toxicology, perhaps because its parameters directly relate to biologically significant metrics of toxicity such as efficacy and potency. Point estimates of these parameters obtained through least squares regression or maximum likelihood are commonly used in high-throughput risk assessment, but such estimates typically fail to include reliable information concerning confidence in (or precision of) the estimates. To address this issue, we examined methods for assessing uncertainty in Hill model parameter estimates derived from concentration-response data. In particular, using a sample of ToxCast concentration-response data sets, we applied four methods for obtaining interval estimates that are based on asymptotic theory, bootstrapping (two varieties), and Bayesian parameter estimation, and then compared the results. These interval estimation methods generally did not agree, so we devised a simulation study to assess their relative performance. We generated simulated data by constructing four statistical error models capable of producing concentration-response data sets comparable to those observed in ToxCast. We then applied the four interval estimation methods to the simulated data and compared the actual coverage of the interval estimates to the nominal coverage (e.g., 95%) in order to quantify performance of each of the methods in a variety of cases (i.e., different values of the true Hill model paramet

Use of Satellite Observations for Long-Term Exposure Assessment of Global Concentrations of Fine Particulate Matter

PubMed Central

Martin, Randall V.; Brauer, Michael; Boys, Brian L.

2014-01-01

Background: More than a decade of satellite observations offers global information about the trend and magnitude of human exposure to fine particulate matter (PM2.5). Objective: In this study, we developed improved global exposure estimates of ambient PM2.5 mass and trend using PM2.5 concentrations inferred from multiple satellite instruments. Methods: We combined three satellite-derived PM2.5 sources to produce global PM2.5 estimates at about 10 km × 10 km from 1998 through 2012. For each source, we related total column retrievals of aerosol optical depth to near-ground PM2.5 using the GEOS–Chem chemical transport model to represent local aerosol optical properties and vertical profiles. We collected 210 global ground-based PM2.5 observations from the literature to evaluate our satellite-based estimates with values measured in areas other than North America and Europe. Results: We estimated that global population-weighted ambient PM2.5 concentrations increased 0.55 μg/m3/year (95% CI: 0.43, 0.67) (2.1%/year; 95% CI: 1.6, 2.6) from 1998 through 2012. Increasing PM2.5 in some developing regions drove this global change, despite decreasing PM2.5 in some developed regions. The estimated proportion of the population of East Asia living above the World Health Organization (WHO) Interim Target-1 of 35 μg/m3 increased from 51% in 1998–2000 to 70% in 2010–2012. In contrast, the North American proportion above the WHO Air Quality Guideline of 10 μg/m3 fell from 62% in 1998–2000 to 19% in 2010–2012. We found significant agreement between satellite-derived estimates and ground-based measurements outside North America and Europe (r = 0.81; n = 210; slope = 0.68). The low bias in satellite-derived estimates suggests that true global concentrations could be even greater. Conclusions: Satellite observations provide insight into global long-term changes in ambient PM2.5 concentrations. Satellite-derived estimates and ground-based PM2.5 observations from this study are available for public use. Citation: van Donkelaar A, Martin RV, Brauer M, Boys BL. 2015. Use of satellite observations for long-term exposure assessment of global concentrations of fine particulate matter. Environ Health Perspect 123:135–143; http://dx.doi.org/10.1289/ehp.1408646 PMID:25343779

Modeling particle number concentrations along Interstate 10 in El Paso, Texas

PubMed Central

Olvera, Hector A.; Jimenez, Omar; Provencio-Vasquez, Elias

2014-01-01

Annual average daily particle number concentrations around a highway were estimated with an atmospheric dispersion model and a land use regression model. The dispersion model was used to estimate particle concentrations along Interstate 10 at 98 locations within El Paso, Texas. This model employed annual averaged wind speed and annual average daily traffic counts as inputs. A land use regression model with vehicle kilometers traveled as the predictor variable was used to estimate local background concentrations away from the highway to adjust the near-highway concentration estimates. Estimated particle number concentrations ranged between 9.8 × 103 particles/cc and 1.3 × 105 particles/cc, and averaged 2.5 × 104 particles/cc (SE 421.0). Estimates were compared against values measured at seven sites located along I10 throughout the region. The average fractional error was 6% and ranged between -1% and -13% across sites. The largest bias of -13% was observed at a semi-rural site where traffic was lowest. The average bias amongst urban sites was 5%. The accuracy of the estimates depended primarily on the emission factor and the adjustment to local background conditions. An emission factor of 1.63 × 1014 particles/veh-km was based on a value proposed in the literature and adjusted with local measurements. The integration of the two modeling techniques ensured that the particle number concentrations estimates captured the impact of traffic along both the highway and arterial roadways. The performance and economical aspects of the two modeling techniques used in this study shows that producing particle concentration surfaces along major roadways would be feasible in urban regions where traffic and meteorological data are readily available. PMID:25313294

Multivariate space-time modelling of multiple air pollutants and their health effects accounting for exposure uncertainty.

PubMed

Huang, Guowen; Lee, Duncan; Scott, E Marian

2018-03-30

The long-term health effects of air pollution are often estimated using a spatio-temporal ecological areal unit study, but this design leads to the following statistical challenges: (1) how to estimate spatially representative pollution concentrations for each areal unit; (2) how to allow for the uncertainty in these estimated concentrations when estimating their health effects; and (3) how to simultaneously estimate the joint effects of multiple correlated pollutants. This article proposes a novel 2-stage Bayesian hierarchical model for addressing these 3 challenges, with inference based on Markov chain Monte Carlo simulation. The first stage is a multivariate spatio-temporal fusion model for predicting areal level average concentrations of multiple pollutants from both monitored and modelled pollution data. The second stage is a spatio-temporal model for estimating the health impact of multiple correlated pollutants simultaneously, which accounts for the uncertainty in the estimated pollution concentrations. The novel methodology is motivated by a new study of the impact of both particulate matter and nitrogen dioxide concentrations on respiratory hospital admissions in Scotland between 2007 and 2011, and the results suggest that both pollutants exhibit substantial and independent health effects. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models.

PubMed

Cotten, Cameron; Reed, Jennifer L

2013-01-30

Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the integrated analysis of multi-omics datasets.

Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models

PubMed Central

2013-01-01

Background Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. Results In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. Conclusions This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the integrated analysis of multi-omics datasets. PMID:23360254

Evaluation of Observation-Fused Regional Air Quality Model Results for Population Air Pollution Exposure Estimation

PubMed Central

Chen, Gang; Li, Jingyi; Ying, Qi; Sherman, Seth; Perkins, Neil; Rajeshwari, Sundaram; Mendola, Pauline

2014-01-01

In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O3 (as well as NOx) monitoring networks in the HRR regions are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses. PMID:24747248

Elimination Rates of Dioxin Congeners in Former Chlorophenol Workers from Midland, Michigan

PubMed Central

Collins, James J.; Bodner, Kenneth M.; Wilken, Michael; Bodnar, Catherine M.

2012-01-01

Background: Exposure reconstructions and risk assessments for 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and other dioxins rely on estimates of elimination rates. Limited data are available on elimination rates for congeners other than TCDD. Objectives: We estimated apparent elimination rates using a simple first-order one-compartment model for selected dioxin congeners based on repeated blood sampling in a previously studied population. Methods: Blood samples collected from 56 former chlorophenol workers in 2004–2005 and again in 2010 were analyzed for dioxin congeners. We calculated the apparent elimination half-life in each individual for each dioxin congener and examined factors potentially influencing elimination rates and the impact of estimated ongoing background exposures on rate estimates. Results: Mean concentrations of all dioxin congeners in the sampled participants declined between sampling times. Median apparent half-lives of elimination based on changes in estimated mass in the body were generally consistent with previous estimates and ranged from 6.8 years (1,2,3,7,8,9-hexachlorodibenzo-p-dioxin) to 11.6 years (pentachlorodibenzo-p-dioxin), with a composite half-life of 9.3 years for TCDD toxic equivalents. None of the factors examined, including age, smoking status, body mass index or change in body mass index, initial measured concentration, or chloracne diagnosis, was consistently associated with the estimated elimination rates in this population. Inclusion of plausible estimates of ongoing background exposures decreased apparent half-lives by approximately 10%. Available concentration-dependent toxicokinetic models for TCDD underpredicted observed elimination rates for concentrations < 100 ppt. Conclusions: The estimated elimination rates from this relatively large serial sampling study can inform occupational and environmental exposure and serum evaluations for dioxin compounds. PMID:23063871

Use of supernatant refractive index and supernatant hemoglobin concentration to assess residual glycerol concentration in cryopreserved red blood cells.

PubMed

Wong, Kenneth A; Nsier, Nada; Acker, Jason P

2009-10-01

Red blood cells (RBCs) cryopreserved in glycerol must be deglycerolized prior to transfusion. The adequacy of glycerol removal is commonly assessed by measurement of the refractive index (RI) of the supernatant fluid. However, the presence of free hemoglobin in the supernatant falsely increases the RI and may lead to discard of units that have an acceptable residual glycerol concentration. We performed an analysis of the diagnostic accuracy of 3 methods for residual glycerol measurement - refractometry, osmometry, and a glycerol assay kit. Residual glycerol measurement using these methods was performed on 12 deglycerolized, citrate-phosphate-dextrose (CPD)/saline-adenine-glucose-mannitol (SAGM) leukoreduced RBCs. A calculation that estimates the glycerol concentration based on the refractive index and supernatant hemoglobin concentration was developed and ensures that units with an elevated RI due to the presence of hemoglobin are not discarded if their residual glycerol concentration was <1.0% (w/v). Osmometry was an accurate method for estimating residual glycerol concentration. Refractometry overestimated the residual glycerol concentration due to the interference from hemoglobin. However, when supernatant hemoglobin values were measured and used in the calculation for glycerol concentration, refractometry accurately estimated the residual glycerol concentration. The residual glycerol concentration of cryopreserved, deglycerolized CPD/SAGM RBCs can be accurately estimated using the supernatant refractive index and an equation that accounts for the supernatant hemoglobin concentration.

Estimation of methane concentrations and loads in groundwater discharge to Sugar Run, Lycoming County, Pennsylvania

USGS Publications Warehouse

Heilweil, Victor M.; Risser, Dennis W.; Conger, Randall W.; Grieve, Paul L.; Hynek, Scott A.

2014-01-01

A stream-sampling study was conducted to estimate methane concentrations and loads in groundwater discharge to a small stream in an active shale-gas development area of northeastern Pennsylvania. Grab samples collected from 15 streams in Bradford, Lycoming, Susquehanna, and Tioga Counties, Pa., during a reconnaissance survey in May and June 2013 contained dissolved methane concentrations ranging from less than the minimum reporting limit (1.0) to 68.5 micrograms per liter (µg/L). The stream-reach mass-balance method of estimating concentrations and loads of methane in groundwater discharge was applied to a 4-kilometer (km) reach of Sugar Run in Lycoming County, one of the four streams with methane concentrations greater than or equal to 5 µg/L. Three synoptic surveys of stream discharge and methane concentrations were conducted during base-flow periods in May, June, and November 2013. Stream discharge at the lower end of the reach was about 0.10, 0.04, and 0.02 cubic meters per second, respectively, and peak stream methane concentrations were about 20, 67, and 29 µg/L. In order to refine estimated amounts of groundwater discharge and locations where groundwater with methane discharges to the stream, the lower part of the study reach was targeted more precisely during the successive studies, with approximate spacing between stream sampling sites of 800 meters (m), 400 m, and 200 m, in May, June, and November, respectively. Samples collected from shallow piezometers and a seep near the location of the peak methane concentration measured in streamwater had groundwater methane concentrations of 2,300 to 4,600 µg/L. These field data, combined with one-dimensional stream-methane transport modeling, indicate groundwater methane loads of 1.8 ±0.8, 0.7 ±0.3, and 0.7 ±0.2 kilograms per day, respectively, discharging to Sugar Run. Estimated groundwater methane concentrations, based on the transport modeling, ranged from 100 to 3,200 µg/L. Although total methane load and the uncertainty in calculated loads both decreased with lower streamflow conditions and finer-resolution sampling in June and November, the higher loads during May could indicate seasonal variability in base flow. This is consistent with flowmeter measurements indicating that there was less inflow occurring at lower streamflow conditions during June and November.

Increasing precision of turbidity-based suspended sediment concentration and load estimates.

PubMed

Jastram, John D; Zipper, Carl E; Zelazny, Lucian W; Hyer, Kenneth E

2010-01-01

Turbidity is an effective tool for estimating and monitoring suspended sediments in aquatic systems. Turbidity can be measured in situ remotely and at fine temporal scales as a surrogate for suspended sediment concentration (SSC), providing opportunity for a more complete record of SSC than is possible with physical sampling approaches. However, there is variability in turbidity-based SSC estimates and in sediment loadings calculated from those estimates. This study investigated the potential to improve turbidity-based SSC, and by extension the resulting sediment loading estimates, by incorporating hydrologic variables that can be monitored remotely and continuously (typically 15-min intervals) into the SSC estimation procedure. On the Roanoke River in southwestern Virginia, hydrologic stage, turbidity, and other water-quality parameters were monitored with in situ instrumentation; suspended sediments were sampled manually during elevated turbidity events; samples were analyzed for SSC and physical properties including particle-size distribution and organic C content; and rainfall was quantified by geologic source area. The study identified physical properties of the suspended-sediment samples that contribute to SSC estimation variance and hydrologic variables that explained variability of those physical properties. Results indicated that the inclusion of any of the measured physical properties in turbidity-based SSC estimation models reduces unexplained variance. Further, the use of hydrologic variables to represent these physical properties, along with turbidity, resulted in a model, relying solely on data collected remotely and continuously, that estimated SSC with less variance than a conventional turbidity-based univariate model, allowing a more precise estimate of sediment loading, Modeling results are consistent with known mechanisms governing sediment transport in hydrologic systems.

Battery Power Management in Heavy-duty HEVs based on the Estimated Critical Surface Charge

DTIC Science & Technology

2011-03-01

health prospects without any penalty on fuel efficiency. Keywords: Lithium - ion battery ; power management; critical surface charge; Lithium-ion...fuel efficiency. 15. SUBJECT TERMS Lithium - ion battery ; power management; critical surface charge; Lithium-ion concentration; estimation; extended...Di Domenico, D., Fiengo, G., and Stefanopoulou, A. (2008) ’ Lithium - ion battery state of charge estimation with a kalman filter based on a

Using a physiologically based pharmacokinetic model to link urinary biomarker concentrations to dietary exposure of perchlorate

EPA Science Inventory

Exposure to perchlorate is widespread in the United States and many studies have attempted to character the perchlorate exposure by estimating the average daily intakes of perchlorate. These approaches provided population-based estimates, but did not provide individual-level exp...

A Nonlinear Regression Model Estimating Single Source Concentrations of Primary and Secondarily Formed 2.5

EPA Science Inventory

Various approaches and tools exist to estimate local and regional PM_2.5 impacts from a single emissions source, ranging from simple screening techniques to Gaussian based dispersion models and complex grid-based Eulerian photochemical transport models. These approache...

Mechanisms of recharge in a fractured porous rock aquifer in a semi-arid region

NASA Astrophysics Data System (ADS)

Manna, Ferdinando; Walton, Kenneth M.; Cherry, John A.; Parker, Beth L.

2017-12-01

Eleven porewater profiles in rock core from an upland exposed sandstone vadose zone in southern California, with thickness varying between 10 and 62 m, were analyzed for chloride (Cl) concentration to examine recharge mechanisms, estimate travel times in the vadose zone, assess spatial and temporal variability of recharge, and determine effects of land use changes on recharge. As a function of their location and the local terrain, the profiles were classified into four groups reflecting the range of site characteristics. Century- to millennium-average recharge varied from 4 to 23 mm y-1, corresponding to <1-5% of the average annual precipitation (451 mm over the 1878-2016 period). Based on the different average Cl concentrations in the vadose zone and in groundwater, the contribution of diffuse flow (estimated at 80%) and preferential flow (20%) to the total recharge was quantified. This model of dual porosity recharge was tested by simulating transient Cl transport along a physically based narrow column using a discrete fracture-matrix numerical model. Using a new approach based on partitioning both water and Cl between matrix and fracture flow, porewater was dated and vertical displacement rates estimated to range in the sandstone matrix from 3 to 19 cm y-1. Moreover, the temporal variability of recharge was estimated and, along each profile, past recharge rates calculated based on the sequence of Cl concentrations in the vadose zone. Recharge rates increased at specific times coincident with historical changes in land use. The consistency between the timing of land use modifications and changes in Cl concentration and the match between observed and simulated Cl concentration values in the vadose zone provide confidence in porewater age estimates, travel times, recharge estimates, and reconstruction of recharge histories. This study represents an advancement of the application of the chloride mass balance method to simultaneously determine recharge mechanisms and reconstruct location-specific recharge histories in fractured porous rock aquifers. The proposed approach can be applied worldwide at sites with similar climatic and geologic characteristics.

Excel-Based Tool for Pharmacokinetically Guided Dose Adjustment of Paclitaxel.

PubMed

Kraff, Stefanie; Lindauer, Andreas; Joerger, Markus; Salamone, Salvatore J; Jaehde, Ulrich

2015-12-01

Neutropenia is a frequent and severe adverse event in patients receiving paclitaxel chemotherapy. The time above a paclitaxel threshold concentration of 0.05 μmol/L (Tc > 0.05 μmol/L) is a strong predictor for paclitaxel-associated neutropenia and has been proposed as a target pharmacokinetic (PK) parameter for paclitaxel therapeutic drug monitoring and dose adaptation. Up to now, individual Tc > 0.05 μmol/L values are estimated based on a published PK model of paclitaxel by using the software NONMEM. Because many clinicians are not familiar with the use of NONMEM, an Excel-based dosing tool was developed to allow calculation of paclitaxel Tc > 0.05 μmol/L and give clinicians an easy-to-use tool. Population PK parameters of paclitaxel were taken from a published PK model. An Alglib VBA code was implemented in Excel 2007 to compute differential equations for the paclitaxel PK model. Maximum a posteriori Bayesian estimates of the PK parameters were determined with the Excel Solver using individual drug concentrations. Concentrations from 250 patients were simulated receiving 1 cycle of paclitaxel chemotherapy. Predictions of paclitaxel Tc > 0.05 μmol/L as calculated by the Excel tool were compared with NONMEM, whereby maximum a posteriori Bayesian estimates were obtained using the POSTHOC function. There was a good concordance and comparable predictive performance between Excel and NONMEM regarding predicted paclitaxel plasma concentrations and Tc > 0.05 μmol/L values. Tc > 0.05 μmol/L had a maximum bias of 3% and an error on precision of <12%. The median relative deviation of the estimated Tc > 0.05 μmol/L values between both programs was 1%. The Excel-based tool can estimate the time above a paclitaxel threshold concentration of 0.05 μmol/L with acceptable accuracy and precision. The presented Excel tool allows reliable calculation of paclitaxel Tc > 0.05 μmol/L and thus allows target concentration intervention to improve the benefit-risk ratio of the drug. The easy use facilitates therapeutic drug monitoring in clinical routine.

Profiles of lead in urban dust and the effect of the distance to multi-industry in an old heavy industry city in China.

PubMed

Yu, Yang; Li, Yingxia; Li, Ben; Shen, Zhenyao; Stenstrom, Michael K

2017-03-01

Lead (Pb) concentration in urban dust is often higher than background concentrations and can result in a wide range of health risks to local communities. To understand Pb distribution in urban dust and how multi-industrial activity affects Pb concentration, 21 sampling sites within the heavy industry city of Jilin, China, were analyzed for Pb concentration. Pb concentrations of all 21 urban dust samples from the Jilin City Center were higher than the background concentration for soil in Jilin Province. The analyses show that distance to industry is an important parameter determining health risks associated with Pb in urban dust. The Pb concentration showed an exponential decrease, with increasing distance from industry. Both maximum likelihood estimation and Bayesian analysis were used to estimate the exponential relationship between Pb concentration and distance to multi-industry areas. We found that Bayesian analysis was a better method with less uncertainty for estimating Pb dust concentrations based on their distance to multi-industry, and this approach is recommended for further study. Copyright © 2016. Published by Elsevier Inc.

Development and evaluation of consensus-based sediment effect concentrations for polychlorinated biphenyls

USGS Publications Warehouse

MacDonald, Donald D.; Dipinto, Lisa M.; Field, Jay; Ingersoll, Christopher G.; Long, Edward R.; Swartz, Richard C.

2000-01-01

Sediment-quality guidelines (SQGs) have been published for polychlorinated biphenyls (PCBs) using both empirical and theoretical approaches. Empirically based guidelines have been developed using the screening-level concentration, effects range, effects level, and apparent effects threshold approaches. Theoretically based guidelines have been developed using the equilibrium-partitioning approach. Empirically-based guidelines were classified into three general categories, in accordance with their original narrative intents, and used to develop three consensus-based sediment effect concentrations (SECs) for total PCBs (tPCBs), including a threshold effect concentration, a midrange effect concentration, and an extreme effect concentration. Consensus-based SECs were derived because they estimate the central tendency of the published SQGs and, thus, reconcile the guidance values that have been derived using various approaches. Initially, consensus-based SECs for tPCBs were developed separately for freshwater sediments and for marine and estuarine sediments. Because the respective SECs were statistically similar, the underlying SQGs were subsequently merged and used to formulate more generally applicable SECs. The three consensus-based SECs were then evaluated for reliability using matching sediment chemistry and toxicity data from field studies, dose-response data from spiked-sediment toxicity tests, and SQGs derived from the equilibrium-partitioning approach. The results of this evaluation demonstrated that the consensus-based SECs can accurately predict both the presence and absence of toxicity in field-collected sediments. Importantly, the incidence of toxicity increases incrementally with increasing concentrations of tPCBs. Moreover, the consensus-based SECs are comparable to the chronic toxicity thresholds that have been estimated from dose-response data and equilibrium-partitioning models. Therefore, consensus-based SECs provide a unifying synthesis of existing SQGs, reflect causal rather than correlative effects, and accurately predict sediment toxicity in PCB-contaminated sediments.

Least Square Regression Method for Estimating Gas Concentration in an Electronic Nose System

PubMed Central

Khalaf, Walaa; Pace, Calogero; Gaudioso, Manlio

2009-01-01

We describe an Electronic Nose (ENose) system which is able to identify the type of analyte and to estimate its concentration. The system consists of seven sensors, five of them being gas sensors (supplied with different heater voltage values), the remainder being a temperature and a humidity sensor, respectively. To identify a new analyte sample and then to estimate its concentration, we use both some machine learning techniques and the least square regression principle. In fact, we apply two different training models; the first one is based on the Support Vector Machine (SVM) approach and is aimed at teaching the system how to discriminate among different gases, while the second one uses the least squares regression approach to predict the concentration of each type of analyte. PMID:22573980

Assessment of 10B concentration in boron neutron capture therapy: potential of image-guided therapy using 18FBPA PET.

PubMed

Shimosegawa, Eku; Isohashi, Kayako; Naka, Sadahiro; Horitsugi, Genki; Hatazawa, Jun

2016-12-01

In boron neutron capture therapy (BNCT) for cancer, the accurate estimation of 10 B tissue concentrations, especially in neighboring normal organs, is important to avoid adverse effects. The 10 B concentration in normal organs after loading with 10 B, however, has not been established in humans. In this study, we performed 4-borono-2-[ 18 F]-fluoro-phenylalanine ( 18 FBPA) PET in healthy volunteers and estimated the chronological changes in the 10 B concentrations of normal organs. In 6 healthy volunteers, whole-body 18 FBPA PET scans were repeated 7 times during 1 h, and the mean 18 FBPA distributions of 13 organs were measured. Based on the 18 FBPA PET data, we then estimated the changes in the 10 B concentrations of the organs when the injection of a therapeutic dose of 10 BPA-fructose complex ( 10 BPA-fr; 30 g, 500 mg/kg body weight) was assumed. The maximum mean 18 FBPA concentrations were reached at 2-6 min after injection in all the organs except the brain and urinary bladder. The mean 18 FBPA concentration in normal brain plateaued at 24 min after injection. When the injection of a therapeutic dose of 10 BPA-fr was assumed, the estimated mean 10 B concentration in the kidney increased to 126.1 ± 24.2 ppm at 3 min after injection and then rapidly decreased to 30.9 ± 7.4 ppm at 53 min. The estimated mean 10 B concentration in the bladder gradually increased and reached 383.6 ± 214.7 ppm at 51 min. The mean 10 B concentration in the brain was estimated to be 7.6 ± 1.5 ppm at 57 min. 18 FBPA PET has a potential to estimate 10 B concentration of normal organs before neutron irradiation of BNCT when several assumptions are validated in the future studies.

Ratio-based vs. model-based methods to correct for urinary creatinine concentrations.

PubMed

Jain, Ram B

2016-08-01

Creatinine-corrected urinary analyte concentration is usually computed as the ratio of the observed level of analyte concentration divided by the observed level of the urinary creatinine concentration (UCR). This ratio-based method is flawed since it implicitly assumes that hydration is the only factor that affects urinary creatinine concentrations. On the contrary, it has been shown in the literature, that age, gender, race/ethnicity, and other factors also affect UCR. Consequently, an optimal method to correct for UCR should correct for hydration as well as other factors like age, gender, and race/ethnicity that affect UCR. Model-based creatinine correction in which observed UCRs are used as an independent variable in regression models has been proposed. This study was conducted to evaluate the performance of ratio-based and model-based creatinine correction methods when the effects of gender, age, and race/ethnicity are evaluated one factor at a time for selected urinary analytes and metabolites. It was observed that ratio-based method leads to statistically significant pairwise differences, for example, between males and females or between non-Hispanic whites (NHW) and non-Hispanic blacks (NHB), more often than the model-based method. However, depending upon the analyte of interest, the reverse is also possible. The estimated ratios of geometric means (GM), for example, male to female or NHW to NHB, were also compared for the two methods. When estimated UCRs were higher for the group (for example, males) in the numerator of this ratio, these ratios were higher for the model-based method, for example, male to female ratio of GMs. When estimated UCR were lower for the group (for example, NHW) in the numerator of this ratio, these ratios were higher for the ratio-based method, for example, NHW to NHB ratio of GMs. Model-based method is the method of choice if all factors that affect UCR are to be accounted for.

An improved geographically weighted regression model for PM2.5 concentration estimation in large areas

NASA Astrophysics Data System (ADS)

Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan

2018-05-01

Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.

Global Estimates of Ambient Fine Particulate Matter Concentrations from Satellite-Based Aerosol Optical Depth: Development and Application

PubMed Central

van Donkelaar, Aaron; Martin, Randall V.; Brauer, Michael; Kahn, Ralph; Levy, Robert; Verduzco, Carolyn; Villeneuve, Paul J.

2010-01-01

Background Epidemiologic and health impact studies of fine particulate matter with diameter < 2.5 μm (PM2.5) are limited by the lack of monitoring data, especially in developing countries. Satellite observations offer valuable global information about PM2.5 concentrations. Objective In this study, we developed a technique for estimating surface PM2.5 concentrations from satellite observations. Methods We mapped global ground-level PM2.5 concentrations using total column aerosol optical depth (AOD) from the MODIS (Moderate Resolution Imaging Spectroradiometer) and MISR (Multiangle Imaging Spectroradiometer) satellite instruments and coincident aerosol vertical profiles from the GEOS-Chem global chemical transport model. Results We determined that global estimates of long-term average (1 January 2001 to 31 December 2006) PM2.5 concentrations at approximately 10 km × 10 km resolution indicate a global population-weighted geometric mean PM2.5 concentration of 20 μg/m3. The World Health Organization Air Quality PM2.5 Interim Target-1 (35 μg/m3 annual average) is exceeded over central and eastern Asia for 38% and for 50% of the population, respectively. Annual mean PM2.5 concentrations exceed 80 μg/m3 over eastern China. Our evaluation of the satellite-derived estimate with ground-based in situ measurements indicates significant spatial agreement with North American measurements (r = 0.77; slope = 1.07; n = 1057) and with noncoincident measurements elsewhere (r = 0.83; slope = 0.86; n = 244). The 1 SD of uncertainty in the satellite-derived PM2.5 is 25%, which is inferred from the AOD retrieval and from aerosol vertical profile errors and sampling. The global population-weighted mean uncertainty is 6.7 μg/m3. Conclusions Satellite-derived total-column AOD, when combined with a chemical transport model, provides estimates of global long-term average PM2.5 concentrations. PMID:20519161

High-throughput dietary exposure predictions for chemical migrants from food contact substances for use in chemical prioritization.

PubMed

Biryol, Derya; Nicolas, Chantel I; Wambaugh, John; Phillips, Katherine; Isaacs, Kristin

2017-11-01

Under the ExpoCast program, United States Environmental Protection Agency (EPA) researchers have developed a high-throughput (HT) framework for estimating aggregate exposures to chemicals from multiple pathways to support rapid prioritization of chemicals. Here, we present methods to estimate HT exposures to chemicals migrating into food from food contact substances (FCS). These methods consisted of combining an empirical model of chemical migration with estimates of daily population food intakes derived from food diaries from the National Health and Nutrition Examination Survey (NHANES). A linear regression model for migration at equilibrium was developed by fitting available migration measurements as a function of temperature, food type (i.e., fatty, aqueous, acidic, alcoholic), initial chemical concentration in the FCS (C 0 ) and chemical properties. The most predictive variables in the resulting model were C 0 , molecular weight, log K ow , and food type (R 2 =0.71, p<0.0001). Migration-based concentrations for 1009 chemicals identified via publicly-available data sources as being present in polymer FCSs were predicted for 12 food groups (combinations of 3 storage temperatures and food type). The model was parameterized with screening-level estimates of C 0 based on the functional role of chemicals in FCS. By combining these concentrations with daily intakes for food groups derived from NHANES, population ingestion exposures of chemical in mg/kg-bodyweight/day (mg/kg-BW/day) were estimated. Calibrated aggregate exposures were estimated for 1931 chemicals by fitting HT FCS and consumer product exposures to exposures inferred from NHANES biomonitoring (R 2 =0.61, p<0.001); both FCS and consumer product pathway exposures were significantly predictive of inferred exposures. Including the FCS pathway significantly impacted the ratio of predicted exposures to those estimated to produce steady-state blood concentrations equal to in-vitro bioactive concentrations. While these HT methods have large uncertainties (and thus may not be appropriate for assessments of single chemicals), they can provide critical refinement to aggregate exposure predictions used in risk-based chemical priority-setting. Published by Elsevier Ltd.

Satellite constraints on surface concentrations of particulate matter

NASA Astrophysics Data System (ADS)

Ford Hotmann, Bonne

Because of the increasing evidence of the widespread adverse effects on human health from exposure to poor air quality and the recommendations of the World Health Organization to significantly reduce PM2.5 in order to reduce these risks, better estimates of surface air quality globally are required. However, surface measurements useful for monitoring particulate exposure are scarce, especially in developing countries which often experience the worst air pollution. Therefore, other methods are necessary to augment estimates in regions with limited surface observations. The prospect of using satellite observations to infer surface air quality is attractive; however, it requires knowledge of the complicated relationship between satellite-observed aerosol optical depth (AOD) and surface concentrations. This dissertation explores how satellite observations can be used in conjunction with a chemical transport model (GEOS-Chem) to better understand this relationship. First, we investigate the seasonality in aerosols over the Southeastern United States using observations from several satellite instruments (MODIS, MISR, CALIOP) and surface network sites (IMPROVE, SEARCH, AERONET). We find that the strong summertime enhancement in satellite-observed aerosol optical depth (factor 2-3 enhancement over wintertime AOD) is not present in surface mass concentrations (25-55% summertime enhancement). Goldstein et al. [2009] previously attributed this seasonality in AOD to biogenic organic aerosol; however, surface observations show that organic aerosol only accounts for ~35% of PM2.5 mass and exhibits similar seasonality to total surface PM2.5. The GEOS-Chem model generally reproduces these surface aerosol measurements, but under represents the AOD seasonality observed by satellites. We show that seasonal differences in water uptake cannot sufficiently explain the magnitude of AOD increase. As CALIOP profiles indicate the presence of additional aerosol in the lower troposphere (below 700 hPa), which cannot be explained by vertical mixing; we conclude that the discrepancy is due to a missing source of aerosols above the surface layer in summer. Next, we examine the usefulness of deriving premature mortality estimates from "satellite-based" PM2.5 concentrations. In particular, we examine how uncertainties in the model AOD-to-surface-PM2.5 relationship, satellite retrieved AOD, and particulars of the concentration-response function can impact these mortality estimates. We find that the satellite-based estimates suggest premature mortality due to chronic PM2.5 exposure is 2-16% higher in the U.S. and 4-13% lower in China compared to model-based estimates. However, this difference is overshadowed by the uncertainty in the methodology, which we quantify to be on order of 20% for the model-to- surface-PM2.5 relationship, 10% for the satellite AOD and 30-60% or greater with regards to the application of concentration response functions. Because there is a desire for acute exposure estimates, especially with regards to extreme events, we also examine how premature mortality due to acute exposure can be estimated from global models and satellite-observations. We find similar differences between model and satellite-based mortality estimates as with chronic exposure. However the range of uncertainty is much larger on these shorter timescales. This work suggests that although satellites can be useful for constraining model estimates of PM2.5, national mortality estimates from the two methods are not significantly different. In order to improve the efficacy of satellite-based PM2.5 mortality estimates, future work will need to focus on improving the model representation of the regional AOD-to-surface-PM2.5 relationship, reducing biases in satellite-retrieved AOD and advancing our understanding of personal and population-level responses to PM2.5 exposure.

Modeling of air pollutant removal by dry deposition to urban trees using a WRF/CMAQ/i-Tree Eco coupled system.

PubMed

Cabaraban, Maria Theresa I; Kroll, Charles N; Hirabayashi, Satoshi; Nowak, David J

2013-05-01

A distributed adaptation of i-Tree Eco was used to simulate dry deposition in an urban area. This investigation focused on the effects of varying temperature, LAI, and NO2 concentration inputs on estimated NO2 dry deposition to trees in Baltimore, MD. A coupled modeling system is described, wherein WRF provided temperature and LAI fields, and CMAQ provided NO2 concentrations. A base case simulation was conducted using built-in distributed i-Tree Eco tools, and simulations using different inputs were compared against this base case. Differences in land cover classification and tree cover between the distributed i-Tree Eco and WRF resulted in changes in estimated LAI, which in turn resulted in variations in simulated NO2 dry deposition. Estimated NO2 removal decreased when CMAQ-derived concentration was applied to the distributed i-Tree Eco simulation. Discrepancies in temperature inputs did little to affect estimates of NO2 removal by dry deposition to trees in Baltimore. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Comparative Study of Three Spatial Interpolation Methodologies for the Analysis of Air Pollution Concentrations in Athens, Greece

NASA Astrophysics Data System (ADS)

Deligiorgi, Despina; Philippopoulos, Kostas; Thanou, Lelouda; Karvounis, Georgios

2010-01-01

Spatial interpolation in air pollution modeling is the procedure for estimating ambient air pollution concentrations at unmonitored locations based on available observations. The selection of the appropriate methodology is based on the nature and the quality of the interpolated data. In this paper, an assessment of three widely used interpolation methodologies is undertaken in order to estimate the errors involved. For this purpose, air quality data from January 2001 to December 2005, from a network of seventeen monitoring stations, operating at the greater area of Athens in Greece, are used. The Nearest Neighbor and the Liner schemes were applied to the mean hourly observations, while the Inverse Distance Weighted (IDW) method to the mean monthly concentrations. The discrepancies of the estimated and measured values are assessed for every station and pollutant, using the correlation coefficient, the scatter diagrams and the statistical residuals. The capability of the methods to estimate air quality data in an area with multiple land-use types and pollution sources, such as Athens, is discussed.

Application of chlorine-36 technique in determining the age of modern groundwater in the Al-Zulfi province, Saudi Arabia.

PubMed

Challan, Mohsen B

2016-06-01

The present study aims to estimate the residence time of groundwater based on bomb-produced (36)Cl. (36)Cl/Cl ratios in the water samples are determined by inductively coupled plasma mass spectrometry and liquid scintillation counting. (36)Cl/Cl ratios in the groundwater were estimated to be 1.0-2.0 × 10(-12). Estimates of residence time were obtained by comparing the measured bomb-derived (36)Cl concentrations in groundwater with the background reference. Dating based on a (36)Cl bomb pulse may be more reliable and sensitive for groundwater recharged before 1975, back as far as the mid-1950s. The above (36)Cl background concentration was deduced by determining the background-corrected Dye-3 ice core data from the frozen Arctic data, according to the estimated total (36)Cl resources. The residence time of 7.81 × 10(4) y is obtained from extrapolated groundwater flow velocity. (36)Cl concentration in groundwater does not reflect the input of bomb pulse (36)Cl, and it belongs to the era before 1950.

Adjustments of the Pesticide Risk Index Used in Environmental Policy in Flanders

PubMed Central

Fevery, Davina; Peeters, Bob; Lenders, Sonia; Spanoghe, Pieter

2015-01-01

Indicators are used to quantify the pressure of pesticides on the environment. Pesticide risk indicators typically require weighting environmental exposure by a no effect concentration. An indicator based on spread equivalents (ΣSeq) is used in environmental policy in Flanders (Belgium). The pesticide risk for aquatic life is estimated by weighting active ingredient usage by the ratio of their maximum allowable concentration and their soil halflife. Accurate estimates of total pesticide usage in the region are essential in such calculations. Up to 2012, the environmental impact of pesticides was estimated on sales figures provided by the Federal Government. Since 2013, pesticide use is calculated based on results from the Farm Accountancy Data Network (FADN). The estimation of pesticide use was supplemented with data for non-agricultural use based on sales figures of amateur use provided by industry and data obtained from public services. The Seq-indicator was modified to better reflect reality. This method was applied for the period 2009-2012 and showed differences between estimated use and sales figures of pesticides. The estimated use of pesticides based on accountancy data is more accurate compared to sales figures. This approach resulted in a better view on pesticide use and its respective environmental impact in Flanders. PMID:26046655

Adjustments of the Pesticide Risk Index Used in Environmental Policy in Flanders.

PubMed

Fevery, Davina; Peeters, Bob; Lenders, Sonia; Spanoghe, Pieter

2015-01-01

Indicators are used to quantify the pressure of pesticides on the environment. Pesticide risk indicators typically require weighting environmental exposure by a no effect concentration. An indicator based on spread equivalents (ΣSeq) is used in environmental policy in Flanders (Belgium). The pesticide risk for aquatic life is estimated by weighting active ingredient usage by the ratio of their maximum allowable concentration and their soil halflife. Accurate estimates of total pesticide usage in the region are essential in such calculations. Up to 2012, the environmental impact of pesticides was estimated on sales figures provided by the Federal Government. Since 2013, pesticide use is calculated based on results from the Farm Accountancy Data Network (FADN). The estimation of pesticide use was supplemented with data for non-agricultural use based on sales figures of amateur use provided by industry and data obtained from public services. The Seq-indicator was modified to better reflect reality. This method was applied for the period 2009-2012 and showed differences between estimated use and sales figures of pesticides. The estimated use of pesticides based on accountancy data is more accurate compared to sales figures. This approach resulted in a better view on pesticide use and its respective environmental impact in Flanders.

Assessment of pollutant mean concentrations in the Yangtze estuary based on MSN theory.

PubMed

Ren, Jing; Gao, Bing-Bo; Fan, Hai-Mei; Zhang, Zhi-Hong; Zhang, Yao; Wang, Jin-Feng

2016-12-15

Reliable assessment of water quality is a critical issue for estuaries. Nutrient concentrations show significant spatial distinctions between areas under the influence of fresh-sea water interaction and anthropogenic effects. For this situation, given the limitations of general mean estimation approaches, a new method for surfaces with non-homogeneity (MSN) was applied to obtain optimized linear unbiased estimations of the mean nutrient concentrations in the study area in the Yangtze estuary from 2011 to 2013. Other mean estimation methods, including block Kriging (BK), simple random sampling (SS) and stratified sampling (ST) inference, were applied simultaneously for comparison. Their performance was evaluated by estimation error. The results show that MSN had the highest accuracy, while SS had the highest estimation error. ST and BK were intermediate in terms of their performance. Thus, MSN is an appropriate method that can be adopted to reduce the uncertainty of mean pollutant estimation in estuaries. Copyright © 2016 Elsevier Ltd. All rights reserved.

A computer program for estimating instream travel times and concentrations of a potential contaminant in the Yellowstone River, Montana

USGS Publications Warehouse

McCarthy, Peter M.

2006-01-01

The Yellowstone River is very important in a variety of ways to the residents of southeastern Montana; however, it is especially vulnerable to spilled contaminants. In 2004, the U.S. Geological Survey, in cooperation with Montana Department of Environmental Quality, initiated a study to develop a computer program to rapidly estimate instream travel times and concentrations of a potential contaminant in the Yellowstone River using regression equations developed in 1999 by the U.S. Geological Survey. The purpose of this report is to describe these equations and their limitations, describe the development of a computer program to apply the equations to the Yellowstone River, and provide detailed instructions on how to use the program. This program is available online at [http://pubs.water.usgs.gov/sir2006-5057/includes/ytot.xls]. The regression equations provide estimates of instream travel times and concentrations in rivers where little or no contaminant-transport data are available. Equations were developed and presented for the most probable flow velocity and the maximum probable flow velocity. These velocity estimates can then be used to calculate instream travel times and concentrations of a potential contaminant. The computer program was developed so estimation equations for instream travel times and concentrations can be solved quickly for sites along the Yellowstone River between Corwin Springs and Sidney, Montana. The basic types of data needed to run the program are spill data, streamflow data, and data for locations of interest along the Yellowstone River. Data output from the program includes spill location, river mileage at specified locations, instantaneous discharge, mean-annual discharge, drainage area, and channel slope. Travel times and concentrations are provided for estimates of the most probable velocity of the peak concentration and the maximum probable velocity of the peak concentration. Verification of estimates of instream travel times and concentrations for the Yellowstone River requires information about the flow velocity throughout the 520 mi of river in the study area. Dye-tracer studies would provide the best data about flow velocities and would provide the best verification of instream travel times and concentrations estimated from this computer program; however, data from such studies does not currently (2006) exist and new studies would be expensive and time-consuming. An alternative approach used in this study for verification of instream travel times is based on the use of flood-wave velocities determined from recorded streamflow hydrographs at selected mainstem streamflow-gaging stations along the Yellowstone River. The ratios of flood-wave velocity to the most probable velocity for the base flow estimated from the computer program are within the accepted range of 2.5 to 4.0 and indicate that flow velocities estimated from the computer program are reasonable for the Yellowstone River. The ratios of flood-wave velocity to the maximum probable velocity are within a range of 1.9 to 2.8 and indicate that the maximum probable flow velocities estimated from the computer program, which corresponds to the shortest travel times and maximum probable concentrations, are conservative and reasonable for the Yellowstone River.

Estimating historical atmospheric mercury concentrations from silver mining and their legacies in present-day surface soil in Potosí, Bolivia

NASA Astrophysics Data System (ADS)

Hagan, Nicole; Robins, Nicholas; Hsu-Kim, Heileen; Halabi, Susan; Morris, Mark; Woodall, George; Zhang, Tong; Bacon, Allan; Richter, Daniel De B.; Vandenberg, John

2011-12-01

Detailed Spanish records of mercury use and silver production during the colonial period in Potosí, Bolivia were evaluated to estimate atmospheric emissions of mercury from silver smelting. Mercury was used in the silver production process in Potosí and nearly 32,000 metric tons of mercury were released to the environment. AERMOD was used in combination with the estimated emissions to approximate historical air concentrations of mercury from colonial mining operations during 1715, a year of relatively low silver production. Source characteristics were selected from archival documents, colonial maps and images of silver smelters in Potosí and a base case of input parameters was selected. Input parameters were varied to understand the sensitivity of the model to each parameter. Modeled maximum 1-h concentrations were most sensitive to stack height and diameter, whereas an index of community exposure was relatively insensitive to uncertainty in input parameters. Modeled 1-h and long-term concentrations were compared to inhalation reference values for elemental mercury vapor. Estimated 1-h maximum concentrations within 500 m of the silver smelters consistently exceeded present-day occupational inhalation reference values. Additionally, the entire community was estimated to have been exposed to levels of mercury vapor that exceed present-day acute inhalation reference values for the general public. Estimated long-term maximum concentrations of mercury were predicted to substantially exceed the EPA Reference Concentration for areas within 600 m of the silver smelters. A concentration gradient predicted by AERMOD was used to select soil sampling locations along transects in Potosí. Total mercury in soils ranged from 0.105 to 155 mg kg-1, among the highest levels reported for surface soils in the scientific literature. The correlation between estimated air concentrations and measured soil concentrations will guide future research to determine the extent to which the current community of Potosí and vicinity is at risk of adverse health effects from historical mercury contamination.

Estimating the Probability of Elevated Nitrate Concentrations in Ground Water in Washington State

USGS Publications Warehouse

Frans, Lonna M.

2008-01-01

Logistic regression was used to relate anthropogenic (manmade) and natural variables to the occurrence of elevated nitrate concentrations in ground water in Washington State. Variables that were analyzed included well depth, ground-water recharge rate, precipitation, population density, fertilizer application amounts, soil characteristics, hydrogeomorphic regions, and land-use types. Two models were developed: one with and one without the hydrogeomorphic regions variable. The variables in both models that best explained the occurrence of elevated nitrate concentrations (defined as concentrations of nitrite plus nitrate as nitrogen greater than 2 milligrams per liter) were the percentage of agricultural land use in a 4-kilometer radius of a well, population density, precipitation, soil drainage class, and well depth. Based on the relations between these variables and measured nitrate concentrations, logistic regression models were developed to estimate the probability of nitrate concentrations in ground water exceeding 2 milligrams per liter. Maps of Washington State were produced that illustrate these estimated probabilities for wells drilled to 145 feet below land surface (median well depth) and the estimated depth to which wells would need to be drilled to have a 90-percent probability of drawing water with a nitrate concentration less than 2 milligrams per liter. Maps showing the estimated probability of elevated nitrate concentrations indicated that the agricultural regions are most at risk followed by urban areas. The estimated depths to which wells would need to be drilled to have a 90-percent probability of obtaining water with nitrate concentrations less than 2 milligrams per liter exceeded 1,000 feet in the agricultural regions; whereas, wells in urban areas generally would need to be drilled to depths in excess of 400 feet.

Remote sensing estimation of the total phosphorus concentration in a large lake using band combinations and regional multivariate statistical modeling techniques.

PubMed

Gao, Yongnian; Gao, Junfeng; Yin, Hongbin; Liu, Chuansheng; Xia, Ting; Wang, Jing; Huang, Qi

2015-03-15

Remote sensing has been widely used for ater quality monitoring, but most of these monitoring studies have only focused on a few water quality variables, such as chlorophyll-a, turbidity, and total suspended solids, which have typically been considered optically active variables. Remote sensing presents a challenge in estimating the phosphorus concentration in water. The total phosphorus (TP) in lakes has been estimated from remotely sensed observations, primarily using the simple individual band ratio or their natural logarithm and the statistical regression method based on the field TP data and the spectral reflectance. In this study, we investigated the possibility of establishing a spatial modeling scheme to estimate the TP concentration of a large lake from multi-spectral satellite imagery using band combinations and regional multivariate statistical modeling techniques, and we tested the applicability of the spatial modeling scheme. The results showed that HJ-1A CCD multi-spectral satellite imagery can be used to estimate the TP concentration in a lake. The correlation and regression analysis showed a highly significant positive relationship between the TP concentration and certain remotely sensed combination variables. The proposed modeling scheme had a higher accuracy for the TP concentration estimation in the large lake compared with the traditional individual band ratio method and the whole-lake scale regression-modeling scheme. The TP concentration values showed a clear spatial variability and were high in western Lake Chaohu and relatively low in eastern Lake Chaohu. The northernmost portion, the northeastern coastal zone and the southeastern portion of western Lake Chaohu had the highest TP concentrations, and the other regions had the lowest TP concentration values, except for the coastal zone of eastern Lake Chaohu. These results strongly suggested that the proposed modeling scheme, i.e., the band combinations and the regional multivariate statistical modeling techniques, demonstrated advantages for estimating the TP concentration in a large lake and had a strong potential for universal application for the TP concentration estimation in large lake waters worldwide. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dry Particulate Nitrate Deposition in China.

PubMed

Liu, Lei; Zhang, Xiuying; Zhang, Yan; Xu, Wen; Liu, Xuejun; Zhang, Xiaomin; Feng, Junlan; Chen, Xinrui; Zhang, Yuehan; Lu, Xuehe; Wang, Shanqian; Zhang, Wuting; Zhao, Limin

2017-05-16

A limited number of ground measurements of dry particulate nitrate deposition (NO 3 - ) makes it difficult and challenging to fully know the status of the spatial and temporal variations of dry NO 3 - depositions over China. This study tries to expand the ground measurements of NO 3 - concentrations at monitoring sites to a national scale, based on the Ozone Monitoring Instrument (OMI) NO 2 columns, NO 2 profiles from an atmospheric chemistry transport model (Model for Ozone and Related chemical Tracers, version 4, MOZART-4) and monitor-based sources, and then estimates the NO 3 - depositions on a regional scale based on an inferred model. The ground NO 2 concentrations were first derived from NO 2 columns and the NO 2 profiles, and then the ground NO 3 - concentrations were derived from the ground NO 2 concentrations and the relationship between NO 2 and NO 3 - based on Chinese Nationwide Nitrogen Deposition Monitoring Network (NNDMN). This estimated dry NO 3 - depositions over China will be helpful in determining the magnitude and pollution status in regions without ground measurements, supporting the construction plan of environmental monitoring in future.

Nutrient Concentrations, Loads, and Yields in the Eucha-Spavinaw Basin, Arkansas and Oklahoma, 2002-2004

USGS Publications Warehouse

Tortorelli, Robert L.

2006-01-01

The City of Tulsa, Oklahoma, uses Lake Eucha and Spavinaw Lake in the Eucha-Spavinaw basin in northwestern Arkansas and northeastern Oklahoma for public water supply. Taste and odor problems in the water attributable to blue-green algae have increased in frequency over time. Changes in the algae community in the lakes may be attributable to increases in nutrient levels in the lakes, and in the waters feeding the lakes. The U.S. Geological Survey, in cooperation with the City of Tulsa, conducted an investigation to summarize nitrogen and phosphorus concentrations and provide estimates of nitrogen and phosphorus loads, yields, and flow-weighted concentrations in the Eucha-Spavinaw basin for a 3-year period from January 2002 through December 2004. This report provides information needed to advance knowledge of the regional hydrologic system and understanding of hydrologic processes, and provides hydrologic data and results useful to multiple parties for interstate compacts. Nitrogen and phosphorus concentrations were significantly greater in runoff samples than in base-flow samples at Spavinaw Creek near Maysville, Arkansas; Spavinaw Creek near Colcord, Oklahoma, and Beaty Creek near Jay, Oklahoma. Runoff concentrations were not significantly greater than in base-flow samples at Spavinaw Creek near Cherokee, Arkansas; and Spavinaw Creek near Sycamore, Oklahoma. Nitrogen concentrations in base-flow samples significantly increased in the downstream direction in Spavinaw Creek from the Maysville to Sycamore stations then significantly decreased from the Sycamore to the Colcord stations. Nitrogen in base-flow samples from Beaty Creek was significantly less than in those from Spavinaw Creek. Phosphorus concentrations in base-flow samples significantly increased from the Maysville to Cherokee stations in Spavinaw Creek, probably due to a point source between those stations, then significantly decreased downstream from the Cherokee to Colcord stations. Phosphorus in base-flow samples from Beaty Creek was significantly less than phosphorus in base-flow samples from Spavinaw Creek downstream from the Maysville station. Nitrogen concentrations in runoff samples were not significantly different among the stations on Spavinaw Creek; however, the concentrations at Beaty Creek were significantly less than at all other stations. Phosphorus concentrations in runoff samples were not significantly different among the three downstream stations on Spavinaw Creek, and not significantly different at the Maysville station on Spavinaw Creek and the Beaty Creek station. Phosphorus and nitrogen concentrations in runoff samples from all stations generally increased with increasing streamflow. Estimated mean annual nitrogen total loads from 2002-2004 were substantially greater at the Spavinaw Creek stations than at Beaty Creek and increased in a downstream direction from Maysville to Colcord in Spavinaw Creek, with the load at the Colcord station about 2 times that of Maysville station. Estimated mean annual nitrogen base-flow loads at the Spavinaw Creek stations were about 5 to 11 times greater than base-flow loads at Beaty Creek. The runoff component of the annual nitrogen total load for Beaty Creek was 85 percent, whereas, at the Spavinaw Creek stations, the range in the runoff component was 60 to 66 percent. Estimated mean annual phosphorus total loads from 2002-2004 were greater at the Spavinaw Creek stations from Cherokee to Colcord than at Beaty Creek and increased in a downstream direction from Maysville to Colcord in Spavinaw Creek, with the load at the Colcord station about 2.5 times that of Maysville station. Estimated mean annual phosphorus base-flow loads at the Spavinaw Creek stations were about 2.5 to 19 times greater than at Beaty Creek. Phosphorus base-flow loads increased about 8 times from Maysville to Cherokee in Spavinaw Creek; the base-flow loads were about the same at the three downstream stations. The runoff component

40 CFR 98.295 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... value shall be the best available estimate(s) of the parameter(s), based on all available process data or data used for accounting purposes. (c) For each missing value collected during the performance test (hourly CO2 concentration, stack gas volumetric flow rate, or average process vent flow from mine...

A tissue dose-based comparative exposure assessment of manganese using physiologically based pharmacokinetic modeling—The importance of homeostatic control for an essential metal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gentry, P. Robinan, E-mail: rgentry@ramboll.com

A physiologically-based pharmacokinetic (PBPK) model (Schroeter et al., 2011) was applied to simulate target tissue manganese (Mn) concentrations following occupational and environmental exposures. These estimates of target tissue Mn concentrations were compared to determine margins of safety (MOS) and to evaluate the biological relevance of applying safety factors to derive acceptable Mn air concentrations. Mn blood concentrations measured in occupational studies permitted verification of the human PBPK models, increasing confidence in the resulting estimates. Mn exposure was determined based on measured ambient air Mn concentrations and dietary data in Canada and the United States (US). Incorporating dietary and inhalation exposuresmore » into the models indicated that increases in target tissue concentrations above endogenous levels only begin to occur when humans are exposed to levels of Mn in ambient air (i.e. > 10 μg/m{sup 3}) that are far higher than those currently measured in Canada or the US. A MOS greater than three orders of magnitude was observed, indicating that current Mn air concentrations are far below concentrations that would be required to produce the target tissue Mn concentrations associated with subclinical neurological effects. This application of PBPK modeling for an essential element clearly demonstrates that the conventional application of default factors to “convert” an occupational exposure to an equivalent continuous environmental exposure, followed by the application of safety factors, is not appropriate in the case of Mn. PBPK modeling demonstrates that the relationship between ambient Mn exposures and dose-to-target tissue is not linear due to normal tissue background levels and homeostatic controls. - Highlights: • Manganese is an essential nutrient, adding complexity to its risk assessment. • Nonlinearities in biological processes are important for manganese risk assessment. • A PBPK model was used to estimate target tissue concentrations of manganese. • An MOS approach also considered target tissue concentrations for ambient exposures. • Relationships between ambient Mn exposures and dose-to-target tissue are not linear.« less

A method to estimate spatiotemporal air quality in an urban traffic corridor.

PubMed

Singh, Nongthombam Premananda; Gokhale, Sharad

2015-12-15

Air quality exposure assessment using personal exposure sampling or direct measurement of spatiotemporal air pollutant concentrations has difficulty and limitations. Most statistical methods used for estimating spatiotemporal air quality do not account for the source characteristics (e.g. emissions). In this study, a prediction method, based on the lognormal probability distribution of hourly-average-spatial concentrations of carbon monoxide (CO) obtained by a CALINE4 model, has been developed and validated in an urban traffic corridor. The data on CO concentrations were collected at three locations and traffic and meteorology within the urban traffic corridor.(1) The method has been developed with the data of one location and validated at other two locations. The method estimated the CO concentrations reasonably well (correlation coefficient, r≥0.96). Later, the method has been applied to estimate the probability of occurrence [P(C≥Cstd] of the spatial CO concentrations in the corridor. The results have been promising and, therefore, may be useful to quantifying spatiotemporal air quality within an urban area. Copyright © 2015 Elsevier B.V. All rights reserved.

A test of the ADV-based Reynolds flux method for in situ estimation of sediment settling velocity in a muddy estuary

NASA Astrophysics Data System (ADS)

Cartwright, Grace M.; Friedrichs, Carl T.; Smith, S. Jarrell

2013-12-01

Under conditions common in muddy coastal and estuarine environments, acoustic Doppler velocimeters (ADVs) can serve to estimate sediment settling velocity ( w s) by assuming a balance between upward turbulent Reynolds flux and downward gravitational settling. Advantages of this method include simple instrument deployment, lack of flow disturbance, and relative insensitivity to biofouling and water column stratification. Although this method is being used with increasing frequency in coastal and estuarine environments, to date it has received little direct ground truthing. This study compared in situ estimates of w s inferred by a 5-MHz ADV to independent in situ observations from a high-definition video settling column over the course of a flood tide in the bottom boundary layer of the York River estuary, Virginia, USA. The ADV-based measurements were found to agree with those of the settling column when the current speed at about 40 cm above the bed was greater than about 20 cm/s. This corresponded to periods when the estimated magnitude of the settling term in the suspended sediment continuity equation was four or more times larger than the time rate of change of concentration. For ADV observations restricted to these conditions, ADV-based estimates of w s (mean 0.48±0.04 mm/s) were highly consistent with those observed by the settling column (mean 0.45±0.02 mm/s). However, the ADV-based method for estimating w s was sensitive to the prescribed concentration of the non-settling washload, C wash. In an objective operational definition, C wash can be set equal to the lowest suspended solids concentration observed around slack water.

Characterization of background concentrations of contaminants using a mixture of normal distributions.

PubMed

Qian, Song S; Lyons, Regan E

2006-10-01

We present a Bayesian approach for characterizing background contaminant concentration distributions using data from sites that may have been contaminated. Our method, focused on estimation, resolves several technical problems of the existing methods sanctioned by the U.S. Environmental Protection Agency (USEPA) (a hypothesis testing based method), resulting in a simple and quick procedure for estimating background contaminant concentrations. The proposed Bayesian method is applied to two data sets from a federal facility regulated under the Resource Conservation and Restoration Act. The results are compared to background distributions identified using existing methods recommended by the USEPA. The two data sets represent low and moderate levels of censorship in the data. Although an unbiased estimator is elusive, we show that the proposed Bayesian estimation method will have a smaller bias than the EPA recommended method.

A robust vision-based sensor fusion approach for real-time pose estimation.

PubMed

Assa, Akbar; Janabi-Sharifi, Farrokh

2014-02-01

Object pose estimation is of great importance to many applications, such as augmented reality, localization and mapping, motion capture, and visual servoing. Although many approaches based on a monocular camera have been proposed, only a few works have concentrated on applying multicamera sensor fusion techniques to pose estimation. Higher accuracy and enhanced robustness toward sensor defects or failures are some of the advantages of these schemes. This paper presents a new Kalman-based sensor fusion approach for pose estimation that offers higher accuracy and precision, and is robust to camera motion and image occlusion, compared to its predecessors. Extensive experiments are conducted to validate the superiority of this fusion method over currently employed vision-based pose estimation algorithms.

Semi-quantitative estimation by IR of framework, extraframework and defect Al species of HBEA zeolites.

PubMed

Marques, João P; Gener, Isabelle; Ayrault, Philippe; Lopes, José M; Ribeiro, F Ramôa; Guisnet, Michel

2004-10-21

A simple method based on the characterization (composition, Bronsted and Lewis acidities) of acid treated HBEA zeolites was developed for estimating the concentrations of framework, extraframework and defect Al species.

Improved prediction of tacrolimus concentrations early after kidney transplantation using theory-based pharmacokinetic modelling.

PubMed

Størset, Elisabet; Holford, Nick; Hennig, Stefanie; Bergmann, Troels K; Bergan, Stein; Bremer, Sara; Åsberg, Anders; Midtvedt, Karsten; Staatz, Christine E

2014-09-01

The aim was to develop a theory-based population pharmacokinetic model of tacrolimus in adult kidney transplant recipients and to externally evaluate this model and two previous empirical models. Data were obtained from 242 patients with 3100 tacrolimus whole blood concentrations. External evaluation was performed by examining model predictive performance using Bayesian forecasting. Pharmacokinetic disposition parameters were estimated based on tacrolimus plasma concentrations, predicted from whole blood concentrations, haematocrit and literature values for tacrolimus binding to red blood cells. Disposition parameters were allometrically scaled to fat free mass. Tacrolimus whole blood clearance/bioavailability standardized to haematocrit of 45% and fat free mass of 60 kg was estimated to be 16.1 l h−1 [95% CI 12.6, 18.0 l h−1]. Tacrolimus clearance was 30% higher (95% CI 13, 46%) and bioavailability 18% lower (95% CI 2, 29%) in CYP3A5 expressers compared with non-expressers. An Emax model described decreasing tacrolimus bioavailability with increasing prednisolone dose. The theory-based model was superior to the empirical models during external evaluation displaying a median prediction error of −1.2% (95% CI −3.0, 0.1%). Based on simulation, Bayesian forecasting led to 65% (95% CI 62, 68%) of patients achieving a tacrolimus average steady-state concentration within a suggested acceptable range. A theory-based population pharmacokinetic model was superior to two empirical models for prediction of tacrolimus concentrations and seemed suitable for Bayesian prediction of tacrolimus doses early after kidney transplantation.

Resistant starch intakes in the United States.

PubMed

Murphy, Mary M; Douglass, Judith Spungen; Birkett, Anne

2008-01-01

Dietary fiber represents a broad class of undigested carbohydrate components. The components vary in chemical and physical nature and in their physiological outcomes. Resistant starch is starch that escapes digestion in the small intestine and that may be fermented in the large intestine. The purpose of this study was to estimate consumption of resistant starch by the US population and to identify key sources of dietary resistant starch. A database of resistant starch concentrations in foods was developed from the publicly available literature. These concentrations were linked to foods reported in 24-hour dietary recalls from participants in the 1999-2002 National Health and Nutrition Examination Surveys and estimates of resistant starch intakes were generated. The study population included 18,305 nonbreastfeeding individuals in the United States. The dietary intake of resistant starch was determined for 10 US subpopulations defined by age, sex, and race/ethnicity. Three estimates of resistant starch intake were made for each person based on the minimum, mean, and maximum concentrations of resistant starch in the foods consumed. Americans aged 1 year and older were estimated to consume approximately 4.9 g resistant starch per day based on mean resistant starch concentrations (range 2.8 to 7.9 g resistant starch per day). Breads, cooked cereals/pastas, and vegetables (other than legumes) contributed 21%, 19%, and 19% of total resistant starch intake, respectively, and were top sources of resistant starch. Findings from this study suggest that the estimated intake of resistant starch by Americans is approximately 3 to 8 g per person per day. These estimates of resistant starch intake provide a valuable reference for researchers and food and nutrition professionals and will allow for more accurate estimates of total intakes of carbohydrate compounds that escape digestion in the small intestine.

Assessment of questionnaire-based PCB exposure focused on food frequency in birth cohorts in Japan.

PubMed

Eguchi, Akifumi; Otake, Masae; Hanazato, Masamichi; Suzuki, Norimichi; Matsuno, Yoshiharu; Nakaoka, Hiroko; Todaka, Emiko; Mori, Chisato

2017-02-01

We investigated the relationship between food frequency questionnaire (FFQ) responses and serum polychlorinated biphenyl (PCB) levels of mothers and fathers recruited from the Chiba Regional Center, which is one of the 15 regional centers of the Japan Environment and Children's Study (mothers: n = 1477, fathers: n = 219). The expected PCB values were estimated from the participants' FFQ answers and medical records (age, body mass index and number of deliveries). Based on the stepwise forward selection results of Bayesian regression models, age and fish and egg consumption were positively associated with PCB concentrations and a number of deliveries were negatively associated with PCB concentrations in mothers, whereas only age was positively associated with PCB concentrations in fathers.These findings indicated that the estimation of daily dietary intake may be useful for the prediction of PCB concentration for mothers.

First experiences with methods to measure ammonia emissions from naturally ventilated cattle buildings in the U.K.

NASA Astrophysics Data System (ADS)

Demmers, T. G. M.; Burgess, L. R.; Short, J. L.; Phillips, V. R.; Clark, J. A.; Wathes, C. M.

A method has been developed to measure the emission rate of ammonia from naturally ventilated U.K. livestock buildings. The method is based on measurements of ammonia concentration and estimates of the ventilation rate of the building by continuous release of carbon monoxide tracer within the building. The tracer concentration is measured at nine positions in openings around the perimeter of the building, as well as around a ring sampling line. Two criteria were evaluated to decide whether, at any given time, a given opening in the building acted as an air inlet or as an air outlet. Carbon monoxide concentration difference across an opening was found to be a better criterion than the temperature difference across the opening. Ammonia concentrations were measured continuously at the sampling points using a chemiluminescence analyser. The method was applied to a straw-bedded beef unit and to a slurry-based dairy unit. Both buildings were of space-boarded construction. Ventilation rates estimated by the ring line sample were consistently higher than by the perimeter samples. During calm weather, the ventilation estimates by both samples were similar (10-20 air changes h -1). However, during windy conditions (>5 m s -1) the ventilation rate was overestimated by the ring line sample (average 100 air changes h -1) compared to the perimeter samples (average 50 air changes h -1). The difference was caused by incomplete mixing of the tracer within the building. The ventilation rate estimated from the perimeter samples was used for the calculation of the emission rate. Preliminary estimates of the ammonia emission factor were 6.0 kg NH 3 (500 kg live-weight) -1 (190 d) -1 for the slurry-based dairy unit and 3.7 for the straw-bedded beef unit.

An assessment of the suspended sediment rating curve approach for load estimation on the Rivers Bandon and Owenabue, Ireland

NASA Astrophysics Data System (ADS)

Harrington, Seán T.; Harrington, Joseph R.

2013-03-01

This paper presents an assessment of the suspended sediment rating curve approach for load estimation on the Rivers Bandon and Owenabue in Ireland. The rivers, located in the South of Ireland, are underlain by sandstone, limestones and mudstones, and the catchments are primarily agricultural. A comprehensive database of suspended sediment data is not available for rivers in Ireland. For such situations, it is common to estimate suspended sediment concentrations from the flow rate using the suspended sediment rating curve approach. These rating curves are most commonly constructed by applying linear regression to the logarithms of flow and suspended sediment concentration or by applying a power curve to normal data. Both methods are assessed in this paper for the Rivers Bandon and Owenabue. Turbidity-based suspended sediment loads are presented for each river based on continuous (15 min) flow data and the use of turbidity as a surrogate for suspended sediment concentration is investigated. A database of paired flow rate and suspended sediment concentration values, collected between the years 2004 and 2011, is used to generate rating curves for each river. From these, suspended sediment load estimates using the rating curve approach are estimated and compared to the turbidity based loads for each river. Loads are also estimated using stage and seasonally separated rating curves and daily flow data, for comparison purposes. The most accurate load estimate on the River Bandon is found using a stage separated power curve, while the most accurate load estimate on the River Owenabue is found using a general power curve. Maximum full monthly errors of - 76% to + 63% are found on the River Bandon with errors of - 65% to + 359% found on the River Owenabue. The average monthly error on the River Bandon is - 12% with an average error of + 87% on the River Owenabue. The use of daily flow data in the load estimation process does not result in a significant loss of accuracy on either river. Historic load estimates (with a 95% confidence interval) were hindcast from the flow record and average annual loads of 7253 ± 673 tonnes on the River Bandon and 1935 ± 325 tonnes on the River Owenabue were estimated to be passing the gauging stations.

A simple optical model to estimate suspended particulate matter in Yellow River Estuary.

PubMed

Qiu, Zhongfeng

2013-11-18

Distribution of the suspended particulate matter (SPM) concentration is a key issue for analyzing the deposition and erosion variety of the estuary and evaluating the material fluxes from river to sea. Satellite remote sensing is a useful tool to investigate the spatial variation of SPM concentration in estuarial zones. However, algorithm developments and validations of the SPM concentrations in Yellow River Estuary (YRE) have been seldom performed before and therefore our knowledge on the quality of retrieval of SPM concentration is poor. In this study, we developed a new simple optical model to estimate SPM concentration in YRE by specifying the optimal wavelength ratios (600-710 nm)/ (530-590 nm) based on observations of 5 cruises during 2004 and 2011. The simple optical model was attentively calibrated and the optimal band ratios were selected for application to multiple sensors, 678/551 for the Moderate Resolution Imaging Spectroradiometer (MODIS), 705/560 for the Medium Resolution Imaging Spectrometer (MERIS) and 680/555 for the Geostationary Ocean Color Imager (GOCI). With the simple optical model, the relative percentage difference and the mean absolute error were 35.4% and 15.6 gm(-3) respectively for MODIS, 42.2% and 16.3 gm(-3) for MERIS, and 34.2% and 14.7 gm(-3) for GOCI, based on an independent validation data set. Our results showed a good precision of estimation for SPM concentration using the new simple optical model, contrasting with the poor estimations derived from existing empirical models. Providing an available atmospheric correction scheme for satellite imagery, our simple model could be used for quantitative monitoring of SPM concentrations in YRE.

[Estimation of average traffic emission factor based on synchronized incremental traffic flow and air pollutant concentration].

PubMed

Li, Run-Kui; Zhao, Tong; Li, Zhi-Peng; Ding, Wen-Jun; Cui, Xiao-Yong; Xu, Qun; Song, Xian-Feng

2014-04-01

On-road vehicle emissions have become the main source of urban air pollution and attracted broad attentions. Vehicle emission factor is a basic parameter to reflect the status of vehicle emissions, but the measured emission factor is difficult to obtain, and the simulated emission factor is not localized in China. Based on the synchronized increments of traffic flow and concentration of air pollutants in the morning rush hour period, while meteorological condition and background air pollution concentration retain relatively stable, the relationship between the increase of traffic and the increase of air pollution concentration close to a road is established. Infinite line source Gaussian dispersion model was transformed for the inversion of average vehicle emission factors. A case study was conducted on a main road in Beijing. Traffic flow, meteorological data and carbon monoxide (CO) concentration were collected to estimate average vehicle emission factors of CO. The results were compared with simulated emission factors of COPERT4 model. Results showed that the average emission factors estimated by the proposed approach and COPERT4 in August were 2.0 g x km(-1) and 1.2 g x km(-1), respectively, and in December were 5.5 g x km(-1) and 5.2 g x km(-1), respectively. The emission factors from the proposed approach and COPERT4 showed close values and similar seasonal trends. The proposed method for average emission factor estimation eliminates the disturbance of background concentrations and potentially provides real-time access to vehicle fleet emission factors.

Transport, biodegradation and isotopic fractionation of chlorinated ethenes: modeling and parameter estimation methods

NASA Astrophysics Data System (ADS)

Béranger, Sandra C.; Sleep, Brent E.; Lollar, Barbara Sherwood; Monteagudo, Fernando Perez

2005-01-01

An analytical, one-dimensional, multi-species, reactive transport model for simulating the concentrations and isotopic signatures of tetrachloroethylene (PCE) and its daughter products was developed. The simulation model was coupled to a genetic algorithm (GA) combined with a gradient-based (GB) method to estimate the first order decay coefficients and enrichment factors. In testing with synthetic data, the hybrid GA-GB method reduced the computational requirements for parameter estimation by a factor as great as 300. The isotopic signature profiles were observed to be more sensitive than the concentration profiles to estimates of both the first order decay constants and enrichment factors. Including isotopic data for parameter estimation significantly increased the GA convergence rate and slightly improved the accuracy of estimation of first order decay constants.

Development of a population pharmacokinetic model for carbamazepine based on sparse therapeutic monitoring data from pediatric patients with epilepsy.

PubMed

Carlsson, Kristin Cecilie; Hoem, Nils Ove; Glauser, Tracy; Vinks, Alexander A

2005-05-01

Population models can be important extensions of therapeutic drug monitoring (TDM), as they allow estimation of individual pharmacokinetic parameters based on a small number of measured drug concentrations. This study used a Bayesian approach to explore the utility of routinely collected and sparse TDM data (1 sample per patient) for carbamazepine (CBZ) monotherapy in developing a population pharmacokinetic (PPK) model for CBZ in pediatric patients that would allow prediction of CBZ concentrations for both immediate- and controlled-release formulations. Patient and TDM data were obtained from a pediatric neurology outpatient database. Data were analyzed using an iterative 2-stage Bayesian algorithm and a nonparametric adaptive grid algorithm. Models were compared by final log likelihood, mean error (ME) as a measure of bias, and root mean squared error (RMSE) as a measure of precision. Fifty-seven entries with data on CBZ monotherapy were identified from the database and used in the analysis (36 from males, 21 from females; mean [SD] age, 9.1 [4.4] years [range, 2-21 years]). Preliminary models estimating clearance (Cl) or the elimination rate constant (K(el)) gave good prediction of serum concentrations compared with measured serum concentrations, but estimates of Cl and K(el) were highly correlated with estimates of volume of distribution (V(d)). Different covariate models were then tested. The selected model had zero-order input and had age and body weight as covariates. Cl (L/h) was calculated as K(el) . V(d), where K(el) = [K(i) - (K(s) . age)] and V(d) = [V(i) + (V(s) . body weight)]. Median parameter estimates were V(i) (intercept) = 11.5 L (fixed); V(s) (slope) = 0.3957 L/kg (range, 0.01200-1.5730); K(i) (intercept) = 0.173 h(-1) (fixed); and K(s) (slope) = 0.004487 h(-1) . y(-1) (range, 0.0001800-0.02969). The fit was good for estimates of steady-state serum concentrations based on prior values (population median estimates) (R = 0.468; R(2) = 0.219) but was even better for predictions based on individual Bayesian posterior values (R(2) = 0.991), with little bias (ME = -0.079) and good precision (RMSE = 0.055). Based on the findings of this study, sparse TDM data can be used for PPK modeling of CBZ clearance in children with epilepsy, and these models can be used to predict Cl at steady state in pediatric patients. However, to estimate additional pharmacokinetic model parameters (eg, the absorption rate constant and V(d)), it would be necessary to combine sparse TDM data with additional well-timed samples. This would allow development of more informative PPK models that could be used as part of Bayesian dose-individualization strategies.

A particle filter for ammonia coverage ratio and input simultaneous estimations in Diesel-engine SCR system.

PubMed

Sun, Kangfeng; Ji, Fenzhu; Yan, Xiaoyu; Jiang, Kai; Yang, Shichun

2018-01-01

As NOx emissions legislation for Diesel-engines is becoming more stringent than ever before, an aftertreatment system has been widely used in many countries. Specifically, to reduce the NOx emissions, a selective catalytic reduction(SCR) system has become one of the most promising techniques for Diesel-engine vehicle applications. In the SCR system, input ammonia concentration and ammonia coverage ratio are regarded as essential states in the control-oriental model. Currently, an ammonia sensor placed before the SCR Can is a good strategy for the input ammonia concentration value. However, physical sensor would increase the SCR system cost and the ammonia coverage ratio information cannot be directly measured by physical sensor. Aiming to tackle this problem, an observer based on particle filter(PF) is investigated to estimate the input ammonia concentration and ammonia coverage ratio. Simulation results through the experimentally-validated full vehicle simulator cX-Emission show that the performance of observer based on PF is outstanding, and the estimation error is very small.

A particle filter for ammonia coverage ratio and input simultaneous estimations in Diesel-engine SCR system

PubMed Central

Ji, Fenzhu; Yan, Xiaoyu; Jiang, Kai

2018-01-01

As NOx emissions legislation for Diesel-engines is becoming more stringent than ever before, an aftertreatment system has been widely used in many countries. Specifically, to reduce the NOx emissions, a selective catalytic reduction(SCR) system has become one of the most promising techniques for Diesel-engine vehicle applications. In the SCR system, input ammonia concentration and ammonia coverage ratio are regarded as essential states in the control-oriental model. Currently, an ammonia sensor placed before the SCR Can is a good strategy for the input ammonia concentration value. However, physical sensor would increase the SCR system cost and the ammonia coverage ratio information cannot be directly measured by physical sensor. Aiming to tackle this problem, an observer based on particle filter(PF) is investigated to estimate the input ammonia concentration and ammonia coverage ratio. Simulation results through the experimentally-validated full vehicle simulator cX-Emission show that the performance of observer based on PF is outstanding, and the estimation error is very small. PMID:29408924

Soft sensor for monitoring biomass subpopulations in mammalian cell culture processes.

PubMed

Kroll, Paul; Stelzer, Ines V; Herwig, Christoph

2017-11-01

Biomass subpopulations in mammalian cell culture processes cause impurities and influence productivity, which requires this critical process parameter to be monitored in real-time. For this reason, a novel soft sensor concept for estimating viable, dead and lysed cell concentration was developed, based on the robust and cheap in situ measurements of permittivity and turbidity in combination with a simple model. It could be shown that the turbidity measurements contain information about all investigated biomass subpopulations. The novelty of the developed soft sensor is the real-time estimation of lysed cell concentration, which is directly correlated to process-related impurities such as DNA and host cell protein in the supernatant. Based on data generated by two fed-batch processes the developed soft sensor is described and discussed. The presented soft sensor concept provides a tool for viable, dead and lysed cell concentration estimation in real-time with adequate accuracy and enables further applications with respect to process optimization and control.

Design and application of an inertial impactor in combination with an ATP bioluminescence detector for in situ rapid estimation of the efficacies of air controlling devices on removal of bioaerosols.

PubMed

Yoon, Ki Young; Park, Chul Woo; Byeon, Jeong Hoon; Hwang, Jungho

2010-03-01

We proposed a rapid method to estimate the efficacies of air controlling devices in situ using ATP bioluminescence in combination with an inertial impactor. The inertial impactor was designed to have 1 mum of cutoff diameter, and its performance was estimated analytically, numerically, and experimentally. The proposed method was characterized using Staphylococcus epidermidis, which was aerosolized with a nebulizer. The bioaerosol concentrations were estimated within 25 min using the proposed method without a culturing process, which requires several days for colony formation. A linear relationship was obtained between the results of the proposed ATP method (RLU/m(3)) and the conventional culture-based method (CFU/m(3)), with R(2) 0.9283. The proposed method was applied to estimate the concentration of indoor bioaerosols, which were identified as a mixture of various microbial species including bacteria, fungi, and actinomycetes, in an occupational indoor environment, controlled by mechanical ventilation and an air cleaner. Consequently, the proposed method showed a linearity with the culture-based method for indoor bioaerosols with R(2) 0.8189, even though various kinds of microorganisms existed in the indoor air. The proposed method may be effective in monitoring the changes of relative concentration of indoor bioaerosols and estimating the effectiveness of air control devices in indoor environments.

Application of geostatistics to risk assessment.

PubMed

Thayer, William C; Griffith, Daniel A; Goodrum, Philip E; Diamond, Gary L; Hassett, James M

2003-10-01

Geostatistics offers two fundamental contributions to environmental contaminant exposure assessment: (1) a group of methods to quantitatively describe the spatial distribution of a pollutant and (2) the ability to improve estimates of the exposure point concentration by exploiting the geospatial information present in the data. The second contribution is particularly valuable when exposure estimates must be derived from small data sets, which is often the case in environmental risk assessment. This article addresses two topics related to the use of geostatistics in human and ecological risk assessments performed at hazardous waste sites: (1) the importance of assessing model assumptions when using geostatistics and (2) the use of geostatistics to improve estimates of the exposure point concentration (EPC) in the limited data scenario. The latter topic is approached here by comparing design-based estimators that are familiar to environmental risk assessors (e.g., Land's method) with geostatistics, a model-based estimator. In this report, we summarize the basics of spatial weighting of sample data, kriging, and geostatistical simulation. We then explore the two topics identified above in a case study, using soil lead concentration data from a Superfund site (a skeet and trap range). We also describe several areas where research is needed to advance the use of geostatistics in environmental risk assessment.

Turbidity-controlled suspended sediment sampling for runoff-event load estimation

Treesearch

Jack Lewis

1996-01-01

Abstract - For estimating suspended sediment concentration (SSC) in rivers, turbidity is generally a much better predictor than water discharge. Although it is now possible to collect continuous turbidity data even at remote sites, sediment sampling and load estimation are still conventionally based on discharge. With frequent calibration the relation of turbidity to...

Estimating the atmospheric concentration of Criegee intermediates and their possible interference in a FAGE-LIF instrument

NASA Astrophysics Data System (ADS)

Novelli, Anna; Hens, Korbinian; Tatum Ernest, Cheryl; Martinez, Monica; Nölscher, Anke C.; Sinha, Vinayak; Paasonen, Pauli; Petäjä, Tuukka; Sipilä, Mikko; Elste, Thomas; Plass-Dülmer, Christian; Phillips, Gavin J.; Kubistin, Dagmar; Williams, Jonathan; Vereecken, Luc; Lelieveld, Jos; Harder, Hartwig

2017-06-01

We analysed the extensive dataset from the HUMPPA-COPEC 2010 and the HOPE 2012 field campaigns in the boreal forest and rural environments of Finland and Germany, respectively, and estimated the abundance of stabilised Criegee intermediates (SCIs) in the lower troposphere. Based on laboratory tests, we propose that the background OH signal observed in our IPI-LIF-FAGE instrument during the aforementioned campaigns is caused at least partially by SCIs. This hypothesis is based on observed correlations with temperature and with concentrations of unsaturated volatile organic compounds and ozone. Just like SCIs, the background OH concentration can be removed through the addition of sulfur dioxide. SCIs also add to the previously underestimated production rate of sulfuric acid. An average estimate of the SCI concentration of ˜ 5.0 × 104 molecules cm-3 (with an order of magnitude uncertainty) is calculated for the two environments. This implies a very low ambient concentration of SCIs, though, over the boreal forest, significant for the conversion of SO2 into H2SO4. The large uncertainties in these calculations, owing to the many unknowns in the chemistry of Criegee intermediates, emphasise the need to better understand these processes and their potential effect on the self-cleaning capacity of the atmosphere.

Magnetic Susceptibility as a B0 Field Strength Independent MRI Biomarker of Liver Iron Overload

PubMed Central

Hernando, Diego; Cook, Rachel J.; Diamond, Carol; Reeder, Scott B.

2013-01-01

Purpose MR-based quantification of liver magnetic susceptibility may enable field strength-independent measurement of liver iron concentration (LIC). However, susceptibility quantification is challenging, due to non-local effects of susceptibility on the B0 field. The purpose of this work is to demonstrate feasibility of susceptibility-based LIC quantification using a fat-referenced approach. Methods Phantoms consisting of vials with increasing iron concentrations immersed between oil/water layers, and twenty-seven subjects (9 controls/18 subjects with liver iron overload) were scanned. Ferriscan (1.5T) provided R2-based reference LIC. Multi-echo 3D-SPGR (1.5T/3T) enabled fat-water, B0- and R2*-mapping. Phantom iron concentration (mg Fe/l) was estimated from B0 differences (ΔB0) between vials and neighboring oil. Liver susceptibility and LIC (mg Fe/g dry tissue) was estimated from ΔB0 between the lateral right lobe of the liver and adjacent subcutaneous adipose tissue (SAT). Results Estimated phantom iron concentrations had good correlation with true iron concentrations (1.5T:slope=0.86, intercept=0.72, r2=0.98; 3T:slope=0.85, intercept=1.73, r2=0.98). In liver, ΔB0 correlated strongly with R2* (1.5T:r2=0.86; 3T:r2=0.93) and B0-LIC had good agreement with Ferriscan-LIC (slopes/intercepts nearly 1.0/0.0, 1.5T:r2=0.67, slope=0.93±0.13, p≈0.50, intercept=1.93±0.78, p≈0.02; 3T:r2=0.84, slope=1.01±0.09, p≈0.90, intercept=0.23±0.52, p≈0.68). Discussion Fat-referenced, susceptibility-based LIC estimation is feasible at both field strengths. This approach may enable improved susceptibility mapping in the abdomen. PMID:23801540

Nonparametric estimation of groundwater residence time distributions: What can environmental tracer data tell us about groundwater residence time?

NASA Astrophysics Data System (ADS)

McCallum, James L.; Engdahl, Nicholas B.; Ginn, Timothy R.; Cook, Peter. G.

2014-03-01

Residence time distributions (RTDs) have been used extensively for quantifying flow and transport in subsurface hydrology. In geochemical approaches, environmental tracer concentrations are used in conjunction with simple lumped parameter models (LPMs). Conversely, numerical simulation techniques require large amounts of parameterization and estimated RTDs are certainly limited by associated uncertainties. In this study, we apply a nonparametric deconvolution approach to estimate RTDs using environmental tracer concentrations. The model is based only on the assumption that flow is steady enough that the observed concentrations are well approximated by linear superposition of the input concentrations with the RTD; that is, the convolution integral holds. Even with large amounts of environmental tracer concentration data, the entire shape of an RTD remains highly nonunique. However, accurate estimates of mean ages and in some cases prediction of young portions of the RTD may be possible. The most useful type of data was found to be the use of a time series of tritium. This was due to the sharp variations in atmospheric concentrations and a short half-life. Conversely, the use of CFC compounds with smoothly varying atmospheric concentrations was more prone to nonuniqueness. This work highlights the benefits and limitations of using environmental tracer data to estimate whole RTDs with either LPMs or through numerical simulation. However, the ability of the nonparametric approach developed here to correct for mixing biases in mean ages appears promising.

Burden of disease attributed to ambient air pollution in Thailand: A GIS-based approach.

PubMed

Pinichka, Chayut; Makka, Nuttapat; Sukkumnoed, Decharut; Chariyalertsak, Suwat; Inchai, Puchong; Bundhamcharoen, Kanitta

2017-01-01

Growing urbanisation and population requiring enhanced electricity generation as well as the increasing numbers of fossil fuel in Thailand pose important challenges to air quality management which impacts on the health of the population. Mortality attributed to ambient air pollution is one of the sustainable development goals (SDGs). We estimated the spatial pattern of mortality burden attributable to selected ambient air pollution in 2009 based on the empirical evidence in Thailand. We estimated the burden of disease attributable to ambient air pollution based on the comparative risk assessment (CRA) framework developed by the World Health Organization (WHO) and the Global Burden of Disease study (GBD). We integrated geographical information systems (GIS)-based exposure assessments into spatial interpolation models to estimate ambient air pollutant concentrations, the population distribution of exposure and the concentration-response (CR) relationship to quantify ambient air pollution exposure and associated mortality. We obtained air quality data from the Pollution Control Department (PCD) of Thailand surface air pollution monitoring network sources and estimated the CR relationship between relative risk (RR) and concentration of air pollutants from the epidemiological literature. We estimated 650-38,410 ambient air pollution-related fatalities and 160-5,982 fatalities that could have been avoided with a 20 reduction in ambient air pollutant concentrations. The summation of population-attributable fraction (PAF) of the disease burden for all-causes mortality in adults due to NO2 and PM2.5 were the highest among all air pollutants at 10% and 7.5%, respectively. The PAF summation of PM2.5 for lung cancer and cardiovascular disease were 16.8% and 14.6% respectively and the PAF summations of mortality attributable to PM10 was 3.4% for all-causes mortality, 1.7% for respiratory and 3.8% for cardiovascular mortality, while the PAF summation of mortality attributable to NO2 was 7.8% for respiratory mortality in Thailand. Mortality due to ambient air pollution in Thailand varies across the country. Geographical distribution estimates can identify high exposure areas for planners and policy-makers. Our results suggest that the benefits of a 20% reduction in ambient air pollution concentration could prevent up to 25% of avoidable fatalities each year in all-causes, respiratory and cardiovascular categories. Furthermore, our findings can provide guidelines for future epidemiological investigations and policy decisions to achieve the SDGs.

Computer simulation comparison of tripolar, bipolar, and spline Laplacian electrocadiogram estimators.

PubMed

Chen, T; Besio, W; Dai, W

2009-01-01

A comparison of the performance of the tripolar and bipolar concentric as well as spline Laplacian electrocardiograms (LECGs) and body surface Laplacian mappings (BSLMs) for localizing and imaging the cardiac electrical activation has been investigated based on computer simulation. In the simulation a simplified eccentric heart-torso sphere-cylinder homogeneous volume conductor model were developed. Multiple dipoles with different orientations were used to simulate the underlying cardiac electrical activities. Results show that the tripolar concentric ring electrodes produce the most accurate LECG and BSLM estimation among the three estimators with the best performance in spatial resolution.

Prediction of digestibility and energy concentration of winter pasture forage and herbage of low-input grassland--a comparison of methods.

PubMed

Opitz v Boberfeld, W; Theobald, P C; Laser, H

2003-06-01

Regarding the estimation of the energy concentration or digestibility of herb-dominated forage and plant samples from winter pastures, it could be expected that the estimation is only reliable when in vitro methods with rumen fluid as inoculum (= gas production techniques) are used. For the verification of this thesis based on logical reflections, an in vitro-method with rumen fluid added as inoculum, as well as chemical, and enzymatic methods were applied under consideration of existing estimating functions. As a possible reason for the observed divergence of the methods, effects of fungal infections or, respectively, secondary compounds in herbs are discussed. At the present state of knowledge, it is adequate to estimate the energy concentration in vitro by gas tests, as far as fattening types like suckler cows and beef cattle are concerned, maybe in contrast to the forage evaluation for dairy cows.

Streptomycin interference in Jaffe reaction - possible false positive creatinine estimation in excessive dose exposure.

PubMed

Syal, Kirtimaan; Srinivasan, Anand; Banerjee, Dibyajyoti

2013-01-01

To study the potential of commonly used aminoglycoside antibiotics to form non-creatinine chromogen with alkaline picrate reagent. We studied the non-creatinine chromogen formation of various concentrations of streptomycin, amikacin, kanamycin, netilmicin, gentamicin and tobramycin added to known creatinine concentrations by the Jaffe reaction based creatinine estimation. Only streptomycin above therapeutic concentrations of 10mg/mL interfered in the Jaffe reaction and acted as non-creatinine chromogen. Therapeutic doses of the aminoglycosides do not form non-creatinine chromogens. Copyright © 2012 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

The effects of sample scheduling and sample numbers on estimates of the annual fluxes of suspended sediment in fluvial systems

USGS Publications Warehouse

Horowitz, Arthur J.; Clarke, Robin T.; Merten, Gustavo Henrique

2015-01-01

Since the 1970s, there has been both continuing and growing interest in developing accurate estimates of the annual fluvial transport (fluxes and loads) of suspended sediment and sediment-associated chemical constituents. This study provides an evaluation of the effects of manual sample numbers (from 4 to 12 year−1) and sample scheduling (random-based, calendar-based and hydrology-based) on the precision, bias and accuracy of annual suspended sediment flux estimates. The evaluation is based on data from selected US Geological Survey daily suspended sediment stations in the USA and covers basins ranging in area from just over 900 km2 to nearly 2 million km2 and annual suspended sediment fluxes ranging from about 4 Kt year−1 to about 200 Mt year−1. The results appear to indicate that there is a scale effect for random-based and calendar-based sampling schemes, with larger sample numbers required as basin size decreases. All the sampling schemes evaluated display some level of positive (overestimates) or negative (underestimates) bias. The study further indicates that hydrology-based sampling schemes are likely to generate the most accurate annual suspended sediment flux estimates with the fewest number of samples, regardless of basin size. This type of scheme seems most appropriate when the determination of suspended sediment concentrations, sediment-associated chemical concentrations, annual suspended sediment and annual suspended sediment-associated chemical fluxes only represent a few of the parameters of interest in multidisciplinary, multiparameter monitoring programmes. The results are just as applicable to the calibration of autosamplers/suspended sediment surrogates currently used to measure/estimate suspended sediment concentrations and ultimately, annual suspended sediment fluxes, because manual samples are required to adjust the sample data/measurements generated by these techniques so that they provide depth-integrated and cross-sectionally representative data. 

A revised probabilistic estimate of the maternal methyl mercury intake dose corresponding to a measured cord blood mercury concentration.

PubMed

Stern, Alan H

2005-02-01

In 2001, the U.S. Environmental Protection Agency (EPA) adopted a revised reference dose (RfD) for methyl mercury (MeHg) of 0.1 microg/kg/day. The RfD is based on neurologic developmental effects measured in children associated with exposure in utero to MeHg from the maternal diet. The RfD derivation proceeded from a point of departure based on measured concentration of mercury in fetal cord blood (micrograms per liter). The RfD, however, is a maternal dose (micrograms per kilogram per day). Reconstruction of the maternal dose corresponding to this cord blood concentration, including the variability around this estimate, is a critical step in the RfD derivation. The dose reconstruction employed by the U.S. EPA using the one-compartment pharmacokinetic model contains two areas of significant uncertainty: It does not directly account for the influence of the ratio of cord blood: maternal blood Hg concentration, and it does not resolve uncertainty regarding the most appropriate central tendency estimates for pregnancy and third-trimester-specific model parameters. A probabilistic reassessment of this dose reconstruction was undertaken to address these areas of uncertainty and generally to reconsider the specification of model input parameters. On the basis of a thorough review of the literature and recalculation of the one-compartment model including sensitivity analyses, I estimated that the 95th and 99th percentiles (i.e., the lower 5th and 1st percentiles) of the maternal intake dose corresponding to a fetal cord blood Hg concentration of 58 microg/L are 0.3 and 0.2 microg/kg/day, respectively. For the 99th percentile, this is half the value previously estimated by the U.S. EPA.

Quantification of nanoparticle concentration in colloidal suspensions by a non-destructive optical method

NASA Astrophysics Data System (ADS)

Clement, Sandhya; Gardner, Brint; Razali, Wan Aizuddin W.; Coleman, Victoria A.; Jämting, Åsa K.; Catchpoole, Heather J.; Goldys, Ewa M.; Herrmann, Jan; Zvyagin, Andrei

2017-11-01

The estimation of nanoparticle number concentration in colloidal suspensions is a prerequisite in many procedures, and in particular in multi-stage, low-yield reactions. Here, we describe a rapid, non-destructive method based on optical extinction and dynamic light scattering (DLS), which combines measurements using common bench-top instrumentation with a numerical algorithm to calculate the particle size distribution (PSD) and concentration. These quantities were derived from Mie theory applied to measurements of the optical extinction spectrum of homogeneous, non-absorbing nanoparticles, and the relative PSD of a colloidal suspension. The work presents an approach to account for PSDs achieved by DLS which, due to the underlying model, may not be representative of the true sample PSD. The presented approach estimates the absolute particle number concentration of samples with mono-, bi-modal and broad size distributions with <50% precision. This provides a convenient and practical solution for number concentration estimation required during many applications of colloidal nanomaterials.

QSAR development and bioavailability determination: the toxicity of chloroanilines to the soil dwelling springtail Folsomia candida.

PubMed

Giesen, Daniel; van Gestel, Cornelis A M

2013-03-01

Quantitative structure-activity relationships (QSARs) are an established tool in environmental risk assessment and a valuable alternative to the exhaustive use of test animals under REACH. In this study a QSAR was developed for the toxicity of a series of six chloroanilines to the soil-dwelling collembolan Folsomia candida in standardized natural LUFA2.2 soil. Toxicity endpoints incorporated in the QSAR were the concentrations causing 10% (EC10) and 50% (EC50) reduction in reproduction of F. candida. Toxicity was based on concentrations in interstitial water estimated from nominal concentrations in the soil and published soil-water partition coefficients. Estimated effect concentrations were negatively correlated with the lipophilicity of the compounds. Interstitial water concentrations for both the EC10 and EC50 for four compounds were determined by using solid-phase microextraction (SPME). Measured and estimated concentrations were comparable only for tetra- and pentachloroaniline. With decreasing chlorination the disparity between modelled and actual concentrations increased. Optimisation of the QSAR therefore could not be accomplished, showing the necessity to move from total soil to (bio)available concentration measurements. Copyright © 2012 Elsevier Ltd. All rights reserved.

Influence of fossil-fuel power plant emissions on the surface fine particulate matter in the Seoul Capital Area, South Korea.

PubMed

Kim, Byeong-Uk; Kim, Okgil; Kim, Hyun Cheol; Kim, Soontae

2016-09-01

The South Korean government plans to reduce region-wide annual PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm) concentrations in the Seoul Capital Area (SCA) from 2010 levels of 27 µg/m(3) to 20 µg/m(3) by 2024. At the same time, it is inevitable that emissions from fossil-fuel power plants will continue to increase if electricity generation expands and the generation portfolio remains the same in the future. To estimate incremental PM2.5 contributions due to projected electricity generation growth in South Korea, we utilized an ensemble forecasting member of the Integrated Multidimensional Air Quality System for Korea based on the Community Multi-scale Air Quality model. We performed sensitivity runs with across-the-board emission reductions for all fossil-fuel power plants in South Korea to estimate the contribution of PM2.5 from domestic fossil-fuel power plants. We estimated that fossil-fuel power plants are responsible for 2.4% of the annual PM2.5 national ambient air quality standard in the SCA as of 2010. Based on the electricity generation and the annual contribution of fossil-fuel power plants in 2010, we estimated that annual PM2.5 concentrations may increase by 0.2 µg/m(3) per 100 TWhr due to additional electricity generation. With currently available information on future electricity demands, we estimated that the total future contribution of fossil-fuel power plants would be 0.87 µg/m(3), which is 12.4% of the target reduction amount of the annual PM2.5 concentration by 2024. We also approximated that the number of premature deaths caused by existing fossil-fuel power plants would be 736 in 2024. Since the proximity of power plants to the SCA and the types of fuel used significantly impact this estimation, further studies are warranted on the impact of physical parameters of plants, such as location and stack height, on PM2.5 concentrations in the SCA due to each precursor. Improving air quality by reducing fine particle pollution is challenging when fossil-fuel-based electricity production is increasing. We show that an air quality forecasting system based on a photochemical model can be utilized to efficiently estimate PM2.5 contributions from and health impacts of domestic power plants. We derived PM2.5 concentrations per unit amount of electricity production from existing fossil-fuel power plants in South Korea. We assessed the health impacts of existing fossil-fuel power plants and the PM2.5 concentrations per unit electricity production to quantify the significance of existing and future fossil-fuel power plants with respect to the planned PM2.5 reduction target.

Monitoring of Batch Industrial Crystallization with Growth, Nucleation, and Agglomeration. Part 2: Structure Design for State Estimation with Secondary Measurements

PubMed Central

2017-01-01

This work investigates the design of alternative monitoring tools based on state estimators for industrial crystallization systems with nucleation, growth, and agglomeration kinetics. The estimation problem is regarded as a structure design problem where the estimation model and the set of innovated states have to be chosen; the estimator is driven by the available measurements of secondary variables. On the basis of Robust Exponential estimability arguments, it is found that the concentration is distinguishable with temperature and solid fraction measurements while the crystal size distribution (CSD) is not. Accordingly, a state estimator structure is selected such that (i) the concentration (and other distinguishable states) are innovated by means of the secondary measurements processed with the geometric estimator (GE), and (ii) the CSD is estimated by means of a rigorous model in open loop mode. The proposed estimator has been tested through simulations showing good performance in the case of mismatch in the initial conditions, parametric plant-model mismatch, and noisy measurements. PMID:28890604

Monitoring of Batch Industrial Crystallization with Growth, Nucleation, and Agglomeration. Part 2: Structure Design for State Estimation with Secondary Measurements.

PubMed

Porru, Marcella; Özkan, Leyla

2017-08-30

This work investigates the design of alternative monitoring tools based on state estimators for industrial crystallization systems with nucleation, growth, and agglomeration kinetics. The estimation problem is regarded as a structure design problem where the estimation model and the set of innovated states have to be chosen; the estimator is driven by the available measurements of secondary variables. On the basis of Robust Exponential estimability arguments, it is found that the concentration is distinguishable with temperature and solid fraction measurements while the crystal size distribution (CSD) is not. Accordingly, a state estimator structure is selected such that (i) the concentration (and other distinguishable states) are innovated by means of the secondary measurements processed with the geometric estimator (GE), and (ii) the CSD is estimated by means of a rigorous model in open loop mode. The proposed estimator has been tested through simulations showing good performance in the case of mismatch in the initial conditions, parametric plant-model mismatch, and noisy measurements.

AIR MONITOR SITING BY OBJECTIVE

EPA Science Inventory

A method is developed whereby measured pollutant concentrations can be used in conjunction with a mathematical air quality model to estimate the full spatial and temporal concentration distributions of the pollutants over a given region. The method is based on the application of ...

Computational Material Processing in Microgravity

NASA Technical Reports Server (NTRS)

2005-01-01

Working with Professor David Matthiesen at Case Western Reserve University (CWRU) a computer model of the DPIMS (Diffusion Processes in Molten Semiconductors) space experiment was developed that is able to predict the thermal field, flow field and concentration profile within a molten germanium capillary under both ground-based and microgravity conditions as illustrated. These models are coupled with a novel nonlinear statistical methodology for estimating the diffusion coefficient from measured concentration values after a given time that yields a more accurate estimate than traditional methods. This code was integrated into a web-based application that has become a standard tool used by engineers in the Materials Science Department at CWRU.

Source Parameter Estimation using the Second-order Closure Integrated Puff Model

DTIC Science & Technology

The sensor measurements are categorized as triggered and non-triggered based on the recorded concentration measurements and a threshold...concentration value. Using each measured value, sources of adjoint material are created from the triggered and non-triggered sensors, and the adjoint transport...equations are solved to predict the adjoint concentration fields. The adjoint source strength is inversely proportional to the concentration measurement

Alumina Concentration Detection Based on the Kernel Extreme Learning Machine.

PubMed

Zhang, Sen; Zhang, Tao; Yin, Yixin; Xiao, Wendong

2017-09-01

The concentration of alumina in the electrolyte is of great significance during the production of aluminum. The amount of the alumina concentration may lead to unbalanced material distribution and low production efficiency and affect the stability of the aluminum reduction cell and current efficiency. The existing methods cannot meet the needs for online measurement because industrial aluminum electrolysis has the characteristics of high temperature, strong magnetic field, coupled parameters, and high nonlinearity. Currently, there are no sensors or equipment that can detect the alumina concentration on line. Most companies acquire the alumina concentration from the electrolyte samples which are analyzed through an X-ray fluorescence spectrometer. To solve the problem, the paper proposes a soft sensing model based on a kernel extreme learning machine algorithm that takes the kernel function into the extreme learning machine. K-fold cross validation is used to estimate the generalization error. The proposed soft sensing algorithm can detect alumina concentration by the electrical signals such as voltages and currents of the anode rods. The predicted results show that the proposed approach can give more accurate estimations of alumina concentration with faster learning speed compared with the other methods such as the basic ELM, BP, and SVM.

Importance of Foliar Nitrogen Concentration to Predict Forest Productivity in the Mid-Atlantic Region

Treesearch

Yude Pan; John Hom; Jennifer Jenkins; Richard Birdsey

2004-01-01

To assess what difference it might make to include spatially defined estimates of foliar nitrogen in the regional application of a forest ecosystem model (PnET-II), we composed model predictions of wood production from extensive ground-based forest inventory analysis data across the Mid-Atlantic region. Spatial variation in foliar N concentration was assigned based on...

Determining Source Strength of Semivolatile Organic Compounds using Measured Concentrations in Indoor Dust

PubMed Central

Shin, Hyeong-Moo; McKone, Thomas E.; Nishioka, Marcia G.; Fallin, M. Daniele; Croen, Lisa A.; Hertz-Picciotto, Irva; Newschaffer, Craig J.; Bennett, Deborah H.

2014-01-01

Consumer products and building materials emit a number of semivolatile organic compounds (SVOCs) in the indoor environment. Because indoor SVOCs accumulate in dust, we explore the use of dust to determine source strength and report here on analysis of dust samples collected in 30 U.S. homes for six phthalates, four personal care product ingredients, and five flame retardants. We then use a fugacity-based indoor mass-balance model to estimate the whole house emission rates of SVOCs that would account for the measured dust concentrations. Di-2-ethylhexyl phthalate (DEHP) and di-iso-nonyl phthalate (DiNP) were the most abundant compounds in these dust samples. On the other hand, the estimated emission rate of diethyl phthalate (DEP) is the largest among phthalates, although its dust concentration is over two orders of magnitude smaller than DEHP and DiNP. The magnitude of the estimated emission rate that corresponds to the measured dust concentration is found to be inversely correlated with the vapor pressure of the compound, indicating that dust concentrations alone cannot be used to determine which compounds have the greatest emission rates. The combined dust-assay modeling approach shows promise for estimating indoor emission rates for SVOCs. PMID:24118221

Fine-Scale Exposure to Allergenic Pollen in the Urban Environment: Evaluation of Land Use Regression Approach.

PubMed

Hjort, Jan; Hugg, Timo T; Antikainen, Harri; Rusanen, Jarmo; Sofiev, Mikhail; Kukkonen, Jaakko; Jaakkola, Maritta S; Jaakkola, Jouni J K

2016-05-01

Despite the recent developments in physically and chemically based analysis of atmospheric particles, no models exist for resolving the spatial variability of pollen concentration at urban scale. We developed a land use regression (LUR) approach for predicting spatial fine-scale allergenic pollen concentrations in the Helsinki metropolitan area, Finland, and evaluated the performance of the models against available empirical data. We used grass pollen data monitored at 16 sites in an urban area during the peak pollen season and geospatial environmental data. The main statistical method was generalized linear model (GLM). GLM-based LURs explained 79% of the spatial variation in the grass pollen data based on all samples, and 47% of the variation when samples from two sites with very high concentrations were excluded. In model evaluation, prediction errors ranged from 6% to 26% of the observed range of grass pollen concentrations. Our findings support the use of geospatial data-based statistical models to predict the spatial variation of allergenic grass pollen concentrations at intra-urban scales. A remote sensing-based vegetation index was the strongest predictor of pollen concentrations for exposure assessments at local scales. The LUR approach provides new opportunities to estimate the relations between environmental determinants and allergenic pollen concentration in human-modified environments at fine spatial scales. This approach could potentially be applied to estimate retrospectively pollen concentrations to be used for long-term exposure assessments. Hjort J, Hugg TT, Antikainen H, Rusanen J, Sofiev M, Kukkonen J, Jaakkola MS, Jaakkola JJ. 2016. Fine-scale exposure to allergenic pollen in the urban environment: evaluation of land use regression approach. Environ Health Perspect 124:619-626; http://dx.doi.org/10.1289/ehp.1509761.

An inverse method to estimate emission rates based on nonlinear least-squares-based ensemble four-dimensional variational data assimilation with local air concentration measurements.

PubMed

Geng, Xiaobing; Xie, Zhenghui; Zhang, Lijun; Xu, Mei; Jia, Binghao

2018-03-01

An inverse source estimation method is proposed to reconstruct emission rates using local air concentration sampling data. It involves the nonlinear least squares-based ensemble four-dimensional variational data assimilation (NLS-4DVar) algorithm and a transfer coefficient matrix (TCM) created using FLEXPART, a Lagrangian atmospheric dispersion model. The method was tested by twin experiments and experiments with actual Cs-137 concentrations measured around the Fukushima Daiichi Nuclear Power Plant (FDNPP). Emission rates can be reconstructed sequentially with the progression of a nuclear accident, which is important in the response to a nuclear emergency. With pseudo observations generated continuously, most of the emission rates were estimated accurately, except under conditions when the wind blew off land toward the sea and at extremely slow wind speeds near the FDNPP. Because of the long duration of accidents and variability in meteorological fields, monitoring networks composed of land stations only in a local area are unable to provide enough information to support an emergency response. The errors in the estimation compared to the real observations from the FDNPP nuclear accident stemmed from a shortage of observations, lack of data control, and an inadequate atmospheric dispersion model without improvement and appropriate meteorological data. The proposed method should be developed further to meet the requirements of a nuclear emergency response. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reflectance spectroscopy of fresh whole leaves for the estimation of chemical concentration

NASA Technical Reports Server (NTRS)

Curran, Paul J.; Dungan, Jennifer L.; Macler, Bruce A.; Plummer, Stephen E.; Peterson, David L.

1992-01-01

Remotely sensed plant-canopy data in the visible and near-IR ranges are used to establish relations between the canopy reflectance and the chemical content of the leaves. The mathematical relation is generated by means of stepwise regression based on the derivative reflectance at certain wavelengths. Fourier filtering and sample control are used to minimize instrument noise and spectral overlap respectively, and absorption features are noted that correspond to sugar and protein. The coefficients of determination between estimated and measured concentrations are at least 0.82 for such substances as starch and chlorophyll. It is recommended in the analysis of remotly sensed canopy data that the chemicals with strong spectral overlaps with the chemical of interest be accounted for in order to estimate foliar chemical concentrations accurately.

Concentrations and Potential Health Risks of Metals in Lip Products

PubMed Central

Liu, Sa; Rojas-Cheatham, Ann

2013-01-01

Background: Metal content in lip products has been an issue of concern. Objectives: We measured lead and eight other metals in a convenience sample of 32 lip products used by young Asian women in Oakland, California, and assessed potential health risks related to estimated intakes of these metals. Methods: We analyzed lip products by inductively coupled plasma optical emission spectrometry and used previous estimates of lip product usage rates to determine daily oral intakes. We derived acceptable daily intakes (ADIs) based on information used to determine public health goals for exposure, and compared ADIs with estimated intakes to assess potential risks. Results: Most of the tested lip products contained high concentrations of titanium and aluminum. All examined products had detectable manganese. Lead was detected in 24 products (75%), with an average concentration of 0.36 ± 0.39 ppm, including one sample with 1.32 ppm. When used at the estimated average daily rate, estimated intakes were > 20% of ADIs derived for aluminum, cadmium, chromium, and manganese. In addition, average daily use of 10 products tested would result in chromium intake exceeding our estimated ADI for chromium. For high rates of product use (above the 95th percentile), the percentages of samples with estimated metal intakes exceeding ADIs were 3% for aluminum, 68% for chromium, and 22% for manganese. Estimated intakes of lead were < 20% of ADIs for average and high use. Conclusions: Cosmetics safety should be assessed not only by the presence of hazardous contents, but also by comparing estimated exposures with health-based standards. In addition to lead, metals such as aluminum, cadmium, chromium, and manganese require further investigation. PMID:23674482

Inter-comparison of interpolated background nitrogen dioxide concentrations across Greater Manchester, UK

NASA Astrophysics Data System (ADS)

Lindley, S. J.; Walsh, T.

There are many modelling methods dedicated to the estimation of spatial patterns in pollutant concentrations, each with their distinctive advantages and disadvantages. The derivation of a surface of air quality values from monitoring data alone requires the conversion of point-based data from a limited number of monitoring stations to a continuous surface using interpolation. Since interpolation techniques involve the estimation of data at un-sampled points based on calculated relationships between data measured at a number of known sample points, they are subject to some uncertainty, both in terms of the values estimated and their spatial distribution. These uncertainties, which are incorporated into many empirical and semi-empirical mapping methodologies, could be recognised in any further usage of the data and also in the assessment of the extent of an exceedence of an air quality standard and the degree of exposure this may represent. There is a wide range of available interpolation techniques and the differences in the characteristics of these result in variations in the output surfaces estimated from the same set of input points. The work presented in this paper provides an examination of uncertainties through the application of a number of interpolation techniques available in standard GIS packages to a case study nitrogen dioxide data set for the Greater Manchester conurbation in northern England. The implications of the use of different techniques are discussed through application to hourly concentrations during an air quality episode and annual average concentrations in 2001. Patterns of concentrations demonstrate considerable differences in the estimated spatial pattern of maxima as the combined effects of chemical processes, topography and meteorology. In the case of air quality episodes, the considerable spatial variability of concentrations results in large uncertainties in the surfaces produced but these uncertainties vary widely from area to area. In view of the uncertainties with classical techniques research is ongoing to develop alternative methods which should in time help improve the suite of tools available to air quality managers.

Defining the baseline for inhibition concentration calculations for hormetic hazards.

PubMed

Bailer, A J; Oris, J T

2000-01-01

The use of endpoint estimates based on modeling inhibition of test organism response relative to a baseline response is an important tool in the testing and evaluation of aquatic hazards. In the presence of a hormetic hazard, the definition of the baseline response is not clear because non-zero levels of the hazard stimulate an enhanced response prior to inhibition. In the present study, the methodology and implications of how one defines a baseline response for inhibition concentration estimation in aquatic toxicity tests was evaluated. Three possible baselines were considered: the control response level; the pooling of responses, including controls and all concentration conditions with responses enhanced relative to controls; and, finally, the maximal response. The statistical methods associated with estimating inhibition relative to the first two baseline definitions were described and a method for estimating inhibition relative to the third baseline definition was derived. These methods were illustrated with data from a standard aquatic zooplankton reproductive toxicity test in which the number of young produced in three broods of a cladoceran exposed to effluent was modeled as a function of effluent concentration. Copyright 2000 John Wiley & Sons, Ltd.

Python-Based Applications for Hydrogeological Modeling

NASA Astrophysics Data System (ADS)

Khambhammettu, P.

2013-12-01

Python is a general-purpose, high-level programming language whose design philosophy emphasizes code readability. Add-on packages supporting fast array computation (numpy), plotting (matplotlib), scientific /mathematical Functions (scipy), have resulted in a powerful ecosystem for scientists interested in exploratory data analysis, high-performance computing and data visualization. Three examples are provided to demonstrate the applicability of the Python environment in hydrogeological applications. Python programs were used to model an aquifer test and estimate aquifer parameters at a Superfund site. The aquifer test conducted at a Groundwater Circulation Well was modeled with the Python/FORTRAN-based TTIM Analytic Element Code. The aquifer parameters were estimated with PEST such that a good match was produced between the simulated and observed drawdowns. Python scripts were written to interface with PEST and visualize the results. A convolution-based approach was used to estimate source concentration histories based on observed concentrations at receptor locations. Unit Response Functions (URFs) that relate the receptor concentrations to a unit release at the source were derived with the ATRANS code. The impact of any releases at the source could then be estimated by convolving the source release history with the URFs. Python scripts were written to compute and visualize receptor concentrations for user-specified source histories. The framework provided a simple and elegant way to test various hypotheses about the site. A Python/FORTRAN-based program TYPECURVEGRID-Py was developed to compute and visualize groundwater elevations and drawdown through time in response to a regional uniform hydraulic gradient and the influence of pumping wells using either the Theis solution for a fully-confined aquifer or the Hantush-Jacob solution for a leaky confined aquifer. The program supports an arbitrary number of wells that can operate according to arbitrary schedules. The python wrapper invokes the underlying FORTRAN layer to compute transient groundwater elevations and processes this information to create time-series and 2D plots.

Comparison of Satellite Data with Ground-Based Measurements for Assessing Local Distributions of PM2.5 in Northeast Mexico.

NASA Astrophysics Data System (ADS)

Carmona, J.; Mendoza, A.; Lozano, D.; Gupta, P.; Mejia, G.; Rios, J.; Hernández, I.

2017-12-01

Estimating ground-level PM2.5 from satellite-derived Aerosol Optical Depth (AOD) through statistical models is a promising method to evaluate the spatial and temporal distribution of PM2.5 in regions where there are no or few ground-based observations, i.e. Latin America. Although PM concentrations are most accurately measured using ground-based instrumentation, the spatial coverage is too sparse to determine local and regional variations in PM. AOD satellite data offer the opportunity to overcome the spatial limitation of ground-based measurements. However, estimating PM surface concentrations from AOD satellite data is challenging, since multiple factors can affect the relationship between the total-column of AOD and the surface-concentration of PM. In this study, an Assembled Multiple Linear Regression Model (MLR) and a Neural Network Model (NN) were performed to estimate the relationship between the AOD and ground-concentrations of PM2.5 within the Monterrey Metropolitan Area (MMA). The MMA is located in northeast Mexico and is the third most populated urban area in the country. Episodes of high PM pollution levels are frequent throughout the year at the MMA. Daily averages of meteorological and air quality parameters were determined from data recorded at 5 monitoring sites of the MMA air quality monitoring network. Daily AOD data were retrieved from the MODIS sensor onboard the Aqua satellite. Overall, the best performance of the models was obtained using an AOD at 550 µm from the MYD04_3k product in combination with Temperature, Relative Humidity, Wind Speed and Wind Direction ground-based data. For the MLR performed, a correlation coefficient of R 0.6 and % bias of -6% were obtained. The NN showed a better performance than the MLR, with a correlation coefficient of R 0.75 and % bias -4%. The results obtained confirmed that satellite-derived AOD in combination with meteorological fields may allow to estimate PM2.5 local distributions.

Uncertainty of streamwater solute fluxes in five contrasting headwater catchments including model uncertainty and natural variability (Invited)

NASA Astrophysics Data System (ADS)

Aulenbach, B. T.; Burns, D. A.; Shanley, J. B.; Yanai, R. D.; Bae, K.; Wild, A.; Yang, Y.; Dong, Y.

2013-12-01

There are many sources of uncertainty in estimates of streamwater solute flux. Flux is the product of discharge and concentration (summed over time), each of which has measurement uncertainty of its own. Discharge can be measured almost continuously, but concentrations are usually determined from discrete samples, which increases uncertainty dependent on sampling frequency and how concentrations are assigned for the periods between samples. Gaps between samples can be estimated by linear interpolation or by models that that use the relations between concentration and continuously measured or known variables such as discharge, season, temperature, and time. For this project, developed in cooperation with QUEST (Quantifying Uncertainty in Ecosystem Studies), we evaluated uncertainty for three flux estimation methods and three different sampling frequencies (monthly, weekly, and weekly plus event). The constituents investigated were dissolved NO3, Si, SO4, and dissolved organic carbon (DOC), solutes whose concentration dynamics exhibit strongly contrasting behavior. The evaluation was completed for a 10-year period at five small, forested watersheds in Georgia, New Hampshire, New York, Puerto Rico, and Vermont. Concentration regression models were developed for each solute at each of the three sampling frequencies for all five watersheds. Fluxes were then calculated using (1) a linear interpolation approach, (2) a regression-model method, and (3) the composite method - which combines the regression-model method for estimating concentrations and the linear interpolation method for correcting model residuals to the observed sample concentrations. We considered the best estimates of flux to be derived using the composite method at the highest sampling frequencies. We also evaluated the importance of sampling frequency and estimation method on flux estimate uncertainty; flux uncertainty was dependent on the variability characteristics of each solute and varied for different reporting periods (e.g. 10-year, study period vs. annually vs. monthly). The usefulness of the two regression model based flux estimation approaches was dependent upon the amount of variance in concentrations the regression models could explain. Our results can guide the development of optimal sampling strategies by weighing sampling frequency with improvements in uncertainty in stream flux estimates for solutes with particular characteristics of variability. The appropriate flux estimation method is dependent on a combination of sampling frequency and the strength of concentration regression models. Sites: Biscuit Brook (Frost Valley, NY), Hubbard Brook Experimental Forest and LTER (West Thornton, NH), Luquillo Experimental Forest and LTER (Luquillo, Puerto Rico), Panola Mountain (Stockbridge, GA), Sleepers River Research Watershed (Danville, VT)

An uncertainty analysis for satellite-based estimates of cloud condensation nuclei number concentrations

NASA Astrophysics Data System (ADS)

Shinozuka, Y.; Clarke, A. D.; Nenes, A.; Jefferson, A.; Wood, R.; McNaughton, C. S.; Ström, J.; Tunved, P.; Redemann, J.; Thornhill, K. L., II; Moore, R.; Lathem, T. L.; Lin, J.; Yoon, Y. J.

2017-12-01

Aerosol-cloud interactions (ACI) are the largest source of uncertainty in estimates of anthropogenic radiative forcing responsible for the on-going climate change. ACI for warm clouds depend on the number concentration of cloud condensation nuclei (CCN), not on aerosol optical properties. Yet, aerosol optical depth (AOD) and its variants weighted by the spectral dependence over visible and near infrared wavelengths are commonly substituted for CCN in ACI studies. The substitution is motivated by the wide availability in space and time of satellite retrievals, an advantage over the sparse CCN measurements. If satellite-based CCN estimates are to continue to complement purely model-based ones, what CCN-AOD relationship should we assume and how large is the associated uncertainty? Our 2015 paper examines airborne and ground-based observations of aerosols to address these questions, focusing on the relationship between CCN and light extinction, σ, of dried particles averaged over one-kilometer horizontal distance. That paper discusses the way the CCN-AOD relationship is influenced not only by the CCN-σ relationship but also by the humidity response of light extinction, the vertical profile, the horizontal-temporal variability and the AOD measurement error. In this presentation, we apply these findings to passive satellite data to analyze the uncertainty in satellite-based CCN estimates.

Atmospheric Sulfur Hexafluoride: Sources, Sinks and Greenhouse Warming

NASA Technical Reports Server (NTRS)

Sze, Nien Dak; Wang, Wei-Chyung; Shia, George; Goldman, Aaron; Murcray, Frank J.; Murcray, David G.; Rinsland, Curtis P.

1993-01-01

Model calculations using estimated reaction rates of sulfur hexafluoride (SF6) with OH and 0('D) indicate that the atmospheric lifetime due to these processes may be very long (25,000 years). An upper limit for the UV cross section would suggest a photolysis lifetime much longer than 1000 years. The possibility of other removal mechanisms are discussed. The estimated lifetimes are consistent with other estimated values based on recent laboratory measurements. There appears to be no known natural source of SF6. An estimate of the current production rate of SF6 is about 5 kt/yr. Based on historical emission rates, we calculated a present-day atmospheric concentrations for SF6 of about 2.5 parts per trillion by volume (pptv) and compared the results with available atmospheric measurements. It is difficult to estimate the atmospheric lifetime of SF6 based on mass balance of the emission rate and observed abundance. There are large uncertainties concerning what portion of the SF6 is released to the atmosphere. Even if the emission rate were precisely known, it would be difficult to distinguish among lifetimes longer than 100 years since the current abundance of SF6 is due to emission in the past three decades. More information on the measured trends over the past decade and observed vertical and latitudinal distributions of SF6 in the lower stratosphere will help to narrow the uncertainty in the lifetime. Based on laboratory-measured IR absorption cross section for SF6, we showed that SF6 is about 3 times more effective as a greenhouse gas compared to CFC 11 on a per molecule basis. However, its effect on atmospheric warming will be minimal because of its very small concentration. We estimated the future concentration of SF6 at 2010 to be 8 and 10 pptv based on two projected emission scenarios. The corresponding equilibrium warming of 0.0035 C and 0.0043 C is to be compared with the estimated warming due to CO2 increase of about 0.8 C in the same period.

Using in situ pore water concentrations to estimate the phytotoxicity of nicosulfuron in soils to corn (Zea mays L.).

PubMed

Liu, Kailin; Cao, Zhengya; Pan, Xiong; Yu, Yunlong

2012-08-01

The phytotoxicity of an herbicide in soil is typically dependent on the soil characteristics. To obtain a comparable value of the concentration that inhibits growth by 50% (IC50), 0.01 M CaCl(2) , excess pore water (EPW) and in situ pore water (IPW) were used to extract the bioavailable fraction of nicosulfuron from five different soils to estimate the nicosulfuron phytotoxicity to corn (Zea mays L.). The results indicated that the phytotoxicity of nicosulfuron in soils to corn depended on the soil type, and the IC50 values calculated based on the amended concentration of nicosulfuron ranged from 0.77 to 9.77 mg/kg among the five tested soils. The range of variation in IC50 values for nicosulfuron was smaller when the concentrations of nicosulfuron extracted with 0.01 M CaCl(2) and EPW were used instead of the amended concentration. No significant difference was observed among the IC50 values calculated from the IPW concentrations of nicosulfuron in the five tested soils, suggesting that the concentration of nicosulfuron in IPW could be used to estimate the phytotoxicity of residual nicosulfuron in soils. Copyright © 2012 SETAC.

Estimated dietary fluoride intake for New Zealanders.

PubMed

Cressey, Peter; Gaw, Sally; Love, John

2010-01-01

Existing fluoride concentration and consumption data were used to estimate fluoride intakes from the diet and toothpaste use, for New Zealand subpopulations, to identify any population groups at risk of high-fluoride intake. For each sub-population, two separate dietary intake estimates were made--one based on a non-fluoridated water supply (fluoride concentration of 0.1 mg/L), and the other based on a water supply fluoridated to a concentration of 1.0 mg/L. Fluoride concentration data were taken from historical surveys, while food consumption data were taken from national 24-hour dietary recall surveys or from simulated diets. Mean and 95th percentile estimations of dietary fluoride intake were well below the upper level of intake (UL), whether intakes were calculated on the basis of a non-fluoridated or fluoridated water supply. The use of fluoride-containing toothpastes provides additional fluoride intake. For many of the population groups considered, mean fluoride intakes were below the adequate intake (AI) level for caries protection, even after inclusion of the fluoride contribution from toothpaste. Intake of fluoride was driven by consumption of dietary staples (bread, potatoes),beverages (particularly tea, soft drinks, and beer), and the fluoride status of drinking water. Estimates of fluoride intake from the diet and toothpaste did not identify any groups at risk of exceeding the UL, with the exception of infants (6-12 months) living in areas with fluoridated water supplies and using high-fluoride toothpaste. In contrast, much of the adult population may be receiving insufficient fluoride for optimum caries protection from these sources, as represented by the AI.

Detection limits of quantitative and digital PCR assays and their influence in presence-absence surveys of environmental DNA

USGS Publications Warehouse

Hunter, Margaret; Dorazio, Robert M.; Butterfield, John S.; Meigs-Friend, Gaia; Nico, Leo; Ferrante, Jason A.

2017-01-01

A set of universal guidelines is needed to determine the limit of detection (LOD) in PCR-based analyses of low concentration DNA. In particular, environmental DNA (eDNA) studies require sensitive and reliable methods to detect rare and cryptic species through shed genetic material in environmental samples. Current strategies for assessing detection limits of eDNA are either too stringent or subjective, possibly resulting in biased estimates of species’ presence. Here, a conservative LOD analysis grounded in analytical chemistry is proposed to correct for overestimated DNA concentrations predominantly caused by the concentration plateau, a nonlinear relationship between expected and measured DNA concentrations. We have used statistical criteria to establish formal mathematical models for both quantitative and droplet digital PCR. To assess the method, a new Grass Carp (Ctenopharyngodon idella) TaqMan assay was developed and tested on both PCR platforms using eDNA in water samples. The LOD adjustment reduced Grass Carp occupancy and detection estimates while increasing uncertainty – indicating that caution needs to be applied to eDNA data without LOD correction. Compared to quantitative PCR, digital PCR had higher occurrence estimates due to increased sensitivity and dilution of inhibitors at low concentrations. Without accurate LOD correction, species occurrence and detection probabilities based on eDNA estimates are prone to a source of bias that cannot be reduced by an increase in sample size or PCR replicates. Other applications also could benefit from a standardized LOD such as GMO food analysis, and forensic and clinical diagnostics.

Quantitative analysis of the effect of supersaturation on in vivo drug absorption.

PubMed

Takano, Ryusuke; Takata, Noriyuki; Saito, Ryoichi; Furumoto, Kentaro; Higo, Shoichi; Hayashi, Yoshiki; Machida, Minoru; Aso, Yoshinori; Yamashita, Shinji

2010-10-04

The purpose of this study is to clarify the effects of intestinal drug supersaturation on solubility-limited nonlinear absorption. Oral absorption of a novel farnesyltransferase inhibitor (FTI-2600) from its crystalline free base and its HCl salt was determined in dogs. To clarify the contribution of supersaturation on improving drug absorption, in vivo intraluminal concentration of FTI-2600 after oral administration was estimated from the pharmacokinetics data using a physiologically based model. Dissolution and precipitation characteristics of FTI-2600 in a biorelevant media were investigated in vitro using a miniscale dissolution test and powder X-ray diffraction analysis. In the in vitro study, the HCl salt immediately dissolved but precipitated rapidly. The metastable amorphous free base precipitant, which did not convert into the stable crystalline free base in the simulated intestinal fluids for several hours, generated a 5-fold increase in dissolved concentration compared to the equilibrium solubility of the crystalline free base. By computer simulation, the intraluminal drug concentration after administration of the free base was estimated to reach the saturated solubility, indicating solubility-limited absorption. On the other hand, administration of the HCl salt resulted in an increased intraluminal concentration and the plasma concentration was 400% greater than that after administration of the free base. This in vivo/in vitro correlation of the increased drug concentrations in the small intestine provide clear evidence that not only the increase in the dissolution rate, but also the supersaturation phenomenon, improved the solubility-limited absorption of FTI-2600. These results indicate that formulation technologies that can induce supersaturation may be of great assistance to the successful development of poorly water-soluble drugs.

Improving Riverine Constituent Concentration and Flux Estimation by Accounting for Antecedent Discharge Conditions

NASA Astrophysics Data System (ADS)

Zhang, Q.; Ball, W. P.

2016-12-01

Regression-based approaches are often employed to estimate riverine constituent concentrations and fluxes based on typically sparse concentration observations. One such approach is the WRTDS ("Weighted Regressions on Time, Discharge, and Season") method, which has been shown to provide more accurate estimates than prior approaches. Centered on WRTDS, this work was aimed at developing improved models for constituent concentration and flux estimation by accounting for antecedent discharge conditions. Twelve modified models were developed and tested, each of which contains one additional variable to represent antecedent conditions. High-resolution ( daily) data at nine monitoring sites were used to evaluate the relative merits of the models for estimation of six constituents - chloride (Cl), nitrate-plus-nitrite (NOx), total Kjeldahl nitrogen (TKN), total phosphorus (TP), soluble reactive phosphorus (SRP), and suspended sediment (SS). For each site-constituent combination, 30 concentration subsets were generated from the original data through Monte Carlo sub-sampling and then used to evaluate model performance. For the sub-sampling, three sampling strategies were adopted: (A) 1 random sample each month (12/year), (B) 12 random monthly samples plus additional 8 random samples per year (20/year), and (C) 12 regular (non-storm) and 8 storm samples per year (20/year). The modified models show general improvement over the original model under all three sampling strategies. Major improvements were achieved for NOx by the long-term flow-anomaly model and for Cl by the ADF (average discounted flow) model and the short-term flow-anomaly model. Moderate improvements were achieved for SS, TP, and TKN by the ADF model. By contrast, no such achievement was achieved for SRP by any proposed model. In terms of sampling strategy, performance of all models was generally best using strategy C and worst using strategy A, and especially so for SS, TP, and SRP, confirming the value of routinely collecting storm-flow samples. Overall, this work provides a comprehensive set of statistical evidence for supporting the incorporation of antecedent discharge conditions into WRTDS for constituent concentration and flux estimation, thereby combining the advantages of two recent developments in water quality modeling.

Lead-rich sediments, Coeur d'Alene River Valley, Idaho: area, volume, tonnage, and lead content

USGS Publications Warehouse

Bookstrom, Arthur A.; Box, Stephen E.; Campbell, Julie K.; Foster, Kathryn I.; Jackson, Berne L.

2001-01-01

In north Idaho, downstream from the Coeur d?Alene (CdA) silver-lead-zinc mining district, lead-rich sediments, containing at least 1,000 ppm of lead, cover approximately 61 km2 (or 73 percent) of the 84-km2 floor of the CdA River valley, from the confluence of its North and South Forks to the top of its delta-front slope, in CdA Lake. Concentrations of lead (Pb) in surface sediments range from 15 to about 38,500 ppm, and average 3,370 ppm, which is 112 times the mean background concentration (30 ppm) of Pb in uncontaminated sediments of the CdA and St. Joe River valleys. Most of the highest concentrations of Pb are in sediments within or near the river channel, or near the base of the stratigraphic section of Pb-rich sediments. Ranges of Pb concentration in Pb-rich sediments gradually decrease with increasing distance from the river and its distributaries. Ranges of thickness of Pb-rich sediments generally decrease abruptly with increasing distance from the river, from about 3 + 3 m in the river channel to about 1 + 1m on upland riverbanks, levees and sand splays, to about 0.3 + 0.3 m in back-levee marshes and lateral lakes. Thickness of Pb-rich dredge spoils (removed from the river and deposited on Cataldo-Mission Flats) is mostly in the range 4 + 4 m, thinning away from an outfall zone north and west of the river, near the formerly dredged channel reach near Cataldo Landing. We attribute lateral variation in ranges of thickness and Pb content of Pb-rich sediments to the dynamic balance between decreasing floodwater flow velocity with increasing distance from the river and the quantity, size, density, and Pb content of particles mobilized, transported, and deposited. We present alternative median- and mean-based estimates of the volume of Pbrich sediments, their wet and dry tonnage, and their tonnage of contained Pb. We calculate separate pairs of estimates for 23 Estimation Units, each of which corresponds to a major depositional environment, divided into down-valley segments. We favor median-based estimates of the thickness and thickness-interval weighted-average Pb concentration, because uncommonly thick and Pb-rich sections may excessively influence mean estimates. Nevertheless, data from partial sections of Pb-rich sediments are included in most estimates, and these tend to reduce both median- and mean-based estimates. Median-based estimates indicate a volume of 32 M m3 of Pb-rich sediments in the CdA River valley, with a dry tonnage of 47 + 4 M t, containing 250 + 75 kt of Pb (considering analytical uncertainties only). An equivalent tonnage of dry CdA River valley sediments of the pre-mining era, with the mean background concentration of 30 ppm of Pb, would contain about 1.4 kt of Pb. Thus, the amount of Pb added to CdA River valley sediments deposited since the onset of mining is estimated as 249 + 75 kt of Pb, or about 99.5 percent of the estimated Pb contained. Of an estimated 850 + 10 kt of Pb lost to streams as a result of mining-related activities, an estimated total of 739 + 319 kt of Pb has been deposited in sediments of the South Fork drainage basin, the CdA River valley, and the bottom of CdA Lake (combined). Based on mid-range values from a set of preferred estimates with uncertainty ranges up to + 50 percent, roughly 24 percent of the 850 + 10 kt of mining-derived Pb lost to streams has been added to sediments of the South Fork drainage basin, 29 percent to sediments of the CdA River valley floor, and 34 percent to sediments on the bottom of CdA Lake. This amounts to roughly 87 percent of the Pb lost to streams, not including Pb contained in sediments of the North Fork drainage basin and the Spokane River valley, the tonnages of which have not yet estimated.

Estimates of nitrate loads and yields from groundwater to streams in the Chesapeake Bay watershed based on land use and geology

USGS Publications Warehouse

Terziotti, Silvia; Capel, Paul D.; Tesoriero, Anthony J.; Hopple, Jessica A.; Kronholm, Scott C.

2018-03-07

The water quality of the Chesapeake Bay may be adversely affected by dissolved nitrate carried in groundwater discharge to streams. To estimate the concentrations, loads, and yields of nitrate from groundwater to streams for the Chesapeake Bay watershed, a regression model was developed based on measured nitrate concentrations from 156 small streams with watersheds less than 500 square miles (mi2 ) at baseflow. The regression model has three predictive variables: geologic unit, percent developed land, and percent agricultural land. Comparisons of estimated and actual values within geologic units were closely matched. The coefficient of determination (R2 ) for the model was 0.6906. The model was used to calculate baseflow nitrate concentrations at over 83,000 National Hydrography Dataset Plus Version 2 catchments and aggregated to 1,966 total 12-digit hydrologic units in the Chesapeake Bay watershed. The modeled output geospatial data layers provided estimated annual loads and yields of nitrate from groundwater into streams. The spatial distribution of annual nitrate yields from groundwater estimated by this method was compared to the total watershed yields of all sources estimated from a Chesapeake Bay SPAtially Referenced Regressions On Watershed attributes (SPARROW) water-quality model. The comparison showed similar spatial patterns. The regression model for groundwater contribution had similar but lower yields, suggesting that groundwater is an important source of nitrogen for streams in the Chesapeake Bay watershed.

Metabolic control analysis using transient metabolite concentrations. Determination of metabolite concentration control coefficients.

PubMed Central

Delgado, J; Liao, J C

1992-01-01

The methodology previously developed for determining the Flux Control Coefficients [Delgado & Liao (1992) Biochem. J. 282, 919-927] is extended to the calculation of metabolite Concentration Control Coefficients. It is shown that the transient metabolite concentrations are related by a few algebraic equations, attributed to mass balance, stoichiometric constraints, quasi-equilibrium or quasi-steady states, and kinetic regulations. The coefficients in these relations can be estimated using linear regression, and can be used to calculate the Control Coefficients. The theoretical basis and two examples are discussed. Although the methodology is derived based on the linear approximation of enzyme kinetics, it yields reasonably good estimates of the Control Coefficients for systems with non-linear kinetics. PMID:1497632

Visualization of hemodynamics and light scattering in exposed brain of rat using multispectral image reconstruction based on Wiener estimation method

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Ishizuka, Tomohiro; Yoshida, Keiichiro; Kawauchi, Satoko; Sato, Shunichi; Sato, Manabu

2015-07-01

We investigate a method to estimate the spectral images of reduced scattering coefficients and the absorption coefficients of in vivo exposed brain tissues in the range from visible to near-infrared wavelength (500-760 nm) based on diffuse reflectance spectroscopy using a digital RGB camera. In the proposed method, the multi-spectral reflectance images of in vivo exposed brain are reconstructed from the digital red, green, blue images using the Wiener estimation algorithm. The Monte Carlo simulation-based multiple regression analysis for the absorbance spectra is then used to specify the absorption and scattering parameters of brain tissue. In this analysis, the concentration of oxygenated hemoglobin and that of deoxygenated hemoglobin are estimated as the absorption parameters whereas the scattering amplitude a and the scattering power b in the expression of μs'=aλ-b as the scattering parameters, respectively. The spectra of absorption and reduced scattering coefficients are reconstructed from the absorption and scattering parameters, and finally, the spectral images of absorption and reduced scattering coefficients are estimated. We performed simultaneous recordings of spectral diffuse reflectance images and of the electrophysiological signals for in vivo exposed rat brain during the cortical spreading depression evoked by the topical application of KCl. Changes in the total hemoglobin concentration and the tissue oxygen saturation imply the temporary change in cerebral blood flow during CSD. Change in the reduced scattering coefficient was observed before the profound increase in the total hemoglobin concentration, and its occurrence was synchronized with the negative dc shift of the local field potential.

Radon measurements and effective dose from radon inhalation estimation in the Neapolitan catacombs.

PubMed

Quarto, M; Pugliese, M; Loffredo, F; Zambella, C; Roca, V

2014-03-01

In this study, the indoor radon activity concentrations have been measured in the Neapolitan catacombs using LR115 detectors. The detectors were exposed for two quarters, one in the warm season and the other in the cold. This has allowed one to evaluate the seasonal variations of concentrations, while the diurnal variations were evaluated performing continuous measurements by a Radim 5 monitor. The authors found that radon concentrations were lower in winter than in summer. Based on their values, taking into consideration the working hours in the catacombs and the equilibrium factor of 0.4, the effective dose to workers was estimated.

Maximum entropy estimation of a Benzene contaminated plume using ecotoxicological assays.

PubMed

Wahyudi, Agung; Bartzke, Mariana; Küster, Eberhard; Bogaert, Patrick

2013-01-01

Ecotoxicological bioassays, e.g. based on Danio rerio teratogenicity (DarT) or the acute luminescence inhibition with Vibrio fischeri, could potentially lead to significant benefits for detecting on site contaminations on qualitative or semi-quantitative bases. The aim was to use the observed effects of two ecotoxicological assays for estimating the extent of a Benzene groundwater contamination plume. We used a Maximum Entropy (MaxEnt) method to rebuild a bivariate probability table that links the observed toxicity from the bioassays with Benzene concentrations. Compared with direct mapping of the contamination plume as obtained from groundwater samples, the MaxEnt concentration map exhibits on average slightly higher concentrations though the global pattern is close to it. This suggest MaxEnt is a valuable method to build a relationship between quantitative data, e.g. contaminant concentrations, and more qualitative or indirect measurements, in a spatial mapping framework, which is especially useful when clear quantitative relation is not at hand. Copyright © 2012 Elsevier Ltd. All rights reserved.

[Algorithm for estimating chlorophyll-a concentration in case II water body based on bio-optical model].

PubMed

Yang, Wei; Chen, Jin; Mausushita, Bunki

2009-01-01

In the present study, a novel retrieval method for estimating chlorophyll-a concentration in case II waters based on bio-optical model was proposed and was tested with the data measured in the laboratory. A series of reflectance spectra, with which the concentration of each sample constituent (for example chlorophyll-a, NPSS etc.) was obtained from accurate experiments, were used to calculate the absorption and backscattering coefficients of the constituents of the case II waters. Then non-negative least square method was applied to calculate the concentration of chlorophyll-a and non-phytoplankton suspended sediments (NPSS). Green algae was firstly collected from the Kasumigaura lake in Japan and then cultured in the laboratory. The reflectance spectra of waters with different amounts of phytoplankton and NPSS were measured in the dark room using FieldSpec Pro VNIR (Analytical Spectral Devises Inc. , Boulder, CO, USA). In order to validate whether this method can be applied in multispectral data (for example Landsat TM), the spectra measured in the laboratory were resampled with Landsat TM bands 1, 2, 3 and 4. Different combinations of TM bands were compared to derive the most appropriate wavelength for detecting chlorophyll-a in case II water for green algae. The results indicated that the combination of TM bands 2, 3 and 4 achieved much better accuracy than other combinations, and the estimated concentration of chlorophyll-a was significantly more accurate than empirical methods. It is expected that this method can be directly applied to the real remotely sensed image because it is based on bio-optical model.

Regression model development and computational procedures to support estimation of real-time concentrations and loads of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-9

USGS Publications Warehouse

Lee, Michael T.; Asquith, William H.; Oden, Timothy D.

2012-01-01

In December 2005, the U.S. Geological Survey (USGS), in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (Escherichia coli and total coliform), atrazine, and suspended sediment at two USGS streamflow-gaging stations that represent watersheds contributing to Lake Houston (08068500 Spring Creek near Spring, Tex., and 08070200 East Fork San Jacinto River near New Caney, Tex.). Data from the discrete water-quality samples collected during 2005–9, in conjunction with continuously monitored real-time data that included streamflow and other physical water-quality properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), were used to develop regression models for the estimation of concentrations of water-quality constituents of substantial source watersheds to Lake Houston. The potential explanatory variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, and time (to account for seasonal variations inherent in some water-quality data). The response variables (the selected constituents) at each site were nitrite plus nitrate nitrogen, total phosphorus, total organic carbon, E. coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities to serve as potential surrogate variables to estimate concentrations of the selected constituents through statistical regression. Statistical regression also facilitates accompanying estimates of uncertainty in the form of prediction intervals. Each regression model potentially can be used to estimate concentrations of a given constituent in real time. Among other regression diagnostics, the diagnostics used as indicators of general model reliability and reported herein include the adjusted R-squared, the residual standard error, residual plots, and p-values. Adjusted R-squared values for the Spring Creek models ranged from .582–.922 (dimensionless). The residual standard errors ranged from .073–.447 (base-10 logarithm). Adjusted R-squared values for the East Fork San Jacinto River models ranged from .253–.853 (dimensionless). The residual standard errors ranged from .076–.388 (base-10 logarithm). In conjunction with estimated concentrations, constituent loads can be estimated by multiplying the estimated concentration by the corresponding streamflow and by applying the appropriate conversion factor. The regression models presented in this report are site specific, that is, they are specific to the Spring Creek and East Fork San Jacinto River streamflow-gaging stations; however, the general methods that were developed and documented could be applied to most perennial streams for the purpose of estimating real-time water quality data.

Preliminary Estimation of Black Carbon Deposition from Nepal Climate Observatory-Pyramid Data and Its Possible Impact on Snow Albedo Changes Over Himalayan Glaciers During the Pre-Monsoon Season

NASA Technical Reports Server (NTRS)

Yasunari, T. J.; Bonasoni, P.; Laj, P.; Fujita, K.; Vuillermoz, E.; Marinoni, A.; Cristofanelli, P.; Duchi, R.; Tartari, G.; Lau, K.-M.

2010-01-01

The possible minimal range of reduction in snow surface albedo due to dry deposition of black carbon (BC) in the pre-monsoon period (March-May) was estimated as a lower bound together with the estimation of its accuracy, based on atmospheric observations at the Nepal Climate Observatory-Pyramid (NCO-P) sited at 5079 m a.s.l. in the Himalayan region. We estimated a total BC deposition rate of 2.89 g m-2 day-1 providing a total deposition of 266 micrograms/ square m for March-May at the site, based on a calculation with a minimal deposition velocity of 1.0 10(exp -4) m/s with atmospheric data of equivalent BC concentration. Main BC size at NCO-P site was determined as 103.1-669.8 nm by correlation analysis between equivalent BC concentration and particulate size distribution in the atmosphere. We also estimated BC deposition from the size distribution data and found that 8.7% of the estimated dry deposition corresponds to the estimated BC deposition from equivalent BC concentration data. If all the BC is deposited uniformly on the top 2-cm pure snow, the corresponding BC concentration is 26.0-68.2 microgram/kg assuming snow density variations of 195-512 kg/ cubic m of Yala Glacier close to NCO-P site. Such a concentration of BC in snow could result in 2.0-5.2% albedo reductions. From a simple numerical calculations and if assuming these albedo reductions continue throughout the year, this would lead to a runoff increases of 70-204 mm of water drainage equivalent of 11.6-33.9% of the annual discharge of a typical Tibetan glacier. Our estimates of BC concentration in snow surface for pre-monsoon season can be considered comparable to those at similar altitude in the Himalayan region, where glaciers and perpetual snow region starts in the vicinity of NCO-P. Our estimates from only BC are likely to represent a lower bound for snow albedo reductions, since a fixed slower deposition velocity was used and atmospheric wind and turbulence effects, snow aging, dust deposition, and snow albedo feedbacks were not considered. This study represents the first investigation about BC deposition on snow from atmospheric aerosol data in Himalayas and related albedo effect is especially the first track at the southern slope of Himalayas.

Improved estimation of sediment source contributions by concentration-dependent Bayesian isotopic mixing model

NASA Astrophysics Data System (ADS)

Ram Upadhayay, Hari; Bodé, Samuel; Griepentrog, Marco; Bajracharya, Roshan Man; Blake, Will; Cornelis, Wim; Boeckx, Pascal

2017-04-01

The implementation of compound-specific stable isotope (CSSI) analyses of biotracers (e.g. fatty acids, FAs) as constraints on sediment-source contributions has become increasingly relevant to understand the origin of sediments in catchments. The CSSI fingerprinting of sediment utilizes CSSI signature of biotracer as input in an isotopic mixing model (IMM) to apportion source soil contributions. So far source studies relied on the linear mixing assumptions of CSSI signature of sources to the sediment without accounting for potential effects of source biotracer concentration. Here we evaluated the effect of FAs concentration in sources on the accuracy of source contribution estimations in artificial soil mixture of three well-separated land use sources. Soil samples from land use sources were mixed to create three groups of artificial mixture with known source contributions. Sources and artificial mixture were analysed for δ13C of FAs using gas chromatography-combustion-isotope ratio mass spectrometry. The source contributions to the mixture were estimated using with and without concentration-dependent MixSIAR, a Bayesian isotopic mixing model. The concentration-dependent MixSIAR provided the closest estimates to the known artificial mixture source contributions (mean absolute error, MAE = 10.9%, and standard error, SE = 1.4%). In contrast, the concentration-independent MixSIAR with post mixing correction of tracer proportions based on aggregated concentration of FAs of sources biased the source contributions (MAE = 22.0%, SE = 3.4%). This study highlights the importance of accounting the potential effect of a source FA concentration for isotopic mixing in sediments that adds realisms to mixing model and allows more accurate estimates of contributions of sources to the mixture. The potential influence of FA concentration on CSSI signature of sediments is an important underlying factor that determines whether the isotopic signature of a given source is observable even after equilibrium. Therefore inclusion of FA concentrations of the sources in the IMM formulation is standard procedure for accurate estimation of source contributions. The post model correction approach that dominates the CSSI fingerprinting causes bias, especially if the FAs concentration of sources differs substantially.

Prediction the concentration of graphite direct exfoliation by liquid solution with solubility parameters map

NASA Astrophysics Data System (ADS)

Liang, Ko-Yuan; Yang, Wein-Duo

2018-01-01

This study is to discuss solvent selection with graphene dispersion concentration of directly exfoliation graphite. That limiting boundaries of fractional cohesion parameters will be draw on the triangular diagram to prediction and estimate. It is based on the literature of data and check with experimental or other literature results, include organic solution, aqueous solution and ionic liquid. In this work, we found that estimated the graphene dispersion concentration by distance (Ra) of Hansen solubility parameters (HSP) between graphene and solvent, the lower Ra; the higher concentration, some case the lower Ra; the lower dispersion concentration (such as acetone). It is compatible with the graphene dispersion concentration on the Hansen space or Triangular fractional cohesion parameters dispersion diagram. From Triangular fractional cohesion parameters dispersion diagram, 2D maps are more convenient for researchers than 3D maps of Hansen space and quickly to find the appropriate combination of solvents for different application.

Residual effects of fertilization history increase nitrous oxide emissions from zero-N controls:Implications for estimating fertilizer-induced emission factors

USDA-ARS?s Scientific Manuscript database

Agricultural N fertilization is the dominant driver of increasing atmospheric nitrous oxide (N2O) concentrations over the past half century, yet there is considerable uncertainty in estimates of N2O emissions from agriculture. Such estimates are typically based on the amount of N applied and a ferti...

Source Term Estimation of Radioxenon Released from the Fukushima Dai-ichi Nuclear Reactors Using Measured Air Concentrations and Atmospheric Transport Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eslinger, Paul W.; Biegalski, S.; Bowyer, Ted W.

2014-01-01

Systems designed to monitor airborne radionuclides released from underground nuclear explosions detected radioactive fallout from the Fukushima Daiichi nuclear accident in March 2011. Atmospheric transport modeling (ATM) of plumes of noble gases and particulates were performed soon after the accident to determine plausible detection locations of any radioactive releases to the atmosphere. We combine sampling data from multiple International Modeling System (IMS) locations in a new way to estimate the magnitude and time sequence of the releases. Dilution factors from the modeled plume at five different detection locations were combined with 57 atmospheric concentration measurements of 133-Xe taken from Marchmore » 18 to March 23 to estimate the source term. This approach estimates that 59% of the 1.24×1019 Bq of 133-Xe present in the reactors at the time of the earthquake was released to the atmosphere over a three day period. Source term estimates from combinations of detection sites have lower spread than estimates based on measurements at single detection sites. Sensitivity cases based on data from four or more detection locations bound the source term between 35% and 255% of available xenon inventory.« less

Practical calculation method to estimate the absolute boron concentration in tissues using 18F-FBPA PET.

PubMed

Watabe, Tadashi; Hanaoka, Kohei; Naka, Sadahiro; Kanai, Yasukazu; Ikeda, Hayato; Aoki, Masanao; Shimosegawa, Eku; Kirihata, Mitsunori; Hatazawa, Jun

2017-07-01

The purpose of this study was to establish a practical method to estimate the absolute boron concentrations in the tissues based on the standardized uptake values (SUVs) after administration of 4-borono-phenylalanine (BPA) using 4-borono-2- 18 F-fluoro-phenylalanine ( 18 F-FBPA) PET. Rat xenograft models of C6 glioma (n = 7, body weight 241 ± 28.0 g) were used for the study. PET was performed 60 min after intravenous injection of 18 F-FBPA (30.5 ± 0.7 MBq). After the PET scanning, BPA-fructose (167.3 ± 18.65 mg/kg) was administered by slow intravenous injection to the same subjects. The rats were killed 60 min after the BPA injection and tissue samples were collected from the major organs and tumors. The absolute boron concentrations (unit: ppm) in the samples were measured by inductively coupled plasma optical emission spectrometry (ICP-OES). The boron concentrations in the tissues/tumors were also estimated from the 18 F-FBPA PET images using the following formula: estimated absolute boron concentration (ppm) = 0.0478 × [BPA dose (mg/kg)] × SUV. The measured absolute boron concentrations (mBC) by ICP-OES and the estimated boron concentrations (eBC) from the PET images were compared. The percent difference between the mBC and eBC calculated based on the SUV max was -5.2 ± 21.1% for the blood, -9.4 ± 22.3% for the brain, 1.6 ± 21.3% for the liver, -14.3 ± 16.8% for the spleen, -9.5 ± 27.5% for the pancreas, and 3.4 ± 43.2% for the tumor. Relatively large underestimation was observed for the lung (-48.4 ± 16.2%), small intestine (-37.8 ± 19.3%) and large intestine (-33.9 ± 11.0%), due to the partial volume effect arising from the air or feces contained in these organs. In contrast, relatively large overestimation was observed for the kidney (34.3 ± 29.3%), due to the influence of the high uptake in urine. The absolute boron concentrations in tissues/tumors can be estimated from the SUVs on 18 F-FBPA PET using a practical formula. Caution must be exercised in interpreting the estimated boron concentrations in the lung, small intestine and large intestine, to prevent the adverse effects of overexposure, which could occur due to underestimation by partial volume effect using PET.

A growth inhibitory model with SOx influenced effective growth rate for estimation of algal biomass concentration under flue gas atmosphere

USDA-ARS?s Scientific Manuscript database

A theoretical model for the prediction of biomass concentration under real flue gas emission has been developed. The model considers the CO2 mass transfer rate, the critical SOx concentration and its role on pH based inter-conversion of bicarbonate in model building. The calibration and subsequent v...

Modeling of breath methane concentration profiles during exercise on an ergometer*

PubMed Central

Szabó, Anna; Unterkofler, Karl; Mochalski, Pawel; Jandacka, Martin; Ruzsanyi, Vera; Szabó, Gábor; Mohácsi, Árpád; Teschl, Susanne; Teschl, Gerald; King, Julian

2016-01-01

We develop a simple three compartment model based on mass balance equations which quantitatively describes the dynamics of breath methane concentration profiles during exercise on an ergometer. With the help of this model it is possible to estimate the endogenous production rate of methane in the large intestine by measuring breath gas concentrations of methane. PMID:26828421

Regression models for explaining and predicting concentrations of organochlorine pesticides in fish from streams in the United States

USGS Publications Warehouse

Nowell, Lisa H.; Crawford, Charles G.; Gilliom, Robert J.; Nakagaki, Naomi; Stone, Wesley W.; Thelin, Gail; Wolock, David M.

2009-01-01

Empirical regression models were developed for estimating concentrations of dieldrin, total chlordane, and total DDT in whole fish from U.S. streams. Models were based on pesticide concentrations measured in whole fish at 648 stream sites nationwide (1992-2001) as part of the U.S. Geological Survey's National Water Quality Assessment Program. Explanatory variables included fish lipid content, estimates (or surrogates) representing historical agricultural and urban sources, watershed characteristics, and geographic location. Models were developed using Tobit regression methods appropriate for data with censoring. Typically, the models explain approximately 50 to 70% of the variability in pesticide concentrations measured in whole fish. The models were used to predict pesticide concentrations in whole fish for streams nationwide using the U.S. Environmental Protection Agency's River Reach File 1 and to estimate the probability that whole-fish concentrations exceed benchmarks for protection of fish-eating wildlife. Predicted concentrations were highest for dieldrin in the Corn Belt, Texas, and scattered urban areas; for total chlordane in the Corn Belt, Texas, the Southeast, and urbanized Northeast; and for total DDT in the Southeast, Texas, California, and urban areas nationwide. The probability of exceeding wildlife benchmarks for dieldrin and chlordane was predicted to be low for most U.S. streams. The probability of exceeding wildlife benchmarks for total DDT is higher but varies depending on the fish taxon and on the benchmark used. Because the models in the present study are based on fish data collected during the 1990s and organochlorine pesticide residues in the environment continue to decline decades after their uses were discontinued, these models may overestimate present-day pesticide concentrations in fish. ?? 2009 SETAC.

Fuzzy rule based estimation of agricultural diffuse pollution concentration in streams.

PubMed

Singh, Raj Mohan

2008-04-01

Outflow from the agricultural fields carries diffuse pollutants like nutrients, pesticides, herbicides etc. and transports the pollutants into the nearby streams. It is a matter of serious concern for water managers and environmental researchers. The application of chemicals in the agricultural fields, and transport of these chemicals into streams are uncertain that cause complexity in reliable stream quality predictions. The chemical characteristics of applied chemical, percentage of area under the chemical application etc. are some of the main inputs that cause pollution concentration as output in streams. Each of these inputs and outputs may contain measurement errors. Fuzzy rule based model based on fuzzy sets suits to address uncertainties in inputs by incorporating overlapping membership functions for each of inputs even for limited data availability situations. In this study, the property of fuzzy sets to address the uncertainty in input-output relationship is utilized to obtain the estimate of concentrations of a herbicide, atrazine, in a stream. The data of White river basin, a part of the Mississippi river system, is used for developing the fuzzy rule based models. The performance of the developed methodology is found encouraging.

Improving riverine constituent concentration and flux estimation by accounting for antecedent discharge conditions

NASA Astrophysics Data System (ADS)

Zhang, Qian; Ball, William P.

2017-04-01

Regression-based approaches are often employed to estimate riverine constituent concentrations and fluxes based on typically sparse concentration observations. One such approach is the recently developed WRTDS ("Weighted Regressions on Time, Discharge, and Season") method, which has been shown to provide more accurate estimates than prior approaches in a wide range of applications. Centered on WRTDS, this work was aimed at developing improved models for constituent concentration and flux estimation by accounting for antecedent discharge conditions. Twelve modified models were developed and tested, each of which contains one additional flow variable to represent antecedent conditions and which can be directly derived from the daily discharge record. High-resolution (∼daily) data at nine diverse monitoring sites were used to evaluate the relative merits of the models for estimation of six constituents - chloride (Cl), nitrate-plus-nitrite (NOx), total Kjeldahl nitrogen (TKN), total phosphorus (TP), soluble reactive phosphorus (SRP), and suspended sediment (SS). For each site-constituent combination, 30 concentration subsets were generated from the original data through Monte Carlo subsampling and then used to evaluate model performance. For the subsampling, three sampling strategies were adopted: (A) 1 random sample each month (12/year), (B) 12 random monthly samples plus additional 8 random samples per year (20/year), and (C) flow-stratified sampling with 12 regular (non-storm) and 8 storm samples per year (20/year). Results reveal that estimation performance varies with both model choice and sampling strategy. In terms of model choice, the modified models show general improvement over the original model under all three sampling strategies. Major improvements were achieved for NOx by the long-term flow-anomaly model and for Cl by the ADF (average discounted flow) model and the short-term flow-anomaly model. Moderate improvements were achieved for SS, TP, and TKN by the ADF model. By contrast, no such achievement was achieved for SRP by any proposed model. In terms of sampling strategy, performance of all models (including the original) was generally best using strategy C and worst using strategy A, and especially so for SS, TP, and SRP, confirming the value of routinely collecting stormflow samples. Overall, this work provides a comprehensive set of statistical evidence for supporting the incorporation of antecedent discharge conditions into the WRTDS model for estimation of constituent concentration and flux, thereby combining the advantages of two recent developments in water quality modeling.

10 CFR 835.209 - Concentrations of radioactive material in air.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Section 835.209 Energy DEPARTMENT OF ENERGY OCCUPATIONAL RADIATION PROTECTION Standards for Internal and External Exposure § 835.209 Concentrations of radioactive material in air. (a) The derived air... exposures to airborne radioactive material. (b) The estimation of internal dose shall be based on bioassay...

Process model for ammonia volatilization from anaerobic swine lagoons incorporating varying wind speeds and biogas bubbling

USDA-ARS?s Scientific Manuscript database

Ammonia volatilization from treatment lagoons varies widely with the total ammonia concentration, pH, temperature, suspended solids, atmospheric ammonia concentration above the water surface, and wind speed. Ammonia emissions were estimated with a process-based mechanistic model integrating ammonia ...

Inter-Individual Variability in High-Throughput Risk ...

EPA Pesticide Factsheets

We incorporate realistic human variability into an open-source high-throughput (HT) toxicokinetics (TK) modeling framework for use in a next-generation risk prioritization approach. Risk prioritization involves rapid triage of thousands of environmental chemicals, most which have little or no existing TK data. Chemicals are prioritized based on model estimates of hazard and exposure, to decide which chemicals should be first in line for further study. Hazard may be estimated with in vitro HT screening assays, e.g., U.S. EPA’s ToxCast program. Bioactive ToxCast concentrations can be extrapolated to doses that produce equivalent concentrations in body tissues using a reverse TK approach in which generic TK models are parameterized with 1) chemical-specific parameters derived from in vitro measurements and predicted from chemical structure; and 2) with physiological parameters for a virtual population. Here we draw physiological parameters from realistic estimates of distributions of demographic and anthropometric quantities in the modern U.S. population, based on the most recent CDC NHANES data. A Monte Carlo approach, accounting for the correlation structure in physiological parameters, is used to estimate ToxCast equivalent doses for the most sensitive portion of the population. To quantify risk, ToxCast equivalent doses are compared to estimates of exposure rates based on Bayesian inferences drawn from NHANES urinary analyte biomonitoring data. The inclusion

Estimating Ground-Level Particulate Matter (PM) Concentration using Satellite-derived Aerosol Optical Depth (AOD)

NASA Astrophysics Data System (ADS)

Park, Seohui; Im, Jungho

2017-04-01

Atmospheric aerosols are strongly associated with adverse human health effects. In particular, particulate matter less than 10 micrometers and 2.5 micrometers (i.e., PM10 and PM2.5, respectively) can cause cardiovascular and lung diseases such as asthma and chronic obstructive pulmonary disease (COPD). Air quality including PM has typically been monitored using station-based in-situ measurements over the world. However, in situ measurements do not provide spatial continuity over large areas. An alternative approach is to use satellite remote sensing as it provides data over vast areas at high temporal resolution. The literature shows that PM concentrations are related with Aerosol Optical Depth (AOD) that is derived from satellite observations, but it is still difficult to identify PM concentrations directly from AOD. Some studies used statistical approaches for estimating PM concentrations from AOD while some others combined numerical models and satellite-derived AOD. In this study, satellite-derived products were used to estimate ground PM concentrations based on machine learning over South Korea. Satellite-derived products include AOD from Geostationary Ocean Color Imager (GOCI), precipitation from Tropical Rainfall Measuring Mission (TRMM), soil moisture from AMSR-2, elevation from Shuttle Radar Topography Mission (SRTM), and land cover, land surface temperature and normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS). PM concentrations data were collected from 318 stations. A statistical ordinary least squares (OLS) approach was also tested and compared with the machine learning approach (i.e., random forest). PM concentration was estimated during spring season (from March to May) in 2015 that typically shows high concentration of PM. The randomly selected 80% of data were used for model calibration and the remaining 20% were used for validation. The developed models were further tested for prediction of PM concentration. Results show that the estimation of PM10 was better than that of PM2.5 for both approaches. The performance of machine learning random forest was better (R2=0.53 and RMSE=17.74µm/m3 for PM10; R2=0.36 and RMSE=26.17 µm/m3 for PM2.5) than the statistical OLS approach (R2=0.13 and RMSE=23.66µm/m3 for PM10; R2=0.09 and RMSE=27.74 µm/m3 for PM2.5). However, both approaches did not fully model the entire dynamic range of PM concentrations, especially for very high concentrations, resulting in moderate underestimation.

Quality control and gap-filling of PM10 daily mean concentrations with the best linear unbiased estimator.

PubMed

Sozzi, R; Bolignano, A; Ceradini, S; Morelli, M; Petenko, I; Argentini, S

2017-10-15

According to the European Directive 2008/50/CE, the air quality assessment consists in the measurement of the concentration fields, and the evaluation of the mean, number of exceedances, etc. of some chemical species dangerous to human health. The measurements provided by an air quality ground-based monitoring network are the main information source but the availability of these data is often limited by several technical and operational problems. In this paper, the best linear unbiased estimator (BLUE) is proposed to validate the pollutant concentration values and to fill the gaps in the measurement of time series collected by a monitoring network. The BLUE algorithm is tested using the daily mean concentrations of particulate matter having aerodynamic diameter less than 10 μ (PM 10 concentrations) measured by the air quality monitoring sensors operating in the Lazio Region in Italy. The comparison between the estimated and measured data evidences an error comparable with the measurement uncertainty. Due to its simplicity and reliability, the BLUE will be used in the routine quality test procedures of the Lazio air quality monitoring network measurements.

Systematic parameter estimation in data-rich environments for cell signalling dynamics

PubMed Central

Nim, Tri Hieu; Luo, Le; Clément, Marie-Véronique; White, Jacob K.; Tucker-Kellogg, Lisa

2013-01-01

Motivation: Computational models of biological signalling networks, based on ordinary differential equations (ODEs), have generated many insights into cellular dynamics, but the model-building process typically requires estimating rate parameters based on experimentally observed concentrations. New proteomic methods can measure concentrations for all molecular species in a pathway; this creates a new opportunity to decompose the optimization of rate parameters. Results: In contrast with conventional parameter estimation methods that minimize the disagreement between simulated and observed concentrations, the SPEDRE method fits spline curves through observed concentration points, estimates derivatives and then matches the derivatives to the production and consumption of each species. This reformulation of the problem permits an extreme decomposition of the high-dimensional optimization into a product of low-dimensional factors, each factor enforcing the equality of one ODE at one time slice. Coarsely discretized solutions to the factors can be computed systematically. Then the discrete solutions are combined using loopy belief propagation, and refined using local optimization. SPEDRE has unique asymptotic behaviour with runtime polynomial in the number of molecules and timepoints, but exponential in the degree of the biochemical network. SPEDRE performance is comparatively evaluated on a novel model of Akt activation dynamics including redox-mediated inactivation of PTEN (phosphatase and tensin homologue). Availability and implementation: Web service, software and supplementary information are available at www.LtkLab.org/SPEDRE Supplementary information: Supplementary data are available at Bioinformatics online. Contact: LisaTK@nus.edu.sg PMID:23426255

Mathematical modeling improves EC50 estimations from classical dose-response curves.

PubMed

Nyman, Elin; Lindgren, Isa; Lövfors, William; Lundengård, Karin; Cervin, Ida; Sjöström, Theresia Arbring; Altimiras, Jordi; Cedersund, Gunnar

2015-03-01

The β-adrenergic response is impaired in failing hearts. When studying β-adrenergic function in vitro, the half-maximal effective concentration (EC50 ) is an important measure of ligand response. We previously measured the in vitro contraction force response of chicken heart tissue to increasing concentrations of adrenaline, and observed a decreasing response at high concentrations. The classical interpretation of such data is to assume a maximal response before the decrease, and to fit a sigmoid curve to the remaining data to determine EC50 . Instead, we have applied a mathematical modeling approach to interpret the full dose-response curve in a new way. The developed model predicts a non-steady-state caused by a short resting time between increased concentrations of agonist, which affect the dose-response characterization. Therefore, an improved estimate of EC50 may be calculated using steady-state simulations of the model. The model-based estimation of EC50 is further refined using additional time-resolved data to decrease the uncertainty of the prediction. The resulting model-based EC50 (180-525 nm) is higher than the classically interpreted EC50 (46-191 nm). Mathematical modeling thus makes it possible to re-interpret previously obtained datasets, and to make accurate estimates of EC50 even when steady-state measurements are not experimentally feasible. The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database, and may be accessed at http://jjj.bio.vu.nl/database/nyman. © 2015 FEBS.

Space photovoltaic modules based on reflective optics

NASA Technical Reports Server (NTRS)

Andreev, V. M.; Larionov, V. R.; Rumyantsev, V. D.; Shvarts, M. Z.

1995-01-01

The conceptual design and experimental results for two types of space application concentrator photovoltaic modules, employing reflective optical elements, are presented. The first type is based on the use of compound parabolic concentrators, the second type is based on the use of line-focus parabolic troughs. Lightweight concentrators are formed with nickel foil coated silver with a diamond-like carbon layer protection. Secondary optical elements, including lenses and cones, are introduced for a better matching of concentrators and solar cells. Both types of modules are characterized by concentration ratios in the range 20x to 30x, depending on the chosen range of misorientation angles. The estimated specific parameters of these modules operating with single junction AlGaAs/GaAs solar cells are 240 W/sq m and 3 kg/sq m.

Spatio-temporal PM and AOD estimations over Northeast Asia during DRAGON NE-Asia campaign

NASA Astrophysics Data System (ADS)

Park, M.; Song, C.; Kim, J.

2013-12-01

Particulate matter (PM) is closely related to human health, air quality, and climate changes. It has been directly measured on the surface level. However, ground-based measurements have a limitation in spatial coverage of PM concentrations. In order to overcome this spatial limitation of ground measurements, AOD, which is considered as a proxy to PM concentration, was used in this study. AOD was first utilized to figure out the characteristics of PM and was then used to estimate the PM concentrations in Northeast Asia during the DRAGON Northeast-Asia campaign (March-May 2012), using CMAQ-estimated AOD, COMS/GOCI-retrieved AOD, and the AOD data from the DRAGON NE-Asia campaign. First of all, current emission inventories (MEIC and INTEX-B based emission inventories) were evaluated to improve CMAQ modeling results. Next, several algorithms to convert aerosol composition to AOD were evaluated using intensive measurement data from the DRAGON NE-Asia campaign. The accuracy of the CMAQ-estimated AOD was further evaluated with hourly observing GOCI-retrieved AOD. After the evaluation, CMAQ-calculated AOD was mathematically combined with GOCI-retrieved AOD via data assimilation. After this, AERONET AOD measured by the DRAGON NE-Asia campaign was again combined with the assimilated AOD from CMAQ and GOCI AODs to produce more accurate spatio-temporal AOD fields over Northeast Asia. Using several relationships between PM (PM10 and PM2.5) and AOD, the best surface-PM concentrations over the entire domain were calculated. It was then evaluated with ground-based PM2.5 measurements from the DRAGON NE-Asia campaign. A good agreement between estimated PM2.5 and measured PM2.5 over the domain was found. Finally, the PM and AOD information was used to investigate the effects of transboundary PM pollution from China to the Korean peninsula.

Global Marine Productivity and Living-Phytoplankton Carbon Biomass Estimated from a Physiological Growth Model

NASA Astrophysics Data System (ADS)

Arteaga, L.; Pahlow, M.; Oschlies, A.

2016-02-01

Primay production by marine phytoplankton essentially drives the oceanic biological carbon pump. Global productivity estimates are commonly founded on chlorophyll-based primary production models. However, a major drawback of most of these models is that variations in chlorophyll concentration do not necessarily account for changes in phytoplankton biomass resulting from the physiological regulation of the chlorophyll-to-carbon ratio (Chl:C). Here we present phytoplankton production rates and surface phytoplankton C concentrations for the global ocean for 2005-2010, obtained by combining satellite Chl observations with a mechanistic model for the acclimation of phytoplankton stoichiometry to variations in nutrients, light and temperature. We compare our inferred phytoplankton C concentrations with an independent estimate of surface particulate organic carbon (POC) to identify for the first time the global contribution of living phytoplankton to total POC in the surface ocean. Our annual primary production (46 Pg C yr-1) is in good agreement with other C-based model estimates obtained from satellite observations. We find that most of the oligotrophic surface ocean is dominated by living phytoplankton biomass (between 30-70% of total particulate carbon). Lower contributions are found in the tropical Pacific (10-30% phytoplankton) and the Southern Ocean (≈ 10%). Our method provides a novel analytical tool for identifying changes in marine plankton communities and carbon cycling.

An initial investigation of multidimensional flow and transverse mixing characteristics of the Ohio River near Cincinnati, Ohio

USGS Publications Warehouse

Holtschlag, David J.

2009-01-01

Two-dimensional hydrodynamic and transport models were applied to a 34-mile reach of the Ohio River from Cincinnati, Ohio, upstream to Meldahl Dam near Neville, Ohio. The hydrodynamic model was based on the generalized finite-element hydrodynamic code RMA2 to simulate depth-averaged velocities and flow depths. The generalized water-quality transport code RMA4 was applied to simulate the transport of vertically mixed, water-soluble constituents that have a density similar to that of water. Boundary conditions for hydrodynamic simulations included water levels at the U.S. Geological Survey water-level gaging station near Cincinnati, Ohio, and flow estimates based on a gate rating at Meldahl Dam. Flows estimated on the basis of the gate rating were adjusted with limited flow-measurement data to more nearly reflect current conditions. An initial calibration of the hydrodynamic model was based on data from acoustic Doppler current profiler surveys and water-level information. These data provided flows, horizontal water velocities, water levels, and flow depths needed to estimate hydrodynamic parameters related to channel resistance to flow and eddy viscosity. Similarly, dye concentration measurements from two dye-injection sites on each side of the river were used to develop initial estimates of transport parameters describing mixing and dye-decay characteristics needed for the transport model. A nonlinear regression-based approach was used to estimate parameters in the hydrodynamic and transport models. Parameters describing channel resistance to flow (Manning’s “n”) were estimated in areas of deep and shallow flows as 0.0234, and 0.0275, respectively. The estimated RMA2 Peclet number, which is used to dynamically compute eddy-viscosity coefficients, was 38.3, which is in the range of 15 to 40 that is typically considered appropriate. Resulting hydrodynamic simulations explained 98.8 percent of the variability in depth-averaged flows, 90.0 percent of the variability in water levels, 93.5 percent of the variability in flow depths, and 92.5 percent of the variability in velocities. Estimates of the water-quality-transport-model parameters describing turbulent mixing characteristics converged to different values for the two dye-injection reaches. For the Big Indian Creek dye-injection study, an RMA4 Peclet number of 37.2 was estimated, which was within the recommended range of 15 to 40, and similar to the RMA2 Peclet number. The estimated dye-decay coefficient was 0.323. Simulated dye concentrations explained 90.2 percent of the variations in measured dye concentrations for the Big Indian Creek injection study. For the dye-injection reach starting downstream from Twelvemile Creek, however, an RMA4 Peclet number of 173 was estimated, which is far outside the recommended range. Simulated dye concentrations were similar to measured concentration distributions at the first four transects downstream from the dye-injection site that were considered vertically mixed. Farther downstream, however, simulated concentrations did not match the attenuation of maximum concentrations or cross-channel transport of dye that were measured. The difficulty of determining a consistent RMA4 Peclet was related to the two-dimension model assumption that velocity distributions are closely approximated by their depth-averaged values. Analysis of velocity data showed significant variations in velocity direction with depth in channel reaches with curvature. Channel irregularities (including curvatures, depth irregularities, and shoreline variations) apparently produce transverse currents that affect the distribution of constituents, but are not fully accounted for in a two-dimensional model. The two-dimensional flow model, using channel resistance to flow parameters of 0.0234 and 0.0275 for deep and shallow areas, respectively, and an RMA2 Peclet number of 38.3, and the RMA4 transport model with a Peclet number of 37.2, may have utility for emergency-planning purposes. Emergency-response efforts would be enhanced by continuous streamgaging records downstream from Meldahl Dam, real-time water-quality monitoring, and three-dimensional modeling. Decay coefficients are constituent specific.

Determining the Uncertainties in Prescribed Burn Emissions Through Comparison of Satellite Estimates to Ground-based Estimates and Air Quality Model Evaluations in Southeastern US

NASA Astrophysics Data System (ADS)

Odman, M. T.; Hu, Y.; Russell, A. G.

2016-12-01

Prescribed burning is practiced throughout the US, and most widely in the Southeast, for the purpose of maintaining and improving the ecosystem, and reducing the wildfire risk. However, prescribed burn emissions contribute significantly to the of trace gas and particulate matter loads in the atmosphere. In places where air quality is already stressed by other anthropogenic emissions, prescribed burns can lead to major health and environmental problems. Air quality modeling efforts are under way to assess the impacts of prescribed burn emissions. Operational forecasts of the impacts are also emerging for use in dynamic management of air quality as well as the burns. Unfortunately, large uncertainties exist in the process of estimating prescribed burn emissions and these uncertainties limit the accuracy of the burn impact predictions. Prescribed burn emissions are estimated by using either ground-based information or satellite observations. When there is sufficient local information about the burn area, the types of fuels, their consumption amounts, and the progression of the fire, ground-based estimates are more accurate. In the absence of such information satellites remain as the only reliable source for emission estimation. To determine the level of uncertainty in prescribed burn emissions, we compared estimates derived from a burn permit database and other ground-based information to the estimates by the Biomass Burning Emissions Product derived from a constellation of NOAA and NASA satellites. Using these emissions estimates we conducted simulations with the Community Multiscale Air Quality (CMAQ) model and predicted trace gas and particulate matter concentrations throughout the Southeast for two consecutive burn seasons (2015 and 2016). In this presentation, we will compare model predicted concentrations to measurements at monitoring stations and evaluate if the differences are commensurate with our emission uncertainty estimates. We will also investigate if spatial and temporal patterns in the differences reveal the sources of the uncertainty in the prescribed burn emission estimates.

Establishment and application of the estimation model for pollutant concentrfation in agriculture drain

NASA Astrophysics Data System (ADS)

Li, Qiangkun; Hu, Yawei; Jia, Qian; Song, Changji

2018-02-01

It is the key point of quantitative research on agricultural non-point source pollution load, the estimation of pollutant concentration in agricultural drain. In the guidance of uncertainty theory, the synthesis of fertilization and irrigation is used as an impulse input to the farmland, meanwhile, the pollutant concentration in agricultural drain is looked as the response process corresponding to the impulse input. The migration and transformation of pollutant in soil is expressed by Inverse Gaussian Probability Density Function. The law of pollutants migration and transformation in soil at crop different growth periods is reflected by adjusting parameters of Inverse Gaussian Distribution. Based on above, the estimation model for pollutant concentration in agricultural drain at field scale was constructed. Taking the of Qing Tong Xia Irrigation District in Ningxia as an example, the concentration of nitrate nitrogen and total phosphorus in agricultural drain was simulated by this model. The results show that the simulated results accorded with measured data approximately and Nash-Sutcliffe coefficients were 0.972 and 0.964, respectively.

MRI contrast agent concentration and tumor interstitial fluid pressure.

PubMed

Liu, L J; Schlesinger, M

2016-10-07

The present work describes the relationship between tumor interstitial fluid pressure (TIFP) and the concentration of contrast agent for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). We predict the spatial distribution of TIFP based on that of contrast agent concentration. We also discuss the cases for estimating tumor interstitial volume fraction (void fraction or porosity of porous medium), ve, and contrast volume transfer constant, K(trans), by measuring the ratio of contrast agent concentration in tissue to that in plasma. A linear fluid velocity distribution may reflect a quadratic function of TIFP distribution and lead to a practical method for TIFP estimation. To calculate TIFP, the parameters or variables should preferably be measured along the direction of the linear fluid velocity (this is in the same direction as the gray value distribution of the image, which is also linear). This method may simplify the calculation for estimating TIFP. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Burden of disease attributed to ambient air pollution in Thailand: A GIS-based approach

PubMed Central

Pinichka, Chayut; Makka, Nuttapat; Sukkumnoed, Decharut; Chariyalertsak, Suwat; Inchai, Puchong

2017-01-01

Background Growing urbanisation and population requiring enhanced electricity generation as well as the increasing numbers of fossil fuel in Thailand pose important challenges to air quality management which impacts on the health of the population. Mortality attributed to ambient air pollution is one of the sustainable development goals (SDGs). We estimated the spatial pattern of mortality burden attributable to selected ambient air pollution in 2009 based on the empirical evidence in Thailand. Methods We estimated the burden of disease attributable to ambient air pollution based on the comparative risk assessment (CRA) framework developed by the World Health Organization (WHO) and the Global Burden of Disease study (GBD). We integrated geographical information systems (GIS)-based exposure assessments into spatial interpolation models to estimate ambient air pollutant concentrations, the population distribution of exposure and the concentration-response (CR) relationship to quantify ambient air pollution exposure and associated mortality. We obtained air quality data from the Pollution Control Department (PCD) of Thailand surface air pollution monitoring network sources and estimated the CR relationship between relative risk (RR) and concentration of air pollutants from the epidemiological literature. Results We estimated 650–38,410 ambient air pollution-related fatalities and 160–5,982 fatalities that could have been avoided with a 20 reduction in ambient air pollutant concentrations. The summation of population-attributable fraction (PAF) of the disease burden for all-causes mortality in adults due to NO2 and PM2.5 were the highest among all air pollutants at 10% and 7.5%, respectively. The PAF summation of PM2.5 for lung cancer and cardiovascular disease were 16.8% and 14.6% respectively and the PAF summations of mortality attributable to PM10 was 3.4% for all-causes mortality, 1.7% for respiratory and 3.8% for cardiovascular mortality, while the PAF summation of mortality attributable to NO2 was 7.8% for respiratory mortality in Thailand. Conclusion Mortality due to ambient air pollution in Thailand varies across the country. Geographical distribution estimates can identify high exposure areas for planners and policy-makers. Our results suggest that the benefits of a 20% reduction in ambient air pollution concentration could prevent up to 25% of avoidable fatalities each year in all-causes, respiratory and cardiovascular categories. Furthermore, our findings can provide guidelines for future epidemiological investigations and policy decisions to achieve the SDGs. PMID:29267319

Estimating physiological skin parameters from hyperspectral signatures

NASA Astrophysics Data System (ADS)

Vyas, Saurabh; Banerjee, Amit; Burlina, Philippe

2013-05-01

We describe an approach for estimating human skin parameters, such as melanosome concentration, collagen concentration, oxygen saturation, and blood volume, using hyperspectral radiometric measurements (signatures) obtained from in vivo skin. We use a computational model based on Kubelka-Munk theory and the Fresnel equations. This model forward maps the skin parameters to a corresponding multiband reflectance spectra. Machine-learning-based regression is used to generate the inverse map, and hence estimate skin parameters from hyperspectral signatures. We test our methods using synthetic and in vivo skin signatures obtained in the visible through the short wave infrared domains from 24 patients of both genders and Caucasian, Asian, and African American ethnicities. Performance validation shows promising results: good agreement with the ground truth and well-established physiological precepts. These methods have potential use in the characterization of skin abnormalities and in minimally-invasive prescreening of malignant skin cancers.

Effects of spatially variable resolution on field-scale estimates of tracer concentration from electrical inversions using Archie's law

USGS Publications Warehouse

Singha, Kamini; Gorelick, Steven M.

2006-01-01

Two important mechanisms affect our ability to estimate solute concentrations quantitatively from the inversion of field-scale electrical resistivity tomography (ERT) data: (1) the spatially variable physical processes that govern the flow of current as well as the variation of physical properties in space and (2) the overparameterization of inverse models, which requires the imposition of a smoothing constraint (regularization) to facilitate convergence of the inverse solution. Based on analyses of field and synthetic data, we find that the ability of ERT to recover the 3D shape and magnitudes of a migrating conductive target is spatially variable. Additionally, the application of Archie's law to tomograms from field ERT data produced solute concentrations that are consistently less than 10% of point measurements collected in the field and estimated from transport modeling. Estimates of concentration from ERT using Archie's law only fit measured solute concentrations if the apparent formation factor is varied with space and time and allowed to take on unreasonably high values. Our analysis suggests that the inability to find a single petrophysical relation in space and time between concentration and electrical resistivity is largely an effect of two properties of ERT surveys: (1) decreased sensitivity of ERT to detect the target plume with increasing distance from the electrodes and (2) the smoothing imprint of regularization used in inversion.

Estimation of Satellite-Based SO42- and NH4+ Composition of Ambient Fine Particulate Matter Over China Using Chemical Transport Model

NASA Astrophysics Data System (ADS)

Si, Y.; Li, S.; Chen, L.; Yu, C.; Zhu, W.

2018-04-01

Epidemiologic and health impact studies have examined the chemical composition of ambient PM2.5 in China but have been constrained by the paucity of long-term ground measurements. Using the GEOS-Chem chemical transport model and satellite-derived PM2.5 data, sulfate and ammonium levels were estimated over China from 2004 to 2014. A comparison of the satellite-estimated dataset with model simulations based on ground measurements obtained from the literature indicated our results are more accurate. Using satellite-derived PM2.5 data with a spatial resolution of 0.1° × 0.1°, we further presented finer satellite-estimated sulfate and ammonium concentrations in anthropogenic polluted regions, including the NCP (the North China Plain), the SCB (the Sichuan Basin) and the PRD (the Pearl River Delta). Linear regression results obtained on a national scale yielded an r value of 0.62, NMB of -35.9 %, NME of 48.2 %, ARB_50 % of 53.68 % for sulfate and an r value of 0.63, slope of 0.67, and intercept of 5.14 for ammonium. In typical regions, the satellite-derived dataset was significantly robust. Based on the satellite-derived dataset, the spatial-temporal variation of 11-year annual average satellite-derived SO42- and NH4+ concentrations and time series of monthly average concentrations were also investigated. On a national scale, both exhibited a downward trend each year between 2004 and 2014 (SO42-: -0.61 %; NH4+: -0.21 %), large values were mainly concentrated in the NCP and SCB. For regions captured at a finer resolution, the inter-annual variation trends presented a positive trend over the periods 2004-2007 and 2008-2011, followed by a negative trend over the period 2012-2014, and sulfate concentrations varied appreciably. Moreover, the seasonal distributions of the 11-year satellite-derived dataset over China were presented. The distribution of both sulfate and ammonium concentrations exhibited seasonal characteristics, with the seasonal concentrations ranking as follows: winter > summer > autumn > spring. High concentrations of these species were concentrated in the NCP and SCB, originating from coal-fired power plants and agricultural activities, respectively. Efforts to reduce sulfur dioxide (SO2) emissions have yielded remarkable results since the government has adopted stricter control measures in recent years. Moreover, ammonia emissions should be controlled while reducing the concentration of sulfur, nitrogen and particulate matter. This study provides an assessment of the population's exposure to certain chemical components.

At the forefront: evidence of the applicability of using environmental DNA to quantify the abundance of fish populations in natural lentic waters with additional sampling considerations

USGS Publications Warehouse

Klobucar, Stephen L.; Rodgers, Torrey W.; Budy, Phaedra

2017-01-01

Environmental DNA (eDNA) sampling has proven to be a valuable tool for detecting species in aquatic ecosystems. Within this rapidly evolving field, a promising application is the ability to obtain quantitative estimates of relative species abundance based on eDNA concentration rather than traditionally labor-intensive methods. We investigated the relationship between eDNA concentration and Arctic char (Salvelinus alpinus) abundance in five well-studied natural lakes; additionally, we examined the effects of different temporal (e.g., season) and spatial (e.g., depth) scales on eDNA concentration. Concentrations of eDNA were linearly correlated with char population estimates ( = 0.78) and exponentially correlated with char densities ( = 0.96 by area; 0.82 by volume). Across lakes, eDNA concentrations were greater and more homogeneous in the water column during mixis; however, when stratified, eDNA concentrations were greater in the hypolimnion. Overall, our findings demonstrate that eDNA techniques can produce effective estimates of relative fish abundance in natural lakes. These findings can guide future studies to improve and expand eDNA methods while informing research and management using rapid and minimally invasive sampling.

Analysis of glycols, glycol ethers, and other volatile organic compounds present in household water-based hand pump sprays.

PubMed

Kawakami, Tsuyoshi; Isama, Kazuo; Tanaka-Kagawa, Toshiko; Jinnno, Hideto

2017-11-10

The aim of this investigation is to clarify the types and concentrations of VOCs present in various commercial household water-based hand pump spray products used in Japan, and to estimate their average concentrations in indoor air when the spray product is used. We selected glycol and glycol ethers as the main target compounds, as these chemicals were detected at high frequencies and concentrations in a national survey of Japanese indoor air pollution. The extraction of these chemicals using graphite carbon cartridges was examined, with good recoveries and reproducibilities being obtained. Eighteen chemicals were analyzed in 54 commercial products and 8 chemicals were detected. More specifically, dipropylene glycol (DPG) was present in 44 samples (1.1 × 10 1 -1.8 × 10 4 μg/mL); propylene glycol (PG) was present in 22 samples (1.5 × 10 1 -2.9 × 10 4 μg/mL); diethylene glycol monoethyl ether (DGMEE) was found in 15 samples (trace amount-1.9 × 10 3 μg/mL); diethylene glycol (DEG) was present in 9 samples (1.0 × 10 1 -2.4 × 10 3 μg/mL); 1,3-butandiol (13BG) was found in 5 samples (trace amount-7.4 × 10 3 μg/mL); 2-ethyl-1-hexanol (2E1H) was detected in 5 samples (3.2 × 10 -1 -4.4 × 10 1 μg/mL); diethylene glycol monobutyl ether (DGMBE) was present in 4 samples (2.1 × 10 1 -7.1 × 10 1 μg/mL); and 3-methoxy-3-methylbutanol (MMB) was found in 2 samples (2.4 × 10 1 -4.7 × 10 2 μg/mL). In addition, the average concentrations of these chemicals in indoor air were estimated using their maximum concentrations observed in the spray product. The estimated average concentrations of the chemicals in indoor air were determined to range between 1.0 × 10 -2 and 1.0 mg/m 3 , with the exception of 2E1H and DGMBE. Furthermore, the estimated average concentrations of PG, 13BG, and DGMEE in indoor air were comparable to or higher than those reported in a national survey of Japanese indoor air pollution. It therefore appeared that household water-based hand pump sprays may contribute to the presence of these chemicals in indoor air. In contrast, estimated average concentrations of 2E1H in indoor air were low, its concentrations observed in a national survey of Japanese indoor air pollution are likely due to the use of plasticizers and paints.

A bootstrap estimation scheme for chemical compositional data with nondetects

USGS Publications Warehouse

Palarea-Albaladejo, J; Martín-Fernández, J.A; Olea, Ricardo A.

2014-01-01

The bootstrap method is commonly used to estimate the distribution of estimators and their associated uncertainty when explicit analytic expressions are not available or are difficult to obtain. It has been widely applied in environmental and geochemical studies, where the data generated often represent parts of whole, typically chemical concentrations. This kind of constrained data is generically called compositional data, and they require specialised statistical methods to properly account for their particular covariance structure. On the other hand, it is not unusual in practice that those data contain labels denoting nondetects, that is, concentrations falling below detection limits. Nondetects impede the implementation of the bootstrap and represent an additional source of uncertainty that must be taken into account. In this work, a bootstrap scheme is devised that handles nondetects by adding an imputation step within the resampling process and conveniently propagates their associated uncertainly. In doing so, it considers the constrained relationships between chemical concentrations originated from their compositional nature. Bootstrap estimates using a range of imputation methods, including new stochastic proposals, are compared across scenarios of increasing difficulty. They are formulated to meet compositional principles following the log-ratio approach, and an adjustment is introduced in the multivariate case to deal with nonclosed samples. Results suggest that nondetect bootstrap based on model-based imputation is generally preferable. A robust approach based on isometric log-ratio transformations appears to be particularly suited in this context. Computer routines in the R statistical programming language are provided. 

Emission of polybrominated diphenyl ethers (PBDEs) in use of electric/electronic equipment and recycling of e-waste in Korea.

PubMed

Park, Jong-Eun; Kang, Young-Yeul; Kim, Woo-Il; Jeon, Tae-Wan; Shin, Sun-Kyoung; Jeong, Mi-Jeong; Kim, Jong-Guk

2014-02-01

The emission rates of polybrominated diphenyl ethers (PBDEs) from electric/electronic products during their use and disposal were estimated. E-wastes, including televisions and refrigerators, gathered at recycling centers were also analyzed to estimate their emissions. The average concentrations of PBDEs in TV rear covers produced before and after the year 2000 were 145,027 mg/kg and 14,049 mg/kg, respectively. The PBDEs concentration in TV front covers was lower than the concentration in TV rear covers. The concentration in the components of the refrigerator samples ranged from ND to 445 mg/kg. We estimated the atmospheric emissions of PBDEs based on the concentrations. The annual emissions from TV rear covers produced before 2000 were calculated to be approximately 162.1 kg and after 2000, the annual emissions were 18.7 kg. Refrigerators showed the lowest annual emissions of PBDEs (0.7 kg). The atmospheric concentrations were also measured to calculate emissions generated during the recycling process. The highest concentration was 16.86 ng/m(3) emitted from the TV sets during the dismantling process. The concentrations of PBDEs generated in the plastic processing field ranged from 2.05 to 5.43 ng/m(3) depending on the products, and ambient air in open-air yards showed concentrations in the range of 0.32 to 5.55 ng/m(3). Emission factors for the recycling process were calculated using the observed concentrations. The estimated emissions according to the emission factors ranged from 0.3×10(-1) to 90.3 kg/year for open-air yards and from 0.1×10(-1) to 292.7 kg/year for the dismantling and crushing processes of TV set, depending on the production year. © 2013 Elsevier B.V. All rights reserved.

Trace elements in animal-based food from Shanghai markets and associated human daily intake and uptake estimation considering bioaccessibility.

PubMed

Lei, Bingli; Chen, Liang; Hao, Ying; Cao, Tiehua; Zhang, Xinyu; Yu, Yingxin; Fu, Jiamo

2013-10-01

The concentrations of four human essential trace elements [iron (Fe), manganese (Mn), zinc (Zn), chromium (Cr)] and non-essential elements [cadmium (Cd), lead (Pb), arsenic (As), and mercury (Hg)] in eighteen animal-based foods including meat, fish, and shellfish collected from markets in Shanghai, China, were analyzed, and the associated human daily intake and uptake considering bioaccessibility were estimated. The mean concentration ranges for eight trace elements measured in the foods were 3.98-131µgg(-1) for Fe, 0.437-18.5µgg(-1) for Mn, 5.47-53.8µgg(-1) for Zn, none detected-0.101µgg(-1) for Cr, 2.88×10(-4)-2.48×10(-2)µgg(-1) for Cd, 1.18×10(-3)-0.747µgg(-1) for Pb, none detected-0.498µgg(-1) for As, and 8.98×10(-4)-6.52×10(-2)µgg(-1) for Hg. The highest mean concentrations of four human essential elements were all found in shellfish. For all the trace elements, the observed mean concentrations are mostly in agreement with the reported values around the world. The total daily intake of trace elements via ingestion of animal-based food via an average Shanghai resident was estimated as 7371µgd(-1) for the human essential elements and 13.0µgd(-1) for the human non-essential elements, but the uptake decreased to 4826µgd(-1) and 6.90µgd(-1), respectively, after trace element bioaccessibility was considered. Livestock and fish for human essential and non-essential elements, respectively, were the main contributor, no matter whether the bioaccessibility was considered or not. Risk estimations showed that the intake and uptake of a signal trace element for an average Shanghai resident via ingestion animal-based foods from Shanghai markets do not exceed the recommended dietary allowance values; consequently, a health risk situation is not indicated. Copyright © 2013. Published by Elsevier Inc.

Densities of Serotonergic Projections as Revealed by In Situ Synthesised Labelled α-Methyl-Serotonin: an Autoradiographic Evaluation

PubMed Central

Nishi, Kyoko; Takahashi, Sho

2013-01-01

An estimate of serotonergic innervation density and regional serotonin (5-HT) concentration was performed from the distribution of in situ produced labelled α-methyl-serotonin. Rats were injected with (3H) labelled α-methyl-L-tryptophan and the tracer distribution was measured using the autoradiographic method 14 days following the injection. In a separate experiment, the total brain concentration of 5-HT in the rat brain was found to be 2.4 ± 0.2 nmol/g. Based on this, and the assumption that the specific activity of in situ produced α-methyl-serotonin is the same as that of the injected tracer, it was possible to estimate the regional concentrations of 5-HT and the relative concentration of regional serotonergic innervations. It was found, and reported for the first time here, that the highest concentration of serotonergic innervation is present in the solitary nucleus. Regionally measured 5-HT concentrations accord well with previously reported concentrations of 5-HT. PMID:21472458

Genetic parameter estimation for milk β-hydroxybutyrate and acetone in early lactation and its association with fat to protein ratio and energy balance in Korean Holstein cattle.

PubMed

Ranaraja, Umanthi; Cho, KwangHyun; Park, MiNa; Kim, SiDong; Lee, SeokHyun; Do, ChangHee

2018-06-01

The objective of this study was to estimate the genetic parameters for milk β-hydroxybutyrate (BHBA), acetone (Ac), fat protein ratio (FPR), and energy balance (EB) using milk test day records and investigate the effect of early lactation FPR and EB on milk ketone body concentrations. Total 262,940 test-day records collected from Korea Animal Improvement Association during the period of 2012 to 2016 were used in this study. BHBA and Ac concentrations in milk were measured by Fourier transform infrared spectroscopy (FTIR). FPR values were obtained using test day records of fat and protein percentage. EB was calculated using previously developed equation based on parity, lactation week, and milk composition data. Genetic parameters were estimated by restricted maximum likelihood procedure based on repeatability model using Wombat program. Elevated milk BHBA and Ac concentrations were observed during the early lactation under the negative energy balance. Milk FPR tends to decrease with the decreasing ketone body concentrations. Heritability estimates for milk BHBA, Ac, EB, and FPR ranged from 0.09 to 0.14, 0.23 to 0.31, 0.19 to 0.52, and 0.16 to 0.42 respectively at parity 1, 2, 3, and 4. The overall heritability for BHBA, Ac, EB and FPR were 0.29, 0.32, 0.58, and 0.38 respectively. A common pattern was observed in heritability of EB and FPR along with parities. FPR and EB can be suggested as potential predictors for risk of hyperketonemia. The heritability estimates of milk BHBA, Ac, EB, and FPR indicate that the selective breeding may contribute to maintaining the milk ketone bodies at optimum level during early lactation.

Air radon equilibrium factor measurement in a Waste Water Pre-Treatment Plant

NASA Astrophysics Data System (ADS)

Martinez, J. E.; Juste, B.; Ortiz, J.; Martorell, S.; Verdu, G.

2017-11-01

We analyze in this paper a Waste Water Pre-Treatment Plant (WWTP) located at the Mediterranean coast with air radon concentration above Spanish action level (600 Bq per cubic meter). This paper presents a method for radon equilibrium determination by gamma spectrometry measuring of the radon progeny concentrations in the air, in order to estimate WWTP workers effective dose more exactly. The method is based on simultaneous sampling of air through a filter paper and alpha spectrometry measurement of radon activity concentration in the air. According to the measured radon activity concentration in the air of 368±45 Bq/m3 the equilibrium factor between radon and progenies is estimated to be F=0.27, which is in good agreement with expected values.

[Research on hyperspectral remote sensing in monitoring snow contamination concentration].

PubMed

Tang, Xu-guang; Liu, Dian-wei; Zhang, Bai; Du, Jia; Lei, Xiao-chun; Zeng, Li-hong; Wang, Yuan-dong; Song, Kai-shan

2011-05-01

Contaminants in the snow can be used to reflect regional and global environmental pollution caused by human activities. However, so far, the research on space-time monitoring of snow contamination concentration for a wide range or areas difficult for human to reach is very scarce. In the present paper, based on the simulated atmospheric deposition experiments, the spectroscopy technique method was applied to analyze the effect of different contamination concentration on the snow reflectance spectra. Then an evaluation of snow contamination concentration (SCC) retrieval methods was conducted using characteristic index method (SDI), principal component analysis (PCA), BP neural network and RBF neural network method, and the estimate effects of four methods were compared. The results showed that the neural network model combined with hyperspectral remote sensing data could estimate the SCC well.

[Application of predictive model to estimate concentrations of chemical substances in the work environment].

PubMed

Kupczewska-Dobecka, Małgorzata; Czerczak, Sławomir; Jakubowski, Marek; Maciaszek, Piotr; Janasik, Beata

2010-01-01

Based on the Estimation and Assessment of Substance Exposure (EASE) predictive model implemented into the European Union System for the Evaluation of Substances (EUSES 2.1.), the exposure to three chosen organic solvents: toluene, ethyl acetate and acetone was estimated and compared with the results of measurements in workplaces. Prior to validation, the EASE model was pretested using three exposure scenarios. The scenarios differed in the decision tree of pattern of use. Five substances were chosen for the test: 1,4-dioxane tert-methyl-butyl ether, diethylamine, 1,1,1-trichloroethane and bisphenol A. After testing the EASE model, the next step was the validation by estimating the exposure level and comparing it with the results of measurements in the workplace. We used the results of measurements of toluene, ethyl acetate and acetone concentrations in the work environment of a paint and lacquer factory, a shoe factory and a refinery. Three types of exposure scenarios, adaptable to the description of working conditions were chosen to estimate inhalation exposure. Comparison of calculated exposure to toluene, ethyl acetate and acetone with measurements in workplaces showed that model predictions are comparable with the measurement results. Only for low concentration ranges, the measured concentrations were higher than those predicted. EASE is a clear, consistent system, which can be successfully used as an additional component of inhalation exposure estimation. If the measurement data are available, they should be preferred to values estimated from models. In addition to inhalation exposure estimation, the EASE model makes it possible not only to assess exposure-related risk but also to predict workers' dermal exposure.

Detection limits of quantitative and digital PCR assays and their influence in presence-absence surveys of environmental DNA.

PubMed

Hunter, Margaret E; Dorazio, Robert M; Butterfield, John S S; Meigs-Friend, Gaia; Nico, Leo G; Ferrante, Jason A

2017-03-01

A set of universal guidelines is needed to determine the limit of detection (LOD) in PCR-based analyses of low-concentration DNA. In particular, environmental DNA (eDNA) studies require sensitive and reliable methods to detect rare and cryptic species through shed genetic material in environmental samples. Current strategies for assessing detection limits of eDNA are either too stringent or subjective, possibly resulting in biased estimates of species' presence. Here, a conservative LOD analysis grounded in analytical chemistry is proposed to correct for overestimated DNA concentrations predominantly caused by the concentration plateau, a nonlinear relationship between expected and measured DNA concentrations. We have used statistical criteria to establish formal mathematical models for both quantitative and droplet digital PCR. To assess the method, a new Grass Carp (Ctenopharyngodon idella) TaqMan assay was developed and tested on both PCR platforms using eDNA in water samples. The LOD adjustment reduced Grass Carp occupancy and detection estimates while increasing uncertainty-indicating that caution needs to be applied to eDNA data without LOD correction. Compared to quantitative PCR, digital PCR had higher occurrence estimates due to increased sensitivity and dilution of inhibitors at low concentrations. Without accurate LOD correction, species occurrence and detection probabilities based on eDNA estimates are prone to a source of bias that cannot be reduced by an increase in sample size or PCR replicates. Other applications also could benefit from a standardized LOD such as GMO food analysis and forensic and clinical diagnostics. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Improving the accuracy of Laplacian estimation with novel multipolar concentric ring electrodes

PubMed Central

Ding, Quan; Besio, Walter G.

2015-01-01

Conventional electroencephalography with disc electrodes has major drawbacks including poor spatial resolution, selectivity and low signal-to-noise ratio that are critically limiting its use. Concentric ring electrodes, consisting of several elements including the central disc and a number of concentric rings, are a promising alternative with potential to improve all of the aforementioned aspects significantly. In our previous work, the tripolar concentric ring electrode was successfully used in a wide range of applications demonstrating its superiority to conventional disc electrode, in particular, in accuracy of Laplacian estimation. This paper takes the next step toward further improving the Laplacian estimation with novel multipolar concentric ring electrodes by completing and validating a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2 that allows cancellation of all the truncation terms up to the order of 2n. An explicit formula based on inversion of a square Vandermonde matrix is derived to make computation of multipolar Laplacian more efficient. To confirm the analytic result of the accuracy of Laplacian estimate increasing with the increase of n and to assess the significance of this gain in accuracy for practical applications finite element method model analysis has been performed. Multipolar concentric ring electrode configurations with n ranging from 1 ring (bipolar electrode configuration) to 6 rings (septapolar electrode configuration) were directly compared and obtained results suggest the significance of the increase in Laplacian accuracy caused by increase of n. PMID:26693200

Improving the accuracy of Laplacian estimation with novel multipolar concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Ding, Quan; Besio, Walter G

2016-02-01

Conventional electroencephalography with disc electrodes has major drawbacks including poor spatial resolution, selectivity and low signal-to-noise ratio that are critically limiting its use. Concentric ring electrodes, consisting of several elements including the central disc and a number of concentric rings, are a promising alternative with potential to improve all of the aforementioned aspects significantly. In our previous work, the tripolar concentric ring electrode was successfully used in a wide range of applications demonstrating its superiority to conventional disc electrode, in particular, in accuracy of Laplacian estimation. This paper takes the next step toward further improving the Laplacian estimation with novel multipolar concentric ring electrodes by completing and validating a general approach to estimation of the Laplacian for an ( n + 1)-polar electrode with n rings using the (4 n + 1)-point method for n ≥ 2 that allows cancellation of all the truncation terms up to the order of 2 n . An explicit formula based on inversion of a square Vandermonde matrix is derived to make computation of multipolar Laplacian more efficient. To confirm the analytic result of the accuracy of Laplacian estimate increasing with the increase of n and to assess the significance of this gain in accuracy for practical applications finite element method model analysis has been performed. Multipolar concentric ring electrode configurations with n ranging from 1 ring (bipolar electrode configuration) to 6 rings (septapolar electrode configuration) were directly compared and obtained results suggest the significance of the increase in Laplacian accuracy caused by increase of n .

Exposure of infants to budesonide through breast milk of asthmatic mothers.

PubMed

Fält, Anette; Bengtsson, Thomas; Kennedy, Britt-Marie; Gyllenberg, Ann; Lindberg, Bengt; Thorsson, Lars; Stråndgarden, Kerstin

2007-10-01

Maintenance treatment with inhaled corticosteroids is often required for asthmatic nursing women. Data on the transfer of inhaled corticosteroids from plasma to breast milk and the subsequent exposure of the breast-feeding infant has been unavailable. We sought to assess budesonide concentrations in milk and plasma of asthmatic nursing women receiving maintenance treatment with the Pulmicort Turbuhaler and estimate the exposure of their breast-fed infants. Milk and plasma samples were collected up to 8 hours after dosing from 8 mothers receiving budesonide maintenance treatment (200 or 400 microg twice daily). Pharmacokinetic parameters were calculated from budesonide milk and plasma concentrations. Infant exposure was estimated based on average milk budesonide concentrations. A single blood sample was obtained from 5 infants close to expected infant maximum concentration. Budesonide concentrations in milk reflected those in maternal plasma, supporting passive diffusion of budesonide between plasma and milk, and was always lower than that in plasma. The mean milk/plasma ratio was 0.46. The estimated daily infant dose was 0.3% of the daily maternal dose for both dose levels, and the average plasma concentration in infants was estimated to be 1/600th of the concentrations observed in maternal plasma, assuming complete infant oral bioavailability. Budesonide concentrations in infant plasma samples were all less than the limit of quantification. Maintenance treatment with inhaled budesonide (200 or 400 microg twice daily) in asthmatic nursing women results in negligible systemic exposure to budesonide in breast-fed infants. These data support continued use of inhaled budesonide during breast-feeding.

Accurate determination of brain metabolite concentrations using ERETIC as external reference.

PubMed

Zoelch, Niklaus; Hock, Andreas; Heinzer-Schweizer, Susanne; Avdievitch, Nikolai; Henning, Anke

2017-08-01

Magnetic Resonance Spectroscopy (MRS) can provide in vivo metabolite concentrations in standard concentration units if a reliable reference signal is available. For 1 H MRS in the human brain, typically the signal from the tissue water is used as the (internal) reference signal. However, a concentration determination based on the tissue water signal most often requires a reliable estimate of the water concentration present in the investigated tissue. Especially in clinically interesting cases, this estimation might be difficult. To avoid assumptions about the water in the investigated tissue, the Electric REference To access In vivo Concentrations (ERETIC) method has been proposed. In this approach, the metabolite signal is compared with a reference signal acquired in a phantom and potential coil-loading differences are corrected using a synthetic reference signal. The aim of this study, conducted with a transceiver quadrature head coil, was to increase the accuracy of the ERETIC method by correcting the influence of spatial B 1 inhomogeneities and to simplify the quantification with ERETIC by incorporating an automatic phase correction for the ERETIC signal. Transmit field ( B1+) differences are minimized with a volume-selective power optimization, whereas reception sensitivity changes are corrected using contrast-minimized images of the brain and by adapting the voxel location in the phantom measurement closely to the position measured in vivo. By applying the proposed B 1 correction scheme, the mean metabolite concentrations determined with ERETIC in 21 healthy subjects at three different positions agree with concentrations derived with the tissue water signal as reference. In addition, brain water concentrations determined with ERETIC were in agreement with estimations derived using tissue segmentation and literature values for relative water densities. Based on the results, the ERETIC method presented here is a valid tool to derive in vivo metabolite concentration, with potential advantages compared with internal water referencing in diseased tissue. Copyright © 2017 John Wiley & Sons, Ltd.

Selective pressure of antibiotic pollution on bacteria of importance to public health.

PubMed

Tello, Alfredo; Austin, Brian; Telfer, Trevor C

2012-08-01

Many bacteria of clinical importance survive and may grow in different environments. Antibiotic pollution may exert on them a selective pressure leading to an increase in the prevalence of resistance. In this study we sought to determine whether environmental concentrations of antibiotics and concentrations representing action limits used in environmental risk assessment may exert a selective pressure on clinically relevant bacteria in the environment. We used bacterial inhibition as an assessment end point to link antibiotic selective pressures to the prevalence of resistance in bacterial populations. Species sensitivity distributions were derived for three antibiotics by fitting log-logistic models to end points calculated from minimum inhibitory concentration (MIC) distributions based on worldwide data collated by the European Committee on Antimicrobial Susceptibility Testing (EUCAST). To place bacteria represented in these distributions in a broader context, we performed a brief phylogenetic analysis. The potentially affected fraction of bacterial genera at measured environmental concentrations of antibiotics and environmental risk assessment action limits was used as a proxy for antibiotic selective pressure. Measured environmental concentrations and environmental risk assessment action limits were also directly compared to wild-type cut-off values. The potentially affected fraction of bacterial genera estimated based on antibiotic concentrations measured in water environments is ≤ 7%. We estimated that measured environmental concentrations in river sediments, swine feces lagoons, liquid manure, and farmed soil inhibit wild-type populations in up to 60%, 92%, 100%, and 30% of bacterial genera, respectively. At concentrations used as action limits in environmental risk assessment, erythromycin and ciprofloxacin were estimated to inhibit wild-type populations in up to 25% and 76% of bacterial genera. Measured environmental concentrations of antibiotics, as well as concentrations representing environmental risk assessment action limits, are high enough to exert a selective pressure on clinically relevant bacteria that may lead to an increase in the prevalence of resistance.

Nutrient Concentrations, Loads, and Yields in the Eucha-Spavinaw Basin, Arkansas and Oklahoma, 2002-2006

USGS Publications Warehouse

Tortorelli, Robert L.

2008-01-01

The City of Tulsa, Oklahoma, uses Lake Eucha and Spavinaw Lake in the Eucha-Spavinaw basin in northwestern Arkansas and northeastern Oklahoma for public water supply. Taste and odor problems in the water attributable to blue-green algae have increased in frequency. Changes in the algae community in the lakes may be attributable to increases in nutrient levels in the lakes, and in the waters feeding the lakes. The U.S. Geological Survey, in cooperation with the City of Tulsa, investigated and summarized nitrogen and phosphorus concentrations and provided estimates of nitrogen and phosphorus loads, yields, and flow-weighted concentrations in the Eucha-Spavinaw basin for three 3-year periods - 2002-2004, 2003-2005, and 2004-2006, to update a previous report that used data from water-quality samples for a 3-year period from January 2002 through December 2004. This report provides information needed to advance knowledge of the regional hydrologic system and understanding of hydrologic processes, and provides hydrologic data and results useful to multiple agencies for interstate agreements. Nitrogen and phosphorus concentrations were significantly greater in runoff samples than in base-flow samples for all three periods at Spavinaw Creek near Maysville, Arkansas; Spavinaw Creek near Colcord, Oklahoma, and Beaty Creek near Jay, Oklahoma. Runoff concentrations were not significantly greater than base-flow concentrations at Spavinaw Creek near Cherokee, Arkansas; and Spavinaw Creek near Sycamore, Oklahoma except for phosphorus during 2003-2005. Nitrogen concentrations in base-flow samples significantly increased downstream in Spavinaw Creek from the Maysville to Sycamore stations then significantly decreased from the Sycamore to the Colcord stations for all three periods. Nitrogen in base-flow samples from Beaty Creek was significantly less than in samples from Spavinaw Creek. Phosphorus concentrations in base-flow samples significantly increased from the Maysville to Cherokee stations in Spavinaw Creek for all three periods, probably because of a wastewater-treatment plant point source between those stations, and then significantly decreased downstream from the Cherokee to Colcord stations. Phosphorus in base-flow samples from Beaty Creek was significantly less than phosphorus in base-flow samples from Spavinaw Creek downstream from the Maysville station. Nitrogen concentrations in runoff samples were not significantly different among the stations on Spavinaw Creek for most of the three periods, except during 2003-2005 when runoff samples at the Colcord station were less than at the Sycamore station; however, the concentrations at Beaty Creek were significantly less than at all other stations. Phosphorus concentrations in runoff samples were not significantly different among the three downstream stations on Spavinaw Creek and were significantly different at the Maysville station on Spavinaw Creek and the Beaty Creek station, only during 2004-2006. Phosphorus and nitrogen concentrations in runoff samples from all stations generally increased with increasing streamflow. Estimated mean annual nitrogen total loads for the three 3-year periods were substantially greater at the Spavinaw Creek stations than at Beaty Creek and increased downstream from Maysville to Colcord in Spavinaw Creek, with the load at the Colcord station about 2 times that at Maysville station. Estimated mean annual nitrogen base-flow loads at the Spavinaw Creek stations were about 5 to 11 times greater than base-flow loads at Beaty Creek. The runoff component of the annual nitrogen total load for Beaty Creek was 85 to 89 percent; whereas, the range in the runoff component at the Spavinaw Creek stations was 60 to 71 percent. Estimated mean annual phosphorus total loads for the three 3-year periods were greater at the Spavinaw Creek stations from Cherokee to Colcord than at Beaty Creek and increased downstream from Maysville to Colcord in Spavinaw Creek, wit

A Portable Electronic Nose For Toxic Vapor Detection, Identification, and Quantification

NASA Technical Reports Server (NTRS)

Linnell, B. R.; Young, R. C.; Griffin, T. P.; Meneghelli, B. J.; Peterson, B. V.; Brooks, K. B.

2005-01-01

A new prototype instrument based on electronic nose (e-nose) technology has demonstrated the ability to identify and quantify many vapors of interest to the Space Program at their minimum required concentrations for both single vapors and two-component vapor mixtures, and may easily be adapted to detect many other toxic vapors. To do this, it was necessary to develop algorithms to classify unknown vapors, recognize when a vapor is not any of the vapors of interest, and estimate the concentrations of the contaminants. This paper describes the design of the portable e-nose instrument, test equipment setup, test protocols, pattern recognition algorithms, concentration estimation methods, and laboratory test results.

Estimate of uptake and translocation of emerging organic contaminants from irrigation water concentration in lettuce grown under controlled conditions.

PubMed

Hurtado, Carlos; Domínguez, Carmen; Pérez-Babace, Lorea; Cañameras, Núria; Comas, Jordi; Bayona, Josep M

2016-03-15

The widespread distribution of emerging organic contaminants (EOCs) in the water cycle can lead to their incorporation in irrigated crops, posing a potential risk for human consumption. To gain further insight into the processes controlling the uptake of organic microcontaminants, Batavia lettuce (Lactuca sativa) grown under controlled conditions was watered with EOCs (e.g., non-steroidal anti-inflammatories, sulfonamides, β-blockers, phenolic estrogens, anticonvulsants, stimulants, polycyclic musks, biocides) at different concentrations (0-40μgL(-1)). Linear correlations were obtained between the EOC concentrations in the roots and leaves and the watering concentrations for most of the contaminants investigated. However, large differences were found in the root concentration factors ( [Formula: see text] =0.27-733) and leaf translocation concentration factors ( [Formula: see text] =0-3) depending on the persistence of the target contaminants in the rhizosphere and the specific physicochemical properties of each one. With the obtained dataset, a simple predictive model based on a linear regression and the root bioconcentration and translocation factors can be used to estimate the concentration of the target EOCs in leaves based on the dose supplied in the irrigation water or the soil concentration. Finally, enantiomeric fractionation of racemic ibuprofen from the initial spiking mixture suggests that biodegradation mainly occurs in the rhizosphere. Copyright © 2015 Elsevier B.V. All rights reserved.

Assessment of MR-based R2* and quantitative susceptibility mapping for the quantification of liver iron concentration in a mouse model at 7T.

PubMed

Simchick, Gregory; Liu, Zhi; Nagy, Tamas; Xiong, May; Zhao, Qun

2018-03-25

To assess the feasibility of quantifying liver iron concentration (LIC) using R2* and quantitative susceptibility mapping (QSM) at a high field strength of 7 Tesla (T). Five different concentrations of Fe-dextran were injected into 12 mice to produce various degrees of liver iron overload. After mice were sacrificed, blood and liver samples were harvested. Ferritin enzyme-linked immunosorbent assay (ELISA) and inductively coupled plasma mass spectrometry were performed to quantify serum ferritin concentration and LIC. Multiecho gradient echo MRI was conducted to estimate R2* and the magnetic susceptibility of each liver sample through complex nonlinear least squares fitting and a morphology enabled dipole inversion method, respectively. Average estimates of serum ferritin concentration, LIC, R2*, and susceptibility all show good linear correlations with injected Fe-dextran concentration; however, the standard deviations in the estimates of R2* and susceptibility increase with injected Fe-dextran concentration. Both R2* and susceptibility measurements also show good linear correlations with LIC (R 2  = 0.78 and R 2  = 0.91, respectively), and a susceptibility-to-LIC conversion factor of 0.829 ppm/(mg/g wet) is derived. The feasibility of quantifying LIC using MR-based  R2* and QSM at a high field strength of 7T is demonstrated. Susceptibility quantification, which is an intrinsic property of tissues and benefits from being field-strength independent, is more robust than R2* quantification in this ex vivo study. A susceptibility-to-LIC conversion factor is presented that agrees relatively well with previously published QSM derived results obtained at 1.5T and 3T. © 2018 International Society for Magnetic Resonance in Medicine.

Titrimetric and photometric methods for determination of hypochlorite in commercial bleaches.

PubMed

Jonnalagadda, Sreekanth B; Gengan, Prabhashini

2010-01-01

Two methods, simple titration and photometric methods for determination of hypochlorite are developed, based its reaction with hydrogen peroxide and titration of the residual peroxide by acidic permanganate. In the titration method, the residual hydrogen peroxide is estimated by titration with standard permanganate solution to estimate the hypochlorite concentration. The photometric method is devised to measure the concentration of remaining permanganate, after the reaction with residual hydrogen peroxide. It employs 4 ranges of calibration curves to enable the determination of hypochlorite accurately. The new photometric method measures hypochlorite in the range 1.90 x 10(-3) to 1.90 x 10(-2) M, with high accuracy and with low variance. The concentrations of hypochlorite in diverse commercial bleach samples and in seawater which is enriched with hypochlorite were estimated using the proposed method and compared with the arsenite method. The statistical analysis validates the superiority of the proposed method.

Numerical modelling of temporal and spatial patterns of petroleum hydrocarbons concentration in the Bohai Sea.

PubMed

Guo, Weijun; Wu, Guoxiang; Xu, Tiaojian; Li, Xueyan; Ren, Xiaozhong; Hao, Yanni

2018-02-01

The discharge of petroleum hydrocarbons (PHs; ~10,000tons annually) into the Bohai Sea, a shallow inland sea in China, presents a serious threat to the marine environment. To evaluate the effects of PHs pollution and estimate the corresponding environmental capacity, we have developed a genetic algorithm-based coupled hydrodynamic/transport for simulating PHs concentration evolution and distribution from July 2006 to October 2007, with the predicted values being in good agreement with monitoring results. Importantly, the mean PHs concentrations and seasonal concentration variations were primarily determined by external loading, i.e., currents were shown to drive PHs transport, reconfigure local PHs patterns, and increase PHs concentration in water masses, even at large distances from discharge sources. The developed model could realistically simulate PHs distribution and evolution, thus being a useful tool for estimating the seasonal environmental capacity of PHs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Participant-based monitoring of indoor and outdoor nitrogen dioxide, volatile organic compounds, and polycyclic aromatic hydrocarbons among MICA-Air households

NASA Astrophysics Data System (ADS)

Johnson, Markey M.; Williams, Ron; Fan, Zhihua; Lin, Lin; Hudgens, Edward; Gallagher, Jane; Vette, Alan; Neas, Lucas; Özkaynak, Halûk

2010-12-01

The Mechanistic Indicators of Childhood Asthma (MICA) study in Detroit, Michigan introduced a participant-based approach to reduce the resource burden associated with collection of indoor and outdoor residential air sampling data. A subset of participants designated as MICA-Air conducted indoor and outdoor residential sampling of nitrogen dioxide (NO 2), volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs). This participant-based methodology was subsequently adapted for use in the Vanguard phase of the U.S. National Children's Study. The current paper examines residential indoor and outdoor concentrations of these pollutant species among health study participants in Detroit, Michigan. Pollutants measured under MICA-Air agreed well with other studies and continuous monitoring data collected in Detroit. For example, NO 2 and BTEX concentrations reported for other Detroit area monitoring were generally within 10-15% of indoor and outdoor concentrations measured in MICA-Air households. Outdoor NO 2 concentrations were typically higher than indoor NO 2 concentration among MICA-Air homes, with a median indoor/outdoor (I/O) ratio of 0.6 in homes that were not impacted by environmental tobacco smoke (ETS) during air sampling. Indoor concentrations generally exceeded outdoor concentrations for VOC and PAH species measured among non-ETS homes in the study. I/O ratios for BTEX species (benzene, toluene, ethylbenzene, and m/p- and o-xylene) ranged from 1.2 for benzene to 3.1 for toluene. Outdoor NO 2 concentrations were approximately 4.5 ppb higher on weekdays versus weekends. As expected, I/O ratios pollutants were generally higher for homes impacted by ETS. These findings suggest that participant-based air sampling can provide a cost-effective alternative to technician-based approaches for assessing indoor and outdoor residential air pollution in community health studies. We also introduced a technique for estimating daily concentrations at each home by weighting 2- and 7-day integrated concentrations using continuous measurements from regulatory monitoring sites. This approach may be applied to estimate short-term daily or hourly pollutant concentrations in future health studies.

Transfer of radiocarbon liquid releases from the AREVA La Hague spent fuel reprocessing plant in the English Channel.

PubMed

Fiévet, Bruno; Voiseux, Claire; Rozet, Marianne; Masson, Michel; Bailly du Bois, Pascal

2006-01-01

The recent risk assessment by the North-Cotentin Radioecology Group (, 1999) outlined that (14)C has become one of the major sources of the low dose to man through seafood consumption. It was recommended that more data should be collected about (14)C in the local marine environment. The present study aims to respond to this recommendation. The estimation of (14)C activity in marine species is based on concentration factor values. The values reported here ranged from 1x10(3) to 5x10(3)Bqkg(-1)ww/BqL(-1). A comparison was made between the observed and predicted values. The accuracy of (14)C activity calculations was estimated between underestimation by a factor of 2 and over-estimation by 50% (95% confidence interval). However, the use of the concentration factor parameter is based on the biological and seawater compartments being in steady state. This assumption may not be met at short distances from the point of release of discharges, where rapid changes in seawater concentration may be smoothed out in living organisms due to transfer kinetics. The data processing technique, previously published by Fiévet and Plet (2003. Estimating biological half-lives of radionuclides in marine compartments from environmental time-series measurements. Journal of Environmental Radioactivity 65, 91-107), was used to deal with (14)C transfer kinetics, and carbon half-lives between seawater and a few biological compartments were thus estimated.

Kalman-filtered compressive sensing for high resolution estimation of anthropogenic greenhouse gas emissions from sparse measurements.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ray, Jaideep; Lee, Jina; Lefantzi, Sophia

2013-09-01

The estimation of fossil-fuel CO2 emissions (ffCO2) from limited ground-based and satellite measurements of CO2 concentrations will form a key component of the monitoring of treaties aimed at the abatement of greenhouse gas emissions. The limited nature of the measured data leads to a severely-underdetermined estimation problem. If the estimation is performed at fine spatial resolutions, it can also be computationally expensive. In order to enable such estimations, advances are needed in the spatial representation of ffCO2 emissions, scalable inversion algorithms and the identification of observables to measure. To that end, we investigate parsimonious spatial parameterizations of ffCO2 emissions whichmore » can be used in atmospheric inversions. We devise and test three random field models, based on wavelets, Gaussian kernels and covariance structures derived from easily-observed proxies of human activity. In doing so, we constructed a novel inversion algorithm, based on compressive sensing and sparse reconstruction, to perform the estimation. We also address scalable ensemble Kalman filters as an inversion mechanism and quantify the impact of Gaussian assumptions inherent in them. We find that the assumption does not impact the estimates of mean ffCO2 source strengths appreciably, but a comparison with Markov chain Monte Carlo estimates show significant differences in the variance of the source strengths. Finally, we study if the very different spatial natures of biogenic and ffCO2 emissions can be used to estimate them, in a disaggregated fashion, solely from CO2 concentration measurements, without extra information from products of incomplete combustion e.g., CO. We find that this is possible during the winter months, though the errors can be as large as 50%.« less

Nitrogen dioxide and respiratory illness in children. Part II: Assessment of exposure to nitrogen dioxide.

PubMed

Lambert, W E; Samet, J M; Hunt, W C; Skipper, B J; Schwab, M; Spengler, J D

1993-06-01

Repeated measurements of nitrogen dioxide were obtained from 1988 to 1991 in the homes of 1,205 infants living in Albuquerque, NM. Passive diffusion samplers were used to obtain a series of two-week integrated measurements from the home of each infant for use in a cohort study of the relation of residential exposure to nitrogen dioxide and respiratory illnesses. Information on stove use and time spent inside the residence was collected at two-week and two-month intervals, respectively. During the winter, in the bedrooms of homes with gas cooking stoves, mean nitrogen dioxide concentrations were 21 parts per billion (ppb); mean concentrations in the living room and kitchen were 29 ppb and 34 ppb, respectively. In homes with electric cooking stoves, the mean bedroom concentration was 7 ppb during the winter. Lower indoor concentrations were observed during the summer in homes with both gas and electric stoves. On average, infants spent approximately 12.3 hours per day in their bedrooms, 7.3 hours in the living rooms, 35 minutes in the kitchens, and 3.8 hours out of their homes. (As a condition of participation, none of the infants spent more than 20 hours per week in day care outside of their homes). The mean time infants spent in the kitchen during cooking was approximately nine minutes per day. We tested whether exposures of infants living in homes with gas stoves could be reasonably estimated by measurements in the bedroom in comparison with time-weighted average concentrations based on time-activity data and simultaneous nitrogen dioxide measurements in the kitchen, living room, and bedroom. In 1,937 two-week intervals from 587 infants, 90% of time-weighted exposure (on the three-level classification used in this study) estimates were in agreement with estimates based on bedroom concentrations alone. The agreement of the time-weighted nitrogen dioxide exposure estimates with the bedroom concentrations is attributed to limited amounts of cooking stove use (the mean was 29 minutes per day), small room-to-room differences in nitrogen dioxide concentrations (the mean kitchen-bedroom difference was 12 ppb), and the relatively large proportion of time that infants spent in their bedrooms.

Comparison between air pollution concentrations measured at the nearest monitoring station to the delivery hospital and those measured at stations nearest the residential postal code regions of pregnant women in Fukuoka.

PubMed

Michikawa, Takehiro; Morokuma, Seiichi; Nitta, Hiroshi; Kato, Kiyoko; Yamazaki, Shin

2017-06-13

Numerous earlier studies examining the association of air pollution with maternal and foetal health estimated maternal exposure to air pollutants based on the women's residential addresses. However, residential addresses, which are personally identifiable information, are not always obtainable. Since a majority of pregnant women reside near their delivery hospitals, the concentrations of air pollutants at the respective delivery hospitals may be surrogate markers of pollutant exposure at home. We compared air pollutant concentrations measured at the nearest monitoring station to Kyushu University Hospital with those measured at the closest monitoring stations to the respective residential postal code regions of pregnant women in Fukuoka. Aggregated postal code data for the home addresses of pregnant women who delivered at Kyushu University Hospital in 2014 was obtained from Kyushu University Hospital. For each of the study's 695 women who resided in Fukuoka Prefecture, we assigned pollutant concentrations measured at the nearest monitoring station to Kyushu University Hospital and pollutant concentrations measured at the nearest monitoring station to their respective residential postal code regions. Among the 695 women, 584 (84.0%) resided in the proximity of the nearest monitoring station to hospital or one of the four other stations (as the nearest stations to their respective residential postal code region) in Fukuoka city. Pearson's correlation for daily mean concentrations among the monitoring stations in Fukuoka city was strong for fine particulate matter (PM 2.5 ), suspended particulate matter (SPM), and photochemical oxidants (Ox) (coefficients ≥0.9), but moderate for coarse particulate matter (the result of subtracting the PM 2.5 from the SPM concentrations), nitrogen dioxide, and sulphur dioxide. Hospital-based and residence-based concentrations of PM 2.5 , SPM, and Ox were comparable. For PM 2.5 , SPM, and Ox, exposure estimation based on the delivery hospital is likely to approximate that based on the home of pregnant women.

Validation of Surrogates of Urine Osmolality in Population Studies.

PubMed

Youhanna, Sonia; Bankir, Lise; Jungers, Paul; Porteous, David; Polasek, Ozren; Bochud, Murielle; Hayward, Caroline; Devuyst, Olivier

2017-01-01

The importance of vasopressin and/or urine concentration in various kidney, cardiovascular, and metabolic diseases has been emphasized recently. Due to technical constraints, urine osmolality (Uosm), a direct reflect of urinary concentrating activity, is rarely measured in epidemiologic studies. We analyzed 2 possible surrogates of Uosm in 4 large population-based cohorts (total n = 4,247) and in patients with chronic kidney disease (CKD, n = 146). An estimated Uosm (eUosm) based on the concentrations of sodium, potassium, and urea, and a urine concentrating index (UCI) based on the ratio of creatinine concentrations in urine and plasma were compared to the measured Uosm (mUosm). eUosm is an excellent surrogate of mUosm, with a highly significant linear relationship and values within 5% of mUosm (r = 0.99 or 0.98 in each population cohort). Bland-Altman plots show a good agreement between eUosm and mUosm with mean differences between the 2 variables within ±24 mmol/L. This was verified in men and women, in day and night urine samples, and in CKD patients. The relationship of UCI with mUosm is also significant but is not linear and exhibits more dispersed values. Moreover, the latter index is no longer representative of mUosm in patients with CKD as it declines much more quickly with declining glomerular filtration rate than mUosm. The eUosm is a valid marker of urine concentration in population-based and CKD cohorts. The UCI can provide an estimate of urine concentration when no other measurement is available, but should be used only in subjects with normal renal function. © 2017 S. Karger AG, Basel.

Seasonal comparisons of sea ice concentration estimates derived from SSM/I, OKEAN, and RADARSAT data

USGS Publications Warehouse

Belchansky, Gennady I.; Douglas, David C.

2002-01-01

The Special Sensor Microwave Imager (SSM/I) microwave satellite radiometer and its predecessor SMMR are primary sources of information for global sea ice and climate studies. However, comparisons of SSM/I, Landsat, AVHRR, and ERS-1 synthetic aperture radar (SAR) have shown substantial seasonal and regional differences in their estimates of sea ice concentration. To evaluate these differences, we compared SSM/I estimates of sea ice coverage derived with the NASA Team and Bootstrap algorithms to estimates made using RADARSAT, and OKEAN-01 satellite sensor data. The study area included the Barents Sea, Kara Sea, Laptev Sea, and adjacent parts of the Arctic Ocean, during October 1995 through October 1999. Ice concentration estimates from spatially and temporally near-coincident imagery were calculated using independent algorithms for each sensor type. The OKEAN algorithm implemented the satellite's two-channel active (radar) and passive microwave data in a linear mixture model based on the measured values of brightness temperature and radar backscatter. The RADARSAT algorithm utilized a segmentation approach of the measured radar backscatter, and the SSM/I ice concentrations were derived at National Snow and Ice Data Center (NSIDC) using the NASA Team and Bootstrap algorithms. Seasonal and monthly differences between SSM/I, OKEAN, and RADARSAT ice concentrations were calculated and compared. Overall, total sea ice concentration estimates derived independently from near-coincident RADARSAT, OKEAN-01, and SSM/I satellite imagery demonstrated mean differences of less than 5.5% (S.D.<9.5%) during the winter period. Differences between the SSM/I NASA Team and the SSM/I Bootstrap concentrations were no more than 3.1% (S.D.<5.4%) during this period. RADARSAT and OKEAN-01 data both yielded higher total ice concentrations than the NASA Team and the Bootstrap algorithms. The Bootstrap algorithm yielded higher total ice concentrations than the NASA Team algorithm. Total ice concentrations derived from OKEAN-01 and SSM/I satellite imagery were highly correlated during winter, spring, and fall, with mean differences of less than 8.1% (S.D.<15%) for the NASA Team algorithm, and less than 2.8% (S.D.<13.8%) for the Bootstrap algorithm. Respective differences between SSM/I NASA Team and SSM/I Bootstrap total concentrations were less than 5.3% (S.D.<6.9%). Monthly mean differences between SSM/I and OKEAN differed annually by less than 6%, with smaller differences primarily in winter. The NASA Team and Bootstrap algorithms underestimated the total sea ice concentrations relative to the RADARSAT ScanSAR no more than 3.0% (S.D.<9%) and 1.2% (S.D.<7.5%) during cold months, and no more than 12% and 7% during summer, respectively. ScanSAR tended to estimate higher ice concentrations for ice concentrations greater than 50%, when compared to SSM/I during all months. ScanSAR underestimated total sea ice concentration by 2% compared to the OKEAN-01 algorithm during cold months, and gave an overestimation by 2% during spring and summer months. Total NASA Team and Bootstrap sea ice concentration estimates derived from coincident SSM/I and OKEAN-01 data demonstrated mean differences of no more than 5.3% (S.D.<7%), 3.1% (S.D.<5.5%), 2.0% (S.D.<5.5%), and 7.3% (S.D.<10%) for fall, winter, spring, and summer periods, respectively. Large disagreements were observed between the OKEAN and NASA Team results in spring and summer for estimates of the first-year (FY) and multiyear (MY) age classes. The OKEAN-01 algorithm and data tended to estimate, on average, lower concentrations of young or FY ice and higher concentrations of total and MY ice for all months and seasons. Our results contribute to the growing body of documentation about the levels of disparity obtained when seasonal sea ice concentrations are estimated using various types of satellite data and algorithms.

A statistical downscaling approach for roadside NO2 concentrations: Application to a WRF-Chem study for Berlin

NASA Astrophysics Data System (ADS)

Kuik, Friderike; Lauer, Axel; von Schneidemesser, Erika; Butler, Tim

2017-04-01

Many European cities continue to struggle with meeting the European air quality limits for NO2. In Berlin, Germany, most of the exceedances in NO2 recorded at monitoring sites near busy roads can be largely attributed to emissions from traffic. In order to assess the impact of changes in traffic emissions on air quality at policy relevant scales, we combine the regional atmosphere-chemistry transport model WRF-Chem at a resolution of 1kmx1km with a statistical downscaling approach. Here, we build on the recently published study evaluating the performance of a WRF-Chem setup in representing observed urban background NO2 concentrations from Kuik et al. (2016) and extend this setup by developing and testing an approach to statistically downscale simulated urban background NO2 concentrations to street level. The approach uses a multilinear regression model to relate roadside NO2 concentrations observed with the municipal monitoring network with observed NO2 concentrations at urban background sites and observed traffic counts. For this, the urban background NO2 concentrations are decomposed into a long term, a synoptic and a diurnal component using the Kolmogorov-Zurbenko filtering method. We estimate the coefficients of the regression model for five different roadside stations in Berlin representing different street types. In a next step we combine the coefficients with simulated urban background concentrations and observed traffic counts, in order to estimate roadside NO2 concentrations based on the results obtained with WRF-Chem at the five selected stations. In a third step, we extrapolate the NO2 concentrations to all major roads in Berlin. The latter is based on available data for Berlin of daily mean traffic counts, diurnal and weekly cycles of traffic as well as simulated urban background NO2 concentrations. We evaluate the NO2 concentrations estimated with this method at street level for Berlin with additional observational data from stationary measurements and mobile measurements conducted during a campaign in summer 2014. The results show that this approach allows us to estimate NO2 concentrations at roadside reasonably well. The approach can be applied when observations show a strong correlation between roadside NO2 concentrations and traffic emissions from a single type of road. The method, however, shows weaknesses for intersections where observed NO2 concentrations are influenced by traffic on several different roads. We then apply this downscaling approach to estimate the impact of different traffic emission scenarios both on urban background and street level NO2 concentrations. References Kuik, F., Lauer, A., Churkina, G., Denier van der Gon, H. A. C., Fenner, D., Mar, K. A., and Butler, T. M.: Air quality modelling in the Berlin-Brandenburg region using WRF-Chem v3.7.1: sensitivity to resolution of model grid and input data, Geosci. Model Dev., 9, 4339-4363, doi:10.5194/gmd-9-4339-2016, 2016.

Using accelerated life testing procedures to compare the relative sensitivity of rainbow trout and the federally listed threatened bull trout to three commonly used rangeland herbicides (picloram, 2,4-D, and clopyralid).

PubMed

Fairchild, James F; Allert, Ann; Sappington, Linda S; Nelson, Karen J; Valle, Janet

2008-03-01

We conducted 96-h static acute toxicity studies to evaluate the relative sensitivity of juveniles of the threatened bull trout (Salvelinus confluentus) and the standard cold-water surrogate rainbow trout (Onchorhyncus mykiss) to three rangeland herbicides commonly used for controlling invasive weeds in the northwestern United States. Relative species sensitivity was compared using three procedures: standard acute toxicity testing, fractional estimates of lethal concentrations, and accelerated life testing chronic estimation procedures. The acutely lethal concentrations (ALC) resulting in 50% mortality at 96 h (96-h ALC50s) were determined using linear regression and indicated that the three herbicides were toxic in the order of picloram acid > 2,4-D acid > clopyralid acid. The 96-h ALC50 values for rainbow trout were as follows: picloram, 41 mg/L; 2.4-D, 707 mg/L; and clopyralid, 700 mg/L. The 96-h ALC50 values for bull trout were as follows: picloram, 24 mg/L; 2.4-D, 398 mg/L; and clopyralid, 802 mg/L. Fractional estimates of safe concentrations, based on 5% of the 96-h ALC50, were conservative (overestimated toxicity) of regression-derived 96-h ALC5 values by an order of magnitude. Accelerated life testing procedures were used to estimate chronic lethal concentrations (CLC) resulting in 1% mortality at 30 d (30-d CLC1) for the three herbicides: picloram (1 mg/L rainbow trout, 5 mg/L bull trout), 2,4-D (56 mg/L rainbow trout, 84 mg/L bull trout), and clopyralid (477 mg/L rainbow trout; 552 mg/L bull trout). Collectively, the results indicated that the standard surrogate rainbow trout is similar in sensitivity to bull trout. Accelerated life testing procedures provided cost-effective, statistically defensible methods for estimating safe chronic concentrations (30-d CLC1s) of herbicides from acute toxicity data because they use statistical models based on the entire mortality:concentration:time data matrix.

Using accelerated life testing procedures to compare the relative sensitivity of rainbow trout and the federally listed threatened bull trout to three commonly used rangeland herbicides (picloram, 2,4-D, and clopyralid)

USGS Publications Warehouse

Fairchild, J.F.; Allert, A.; Sappington, L.S.; Nelson, K.J.; Valle, J.

2008-01-01

We conducted 96-h static acute toxicity studies to evaluate the relative sensitivity of juveniles of the threatened bull trout (Salvelinus confluentus) and the standard cold-water surrogate rainbow trout (Onchorhyncus mykiss) to three rangeland herbicides commonly used for controlling invasive weeds in the northwestern United States. Relative species sensitivity was compared using three procedures: standard acute toxicity testing, fractional estimates of lethal concentrations, and accelerated life testing chronic estimation procedures. The acutely lethal concentrations (ALC) resulting in 50% mortality at 96 h (96-h ALC50s) were determined using linear regression and indicated that the three herbicides were toxic in the order of picloram acid > 2,4-D acid > clopyralid acid. The 96-h ALC50 values for rainbow trout were as follows: picloram, 41 mg/L; 2.4-D, 707 mg/L; and clopyralid, 700 mg/L. The 96-h ALC50 values for bull trout were as follows: picloram, 24 mg/L; 2.4-D, 398 mg/L; and clopyralid, 802 mg/L. Fractional estimates of safe concentrations, based on 5% of the 96-h ALC50, were conservative (overestimated toxicity) of regression-derived 96-h ALC5 values by an order of magnitude. Accelerated life testing procedures were used to estimate chronic lethal concentrations (CLC) resulting in 1% mortality at 30 d (30-d CLC1) for the three herbicides: picloram (1 mg/L rainbow trout, 5 mg/L bull trout), 2,4-D (56 mg/L rainbow trout, 84 mg/L bull trout), and clopyralid (477 mg/L rainbow trout; 552 mg/L bull trout). Collectively, the results indicated that the standard surrogate rainbow trout is similar in sensitivity to bull trout. Accelerated life testing procedures provided cost-effective, statistically defensible methods for estimating safe chronic concentrations (30-d CLC1s) of herbicides from acute toxicity data because they use statistical models based on the entire mortality:concentration: time data matrix. ?? 2008 SETAC.

Development of Preliminary Remediation Goals for Indoor Dust at the Colonie FUSRAP Site - 12273

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watters, David J.; Opdyke, Clifford P.; Moore, James T.

2012-07-01

The Colonie FUSRAP Site is located in the Town of Colonie, Albany County, New York. The U.S. Army Corps of Engineers is currently addressing environmental contamination associated with the Site under the Comprehensive Environmental Response, Compensation and Liability Act (CERCLA) process as part of the Formerly Utilized Sites Remedial Action Program (FUSRAP). Soil remediation activities have been substantially completed at the Colonie FUSRAP Site and its vicinity properties under the FUSRAP. A study unrelated to FUSRAP was recently performed by an independent party to establish the distribution of DU contamination in various media in the environs of the Site. Asmore » part of this study, dust samples were collected in residencies and businesses in the immediate vicinity of the Site. These samples were collected in non-living areas such as basement window sills and garages. Many of these samples tested positive for DU. An assessment was performed to establish preliminary remediation goals (PRGs) for indoor dust in non-living areas of residential homes and businesses in the vicinity of the Site. The results of this assessment provide estimates of dose-based, carcinogenic risk-based, and noncarcinogenic-based PRGs derived from a hypothetical exposure scenario with reasonable levels of conservatism. Ultimately, the PRGs will be compared to results of dust sampling and analyses in residences and businesses in proximity of the Site to determine whether a response action is appropriate. This assessment estimates PRGs for DU contaminated dust in non-living areas of residences in the vicinity of the Colonie FUSRAP site based on a reasonably conservative exposure scenario. Estimated PRGs based on residential receptors are considered to be conservatively representative of workers in nearby businesses based on the considerably longer exposure duration of residents relative to workers. This assessment provides reasonably conservative estimates of PRGs for DU contaminated dust in non-living areas within residences in the vicinity of the Site. It should be noted that the PRGs include hypothetical exposures resulting from activities in both the living areas and non-living areas of a residence. The PRGs are derived and presented in terms of DU dust concentration in non-living areas to facilitate comparison to results of a planned Site Investigation that will characterize concentrations of DU in dust in non-living areas. It is important to recognize that the exposure assumptions used to derive these PRGs are based on average dust DU concentrations in non-living areas. It is inappropriate to compare these PRGs to the dust DU concentration in an isolated small area. The ongoing Site Investigation addresses this consideration and is designed to provide reasonable estimates of average dust DU concentrations in non-living areas of vicinity properties. In order to accomplish this, sampling is conducted in accordance with EPA Guidance for the Sampling and Analysis of Lead in Indoor Residential Dust for Use in the Integrated Exposure Uptake Biokinetic (IEUBK) Model, (EPA 2008), which specifically addresses estimating average contaminant concentrations in dust. Four (4) large-area samples are collected from each VP in accordance with this guidance. It is anticipated that the results of the Site Investigation will be used in conjunction with the results of this assessment, and/or subsequent assessments, to establish whether or not a response action is appropriate. (authors)« less

The role of meteorological conditions and pollution control strategies in reducing air pollution in Beijing during APEC 2014 and Victory Parade 2015

NASA Astrophysics Data System (ADS)

Liang, Pengfei; Zhu, Tong; Fang, Yanhua; Li, Yingruo; Han, Yiqun; Wu, Yusheng; Hu, Min; Wang, Junxia

2017-11-01

To control severe air pollution in China, comprehensive pollution control strategies have been implemented throughout the country in recent years. To evaluate the effectiveness of these strategies, the influence of meteorological conditions on levels of air pollution needs to be determined. Using the intensive air pollution control strategies implemented during the Asia-Pacific Economic Cooperation Forum in 2014 (APEC 2014) and the 2015 China Victory Day Parade (Victory Parade 2015) as examples, we estimated the role of meteorological conditions and pollution control strategies in reducing air pollution levels in Beijing. Atmospheric particulate matter of aerodynamic diameter ≤ 2.5 µm (PM2.5) samples were collected and gaseous pollutants (SO2, NO, NOx, and O3) were measured online at a site in Peking University (PKU). To determine the influence of meteorological conditions on the levels of air pollution, we first compared the air pollutant concentrations during days with stable meteorological conditions. However, there were few days with stable meteorological conditions during the Victory Parade. As such, we were unable to estimate the level of emission reduction efforts during this period. Finally, a generalized linear regression model (GLM) based only on meteorological parameters was built to predict air pollutant concentrations, which could explain more than 70 % of the variation in air pollutant concentration levels, after incorporating the nonlinear relationships between certain meteorological parameters and the concentrations of air pollutants. Evaluation of the GLM performance revealed that the GLM, even based only on meteorological parameters, could be satisfactory to estimate the contribution of meteorological conditions in reducing air pollution and, hence, the contribution of control strategies in reducing air pollution. Using the GLM, we found that the meteorological conditions and pollution control strategies contributed 30 and 28 % to the reduction of the PM2.5 concentration during APEC and 38 and 25 % during the Victory Parade, respectively, based on the assumption that the concentrations of air pollutants are only determined by meteorological conditions and emission intensities. We also estimated the contribution of meteorological conditions and control strategies in reducing the concentrations of gaseous pollutants and PM2.5 components with the GLMs, revealing the effective control of anthropogenic emissions.

GPS-based Microenvironment Tracker (MicroTrac) Model to Estimate Time-Location of Individuals for Air Pollution Exposure Assessments: Model Evaluation in Central North Carolina

EPA Science Inventory

A critical aspect of air pollution exposure assessment is the estimation of the time spent by individuals in various microenvironments (ME). Accounting for the time spent in different ME with different pollutant concentrations can reduce exposure misclassifications, while failure...

SEASONAL NH3 EMISSION ESTIMATES FOR THE EASTERN UNITED STATES BASED ON AMMONIUM WET CONCENTRATIONS AND AN INVERSE MODELING METHOD

EPA Science Inventory

Significant uncertainty exists in the magnitude and variability of ammonia (NH3) emissions. NH3 emissions are needed as input for air quality modeling of aerosols and deposition of nitrogen compounds. Approximately 85% of NH3 emissions are estimated to come from agricultural ...

In Situ Monitoring of Groundwater Contamination Using the Kalman Filter For Sustainable Remediation

NASA Astrophysics Data System (ADS)

Schmidt, F.; Wainwright, H. M.; Faybishenko, B.; Denham, M. E.; Eddy-Dilek, C. A.

2017-12-01

Sustainable remediation - based on less intensive passive remediation and natural attenuation - has become a desirable remediation alternative at contaminated sites. Although it has a number of benefits, such as reduced waste and water/energy usage, it carries a significant burden of proof to verify plume stability and to ensure insignificant increase of risk to public health. Modeling of contaminant transport is still challenging despite recent advances in numerical methods. Long-term monitoring has, therefore, become a critical component in sustainable remediation. However, the current approach, which relies on sparse groundwater sampling, is problematic, since it could miss sudden significant changes in plume behavior. A new method is needed to combine existing knowledge about contaminant behavior and latest advances in in situ groundwater sensors. This study presents an example of the effective use of the Kalman filter approach to estimate contaminant concentrations, based on in situ measured water quality parameters (e.g. electrical conductivity and pH) along with the results of sparse groundwater sampling. The Kalman filter can effectively couple physical models and data correlations between the contaminant concentrations and in situ measured variables. We aim (1) to develop a framework capable of integrating different data types to provide accurate contaminant concentration estimates, (2) to demonstrate that these results remain reliable, even when the groundwater sampling frequency is reduced, and (3) to evaluate the future efficacy of this strategy using reactive transport simulations. This framework can also serve as an early warning system for detecting unexpected plume migration. We demonstrate our approach using historical and current groundwater data from the Savannah River Site (SRS) F-Area Seepage Basins to estimate uranium and tritium concentrations. The results show that the developed method can provide reliable estimates of contaminant concentrations. We also show that we can reduce the groundwater sampling frequency significantly, while capturing the dynamics of contaminant concentration changes. To our knowledge, this is the first study to apply data analytics to long-term groundwater monitoring extensively.

Estimating the concentration of urea and creatinine in the human serum of normal and dialysis patients through Raman spectroscopy.

PubMed

de Almeida, Maurício Liberal; Saatkamp, Cassiano Junior; Fernandes, Adriana Barrinha; Pinheiro, Antonio Luiz Barbosa; Silveira, Landulfo

2016-09-01

Urea and creatinine are commonly used as biomarkers of renal function. Abnormal concentrations of these biomarkers are indicative of pathological processes such as renal failure. This study aimed to develop a model based on Raman spectroscopy to estimate the concentration values of urea and creatinine in human serum. Blood sera from 55 clinically normal subjects and 47 patients with chronic kidney disease undergoing dialysis were collected, and concentrations of urea and creatinine were determined by spectrophotometric methods. A Raman spectrum was obtained with a high-resolution dispersive Raman spectrometer (830 nm). A spectral model was developed based on partial least squares (PLS), where the concentrations of urea and creatinine were correlated with the Raman features. Principal components analysis (PCA) was used to discriminate dialysis patients from normal subjects. The PLS model showed r = 0.97 and r = 0.93 for urea and creatinine, respectively. The root mean square errors of cross-validation (RMSECV) for the model were 17.6 and 1.94 mg/dL, respectively. PCA showed high discrimination between dialysis and normality (95 % accuracy). The Raman technique was able to determine the concentrations with low error and to discriminate dialysis from normal subjects, consistent with a rapid and low-cost test.

Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England.

PubMed

Pannullo, Francesca; Lee, Duncan; Neal, Lucy; Dalvi, Mohit; Agnew, Paul; O'Connor, Fiona M; Mukhopadhyay, Sabyasachi; Sahu, Sujit; Sarran, Christophe

2017-03-27

Estimating the long-term health impact of air pollution in a spatio-temporal ecological study requires representative concentrations of air pollutants to be constructed for each geographical unit and time period. Averaging concentrations in space and time is commonly carried out, but little is known about how robust the estimated health effects are to different aggregation functions. A second under researched question is what impact air pollution is likely to have in the future. We conducted a study for England between 2007 and 2011, investigating the relationship between respiratory hospital admissions and different pollutants: nitrogen dioxide (NO 2 ); ozone (O 3 ); particulate matter, the latter including particles with an aerodynamic diameter less than 2.5 micrometers (PM 2.5 ), and less than 10 micrometers (PM 10 ); and sulphur dioxide (SO 2 ). Bayesian Poisson regression models accounting for localised spatio-temporal autocorrelation were used to estimate the relative risks (RRs) of pollution on disease risk, and for each pollutant four representative concentrations were constructed using combinations of spatial and temporal averages and maximums. The estimated RRs were then used to make projections of the numbers of likely respiratory hospital admissions in the 2050s attributable to air pollution, based on emission projections from a number of Representative Concentration Pathways (RCP). NO 2 exhibited the largest association with respiratory hospital admissions out of the pollutants considered, with estimated increased risks of between 0.9 and 1.6% for a one standard deviation increase in concentrations. In the future the projected numbers of respiratory hospital admissions attributable to NO 2 in the 2050s are lower than present day rates under 3 Representative Concentration Pathways (RCPs): 2.6, 6.0, and 8.5, which is due to projected reductions in future NO 2 emissions and concentrations. NO 2 concentrations exhibit consistent substantial present-day health effects regardless of how a representative concentration is constructed in space and time. Thus as concentrations are predicted to remain above limits set by European Union Legislation until the 2030s in parts of urban England, it will remain a substantial health risk for some time.

Statistical evaluation of time-dependent metabolite concentrations: estimation of post-mortem intervals based on in situ 1H-MRS of the brain.

PubMed

Scheurer, Eva; Ith, Michael; Dietrich, Daniel; Kreis, Roland; Hüsler, Jürg; Dirnhofer, Richard; Boesch, Chris

2005-05-01

Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs. Copyright 2004 John Wiley & Sons, Ltd.

Lung cancer prevalence associated with radon exposure in Norwegian homes.

PubMed

Hassfjell, Christina Søyland; Grimsrud, Tom Kristian; Standring, William J F; Tretli, Steinar

2017-08-22

Radioactive radon gas is generated from uranium and thorium in underlying rocks and seeps into buildings. The gas and its decay products emit carcinogenic radiation and are regarded as the second most important risk factor for lung cancer after active tobacco smoking. The average radon concentration in Norwegian homes is higher than in most other Western countries. From a health and cost perspective, it is important to be able to quantify the risk of lung cancer posed by radon exposure. We estimated the radon-related risk of lung cancer in Norway based on risk estimates from the largest pooled analysis of European case-control studies, combined with the hitherto largest set of data on radon concentration measurements in Norwegian homes. Based on these estimates, we calculate that radon is a contributory factor in 12 % of all cases of lung cancer annually, assuming an average radon concentration of 88 Bq/m3 in Norwegian homes. For 2015, this accounted for 373 cases of lung cancer, with an approximate 95 % confidence interval of 145 – 682. Radon most likely contributes to a considerable number of cases of lung cancer. Since most cases of radon-associated lung cancer involve smokers or former smokers, a reduction of the radon concentration in homes could be a key measure to reduce the risk, especially for persons who are unable to quit smoking. The uncertainty in the estimated number of radon-associated cases can be reduced through a new national radon mapping study with an improved design.

The effect of dilution and the use of a post-extraction nucleic acid purification column on the accuracy, precision, and inhibition of environmental DNA samples

USGS Publications Warehouse

Mckee, Anna M.; Spear, Stephen F.; Pierson, Todd W.

2015-01-01

Isolation of environmental DNA (eDNA) is an increasingly common method for detecting presence and assessing relative abundance of rare or elusive species in aquatic systems via the isolation of DNA from environmental samples and the amplification of species-specific sequences using quantitative PCR (qPCR). Co-extracted substances that inhibit qPCR can lead to inaccurate results and subsequent misinterpretation about a species’ status in the tested system. We tested three treatments (5-fold and 10-fold dilutions, and spin-column purification) for reducing qPCR inhibition from 21 partially and fully inhibited eDNA samples collected from coastal plain wetlands and mountain headwater streams in the southeastern USA. All treatments reduced the concentration of DNA in the samples. However, column purified samples retained the greatest sensitivity. For stream samples, all three treatments effectively reduced qPCR inhibition. However, for wetland samples, the 5-fold dilution was less effective than other treatments. Quantitative PCR results for column purified samples were more precise than the 5-fold and 10-fold dilutions by 2.2× and 3.7×, respectively. Column purified samples consistently underestimated qPCR-based DNA concentrations by approximately 25%, whereas the directional bias in qPCR-based DNA concentration estimates differed between stream and wetland samples for both dilution treatments. While the directional bias of qPCR-based DNA concentration estimates differed among treatments and locations, the magnitude of inaccuracy did not. Our results suggest that 10-fold dilution and column purification effectively reduce qPCR inhibition in mountain headwater stream and coastal plain wetland eDNA samples, and if applied to all samples in a study, column purification may provide the most accurate relative qPCR-based DNA concentrations estimates while retaining the greatest assay sensitivity.

Comparative study of disinfectants for use in low-cost gravity driven household water purifiers.

PubMed

Patil, Rajshree A; Kausley, Shankar B; Balkunde, Pradeep L; Malhotra, Chetan P

2013-09-01

Point-of-use (POU) gravity-driven household water purifiers have been proven to be a simple, low-cost and effective intervention for reducing the impact of waterborne diseases in developing countries. The goal of this study was to compare commonly used water disinfectants for their feasibility of adoption in low-cost POU water purifiers. The potency of each candidate disinfectant was evaluated by conducting a batch disinfection study for estimating the concentration of disinfectant needed to inactivate a given concentration of the bacterial strain Escherichia coli ATCC 11229. Based on the concentration of disinfectant required, the size, weight and cost of a model purifier employing that disinfectant were estimated. Model purifiers based on different disinfectants were compared and disinfectants which resulted in the most safe, compact and inexpensive purifiers were identified. Purifiers based on bromine, tincture iodine, calcium hypochlorite and sodium dichloroisocyanurate were found to be most efficient, cost effective and compact with replacement parts costing US$3.60-6.00 for every 3,000 L of water purified and are thus expected to present the most attractive value proposition to end users.

Estimating suspended sediment and trace element fluxes in large river basins: Methodological considerations as applied to the NASQAN programme

USGS Publications Warehouse

Horowitz, A.J.; Elrick, K.A.; Smith, J.J.

2001-01-01

In 1994, the NASQAN (National Stream Quality Accounting Network) programme was redesigned as a flux-based water-quality monitoring network for the Mississippi, Columbia, Colorado, and Rio Grande Basins. As the new programme represented a departure from the original, new sampling, processing, analytical, and data handling procedures had to be selected/developed to provide data on discharge, suspended sediment concentration, and the concentrations of suspended sediment and dissolved trace elements. Annual suspended sediment fluxes were estimated by summing daily instantaneous fluxes based on predicted suspended sediment concentrations derived from discharge-based log-log regression (rating-curve) models. The models were developed using both historical and current site-specific discharge and suspended sediment concentrations. Errors using this approach typically are less than ?? 10% for the 3-year reporting period; however, the magnitude of the errors increases substantially for temporal spans shorter than 1 year. Total, rather than total-recoverable, suspended sediment-associated trace element concentrations were determined by direct analysis of material dewatered from large-volume whole-water samples. Site-specific intra- and inter-annual suspended sediment-associated chemical variations were less (typically by no more than a factor of two) than those for either discharge or suspended sediment concentrations (usually more than 10-fold). The concentrations, hence the annual fluxes, for suspended sediment-associated phosphorus and organic carbon, determined by direct analyses, were higher than those determined using a more traditional paired, whole-water/filtered-water approach (by factors ranging from 1.5- to 10-fold). This may be important for such issues as eutrophication and coastal productivity. Filtered water-associated (dissolved) trace element concentrations were markedly lower than those determined during the historical NASQAN programme; many were below their respective detection limits. This resulted from the use of clean sampling, processing, and analytical protocols. Hence, the fluxes for filtered water-associated (dissolved) Ag, Pb, Co, V, Be, Sb, and Se, as well as the total (filtered water plus suspended sediment-associated) fluxes for these constituents, could not be estimated.

Rapid estimation of concentration of aromatic classes in middistillate fuels by high-performance liquid chromatography

NASA Technical Reports Server (NTRS)

Otterson, D. A.; Seng, G. T.

1985-01-01

An high performance liquid chromatography (HPLC) method to estimate four aromatic classes in middistillate fuels is presented. Average refractive indices are used in a correlation to obtain the concentrations of each of the aromatic classes from HPLC data. The aromatic class concentrations can be obtained in about 15 min when the concentration of the aromatic group is known. Seven fuels with a wide range of compositions were used to test the method. Relative errors in the concentration of the two major aromatic classes were not over 10 percent. Absolute errors of the minor classes were all less than 0.3 percent. The data show that errors in group-type analyses using sulfuric acid derived standards are greater for fuels containing high concentrations of polycyclic aromatics. Corrections are based on the change in refractive index of the aromatic fraction which can occur when sulfuric acid and the fuel react. These corrections improved both the precision and the accuracy of the group-type results.

Perfluorinated compounds and polybrominated diphenyl ethers in great blue heron eggs from Indiana Dunes National Lakeshore, Indiana

USGS Publications Warehouse

Custer, T.W.; Kannan, K.; Tao, L.; Saxena, A.R.; Route, B.

2009-01-01

In 2007 archived great blue heron (Ardea herodias) eggs collected from Indiana Dunes National Lakeshore, IN, (Indiana Dunes) in 1993 were analyzed for 11 perfluorinated compounds (PFCs) and 7 polybrominated diphenyl ethers (PBDEs). Concentrations of perfluorooctane sulfonate, the major contributor to total PFC concentrations, were below the toxicity thresholds estimated for bobwhite quail (Colinus virginianus) and mallards (Anas platyrhynchos), but within the toxicity threshold estimated for white leghorn chickens (Gallus domesticus). The ranking of PBDE congener concentrations by percent concentration (PBDE-47 > -99 > -100 > -153 > -154 > -28 > -183) was consistent with the Penta-PBDE formulation. Total PBDE concentrations in great blue heron eggs from Indiana Dunes were elevated and probably reflect local contamination from highly urbanized and industrialized inputs into Lake Michigan. Polybrominated diphenyl ether concentrations were within levels associated with altered reproductive behavior in other avian species and based on trends in other Great Lakes birds are probably higher today.

Modeled and monitored variation in space and time of PCB-153 concentrations in air, sediment, soil and aquatic biota on a European scale.

PubMed

Hauck, Mara; Huijbregts, Mark A J; Hollander, Anne; Hendriks, A Jan; van de Meent, Dik

2010-08-15

We evaluated various modeling options for estimating concentrations of PCB-153 in the environment and in biota across Europe, using a nested multimedia fate model coupled with a bioaccumulation model. The most detailed model set up estimates concentrations in air, soil, fresh water sediment and fresh water biota with spatially explicit environmental characteristics and spatially explicit emissions to air and water in the period 1930-2005. Model performance was evaluated with the root mean square error (RMSE(log)), based on the difference between estimated and measured concentrations. The RMSE(log) was 5.4 for air, 5.6-6.3 for sediment and biota, and 5.5 for soil in the most detailed model scenario. Generally, model estimations tended to underestimate observed values for all compartments, except air. The decline in observed concentrations was also slightly underestimated by the model for the period where measurements were available (1989-2002). Applying a generic model setup with averaged emissions and averaged environmental characteristics, the RMSE(log) increased to 21 for air and 49 for sediment. For soil the RMSE(log) decreased to 3.5. We found that including spatial variation in emissions was most relevant for all compartments, except soil, while including spatial variation in environmental characteristics was less influential. For improving predictions of concentrations in sediment and aquatic biota, including emissions to water was found to be relevant as well. Copyright 2009 Elsevier B.V. All rights reserved.

Can we use modelling methodologies to assess airborne benzo[a]pyrene from biomonitors? A comprehensive evaluation approach

NASA Astrophysics Data System (ADS)

Ratola, N.; Jiménez-Guerrero, P.

2015-09-01

Biomonitoring data available on levels of atmospheric polycyclic aromatic hydrocarbons (PAHs) in pine needles from the Iberian Peninsula was used to estimate air concentrations of benzo[a]pyrene (BaP) and, at the same time, fuelled the comparison with chemistry transport model representations. Simulations with the modelling system WRF + CHIMERE were validated against data from the European Monitoring and Evaluation Programme (EMEP) air sampling network and using modelled atmospheric concentrations as a consistent reference in order to compare the performance of vegetation-to-air estimating methods. A spatial and temporal resolution of 9 km and 1 h was implemented. The field-based database relied on a pine needles sampling scheme comprising 33 sites in Portugal and 37 sites in Spain complemented with the BaP measurements available from the EMEP sites. The ability of pine needles to act as biomonitoring markers for the atmospheric concentrations of BaP was estimated converting the levels obtained in pine needles into air concentrations by six different approaches, one of them presenting realistic concentrations when compared to the modelled atmospheric values. The justification for this study is the gaps still existing in the knowledge of the life cycles of semi-volatile organic compounds (SVOCs), particularly the partition processes between air and vegetation. The strategy followed in this work allows the definition of the transport patterns (e.g. dispersion) established by the model for atmospheric concentrations and the estimated values in vegetation.

Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed

USGS Publications Warehouse

Moyer, Douglas; Hirsch, Robert M.; Hyer, Kenneth

2012-01-01

Nutrient and sediment fluxes and changes in fluxes over time are key indicators that water resource managers can use to assess the progress being made in improving the structure and function of the Chesapeake Bay ecosystem. The U.S. Geological Survey collects annual nutrient (nitrogen and phosphorus) and sediment flux data and computes trends that describe the extent to which water-quality conditions are changing within the major Chesapeake Bay tributaries. Two regression-based approaches were compared for estimating annual nutrient and sediment fluxes and for characterizing how these annual fluxes are changing over time. The two regression models compared are the traditionally used ESTIMATOR and the newly developed Weighted Regression on Time, Discharge, and Season (WRTDS). The model comparison focused on answering three questions: (1) What are the differences between the functional form and construction of each model? (2) Which model produces estimates of flux with the greatest accuracy and least amount of bias? (3) How different would the historical estimates of annual flux be if WRTDS had been used instead of ESTIMATOR? One additional point of comparison between the two models is how each model determines trends in annual flux once the year-to-year variations in discharge have been determined. All comparisons were made using total nitrogen, nitrate, total phosphorus, orthophosphorus, and suspended-sediment concentration data collected at the nine U.S. Geological Survey River Input Monitoring stations located on the Susquehanna, Potomac, James, Rappahannock, Appomattox, Pamunkey, Mattaponi, Patuxent, and Choptank Rivers in the Chesapeake Bay watershed. Two model characteristics that uniquely distinguish ESTIMATOR and WRTDS are the fundamental model form and the determination of model coefficients. ESTIMATOR and WRTDS both predict water-quality constituent concentration by developing a linear relation between the natural logarithm of observed constituent concentration and three explanatory variables—the natural log of discharge, time, and season. ESTIMATOR uses two additional explanatory variables—the square of the log of discharge and time-squared. Both models determine coefficients for variables for a series of estimation windows. ESTIMATOR establishes variable coefficients for a series of 9-year moving windows; all observed constituent concentration data within the 9-year window are used to establish each coefficient. Conversely, WRTDS establishes variable coefficients for each combination of discharge and time using only observed concentration data that are similar in time, season, and discharge to the day being estimated. As a result of these distinguishing characteristics, ESTIMATOR reproduces concentration-discharge relations that are closely approximated by a quadratic or linear function with respect to both the log of discharge and time. Conversely, the linear model form of WRTDS coupled with extensive model windowing for each combination of discharge and time allows WRTDS to reproduce observed concentration-discharge relations that are more sinuous in form. Another distinction between ESTIMATOR and WRTDS is the reporting of uncertainty associated with the model estimates of flux and trend. ESTIMATOR quantifies the standard error of prediction associated with the determination of flux and trends. The standard error of prediction enables the determination of the 95-percent confidence intervals for flux and trend as well as the ability to test whether the reported trend is significantly different from zero (where zero equals no trend). Conversely, WRTDS is unable to propagate error through the many (over 5,000) models for unique combinations of flow and time to determine a total standard error. As a result, WRTDS flux estimates are not reported with confidence intervals and a level of significance is not determined for flow-normalized fluxes. The differences between ESTIMATOR and WRTDS, with regard to model form and determination of model coefficients, have an influence on the determination of nutrient and sediment fluxes and associated changes in flux over time as a result of management activities. The comparison between the model estimates of flux and trend was made for combinations of five water-quality constituents at nine River Input Monitoring stations. The major findings with regard to nutrient and sediment fluxes are as follows: (1)WRTDS produced estimates of flux for all combinations that were more accurate, based on reduction in root mean squared error, than flux estimates from ESTIMATOR; (2) for 67 percent of the combinations, WRTDS and ESTIMATOR both produced estimates of flux that were minimally biased compared to observed fluxes(flux bias = tendency to over or underpredict flux observations); however, for 33 percent of the combinations, WRTDS produced estimates of flux that were considerably less biased (by at least 10 percent) than flux estimates from ESTIMATOR; (3) the average percent difference in annual fluxes generated by ESTIMATOR and WRTDS was less than 10 percent at 80 percent of the combinations; and (4) the greatest differences related to flux bias and annual fluxes all occurred for combinations where the pattern in observed concentration-discharge relation was sinuous (two points of inflection) rather than linear or quadratic (zero or one point of inflection). The major findings with regard to trends are as follows: (1) both models produce water-quality trends that have factored in the year-to-year variations in flow; (2) trends in water-quality condition are represented by ESTIMATOR as a trend in flow-adjusted concentration and by WRTDS as a flow normalized flux; (3) for 67 percent of the combinations with trend estimates, the WRTDS trends in flow-normalized flux are in the same direction and magnitude to the ESTIMATOR trends in flow-adjusted concentration, and at the remaining 33 percent the differences in trend magnitude and direction are related to fundamental differences between concentration and flux; and (4) the majority (85 percent) of the total nitrogen, nitrate, and orthophosphorus combinations exhibited long-term (1985 to 2010) trends in WRTDS flow-normalized flux that indicate improvement or reduction in associated flux and the majority (83 percent) of the total phosphorus (from 1985 to 2010) and suspended sediment (from 2001 to 2010) combinations exhibited trends in WRTDS flow-normalized flux that indicate degradation or increases in the flux delivered.

Vertical distribution of aerosols in the vicinity of Mexico City during MILAGRO-2006 Campaign

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewandowski, P.A.; Kleinman, L.; Eichinger, W. E.

On 7 March 2006, a mobile, ground-based, vertical pointing, elastic lidar system made a North-South transect through the Mexico City basin. Column averaged, aerosol size distribution (ASD) measurements were made on the ground concurrently with the lidar measurements. The ASD ground measurements allowed calculation of the column averaged mass extinction efficiency (MEE) for the lidar system (1064 nm). The value of column averaged MEE was combined with spatially resolved lidar extinction coefficients to produce total aerosol mass concentration estimates with the resolution of the lidar (1.5 m vertical spatial and 1 s temporal). Airborne ASD measurements from DOE G-1 aircraftmore » made later in the day on 7 March 2006, allowed the evaluation of the assumptions of constant ASD with height and time used for estimating the column averaged MEE. The results showed that the aerosol loading within the basin is about twice what is observed outside of the basin. The total aerosol base concentrations observed in the basin are of the order of 200 {mu}g/m{sup 3} and the base levels outside are of the order of 100 {mu}g/m{sup 3}. The local heavy traffic events can introduce aerosol levels near the ground as high as 900 {mu}g/m{sup 3}. The article presents the methodology for estimating aerosol mass concentration from mobile, ground-based lidar measurements in combination with aerosol size distribution measurements. An uncertainty analysis of the methodology is also presented.« less

Dietary Iron Bioavailability: Agreement between Estimation Methods and Association with Serum Ferritin Concentrations in Women of Childbearing Age

PubMed Central

Dias, Gisele Cristina; Morimoto, Juliana Massami; Marchioni, Dirce Maria Lobo; Colli, Célia

2018-01-01

Predictive iron bioavailability (FeBio) methods aimed at evaluating the association between diet and body iron have been proposed, but few studies explored their validity and practical usefulness in epidemiological studies. In this cross-sectional study involving 127 women (18–42 years) with presumably steady-state body iron balance, correlations were checked among various FeBio estimates (probabilistic approach and meal-based and diet-based algorithms) and serum ferritin (SF) concentrations. Iron deficiency was defined as SF < 15 µg/L. Pearson correlation, Friedman test, and linear regression were employed. Iron intake and prevalence of iron deficiency were 10.9 mg/day and 12.6%. Algorithm estimates were strongly correlated (0.69≤ r ≥0.85; p < 0.001), although diet-based models (8.5–8.9%) diverged from meal-based models (11.6–12.8%; p < 0.001). Still, all algorithms underestimated the probabilistic approach (17.2%). No significant association was found between SF and FeBio from Monsen (1978), Reddy (2000), and Armah (2013) algorithms. Nevertheless, there was a 30–37% difference in SF concentrations between women stratified at extreme tertiles of FeBio from Hallberg and Hulthén (2000) and Collings’ (2013) models. The results demonstrate discordance of FeBio from probabilistic approach and algorithm methods while suggesting two models with best performances to rank individuals according to their bioavailable iron intakes. PMID:29883384

Integrating Aggregate Exposure Pathway (AEP) and Adverse ...

EPA Pesticide Factsheets

High throughput toxicity testing (HTT) holds the promise of providing data for tens of thousands of chemicals that currently have no data due to the cost and time required for animal testing. Interpretation of these results require information linking the perturbations seen in vitro with adverse outcomes in vivo and requires knowledge of how estimated exposure to the chemicals compare to the in vitro concentrations that show an effect. This abstract discusses how Adverse Outcome Pathways (AOPs) can be used to link HTT with adverse outcomes of regulatory significance and how Aggregate Exposure Pathways (AEPs) can connect concentrations of environment stressors at a source with an expected target site concentration designed to provide exposure estimates that are comparable to concentrations identified in HTT. Presentation at the ICCA-LRI and JRC Workshop: Fit-For-Purpose Exposure Assessment For Risk-Based Decision Making

Contemporary Trends in the Acid-Base Status of the Two Acid-Sensitive Streams in Western Maryland

NASA Technical Reports Server (NTRS)

Eshleman, Keith N.; Kline, Kathleen M.; Morgan, Raymond P., II; Castro, Nancy M.; Negley, Timothy L.

2008-01-01

Recovery of streamwater acid neutralizing capacity (ANC) resulting from declines in regional acid deposition was examined using contemporary (1990-2005) data from two long-term monitoring stations located on the Appalachian Plateau in western Maryland, U.S. Two computational methods were used to estimate daily, monthly, and annual fluxes and discharge-weighted concentrations of ANC, sulfate, nitrate, and base cations over the period of record, and two statistical methods were used to evaluate long-term trends in fluxes and concentrations. The methods used to estimate concentrations, as well as the, statistical techniques, produced very similar results, underlining the robustness of the identified trends. We found clear evidence that streamwater sulfate concentrations have declined at an average rate of about 3 (microns)eq L(exp -1) yr(exp -1) at the two sites due to a 34% reduction in wet atmospheric sulfur deposition. Trends in nitrate concentrations appear to be related to other watershed factors, especially forest disturbance. The best evidence of recovery is based on a doubling of ANC (from 21 to 42 (microns)eq L(exp -1) at the more acid-sensitive site over the 16-year period. A slowing, or possible reversal, in the sulfate, nitrate, and SBC trends is evident in our data and may portend a decline in the rate of--or end to--further recovery.

Regional estimation of groundwater arsenic concentrations through systematical dynamic-neural modeling

NASA Astrophysics Data System (ADS)

Chang, Fi-John; Chen, Pin-An; Liu, Chen-Wuing; Liao, Vivian Hsiu-Chuan; Liao, Chung-Min

2013-08-01

Arsenic (As) is an odorless semi-metal that occurs naturally in rock and soil, and As contamination in groundwater resources has become a serious threat to human health. Thus, assessing the spatial and temporal variability of As concentration is highly desirable, particularly in heavily As-contaminated areas. However, various difficulties may be encountered in the regional estimation of As concentration such as cost-intensive field monitoring, scarcity of field data, identification of important factors affecting As, over-fitting or poor estimation accuracy. This study develops a novel systematical dynamic-neural modeling (SDM) for effectively estimating regional As-contaminated water quality by using easily-measured water quality variables. To tackle the difficulties commonly encountered in regional estimation, the SDM comprises of a neural network and four statistical techniques: the Nonlinear Autoregressive with eXogenous input (NARX) network, Gamma test, cross-validation, Bayesian regularization method and indicator kriging (IK). For practical application, this study investigated a heavily As-contaminated area in Taiwan. The backpropagation neural network (BPNN) is adopted for comparison purpose. The results demonstrate that the NARX network (Root mean square error (RMSE): 95.11 μg l-1 for training; 106.13 μg l-1 for validation) outperforms the BPNN (RMSE: 121.54 μg l-1 for training; 143.37 μg l-1 for validation). The constructed SDM can provide reliable estimation (R2 > 0.89) of As concentration at ungauged sites based merely on three easily-measured water quality variables (Alk, Ca2+ and pH). In addition, risk maps under the threshold of the WHO drinking water standard (10 μg l-1) are derived by the IK to visually display the spatial and temporal variation of the As concentration in the whole study area at different time spans. The proposed SDM can be practically applied with satisfaction to the regional estimation in study areas of interest and the estimation of missing, hazardous or costly data to facilitate water resources management.

Leachate concentrations from water leach and column leach tests on fly ash-stabilized soils

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bin-Shafique, S.; Benson, C.H.; Edil, T.B.

2006-01-15

Batch water leaching tests (WLTs) and column leaching tests (CLTs) were conducted on coal-combustion fly ashes, soil, and soil-fly ash mixtures to characterize leaching of Cd, Cr, Se, and Ag. The concentrations of these metals were also measured in the field at two sites where soft fine-grained soils were mechanically stabilized with fly ash. Concentrations in leachate from the WLTs on soil-fly ash mixtures are different from those on fly ash alone and cannot be accurately estimated based on linear dilution calculations using concentrations from WLTs on fly ash alone. The concentration varies nonlinearly with fly ash content due tomore » the variation in pH with fly ash content. Leachate concentrations are low when the pH of the leachate or the cation exchange capacity (CEC) of the soil is high. Initial concentrations from CLTs are higher than concentrations from WLTs due to differences in solid-liquid ratio, pH, and solid-liquid contact. However, both exhibit similar trends with fly ash content, leachate pH, and soil properties. Scaling factors can be applied to WLT concentrations (50 for Ag and Cd, 10 for Cr and Se) to estimate initial concentrations for CLTs. Concentrations in leachate collected from the field sites were generally similar or slightly lower than concentrations measured in CLTs on the same materials. Thus, CLTs appear to provide a good indication of conditions that occur in the field provided that the test conditions mimic the field conditions. In addition, initial concentrations in the field can be conservatively estimated from WLT concentrations using the aforementioned scaling factors provided that the pH of the infiltrating water is near neutral.« less

Methylmercury dose estimation from umbilical cord concentrations in patients with Minamata disease.

PubMed

Akagi, H; Grandjean, P; Takizawa, Y; Weihe, P

1998-05-01

The methylmercury exposure of patients with congenital or infantile Minamata disease is known only from a small number of analyses of umbilical cords. Four laboratories in Japan have analyzed a total of 176 samples of umbilical cord tissue obtained from Minamata. The highest concentrations were seen in cord tissue from children born during 1950-1965, i.e., the peak period of acetaldehyde production in Minamata before installation of waste water treatment. Twenty-four samples from patients diagnosed with Minamata disease showed a median mercury concentration of 1.63 microg/g and differed significantly from levels seen in cord tissue from control children. However, children diagnosed with mental retardation had mercury concentrations in cord that were intermediate between the two other groups. Using regression coefficients obtained at a study conducted at the Faroe Islands, the median cord mercury concentration from the children with Minamata disease is estimated to correspond to about 216 microg/L cord blood and 41 microg/g in maternal hair. Based on correlations reported in the literature, the median daily mercury intake of the women whose children developed Minamata disease can then be estimated at about 225 microg. Although these children had fully developed Minamata disease, the estimates of median mercury levels are only four to five times higher than current mercury exposure limits. Copyright 1998 Academic Press.

Blending Multiple Nitrogen Dioxide Data Sources for Neighborhood Estimates of Long-Term Exposure for Health Research.

PubMed

Hanigan, Ivan C; Williamson, Grant J; Knibbs, Luke D; Horsley, Joshua; Rolfe, Margaret I; Cope, Martin; Barnett, Adrian G; Cowie, Christine T; Heyworth, Jane S; Serre, Marc L; Jalaludin, Bin; Morgan, Geoffrey G

2017-11-07

Exposure to traffic related nitrogen dioxide (NO 2 ) air pollution is associated with adverse health outcomes. Average pollutant concentrations for fixed monitoring sites are often used to estimate exposures for health studies, however these can be imprecise due to difficulty and cost of spatial modeling at the resolution of neighborhoods (e.g., a scale of tens of meters) rather than at a coarse scale (around several kilometers). The objective of this study was to derive improved estimates of neighborhood NO 2 concentrations by blending measurements with modeled predictions in Sydney, Australia (a low pollution environment). We implemented the Bayesian maximum entropy approach to blend data with uncertainty defined using informative priors. We compiled NO 2 data from fixed-site monitors, chemical transport models, and satellite-based land use regression models to estimate neighborhood annual average NO 2 . The spatial model produced a posterior probability density function of estimated annual average concentrations that spanned an order of magnitude from 3 to 35 ppb. Validation using independent data showed improvement, with root mean squared error improvement of 6% compared with the land use regression model and 16% over the chemical transport model. These estimates will be used in studies of health effects and should minimize misclassification bias.

Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases

NASA Astrophysics Data System (ADS)

Arora, V. K.; Scinocca, J. F.; Boer, G. J.; Christian, J. R.; Denman, K. L.; Flato, G. M.; Kharin, V. V.; Lee, W. G.; Merryfield, W. J.

2011-03-01

The response of the second-generation Canadian earth system model (CanESM2) to historical (1850-2005) and future (2006-2100) natural and anthropogenic forcing is assessed using the newly-developed representative concentration pathways (RCPs) of greenhouse gases (GHGs) and aerosols. Allowable emissions required to achieve the future atmospheric CO2 concentration pathways, are reported for the RCP 2.6, 4.5 and 8.5 scenarios. For the historical 1850-2005 period, cumulative land plus ocean carbon uptake and, consequently, cumulative diagnosed emissions compare well with observation-based estimates. The simulated historical carbon uptake is somewhat weaker for the ocean and stronger for the land relative to their observation-based estimates. The simulated historical warming of 0.9°C compares well with the observation-based estimate of 0.76 ± 0.19°C. The RCP 2.6, 4.5 and 8.5 scenarios respectively yield warmings of 1.4, 2.3, and 4.9°C and cumulative diagnosed fossil fuel emissions of 182, 643 and 1617 Pg C over the 2006-2100 period. The simulated warming of 2.3°C over the 1850-2100 period in the RCP 2.6 scenario, with the lowest concentration of GHGs, is slightly larger than the 2°C warming target set to avoid dangerous climate change by the 2009 UN Copenhagen Accord. The results of this study suggest that limiting warming to roughly 2°C by the end of this century is unlikely since it requires an immediate ramp down of emissions followed by ongoing carbon sequestration in the second half of this century.

Hypnosis control based on the minimum concentration of anesthetic drug for maintaining appropriate hypnosis.

PubMed

Furutani, Eiko; Nishigaki, Yuki; Kanda, Chiaki; Takeda, Toshihiro; Shirakami, Gotaro

2013-01-01

This paper proposes a novel hypnosis control method using Auditory Evoked Potential Index (aepEX) as a hypnosis index. In order to avoid side effects of an anesthetic drug, it is desirable to reduce the amount of an anesthetic drug during surgery. For this purpose many studies of hypnosis control systems have been done. Most of them use Bispectral Index (BIS), another hypnosis index, but it has problems of dependence on anesthetic drugs and nonsmooth change near some particular values. On the other hand, aepEX has an ability of clear distinction between patient consciousness and unconsciousness and independence of anesthetic drugs. The control method proposed in this paper consists of two elements: estimating the minimum effect-site concentration for maintaining appropriate hypnosis and adjusting infusion rate of an anesthetic drug, propofol, using model predictive control. The minimum effect-site concentration is estimated utilizing the property of aepEX pharmacodynamics. The infusion rate of propofol is adjusted so that effect-site concentration of propofol may be kept near and always above the minimum effect-site concentration. Simulation results of hypnosis control using the proposed method show that the minimum concentration can be estimated appropriately and that the proposed control method can maintain hypnosis adequately and reduce the total infusion amount of propofol.

Annual sediment flux estimates in a tidal strait using surrogate measurements

USGS Publications Warehouse

Ganju, N.K.; Schoellhamer, D.H.

2006-01-01

Annual suspended-sediment flux estimates through Carquinez Strait (the seaward boundary of Suisun Bay, California) are provided based on surrogate measurements for advective, dispersive, and Stokes drift flux. The surrogates are landward watershed discharge, suspended-sediment concentration at one location in the Strait, and the longitudinal salinity gradient. The first two surrogates substitute for tidally averaged discharge and velocity-weighted suspended-sediment concentration in the Strait, thereby providing advective flux estimates, while Stokes drift is estimated with suspended-sediment concentration alone. Dispersive flux is estimated using the product of longitudinal salinity gradient and the root-mean-square value of velocity-weighted suspended-sediment concentration as an added surrogate variable. Cross-sectional measurements validated the use of surrogates during the monitoring period. During high freshwater flow advective and dispersive flux were in the seaward direction, while landward dispersive flux dominated and advective flux approached zero during low freshwater flow. Stokes drift flux was consistently in the landward direction. Wetter than average years led to net export from Suisun Bay, while dry years led to net sediment import. Relatively low watershed sediment fluxes to Suisun Bay contribute to net export during the wet season, while gravitational circulation in Carquinez Strait and higher suspended-sediment concentrations in San Pablo Bay (seaward end of Carquinez Strait) are responsible for the net import of sediment during the dry season. Annual predictions of suspended-sediment fluxes, using these methods, will allow for a sediment budget for Suisun Bay, which has implications for marsh restoration and nutrient/contaminant transport. These methods also provide a general framework for estimating sediment fluxes in estuarine environments, where temporal and spatial variability of transport are large. ?? 2006 Elsevier Ltd. All rights reserved.

Gas hydrate concentration and characteristics within Hydrate Ridge inferred from multicomponent seismic reflection data

NASA Astrophysics Data System (ADS)

Kumar, Dhananjay; Sen, Mrinal K.; Bangs, Nathan L.

2007-12-01

A seismic experiment composed of streamer and ocean bottom seismometer (OBS) surveys was conducted in the summer of 2002 at southern Hydrate Ridge, offshore Oregon, to map the gas hydrate distribution within the hydrate stability zone. Gas hydrate concentrations within the reservoir can be estimated with P wave velocity (Vp); however, we can further constrain gas hydrate concentrations using S wave velocity (Vs), and use Vs through its relationship to Vp (Vp/Vs) to reveal additional details such as gas hydrate form within the matrix (i.e., hydrate cements the grains, becomes part of the matrix frame or floats in pore space). Both Vp and Vs can be derived simultaneously by inverting multicomponent seismic data. In this study, we use OBS data to estimate seismic velocities where both gas hydrate and free gas are present in the shallow sediments. Once Vp and Vs are estimated, they are simultaneously matched with modeled velocities to estimate the gas hydrate concentration. We model Vp using an equation based on a modification of Wood's equation that incorporates an appropriate rock physics model and Vs using an empirical relation. The gas hydrate concentration is estimated to be up to 7% of the rock volume, or 12% of the pore space. However, Vp and Vs do not always fit the model simultaneously. Vp can vary substantially more than Vs. Thus we conclude that a model, in which higher concentrations of hydrate do not affect shear stiffness, is more appropriate. Results suggest gas hydrates form within the pore space of the sediments and become part of the rock framework in our survey area.

A Bayesian geostatistical approach for evaluating the uncertainty of contaminant mass discharges from point sources

NASA Astrophysics Data System (ADS)

Troldborg, M.; Nowak, W.; Binning, P. J.; Bjerg, P. L.

2012-12-01

Estimates of mass discharge (mass/time) are increasingly being used when assessing risks of groundwater contamination and designing remedial systems at contaminated sites. Mass discharge estimates are, however, prone to rather large uncertainties as they integrate uncertain spatial distributions of both concentration and groundwater flow velocities. For risk assessments or any other decisions that are being based on mass discharge estimates, it is essential to address these uncertainties. We present a novel Bayesian geostatistical approach for quantifying the uncertainty of the mass discharge across a multilevel control plane. The method decouples the flow and transport simulation and has the advantage of avoiding the heavy computational burden of three-dimensional numerical flow and transport simulation coupled with geostatistical inversion. It may therefore be of practical relevance to practitioners compared to existing methods that are either too simple or computationally demanding. The method is based on conditional geostatistical simulation and accounts for i) heterogeneity of both the flow field and the concentration distribution through Bayesian geostatistics (including the uncertainty in covariance functions), ii) measurement uncertainty, and iii) uncertain source zone geometry and transport parameters. The method generates multiple equally likely realizations of the spatial flow and concentration distribution, which all honour the measured data at the control plane. The flow realizations are generated by analytical co-simulation of the hydraulic conductivity and the hydraulic gradient across the control plane. These realizations are made consistent with measurements of both hydraulic conductivity and head at the site. An analytical macro-dispersive transport solution is employed to simulate the mean concentration distribution across the control plane, and a geostatistical model of the Box-Cox transformed concentration data is used to simulate observed deviations from this mean solution. By combining the flow and concentration realizations, a mass discharge probability distribution is obtained. Tests show that the decoupled approach is both efficient and able to provide accurate uncertainty estimates. The method is demonstrated on a Danish field site contaminated with chlorinated ethenes. For this site, we show that including a physically meaningful concentration trend and the co-simulation of hydraulic conductivity and hydraulic gradient across the transect helps constrain the mass discharge uncertainty. The number of sampling points required for accurate mass discharge estimation and the relative influence of different data types on mass discharge uncertainty is discussed.

Long-term radon concentrations estimated from 210Po embedded in glass

USGS Publications Warehouse

Lively, R.S.; Steck, D.J.

1993-01-01

Measured surface-alpha activity on glass exposed in radon chambers and houses has a linear correlation to the integrated radon exposure. Experimental results in chambers and houses have been obtained on glass exposed to radon concentrations between 100 Bq m-3 and 9 MBq m-3 for periods of a few days to several years. Theoretical calculations support the experimental results through a model that predicts the fractions of airborne activity that deposit and become embedded or adsorbed. The combination of measured activity and calculated embedded fraction for a given deposition environment can be applied to most indoor areas and produces a better estimate for lifetime radon exposure than estimates based on short-term indoor radon measurements.

Quantitative in vivo cell-surface receptor imaging in oncology: kinetic modeling & paired-agent principles from nuclear medicine and optical imaging

PubMed Central

Tichauer, Kenneth M.; Wang, Yu; Pogue, Brian W.; Liu, Jonathan T. C.

2015-01-01

The development of methods to accurately quantify cell-surface receptors in living tissues would have a seminal impact in oncology. For example, accurate measures of receptor density in vivo could enhance early detection or surgical resection of tumors via protein-based contrast, allowing removal of cancer with high phenotype specificity. Alternatively, accurate receptor expression estimation could be used as a biomarker to guide patient-specific clinical oncology targeting of the same molecular pathway. Unfortunately, conventional molecular contrast-based imaging approaches are not well adapted to accurately estimating the nanomolar-level cell-surface receptor concentrations in tumors, as most images are dominated by nonspecific sources of contrast such as high vascular permeability and lymphatic inhibition. This article reviews approaches for overcoming these limitations based upon tracer kinetic modeling and the use of emerging protocols to estimate binding potential and the related receptor concentration. Methods such as using single time point imaging or a reference-tissue approach tend to have low accuracy in tumors, whereas paired-agent methods or advanced kinetic analyses are more promising to eliminate the dominance of interstitial space in the signals. Nuclear medicine and optical molecular imaging are the primary modalities used, as they have the nanomolar level sensitivity needed to quantify cell-surface receptor concentrations present in tissue, although each likely has a different clinical niche. PMID:26134619

Estimation and application of indicator values for common macroinvertebrate genera and families of the United States

USGS Publications Warehouse

Carlisle, D.M.; Meador, M.R.; Moulton, S.R.; Ruhl, P.M.

2007-01-01

Tolerance of macroinvertebrate taxa to chemical and physical stressors is widely used in the analysis and interpretation of bioassessment data, but many estimates lack empirical bases. Our main objective was to estimate genus- and family-level indicator values (IVs) from a data set of macroinvertebrate communities, chemical, and physical stressors collected in a consistent manner throughout the United States. We then demonstrated an application of these IVs to detect alterations in benthic macroinvertebrate assemblages along gradients of urbanization in New England and Alabama. Principal components analysis (PCA) was used to create synthetic gradients of chemical stressors, for which genus- and family-level weighted averages (WAs) were calculated. Based on results of PCA, WAs were calculated for three synthetic gradients (ionic concentration, nutrient concentration, and dissolved oxygen/water temperature) and two uncorrelated physical variables (suspended sediment concentration and percent fines). Indicator values for each stress gradient were subsequently created by transforming WAs into ten ordinal ranks based on percentiles of values across all taxa. Mean IVs of genera and families were highly correlated to road density in Alabama and New England, and supported the conclusions of independent assessments of the chemical and physical stressors acting in each geographic area. Family IVs were nearly as responsive to urbanization as genus IVs. The limitations of widespread use of these IVs are discussed.

Effects of forage:concentrate ratio and forage type on apparent digestibility, ruminal fermentation, and microbial growth in goats.

PubMed

Cantalapiedra-Hijar, G; Yáñez-Ruiz, D R; Martín-García, A I; Molina-Alcaide, E

2009-02-01

The effects of forage type and forage:concentrate ratio (F:C) on apparent nutrient digestibility, ruminal fermentation, and microbial growth were investigated in goats. A comparison between liquid (LAB) and solid (SAB)-associated bacteria to estimate microbial N flow (MNF) from urinary purine derivative excretion was also examined. Treatments were a 2 x 2 factorial arrangement of forage type (grass hay vs. alfalfa hay) and high vs. low F:C (70:30 and 30:70, respectively). Four ruminally cannulated goats were fed, at maintenance intake, 4 experimental diets according to a 4 x 4 Latin square design. High-concentrate diets resulted in greater (P < 0.001) nutrient digestibility except for ADF. However, CP digestibility increased (P < 0.001) only for the high-concentrate diets including grass hay. Likewise, N retention, ruminal NH(3)-N concentration, and urinary excretion of purine derivatives increased (P < 0.05) with increasing concentrate in animals fed diets based on grass hay (0.23 vs. 0.13 g of retained N/g of digested N, 30.1 vs. 12.9 mg of NH(3)-N/100 mL, and 11.5 vs. 8.40 mmol/d, respectively), but not (P > 0.05) when diets included alfalfa hay. Total protozoa numbers and holotricha proportion were greater and less (P < 0.001), respectively, in high- than in low-concentrate diets. The F:C affected (P < 0.001) ruminal pH but not total VFA concentration (P = 0.12). Ammonia-N concentration was similar (P = 0.13) over time, whereas pH, VFA concentration, and protozoa numbers differed (P < 0.001) among diets. Estimated MNF was strongly influenced by using either the purine bases:N ratio obtained in our experimental conditions or values reported in the literature for small ruminants. There was a F:C effect (P = 0.006) on MNF estimated from LAB but not from SAB. The effect of F:C shifting from 70:30 to 30:70 in goat diets depends on the type of forage used. The MNF measured in goats fed different diets was influenced by the bacterial pellet (LAB or SAB). In addition, the purine bases:N ratio values found were different from those reported in the literature, which underlines the need for these variables to be analyzed directly in pellets isolated from specific animals and experimental conditions.

Estimates of residence time and related variations in quality of ground water beneath Submarine Base Bangor and vicinity, Kitsap County, Washington

USGS Publications Warehouse

Cox, S.E.

2003-01-01

Estimates of residence time of ground water beneath Submarine Base Bangor and vicinity ranged from less than 50 to 4,550 years before present, based on analysis of the environmental tracers tritium, chlorofluorocarbons (CFCs), and carbon-14 (14C), in 33 ground-water samples collected from wells tapping the ground-water system. The concentrations of multiple environmental tracers tritium, CFCs, and 14C were used to classify ground water as modern (recharged after 1953), pre-modern (recharged prior to 1953), or indeterminate. Estimates of the residence time of pre-modern ground water were based on evaluation of 14C of dissolved inorganic carbon present in ground water using geochemical mass-transfer modeling to account for the interactions of the carbon in ground water with carbon of the aquifer sediments. Ground-water samples were obtained from two extensive aquifers and from permeable interbeds within the thick confining unit separating the sampled aquifers. Estimates of ground-water residence time for all ground-water samples from the shallow aquifer were less than 45 years and were classified as modern. Estimates of the residence time of ground water in the permeable interbeds within the confining unit ranged from modern to 4,200 years and varied spatially. Near the recharge area, residence times in the permeable interbeds typically were less than 800 years, whereas near the discharge area residence times were in excess of several thousand years. In the deeper aquifers, estimates of ground-water residence times typically were several thousand years but ranged from modern to 4,550 years. These estimates of ground-water residence time based on 14C were often larger than estimates of ground-water residence time developed by particle-tracking analysis using a ground-water flow model. There were large uncertainties?on the order of 1,000-2,000 years?in the estimates based on 14C. Modern ground-water tracers found in some samples from large-capacity production wells screened in the deeper aquifer may be the result of preferential ground-water pathways or induced downward flow caused by pumping stress. Spatial variations in water quality were used to develop a conceptual model of chemical evolution of ground water. Stable isotope ratios of deuterium and oxygen-18 in the 33 ground-water samples were similar, indicating similar climatic conditions and source of precipitation recharge for all of the sampled ground water. Oxidation of organic matter and mineral dissolution increased the concentrations of dissolved inorganic carbon and common ions in downgradient ground waters. However, the largest concentrations were not found near areas of ground-water discharge, but at intermediate locations where organic carbon concentrations were greatest. Dissolved methane, derived from microbial methanogenesis, was present in some ground waters. Methanogenesis resulted in substantial alteration of the carbon isotopic composition of ground water. The NETPATH geochemical model code was used to model mass-transfers of carbon affecting the 14C estimate of ground-water residence time. Carbon sources in ground water include dispersed particulate organic matter present in the confining unit separating the two aquifers and methane present in some ground water. Carbonate minerals were not observed in the lithologic material of the ground-water system but may be present, because they have been found in the bedrock of stream drainages that contribute sediment to the study area.

Devolatilization Analysis in a Twin Screw Extruder by using the Flow Analysis Network (FAN) Method

NASA Astrophysics Data System (ADS)

Tomiyama, Hideki; Takamoto, Seiji; Shintani, Hiroaki; Inoue, Shigeki

We derived the theoretical formulas for three mechanisms of devolatilization in a twin screw extruder. These are flash, surface refreshment and forced expansion. The method for flash devolatilization is based on the equation of equilibrium concentration which shows that volatiles break off from polymer when they are relieved from high pressure condition. For surface refreshment devolatilization, we applied Latinen's model to allow estimation of polymer behavior in the unfilled screw conveying condition. Forced expansion devolatilization is based on the expansion theory in which foams are generated under reduced pressure and volatiles are diffused on the exposed surface layer after mixing with the injected devolatilization agent. Based on these models, we developed the simulation software of twin-screw extrusion by the FAN method and it allows us to quantitatively estimate volatile concentration and polymer temperature with a high accuracy in the actual multi-vent extrusion process for LDPE + n-hexane.

Relationship of glomerular filtration rate based on serum iodixanol clearance to IRIS staging in cats with chronic kidney disease.

PubMed

Iwama, Ryosuke; Sato, Tsubasa; Katayama, Masaaki; Shimamura, Shunsuke; Satoh, Hiroshi; Ichijo, Toshihiro; Furuhama, Kazuhisa

2015-08-01

We examined the correlation between the glomerular filtration rate (GFR) estimated from an equation based on the serum iodixanol clearance technique and International Renal Interest Society (IRIS) stages of chronic kidney disease (CKD) in cats. The equation included the injection dose, sampling time, serum concentration and estimated volume of distribution (Vd) of the isotonic, nonionic, contrast medium iodixanol as a test tracer. The percent changes in the median basal GFR values calculated from the equation in CKD cats resembled those of IRIS stages 1-3. These data validate the association between the GFR derived from the simplified equation and IRIS stages based on the serum creatinine concentration in cats with CKD. They describe the GFR ranges determined using single-sample iodixanol clearance for healthy cats and cats with various IRIS stages of CKD.

Phosphorus Concentrations, Loads, and Yields in the Illinois River Basin, Arkansas and Oklahoma, 1997-2001

USGS Publications Warehouse

Pickup, Barbara E.; Andrews, William J.; Haggard, Brian E.; Green, W. Reed

2003-01-01

The Illinois River and tributaries, Flint Creek and the Baron Fork, are designated scenic rivers in Oklahoma. Recent phosphorus increases in streams in the basin have resulted in the growth of excess algae, which have limited the aesthetic benefits of water bodies in the basin, especially the Illinois River and Lake Tenkiller. The Oklahoma Water Resources Board has established a standard for total phosphorus not to exceed the 30- day geometric mean concentration of 0.037 milligram per liter in Oklahoma Scenic Rivers. Data from water-quality samples from 1997 to 2001 were used to summarize phosphorus concentrations and estimate phosphorus loads, yields, and flowweighted concentrations in the Illinois River basin. Phosphorus concentrations in the Illinois River basin generally were significantly greater in runoff-event samples than in base-flow samples. Phosphorus concentrations generally decreased with increasing base flow, from dilution, and increased with runoff, possibly because of phosphorus resuspension, stream bank erosion, and the addition of phosphorus from nonpoint sources. Estimated mean annual phosphorus loads were greater at the Illinois River stations than at Flint Creek and the Baron Fork. Loads appeared to generally increase with time during 1997-2001 at all stations, but this increase might be partly attributable to the beginning of runoff-event sampling in the basin in July 1999. Base-flow loads at stations on the Illinois River were about 10 times greater than those on the Baron Fork and 5 times greater than those on Flint Creek. Runoff components of the annual total phosphorus load ranged from 58.7 to 96.8 percent from 1997-2001. Base-flow and runoff loads were generally greatest in spring (March through May) or summer (June through August), and were least in fall (September through November). Total yields of phosphorus ranged from 107 to 797 pounds per year per square mile. Greatest yields were at Flint Creek near Kansas (365 to 797 pounds per year per square mile) and the least yields were at Baron Fork at Eldon (107 to 440 pounds per year per square mile). Estimated mean flow-weighted concentrations were more than 10 times greater than the median and were consistently greater than the 75th percentile of flow-weighted phosphorus concentrations in samples collected at relatively undeveloped basins of the United States (0.022 milligram per liter and 0.037 milligram per liter, respectively). In addition, flow-weighted phosphorus concentrations in 1999-2001 at all Illinois River stations and at Flint Creek near Kansas were equal to or greater than the 75th percentile of all National Water-Quality Assessment program stations in the United States (0.29 milligram per liter). The annual average phosphorus load entering Lake Tenkiller was about 577,000 pounds per year, and more than 86 percent of the load was transported to the lake by runoff.The Illinois River and tributaries, Flint Creek and the Baron Fork, are designated scenic rivers in Oklahoma. Recent phosphorus increases in streams in the basin have resulted in the growth of excess algae, which have limited the aesthetic benefits of water bodies in the basin, especially the Illinois River and Lake Tenkiller. The Oklahoma Water Resources Board has established a standard for total phosphorus not to exceed the 30- day geometric mean concentration of 0.037 milligram per liter in Oklahoma Scenic Rivers. Data from water-quality samples from 1997 to 2001 were used to summarize phosphorus concentrations and estimate phosphorus loads, yields, and flowweighted concentrations in the Illinois River basin. Phosphorus concentrations in the Illinois River basin generally were significantly greater in runoff-event samples than in base-flow samples. Phosphorus concentrations generally decreased with increasing base flow, from dilution, and increased with runoff, possibly because of phosphorus resuspension, stream bank erosion, and the addition of phosphorus

A fluorometric paper-based sensor array for the discrimination of heavy-metal ions.

PubMed

Feng, Liang; Li, Hui; Niu, Li-Ya; Guan, Ying-Shi; Duan, Chun-Feng; Guan, Ya-Feng; Tung, Chen-Ho; Yang, Qing-Zheng

2013-04-15

A fluorometric paper-based sensor array has been developed for the sensitive and convenient determination of seven heavy-metal ions at their wastewater discharge standard concentrations. Combining with nine cross-reactive BODIPY fluorescent indicators and array technologies-based pattern-recognition, we have obtained the discrimination capability of seven different heavy-metal ions at their wastewater discharge standard concentrations. After the immobilization of indicators and the enrichment of analytes, identification of the heavy-metal ions was readily acquired using a standard chemometric approach. Clear differentiation among heavy-metal ions as a function of concentration was also achieved, even down to 10(-7)M. A semi-quantitative estimation of the heavy-metal ion concentration was obtained by comparing color changes with a set of known concentrations. The sensor array was tentatively investigated in spiked tap water and sea water, and showed possible feasibility for real sample testing. Copyright © 2013 Elsevier B.V. All rights reserved.

Bayesian source term estimation of atmospheric releases in urban areas using LES approach.

PubMed

Xue, Fei; Kikumoto, Hideki; Li, Xiaofeng; Ooka, Ryozo

2018-05-05

The estimation of source information from limited measurements of a sensor network is a challenging inverse problem, which can be viewed as an assimilation process of the observed concentration data and the predicted concentration data. When dealing with releases in built-up areas, the predicted data are generally obtained by the Reynolds-averaged Navier-Stokes (RANS) equations, which yields building-resolving results; however, RANS-based models are outperformed by large-eddy simulation (LES) in the predictions of both airflow and dispersion. Therefore, it is important to explore the possibility of improving the estimation of the source parameters by using the LES approach. In this paper, a novel source term estimation method is proposed based on LES approach using Bayesian inference. The source-receptor relationship is obtained by solving the adjoint equations constructed using the time-averaged flow field simulated by the LES approach based on the gradient diffusion hypothesis. A wind tunnel experiment with a constant point source downwind of a single building model is used to evaluate the performance of the proposed method, which is compared with that of the existing method using a RANS model. The results show that the proposed method reduces the errors of source location and releasing strength by 77% and 28%, respectively. Copyright © 2018 Elsevier B.V. All rights reserved.

A tiered approach for integrating exposure and dosimetry with ...

EPA Pesticide Factsheets

High-throughput (HT) risk screening approaches apply in vitro dose-response data to estimate potential health risks that arise from exposure to chemicals. However, much uncertainty is inherent in relating bioactivities observed in an in vitro system to the perturbations of biological mechanisms that lead to apical adverse health outcomes in living organisms. The chemical-agnostic Adverse Outcome Pathway (AOP) framework addresses this uncertainty by acting as a scaffold onto which pathway-based data can be arranged to aid in the understanding of in vitro toxicity testing results. In addition, risk estimation also requires reconciling chemical concentrations sufficient to produce bioactivity in vitro with concentrations that trigger a molecular initiating event (MIE) at the relevant biological target in vivo. Such target site exposures (TSEs) can be estimated using computational models to integrate exposure information with a chemical’s absorption, distribution, metabolism, and elimination (ADME) processes. In this presentation, the utility of a tiered approach for integrating exposure, ADME, and hazard into risk-based decision making will be demonstrated using several case studies, along with the investigation of how uncertainties in exposure and ADME might impact risk estimates. These case studies involve 1) identifying and prioritizing chemicals capable of altering biological pathways based on their potential to reach an in vivo target; 2) evaluating the infl

Estimation of Fine Particulate Matter in Taipei Using Landuse Regression and Bayesian Maximum Entropy Methods

PubMed Central

Yu, Hwa-Lung; Wang, Chih-Hsih; Liu, Ming-Che; Kuo, Yi-Ming

2011-01-01

Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS), the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME) method. The resulting epistemic framework can assimilate knowledge bases including: (a) empirical-based spatial trends of PM concentration based on landuse regression, (b) the spatio-temporal dependence among PM observation information, and (c) site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan) from 2005–2007. PMID:21776223

Estimation of fine particulate matter in Taipei using landuse regression and bayesian maximum entropy methods.

PubMed

Yu, Hwa-Lung; Wang, Chih-Hsih; Liu, Ming-Che; Kuo, Yi-Ming

2011-06-01

Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS), the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME) method. The resulting epistemic framework can assimilate knowledge bases including: (a) empirical-based spatial trends of PM concentration based on landuse regression, (b) the spatio-temporal dependence among PM observation information, and (c) site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan) from 2005-2007.

Global Mass Flux Solutions from GRACE: A Comparison of Parameter Estimation Strategies - Mass Concentrations Versus Stokes Coefficients

NASA Technical Reports Server (NTRS)

Rowlands, D. D.; Luthcke, S. B.; McCarthy J. J.; Klosko, S. M.; Chinn, D. S.; Lemoine, F. G.; Boy, J.-P.; Sabaka, T. J.

2010-01-01

The differences between mass concentration (mas con) parameters and standard Stokes coefficient parameters in the recovery of gravity infonnation from gravity recovery and climate experiment (GRACE) intersatellite K-band range rate data are investigated. First, mascons are decomposed into their Stokes coefficient representations to gauge the range of solutions available using each of the two types of parameters. Next, a direct comparison is made between two time series of unconstrained gravity solutions, one based on a set of global equal area mascon parameters (equivalent to 4deg x 4deg at the equator), and the other based on standard Stokes coefficients with each time series using the same fundamental processing of the GRACE tracking data. It is shown that in unconstrained solutions, the type of gravity parameter being estimated does not qualitatively affect the estimated gravity field. It is also shown that many of the differences in mass flux derivations from GRACE gravity solutions arise from the type of smoothing being used and that the type of smoothing that can be embedded in mas con solutions has distinct advantages over postsolution smoothing. Finally, a 1 year time series based on global 2deg equal area mascons estimated every 10 days is presented.

Model simulations of cooking organic aerosol (COA) over the UK using estimates of emissions based on measurements at two sites in London

NASA Astrophysics Data System (ADS)

Ots, Riinu; Vieno, Massimo; Allan, James D.; Reis, Stefan; Nemitz, Eiko; Young, Dominique E.; Coe, Hugh; Di Marco, Chiara; Detournay, Anais; Mackenzie, Ian A.; Green, David C.; Heal, Mathew R.

2016-11-01

Cooking organic aerosol (COA) is currently not included in European emission inventories. However, recent positive matrix factorization (PMF) analyses of aerosol mass spectrometer (AMS) measurements have suggested important contributions of COA in several European cities. In this study, emissions of COA were estimated for the UK, based on hourly AMS measurements of COA made at two sites in London (a kerbside site in central London and an urban background site in a residential area close to central London) for the full calendar year of 2012 during the Clean Air for London (ClearfLo) campaign. Iteration of COA emissions estimates and subsequent evaluation and sensitivity experiments were conducted with the EMEP4UK atmospheric chemistry transport modelling system with a horizontal resolution of 5 km × 5 km. The spatial distribution of these emissions was based on workday population density derived from the 2011 census data. The estimated UK annual COA emission was 7.4 Gg per year, which is an almost 10 % addition to the officially reported UK national total anthropogenic emissions of PM2.5 (82 Gg in 2012), corresponding to 320 mg person-1 day-1 on average. Weekday and weekend diurnal variation in COA emissions were also based on the AMS measurements. Modelled concentrations of COA were then independently evaluated against AMS-derived COA measurements from another city and time period (Manchester, January-February 2007), as well as with COA estimated by a chemical mass balance model of measurements for a 2-week period at the Harwell rural site (˜ 80 km west of central London). The modelled annual average contribution of COA to ambient particulate matter (PM) in central London was between 1 and 2 µg m-3 (˜ 20 % of total measured OA1) and between 0.5 and 0.7 µg m-3 in other major cities in England (Manchester, Birmingham, Leeds). It was also shown that cities smaller than London can have a central hotspot of population density of smaller area than the computational grid cell, in which case higher localized COA concentrations than modelled here may be expected. Modelled COA concentrations dropped rapidly outside of major urban areas (annual average of 0.12 µg m-3 for the Harwell location), indicating that although COA can be a notable component in urban air, it does not have a significant effect on PM concentrations on rural areas. The possibility that the AMS-PMF apportionment measurements overestimate COA concentrations by up to a factor of 2 is discussed. Since COA is a primary emission, any downward adjustments in COA emissions would lead to a proportional linear downward scaling in the absolute magnitudes of COA concentrations simulated in the model.

Illicit and pharmaceutical drug consumption estimated via wastewater analysis. Part B: placing back-calculations in a formal statistical framework.

PubMed

Jones, Hayley E; Hickman, Matthew; Kasprzyk-Hordern, Barbara; Welton, Nicky J; Baker, David R; Ades, A E

2014-07-15

Concentrations of metabolites of illicit drugs in sewage water can be measured with great accuracy and precision, thanks to the development of sensitive and robust analytical methods. Based on assumptions about factors including the excretion profile of the parent drug, routes of administration and the number of individuals using the wastewater system, the level of consumption of a drug can be estimated from such measured concentrations. When presenting results from these 'back-calculations', the multiple sources of uncertainty are often discussed, but are not usually explicitly taken into account in the estimation process. In this paper we demonstrate how these calculations can be placed in a more formal statistical framework by assuming a distribution for each parameter involved, based on a review of the evidence underpinning it. Using a Monte Carlo simulations approach, it is then straightforward to propagate uncertainty in each parameter through the back-calculations, producing a distribution for instead of a single estimate of daily or average consumption. This can be summarised for example by a median and credible interval. To demonstrate this approach, we estimate cocaine consumption in a large urban UK population, using measured concentrations of two of its metabolites, benzoylecgonine and norbenzoylecgonine. We also demonstrate a more sophisticated analysis, implemented within a Bayesian statistical framework using Markov chain Monte Carlo simulation. Our model allows the two metabolites to simultaneously inform estimates of daily cocaine consumption and explicitly allows for variability between days. After accounting for this variability, the resulting credible interval for average daily consumption is appropriately wider, representing additional uncertainty. We discuss possibilities for extensions to the model, and whether analysis of wastewater samples has potential to contribute to a prevalence model for illicit drug use. Copyright © 2014. Published by Elsevier B.V.

Illicit and pharmaceutical drug consumption estimated via wastewater analysis. Part B: Placing back-calculations in a formal statistical framework

PubMed Central

Jones, Hayley E.; Hickman, Matthew; Kasprzyk-Hordern, Barbara; Welton, Nicky J.; Baker, David R.; Ades, A.E.

2014-01-01

Concentrations of metabolites of illicit drugs in sewage water can be measured with great accuracy and precision, thanks to the development of sensitive and robust analytical methods. Based on assumptions about factors including the excretion profile of the parent drug, routes of administration and the number of individuals using the wastewater system, the level of consumption of a drug can be estimated from such measured concentrations. When presenting results from these ‘back-calculations’, the multiple sources of uncertainty are often discussed, but are not usually explicitly taken into account in the estimation process. In this paper we demonstrate how these calculations can be placed in a more formal statistical framework by assuming a distribution for each parameter involved, based on a review of the evidence underpinning it. Using a Monte Carlo simulations approach, it is then straightforward to propagate uncertainty in each parameter through the back-calculations, producing a distribution for instead of a single estimate of daily or average consumption. This can be summarised for example by a median and credible interval. To demonstrate this approach, we estimate cocaine consumption in a large urban UK population, using measured concentrations of two of its metabolites, benzoylecgonine and norbenzoylecgonine. We also demonstrate a more sophisticated analysis, implemented within a Bayesian statistical framework using Markov chain Monte Carlo simulation. Our model allows the two metabolites to simultaneously inform estimates of daily cocaine consumption and explicitly allows for variability between days. After accounting for this variability, the resulting credible interval for average daily consumption is appropriately wider, representing additional uncertainty. We discuss possibilities for extensions to the model, and whether analysis of wastewater samples has potential to contribute to a prevalence model for illicit drug use. PMID:24636801

A Study on Pharmacokinetics of Bosentan with Systems Modeling, Part 1: Translating Systemic Plasma Concentration to Liver Exposure in Healthy Subjects.

PubMed

Li, Rui; Niosi, Mark; Johnson, Nathaniel; Tess, David A; Kimoto, Emi; Lin, Jian; Yang, Xin; Riccardi, Keith A; Ryu, Sangwoo; El-Kattan, Ayman F; Maurer, Tristan S; Tremaine, Larry M; Di, Li

2018-04-01

Understanding liver exposure of hepatic transporter substrates in clinical studies is often critical, as it typically governs pharmacodynamics, drug-drug interactions, and toxicity for certain drugs. However, this is a challenging task since there is currently no easy method to directly measure drug concentration in the human liver. Using bosentan as an example, we demonstrate a new approach to estimate liver exposure based on observed systemic pharmacokinetics from clinical studies using physiologically based pharmacokinetic modeling. The prediction was verified to be both accurate and precise using sensitivity analysis. For bosentan, the predicted pseudo steady-state unbound liver-to-unbound systemic plasma concentration ratio was 34.9 (95% confidence interval: 4.2, 50). Drug-drug interaction (i.e., CYP3A and CYP2B6 induction) and inhibition of hepatic transporters (i.e., bile salt export pump, multidrug resistance-associated proteins, and sodium-taurocholate cotransporting polypeptide) were predicted based on the estimated unbound liver tissue or plasma concentrations. With further validation and refinement, we conclude that this approach may serve to predict human liver exposure and complement other methods involving tissue biopsy and imaging. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.

Aircraft- and ground-based assessment of the CCN-AOD relationship and implications on model analysis of ACI and underlying aerosol processes

NASA Astrophysics Data System (ADS)

Shinozuka, Y.; Clarke, A. D.; Nenes, A.; Lathem, T. L.; Redemann, J.; Jefferson, A.; Wood, R.

2014-12-01

Contrary to common assumptions in satellite-based modeling of aerosol-cloud interactions, ∂logCCN/∂logAOD is less than unity, i.e., the number concentration of cloud condensation nuclei (CCN) less than doubles as aerosol optical depth (AOD) doubles. This can be explained by omnipresent aerosol processes. Condensation, coagulation and cloud processing, for example, generally make particles scatter more light while hardly increasing their number. This paper reports on the relationship in local air masses between CCN concentration, aerosol size distribution and light extinction observed from aircraft and the ground at diverse locations. The CCN-to-local-extinction relationship, when averaged over ~1 km distance and sorted by the wavelength dependence of extinction, varies approximately by a factor of 2, reflecting the variability in aerosol intensive properties. This, together with retrieval uncertainties and the variability in aerosol spatio-temporal distribution and hygroscopic growth, challenges satellite-based CCN estimates. However, the large differences in estimated CCN may correspond to a considerably lower uncertainty in cloud drop number concentration (CDNC), given the sublinear response of CDNC to CCN. Overall, our findings from airborne and ground-based observations call for model-based reexamination of aerosol-cloud interactions and underlying aerosol processes.

Pseudo-Boltzmann model for modeling the junctionless transistors

NASA Astrophysics Data System (ADS)

Avila-Herrera, F.; Cerdeira, A.; Roldan, J. B.; Sánchez-Moreno, P.; Tienda-Luna, I. M.; Iñiguez, B.

2014-05-01

Calculation of the carrier concentrations in semiconductors using the Fermi-Dirac integral requires complex numerical calculations; in this context, practically all analytical device models are based on Boltzmann statistics, even though it is known that it leads to an over-estimation of carriers densities for high doping concentrations. In this paper, a new approximation to Fermi-Dirac integral, called Pseudo-Boltzmann model, is presented for modeling junctionless transistors with high doping concentrations.

A statistical approach to determining the uncertainty in power-law model estimates of emissions based on time-dependent chamber concentration measurements

EPA Science Inventory

The use of models for estimating emissions from products beyond the timeframe of an emissions test is a means of managing the time and expenses associated with product emissions certification. This paper presents a discussion of (1) the impact of uncertainty in test chamber emiss...

An empirical inferential method of estimating nitrogen deposition to Mediterranean-type ecosystems: the San Bernardino Mountains case study

Treesearch

A. Bytnerowicz; R.F. Johnson; L. Zhang; G.D. Jenerette; M.E. Fenn; S.L. Schilling; I. Gonzalez-Fernandez

2015-01-01

The empirical inferential method (EIM) allows for spatially and temporally-dense estimates of atmospheric nitrogen (N) deposition to Mediterranean ecosystems. This method, set within a GIS platform, is based on ambient concentrations of NH3, NO, NO2 and HNO3; surface conductance of NH4...

A potential dating technique using 228Th/228Ra ratio for tracing the chronosequence of elemental concentrations in plants.

PubMed

Chao, J H; Niu, H; Chiu, C Y; Lin, C

2007-06-01

We propose a radiometric method based on measurement of the radioactivity of the naturally occurring radionuclides (228)Ra and 228)Th and the derived (228)Th/(228)Ra ratios in plant samples to estimate plant age and the corresponding nutritional conditions in a field-growing fern, Dicranopteris linearis. Plant age (tissue age) was associated with the (228)Th/(228)Ra ratio in fronds, which implies the accumulation time of immobile elements in the plant tissue or the life span of the fronds. Results indicated that the accumulation of alkaline earth elements in D. linearis is relatively constant with increased age, while the K concentration is reversed with age because of translocation among plant tissues. Estimation of dating uncertainty based on measurement conditions revealed that the radiometric technique can be applied to trace chronosequential changes of elemental concentrations and environmental pollutants in plants with ages of less than 10-15 years.

Metallurgical Laboratory (MetLab) Treatability Study: An Analysis of Passive Soil Vapor Extraction Wells (PSVE) FY1999 Update

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riha, B.D.

1999-10-20

The results to date on the treatability study of the PSVE system at the MetLab of the Savannah River Site (SRS) indicate the technology is performing well. Well concentrations are decreasing and contour maps of the vadose zone soil gas plume show a decrease in the extent of the plume. In the 18 months of operation approximately 200 pounds of chlorinated organic contaminants have been removed by natural barometric pumping of wells fitted with BaroBall valves (low pressure check valves). The mass removal estimates are approximate since the flow rates are estimated, the concentration data is based on exponential fitsmore » of a limited data set, and the concentration data is normalized to the average CO2.The concentration values presented in this report should be taken as the general trend or order of magnitude of concentration until longer-term data is collected. These trends are of exponentially decreasing concentration showing the same characteristics as the concentration trends at the SRS Miscellaneous Chemical Basin after three years of PSVE (Riha et. al., 1999).« less

Concentration dependence of biotransformation in fish liver S9: Optimizing substrate concentrations to estimate hepatic clearance for bioaccumulation assessment.

PubMed

Lo, Justin C; Allard, Gayatri N; Otton, S Victoria; Campbell, David A; Gobas, Frank A P C

2015-12-01

In vitro bioassays to estimate biotransformation rate constants of contaminants in fish are currently being investigated to improve bioaccumulation assessments of hydrophobic contaminants. The present study investigates the relationship between chemical substrate concentration and in vitro biotransformation rate of 4 environmental contaminants (9-methylanthracene, pyrene, chrysene, and benzo[a]pyrene) in rainbow trout (Oncorhynchus mykiss) liver S9 fractions and methods to determine maximum first-order biotransformation rate constants. Substrate depletion experiments using a series of initial substrate concentrations showed that in vitro biotransformation rates exhibit strong concentration dependence, consistent with a Michaelis-Menten kinetic model. The results indicate that depletion rate constants measured at initial substrate concentrations of 1 μM (a current convention) could underestimate the in vitro biotransformation potential and may cause bioconcentration factors to be overestimated if in vitro biotransformation rates are used to assess bioconcentration factors in fish. Depletion rate constants measured using thin-film sorbent dosing experiments were not statistically different from the maximum depletion rate constants derived using a series of solvent delivery-based depletion experiments for 3 of the 4 test chemicals. Multiple solvent delivery-based depletion experiments at a range of initial concentrations are recommended for determining the concentration dependence of in vitro biotransformation rates in fish liver fractions, whereas a single sorbent phase dosing experiment may be able to provide reasonable approximations of maximum depletion rates of very hydrophobic substances. © 2015 SETAC.

A first European scale multimedia fate modelling of BDE-209 from 1970 to 2020.

PubMed

Earnshaw, Mark R; Jones, Kevin C; Sweetman, Andy J

2015-01-01

The European Variant Berkeley Trent (EVn-BETR) multimedia fugacity model is used to test the validity of previously derived emission estimates and predict environmental concentrations of the main decabromodiphenyl ether congener, BDE-209. The results are presented here and compared with measured environmental data from the literature. Future multimedia concentration trends are predicted using three emission scenarios (Low, Realistic and High) in the dynamic unsteady state mode covering the period 1970-2020. The spatial and temporal distributions of emissions are evaluated. It is predicted that BDE-209 atmospheric concentrations peaked in 2004 and will decline to negligible levels by 2025. Freshwater concentrations should have peaked in 2011, one year after the emissions peak with sediment concentrations peaking in 2013. Predicted atmospheric concentrations are in good agreement with measured data for the Realistic (best estimate of emissions) and High (worst case scenario) emission scenarios. The Low emission scenario consistently underestimates measured data. The German unilateral ban on the use of DecaBDE in the textile industry is simulated in an additional scenario, the effects of which are mainly observed within Germany with only a small effect on the surrounding areas. Overall, the EVn-BTER model predicts atmospheric concentrations reasonably well, within a factor of 5 and 1.2 for the Realistic and High emission scenarios respectively, providing partial validation for the original emission estimate. Total mean MEC:PEC shows the High emission scenario predicts the best fit between air, freshwater and sediment data. An alternative spatial distribution of emissions is tested, based on higher consumption in EBFRIP member states, resulting in improved agreement between MECs and PECs in comparison with the Uniform spatial distribution based on population density. Despite good agreement between modelled and measured point data, more long-term monitoring datasets are needed to compare predicted trends in concentration to determine the rate of change of POPs within the environment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Estimating hourly PM1 concentrations from Himawari-8 aerosol optical depth in China.

PubMed

Zang, Lin; Mao, Feiyue; Guo, Jianping; Gong, Wei; Wang, Wei; Pan, Zengxin

2018-06-11

Particulate matter with diameter less than 1 μm (PM 1 ) has been found to be closely associated with air quality, climate changes, and even adverse human health. However, a large gap in our knowledge concerning the large-scale distribution and variability of PM 1 remains, which is expected to be bridged with advanced remote-sensing techniques. In this study, a hybrid model called principal component analysis-general regression neural network (PCA-GRNN) is developed to estimate hourly PM 1 concentrations from Himawari-8 aerosol optical depth in combination with coincident ground-based PM 1 measurements in China. Results indicate that the hourly estimated PM 1 concentrations from satellite agree well with the measured values at national scale, with R 2 of 0.65, root-mean-square error (RMSE) of 22.0 μg/m 3 and mean absolute error (MAE) of 13.8 μg/m 3 . On daily and monthly time scales, R 2 increases to 0.70 and 0.81, respectively. Spatially, highly polluted regions of PM 1 are largely located in the North China Plain and Northeast China, in accordance with the distribution of industrialisation and urbanisation. In terms of diurnal variability, PM 1 concentration tends to peak in rush hours during the daytime. PM 1 exhibits distinct seasonality with winter having the largest concentration (31.5±3.5 μg/m 3 ), largely due to peak combustion emissions. We further attempt to estimate PM 2.5 and PM 10 with the proposed method and find that the accuracies of the proposed model for PM 1 and PM 2.5 estimation are significantly higher than that of PM 10 . Our findings suggest that geostationary data is one of the promising data to estimate fine particle concentration on large spatial scale. Copyright © 2018 Elsevier Ltd. All rights reserved.

Water quality of storm runoff and comparison of procedures for estimating storm-runoff loads, volume, event-mean concentrations, and the mean load for a storm for selected properties and constituents for Colorado Springs, southeastern Colorado, 1992

USGS Publications Warehouse

Von Guerard, Paul; Weiss, W.B.

1995-01-01

The U.S. Environmental Protection Agency requires that municipalities that have a population of 100,000 or greater obtain National Pollutant Discharge Elimination System permits to characterize the quality of their storm runoff. In 1992, the U.S. Geological Survey, in cooperation with the Colorado Springs City Engineering Division, began a study to characterize the water quality of storm runoff and to evaluate procedures for the estimation of storm-runoff loads, volume and event-mean concentrations for selected properties and constituents. Precipitation, streamflow, and water-quality data were collected during 1992 at five sites in Colorado Springs. Thirty-five samples were collected, seven at each of the five sites. At each site, three samples were collected for permitting purposes; two of the samples were collected during rainfall runoff, and one sample was collected during snowmelt runoff. Four additional samples were collected at each site to obtain a large enough sample size to estimate storm-runoff loads, volume, and event-mean concentrations for selected properties and constituents using linear-regression procedures developed using data from the Nationwide Urban Runoff Program (NURP). Storm-water samples were analyzed for as many as 186 properties and constituents. The constituents measured include total-recoverable metals, vola-tile-organic compounds, acid-base/neutral organic compounds, and pesticides. Storm runoff sampled had large concentrations of chemical oxygen demand and 5-day biochemical oxygen demand. Chemical oxygen demand ranged from 100 to 830 milligrams per liter, and 5.-day biochemical oxygen demand ranged from 14 to 260 milligrams per liter. Total-organic carbon concentrations ranged from 18 to 240 milligrams per liter. The total-recoverable metals lead and zinc had the largest concentrations of the total-recoverable metals analyzed. Concentrations of lead ranged from 23 to 350 micrograms per liter, and concentrations of zinc ranged from 110 to 1,400 micrograms per liter. The data for 30 storms representing rainfall runoff from 5 drainage basins were used to develop single-storm local-regression models. The response variables, storm-runoff loads, volume, and event-mean concentrations were modeled using explanatory variables for climatic, physical, and land-use characteristics. The r2 for models that use ordinary least-squares regression ranged from 0.57 to 0.86 for storm-runoff loads and volume and from 0.25 to 0.63 for storm-runoff event-mean concentrations. Except for cadmium, standard errors of estimate ranged from 43 to 115 percent for storm- runoff loads and volume and from 35 to 66 percent for storm-runoff event-mean concentrations. Eleven of the 30 concentrations collected during rainfall runoff for total-recoverable cadmium were censored (less than) concentrations. Ordinary least-squares regression should not be used with censored data; however, censored data can be included with uncensored data using tobit regression. Standard errors of estimate for storm-runoff load and event-mean concentration for total-recoverable cadmium, computed using tobit regression, are 247 and 171 percent. Estimates from single-storm regional-regression models, developed from the Nationwide Urban Runoff Program data base, were compared with observed storm-runoff loads, volume, and event-mean concentrations determined from samples collected in the study area. Single-storm regional-regression models tended to overestimate storm-runoff loads, volume, and event-mean con-centrations. Therefore, single-storm local- and regional-regression models were combined using model-adjustment procedures to take advantage of the strengths of both models while minimizing the deficiencies of each model. Procedures were used to develop single-stormregression equations that were adjusted using local data and estimates from single-storm regional-regression equations. Single-storm regression models developed using model- adjustment proce

Load estimator (LOADEST): a FORTRAN program for estimating constituent loads in streams and rivers

USGS Publications Warehouse

Runkel, Robert L.; Crawford, Charles G.; Cohn, Timothy A.

2004-01-01

LOAD ESTimator (LOADEST) is a FORTRAN program for estimating constituent loads in streams and rivers. Given a time series of streamflow, additional data variables, and constituent concentration, LOADEST assists the user in developing a regression model for the estimation of constituent load (calibration). Explanatory variables within the regression model include various functions of streamflow, decimal time, and additional user-specified data variables. The formulated regression model then is used to estimate loads over a user-specified time interval (estimation). Mean load estimates, standard errors, and 95 percent confidence intervals are developed on a monthly and(or) seasonal basis. The calibration and estimation procedures within LOADEST are based on three statistical estimation methods. The first two methods, Adjusted Maximum Likelihood Estimation (AMLE) and Maximum Likelihood Estimation (MLE), are appropriate when the calibration model errors (residuals) are normally distributed. Of the two, AMLE is the method of choice when the calibration data set (time series of streamflow, additional data variables, and concentration) contains censored data. The third method, Least Absolute Deviation (LAD), is an alternative to maximum likelihood estimation when the residuals are not normally distributed. LOADEST output includes diagnostic tests and warnings to assist the user in determining the appropriate estimation method and in interpreting the estimated loads. This report describes the development and application of LOADEST. Sections of the report describe estimation theory, input/output specifications, sample applications, and installation instructions.

Airborne particle-bound brominated flame retardants: Levels, size distribution and indoor-outdoor exchange.

PubMed

Zhu, Yue-Shan; Yang, Wan-Dong; Li, Xiu-Wen; Ni, Hong-Gang; Zeng, Hui

2018-02-01

The quality of indoor environments has a significant impact on public health. Usually, an indoor environment is treated as a static box, in which physicochemical reactions of indoor air contaminants are negligible. This results in conservative estimates for primary indoor air pollutant concentrations, while also ignoring secondary pollutants. Thus, understanding the relationship between indoor and outdoor particles and particle-bound pollutants is of great significance. For this reason, we collected simultaneous indoor and outdoor measurements of the size distribution of airborne brominated flame retardant (BFR) congeners. The time-dependent concentrations of indoor particles and particle-bound BFRs were then estimated with the mass balance model, accounting for the outdoor concentration, indoor source strength, infiltration, penetration, deposition and indoor resuspension. Based on qualitative observation, the size distributions of ΣPBDE and ΣHBCD were characterized by bimodal peaks. According to our results, particle-bound BDE209 and γ-HBCD underwent degradation. Regardless of the surface adsorption capability of particles and the physicochemical properties of the target compounds, the concentration of BFRs in particles of different size fractions seemed to be governed by the particle distribution. Based on our estimations, for airborne particles and particle-bound BFRs, a window-open ventilated room only takes a quarter of the time to reach an equilibrium between the concentration of pollutants inside and outside compared to a closed room. Unfortunately, indoor pollutants and outdoor pollutants always exist simultaneously, which poses a window-open-or-closed dilemma to achieve proper ventilation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Methods for estimating monthly mean concentrations of selected water-quality constituents for stream sites in the Red River of the North basin, North Dakota and Minnesota

USGS Publications Warehouse

Guenthner, R.S.

1991-01-01

Future development of the Garrison Diversion Unit may divert water from the Missouri River into the Sheyenne River and the Red River of the North for municipal and industrial use. The U.S. Bureau of Reclamation's Canals, Rivers, and Reservoirs Salinity Accounting Procedures model can be used to predict the effect various operating plans could have on water quality in the Sheyenne River and the Red River of the North. The model uses, as Input, monthly means of streamflow and selected water-quality constituents for a 54-year period at 28 nodes on the Sheyenne River and the Red River of the North. This report provides methods for estimating monthly mean concentrations of selected water-quality constituents that can be used for input to and calibration of the salinity model.Mater-quality data for 32 gaging stations can be used to define selected water-quality characteristics at the 28 model nodes. Materquality data were retrieved from the U.S. Geological Survey's National Mater Data Storage and Retrieval System data base and statistical summaries were prepared. The frequency of water-quality data collection at the gaging stations is inadequate to define monthly mean concentrations of the individual water-quality constituents for all months for the 54-year period; therefore, methods for estimating monthly mean concentrations were developed. Relations between selected water-quality constituents [dissolved solids, hardness (as CaCO3), sodium, sulfate, and chloride] and streamflow were developed as the primary method to estimate monthly mean concentrations. Relations between specific conductance and streamflow and relations between selected water-quality constituents [dissolved solids, hardness (as CaCO3), sodium, sulfate, and chloride] and specific conductance were developed so that a cascaded-regression relation could be developed as a second method of estimating monthly mean concentrations and, thus, utilize a large specific-conductance data base. Information about the quantity and the quality of ground water discharging to the Sheyenne River is needed for model input for reaches of the river where ground water accounts for a substantial part of streamflow during periods of low flow. Ground-water discharge was identified for two reaches of the Sheyenne River. Ground-water discharge to the Sheyenne River in the vicinity of Warwick, N.Dak., was about 14.8 cubic feet per second and the estimated dissolved-solids concentration was about 441 milligrams per liter during October 15 and 16, 1986. Ground-water discharge to the Sheyenne River in a reach between Lisbon and Kindred, N.Dak., ranged from an average of 25.3 cubic feet per second during September 13 to November 19, 1963, to about 45.0 cubic feet per second during October 21 and 22, 1986. Dissolved-solids concentration was estimated at about 442 milligrams per liter during October 21 and 22, 1986.

Propagating Water Quality Analysis Uncertainty Into Resource Management Decisions Through Probabilistic Modeling

NASA Astrophysics Data System (ADS)

Gronewold, A. D.; Wolpert, R. L.; Reckhow, K. H.

2007-12-01

Most probable number (MPN) and colony-forming-unit (CFU) are two estimates of fecal coliform bacteria concentration commonly used as measures of water quality in United States shellfish harvesting waters. The MPN is the maximum likelihood estimate (or MLE) of the true fecal coliform concentration based on counts of non-sterile tubes in serial dilution of a sample aliquot, indicating bacterial metabolic activity. The CFU is the MLE of the true fecal coliform concentration based on the number of bacteria colonies emerging on a growth plate after inoculation from a sample aliquot. Each estimating procedure has intrinsic variability and is subject to additional uncertainty arising from minor variations in experimental protocol. Several versions of each procedure (using different sized aliquots or different numbers of tubes, for example) are in common use, each with its own levels of probabilistic and experimental error and uncertainty. It has been observed empirically that the MPN procedure is more variable than the CFU procedure, and that MPN estimates are somewhat higher on average than CFU estimates, on split samples from the same water bodies. We construct a probabilistic model that provides a clear theoretical explanation for the observed variability in, and discrepancy between, MPN and CFU measurements. We then explore how this variability and uncertainty might propagate into shellfish harvesting area management decisions through a two-phased modeling strategy. First, we apply our probabilistic model in a simulation-based analysis of future water quality standard violation frequencies under alternative land use scenarios, such as those evaluated under guidelines of the total maximum daily load (TMDL) program. Second, we apply our model to water quality data from shellfish harvesting areas which at present are closed (either conditionally or permanently) to shellfishing, to determine if alternative laboratory analysis procedures might have led to different management decisions. Our research results indicate that the (often large) observed differences between MPN and CFU values for the same water body are well within the ranges predicted by our probabilistic model. Our research also indicates that the probability of violating current water quality guidelines at specified true fecal coliform concentrations depends on the laboratory procedure used. As a result, quality-based management decisions, such as opening or closing a shellfishing area, may also depend on the laboratory procedure used.

Temporal variation of VOC emission from solvent and water based wood stains

NASA Astrophysics Data System (ADS)

de Gennaro, Gianluigi; Loiotile, Annamaria Demarinis; Fracchiolla, Roberta; Palmisani, Jolanda; Saracino, Maria Rosaria; Tutino, Maria

2015-08-01

Solvent- and water-based wood stains were monitored using a small test emission chamber in order to characterize their emission profiles in terms of Total and individual VOCs. The study of concentration-time profiles of individual VOCs enabled to identify the compounds emitted at higher concentration for each type of stain, to examine their decay curve and finally to estimate the concentration in a reference room. The solvent-based wood stain was characterized by the highest Total VOCs emission level (5.7 mg/m3) that decreased over time more slowly than those related to water-based ones. The same finding was observed for the main detected compounds: Benzene, Toluene, Ethylbenzene, Xylenes, Styrene, alpha-Pinene and Camphene. On the other hand, the highest level of Limonene was emitted by a water-based wood stain. However, the concentration-time profile showed that water-based product was characterized by a remarkable reduction of the time of maximum and minimum emission: Limonene concentration reached the minimum concentration in about half the time compared to the solvent-based product. According to AgBB evaluation scheme, only one of the investigated water-based wood stains can be classified as a low-emitting product whose use may not determine any potential adverse effect on human health.

Parameter estimation and characterization of a single-chamber microbial fuel cell for dairy wastewater treatment.

PubMed

Sedaqatvand, Ramin; Nasr Esfahany, Mohsen; Behzad, Tayebeh; Mohseni, Madjid; Mardanpour, Mohammad Mahdi

2013-10-01

In this study, for the first time, the conduction-based model is extended, and then combined with Genetic Algorithm to estimate the design parameters of a MFC treating dairy wastewater. The optimized parameters are, then, validated. The estimated half-saturation potential of -0.13 V (vs. SHE) is in good agreement while the biofilm conductivity of 8.76×10(-4) mS cm(-1) is three orders of magnitude lower than that previously-reported for pure-culture biofilm. Simulations show that the ohmic and concentration overpotentials contribute almost equally in dropping cell voltage in which the concentration film and biofilm conductivity comprise the main resistances, respectively. Thus, polarization analysis and determining the controlling steps will be possible through that developed extension. This study introduces a reliable method to estimate the design parameters of a particular MFC and to characterize it. Copyright © 2013 Elsevier Ltd. All rights reserved.

Development of advanced methods for analysis of experimental data in diffusion

NASA Astrophysics Data System (ADS)

Jaques, Alonso V.

There are numerous experimental configurations and data analysis techniques for the characterization of diffusion phenomena. However, the mathematical methods for estimating diffusivities traditionally do not take into account the effects of experimental errors in the data, and often require smooth, noiseless data sets to perform the necessary analysis steps. The current methods used for data smoothing require strong assumptions which can introduce numerical "artifacts" into the data, affecting confidence in the estimated parameters. The Boltzmann-Matano method is used extensively in the determination of concentration - dependent diffusivities, D(C), in alloys. In the course of analyzing experimental data, numerical integrations and differentiations of the concentration profile are performed. These methods require smoothing of the data prior to analysis. We present here an approach to the Boltzmann-Matano method that is based on a regularization method to estimate a differentiation operation on the data, i.e., estimate the concentration gradient term, which is important in the analysis process for determining the diffusivity. This approach, therefore, has the potential to be less subjective, and in numerical simulations shows an increased accuracy in the estimated diffusion coefficients. We present a regression approach to estimate linear multicomponent diffusion coefficients that eliminates the need pre-treat or pre-condition the concentration profile. This approach fits the data to a functional form of the mathematical expression for the concentration profile, and allows us to determine the diffusivity matrix directly from the fitted parameters. Reformulation of the equation for the analytical solution is done in order to reduce the size of the problem and accelerate the convergence. The objective function for the regression can incorporate point estimations for error in the concentration, improving the statistical confidence in the estimated diffusivity matrix. Case studies are presented to demonstrate the reliability and the stability of the method. To the best of our knowledge there is no published analysis of the effects of experimental errors on the reliability of the estimates for the diffusivities. For the case of linear multicomponent diffusion, we analyze the effects of the instrument analytical spot size, positioning uncertainty, and concentration uncertainty on the resulting values of the diffusivities. These effects are studied using Monte Carlo method on simulated experimental data. Several useful scaling relationships were identified which allow more rigorous and quantitative estimates of the errors in the measured data, and are valuable for experimental design. To further analyze anomalous diffusion processes, where traditional diffusional transport equations do not hold, we explore the use of fractional calculus in analytically representing these processes is proposed. We use the fractional calculus approach for anomalous diffusion processes occurring through a finite plane sheet with one face held at a fixed concentration, the other held at zero, and the initial concentration within the sheet equal to zero. This problem is related to cases in nature where diffusion is enhanced relative to the classical process, and the order of differentiation is not necessarily a second--order differential equation. That is, differentiation is of fractional order alpha, where 1 ≤ alpha < 2. For alpha = 2, the presented solutions reduce to the classical second-order diffusion solution for the conditions studied. The solution obtained allows the analysis of permeation experiments. Frequently, hydrogen diffusion is analyzed using electrochemical permeation methods using the traditional, Fickian-based theory. Experimental evidence shows the latter analytical approach is not always appropiate, because reported data shows qualitative (and quantitative) deviation from its theoretical scaling predictions. Preliminary analysis of data shows better agreement with fractional diffusion analysis when compared to traditional square-root scaling. Although there is a large amount of work in the estimation of the diffusivity from experimental data, reported studies typically present only the analytical description for the diffusivity, without scattering. However, because these studies do not consider effects produced by instrument analysis, their direct applicability is limited. We propose alternatives to address these, and to evaluate their influence on the final resulting diffusivity values.

Comparing emission rates derived from a model with a plume-based approach and quantifying the contribution of vehicle classes to on-road emissions and air quality.

PubMed

Xu, Junshi; Wang, Jonathan; Hilker, Nathan; Fallah-Shorshani, Masoud; Saleh, Marc; Tu, Ran; Wang, An; Minet, Laura; Stogios, Christos; Evans, Greg; Hatzopoulou, Marianne

2018-06-05

This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to carbon monoxide (CO), nitrogen oxides (NO x ), and elemental carbon (EC) along an urban corridor. To this end, a field campaign was conducted over one week in June 2016 on an arterial road in Toronto, Canada. Traffic data were collected using a traffic camera and a radar, while air quality was characterized using two monitoring stations: one located at ground-level and another at the rooftop of a four-storey building. A traffic simulation model was calibrated and validated and sec-by-sec speed profiles for all vehicle trajectories were extracted to model emissions. In addition, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. Our results indicate that modelled EFs for CO and NO x are twice as high as plume-based EFs. Besides, modelled results indicate that transit bus emissions accounted for 60% and 70% of the total emissions of NO x and EC. Transit bus emission rates in g/passenger.km for NO x and EC were up to 8 and 22 times the emission rates of passenger cars. In contrast, the Toronto streetcars, which are electrically fuelled, were found to improve near-road air quality despite their negative impact on traffic speeds. Finally, we observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background given that the study network is located in a busy downtown area. Implications This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to various pollutants. Besides, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. We observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background as the study network is located in a busy downtown area.

Traveltime and longitudinal dispersion in Illinois streams

USGS Publications Warehouse

Graf, Julia B.

1986-01-01

Twenty-seven measurements of traveltime and longitudinal dispersion in 10 Illinois streams made from 1975 to 1982 provide data needed for estimating traveltime of peak concentration of a conservative solute, traveltime of the leading edge of a solute cloud, peak concentration resulting from injection of a given quantity of solute, and passage time of solute past a given point on a stream. These four variables can be estimated graphically for each stream from distance of travel and either discharge at the downstream end of the reach or flow-duration frequency. From equations developed from field measurements, the traveltime and dispersion characteristics also can be estimated for other unregulated streams in Illinois that have drainage areas less than about 1,500 square miles. For unmeasured streams, traveltime of peak concentration and of the leading edge of the cloud are related to discharge at the downstream end of the reach and to distance of travel. For both measured and unmeasured streams, peak concentration and passage time are best estimated from the relation of each to traveltime. In measured streams, dispersion efficiency is greater than that predicted by Fickian diffusion theory. The rate of decrease in peak concentration with traveltime is about equal to the rate of increase in passage time. Average velocity in a stream reach, given by the velocity of the center of solute mass in that reach, can be estimated from an equation developed from measured values. The equation relates average reach velocity to discharge at the downstream end of the reach. Average reach velocities computed for 9 of the 10 streams from available equations that are based on hydraulic-geometry relations are high relative to measured values. The estimating equation developed from measured velocities provides estimates of average reach velocity that are closer to measured velocities than are those computed using equations developed from hydraulic-geometry relations.

Validation of farm-scale methane emissions using nocturnal boundary layer budgets

NASA Astrophysics Data System (ADS)

Stieger, J.; Bamberger, I.; Buchmann, N.; Eugster, W.

2015-08-01

This study provides the first experimental validation of Swiss agricultural methane emission estimates at the farm scale. We measured CH4 concentrations at a Swiss farmstead during two intensive field campaigns in August 2011 and July 2012 to (1) quantify the source strength of livestock methane emissions using a tethered balloon system, and (2) to validate inventory emission estimates via nocturnal boundary layer (NBL) budgets. Field measurements were performed at a distance of 150 m from the nearest farm buildings with a tethered balloon system in combination with gradient measurements at eight heights on a 10 m tower to better resolve the near-surface concentrations. Vertical profiles of air temperature, relative humidity, CH4 concentration, wind speed and wind direction showed that the NBL was strongly influenced by local transport processes and by the valley wind system. Methane concentrations showed a pronounced time course, with highest concentrations in the second half of the night. NBL budget flux estimates were obtained via a time-space kriging approach. Main uncertainties of NBL budget flux estimates were associated with instationary atmospheric conditions and the estimate of the inversion height zi (top of volume integration). The mean NBL budget fluxes of 1.60 ± 0.31 μg CH4 m-2 s-1 (1.40 ± 0.50 and 1.66 ± 0.20 μg CH4 m-2 s-1 in 2011 and 2012, respectively) were in good agreement with local inventory estimates based on current livestock number and default emission factors, with 1.29 ± 0.47 and 1.74 ± 0.63 μg CH4 m-2 s-1 for 2011 and 2012, respectively. This indicates that emission factors used for the national inventory reports are adequate, and we conclude that the NBL budget approach is a useful tool to validate emission inventory estimates.

Validation of farm-scale methane emissions using nocturnal boundary layer budgets

NASA Astrophysics Data System (ADS)

Stieger, J.; Bamberger, I.; Buchmann, N.; Eugster, W.

2015-12-01

This study provides the first experimental validation of Swiss agricultural methane emission estimates at the farm scale. We measured CH4 concentrations at a Swiss farmstead during two intensive field campaigns in August 2011 and July 2012 to (1) quantify the source strength of livestock methane emissions using a tethered balloon system and (2) to validate inventory emission estimates via nocturnal boundary layer (NBL) budgets. Field measurements were performed at a distance of 150 m from the nearest farm buildings with a tethered balloon system in combination with gradient measurements at eight heights on a 10 m tower to better resolve the near-surface concentrations. Vertical profiles of air temperature, relative humidity, CH4 concentration, wind speed, and wind direction showed that the NBL was strongly influenced by local transport processes and by the valley wind system. Methane concentrations showed a pronounced time course, with highest concentrations in the second half of the night. NBL budget flux estimates were obtained via a time-space kriging approach. Main uncertainties of NBL budget flux estimates were associated with nonstationary atmospheric conditions and the estimate of the inversion height zi (top of volume integration). The mean NBL budget fluxes of 1.60 ± 0.31 μg CH4 m-2 s-1 (1.40 ± 0.50 and 1.66 ± 0.20 μg CH4 m-2 s-1 in 2011 and 2012 respectively) were in good agreement with local inventory estimates based on current livestock number and default emission factors, with 1.29 ± 0.47 and 1.74 ± 0.63 μg CH4 m-2 s-1 for 2011 and 2012 respectively. This indicates that emission factors used for the national inventory reports are adequate, and we conclude that the NBL budget approach is a useful tool to validate emission inventory estimates.

Models and signal processing for an implanted ethanol bio-sensor.

PubMed

Han, Jae-Joon; Doerschuk, Peter C; Gelfand, Saul B; O'Connor, Sean J

2008-02-01

The understanding of drinking patterns leading to alcoholism has been hindered by an inability to unobtrusively measure ethanol consumption over periods of weeks to months in the community environment. An implantable ethanol sensor is under development using microelectromechanical systems technology. For safety and user acceptability issues, the sensor will be implanted subcutaneously and, therefore, measure peripheral-tissue ethanol concentration. Determining ethanol consumption and kinetics in other compartments from the time course of peripheral-tissue ethanol concentration requires sophisticated signal processing based on detailed descriptions of the relevant physiology. A statistical signal processing system based on detailed models of the physiology and using extended Kalman filtering and dynamic programming tools is described which can estimate the time series of ethanol concentration in blood, liver, and peripheral tissue and the time series of ethanol consumption based on peripheral-tissue ethanol concentration measurements.

Comparison of LCModel and SAGE in Analysis of Brain Metabolite Concentrations-A study of Patients with Mild Cognitive Impairment.

PubMed

Shih, Chiu-Ming; Lai, Jui-Jen; Chang, Chin-Ching; Chen, Cheng-Sheng; Yeh, Yi-Chun; Jaw, Twei-Shiun; Hsu, Jui-Sheng; Li, Chun-Wei

2017-03-15

The purpose of this study was to compare brain metabolite concentration ratios determined by LCModel and Spectroscopy Analysis by General Electric (SAGE) quantitative methods to elucidate the advantages and disadvantages of each method. A total of 10 healthy volunteers and 10 patients with mild cognitive impairment (MCI) were recruited in this study. A point-resolved spectroscopy (PRESS) sequence was used to obtain the brain magnetic resonance spectroscopy (MRS) spectra of the volunteers and patients, as well as the General Electric (GE) MRS-HD-sphere phantom. The brain metabolite concentration ratios were estimated based on the peak area obtained from both LCModel and SAGE software. Three brain regions were sampled for each volunteer or patient, and 20 replicates were acquired at different times for the phantom analysis. The metabolite ratios of the GE phantom were estimated to be myo-inositol (mI)/creatine (Cr): 0.70 ± 0.01, choline (Cho)/Cr: 0.37 ± 0.00, N-acetylaspartate (NAA)/Cr: 1.26 ± 0.02, and NAA/mI: 1.81 ± 0.04 by LCModel, and mI/Cr: 0.88 ± 0.15, Cho/Cr: 0.35 ± 0.01, NAA/Cr: 1.33 ± 0.03, and NAA/mI: 1.55 ± 0.26 by SAGE. In the healthy volunteers and MCI patients, the ratios of mI/Cr and Cho/Cr estimated by LCModel were higher than those estimated by SAGE. In contrast, the ratio of NAA/Cr estimated by LCModel was lower than that estimated by SAGE. Both methods were acceptable in estimating brain metabolite concentration ratios. However, LCModel was marginally more accurate than SAGE because of its full automation, basis set, and user independency.

A probabilistic model of gastroenteritis risks associated with consumption of street food salads in Kumasi, Ghana: evaluation of methods to estimate pathogen dose from water, produce or food quality.

PubMed

Barker, S Fiona; Amoah, Philip; Drechsel, Pay

2014-07-15

With a rapidly growing urban population in Kumasi, Ghana, the consumption of street food is increasing. Raw salads, which often accompany street food dishes, are typically composed of perishable vegetables that are grown in close proximity to the city using poor quality water for irrigation. This study assessed the risk of gastroenteritis illness (caused by rotavirus, norovirus and Ascaris lumbricoides) associated with the consumption of street food salads using Quantitative Microbial Risk Assessment (QMRA). Three different risk assessment models were constructed, based on availability of microbial concentrations: 1) Water - starting from irrigation water quality, 2) Produce - starting from the quality of produce at market, and 3) Street - using microbial quality of street food salad. In the absence of viral concentrations, published ratios between faecal coliforms and viruses were used to estimate the quality of water, produce and salad, and annual disease burdens were determined. Rotavirus dominated the estimates of annual disease burden (~10(-3)Disability Adjusted Life Years per person per year (DALYs pppy)), although norovirus also exceeded the 10(-4)DALY threshold for both Produce and Street models. The Water model ignored other on-farm and post-harvest sources of contamination and consistently produced lower estimates of risk; it likely underestimates disease burden and therefore is not recommended. Required log reductions of up to 5.3 (95th percentile) for rotavirus were estimated for the Street model, demonstrating that significant interventions are required to protect the health and safety of street food consumers in Kumasi. Estimates of virus concentrations were a significant source of model uncertainty and more data on pathogen concentrations is needed to refine QMRA estimates of disease burden. Copyright © 2014 Elsevier B.V. All rights reserved.

Estimated and measured traveltime for the Crow River watershed, Minnesota

USGS Publications Warehouse

Arntson, Allan D.

2007-01-01

A time-of-travel study involving a luminescent dye was done on the Crow River in Minnesota from Rockford to the confluence with the Mississippi River at Dayton on July 11, 2006, at a streamflow of 293 cubic feet per second at Rockford. Dye was injected in the Crow River at Rockford, and traveltime and concentrations were measured at three sampling locations downstream: at the Hanover historic bridge in Hanover, at County Road 116 near St. Michael, and at County Road 12 in Dayton. The results of the measured traveltimes were compared to estimated traveltimes from a previous study of the Crow River and six other rivers in the Upper Mississippi River basin in 2003. Regression equations based on watershed characteristics of drainage area, river slope, mean-annual streamflow, and instantaneous streamflow at the time of measurement from more than 900 stream segments across the Nation were used to estimate traveltimes. Traveltimes were estimated and measured for the leading edge, peak concentration, and trailing edge of tracer-response curves. Estimated traveltimes for the leading edge, peak concentration, and trailing edge at Dayton were 25.3, 28.4, and 35.6 hours, respectively. Measured traveltimes for the leading edge, peak concentration, and trailing edge at Dayton were 33.2, 38.2, and 49.2 hours, respectively, for the 22.4-mile reach. Although traveltimes for the Crow and the Sauk Rivers were underestimated by use of the regression equations, the regression estimates were close enough to measured values to be considered satisfactory; hence, this estimating technique should be applicable in other source-water planning efforts in and near the study area.

Installation Restoration Program. Remedial Investigation Report: Minnesota Air National Guard Base Duluth International Airport, Duluth, Minnesota. Volume 7

DTIC Science & Technology

1990-01-01

Selection of Indicator Chemicals 6-36 6.2.2 Estimation of Exposure Point Concentrations or Emission Rates 6-38 6.2.2.1 Exposure Pathway Analysis 6-38...Exposure Point Concentrations or Emission Rates 6-50 j 6.3.2.1 Exposure Pathway Analysis 6-52 6.3.2.2 Exposure Point Concentrations 6-55 6.3.2.3...Exposure Point Concentrations or Emission Rates 6-62 6.4.2.1 Exposure Pathway Analysis 6-62 6.4.2.2 Exposure Point Concentrations 6-69 6.4.2.3

Informing Selection of Nanomaterial Concentrations for ...

EPA Pesticide Factsheets

Little justification is generally provided for selection of in vitro assay testing concentrations for engineered nanomaterials (ENMs). Selection of concentration levels for hazard evaluation based on real-world exposure scenarios is desirable. We reviewed published ENM concentrations measured in air in manufacturing and R&D labs to identify input levels for estimating ENM mass retained in the human lung using the Multiple-Path Particle Dosimetry (MPPD) model. Model input parameters were individually varied to estimate alveolar mass retained for different particle sizes (5-1000 nm), aerosol concentrations (0.1, 1 mg/m3), aspect ratios (2, 4, 10, 167), and exposure durations (24 hours and a working lifetime). The calculated lung surface concentrations were then converted to in vitro solution concentrations. Modeled alveolar mass retained after 24 hours is most affected by activity level and aerosol concentration. Alveolar retention for Ag and TiO2 nanoparticles and CNTs for a working lifetime (45 years) exposure duration is similar to high-end concentrations (~ 30-400 μg/mL) typical of in vitro testing reported in the literature. Analyses performed are generally applicable to provide ENM testing concentrations for in vitro hazard screening studies though further research is needed to improve the approach. Understanding the relationship between potential real-world exposures and in vitro test concentrations will facilitate interpretation of toxicological results

Lactate threshold by muscle electrical impedance in professional rowers

NASA Astrophysics Data System (ADS)

Jotta, B.; Coutinho, A. B. B.; Pino, A. V.; Souza, M. N.

2017-04-01

Lactate threshold (LT) is one of the physiological parameters usually used in rowing sport training prescription because it indicates the transitions from aerobic to anaerobic metabolism. Assessment of LT is classically based on a series of values of blood lactate concentrations obtained during progressive exercise tests and thus has an invasive aspect. The feasibility of noninvasive LT estimative through bioelectrical impedance spectroscopy (BIS) data collected in thigh muscles during rowing ergometer exercise tests was investigated. Nineteen professional rowers, age 19 (mean) ± 4.8 (standard deviation) yr, height 187.3 ± 6.6 cm, body mass 83 ± 7.7 kg, and training experience of 7 ± 4 yr, were evaluated in a rowing ergometer progressive test with paired measures of blood lactate concentration and BIS in thigh muscles. Bioelectrical impedance data were obtained by using a bipolar method of spectroscopy based on the current response to a voltage step. An electrical model was used to interpret BIS data and to derive parameters that were investigated to estimate LT noninvasively. From the serial blood lactate measurements, LT was also determined through Dmax method (LTDmax). The zero crossing of the second derivative of kinetic of the capacitance electrode (Ce), one of the BIS parameters, was used to estimate LT. The agreement between the LT estimates through BIS (LTBIS) and through Dmax method (LTDmax) was evaluated using Bland-Altman plots, leading to a mean difference between the estimates of just 0.07 W and a Pearson correlation coefficient r = 0.85. This result supports the utilization of the proposed method based on BIS parameters for estimating noninvasively the lactate threshold in rowing.

Statistics of concentrations due to single air pollution sources to be applied in numerical modelling of pollutant dispersion

NASA Astrophysics Data System (ADS)

Tumanov, Sergiu

A test of goodness of fit based on rank statistics was applied to prove the applicability of the Eggenberger-Polya discrete probability law to hourly SO 2-concentrations measured in the vicinity of single sources. With this end in view, the pollutant concentration was considered an integral quantity which may be accepted if one properly chooses the unit of measurement (in this case μg m -3) and if account is taken of the limited accuracy of measurements. The results of the test being satisfactory, even in the range of upper quantiles, the Eggenberger-Polya law was used in association with numerical modelling to estimate statistical parameters, e.g. quantiles, cumulative probabilities of threshold concentrations to be exceeded, and so on, in the grid points of a network covering the area of interest. This only needs accurate estimations of means and variances of the concentration series which can readily be obtained through routine air pollution dispersion modelling.

Optical sensor for remote estimation of alcohol concentration in blood stream

NASA Astrophysics Data System (ADS)

Shenhav, Asaf; Brodie, Ziv; Beiderman, Yevgeny; Garcia, Javier; Mico, Vicente; Zalevsky, Zeev

2013-02-01

The purpose of this manuscript is to validate our recently developed novel optical approach for extraction of remote vibration sources as a successful technique to estimate the alcohol concentration in blood stream. This technique is based on the tracking of temporal changes of reflected secondary speckle patterns produced in human skin when being illuminated by a laser beam. Since the skin's vibrations profile is changed due to the alcohol in the blood stream, the extraction of the vibration profile can be translated into the corresponding alcohol concentration values by means of defining several parameters acting as indicators for the presence of alcohol in the blood stream. We have conducted several experimental tests showing a good correlation with conventional breath alcohol concentration measurement device when determining alcohol concentration in blood. The presented preliminary results validate the proposed optical sensor as a potentially useful device for measuring alcohol in blood stream with subjects that can be car drivers inspected by police authorities or medically monitored patients.

Large inter-individual variation in isoflavone plasma concentration limits use of isoflavone intake data for risk assessment

PubMed Central

van der Velpen, V; Hollman, P C; van Nielen, M; Schouten, E G; Mensink, M; van't Veer, P; Geelen, A

2014-01-01

Background/objectives: Isoflavones are present in soy foods and soy-based supplements. Despite low plasma isoflavone concentrations in the general Western population, concentrations in supplement users exceed those suggested to be beneficial for health in Asian populations, raising concerns for adverse effects. To aid risk assessment, quantification of the relation between isoflavone intake and plasma concentrations is essential. Subjects/methods: Plasma samples were collected from postmenopausal women in three placebo-controlled crossover studies with 8-week periods for supplements (two studies, ~100 mg isoflavones/day, n=88) or 4-week periods for soy foods (one study, ~48 mg isoflavones/day, n=15). Plasma isoflavone concentrations (daidzein, equol, genistein and glycitein) were quantified using high-performance liquid chromatography and electrochemical detection. The association between plasma concentrations and isoflavone intake, equol producer status, intake–producer interaction and background dietary intake was assessed based on the assumption of a log-linear relation. Results: Median plasma total isoflavone concentrations after the soy food and supplement interventions were respectively 2.16 and 3.47 μmol/l for equol producers and 1.30 and 2.39 μmol/l for non-producers. Regression analysis showed that doubling isoflavone intake increased plasma concentrations by 55–62% (±s.e. 1–2%, R2>0.87) for daidzein, genistein, equol (only for producers) and total isoflavones; for glycitein the association was weaker (15±1%, R2=0.48). Adjustments for energy, carbohydrate and fat intake did not affect these estimates. Inter-individual variation, estimated based on repeated measures in one of the studies, was 30–96%. Conclusions: Although the relation between isoflavone intake and plasma concentrations was adequately quantified, the use of isoflavone intake data for risk assessment needs caution due to large inter-individual variation in plasma concentrations. PMID:24939433

Estimating Grass-Soil Bioconcentration of Munitions Compounds from Molecular Structure.

PubMed

Torralba Sanchez, Tifany L; Liang, Yuzhen; Di Toro, Dominic M

2017-10-03

A partitioning-based model is presented to estimate the bioconcentration of five munitions compounds and two munition-like compounds in grasses. The model uses polyparameter linear free energy relationships (pp-LFERs) to estimate the partition coefficients between soil organic carbon and interstitial water and between interstitial water and the plant cuticle, a lipid-like plant component. Inputs for the pp-LFERs are a set of numerical descriptors computed from molecular structure only that characterize the molecular properties that determine the interaction with soil organic carbon, interstitial water, and plant cuticle. The model is validated by predicting concentrations measured in the whole plant during independent uptake experiments with a root-mean-square error (log predicted plant concentration-log observed plant concentration) of 0.429. This highlights the dominant role of partitioning between the exposure medium and the plant cuticle in the bioconcentration of these compounds. The pp-LFERs can be used to assess the environmental risk of munitions compounds and munition-like compounds using only their molecular structure as input.

Comparison of questionnaire-based estimation of pesticide residue intake from fruits and vegetables with urinary concentrations of pesticide biomarkers.

PubMed

Chiu, Yu-Han; Williams, Paige L; Mínguez-Alarcón, Lidia; Gillman, Matthew; Sun, Qi; Ospina, Maria; Calafat, Antonia M; Hauser, Russ; Chavarro, Jorge E

2018-01-01

We developed a pesticide residue burden score (PRBS) based on a food frequency questionnaire and surveillance data on food pesticide residues to characterize dietary exposure over the past year. In the present study, we evaluated the association of the PRBS with urinary concentrations of pesticide biomarkers. Fruit and vegetable (FV) intake was classified as having high (PRBS≥4) or low (PRBS<4) pesticide residues for 90 men from the EARTH study. Two urine samples per man were analyzed for seven biomarkers of organophosphate and pyrethroid insecticides, and the herbicide 2,4-dichlorophenoxyacetic acid. We used generalized estimating equations to analyze the association of the PRBS with urinary concentrations of pesticide biomarkers. Urinary concentrations of pesticide biomarkers were positively related to high pesticide FV intake but inversely related to low pesticide FV intake. The molar sum of urinary concentrations of pesticide biomarkers was 21% (95% confidence interval (CI): 2%, 44%) higher for each one serving/day increase in high pesticide FV intake, and 10% (95% CI: 1%, 18%) lower for each one serving/day increase in low pesticide FV intake. Furthermore, intake of high pesticide FVs positively related to most individual urinary biomarkers. Our findings support the usefulness of the PRBS approach to characterize dietary exposure to select pesticides.

Single image super-resolution reconstruction algorithm based on eage selection

NASA Astrophysics Data System (ADS)

Zhang, Yaolan; Liu, Yijun

2017-05-01

Super-resolution (SR) has become more important, because it can generate high-quality high-resolution (HR) images from low-resolution (LR) input images. At present, there are a lot of work is concentrated on developing sophisticated image priors to improve the image quality, while taking much less attention to estimating and incorporating the blur model that can also impact the reconstruction results. We present a new reconstruction method based on eager selection. This method takes full account of the factors that affect the blur kernel estimation and accurately estimating the blur process. When comparing with the state-of-the-art methods, our method has comparable performance.

Estimates of water and solute release from a coal waste rock dump in the Elk Valley, British Columbia, Canada.

PubMed

Villeneuve, S A; Barbour, S L; Hendry, M J; Carey, S K

2017-12-01

Long term (1999 to 2014) flow and water quality data from a rock drain located at the base of a coal waste rock dump constructed in the Elk Valley, British Columbia was used to characterize the release of three solutes (NO 3 - , Cl - and SO 4 2- ) from the dump and obtain whole dump estimates of net percolation (NP). The concentrations of dump derived solutes in the rock drain water were diluted by snowmelt waters from the adjacent natural watershed during the spring freshet and reached a maximum concentration during the winter baseflow period. Historical peak baseflow concentrations of conservative ions (NO 3 - and Cl - ) increased until 2006/07 after which they decreased. This decrease was attributed to completion of the flushing of the first pore volume of water stored within the dump. The baseflow SO 4 2- concentrations increased proportionally with NO 3 - and Cl - to 2007, but then continued to slowly increase as NO 3 - and Cl - concentrations decreased. This was attributed to ongoing production of SO 4 2- due to oxidation of sulfide minerals within the dump. Based on partitioning of the annual volume of water discharged from the rock drain to waste rock effluent (NP) and water entering the rock drain laterally from the natural watershed, the mean NP values were estimated to be 446±50mm/a (area normalized net percolation/year) for the dump and 172±71mm/a for the natural watershed. The difference was attributed to greater rates of recharge in the dump from summer precipitation compared to the natural watershed where rainfall interception and enhanced evapotranspiration will increase water losses. These estimates included water moving through subsurface pathways. However, given the limitations in quantifying these flows the estimated NP rates for both the natural watershed and the waste rock dump are considered to be low, and could be much higher (e.g. ~450mm/a and ~800mm/a). Copyright © 2017 Elsevier B.V. All rights reserved.

Investigation of metabolite changes in the transition from pre-invasive to invasive cervical cancer measured using (1)H and (31)P magic angle spinning MRS of intact tissue.

PubMed

De Silva, Sonali S; Payne, Geoffrey S; Thomas, Valerie; Carter, Paul G; Ind, Thomas E J; deSouza, Nandita M

2009-02-01

The aim of this study was to determine the metabolic changes in the transition from pre-invasive to invasive cervical cancer using high-resolution magic angle spinning (HR-MAS) MRS. Biopsy specimens were obtained from women with histologically normal cervix (n = 5), cervical intraepithelial neoplasia (CIN; mild, n = 5; moderate/severe, n = 40), and invasive cancer (n = 23). (1)H HR-MAS MRS data were acquired using a Bruker Avance 11.74 T spectrometer (Carr-Purcell-Meiboom-Gill sequence; TR = 4.8 s; TE = 135 ms; 512 scans; 41 min acquisition). (31)P HR-MAS spectra were obtained from the normal subjects and cancer patients only (as acetic acid applied before tissue sampling in patients with CIN impaired spectral quality) using a (1)H-decoupled pulse-acquire sequence (TR = 2.82 s; 2048 scans; 96 min acquisition). Peak assignments were based on values reported in the literature. Peak areas were measured using the AMARES algorithm. Estimated metabolite concentrations were compared between patient diagnostic categories and tissue histology using independent samples t tests. Comparisons based on patient category at diagnosis showed significantly higher estimated concentrations of choline (P = 0.0001) and phosphocholine (P = 0.002) in tissue from patients with cancer than from patients with high-grade dyskaryosis, but no differences between non-cancer groups. Division by histology of the sample also showed increases in choline (P = 0.002) and phosphocholine (P = 0.002) in cancer compared with high-grade CIN tissue. Phosphoethanolamine was increased in cancer compared with normal tissue (P = 0.0001). Estimated concentrations of alanine (P = 0.01) and creatine (P = 0.008) were significantly reduced in normal tissue from cancer patients compared with normal tissue from non-cancer patients. The estimated concentration of choline was significantly increased in CIN tissue from cancer patients compared with CIN tissue from non-cancer patients (P = 0.0001). Estimated concentrations of choline-containing metabolites increased from pre-invasive to invasive cervical cancer. Concurrent metabolite depletion occurs in normal tissue adjacent to cancer tissue. Copyright (c) 2008 John Wiley & Sons, Ltd.

Prediction of fish and sediment mercury in streams using landscape variables and historical mining.

PubMed

Alpers, Charles N; Yee, Julie L; Ackerman, Joshua T; Orlando, James L; Slotton, Darrel G; Marvin-DiPasquale, Mark C

2016-11-15

Widespread mercury (Hg) contamination of aquatic systems in the Sierra Nevada of California, U.S., is associated with historical use to enhance gold (Au) recovery by amalgamation. In areas affected by historical Au mining operations, including the western slope of the Sierra Nevada and downstream areas in northern California, such as San Francisco Bay and the Sacramento River-San Joaquin River Delta, microbial conversion of Hg to methylmercury (MeHg) leads to bioaccumulation of MeHg in food webs, and increased risks to humans and wildlife. This study focused on developing a predictive model for THg in stream fish tissue based on geospatial data, including land use/land cover data, and the distribution of legacy Au mines. Data on total mercury (THg) and MeHg concentrations in fish tissue and streambed sediment collected during 1980-2012 from stream sites in the Sierra Nevada, California were combined with geospatial data to estimate fish THg concentrations across the landscape. THg concentrations of five fish species (Brown Trout, Rainbow Trout, Sacramento Pikeminnow, Sacramento Sucker, and Smallmouth Bass) within stream sections were predicted using multi-model inference based on Akaike Information Criteria, using geospatial data for mining history and landscape characteristics as well as fish species and length (r(2)=0.61, p<0.001). Including THg concentrations in streambed sediment did not improve the model's fit, however including MeHg concentrations in streambed sediment, organic content (loss on ignition), and sediment grain size resulted in an improved fit (r(2)=0.63, p<0.001). These models can be used to estimate THg concentrations in stream fish based on landscape variables in the Sierra Nevada in areas where direct measurements of THg concentration in fish are unavailable. Published by Elsevier B.V.

Prediction of fish and sediment mercury in streams using landscape variables and historical mining

USGS Publications Warehouse

Alpers, Charles N.; Yee, Julie L.; Ackerman, Joshua T.; Orlando, James L.; Slotton, Darrell G.; Marvin-DiPasquale, Mark C.

2016-01-01

Widespread mercury (Hg) contamination of aquatic systems in the Sierra Nevada of California, U.S., is associated with historical use to enhance gold (Au) recovery by amalgamation. In areas affected by historical Au mining operations, including the western slope of the Sierra Nevada and downstream areas in northern California, such as San Francisco Bay and the Sacramento River–San Joaquin River Delta, microbial conversion of Hg to methylmercury (MeHg) leads to bioaccumulation of MeHg in food webs, and increased risks to humans and wildlife. This study focused on developing a predictive model for THg in stream fish tissue based on geospatial data, including land use/land cover data, and the distribution of legacy Au mines. Data on total mercury (THg) and MeHg concentrations in fish tissue and streambed sediment collected during 1980–2012 from stream sites in the Sierra Nevada, California were combined with geospatial data to estimate fish THg concentrations across the landscape. THg concentrations of five fish species (Brown Trout, Rainbow Trout, Sacramento Pikeminnow, Sacramento Sucker, and Smallmouth Bass) within stream sections were predicted using multi-model inference based on Akaike Information Criteria, using geospatial data for mining history and landscape characteristics as well as fish species and length (r2 = 0.61, p < 0.001). Including THg concentrations in streambed sediment did not improve the model's fit, however including MeHg concentrations in streambed sediment, organic content (loss on ignition), and sediment grain size resulted in an improved fit (r2 = 0.63, p < 0.001). These models can be used to estimate THg concentrations in stream fish based on landscape variables in the Sierra Nevada in areas where direct measurements of THg concentration in fish are unavailable.

State and national household concentrations of PM2.5 from solid cookfuel use: Results from measurements and modeling in India for estimation of the global burden of disease

PubMed Central

2013-01-01

Background Previous global burden of disease (GBD) estimates for household air pollution (HAP) from solid cookfuel use were based on categorical indicators of exposure. Recent progress in GBD methodologies that use integrated–exposure–response (IER) curves for combustion particles required the development of models to quantitatively estimate average HAP levels experienced by large populations. Such models can also serve to inform public health intervention efforts. Thus, we developed a model to estimate national household concentrations of PM2.5 from solid cookfuel use in India, together with estimates for 29 states. Methods We monitored 24-hr household concentrations of PM2.5, in 617 rural households from 4 states in India on a cross-sectional basis between November 2004 and March 2005. We then, developed log-linear regression models that predict household concentrations as a function of multiple, independent household level variables available in national household surveys and generated national / state estimates using The Indian National Family and Health Survey (NFHS 2005). Results The measured mean 24-hr concentration of PM2.5 in solid cookfuel using households ranged from 163 μg/m3 (95% CI: 143,183; median 106; IQR: 191) in the living area to 609 μg/m3 (95% CI: 547,671; median: 472; IQR: 734) in the kitchen area. Fuel type, kitchen type, ventilation, geographical location and cooking duration were found to be significant predictors of PM2.5 concentrations in the household model. k-fold cross validation showed a fair degree of correlation (r = 0.56) between modeled and measured values. Extrapolation of the household results by state to all solid cookfuel-using households in India, covered by NFHS 2005, resulted in a modeled estimate of 450 μg/m3 (95% CI: 318,640) and 113 μg/m3 (95% CI: 102,127) , for national average 24-hr PM2.5 concentrations in the kitchen and living areas respectively. Conclusions The model affords substantial improvement over commonly used exposure indicators such as “percent solid cookfuel use” in HAP disease burden assessments, by providing some of the first estimates of national average HAP levels experienced in India. Model estimates also add considerable strength of evidence for framing and implementation of intervention efforts at the state and national levels. PMID:24020494

Estimation of the activation energy in the Belousov-Zhabotinsky reaction by temperature effect on excitable waves.

PubMed

Zhang, Jinzhong; Zhou, Luqun; Ouyang, Qi

2007-02-15

We report the temperature effect on the propagation of excitable traveling waves in a quasi-two-dimensional Belousov-Zhabotinsky reaction-diffusion system. The onset of excitable waves as a function of the sulfuric acid concentration and temperature is identified, on which the sulfuric acid concentration exhibits an Arrhenius dependence on temperature. On the basis of this experimental data, the activation energy of the self-catalyzed reaction in the Oregonator model is estimated to be 83-113 kJ/mol, which is further supported by our numerical simulations. The estimation proceeds without analyzing detailed reaction steps but rather through observing the global dynamic behaviors in the BZ reaction. For a supplement, the wave propagation velocities are calculated based on our results and compared with the experimental observations.

Interaction between air pollution dispersion and residential heating demands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lipfert, F.W.; Moskowitz, P.D.; Dungan, J.

The effect of the short-term correlation of a specific emission (sulfur dioxide) from residential space heating, with air pollution dispersion rates on the accuracy of model estimates of urban air pollution on a seasonal or annual basis is analyzed. Hourly climatological and residential emission estimates for six U.S. cities and a simplified area source-dispersion model based on a circular receptor grid are used. The effect on annual average concentration estimations is found to be slight (approximately + or - 12 percent), while the maximum hourly concentrations are shown to vary considerably more, since maximum heat demand and worst-case dispersion aremore » not coincident. Accounting for the correlations between heating demand and dispersion makes possible a differentiation in air pollution potential between coastal and interior cities.« less

Anaerobic Transformation of Chlorinated Aliphatic Hydrocarbons in a Sand Aquifer Based on Spatial Chemical Distributions

NASA Astrophysics Data System (ADS)

Semprini, Lewis; Kitanidis, Peter K.; Kampbell, Don H.; Wilson, John T.

1995-04-01

We estimated the distribution of chlorinated aliphatic hydrocarbons (CAHs) from groundwater samples collected along three transects in a sand aquifer. Trichloroethylene (TCE) leaked and contaminated the aquifer probably more than a decade before we collected the measurements. The data show significant concentrations of TCE, cis-l,2-dichloroethylene (c-DCE), vinyl chloride (VC), and ethene. We attributed DCE, VC, and ethene to the reductive dehalogenation of TCE. The CAH concentrations varied significantly with depth and correlate with sulfate and methane concentrations. Anoxic aquifer conditions exist with methane present at relatively high concentrations at depth. High concentrations of TCE correspond with the absence of methane or low methane concentrations, whereas products of TCE dehalogenation are associated with higher methane concentrations and low sulfate concentrations. Indications are that the dechlorination of TCE and DCE to VC and ethene is associated with sulfate reduction and active methanogenesis. TCE dechlorination to DCE is likely occurring under the less reducing conditions of sulfate reduction, with further reductions to VC and ethene occurring under methanogenic conditions. We estimated that about 20% of TCE has dechlorinated to ethene. The analysis of the data enhanced our knowledge of natural in situ transformation and transport processes of CAHs.

On-line estimation and detection of abnormal substrate concentrations in WWTPs using a software sensor: a benchmark study.

PubMed

Benazzi, F; Gernaey, K V; Jeppsson, U; Katebi, R

2007-08-01

In this paper, a new approach for on-line monitoring and detection of abnormal readily biodegradable substrate (S(s)) and slowly biodegradable substrate (X(s)) concentrations, for example due to input of toxic loads from the sewer, or due to influent substrate shock load, is proposed. Considering that measurements of S(s) and X(s) concentrations are not available in real wastewater treatment plants, the S(s) / X(s) software sensor can activate an alarm with a response time of about 60 and 90 minutes, respectively, based on the dissolved oxygen measurement. The software sensor implementation is based on an extended Kalman filter observer and disturbances are modelled using fast Fourier transform and spectrum analyses. Three case studies are described. The first one illustrates the fast and accurate convergence of the extended Kalman filter algorithm, which is achieved in less than 2 hours. Furthermore, the difficulties of estimating X(s) when off-line analysis is not available are depicted, and the S(s) / X(s) software sensor performances when no measurements of S(s) and X(s) are available are illustrated. Estimation problems related to the death-regeneration concept of the activated sludge model no.1 and possible application of the software sensor in wastewater monitoring are discussed.

A statistical regression model for the estimation of acrylamide concentrations in French fries for excess lifetime cancer risk assessment.

PubMed

Chen, Ming-Jen; Hsu, Hui-Tsung; Lin, Cheng-Li; Ju, Wei-Yuan

2012-10-01

Human exposure to acrylamide (AA) through consumption of French fries and other foods has been recognized as a potential health concern. Here, we used a statistical non-linear regression model, based on the two most influential factors, cooking temperature and time, to estimate AA concentrations in French fries. The R(2) of the predictive model is 0.83, suggesting the developed model was significant and valid. Based on French fry intake survey data conducted in this study and eight frying temperature-time schemes which can produce tasty and visually appealing French fries, the Monte Carlo simulation results showed that if AA concentration is higher than 168 ppb, the estimated cancer risk for adolescents aged 13-18 years in Taichung City would be already higher than the target excess lifetime cancer risk (ELCR), and that by taking into account this limited life span only. In order to reduce the cancer risk associated with AA intake, the AA levels in French fries might have to be reduced even further if the epidemiological observations are valid. Our mathematical model can serve as basis for further investigations on ELCR including different life stages and behavior and population groups. Copyright © 2012 Elsevier Ltd. All rights reserved.

Overview of NASA's Carbon Monitoring System Flux-Pilot Project

NASA Technical Reports Server (NTRS)

Pawson, Steven; Gunson, Michael R.; Jucks, Kenneth

2011-01-01

NASA's space-based observations of physical, chemical and biological parameters in the Earth System along with state-of-the-art modeling capabilities provide unique capabilities for analyses of the carbon cycle. The Carbon Monitoring System is developing an exploratory framework for detecting carbon in the environment and its changes, with a view towards contributing to national and international monitoring activities. The Flux-Pilot Project aims to provide a unified view of land-atmosphere and ocean-atmosphere carbon exchange, using observation-constrained models. Central to the project is the application of NASA's satellite observations (especially MODIS), the ACOS retrievals of the JAXA-GOSAT observations, and the "MERRA" meteorological reanalysis produced with GEOS-S. With a primary objective of estimating uncertainty in computed fluxes, two land- and two ocean-systems are run for 2009-2010 and compared with existing flux estimates. An transport model is used to evaluate simulated CO2 concentrations with in-situ and space-based observations, in order to assess the realism of the fluxes and how uncertainties in fluxes propagate into atmospheric concentrations that can be more readily evaluated. Finally, the atmospheric partial CO2 columns observed from space are inverted to give new estimates of surface fluxes, which are evaluated using the bottom-up estimates and independent datasets. The focus of this presentation will be on the science goals and current achievements of the pilot project, with emphasis on how policy-relevant questions help focus the scientific direction. Examples include the issue of what spatio-temporal resolution of fluxes can be detected from polar-orbiting satellites and whether it is possible to use space-based observations to separate contributions to atmospheric concentrations of (say) fossil-fuel and biological activity

The Statistical Value of Raw Fluorescence Signal in Luminex xMAP Based Multiplex Immunoassays

PubMed Central

Breen, Edmond J.; Tan, Woei; Khan, Alamgir

2016-01-01

Tissue samples (plasma, saliva, serum or urine) from 169 patients classified as either normal or having one of seven possible diseases are analysed across three 96-well plates for the presences of 37 analytes using cytokine inflammation multiplexed immunoassay panels. Censoring for concentration data caused problems for analysis of the low abundant analytes. Using fluorescence analysis over concentration based analysis allowed analysis of these low abundant analytes. Mixed-effects analysis on the resulting fluorescence and concentration responses reveals a combination of censoring and mapping the fluorescence responses to concentration values, through a 5PL curve, changed observed analyte concentrations. Simulation verifies this, by showing a dependence on the mean florescence response and its distribution on the observed analyte concentration levels. Differences from normality, in the fluorescence responses, can lead to differences in concentration estimates and unreliable probabilities for treatment effects. It is seen that when fluorescence responses are normally distributed, probabilities of treatment effects for fluorescence based t-tests has greater statistical power than the same probabilities from concentration based t-tests. We add evidence that the fluorescence response, unlike concentration values, doesn’t require censoring and we show with respect to differential analysis on the fluorescence responses that background correction is not required. PMID:27243383

Estimation of surface PM10 concentration in Seoul during the DRAGON-Asia campaign based on the physical relationship between AOD and PM

NASA Astrophysics Data System (ADS)

Seo, S.; Kim, J.; Lee, H.; Jeong, U.; Kim, W. V.; Holben, B. N.; Kim, S.

2013-12-01

Atmospheric aerosols are known to play a role in climate change while it also adverse effects on human health such as respiratory and cardiovascular diseases. Especially, in terms of air quality, many studies have been conducted to estimate surface-level particulate matter (PM) concentration by using the satellite measurements to overcome the spatial limitation of ground-based aerosol measurements. In this study, we investigate the relationship between the column aerosol optical depth (AOD) and the surface PM10 concentration using the aerosol measurements during the DRAGON (Distributed Regional Aerosol Gridded Observation Network) - Asia campaign took place in Seoul from March to May, 2012. Based on the physical relationship between AOD and PM concentration, we develop various empirical linear models and evaluate the performance of these models. The best correlation (r = 0.67) is shown when vertical and size distribution of aerosols are additionally considered by using the boundary layer height (BLH) from backscattered lidar signals and the effective radius provided in AERONET inversion products. Similarly, MODIS AOD divided by BLH shows the best correlation with hourly PM10 (r = 0.62). We also identify the variability of correlations between AOD and PM10 depending on the environment characteristics in a complex megacity, Seoul by using the aerosol optical properties measured at mesoscale-level at 10 AERONET sites during the DRAGON campaign. Both AERONET and MODIS show higher correlation in residential area than near source area. Finally, we investigate the seasonal effects on the performance of various empirical linear models and find important factors of each season in PM estimation.

Air pollution and acute respiratory response in a panel of asthmatic children along the U.S.-Mexico border.

PubMed

Sarnat, Stefanie Ebelt; Raysoni, Amit U; Li, Wen-Whai; Holguin, Fernando; Johnson, Brent A; Flores Luevano, Silvia; Garcia, Jose Humberto; Sarnat, Jeremy A

2012-03-01

Concerns regarding the health impact of urban air pollution on asthmatic children are pronounced along the U.S.-Mexico border because of rapid population growth near busy border highways and roads. We conducted the first binational study of the impacts of air pollution on asthmatic children in Ciudad Juarez, Mexico, and El Paso, Texas, USA, and compared different exposure metrics to assess acute respiratory response. We recruited 58 asthmatic children from two schools in Ciudad Juarez and two schools in El Paso. A marker of airway inflammation [exhaled nitric oxide (eNO)], respiratory symptom surveys, and pollutant measurements (indoor and outdoor 48-hr size-fractionated particulate matter, 48-hr black carbon, and 96-hr nitrogen dioxide) were collected at each school for 16 weeks. We examined associations between the pollutants and respiratory response using generalized linear mixed models. We observed small but consistent associations between eNO and numerous pollutant metrics, with estimated increases in eNO ranging from 1% to 3% per interquartile range increase in pollutant concentrations. Effect estimates from models using school-based concentrations were generally stronger than corresponding estimates based on concentrations from ambient air monitors. Both traffic-related and non-traffic-related particles were typically more robust predictors of eNO than was nitrogen dioxide, for which associations were highly sensitive to model specification. Associations differed significantly across the four school-based cohorts, consistent with heterogeneity in pollutant concentrations and cohort characteristics. Models examining respiratory symptoms were consistent with the null. The results indicate adverse effects of air pollution on the subclinical respiratory health of asthmatic children in this region and provide preliminary support for the use of air pollution monitors close to schools to track exposure and potential health risk in this population.

Estimation of Phytoplankton Accessory Pigments From Hyperspectral Reflectance Spectra: Toward a Global Algorithm

NASA Astrophysics Data System (ADS)

Chase, A. P.; Boss, E.; Cetinić, I.; Slade, W.

2017-12-01

Phytoplankton community composition in the ocean is complex and highly variable over a wide range of space and time scales. Able to cover these scales, remote-sensing reflectance spectra can be measured both by satellite and by in situ radiometers. The spectral shape of reflectance in the open ocean is influenced by the particles in the water, mainly phytoplankton and covarying nonalgal particles. We investigate the utility of in situ hyperspectral remote-sensing reflectance measurements to detect phytoplankton pigments by using an inversion algorithm that defines phytoplankton pigment absorption as a sum of Gaussian functions. The inverted amplitudes of the Gaussian functions representing pigment absorption are compared to coincident High Performance Liquid Chromatography measurements of pigment concentration. We determined strong predictive capability for chlorophylls a, b, c1+c2, and the photoprotective carotenoids. We also tested the estimation of pigment concentrations from reflectance-derived chlorophyll a using global relationships of covariation between chlorophyll a and the accessory pigments. We found similar errors in pigment estimation based on the relationships of covariation versus the inversion algorithm. An investigation of spectral residuals in reflectance data after removal of chlorophyll-based average absorption spectra showed no strong relationship between spectral residuals and pigments. Ultimately, we are able to estimate concentrations of three chlorophylls and the photoprotective carotenoid pigments, noting that further work is necessary to address the challenge of extracting information from hyperspectral reflectance beyond the information that can be determined from chlorophyll a and its covariation with other pigments.

Genotypic gain with simultaneous selection of production, nutrition, and culinary traits in cowpea crosses and backcrosses using mixed models.

PubMed

Oliveira, D G; Rocha, M M; Damasceno-Silva, K J; Sá, F V; Lima, L R L; Resende, M D V

2017-08-17

The aim of this study was to estimate the genotypic gain with simultaneous selection of production, nutrition, and culinary traits in cowpea crosses and backcrosses and to compare different selection indexes. Eleven cowpea populations were evaluated in a randomized complete block design with four replications. Fourteen traits were evaluated, and the following parameters were estimated: genotypic variation coefficient, genotypic determination coefficient, experimental quality indicator and selection reliability, estimated genotypic values ​​- BLUE, genotypic correlation coefficient among traits, and genotypic gain with simultaneous selection of all traits. The genotypic gain was estimated based on tree selection indexes: classical, multiplicative, and the sum of ranks. The genotypic variation coefficient was higher than the environmental variation coefficient for the number of days to start flowering, plant type, the weight of one hundred grains, grain index, and protein concentration. The majority of the traits presented genotypic determination coefficient from medium to high magnitude. The identification of increases in the production components is associated with decreases in protein concentration, and the increase in precocity leads to decreases in protein concentration and cooking time. The index based on the sum of ranks was the best alternative for simultaneous selection of traits in the cowpea segregating populations resulting from the crosses and backcrosses evaluated, with emphasis on the F 4 BC 12 , F 4 C 21 , and F 4 C 12 populations, which had the highest genotypic gains.

Influence of time of concentration on variation of runoff from a small urbanized watershed

Treesearch

Devendra Amatya; Agnieszka Cupak; Andrzej Walega

2015-01-01

The main objective of the paper is to estimate the influence of time of concentration (TC) on maximum flow in an urbanized watershed. The calculations of maximum flow have been carried out using the Rational method, Technical Release 55 (TR55) procedure based on NRCS (National Resources Conservation Services) guidelines, and NRCS-UH rainfall-runoff model. Similarly,...

Comparison of Techniques to Estimate Ammonia Emissions at Cattle Feedlots Using Time-Averaged and Instantaneous Concentration Measurements

NASA Astrophysics Data System (ADS)

Shonkwiler, K. B.; Ham, J. M.; Williams, C. M.

2013-12-01

Ammonia (NH3) that volatilizes from confined animal feeding operations (CAFOs) can form aerosols that travel long distances where such aerosols can deposit in sensitive regions, potentially causing harm to local ecosystems. However, quantifying the emissions of ammonia from CAFOs through direct measurement is very difficult and costly to perform. A system was therefore developed at Colorado State University for conditionally sampling NH3 concentrations based on weather parameters measured using inexpensive equipment. These systems use passive diffusive cartridges (Radiello, Sigma-Aldrich, St. Louis, MO, USA) that provide time-averaged concentrations representative of a two-week deployment period. The samplers are exposed by a robotic mechanism so they are only deployed when wind is from the direction of the CAFO at 1.4 m/s or greater. These concentration data, along with other weather variables measured during each sampler deployment period, can then be used in a simple inverse model (FIDES, UMR Environnement et Grandes Cultures, Thiverval-Grignon, France) to estimate emissions. There are not yet any direct comparisons of the modeled emissions derived from time-averaged concentration data to modeled emissions from more sophisticated backward Lagrangian stochastic (bLs) techniques that utilize instantaneous measurements of NH3 concentration. In the summer and autumn of 2013, a suite of robotic passive sampler systems were deployed at a 25,000-head cattle feedlot at the same time as an open-path infrared (IR) diode laser (GasFinder2, Boreal Laser Inc., Edmonton, Alberta, Canada) which continuously measured ammonia concentrations instantaneously over a 225-m path. This particular laser is utilized in agricultural settings, and in combination with a bLs model (WindTrax, Thunder Beach Scientific, Inc., Halifax, Nova Scotia, Canada), has become a common method for estimating NH3 emissions from a variety of agricultural and industrial operations. This study will first compare the ammonia concentrations measured with the Radiello system to that measured with the long-path IR laser. Second, NH3 emissions estimated using the simple inverse model (FIDES) and the time-averaged data will be compared to emissions derived from the bLS model (WindTrax) using the laser-based NH3 data. Results could lead to a more cost-efficient and simpler technique for monitoring ammonia fluxes from of CAFOs and other strong areal sources.

Optimal estimation of suspended-sediment concentrations in streams

USGS Publications Warehouse

Holtschlag, D.J.

2001-01-01

Optimal estimators are developed for computation of suspended-sediment concentrations in streams. The estimators are a function of parameters, computed by use of generalized least squares, which simultaneously account for effects of streamflow, seasonal variations in average sediment concentrations, a dynamic error component, and the uncertainty in concentration measurements. The parameters are used in a Kalman filter for on-line estimation and an associated smoother for off-line estimation of suspended-sediment concentrations. The accuracies of the optimal estimators are compared with alternative time-averaging interpolators and flow-weighting regression estimators by use of long-term daily-mean suspended-sediment concentration and streamflow data from 10 sites within the United States. For sampling intervals from 3 to 48 days, the standard errors of on-line and off-line optimal estimators ranged from 52.7 to 107%, and from 39.5 to 93.0%, respectively. The corresponding standard errors of linear and cubic-spline interpolators ranged from 48.8 to 158%, and from 50.6 to 176%, respectively. The standard errors of simple and multiple regression estimators, which did not vary with the sampling interval, were 124 and 105%, respectively. Thus, the optimal off-line estimator (Kalman smoother) had the lowest error characteristics of those evaluated. Because suspended-sediment concentrations are typically measured at less than 3-day intervals, use of optimal estimators will likely result in significant improvements in the accuracy of continuous suspended-sediment concentration records. Additional research on the integration of direct suspended-sediment concentration measurements and optimal estimators applied at hourly or shorter intervals is needed.

On-line estimation of suspended solids in biological reactors of WWTPs using a Kalman observer.

PubMed

Beltrán, S; Irizar, I; Monclús, H; Rodríguez-Roda, I; Ayesa, E

2009-01-01

The total amount of solids in Wastewater Treatment Plants (WWTPs) and their distribution among the different elements and lines play a crucial role in the stability, performance and operational costs of the process. However, an accurate prediction of the evolution of solids concentration in the different elements of a WWTP is not a straightforward task. This paper presents the design, development and validation of a generic Kalman observer for the on-line estimation of solids concentration in the tank reactors of WWTPs. The proposed observer is based on the fact that the information about the evolution of the total amount of solids in the plant can be supplied by the available on-line Suspended Solids (SS) analysers, while their distribution can be simultaneously estimated from the hydraulic pattern of the plant. The proposed observer has been applied to the on-line estimation of SS in the reactors of a pilot-scale Membrane Bio-Reactor (MBR). The results obtained have shown that the experimental information supplied by a sole on-line SS analyser located in the first reactor of the pilot plant, in combination with updated information about internal flow rates data, has been able to give a reasonable estimation of the evolution of the SS concentration in all the tanks.

Estimation of personal exposure to asbestos of brake repair workers.

PubMed

Cely-García, María Fernanda; Curriero, Frank C; Sánchez-Silva, Mauricio; Breysse, Patrick N; Giraldo, Margarita; Méndez, Lorena; Torres-Duque, Carlos; Durán, Mauricio; González-García, Mauricio; Parada, Patricia; Ramos-Bonilla, Juan Pablo

2017-07-01

Exposure assessments are key tools to conduct epidemiological studies. Since 2010, 28 riveters from 18 brake repair shops with different characteristics and workloads were sampled for asbestos exposure in Bogotá, Colombia. Short-term personal samples collected during manipulation activities of brake products, and personal samples collected during non-manipulation activities were used to calculate 103 8-h TWA PCM-equivalent personal asbestos concentrations. The aims of this study are to identify exposure determinant variables associated with the 8-h TWA personal asbestos concentrations among brake mechanics, and propose different models to estimate potential asbestos exposure of brake mechanics in an 8-h work-shift. Longitudinal-based multivariate linear regression models were used to determine the association between personal asbestos concentrations in a work-shift with different variables related to work tasks and workload of the mechanics, and some characteristics of the shops. Monte Carlo simulations were used to estimate the 8-h TWA PCM-Eq personal asbestos concentration in work-shifts that had manipulations of brake products or cleaning activities of the manipulation area, using the results of the sampling campaigns. The simulations proposed could be applied for both current and retrospective studies to determine personal asbestos exposures of brake mechanics, without the need of sampling campaigns or historical data of air asbestos concentrations.

Quantitative Microbial Risk Assessment for Spray Irrigation of Dairy Manure Based on an Empirical Fate and Transport Model

PubMed Central

Burch, Tucker R.; Spencer, Susan K.; Stokdyk, Joel P.; Kieke, Burney A.; Larson, Rebecca A.; Firnstahl, Aaron D.; Rule, Ana M.

2017-01-01

Background: Spray irrigation for land-applying livestock manure is increasing in the United States as farms become larger and economies of scale make manure irrigation affordable. Human health risks from exposure to zoonotic pathogens aerosolized during manure irrigation are not well understood. Objectives: We aimed to a) estimate human health risks due to aerosolized zoonotic pathogens downwind of spray-irrigated dairy manure; and b) determine which factors (e.g., distance, weather conditions) have the greatest influence on risk estimates. Methods: We sampled downwind air concentrations of manure-borne fecal indicators and zoonotic pathogens during 21 full-scale dairy manure irrigation events at three farms. We fit these data to hierarchical empirical models and used model outputs in a quantitative microbial risk assessment (QMRA) to estimate risk [probability of acute gastrointestinal illness (AGI)] for individuals exposed to spray-irrigated dairy manure containing Campylobacter jejuni, enterohemorrhagic Escherichia coli (EHEC), or Salmonella spp. Results: Median risk estimates from Monte Carlo simulations ranged from 10−5 to 10−2 and decreased with distance from the source. Risk estimates for Salmonella or EHEC-related AGI were most sensitive to the assumed level of pathogen prevalence in dairy manure, while risk estimates for C. jejuni were not sensitive to any single variable. Airborne microbe concentrations were negatively associated with distance and positively associated with wind speed, both of which were retained in models as a significant predictor more often than relative humidity, solar irradiation, or temperature. Conclusions: Our model-based estimates suggest that reducing pathogen prevalence and concentration in source manure would reduce the risk of AGI from exposure to manure irrigation, and that increasing the distance from irrigated manure (i.e., setbacks) and limiting irrigation to times of low wind speed may also reduce risk. https://doi.org/10.1289/EHP283 PMID:28885976

Quantitative microbial risk assessment for spray irrigation of dairy manure based on an empirical fate and transport model

USGS Publications Warehouse

Burch, Tucker R; Spencer, Susan K.; Stokdyk, Joel; Kieke, Burney A; Larson, Rebecca A; Firnstahl, Aaron; Rule, Ana M; Borchardt, Mark A.

2017-01-01

BACKGROUND: Spray irrigation for land-applying livestock manure is increasing in the United States as farms become larger and economies of scale make manure irrigation affordable. Human health risks from exposure to zoonotic pathogens aerosolized during manure irrigation are not well understood. OBJECTIVES: We aimed to a) estimate human health risks due to aerosolized zoonotic pathogens downwind of spray-irrigated dairy manure; and b) determine which factors (e.g., distance, weather conditions) have the greatest influence on risk estimates. METHODS: We sampled downwind air concentrations of manure-borne fecal indicators and zoonotic pathogens during 21 full-scale dairy manure irri- gation events at three farms. We fit these data to hierarchical empirical models and used model outputs in a quantitative microbial risk assessment (QMRA) to estimate risk [probability of acute gastrointestinal illness (AGI)] for individuals exposed to spray-irrigated dairy manure containing Campylobacter jejuni, enterohemorrhagic Escherichia coli (EHEC), or Salmonella spp. RESULTS: Median risk estimates from Monte Carlo simulations ranged from 10−5 to 10−2 and decreased with distance from the source. Risk estimates for Salmonella or EHEC-related AGI were most sensitive to the assumed level of pathogen prevalence in dairy manure, while risk estimates for C. jejuni were not sensitive to any single variable. Airborne microbe concentrations were negatively associated with distance and positively associated with wind speed, both of which were retained in models as a significant predictor more often than relative humidity, solar irradiation, or temperature. CONCLUSIONS: Our model-based estimates suggest that reducing pathogen prevalence and concentration in source manure would reduce the risk of AGI from exposure to manure irrigation, and that increasing the distance from irrigated manure (i.e., setbacks) and limiting irrigation to times of low wind speed may also reduce risk.

Applying an Inverse Model to Estimate Ammonia Emissions at Cattle Feedlots Using Three Different Observation-Based Approaches

NASA Astrophysics Data System (ADS)

Shonkwiler, K. B.; Ham, J. M.; Nash, C.

2014-12-01

Accurately quantifying emissions of ammonia (NH3) from confined animal feeding operations (CAFOs) is vital not only to the livestock industry, but essential to understanding nitrogen cycling along the Front Range of Colorado, USA, where intensive agriculture, urban sprawl, and pristine ecosystems (e.g., Rocky Mtn Nat'l Park) lie within 100-km of each other. Most observation-based techniques for estimating NH3 emissions can be expensive and highly technical. Many methods rely on concentration observations on location, which implicitly depends on weather conditions. A system for sampling NH3 using on-site weather data was developed to allow remote measurement of NH3 in a simple, cost-effective way. These systems use passive diffusive cartridges (Radiello, Sigma-Aldrich) that provide time-averaged concentrations representative of a typical two-week deployment. Cartridge exposure is robotically managed so they are only visible when winds are 1.4 m/s or greater from the direction of the CAFO. These concentration data can be coupled with stability parameters (measured on-site) in a simple inverse model to estimate emissions (FIDES, UMR Environnement et Grandes Cultures). Few studies have directly compared emissions estimates of NH3 using concentration data obtained from multiple measurement systems at different temporal and spatial scales. Therefore, in the summer and autumn of 2014, several conditional sampler systems were deployed at a 25,000-head cattle feedlot concomitant with an open-path infrared laser (GasFinder2, Boreal Laser Inc.) and a Cavity Ring Down Spectrometer (CRDS) (G1103, Picarro Inc.) which each measured instantaneous NH3 concentrations. This study will test the sampler technology by first comparing concentration data from the three different methods. In livestock research, it is common to estimate NH3 emissions by using such instantaneous data in a backward Lagrangian stochastic (bLs) model (WindTrax, Thunder Beach Sci.) Considering this, NH3 fluxes from the inverse model (FIDES) using all three datasets will be compared to emissions from the bLS model (WindTrax) using only high speed data (laser; CRDS). Results may lend further validity to the conditional sampler approach for more easily and accurately monitoring NH3 fluxes from CAFOs and other strong areal sources.

An Investigation of Widespread Ozone Damage to the Soybean Crop in the Upper Midwest Determined From Ground-Based and Satellite Measurements

NASA Technical Reports Server (NTRS)

Fishman, Jack; Creilson, John K.; Parker, Peter A.; Ainsworth, Elizabeth A.; Vining, G. Geoffrey; Szarka, John; Booker, Fitzgerald L.; Xu, Xiaojing

2010-01-01

Elevated concentrations of ground-level ozone (O3) are frequently measured over farmland regions in many parts of the world. While numerous experimental studies show that O3 can significantly decrease crop productivity, independent verifications of yield losses at current ambient O3 concentrations in rural locations are sparse. In this study, soybean crop yield data during a 5-year period over the Midwest of the United States were combined with ground and satellite O3 measurements to provide evidence that yield losses on the order of 10% could be estimated through the use of a multiple linear regression model. Yield loss trends based on both conventional ground-based instrumentation and satellite-derived tropospheric O3 measurements were statistically significant and were consistent with results obtained from open-top chamber experiments and an open-air experimental facility (SoyFACE, Soybean Free Air Concentration Enrichment) in central Illinois. Our analysis suggests that such losses are a relatively new phenomenon due to the increase in background tropospheric O3 levels over recent decades. Extrapolation of these findings supports previous studies that estimate the global economic loss to the farming community of more than $10 billion annually.

Risk-Based Consumption Advice for Farmed Atlantic and Wild Pacific Salmon Contaminated with Dioxins and Dioxin-like Compounds

PubMed Central

Foran, Jeffery A.; Carpenter, David O.; Hamilton, M. Coreen; Knuth, Barbara A.; Schwager, Steven J.

2005-01-01

We reported recently that several organic contaminants occurred at elevated concentrations in farmed Atlantic salmon compared with concentrations of the same contaminants in wild Pacific salmon [Hites et al. Science 303:226–229 (2004)]. We also found that polychlorinated biphenyls (PCBs), toxaphene, dieldrin, dioxins, and polybrominated diphenyl ethers occurred at higher concentrations in European farm-raised salmon than in farmed salmon from North and South America. Health risks (based on a quantitative cancer risk assessment) associated with consumption of farmed salmon contaminated with PCBs, toxaphene, and dieldrin were higher than risks associated with exposure to the same contaminants in wild salmon. Here we present information on cancer and noncancer health risks of exposure to dioxins in farmed and wild salmon. The analysis is based on a tolerable intake level for dioxin-like compounds established by the World Health Organization and on risk estimates for human exposure to dioxins developed by the U.S. Environmental Protection Agency. Consumption of farmed salmon at relatively low frequencies results in elevated exposure to dioxins and dioxin-like compounds with commensurate elevation in estimates of health risk. PMID:15866762

New closed-form approximation for skin chromophore mapping.

PubMed

Välisuo, Petri; Kaartinen, Ilkka; Tuchin, Valery; Alander, Jarmo

2011-04-01

The concentrations of blood and melanin in skin can be estimated based on the reflectance of light. Many models for this estimation have been built, such as Monte Carlo simulation, diffusion models, and the differential modified Beer-Lambert law. The optimization-based methods are too slow for chromophore mapping of high-resolution spectral images, and the differential modified Beer-Lambert is not often accurate enough. Optimal coefficients for the differential Beer-Lambert model are calculated by differentiating the diffusion model, optimized to the normal skin spectrum. The derivatives are then used in predicting the difference in chromophore concentrations from the difference in absorption spectra. The accuracy of the method is tested both computationally and experimentally using a Monte Carlo multilayer simulation model, and the data are measured from the palm of a hand during an Allen's test, which modulates the blood content of skin. The correlations of the given and predicted blood, melanin, and oxygen saturation levels are correspondingly r = 0.94, r = 0.99, and r = 0.73. The prediction of the concentrations for all pixels in a 1-megapixel image would take ∼ 20 min, which is orders of magnitude faster than the methods based on optimization during the prediction.

Estimates of late middle Eocene pCO2 based on stomatal density of modern and fossil Nageia leaves

NASA Astrophysics Data System (ADS)

Liu, X. Y.; Gao, Q.; Han, M.; Jin, J. H.

2016-02-01

Atmospheric pCO2 concentrations have been estimated for intervals of the Eocene using various models and proxy information. Here we reconstruct late middle Eocene (42.0-38.5 Ma) pCO2 based on the fossil leaves of Nageia maomingensis Jin et Liu collected from the Maoming Basin, Guangdong Province, China. We first determine relationships between atmospheric pCO2 concentrations, stomatal density (SD) and stomatal index (SI) using "modern" leaves of N. motleyi (Parl.) De Laub, the nearest living species to the Eocene fossils. This work indicates that the SD inversely responds to pCO2, while SI has almost no relationship with pCO2. Eocene pCO2 concentrations can be reconstructed based on a regression approach and the stomatal ratio method by using the SD. The first approach gives a pCO2 of 351.9 ± 6.6 ppmv, whereas the one based on stomatal ratio gives a pCO2 of 537.5 ± 56.5 ppmv. Here, we explored the potential of N. maomingensis in pCO2 reconstruction and obtained different results according to different methods, providing a new insight for the reconstruction of paleoclimate and paleoenvironment in conifers.

Uncertainty Of Stream Nutrient Transport Estimates Using Random Sampling Of Storm Events From High Resolution Water Quality And Discharge Data

NASA Astrophysics Data System (ADS)

Scholefield, P. A.; Arnscheidt, J.; Jordan, P.; Beven, K.; Heathwaite, L.

2007-12-01

The uncertainties associated with stream nutrient transport estimates are frequently overlooked and the sampling strategy is rarely if ever investigated. Indeed, the impact of sampling strategy and estimation method on the bias and precision of stream phosphorus (P) transport calculations is little understood despite the use of such values in the calibration and testing of models of phosphorus transport. The objectives of this research were to investigate the variability and uncertainty in the estimates of total phosphorus transfers at an intensively monitored agricultural catchment. The Oona Water which is located in the Irish border region, is part of a long term monitoring program focusing on water quality. The Oona Water is a rural river catchment with grassland agriculture and scattered dwelling houses and has been monitored for total phosphorus (TP) at 10 min resolution for several years (Jordan et al, 2007). Concurrent sensitive measurements of discharge are also collected. The water quality and discharge data were provided at 1 hour resolution (averaged) and this meant that a robust estimate of the annual flow weighted concentration could be obtained by simple interpolation between points. A two-strata approach (Kronvang and Bruhn, 1996) was used to estimate flow weighted concentrations using randomly sampled storm events from the 400 identified within the time series and also base flow concentrations. Using a random stratified sampling approach for the selection of events, a series ranging from 10 through to the full 400 were used, each time generating a flow weighted mean using a load-discharge relationship identified through log-log regression and monte-carlo simulation. These values were then compared to the observed total phosphorus concentration for the catchment. Analysis of these results show the impact of sampling strategy, the inherent bias in any estimate of phosphorus concentrations and the uncertainty associated with such estimates. The estimates generated using the full time series underestimate the flow weighted mean concentration of total phosphorus. This work compliments other contemporary work in the area of load estimation uncertainty in the UK (Johnes, 2007). Johnes P,J. 2007, Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density, Journal of hydrology 332 (1- 2): 241-258 Jordan, P., Arnscheidt, J., McGrogan, H & McCormick, S., 2007. Characterising phosphorus transfers in rural transfers using a continuous bank-side analyser. Hydrology and Earth System Science 11, 372-381 Kronvang B & Bruhn, A. J, 1996. Choice of sampling strategy and estimation method for calculating nitrogen and phosphorus transport in small lowland streams , Hydrological processes 10 (11): 1483-1501

Characterizing toxicity of metal-contaminated sediments from mining areas

USGS Publications Warehouse

Besser, John M.; Brumbaugh, William G.; Ingersoll, Christopher G.

2015-01-01

This paper reviews methods for testing the toxicity of metals associated with freshwater sediments, linking toxic effects with metal exposure and bioavailability, and developing sediment quality guidelines. The most broadly applicable approach for characterizing metal toxicity is whole-sediment toxicity testing, which attempts to simulate natural exposure conditions in the laboratory. Standard methods for whole-sediment testing can be adapted to test a wide variety of taxa. Chronic sediment tests that characterize effects on multiple endpoints (e.g., survival, growth, and reproduction) can be highly sensitive indicators of adverse effects on resident invertebrate taxa. Methods for testing of aqueous phases (pore water, overlying water, or elutriates) are used less frequently. Analysis of sediment toxicity data focuses on statistical comparisons between responses in sediments from the study area and responses in one or more uncontaminated reference sediments. For large or complex study areas, a greater number of reference sediments is recommended to reliably define the normal range of responses in uncontaminated sediments – the ‘reference envelope’. Data on metal concentrations and effects on test organisms across a gradient of contamination may allow development of concentration-response models, which estimate metal concentrations associated with specified levels of toxic effects (e.g. 20% effect concentration or EC20). Comparisons of toxic effects in laboratory tests with measures of impacts on resident benthic invertebrate communities can help document causal relationships between metal contamination and biological effects. Total or total-recoverable metal concentrations in sediments are the most common measure of metal contamination in sediments, but metal concentrations in labile sediment fractions (e.g., determined as part of selective sediment extraction protocols) may better represent metal bioavailability. Metals released by the weak-acid extraction of acid-volatile sulfide (AVS), termed simultaneously-extracted metals (SEM), are widely used to estimate the ‘potentially-bioavailable’ fraction of metals that is not bound to sulfides (i.e., SEM-AVS). Metal concentrations in pore water are widely considered to be direct measures of metal bioavailability, and predictions of toxicity based on pore-water metal concentrations may be further improved by modeling interactions of metals with other pore-water constituents using Biotic Ligand Models. Data from sediment toxicity tests and metal analyses has provided the basis for development of sediment quality guidelines, which estimate thresholds for toxicity of metals in sediments. Empirical guidelines such as Probable Effects Concentrations or (PECs) are based on associations between sediment metal concentrations and occurrence of toxic effects in large datasets. PECs do not model bioavailable metals, but they can be used to estimate the toxicity of metal mixtures using by calculation of probable effect quotients (PEQ = sediment metal concentration/PEC). In contrast, mechanistic guidelines, such as Equilibrium Partitioning Sediment Benchmarks (ESBs) attempt to predict both bioavailability and mixture toxicity. Application of these simple bioavailability models requires more extensive chemical characterization of sediments or pore water, compared to empirical guidelines, but may provide more reliable estimates of metal toxicity across a wide range of sediment types.

E-FAST-Exposure and Fate Assessment Screening Tool Version 2014

EPA Pesticide Factsheets

E-FAST estimates potential exposures to the general population and surface water concentrations based on releases from industrial operations and basic physical-chemical properties and fate parameters of the substance

A simulation of air pollution model parameter estimation using data from a ground-based LIDAR remote sensor

NASA Technical Reports Server (NTRS)

Kibler, J. F.; Suttles, J. T.

1977-01-01

One way to obtain estimates of the unknown parameters in a pollution dispersion model is to compare the model predictions with remotely sensed air quality data. A ground-based LIDAR sensor provides relative pollution concentration measurements as a function of space and time. The measured sensor data are compared with the dispersion model output through a numerical estimation procedure to yield parameter estimates which best fit the data. This overall process is tested in a computer simulation to study the effects of various measurement strategies. Such a simulation is useful prior to a field measurement exercise to maximize the information content in the collected data. Parametric studies of simulated data matched to a Gaussian plume dispersion model indicate the trade offs available between estimation accuracy and data acquisition strategy.

Application of Acoustic and Optic Methods for Estimating Suspended-Solids Concentrations in the St. Lucie River Estuary, Florida

USGS Publications Warehouse

Patino, Eduardo; Byrne, Michael J.

2004-01-01

Acoustic and optic methods were applied to estimate suspended-solids concentrations in the St. Lucie River Estuary, southeastern Florida. Acoustic Doppler velocity meters were installed at the North Fork, Speedy Point, and Steele Point sites within the estuary. These sites provide varying flow, salinity, water-quality, and channel cross-sectional characteristics. The monitoring site at Steele Point was not used in the analyses because repeated instrument relocations (due to bridge construction) prevented a sufficient number of samples from being collected at the various locations. Acoustic and optic instruments were installed to collect water velocity, acoustic backscatter strength (ABS), and turbidity data that were used to assess the feasibility of estimating suspended-solids concentrations in the estuary. Other data collected at the monitoring sites include tidal stage, salinity, temperature, and periodic discharge measurements. Regression analyses were used to determine the relations of suspended-solids concentration to ABS and suspended-solids concentration to turbidity at the North Fork and Speedy Point sites. For samples used in regression analyses, measured suspended-solids concentrations at the North Fork and Speedy Point sites ranged from 3 to 37 milligrams per liter, and organic content ranged from 50 to 83 percent. Corresponding salinity for these samples ranged from 0.12 to 22.7 parts per thousand, and corresponding temperature ranged from 19.4 to 31.8 ?C. Relations determined using this technique are site specific and only describe suspended-solids concentrations at locations where data were collected. The suspended-solids concentration to ABS relation resulted in correlation coefficients of 0.78 and 0.63 at the North Fork and Speedy Point sites, respectively. The suspended-solids concentration to turbidity relation resulted in correlation coefficients of 0.73 and 0.89 at the North Fork and Speedy Point sites, respectively. The adequacy of the empirical equations seems to be limited by the number and distribution of suspended-solids samples collected throughout the expected concentration range at the North Fork and Speedy Point sites. Additionally, the ABS relations for both sites seem to overestimate at the low end and underestimate at the high end of the concentration range. Based on the sensitivity analysis, temperature had a greater effect than salinity on estimated suspended-solids concentrations. Temperature also appeared to affect ABS data, perhaps by changing the absorptive and reflective characteristics of the suspended material. Salinity and temperature had no observed effects on the turbidity relation at the North Fork and Speedy Point sites. Estimates of suspended-solids concentrations using ABS data were less 'erratic' than estimates using turbidity data. Combining ABS and turbidity data into one equation did not improve the accuracy of results, and therefore, was not considered.

Polar ice magnetization: Comparison of results from NorthGRIP (Greenland) and Vostok (Antarctica) ice cores

NASA Astrophysics Data System (ADS)

Lanci, L.; Kent, D. V.

2007-12-01

Low temperature measurements of isothermal remanent magnetization (IRM) in Greenland ice spanning the last glacial and Holocene have shown that ice samples contain a measurable concentration of magnetic minerals which are part of the atmospheric aerosol. Assuming that the source materials do not change much with time, the concentration of magnetic minerals should be proportional to the measured concentration of dust in ice. We have indeed found a consistent linear relationship with the contents of dust. However, the linear relationship between low temperature ice magnetization vs. dust concentration has an offset, which when extrapolated to zero dust concentration would seemingly indicate that a significantly large magnetization corresponds to a null amount of dust in ice. Thermal relaxation experiments have shown that magnetic grains of nanometric size carry virtually all the uncorrelated magnetization. Magnetic measurements in Antarctic ice cores confirm the existence of a similar nanometric-size magnetic fraction, which also appear uncorrelated with measured aerosol concentration. The magnitude of the uncorrelated magnetization from Vostok is similar to that measured in NorthGRIP ice. Measurements of IRM at 250K suggest that the SP magnetic particles are in the size range of about 7-17 nm, which is compatible with the expected size of particles produced by ablation and subsequent condensation of meteorites in the atmosphere. The concentration of extraterrestrial material in NorthGRIP ice was estimated from the magnetic relaxation data based on a crude estimate of chondritic Ms. The resulting concentration of 0.78±0.22 ppb for Greenland is in good agreement with the outcome based on published iridium concentrations; a virtually identical concentration of 0.53±0.18 ppb has been measured in Vostok ice core.

A hybrid model for predicting carbon monoxide from vehicular exhausts in urban environments

NASA Astrophysics Data System (ADS)

Gokhale, Sharad; Khare, Mukesh

Several deterministic-based air quality models evaluate and predict the frequently occurring pollutant concentration well but, in general, are incapable of predicting the 'extreme' concentrations. In contrast, the statistical distribution models overcome the above limitation of the deterministic models and predict the 'extreme' concentrations. However, the environmental damages are caused by both extremes as well as by the sustained average concentration of pollutants. Hence, the model should predict not only 'extreme' ranges but also the 'middle' ranges of pollutant concentrations, i.e. the entire range. Hybrid modelling is one of the techniques that estimates/predicts the 'entire range' of the distribution of pollutant concentrations by combining the deterministic based models with suitable statistical distribution models ( Jakeman, et al., 1988). In the present paper, a hybrid model has been developed to predict the carbon monoxide (CO) concentration distributions at one of the traffic intersections, Income Tax Office (ITO), in the Delhi city, where the traffic is heterogeneous in nature and meteorology is 'tropical'. The model combines the general finite line source model (GFLSM) as its deterministic, and log logistic distribution (LLD) model, as its statistical components. The hybrid (GFLSM-LLD) model is then applied at the ITO intersection. The results show that the hybrid model predictions match with that of the observed CO concentration data within the 5-99 percentiles range. The model is further validated at different street location, i.e. Sirifort roadway. The validation results show that the model predicts CO concentrations fairly well ( d=0.91) in 10-95 percentiles range. The regulatory compliance is also developed to estimate the probability of exceedance of hourly CO concentration beyond the National Ambient Air Quality Standards (NAAQS) of India. It consists of light vehicles, heavy vehicles, three- wheelers (auto rickshaws) and two-wheelers (scooters, motorcycles, etc).

A PHYSIOLOGICALLY BASED PHARMACOKINETIC/PHARMACODYNAMIC (PBPK/PD) MODEL FOR ESTIMATION OF CUMULATIVE RISK FROM EXPOSURE TO THREE N-METHYL CARBAMATES: CARBARYL, ALDICARB, AND CARBOFURAN

EPA Science Inventory

A physiologically-based pharmacokinetic (PBPK) model for a mixture of N-methyl carbamate pesticides was developed based on single chemical models. The model was used to compare urinary metabolite concentrations to levels from National Health and Nutrition Examination Survey (NHA...

A Triple Functional Approach To Simultaneously Determine the Type, Concentration, and Size of Titanium Dioxide Particles.

PubMed

Zhao, Bin; Yang, Tianxi; Zhang, Zhiyun; Hickey, Michael E; He, Lili

2018-03-06

The large-scale manufacturing and use of titanium dioxide (TiO 2 ) particles in food and consumer products significantly increase the likelihood of human exposure and release into the environment. We present a simple and innovative approach to rapidly identify the type (anatase or rutile), as well as to estimate, the size and concentration of TiO 2 particles using Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS). The identification and discrimination of rutile and anatase were based on their intrinsic Raman signatures. The concentration of the TiO 2 particles was determined based on Raman peak intensity. Particle sizes were estimated based on the ratio between the Raman intensity of TiO 2 and the SERS intensity of myricetin bound to the nanoparticles (NPs), which was proven to be independent of TiO 2 nanoparticle concentrations. The ratio that was calculated from the 100 nm particles was used as a cutoff value when estimating the presence of nanosized particles within a mixture. We also demonstrated the practical use of this approach when determining the type, concentration, and size of E171: a mixture that contains TiO 2 particles of various sizes which are commonly used in many food products as food additives. The presence of TiO 2 anatase NPs in E171 was confirmed using the developed approach and was validated by transmission electron micrographs. TiO 2 presence in pond water was also demonstrated to be an analytical capability of this method. Our approach shows great promise for the rapid screening of nanosized rutile and anatase TiO 2 particles in complex matrixes. This approach will strongly improve the measurement of TiO 2 quality during production, as well as the survey capacity and risk assessment of TiO 2 NPs in food, consumer goods, and environmental samples.

Estimating sediment discharge: Appendix D

USGS Publications Warehouse

Gray, John R.; Simões, Francisco J. M.

2008-01-01

Sediment-discharge measurements usually are available on a discrete or periodic basis. However, estimates of sediment transport often are needed for unmeasured periods, such as when daily or annual sediment-discharge values are sought, or when estimates of transport rates for unmeasured or hypothetical flows are required. Selected methods for estimating suspended-sediment, bed-load, bed- material-load, and total-load discharges have been presented in some detail elsewhere in this volume. The purposes of this contribution are to present some limitations and potential pitfalls associated with obtaining and using the requisite data and equations to estimate sediment discharges and to provide guidance for selecting appropriate estimating equations. Records of sediment discharge are derived from data collected with sufficient frequency to obtain reliable estimates for the computational interval and period. Most sediment- discharge records are computed at daily or annual intervals based on periodically collected data, although some partial records represent discrete or seasonal intervals such as those for flood periods. The method used to calculate sediment- discharge records is dependent on the types and frequency of available data. Records for suspended-sediment discharge computed by methods described by Porterfield (1972) are most prevalent, in part because measurement protocols and computational techniques are well established and because suspended sediment composes the bulk of sediment dis- charges for many rivers. Discharge records for bed load, total load, or in some cases bed-material load plus wash load are less common. Reliable estimation of sediment discharges presupposes that the data on which the estimates are based are comparable and reliable. Unfortunately, data describing a selected characteristic of sediment were not necessarily derived—collected, processed, analyzed, or interpreted—in a consistent manner. For example, bed-load data collected with different types of bed-load samplers may not be comparable (Gray et al. 1991; Childers 1999; Edwards and Glysson 1999). The total suspended solids (TSS) analytical method tends to produce concentration data from open-channel flows that are biased low with respect to their paired suspended-sediment concentration values, particularly when sand-size material composes more than about a quarter of the material in suspension. Instantaneous sediment-discharge values based on TSS data may differ from the more reliable product of suspended- sediment concentration values and the same water-discharge data by an order of magnitude (Gray et al. 2000; Bent et al. 2001; Glysson et al. 2000; 2001). An assessment of data comparability and reliability is an important first step in the estimation of sediment discharges. There are two approaches to obtaining values describing sediment loads in streams. One is based on direct measurement of the quantities of interest, and the other on relations developed between hydraulic parameters and sediment- transport potential. In the next sections, the most common techniques for both approaches are briefly addressed.

An evaluation of methods for estimating decadal stream loads

NASA Astrophysics Data System (ADS)

Lee, Casey J.; Hirsch, Robert M.; Schwarz, Gregory E.; Holtschlag, David J.; Preston, Stephen D.; Crawford, Charles G.; Vecchia, Aldo V.

2016-11-01

Effective management of water resources requires accurate information on the mass, or load of water-quality constituents transported from upstream watersheds to downstream receiving waters. Despite this need, no single method has been shown to consistently provide accurate load estimates among different water-quality constituents, sampling sites, and sampling regimes. We evaluate the accuracy of several load estimation methods across a broad range of sampling and environmental conditions. This analysis uses random sub-samples drawn from temporally-dense data sets of total nitrogen, total phosphorus, nitrate, and suspended-sediment concentration, and includes measurements of specific conductance which was used as a surrogate for dissolved solids concentration. Methods considered include linear interpolation and ratio estimators, regression-based methods historically employed by the U.S. Geological Survey, and newer flexible techniques including Weighted Regressions on Time, Season, and Discharge (WRTDS) and a generalized non-linear additive model. No single method is identified to have the greatest accuracy across all constituents, sites, and sampling scenarios. Most methods provide accurate estimates of specific conductance (used as a surrogate for total dissolved solids or specific major ions) and total nitrogen - lower accuracy is observed for the estimation of nitrate, total phosphorus and suspended sediment loads. Methods that allow for flexibility in the relation between concentration and flow conditions, specifically Beale's ratio estimator and WRTDS, exhibit greater estimation accuracy and lower bias. Evaluation of methods across simulated sampling scenarios indicate that (1) high-flow sampling is necessary to produce accurate load estimates, (2) extrapolation of sample data through time or across more extreme flow conditions reduces load estimate accuracy, and (3) WRTDS and methods that use a Kalman filter or smoothing to correct for departures between individual modeled and observed values benefit most from more frequent water-quality sampling.

An evaluation of methods for estimating decadal stream loads

USGS Publications Warehouse

Lee, Casey; Hirsch, Robert M.; Schwarz, Gregory E.; Holtschlag, David J.; Preston, Stephen D.; Crawford, Charles G.; Vecchia, Aldo V.

2016-01-01

Effective management of water resources requires accurate information on the mass, or load of water-quality constituents transported from upstream watersheds to downstream receiving waters. Despite this need, no single method has been shown to consistently provide accurate load estimates among different water-quality constituents, sampling sites, and sampling regimes. We evaluate the accuracy of several load estimation methods across a broad range of sampling and environmental conditions. This analysis uses random sub-samples drawn from temporally-dense data sets of total nitrogen, total phosphorus, nitrate, and suspended-sediment concentration, and includes measurements of specific conductance which was used as a surrogate for dissolved solids concentration. Methods considered include linear interpolation and ratio estimators, regression-based methods historically employed by the U.S. Geological Survey, and newer flexible techniques including Weighted Regressions on Time, Season, and Discharge (WRTDS) and a generalized non-linear additive model. No single method is identified to have the greatest accuracy across all constituents, sites, and sampling scenarios. Most methods provide accurate estimates of specific conductance (used as a surrogate for total dissolved solids or specific major ions) and total nitrogen – lower accuracy is observed for the estimation of nitrate, total phosphorus and suspended sediment loads. Methods that allow for flexibility in the relation between concentration and flow conditions, specifically Beale’s ratio estimator and WRTDS, exhibit greater estimation accuracy and lower bias. Evaluation of methods across simulated sampling scenarios indicate that (1) high-flow sampling is necessary to produce accurate load estimates, (2) extrapolation of sample data through time or across more extreme flow conditions reduces load estimate accuracy, and (3) WRTDS and methods that use a Kalman filter or smoothing to correct for departures between individual modeled and observed values benefit most from more frequent water-quality sampling.

Comparison of the radiological and chemical toxicity of lead

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beitel, G.A.; Mott, S.

1995-03-01

This report estimates the worst-case radiological dose to an individual from ingested lead containing picocurie levels of radionuclides and then compares the calculated radiological health effects to the chemical toxic effects from that same lead. This comparison provides an estimate of the consequences of inadvertently recycling, in the commercial market, lead containing nominally undetectable concentrations of radionuclides. Quantitative expressions for the radiological and chemical toxicities of lead are based on concentrations of lead in the blood stream. The result shows that the chemical toxicity of lead is a greater health hazard, by orders of magnitude, than any probable companion radiationmore » dose.« less

Environmental DNA as a ‘Snapshot’ of Fish Distribution: A Case Study of Japanese Jack Mackerel in Maizuru Bay, Sea of Japan

PubMed Central

Takahashi, Kohji; Sawada, Hideki; Murakami, Hiroaki; Tsuji, Satsuki; Hashizume, Hiroki; Kubonaga, Shou; Horiuchi, Tomoya; Hongo, Masamichi; Nishida, Jo; Okugawa, Yuta; Fujiwara, Ayaka; Fukuda, Miho; Hidaka, Shunsuke; Suzuki, Keita W.; Miya, Masaki; Araki, Hitoshi; Yamanaka, Hiroki; Maruyama, Atsushi; Miyashita, Kazushi; Masuda, Reiji; Minamoto, Toshifumi; Kondoh, Michio

2016-01-01

Recent studies in streams and ponds have demonstrated that the distribution and biomass of aquatic organisms can be estimated by detection and quantification of environmental DNA (eDNA). In more open systems such as seas, it is not evident whether eDNA can represent the distribution and biomass of aquatic organisms because various environmental factors (e.g., water flow) are expected to affect eDNA distribution and concentration. To test the relationships between the distribution of fish and eDNA, we conducted a grid survey in Maizuru Bay, Sea of Japan, and sampled surface and bottom waters while monitoring biomass of the Japanese jack mackerel (Trachurus japonicus) using echo sounder technology. A linear model showed a high R2 value (0.665) without outlier data points, and the association between estimated eDNA concentrations from the surface water samples and echo intensity was significantly positive, suggesting that the estimated spatial variation in eDNA concentration can reflect the local biomass of the jack mackerel. We also found that a best-fit model included echo intensity obtained within 10–150 m from water sampling sites, indicating that the estimated eDNA concentration most likely reflects fish biomass within 150 m in the bay. Although eDNA from a wholesale fish market partially affected eDNA concentration, we conclude that eDNA generally provides a ‘snapshot’ of fish distribution and biomass in a large area. Further studies in which dynamics of eDNA under field conditions (e.g., patterns of release, degradation, and diffusion of eDNA) are taken into account will provide a better estimate of fish distribution and biomass based on eDNA. PMID:26933889

Application of physiologically based pharmacokinetic (PBPK) model of trichloroethylene in rats for estimation of internal dose

EPA Science Inventory

Potential human health risk from chemical exposure must often be assessed for conditions for which suitable human or animal data are not available, requiring extrapolation across duration and concentration. The default method for exposure-duration adjustment is based on Haber's r...

Estimating lake susceptibility to acidification due to acid deposition.

Treesearch

Dale S. Nichols

1990-01-01

Presents a graphical procedure for evaluating the same sensitivity of lakes to acidification due to acid deposition. The procedure is based on empirical relationships between sulfur (and in some cases nitrogen) deposition rates and lake pH, acid-neutralizing capacity, base cation concentrations, and the amount of runoff.

Estimation of plant protection product application dates for environmental fate modeling based on phenological stages of crops.

PubMed

Gericke, Dirk; Nekovar, Jiri; Horold, Claudia

2010-10-01

According to the EU directive 91/414/EEC potential environmental concentrations of pesticides have to be assessed with environmental fate models. For the calculation of pesticide concentrations it is necessary to provide an application date which has to match the specific Biologische Bundesanstalt, Bundesamt, Chemische Industrie (BBCH) stage at which the pesticide shall be applied. If these application dates are not available for a specific stage, crop and country they must be estimated, which adds an additional uncertainty to the predicted concentrations. In the present study, we therefore evaluate to which extent application dates can be derived from phenological data. For this analysis phenological data, converted to BBCH stages, of two field crops provided by the German Weather Service (DWD) were analyzed. We found a linear correlation between BBCH stages and the respective appearance dates, which can be used for interpolation of appearance dates of specific BBCH stages. Remarkably, when comparing BBCH stages from Germany and the Czech Republic almost identical correlations of appearance dates and BBCH stages were found. In the next step, soil and climate data from Joint Research Centre (JRC) were analyzed together with phenological data in order to evaluate if BBCH stages can be estimated for countries with other climate or soil conditions. This analysis revealed that temperature, global radiation and evaporation were the parameters with the strongest impact. These parameters were used for estimating appearance dates of BBCH stages for other countries. Exemplarily, appearance dates for maize BBCH were calculated for Italy. Estimated and observed appearance dates showed a high concordance (on average six days difference). Finally, the political of impact a variation of a few days on calculated pesticide concentration was analyzed. Exemplarily, the pesticide fate model FOCUS PEARL was used to estimate pesticide groundwater concentrations. When calculating concentrations for application dates varying by ± two weeks, concentrations in groundwater usually varied very little. The highest variation was found for application at BBCH 30 in maize (6.6 % variation over all scenarios). These results showed that the uncertainty included in the estimation of appearance dates of BBCH stages for other countries has a relatively small effect on the results of PEARL and consequentially on the decision of the pesticide risk assessment by changing only the application date.

Probabilistic risk model for staphylococcal intoxication from pork-based food dishes prepared in food service establishments in Korea.

PubMed

Kim, Hyun Jung; Griffiths, Mansel W; Fazil, Aamir M; Lammerding, Anna M

2009-09-01

Foodborne illness contracted at food service operations is an important public health issue in Korea. In this study, the probabilities for growth of, and enterotoxin production by, Staphylococcus aureus in pork meat-based foods prepared in food service operations were estimated by the Monte Carlo simulation. Data on the prevalence and concentration of S. aureus as well as compliance to guidelines for time and temperature controls during food service operations were collected. The growth of S. aureus was initially estimated by using the U.S. Department of Agriculture's Pathogen Modeling Program. A second model based on raw pork meat was derived to compare cell number predictions. The correlation between toxin level and cell number as well as minimum toxin dose obtained from published data was adopted to quantify the probability of staphylococcal intoxication. When data gaps were found, assumptions were made based on guidelines for food service practices. Baseline risk model and scenario analyses were performed to indicate possible outcomes of staphylococcal intoxication under the scenarios generated based on these data gaps. Staphylococcal growth was predicted during holding before and after cooking, and the highest estimated concentration (4.59 log CFU/g for the 99.9th percentile value) of S. aureus was observed in raw pork initially contaminated with S. aureus and held before cooking. The estimated probability for staphylococcal intoxication was very low, using currently available data. However, scenario analyses revealed an increased possibility of staphylococcal intoxication when increased levels of initial contamination in the raw meat, andlonger holding time both before and after cooking the meat occurred.

Real-world automotive particulate matter and PAH emission factors and profile concentrations: Results from an urban tunnel experiment in Naples, Italy

NASA Astrophysics Data System (ADS)

Riccio, A.; Chianese, E.; Monaco, D.; Costagliola, M. A.; Perretta, G.; Prati, M. V.; Agrillo, G.; Esposito, A.; Gasbarra, D.; Shindler, L.; Brusasca, G.; Nanni, A.; Pozzi, C.; Magliulo, V.

2016-09-01

On-road particulate matter (PM) mass was measured during a sampling campaign in March of 2015 in the '4 giornate' tunnel in Naples, Italy. Two sets of samples were collected at both sides of the tunnel, each set representing the daily cycle at a 1 h time resolution. Distance-based - mass per kilometer - and fuel-based - mass per burned fuel - emission factors (EFs) were calculated using mass concentrations, traffic flow rates and wind speed as a function of fleet composition. Also, chemical analyses were performed for polycyclic aromatic hydrocarbons (PAHs). Due to the high traffic volume, particle mass concentration at the tunnel exit was always significantly elevated relative to entrance concentration; depending on the hour of the day, PM10 concentration ranged between 300 μg/m3, during the early afternoon, and 600 μg/m3 during rush hours at the tunnel exit. Correspondingly, PAHs achieved concentrations as high as 1450 ng/m3, and benzo(a)pyrene, a surely carcinogenic compound, achieved concentrations as high as 69 ng/m3, raising serious concerns in relation to population exposure close to this urban tunnel. Distance-based and fuel-based emission factors for CO2, PM10 and PAHs were estimated, but while the EF for CO2 was within the range of expected values, the present study found much higher EFs for particulate matter and PAHs. According to the national official statistics from ISPRA (the Italian Institute for the Protection and Research on Environment), derived from the COPERT database, we expected an EF for particulate matter of about 55 mg/km, but the EF estimated from measurements taken at both sides of the tunnel was about four times higher than that expected; also, benzo(a)pyrene achieved an average EF of 2.7 μg/km, about three times higher than that expected from the ISPRA database.

Sea Ice Concentration Estimation Using Active and Passive Remote Sensing Data Fusion

NASA Astrophysics Data System (ADS)

Zhang, Y.; Li, F.; Zhang, S.; Zhu, T.

2017-12-01

In this abstract, a decision-level fusion method by utilizing SAR and passive microwave remote sensing data for sea ice concentration estimation is investigated. Sea ice concentration product from passive microwave concentration retrieval methods has large uncertainty within thin ice zone. Passive microwave data including SSM/I, AMSR-E, and AMSR-2 provide daily and long time series observations covering whole polar sea ice scene, and SAR images provide rich sea ice details with high spatial resolution including deformation and polarimetric features. In the proposed method, the merits from passive microwave data and SAR data are considered. Sea ice concentration products from ASI and sea ice category label derived from CRF framework in SAR imagery are calibrated under least distance protocol. For SAR imagery, incident angle and azimuth angle were used to correct backscattering values from slant range to ground range in order to improve geocoding accuracy. The posterior probability distribution between category label from SAR imagery and passive microwave sea ice concentration product is modeled and integrated under Bayesian network, where Gaussian statistical distribution from ASI sea ice concentration products serves as the prior term, which represented as an uncertainty of sea ice concentration. Empirical model based likelihood term is constructed under Bernoulli theory, which meets the non-negative and monotonically increasing conditions. In the posterior probability estimation procedure, final sea ice concentration is obtained using MAP criterion, which equals to minimize the cost function and it can be calculated with nonlinear iteration method. The proposed algorithm is tested on multiple satellite SAR data sets including GF-3, Sentinel-1A, RADARSAT-2 and Envisat ASAR. Results show that the proposed algorithm can improve the accuracy of ASI sea ice concentration products and reduce the uncertainty along the ice edge.

Comparative analysis of radon, thoron and thoron progeny concentration measurements.

PubMed

Janik, Miroslaw; Tokonami, Shinji; Kranrod, Chutima; Sorimachi, Atsuyuki; Ishikawa, Tetsuo; Hosoda, Masahiro; McLaughlin, James; Chang, Byung-Uck; Kim, Yong Jae

2013-07-01

This study examined correlations between radon, thoron and thoron progeny concentrations based on surveys conducted in several different countries. For this purpose, passive detectors developed or modified by the National Institute of Radiological Sciences (NIRS) were used. Radon and thoron concentrations were measured using passive discriminative radon-thoron detectors. Thoron progeny measurements were conducted using the NIRS-modified detector, originally developed by Zhuo and Iida. Weak correlations were found between radon and thoron as well as between thoron and thoron progeny. The statistical evaluation showed that attention should be paid to the thoron equilibrium factor for calculation of thoron progeny concentrations based on thoron measurements. In addition, this evaluation indicated that radon, thoron and thoron progeny were independent parameters, so it would be difficult to estimate the concentration of one from those of the others.

Comparative analysis of radon, thoron and thoron progeny concentration measurements

PubMed Central

Janik, Miroslaw; Tokonami, Shinji; Kranrod, Chutima; Sorimachi, Atsuyuki; Ishikawa, Tetsuo; Hosoda, Masahiro; Mclaughlin, James; Chang, Byung-Uck; Kim, Yong Jae

2013-01-01

This study examined correlations between radon, thoron and thoron progeny concentrations based on surveys conducted in several different countries. For this purpose, passive detectors developed or modified by the National Institute of Radiological Sciences (NIRS) were used. Radon and thoron concentrations were measured using passive discriminative radon-thoron detectors. Thoron progeny measurements were conducted using the NIRS-modified detector, originally developed by Zhuo and Iida. Weak correlations were found between radon and thoron as well as between thoron and thoron progeny. The statistical evaluation showed that attention should be paid to the thoron equilibrium factor for calculation of thoron progeny concentrations based on thoron measurements. In addition, this evaluation indicated that radon, thoron and thoron progeny were independent parameters, so it would be difficult to estimate the concentration of one from those of the others. PMID:23297318

A Calibration-Free Laser-Induced Breakdown Spectroscopy (CF-LIBS) Quantitative Analysis Method Based on the Auto-Selection of an Internal Reference Line and Optimized Estimation of Plasma Temperature.

PubMed

Yang, Jianhong; Li, Xiaomeng; Xu, Jinwu; Ma, Xianghong

2018-01-01

The quantitative analysis accuracy of calibration-free laser-induced breakdown spectroscopy (CF-LIBS) is severely affected by the self-absorption effect and estimation of plasma temperature. Herein, a CF-LIBS quantitative analysis method based on the auto-selection of internal reference line and the optimized estimation of plasma temperature is proposed. The internal reference line of each species is automatically selected from analytical lines by a programmable procedure through easily accessible parameters. Furthermore, the self-absorption effect of the internal reference line is considered during the correction procedure. To improve the analysis accuracy of CF-LIBS, the particle swarm optimization (PSO) algorithm is introduced to estimate the plasma temperature based on the calculation results from the Boltzmann plot. Thereafter, the species concentrations of a sample can be calculated according to the classical CF-LIBS method. A total of 15 certified alloy steel standard samples of known compositions and elemental weight percentages were used in the experiment. Using the proposed method, the average relative errors of Cr, Ni, and Fe calculated concentrations were 4.40%, 6.81%, and 2.29%, respectively. The quantitative results demonstrated an improvement compared with the classical CF-LIBS method and the promising potential of in situ and real-time application.

Modeling of testosterone regulation by pulse-modulated feedback: An experimental data study

NASA Astrophysics Data System (ADS)

Mattsson, Per; Medvedev, Alexander

2013-10-01

The continuous part of a hybrid (pulse-modulated) model of testosterone feedback regulation is extended with infinite-dimensional and nonlinear dynamics, to better explain the testosterone concentration profiles observed in clinical data. A linear least-squares based optimization algorithm is developed for the purpose of detecting impulses of gonadotropin-realsing hormone from measured concentration of luteinizing hormone. The parameters in the model are estimated from hormone concentration measured in human males, and simulation results from the full closed-loop system are provided.

The Model-Based Study of the Effectiveness of Reporting Lists of Small Feature Sets Using RNA-Seq Data.

PubMed

Kim, Eunji; Ivanov, Ivan; Hua, Jianping; Lampe, Johanna W; Hullar, Meredith Aj; Chapkin, Robert S; Dougherty, Edward R

2017-01-01

Ranking feature sets for phenotype classification based on gene expression is a challenging issue in cancer bioinformatics. When the number of samples is small, all feature selection algorithms are known to be unreliable, producing significant error, and error estimators suffer from different degrees of imprecision. The problem is compounded by the fact that the accuracy of classification depends on the manner in which the phenomena are transformed into data by the measurement technology. Because next-generation sequencing technologies amount to a nonlinear transformation of the actual gene or RNA concentrations, they can potentially produce less discriminative data relative to the actual gene expression levels. In this study, we compare the performance of ranking feature sets derived from a model of RNA-Seq data with that of a multivariate normal model of gene concentrations using 3 measures: (1) ranking power, (2) length of extensions, and (3) Bayes features. This is the model-based study to examine the effectiveness of reporting lists of small feature sets using RNA-Seq data and the effects of different model parameters and error estimators. The results demonstrate that the general trends of the parameter effects on the ranking power of the underlying gene concentrations are preserved in the RNA-Seq data, whereas the power of finding a good feature set becomes weaker when gene concentrations are transformed by the sequencing machine.

Runoff load estimation of particulate and dissolved nitrogen in Lake Inba watershed using continuous monitoring data on turbidity and electric conductivity.

PubMed

Kim, J; Nagano, Y; Furumai, H

2012-01-01

Easy-to-measure surrogate parameters for water quality indicators are needed for real time monitoring as well as for generating data for model calibration and validation. In this study, a novel linear regression model for estimating total nitrogen (TN) based on two surrogate parameters is proposed based on evaluation of pollutant loads flowing into a eutrophic lake. Based on their runoff characteristics during wet weather, electric conductivity (EC) and turbidity were selected as surrogates for particulate nitrogen (PN) and dissolved nitrogen (DN), respectively. Strong linear relationships were established between PN and turbidity and DN and EC, and both models subsequently combined for estimation of TN. This model was evaluated by comparison of estimated and observed TN runoff loads during rainfall events. This analysis showed that turbidity and EC are viable surrogates for PN and DN, respectively, and that the linear regression model for TN concentration was successful in estimating TN runoff loads during rainfall events and also under dry weather conditions.

Maximum a posteriori Bayesian estimation of mycophenolic Acid area under the concentration-time curve: is this clinically useful for dosage prediction yet?

PubMed

Staatz, Christine E; Tett, Susan E

2011-12-01

This review seeks to summarize the available data about Bayesian estimation of area under the plasma concentration-time curve (AUC) and dosage prediction for mycophenolic acid (MPA) and evaluate whether sufficient evidence is available for routine use of Bayesian dosage prediction in clinical practice. A literature search identified 14 studies that assessed the predictive performance of maximum a posteriori Bayesian estimation of MPA AUC and one report that retrospectively evaluated how closely dosage recommendations based on Bayesian forecasting achieved targeted MPA exposure. Studies to date have mostly been undertaken in renal transplant recipients, with limited investigation in patients treated with MPA for autoimmune disease or haematopoietic stem cell transplantation. All of these studies have involved use of the mycophenolate mofetil (MMF) formulation of MPA, rather than the enteric-coated mycophenolate sodium (EC-MPS) formulation. Bias associated with estimation of MPA AUC using Bayesian forecasting was generally less than 10%. However some difficulties with imprecision was evident, with values ranging from 4% to 34% (based on estimation involving two or more concentration measurements). Evaluation of whether MPA dosing decisions based on Bayesian forecasting (by the free website service https://pharmaco.chu-limoges.fr) achieved target drug exposure has only been undertaken once. When MMF dosage recommendations were applied by clinicians, a higher proportion (72-80%) of subsequent estimated MPA AUC values were within the 30-60 mg · h/L target range, compared with when dosage recommendations were not followed (only 39-57% within target range). Such findings provide evidence that Bayesian dosage prediction is clinically useful for achieving target MPA AUC. This study, however, was retrospective and focussed only on adult renal transplant recipients. Furthermore, in this study, Bayesian-generated AUC estimations and dosage predictions were not compared with a later full measured AUC but rather with a further AUC estimate based on a second Bayesian analysis. This study also provided some evidence that a useful monitoring schedule for MPA AUC following adult renal transplant would be every 2 weeks during the first month post-transplant, every 1-3 months between months 1 and 12, and each year thereafter. It will be interesting to see further validations in different patient groups using the free website service. In summary, the predictive performance of Bayesian estimation of MPA, comparing estimated with measured AUC values, has been reported in several studies. However, the next step of predicting dosages based on these Bayesian-estimated AUCs, and prospectively determining how closely these predicted dosages give drug exposure matching targeted AUCs, remains largely unaddressed. Further prospective studies are required, particularly in non-renal transplant patients and with the EC-MPS formulation. Other important questions remain to be answered, such as: do Bayesian forecasting methods devised to date use the best population pharmacokinetic models or most accurate algorithms; are the methods simple to use for routine clinical practice; do the algorithms actually improve dosage estimations beyond empirical recommendations in all groups that receive MPA therapy; and, importantly, do the dosage predictions, when followed, improve patient health outcomes?

Time-series analyses of air pollution and mortality in the United States: a subsampling approach.

PubMed

Moolgavkar, Suresh H; McClellan, Roger O; Dewanji, Anup; Turim, Jay; Luebeck, E Georg; Edwards, Melanie

2013-01-01

Hierarchical Bayesian methods have been used in previous papers to estimate national mean effects of air pollutants on daily deaths in time-series analyses. We obtained maximum likelihood estimates of the common national effects of the criteria pollutants on mortality based on time-series data from ≤ 108 metropolitan areas in the United States. We used a subsampling bootstrap procedure to obtain the maximum likelihood estimates and confidence bounds for common national effects of the criteria pollutants, as measured by the percentage increase in daily mortality associated with a unit increase in daily 24-hr mean pollutant concentration on the previous day, while controlling for weather and temporal trends. We considered five pollutants [PM10, ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2)] in single- and multipollutant analyses. Flexible ambient concentration-response models for the pollutant effects were considered as well. We performed limited sensitivity analyses with different degrees of freedom for time trends. In single-pollutant models, we observed significant associations of daily deaths with all pollutants. The O3 coefficient was highly sensitive to the degree of smoothing of time trends. Among the gases, SO2 and NO2 were most strongly associated with mortality. The flexible ambient concentration-response curve for O3 showed evidence of nonlinearity and a threshold at about 30 ppb. Differences between the results of our analyses and those reported from using the Bayesian approach suggest that estimates of the quantitative impact of pollutants depend on the choice of statistical approach, although results are not directly comparable because they are based on different data. In addition, the estimate of the O3-mortality coefficient depends on the amount of smoothing of time trends.

Acid–base chemical reaction model for nucleation rates in the polluted atmospheric boundary layer

PubMed Central

Chen, Modi; Titcombe, Mari; Jiang, Jingkun; Jen, Coty; Kuang, Chongai; Fischer, Marc L.; Eisele, Fred L.; Siepmann, J. Ilja; Hanson, David R.; Zhao, Jun; McMurry, Peter H.

2012-01-01

Climate models show that particles formed by nucleation can affect cloud cover and, therefore, the earth's radiation budget. Measurements worldwide show that nucleation rates in the atmospheric boundary layer are positively correlated with concentrations of sulfuric acid vapor. However, current nucleation theories do not correctly predict either the observed nucleation rates or their functional dependence on sulfuric acid concentrations. This paper develops an alternative approach for modeling nucleation rates, based on a sequence of acid–base reactions. The model uses empirical estimates of sulfuric acid evaporation rates obtained from new measurements of neutral molecular clusters. The model predicts that nucleation rates equal the sulfuric acid vapor collision rate times a prefactor that is less than unity and that depends on the concentrations of basic gaseous compounds and preexisting particles. Predicted nucleation rates and their dependence on sulfuric acid vapor concentrations are in reasonable agreement with measurements from Mexico City and Atlanta. PMID:23091030

Acid-base chemical reaction model for nucleation rates in the polluted atmospheric boundary layer.

PubMed

Chen, Modi; Titcombe, Mari; Jiang, Jingkun; Jen, Coty; Kuang, Chongai; Fischer, Marc L; Eisele, Fred L; Siepmann, J Ilja; Hanson, David R; Zhao, Jun; McMurry, Peter H

2012-11-13

Climate models show that particles formed by nucleation can affect cloud cover and, therefore, the earth's radiation budget. Measurements worldwide show that nucleation rates in the atmospheric boundary layer are positively correlated with concentrations of sulfuric acid vapor. However, current nucleation theories do not correctly predict either the observed nucleation rates or their functional dependence on sulfuric acid concentrations. This paper develops an alternative approach for modeling nucleation rates, based on a sequence of acid-base reactions. The model uses empirical estimates of sulfuric acid evaporation rates obtained from new measurements of neutral molecular clusters. The model predicts that nucleation rates equal the sulfuric acid vapor collision rate times a prefactor that is less than unity and that depends on the concentrations of basic gaseous compounds and preexisting particles. Predicted nucleation rates and their dependence on sulfuric acid vapor concentrations are in reasonable agreement with measurements from Mexico City and Atlanta.

Investigation of Aerosol Surface Area Estimation from Number and Mass Concentration Measurements: Particle Density Effect

PubMed Central

Ku, Bon Ki; Evans, Douglas E.

2015-01-01

For nanoparticles with nonspherical morphologies, e.g., open agglomerates or fibrous particles, it is expected that the actual density of agglomerates may be significantly different from the bulk material density. It is further expected that using the material density may upset the relationship between surface area and mass when a method for estimating aerosol surface area from number and mass concentrations (referred to as “Maynard’s estimation method”) is used. Therefore, it is necessary to quantitatively investigate how much the Maynard’s estimation method depends on particle morphology and density. In this study, aerosol surface area estimated from number and mass concentration measurements was evaluated and compared with values from two reference methods: a method proposed by Lall and Friedlander for agglomerates and a mobility based method for compact nonspherical particles using well-defined polydisperse aerosols with known particle densities. Polydisperse silver aerosol particles were generated by an aerosol generation facility. Generated aerosols had a range of morphologies, count median diameters (CMD) between 25 and 50 nm, and geometric standard deviations (GSD) between 1.5 and 1.8. The surface area estimates from number and mass concentration measurements correlated well with the two reference values when gravimetric mass was used. The aerosol surface area estimates from the Maynard’s estimation method were comparable to the reference method for all particle morphologies within the surface area ratios of 3.31 and 0.19 for assumed GSDs 1.5 and 1.8, respectively, when the bulk material density of silver was used. The difference between the Maynard’s estimation method and surface area measured by the reference method for fractal-like agglomerates decreased from 79% to 23% when the measured effective particle density was used, while the difference for nearly spherical particles decreased from 30% to 24%. The results indicate that the use of particle density of agglomerates improves the accuracy of the Maynard’s estimation method and that an effective density should be taken into account, when known, when estimating aerosol surface area of nonspherical aerosol such as open agglomerates and fibrous particles. PMID:26526560

Investigation of Aerosol Surface Area Estimation from Number and Mass Concentration Measurements: Particle Density Effect.

PubMed

Ku, Bon Ki; Evans, Douglas E

2012-04-01

For nanoparticles with nonspherical morphologies, e.g., open agglomerates or fibrous particles, it is expected that the actual density of agglomerates may be significantly different from the bulk material density. It is further expected that using the material density may upset the relationship between surface area and mass when a method for estimating aerosol surface area from number and mass concentrations (referred to as "Maynard's estimation method") is used. Therefore, it is necessary to quantitatively investigate how much the Maynard's estimation method depends on particle morphology and density. In this study, aerosol surface area estimated from number and mass concentration measurements was evaluated and compared with values from two reference methods: a method proposed by Lall and Friedlander for agglomerates and a mobility based method for compact nonspherical particles using well-defined polydisperse aerosols with known particle densities. Polydisperse silver aerosol particles were generated by an aerosol generation facility. Generated aerosols had a range of morphologies, count median diameters (CMD) between 25 and 50 nm, and geometric standard deviations (GSD) between 1.5 and 1.8. The surface area estimates from number and mass concentration measurements correlated well with the two reference values when gravimetric mass was used. The aerosol surface area estimates from the Maynard's estimation method were comparable to the reference method for all particle morphologies within the surface area ratios of 3.31 and 0.19 for assumed GSDs 1.5 and 1.8, respectively, when the bulk material density of silver was used. The difference between the Maynard's estimation method and surface area measured by the reference method for fractal-like agglomerates decreased from 79% to 23% when the measured effective particle density was used, while the difference for nearly spherical particles decreased from 30% to 24%. The results indicate that the use of particle density of agglomerates improves the accuracy of the Maynard's estimation method and that an effective density should be taken into account, when known, when estimating aerosol surface area of nonspherical aerosol such as open agglomerates and fibrous particles.

Field Validity and Feasibility of Four Techniques for the Detection of Trichuris in Simians: A Model for Monitoring Drug Efficacy in Public Health?

PubMed Central

Levecke, Bruno; De Wilde, Nathalie; Vandenhoute, Els; Vercruysse, Jozef

2009-01-01

Background Soil-transmitted helminths, such as Trichuris trichiura, are of major concern in public health. Current efforts to control these helminth infections involve periodic mass treatment in endemic areas. Since these large-scale interventions are likely to intensify, monitoring the drug efficacy will become indispensible. However, studies comparing detection techniques based on sensitivity, fecal egg counts (FEC), feasibility for mass diagnosis and drug efficacy estimates are scarce. Methodology/Principal Findings In the present study, the ether-based concentration, the Parasep Solvent Free (SF), the McMaster and the FLOTAC techniques were compared based on both validity and feasibility for the detection of Trichuris eggs in 100 fecal samples of nonhuman primates. In addition, the drug efficacy estimates of quantitative techniques was examined using a statistical simulation. Trichuris eggs were found in 47% of the samples. FLOTAC was the most sensitive technique (100%), followed by the Parasep SF (83.0% [95% confidence interval (CI): 82.4–83.6%]) and the ether-based concentration technique (76.6% [95% CI: 75.8–77.3%]). McMaster was the least sensitive (61.7% [95% CI: 60.7–62.6%]) and failed to detect low FEC. The quantitative comparison revealed a positive correlation between the four techniques (Rs = 0.85–0.93; p<0.0001). However, the ether-based concentration technique and the Parasep SF detected significantly fewer eggs than both the McMaster and the FLOTAC (p<0.0083). Overall, the McMaster was the most feasible technique (3.9 min/sample for preparing, reading and cleaning of the apparatus), followed by the ether-based concentration technique (7.7 min/sample) and the FLOTAC (9.8 min/sample). Parasep SF was the least feasible (17.7 min/sample). The simulation revealed that the sensitivity is less important for monitoring drug efficacy and that both FLOTAC and McMaster were reliable estimators. Conclusions/Significance The results of this study demonstrated that McMaster is a promising technique when making use of FEC to monitor drug efficacy in Trichuris. PMID:19172171

Occurrence of toluene in Canadian total diet foods and its significance to overall human exposure.

PubMed

Cao, Xu-Liang; Pelletier, Luc; Sparling, Melissa; Dabeka, Robert

2018-01-01

Levels of most VOCs in foods are usually low because of their volatility, and human exposure to VOCs is expected to be mainly via inhalation of ambient and indoor air. However, dietary exposures to VOCs can be significant to overall exposures if elevated concentrations of VOCs are present in foods consumed in high amounts and/or on a regular basis, and this was demonstrated in this study with the occurrence data of toluene from the recent 2014 Canadian Total Diet Study (TDS). Concentrations of toluene in the composite samples of most food types from the 2014 TDS are low and similar to the results from the previous 2007 TDS with some exceptions, such as beef steak (670 ng/g (2014 TDS) vs. 14 ng/g (2007 TDS)), poultry, chicken and turkey (307 ng/g (2014 TDS) vs. 8.8 ng/g (2007 TDS)). Toluene concentrations in most of the grain-based and fast food composite samples from the 2014 TDS are considerably higher than those from the 2007 TDS, with the highest level of 4655 ng/g found in the composite sample of crackers from the 2014 TDS (compared to 18 ng/g from 2007 TDS). Dietary exposure estimates for toluene based on the occurrence results from the 2014 TDS show that for most of the age groups, grain-based foods are the primary source, accounting for an average of 77.5% of the overall toluene intake from the diet. The highest dietary exposures to toluene were observed for the adult age groups, with estimated average exposures ranging from 177.4 to 184.5 µg/d. Dietary exposure estimates to toluene are well below oral doses associated with toxicological effects and also below the maximum estimated intake (819 µg/d) from air inhalation for adult group (20 - 70 years) based on the results from CEPA (Canadian Environmental Protection Act) assessment in 1992.

Evaluating remedial alternatives for an acid mine drainage stream: Application of a reactive transport model

USGS Publications Warehouse

Runkel, R.L.; Kimball, B.A.

2002-01-01

A reactive transport model based on one-dimensional transport and equilibrium chemistry is applied to synoptic data from an acid mine drainage stream. Model inputs include streamflow estimates based on tracer dilution, inflow chemistry based on synoptic sampling, and equilibrium constants describing acid/base, complexation, precipitation/dissolution, and sorption reactions. The dominant features of observed spatial profiles in pH and metal concentration are reproduced along the 3.5-km study reach by simulating the precipitation of Fe(III) and Al solid phases and the sorption of Cu, As, and Pb onto freshly precipitated iron-(III) oxides. Given this quantitative description of existing conditions, additional simulations are conducted to estimate the streamwater quality that could result from two hypothetical remediation plans. Both remediation plans involve the addition of CaCO3 to raise the pH of a small, acidic inflow from ???2.4 to ???7.0. This pH increase results in a reduced metal load that is routed downstream by the reactive transport model, thereby providing an estimate of post-remediation water quality. The first remediation plan assumes a closed system wherein inflow Fe(II) is not oxidized by the treatment system; under the second remediation plan, an open system is assumed, and Fe(II) is oxidized within the treatment system. Both plans increase instream pH and substantially reduce total and dissolved concentrations of Al, As, Cu, and Fe(II+III) at the terminus of the study reach. Dissolved Pb concentrations are reduced by ???18% under the first remediation plan due to sorption onto iron-(III) oxides within the treatment system and stream channel. In contrast, iron(III) oxides are limiting under the second remediation plan, and removal of dissolved Pb occurs primarily within the treatment system. This limitation results in an increase in dissolved Pb concentrations over existing conditions as additional downstream sources of Pb are not attenuated by sorption.

Chemical and isotopic methods for quantifying ground-water recharge in a regional, semiarid environment

USGS Publications Warehouse

Wood, Warren W.; Sanford, Ward E.

1995-01-01

The High Plains aquifer underlying the semiarid Southern High Plains of Texas and New Mexico, USA was used to illustrate solute and isotopic methods for evaluating recharge fluxes, runoff, and spatial and temporal distribution of recharge. The chloride mass-balance method can provide, under certain conditions, a time-integrated technique for evaluation of recharge flux to regional aquifers that is independent of physical parameters. Applying this method to the High Plains aquifer of the Southern High Plains suggests that recharge flux is approximately 2% of precipitation, or approximately 11 ± 2 mm/y, consistent with previous estimates based on a variety of physically based measurements. The method is useful because long-term average precipitation and chloride concentrations in rain and ground water have less uncertainty and are generally less expensive to acquire than physically based parameters commonly used in analyzing recharge. Spatial and temporal distribution of recharge was evaluated by use of δ2H, δ18O, and tritium concentrations in both ground water and the unsaturated zone. Analyses suggest that nearly half of the recharge to the Southern High Plains occurs as piston flow through playa basin floors that occupy approximately 6% of the area, and that macropore recharge may be important in the remaining recharge. Tritium and chloride concentrations in the unsaturated zone were used in a new equation developed to quantify runoff. Using this equation and data from a representative basin, runoff was found to be 24 ± 3 mm/y; that is in close agreement with values obtained from water-balance measurements on experimental watersheds in the area. Such geochemical estimates are possible because tritium is used to calculate a recharge flux that is independent of precipitation and runoff, whereas recharge flux based on chloride concentration in the unsaturated zone is dependent upon the amount of runoff. The difference between these two estimates yields the amount of runoff to the basin.

Consideration of exposure and species sensitivity of triclosan in the freshwater environment.

PubMed

Capdevielle, Marie; Van Egmond, Roger; Whelan, Mick; Versteeg, Donald; Hofmann-Kamensky, Matthias; Inauen, Josef; Cunningham, Virginia; Woltering, Daniel

2008-01-01

Triclosan (TCS) is a broad-spectrum antimicrobial used in consumer products including toothpaste and hand soap. After being used, TCS is washed or rinsed off and residuals that are not biodegraded or otherwise removed during wastewater treatment can enter the aquatic environment in wastewater effluents and sludges. The environmental exposure and toxicity of TCS has been the subject of various scientific and regulatory discussions in recent years. There have been a number of publications in the past 5 y reporting toxicity, fate and transport, and in-stream monitoring data as well as predictions from aquatic risk assessments. State-of-the-science probabilistic exposure models, including Geography-referenced Regional Exposure Assessment Tool for European Rivers (GREAT-ER) for European surface waters and Pharmaceutical Assessment and Transport Evalutation (PhATE) for US surface waters, have been used to predict in-stream concentrations (PECs). These models take into account spatial and temporal variability in river flows and wastewater emissions based on empirically derived estimates of chemical removal in wastewater treatment and in receiving waters. These model simulations (based on realistic use levels of TCS) have been validated with river monitoring data in areas known to be receiving high wastewater loads. The results suggest that 90th percentile (low flow) TCS concentrations are less than 200 ng/L for the Aire-Calder catchment in the United Kingdom and between 250 ng/L (with in-stream removal) and 850 ng/L (without in-stream removal) for a range of US surface waters. To better identify the aquatic risk of TCS, a species sensitivity distribution (SSD) was constructed based on chronic toxicity values, either no observed effect concentrations (NOECs) or various percentile adverse effect concentrations (EC10-25 values) for 14 aquatic species including fish, invertebrates, macrophytes, and algae. The SSD approach is believed to represent a more realistic threshold of effect than a predicted no effect concentration (PNEC) based on the data from the single most sensitive species tested. The log-logistic SSD was used to estimate a PNEC, based on an HC5,50 (the concentration estimated to affect the survival, reproduction and/or growth of 5% of species with a 50% confidence interval). The PNEC for TCS was 1,550 ng/L. Comparing the SSD-based PNEC with the PECs derived from GREATER and PhATE modeling to simulate in-river conditions in Europe and the United States, the PEC to PNEC ratios are less than unity suggesting risks to pelagic species are low even under the highest likely exposures which would occur immediately downstream of wastewater treatment plant (WWTP) discharge points. In-stream sorption, biodegradation, and photodegradation will further reduce pelagic exposures of TCS. Monitoring data in Europe and the United States corroborate the modeled PEC estimates and reductions in TCS concentrations with distance downstream of WWTP discharges. Environmental metabolites, bioaccumulation, biochemical responses including endocrine-related effects, and community level effects are far less well studied for this chemical but are addressed in the discussion. The aquatic risk assessment for TCS should be refined as additional information becomes available.

StreamVOC - A deterministic source-apportionment model to estimate volatile organic compound concentrations in rivers and streams

USGS Publications Warehouse

Asher, William E.; Bender, David A.; Zogorski, John S.; Bartholomay, Roy C.

2006-01-01

This report documents the construction and verification of the model, StreamVOC, that estimates (1) the time- and position-dependent concentrations of volatile organic compounds (VOCs) in rivers and streams as well as (2) the source apportionment (SA) of those concentrations. The model considers how different types of sources and loss processes can act together to yield a given observed VOC concentration. Reasons for interest in the relative and absolute contributions of different sources to contaminant concentrations include the need to apportion: (1) the origins for an observed contamination, and (2) the associated human and ecosystem risks. For VOCs, sources of interest include the atmosphere (by absorption), as well as point and nonpoint inflows of VOC-containing water. Loss processes of interest include volatilization to the atmosphere, degradation, and outflows of VOC-containing water from the stream to local ground water. This report presents the details of StreamVOC and compares model output with measured concentrations for eight VOCs found in the Aberjona River at Winchester, Massachusetts. Input data for the model were obtained during a synoptic study of the stream system conducted July 11-13, 2001, as part of the National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey. The input data included a variety of basic stream characteristics (for example, flows, temperature, and VOC concentrations). The StreamVOC concentration results agreed moderately well with the measured concentration data for several VOCs and provided compound-dependent SA estimates as a function of longitudinal distance down the river. For many VOCs, the quality of the agreement between the model-simulated and measured concentrations could be improved by simple adjustments of the model input parameters. In general, this study illustrated: (1) the considerable difficulty of quantifying correctly the locations and magnitudes of ground-water-related sources of contamination in streams; and (2) that model-based estimates of stream VOC concentrations are likely to be most accurate when the major sources are point sources or tributaries where the spatial extent and magnitude of the sources are tightly constrained and easily determined.

MRI Estimates of Brain Iron Concentration in Normal Aging Using Quantitative Susceptibility Mapping

PubMed Central

Bilgic, Berkin; Pfefferbaum, Adolf; Rohlfing, Torsten; Sullivan, Edith V.; Adalsteinsson, Elfar

2011-01-01

Quantifying tissue iron concentration in vivo is instrumental for understanding the role of iron in physiology and in neurological diseases associated with abnormal iron distribution. Herein, we use recently-developed Quantitative Susceptibility Mapping (QSM) methodology to estimate the tissue magnetic susceptibility based on MRI signal phase. To investigate the effect of different regularization choices, we implement and compare ℓ1 and ℓ2 norm regularized QSM algorithms. These regularized approaches solve for the underlying magnetic susceptibility distribution, a sensitive measure of the tissue iron concentration, that gives rise to the observed signal phase. Regularized QSM methodology also involves a pre-processing step that removes, by dipole fitting, unwanted background phase effects due to bulk susceptibility variations between air and tissue and requires data acquisition only at a single field strength. For validation, performances of the two QSM methods were measured against published estimates of regional brain iron from postmortem and in vivo data. The in vivo comparison was based on data previously acquired using Field-Dependent Relaxation Rate Increase (FDRI), an estimate of MRI relaxivity enhancement due to increased main magnetic field strength, requiring data acquired at two different field strengths. The QSM analysis was based on susceptibility-weighted images acquired at 1.5T, whereas FDRI analysis used Multi-Shot Echo-Planar Spin Echo images collected at 1.5T and 3.0T. Both datasets were collected in the same healthy young and elderly adults. The in vivo estimates of regional iron concentration comported well with published postmortem measurements; both QSM approaches yielded the same rank ordering of iron concentration by brain structure, with the lowest in white matter and the highest in globus pallidus. Further validation was provided by comparison of the in vivo measurements, ℓ1-regularized QSM versus FDRI and ℓ2-regularized QSM versus FDRI, which again yielded perfect rank ordering of iron by brain structure. The final means of validation was to assess how well each in vivo method detected known age-related differences in regional iron concentrations measured in the same young and elderly healthy adults. Both QSM methods and FDRI were consistent in identifying higher iron concentrations in striatal and brain stem ROIs (i.e., caudate nucleus, putamen, globus pallidus, red nucleus, and substantia nigra) in the older than in the young group. The two QSM methods appeared more sensitive in detecting age differences in brain stem structures as they revealed differences of much higher statistical significance between the young and elderly groups than did FDRI. However, QSM values are influenced by factors such as the myelin content, whereas FDRI is a more specific indicator of iron content. Hence, FDRI demonstrated higher specificity to iron yet yielded noisier data despite longer scan times and lower spatial resolution than QSM. The robustness, practicality, and demonstrated ability of predicting the change in iron deposition in adult aging suggest that regularized QSM algorithms using single-field-strength data are possible alternatives to tissue iron estimation requiring two field strengths. PMID:21925274

Atmospheric deposition of polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans, and dioxin-like polychlorinated biphenyls in the Kanto Region, Japan.

PubMed

Ogura, I; Masunaga, S; Nakanishi, J

2001-09-01

The atmospheric bulk (dry and wet) deposition of dioxins was investigated at four locations (Tokyo, Yokohama, Tsukuba, and Tanzawa) in the Kanto region (in Japan) over one year using a stainless-steel pot. Annual average polychlorinated dibenzo-p-dioxins/polychlorinated dibenzofurans (PCDD/PCDF) deposition fluxes were estimated to be from 450 to 1300 ng/m2/yr, and the annual average TEQ fluxes from 5.7 to 17 ng-TEQ/m2/yr at the four locations. The PCDD/PCDF deposition flux was higher in winter than in summer. The deposition flux could be related to ambient temperature, particularly for less chlorinated PCDDs/PCDFs, while the deposition flux is not necessarily related to the amount of precipitation. The PCDD/PCDF deposition flux increased as the particle deposition flux increased, for the winter samples. Based on the ratio of the PCDD/PCDF deposition fluxes to the particle deposition fluxes, the contribution of the reentrainment of soil particles to the TEQ of PCDD/PCDF deposition was considered to be negligible in this region. Based on the air concentrations monitored near our deposition sampling points by the municipalities, the ratio of the annual deposition flux to the annual average air concentration was roughly estimated to be 0.082 cm/s. The range of deposition flux in the Kanto region was estimated to be from 1.5 to 31 (median: 9.8) ng-TEQ/m2/yr based on the range of air concentration data measured by the municipalities. The total annual deposition flux in the entire Kanto region was estimated to range from 50 to 900 g-TEQ/yr (median 320 g-TEQ/yr). This estimated flux was of the same order as the sum of estimated emissions from municipal solid waste incinerators and industrial waste incinerators in the Kanto region. The contributions of dioxin-like PCBs in Yokohama, Tsukuba, and Tanzawa depositions were less than 10% of the total TEQ; however, in Tokyo it was almost equal to or more than 50%.

Aggregation-Induced Emission Luminogen-Based Direct Visualization of Concentration Gradient Inside an Evaporating Binary Sessile Droplet.

PubMed

Cai, Xin; Xie, Ni; Qiu, Zijie; Yang, Junxian; He, Minghao; Wong, Kam Sing; Tang, Ben Zhong; Qiu, Huihe

2017-08-30

In this study, the concentration gradient inside evaporating binary sessile droplets of 30, 50, and 60 vol % tetrahydrofuran (THF)/water mixtures was investigated. The 5 μL THF/water droplets were evaporated on a transparent hydrophobic substrate. This is the first demonstration of local concentration mapping within an evaporating binary droplet utilizing the aggregation-induced emission material. During the first two evaporation stages of the binary droplet, the local concentration can be directly visualized by the change of fluorescence emission intensity. Time-resolved average and local concentrations can be estimated by using the pre-established function of fluorescence intensity versus water volume fraction.

Tipping point analysis of atmospheric oxygen concentration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Livina, V. N.; Forbes, A. B.; Vaz Martins, T. M.

2015-03-15

We apply tipping point analysis to nine observational oxygen concentration records around the globe, analyse their dynamics and perform projections under possible future scenarios, leading to oxygen deficiency in the atmosphere. The analysis is based on statistical physics framework with stochastic modelling, where we represent the observed data as a composition of deterministic and stochastic components estimated from the observed data using Bayesian and wavelet techniques.

Estimating soil zinc concentrations using reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Sun, Weichao; Zhang, Xia

2017-06-01

Soil contamination by heavy metals has been an increasingly severe threat to nature environment and human health. Efficiently investigation of contamination status is essential to soil protection and remediation. Visible and near-infrared reflectance spectroscopy (VNIRS) has been regarded as an alternative for monitoring soil contamination by heavy metals. Generally, the entire VNIR spectral bands are employed to estimate heavy metal concentration, which lacks interpretability and requires much calculation. In this study, 74 soil samples were collected from Hunan Province, China and their reflectance spectra were used to estimate zinc (Zn) concentration in soil. Organic matter and clay minerals have strong adsorption for Zn in soil. Spectral bands associated with organic matter and clay minerals were used for estimation with genetic algorithm based partial least square regression (GA-PLSR). The entire VNIR spectral bands, the bands associated with organic matter and the bands associated with clay minerals were incorporated as comparisons. Root mean square error of prediction, residual prediction deviation, and coefficient of determination (R2) for the model developed using combined bands of organic matter and clay minerals were 329.65 mg kg-1, 1.96 and 0.73, which is better than 341.88 mg kg-1, 1.89 and 0.71 for the entire VNIR spectral bands, 492.65 mg kg-1, 1.31 and 0.40 for the organic matter, and 430.26 mg kg-1, 1.50 and 0.54 for the clay minerals. Additionally, in consideration of atmospheric water vapor absorption in field spectra measurement, combined bands of organic matter and absorption around 2200 nm were used for estimation and achieved high prediction accuracy with R2 reached 0.640. The results indicate huge potential of soil reflectance spectroscopy in estimating Zn concentrations in soil.

Estimation of VOC emissions from produced-water treatment ponds in Uintah Basin oil and gas field using modeling techniques

NASA Astrophysics Data System (ADS)

Tran, H.; Mansfield, M. L.; Lyman, S. N.; O'Neil, T.; Jones, C. P.

2015-12-01

Emissions from produced-water treatment ponds are poorly characterized sources in oil and gas emission inventories that play a critical role in studying elevated winter ozone events in the Uintah Basin, Utah, U.S. Information gaps include un-quantified amounts and compositions of gases emitted from these facilities. The emitted gases are often known as volatile organic compounds (VOCs) which, beside nitrogen oxides (NOX), are major precursors for ozone formation in the near-surface layer. Field measurement campaigns using the flux-chamber technique have been performed to measure VOC emissions from a limited number of produced water ponds in the Uintah Basin of eastern Utah. Although the flux chamber provides accurate measurements at the point of sampling, it covers just a limited area of the ponds and is prone to altering environmental conditions (e.g., temperature, pressure). This fact raises the need to validate flux chamber measurements. In this study, we apply an inverse-dispersion modeling technique with evacuated canister sampling to validate the flux-chamber measurements. This modeling technique applies an initial and arbitrary emission rate to estimate pollutant concentrations at pre-defined receptors, and adjusts the emission rate until the estimated pollutant concentrations approximates measured concentrations at the receptors. The derived emission rates are then compared with flux-chamber measurements and differences are analyzed. Additionally, we investigate the applicability of the WATER9 wastewater emission model for the estimation of VOC emissions from produced-water ponds in the Uintah Basin. WATER9 estimates the emission of each gas based on properties of the gas, its concentration in the waste water, and the characteristics of the influent and treatment units. Results of VOC emission estimations using inverse-dispersion and WATER9 modeling techniques will be reported.

Analysis of radon and thoron progeny measurements based on air filtration.

PubMed

Stajic, J M; Nikezic, D

2015-02-01

Measuring of radon and thoron progeny concentrations in air, based on air filtration, was analysed in order to assess the reliability of the method. Changes of radon and thoron progeny activities on the filter during and after air sampling were investigated. Simulation experiments were performed involving realistic measuring parameters. The sensitivity of results (radon and thoron concentrations in air) to the variations of alpha counting in three and five intervals was studied. The concentration of (218)Po showed up to be the most sensitive to these changes, as was expected because of its short half-life. The well-known method for measuring of progeny concentrations based on air filtration is rather unreliable and obtaining unrealistic or incorrect results appears to be quite possible. A simple method for quick estimation of radon potential alpha energy concentration (PAEC), based on measurements of alpha activity in a saturation regime, was proposed. Thoron PAEC can be determined from the saturation activity on the filter, through beta or alpha measurements. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Comparative Risks of Cancer from Drywall Finishing Based on Stochastic Modeling of Cumulative Exposures to Respirable Dusts and Chrysotile Asbestos Fibers.

PubMed

Boelter, Fred W; Xia, Yulin; Dell, Linda

2015-05-01

Sanding joint compounds is a dusty activity and exposures are not well characterized. Until the mid 1970s, asbestos-containing joint compounds were used by some people such that sanding could emit dust and asbestos fibers. We estimated the distribution of 8-h TWA concentrations and cumulative exposures to respirable dusts and chrysotile asbestos fibers for four worker groups: (1) drywall specialists, (2) generalists, (3) tradespersons who are bystanders to drywall finishing, and (4) do-it-yourselfers (DIYers). Data collected through a survey of experienced contractors, direct field observations, and literature were used to develop prototypical exposure scenarios for each worker group. To these exposure scenarios, we applied a previously developed semi-empirical mathematical model that predicts area as well as personal breathing zone respirable dust concentrations. An empirical factor was used to estimate chrysotile fiber concentrations from respirable dust concentrations. On a task basis, we found mean 8-h TWA concentrations of respirable dust and chrysotile fibers are numerically highest for specialists, followed by generalists, DIYers, and bystander tradespersons; these concentrations are estimated to be in excess of the respective current but not historical Threshold Limit Values. Due to differences in frequency of activities, annual cumulative exposures are highest for specialists, followed by generalists, bystander tradespersons, and DIYers. Cumulative exposure estimates for chrysotile fibers from drywall finishing are expected to result in few, if any, mesothelioma or excess lung cancer deaths according to recently published risk assessments. Given the dustiness of drywall finishing, we recommend diligence in the use of readily available source controls. © 2014 Society for Risk Analysis.

Evaluations of carbon fluxes estimated by top-down and bottom-up approaches

NASA Astrophysics Data System (ADS)

Murakami, K.; Sasai, T.; Kato, S.; Hiraki, K.; Maksyutov, S. S.; Yokota, T.; Nasahara, K.; Matsunaga, T.

2013-12-01

There are two types of estimating carbon fluxes using satellite observation data, and these are referred to as top-down and bottom-up approaches. Many uncertainties are however still remain in these carbon flux estimations, because the true values of carbon flux are still unclear and estimations vary according to the type of the model (e.g. a transport model, a process based model) and input data. The CO2 fluxes in these approaches are estimated by using different satellite data such as the distribution of CO2 concentration in the top-down approach and the land cover information (e.g. leaf area, surface temperature) in the bottom-up approach. The satellite-based CO2 flux estimations with reduced uncertainty can be used efficiently for identifications of large emission area and carbon stocks of forest area. In this study, we evaluated the carbon flux estimates from two approaches by comparing with each other. The Greenhouse gases Observing SATellite (GOSAT) has been observing atmospheric CO2 concentrations since 2009. GOSAT L4A data product is the monthly CO2 flux estimations for 64 sub-continental regions and is estimated by using GOSAT FTS SWIR L2 XCO2 data and atmospheric tracer transport model. We used GOSAT L4A CO2 flux as top-down approach estimations and net ecosystem productions (NEP) estimated by the diagnostic type biosphere model BEAMS as bottom-up approach estimations. BEAMS NEP is only natural land CO2 flux, so we used GOSAT L4A CO2 flux after subtraction of anthropogenic CO2 emissions and oceanic CO2 flux. We compared with two approach in temperate north-east Asia region. This region is covered by grassland and crop land (about 60 %), forest (about 20 %) and bare ground (about 20 %). The temporal variation for one year period was indicated similar trends between two approaches. Furthermore we show the comparison of CO2 flux estimations in other sub-continental regions.

Health risk assessment of air emissions from a municipal solid waste incineration plant--a case study.

PubMed

Cangialosi, Federico; Intini, Gianluca; Liberti, Lorenzo; Notarnicola, Michele; Stellacci, Paolo

2008-01-01

A health risk assessment of long-term emissions of carcinogenic and non-carcinogenic air pollutants has been carried out for the municipal solid waste incinerator (MSWI) of the city of Taranto, Italy. Ground level air concentrations and soil deposition of carcinogenic (Polychlorinated Dibenzo-p-Dioxins/Furans and Cd) and non-carcinogenic (Pb and Hg) pollutants have been estimated using a well documented atmospheric dispersion model. Health risk values for air inhalation, dermal contact, soil and food ingestion have been calculated based on a combination of these concentrations and a matrix of environmental exposure factors. Exposure of the surrounding population has been addressed for different release scenarios based on four pollutants, four exposure pathways and two receptor groups (children and adults). Spatial risk distribution and cancer excess cases projected from plant emissions have been compared with background mortality records. Estimated results based on the MSWI emissions show: (1) individual risks well below maximum acceptable levels, (2) very small incremental cancer risk compared with background level.

Aerosol effect on cloud droplet size as monitored from surface-based remote sensing over East China Sea region

NASA Astrophysics Data System (ADS)

Pandithurai, G.; Takamura, T.; Yamaguchi, J.; Miyagi, K.; Takano, T.; Ishizaka, Y.; Dipu, S.; Shimizu, A.

2009-07-01

The effect of increased aerosol concentrations on the low-level, non-precipitating, ice-free stratus clouds is examined using a suite of surface-based remote sensing systems. Cloud droplet effective radius and liquid water path are retrieved using cloud radar and microwave radiometer. Collocated measurements of aerosol scattering coefficient, size distribution and cloud condensation nuclei (CCN) concentrations were used to examine the response of cloud droplet size and optical thickness to increased CCN proxies. During the episodic events of increase in aerosol accumulation-mode volume distribution, the decrease in droplet size and increase in cloud optical thickness is observed. The indirect effect estimates are made for both droplet effective radius and cloud optical thickness for different liquid water path ranges and they range 0.02-0.18 and 0.005-0.154, respectively. Data are also categorized into thin and thick clouds based on cloud geometric thickness (Δz) and estimates show IE values are relatively higher for thicker clouds.

Investigation of particle inertial migration in high particle concentration suspension flow by multi-electrodes sensing and Eulerian-Lagrangian simulation in a square microchannel

PubMed Central

Zhao, Tong; Liu, Kai; Takei, Masahiro

2016-01-01

The inertial migration of neutrally buoyant spherical particles in high particle concentration (αpi > 3%) suspension flow in a square microchannel was investigated by means of the multi-electrodes sensing method which broke through the limitation of conventional optical measurement techniques in the high particle concentration suspensions due to interference from the large particle numbers. Based on the measured particle concentrations near the wall and at the corner of the square microchannel, particle cross-sectional migration ratios are calculated to quantitatively estimate the migration degree. As a result, particle migration to four stable equilibrium positions near the centre of each face of the square microchannel is found only in the cases of low initial particle concentration up to 5.0 v/v%, while the migration phenomenon becomes partial as the initial particle concentration achieves 10.0 v/v% and disappears in the cases of the initial particle concentration αpi ≥ 15%. In order to clarify the influential mechanism of particle-particle interaction on particle migration, an Eulerian-Lagrangian numerical model was proposed by employing the Lennard-Jones potential as the inter-particle potential, while the inertial lift coefficient is calculated by a pre-processed semi-analytical simulation. Moreover, based on the experimental and simulation results, a dimensionless number named migration index was proposed to evaluate the influence of the initial particle concentration on the particle migration phenomenon. The migration index less than 0.1 is found to denote obvious particle inertial migration, while a larger migration index denotes the absence of it. This index is helpful for estimation of the maximum initial particle concentration for the design of inertial microfluidic devices. PMID:27158288

Colorectal Cancer and Long-Term Exposure to Trihalomethanes in Drinking Water: A Multicenter Case-Control Study in Spain and Italy.

PubMed

Villanueva, Cristina M; Gracia-Lavedan, Esther; Bosetti, Cristina; Righi, Elena; Molina, Antonio José; Martín, Vicente; Boldo, Elena; Aragonés, Nuria; Perez-Gomez, Beatriz; Pollan, Marina; Acebo, Ines Gomez; Altzibar, Jone M; Zabala, Ana Jiménez; Ardanaz, Eva; Peiró, Rosana; Tardón, Adonina; Chirlaque, Maria Dolores; Tavani, Alessandra; Polesel, Jerry; Serraino, Diego; Pisa, Federica; Castaño-Vinyals, Gemma; Espinosa, Ana; Espejo-Herrera, Nadia; Palau, Margarita; Moreno, Victor; La Vecchia, Carlo; Aggazzotti, Gabriella; Nieuwenhuijsen, Mark J; Kogevinas, Manolis

2017-01-01

Evidence on the association between colorectal cancer and exposure to disinfection by-products in drinking water is inconsistent. We assessed long-term exposure to trihalomethanes (THMs), the most prevalent group of chlorination by-products, to evaluate the association with colorectal cancer. A multicenter case-control study was conducted in Spain and Italy in 2008-2013. Hospital-based incident cases and population-based (Spain) and hospital-based (Italy) controls were interviewed to ascertain residential histories, type of water consumed in each residence, frequency and duration of showering/bathing, and major recognized risk factors for colorectal cancer. We estimated adjusted odds ratios (OR) for colorectal cancer in association with quartiles of estimated average lifetime THM concentrations in each participant's residential tap water (micrograms/liter; from age 18 to 2 years before the interview) and estimated average lifetime THM ingestion from drinking residential tap water (micrograms/day). We analyzed 2,047 cases and 3,718 controls. Median values (ranges) for average lifetime residential tap water concentrations of total THMs, chloroform, and brominated THMs were 30 (0-174), 17 (0-63), and 9 (0-145) μg/L, respectively. Total THM concentration in residential tap water was not associated with colorectal cancer (OR = 0.92, 95% CI: 0.66, 1.28 for highest vs. lowest quartile), but chloroform concentrations were inversely associated (OR = 0.31, 95% CI: 0.24, 0.41 for highest vs. lowest quartile). Brominated THM concentrations showed a positive association among men in the highest versus the lowest quartile (OR = 1.43, 95% CI: 0.83, 2.46). Patterns of association were similar for estimated average THM ingestion through residential water consumption. We did not find clear evidence of an association between detailed estimates of lifetime total THM exposure and colorectal cancer in our large case-control study population. Negative associations with chloroform concentrations and ingestion suggest differences among specific THMs, but these findings should be confirmed in other study populations. Citation: Villanueva CM, Gracia-Lavedan E, Bosetti C, Righi E, Molina AJ, Martín V, Boldo E, Aragonés N, Perez-Gomez B, Pollan M, Gomez Acebo I, Altzibar JM, Jiménez Zabala A, Ardanaz E, Peiró R, Tardón A, Chirlaque MD, Tavani A, Polesel J, Serraino D, Pisa F, Castaño-Vinyals G, Espinosa A, Espejo-Herrera N, Palau M, Moreno V, La Vecchia C, Aggazzotti G, Nieuwenhuijsen MJ, Kogevinas M. 2017. Colorectal cancer and long-term exposure to trihalomethanes in drinking water: a multicenter case---control study in Spain and Italy. Environ Health Perspect 125:56-65; http://dx.doi.org/10.1289/EHP155.

Colorectal Cancer and Long-Term Exposure to Trihalomethanes in Drinking Water: A Multicenter Case–Control Study in Spain and Italy

PubMed Central

Villanueva, Cristina M.; Gracia-Lavedan, Esther; Bosetti, Cristina; Righi, Elena; Molina, Antonio José; Martín, Vicente; Boldo, Elena; Aragonés, Nuria; Perez-Gomez, Beatriz; Pollan, Marina; Acebo, Ines Gomez; Altzibar, Jone M.; Zabala, Ana Jiménez; Ardanaz, Eva; Peiró, Rosana; Tardón, Adonina; Chirlaque, Maria Dolores; Tavani, Alessandra; Polesel, Jerry; Serraino, Diego; Pisa, Federica; Castaño-Vinyals, Gemma; Espinosa, Ana; Espejo-Herrera, Nadia; Palau, Margarita; Moreno, Victor; La Vecchia, Carlo; Aggazzotti, Gabriella; Nieuwenhuijsen, Mark J; Kogevinas, Manolis

2016-01-01

Background: Evidence on the association between colorectal cancer and exposure to disinfection by-products in drinking water is inconsistent. Objectives: We assessed long-term exposure to trihalomethanes (THMs), the most prevalent group of chlorination by-products, to evaluate the association with colorectal cancer. Methods: A multicenter case–control study was conducted in Spain and Italy in 2008–2013. Hospital-based incident cases and population-based (Spain) and hospital-based (Italy) controls were interviewed to ascertain residential histories, type of water consumed in each residence, frequency and duration of showering/bathing, and major recognized risk factors for colorectal cancer. We estimated adjusted odds ratios (OR) for colorectal cancer in association with quartiles of estimated average lifetime THM concentrations in each participant’s residential tap water (micrograms/liter; from age 18 to 2 years before the interview) and estimated average lifetime THM ingestion from drinking residential tap water (micrograms/day). Results: We analyzed 2,047 cases and 3,718 controls. Median values (ranges) for average lifetime residential tap water concentrations of total THMs, chloroform, and brominated THMs were 30 (0–174), 17 (0–63), and 9 (0–145) μg/L, respectively. Total THM concentration in residential tap water was not associated with colorectal cancer (OR = 0.92, 95% CI: 0.66, 1.28 for highest vs. lowest quartile), but chloroform concentrations were inversely associated (OR = 0.31, 95% CI: 0.24, 0.41 for highest vs. lowest quartile). Brominated THM concentrations showed a positive association among men in the highest versus the lowest quartile (OR = 1.43, 95% CI: 0.83, 2.46). Patterns of association were similar for estimated average THM ingestion through residential water consumption. Conclusions: We did not find clear evidence of an association between detailed estimates of lifetime total THM exposure and colorectal cancer in our large case–control study population. Negative associations with chloroform concentrations and ingestion suggest differences among specific THMs, but these findings should be confirmed in other study populations. Citation: Villanueva CM, Gracia-Lavedan E, Bosetti C, Righi E, Molina AJ, Martín V, Boldo E, Aragonés N, Perez-Gomez B, Pollan M, Gomez Acebo I, Altzibar JM, Jiménez Zabala A, Ardanaz E, Peiró R, Tardón A, Chirlaque MD, Tavani A, Polesel J, Serraino D, Pisa F, Castaño-Vinyals G, Espinosa A, Espejo-Herrera N, Palau M, Moreno V, La Vecchia C, Aggazzotti G, Nieuwenhuijsen MJ, Kogevinas M. 2017. Colorectal cancer and long-term exposure to trihalomethanes in drinking water: a multicenter case–––control study in Spain and Italy. Environ Health Perspect 125:56–65; http://dx.doi.org/10.1289/EHP155 PMID:27383820

Pilot estimates of glidepath and aim point during simulated landing approaches

NASA Technical Reports Server (NTRS)

Acree, C. W., Jr.

1981-01-01

Pilot perceptions of glidepath angle and aim point were measured during simulated landings. A fixed-base cockpit simulator was used with video recordings of simulated landing approaches shown on a video projector. Pilots estimated the magnitudes of approach errors during observation without attempting to make corrections. Pilots estimated glidepath angular errors well, but had difficulty estimating aim-point errors. The data make plausible the hypothesis that pilots are little concerned with aim point during most of an approach, concentrating instead on keeping close to the nominal glidepath and trusting this technique to guide them to the proper touchdown point.

Deriving an explicit hepatic clearance equation accounting for plasma protein binding and hepatocellular uptake.

PubMed

Yoon, Miyoung; Clewell, Harvey J; Andersen, Melvin E

2013-02-01

High throughput in vitro biochemical and cell-based assays have the promise to provide more mechanism-based assessments of the adverse effects of large numbers of chemicals. One of the most challenging hurdles for interpreting in vitro toxicity findings is the need for reverse dosimetry tools that estimate the exposures that will give concentrations in vivo similar to the active concentrations in vitro. Recent experience using IVIVE approaches to estimate in vivo pharmacokinetics (Wetmore et al., 2012) identified the need to develop a hepatic clearance equation that explicitly accounted for a broader set of protein binding and membrane transport processes and did not depend on a well-mixed description of the liver compartment. Here we derive an explicit steady-state hepatic clearance equation that includes these factors. In addition to the derivation, we provide simple computer code to calculate steady-state extraction for any combination of blood flow, membrane transport processes and plasma protein-chemical binding rates. This expanded equation provides a tool to estimate hepatic clearance for a more diverse array of compounds. Copyright © 2012 Elsevier Ltd. All rights reserved.

Suspended-sediment loads in the lower Stillaguamish River, Snohomish County, Washington, 2014–15

USGS Publications Warehouse

Anderson, Scott A.; Curran, Christopher A.; Grossman, Eric E.

2017-08-03

Continuous records of discharge and turbidity at a U.S. Geological Survey (USGS) streamgage in the lower Stillaguamish River were paired with discrete measurements of suspended-sediment concentration (SSC) in order to estimate suspended-sediment loads over the water years 2014 and 2015. First, relations between turbidity and SSC were developed and used to translate the continuous turbidity record into a continuous estimate of SSC. Those concentrations were then used to predict suspended-sediment loads based on the current discharge record, reported at daily intervals. Alternative methods were used to in-fill a small number of days with either missing periods of turbidity or discharge records. Uncertainties in our predictions at daily and annual time scales were estimated based on the parameter uncertainties in our turbidity-SSC regressions. Daily loads ranged from as high as 121,000 tons during a large autumn storm to as low as –56 tons, when tidal return flow moved more sediment upstream than river discharge did downstream. Annual suspended-sediment loads for both water years were close to 1.4 ± 0.2 million tons.

Quantitative dose-response assessment of inhalation exposures to toxic air pollutants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jarabek, A.M.; Foureman, G.L.; Gift, J.S.

1997-12-31

Implementation of the 1990 Clean Air Act Amendments, including evaluation of residual risks. requires accurate human health risk estimates of both acute and chronic inhalation exposures to toxic air pollutants. The U.S. Environmental Protection Agency`s National Center for Environmental Assessment, Research Triangle Park, NC, has a research program that addresses several key issues for development of improved quantitative approaches for dose-response assessment. This paper describes three projects underway in the program. Project A describes a Bayesian approach that was developed to base dose-response estimates on combined data sets and that expresses these estimates as probability density functions. A categorical regressionmore » model has been developed that allows for the combination of all available acute data, with toxicity expressed as severity categories (e.g., mild, moderate, severe), and with both duration and concentration as governing factors. Project C encompasses two refinements to uncertainty factors (UFs) often applied to extrapolate dose-response estimates from laboratory animal data to human equivalent concentrations. Traditional UFs have been based on analyses of oral administration and may not be appropriate for extrapolation of inhalation exposures. Refinement of the UF applied to account for the use of subchronic rather than chronic data was based on an analysis of data from inhalation exposures (Project C-1). Mathematical modeling using the BMD approach was used to calculate the dose-response estimates for comparison between the subchronic and chronic data so that the estimates were not subject to dose-spacing or sample size variability. The second UF that was refined for extrapolation of inhalation data was the adjustment for the use of a LOAEL rather than a NOAEL (Project C-2).« less

Median infectious dose (ID₅₀) of porcine reproductive and respiratory syndrome virus isolate MN-184 via aerosol exposure.

PubMed

Cutler, Timothy D; Wang, Chong; Hoff, Steven J; Kittawornrat, Apisit; Zimmerman, Jeffrey J

2011-08-05

The median infectious dose (ID(50)) of porcine reproductive and respiratory syndrome (PRRS) virus isolate MN-184 was determined for aerosol exposure. In 7 replicates, 3-week-old pigs (n=58) respired 10l of airborne PRRS virus from a dynamic aerosol toroid (DAT) maintained at -4°C. Thereafter, pigs were housed in isolation and monitored for evidence of infection. Infection occurred at virus concentrations too low to quantify by microinfectivity assays. Therefore, exposure dose was determined using two indirect methods ("calculated" and "theoretical"). "Calculated" virus dose was derived from the concentration of rhodamine B monitored over the exposure sequence. "Theoretical" virus dose was based on the continuous stirred-tank reactor model. The ID(50) estimate was modeled on the proportion of pigs that became infected using the probit and logit link functions for both "calculated" and "theoretical" exposure doses. Based on "calculated" doses, the probit and logit ID(50) estimates were 1 × 10(-0.13)TCID(50) and 1 × 10(-0.14)TCID(50), respectively. Based on "theoretical" doses, the probit and logit ID(50) were 1 × 10(0.26)TCID(50) and 1 × 10(0.24)TCID(50), respectively. For each point estimate, the 95% confidence interval included the other three point estimates. The results indicated that MN-184 was far more infectious than PRRS virus isolate VR-2332, the only other PRRS virus isolate for which ID(50) has been estimated for airborne exposure. Since aerosol ID(50) estimates are available for only these two isolates, it is uncertain whether one or both of these isolates represent the normal range of PRRS virus infectivity by this route. Copyright © 2011 Elsevier B.V. All rights reserved.

Blind Deconvolution for Distributed Parameter Systems with Unbounded Input and Output and Determining Blood Alcohol Concentration from Transdermal Biosensor Data.

PubMed

Rosen, I G; Luczak, Susan E; Weiss, Jordan

2014-03-15

We develop a blind deconvolution scheme for input-output systems described by distributed parameter systems with boundary input and output. An abstract functional analytic theory based on results for the linear quadratic control of infinite dimensional systems with unbounded input and output operators is presented. The blind deconvolution problem is then reformulated as a series of constrained linear and nonlinear optimization problems involving infinite dimensional dynamical systems. A finite dimensional approximation and convergence theory is developed. The theory is applied to the problem of estimating blood or breath alcohol concentration (respectively, BAC or BrAC) from biosensor-measured transdermal alcohol concentration (TAC) in the field. A distributed parameter model with boundary input and output is proposed for the transdermal transport of ethanol from the blood through the skin to the sensor. The problem of estimating BAC or BrAC from the TAC data is formulated as a blind deconvolution problem. A scheme to identify distinct drinking episodes in TAC data based on a Hodrick Prescott filter is discussed. Numerical results involving actual patient data are presented.

Coulometric determination of NAD+ and NADH in normal and cancer cells using LDH, RVC and a polymer mediator.

PubMed

Torabi, F; Ramanathan, K; Larsson, P O; Gorton, L; Svanberg, K; Okamoto, Y; Danielsson, B; Khayyami, M

1999-11-15

An electrochemical method for the measurement of NAD(+) and NADH in normal and cancer tissues using flow injection analysis (FIA) is reported. Reticulated vitreous carbon (RVC) electrodes with entrapped l-lactate dehydrogenase (LDH) and a new redox polymer containing covalently bound toluidine blue O (TBO) were employed for this purpose. Both NAD(+) and NADH were estimated coulometrically based on their reaction with LDH. The latter was immobilized on controlled pore glass (CPG) by cross-linking with glutaraldehyde and packed within the RVC. The concentrations of NAD(+) and NADH in the tissues, estimated using different electron mediators such as ferricyanide (FCN), meldola blue (MB) and TBO have also been compared. The effects of flow rate, pH, applied potential (versus Ag/AgCl reference) and adsorption of the mediators have also been investigated. Based on the measurements of NAD(+) and NADH in normal and cancer tissues it has been concluded that the NADH concentration is lower, while the NAD(+) concentration is higher in cancer tissues. Amongst the electron mediators TBO was found to be a more stable mediator for such measurements.

Validation of two dilution models to predict chloramine-T concentrations in aquaculture facility effluent

USGS Publications Warehouse

Gaikowski, M.P.; Larson, W.J.; Steuer, J.J.; Gingerich, W.H.

2004-01-01

Accurate estimates of drug concentrations in hatchery effluent are critical to assess the environmental risk of hatchery drug discharge resulting from disease treatment. This study validated two dilution simple n models to estimate chloramine-T environmental introduction concentrations by comparing measured and predicted chloramine-T concentrations using the US Geological Survey's Upper Midwest Environmental Sciences Center aquaculture facility effluent as an example. The hydraulic characteristics of our treated raceway and effluent and the accuracy of our water flow rate measurements were confirmed with the marker dye rhodamine WT. We also used the rhodamine WT data to develop dilution models that would (1) estimate the chloramine-T concentration at a given time and location in the effluent system and (2) estimate the average chloramine-T concentration at a given location over the entire discharge period. To test our models, we predicted the chloramine-T concentration at two sample points based on effluent flow and the maintenance of chloramine-T at 20 mg/l for 60 min in the same raceway used with rhodamine WT. The effluent sample points selected (sample points A and B) represented 47 and 100% of the total effluent flow, respectively. Sample point B is-analogous to the discharge of a hatchery that does not have a detention lagoon, i.e. The sample site was downstream of the last dilution water addition following treatment. We then applied four chloramine-T flow-through treatments at 20mg/l for 60 min and measured the chloramine-T concentration in water samples collected every 15 min for about 180 min from the treated raceway and sample points A and B during and after application. The predicted chloramine-T concentration at each sampling interval was similar to the measured chloramine-T concentration at sample points A and B and was generally bounded by the measured 90% confidence intervals. The predicted aver,age chloramine-T concentrations at sample points A or B (2.8 and 1.3 mg/l, respectively) were not significantly different (P > 0.05) from the average measured chloramine-T concentrations (2.7 and 1.3 mg/l, respectively). The close agreement between our predicted and measured chloramine-T concentrations indicate either of the dilution models could be used to adequately predict the chloramine-T environmental introduction concentration in Upper Midwest Environmental Sciences Center effluent. (C) 2003 Elsevier B.V. All rights reserved.

Bioaccumulation of organic and inorganic selenium in a laboratory food chain

USGS Publications Warehouse

Besser, John M.; Canfield, Timothy J.; La Point, Thomas W.

1993-01-01

Aquatic organisms accumulated selenium (Se) from inorganic and organic Se species via aqueous and food-chain exposure routes. We measured aqueous and food-chain Se bioaccumulation from selenate, selenite, and seleno-L-methionine in a laboratory food chain of algae (Chlamydomonas reinhardtii), daphnids (Daphnia magna), and fish (bluegill, Lepomis macrochirus). Selenium concentrations were monitored radiometrically with 75Se-labeled compounds. All three organisms concentrated Se more strongly from aqueous selenomethionine than from either inorganic Se species. Bioconcentration factors (BCFs) estimated from 1 μg Se/L Se-methionine exposures were approximately 16,000 for algae, 200,000 for daphnids, and 5,000 for bluegills. Algae and daphnids concentrated Se more strongly from selenite (BCFs = 220–3,600) than selenate (BCFs = 65–500) whereas bluegills concenrated Se about equally from both inorganic species (estimated BCFs = 13 to 106). Bioaccumulation of foodborne Se by daphnids and bluegills was similar in food chains dosed with different Se species. Daphnids and bluegills did not accumulate Se concentrations greater than those in their diet, except at very low dietary Se concentrations. Food-chain concentration factors (CFs) for daphnids decreased from near 1.0 to 0.5 with increases in algal Se concentrations, whereas CFs estimated from bluegill exposures averaged 0.5 over a range of foodborne Se concentrations. In exposures based on selenite, bluegills accumulated greater Se concentrations from food than from water. Aqueous and food-chain Se uptakes were approximately additive, and depuration rates were similar in aqueous, food-chain, and combined exposures. Our results suggest that bluegills in Secontaminated habitats accumulate inorganic Se species primarily via food-chain uptake, although organoselenium compounds such as Se-methionine may contribute significantly to Se bioaccumulation by bluegills via both aqueous and food-chain uptake.

Improved estimates of filtered total mercury loadings and total mercury concentrations of solids from potential sources to Sinclair Inlet, Kitsap County, Washington

USGS Publications Warehouse

Paulson, Anthony J.; Conn, Kathleen E.; DeWild, John F.

2013-01-01

Previous investigations examined sources and sinks of mercury to Sinclair Inlet based on historic and new data. This included an evaluation of mercury concentrations from various sources and mercury loadings from industrial discharges and groundwater flowing from the Bremerton naval complex to Sinclair Inlet. This report provides new data from four potential sources of mercury to Sinclair Inlet: (1) filtered and particulate total mercury concentrations of creek water during the wet season, (2) filtered and particulate total mercury releases from the Navy steam plant following changes in the water softening process and discharge operations, (3) release of mercury from soils to groundwater in two landfill areas at the Bremerton naval complex, and (4) total mercury concentrations of solids in dry dock sumps that were not affected by bias from sequential sampling. The previous estimate of the loading of filtered total mercury from Sinclair Inlet creeks was based solely on dry season samples. Concentrations of filtered total mercury in creek samples collected during wet weather were significantly higher than dry weather concentrations, which increased the estimated loading of filtered total mercury from creek basins from 27.1 to 78.1 grams per year. Changes in the concentrations and loading of filtered and particulate total mercury in the effluent of the steam plant were investigated after the water softening process was changed from ion-exchange to reverse osmosis and the discharge of stack blow-down wash began to be diverted to the municipal water-treatment plant. These changes reduced the concentrations of filtered and particulate total mercury from the steam plant of the Bremerton naval complex, which resulted in reduced loadings of filtered total mercury from 5.9 to 0.15 grams per year. Previous investigations identified three fill areas on the Bremerton naval complex, of which the western fill area is thought to be the largest source of mercury on the base. Studies of groundwater in the other two fill areas were conducted under worst-case higher high tidal conditions. A December 2011 study found that concentrations of filtered total mercury in the well in the fill area on the eastern boundary of the Bremerton naval complex were less than or equal to 11 nanograms per liter, indicating that releases from the eastern area were unlikely. In addition, concentrations of total mercury of solids were low (<3 milligrams per kilogram). In contrast, data from the November 2011 study indicated that the concentrations of filtered total mercury in the well located in the central fill area had tidally influenced concentrations of up to 500 nanograms per liter and elevated concentrations of total mercury of solids (29–41 milligrams per kilogram). This suggests that releases from this area, which has not been previously studied in detail, may be substantial. Previous measurements of total mercury of suspended solids in the dry dock discharges revealed high concentration of total mercury when suspended-solids concentrations were low. However, this result could have been owing to bias from sequential sampling during changing suspended‑solids concentrations. Sampling of two dry dock systems on the complex in a manner that precluded this bias confirmed that suspended-solids concentrations and total mercury concentrations of suspended solids varied considerably during pumping cycles. These new data result in revised estimates of solids loadings from the dry docks. Although most of the solids discharged by the dry docks seem to be recycled Operable Unit B Marine sediment, a total of about 3.2 metric tons of solids per year containing high concentrations of total mercury were estimated to be discharged by the two dry dock systems. A simple calculation, in which solids (from dry docks, the steam plant, and tidal flushing of the largest stormwater drain) are widely dispersed throughout Operable Unit B Marine, suggests that Bremerton naval complex solids would likely have little effect on Operable Unit B Marine sediments because of high concentrations of mercury already present in the sediment.

Measured removal rates of chrysotile asbestos fibers from air and comparison with theoretical estimates based on gravitational settling and dilution ventilation.

PubMed

Sahmel, J; Avens, H J; Scott, P K; Unice, K; Burns, A; Barlow, C A; Madl, A K; Henshaw, J; Paustenbach, D J

2015-01-01

Industrial hygiene assessments often focus on activity-based airborne asbestos concentration measurements, but few empirical data exist regarding the fiber removal rate from air after activities cease. Grade 7T chrysotile indoor fiber settling (FS) rates were characterized using air sampling (NIOSH Method 7402). Six replicate events were conducted in a 58 m(3) study chamber (ventilation 3.5 ACH), in which chrysotile-contaminated work clothing was manipulated for 15 min followed by 30 min of no activity. The fiber concentration decay constant and removal rate were characterized using an exponential decay model based on the measurements. Breathing zone airborne chrysotile concentrations decreased by 86% within 15-30 min after fiber disturbance, compared to concentrations during active disturbance (p < 0.05). Estimated mean time required for 99% of the phase contrast microscopy-equivalent (PCME) fibers to be removed from air was approximately 30 min (95% CI: 22-57 min). The observed effective FS velocity was 0.0034 m/s. This settling velocity was between 4.5-fold and 180-fold faster than predicted by two different particulate gravitational settling models. Additionally, PCME concentrations decreased approximately 2.5-fold faster than predicted due to air exchange alone (32 versus 79 min to 99% decrease in concentration). Other measurement studies have reported similar airborne fiber removal rates, supporting the finding that factors other than gravitational settling and dilution ventilation contribute measurably to PCM fiber removal from air (e.g. impaction, agglomeration). Overall, the scientific weight of evidence indicates that the time necessary for removal of 99% of fibers greater than 5 μm in length (with aspect ratios greater than 3:1) is approximately 20-80 min.

Absorption of phenytoin from rectal suppositories formulated with a polyethylene glycol base.

PubMed

Burstein, A H; Fisher, K M; McPherson, M L; Roby, C A

2000-05-01

To compare phenytoin pharmacokinetics following administration of an oral suspension and a rectal suppository formulated with a polyethylene glycol base. Unblinded, single-dose, randomized, crossover trial. University-affiliated pharmacokinetics and biopharmaceutics laboratory. Six healthy subjects. Subjects were given a single 200-mg dose of phenytoin as an oral suspension and a rectal suppository separated by a 1-week washout. Blood for plasma phenytoin concentrations was obtained at baseline and 0.5, 1, 2, 4, 6, 8, 10, 12, and 24 hours after administration. Plasma was analyzed by high-performance liquid chromatography (coefficient of variation < 6%) for total phenytoin concentration. Phenytoin maximum concentration (Cmax), time to Cmax (Tmax), time to first measurable concentration (Tlag), and area under the curve from time zero to time of last measurable concentration (AUClast) were estimated for oral and rectal administration by WinNonlin (v 1.1) and compared using Wilcoxon's signed rank test (p<0.05 for statistical significance). Two subjects did not have detectable plasma phenytoin concentrations after rectal administration. For the other four subjects, median rectal Cmax was significantly lower than oral Cmax (0.4 vs 1.9 microg/ml, p=0.028), median rectal Tmax did not differ from oral Tmax (11.9 vs 8.0 hrs, p=0.465), and median rectal AUClast, although highly variable, was significantly lower than oral AUClast (5.4 vs 36.2 microg x hr/ml, p=0.046). No Tlag was seen after oral administration, but with rectal administration the median Tlag was 2 hours. The estimated relative bioavailability of rectal phenytoin suppositories based on AUC0-24 was 4.7%, with individual values ranging from 0-58.3%. It appears that absorption of phenytoin from polyethylene glycol rectal suppositories in healthy subjects is highly variable and unpredictable. Thus this formulation is not recommended.

Scale-up of a physiologically-based pharmacokinetic model to predict the disposition of monoclonal antibodies in monkeys.

PubMed

Glassman, Patrick M; Chen, Yang; Balthasar, Joseph P

2015-10-01

Preclinical assessment of monoclonal antibody (mAb) disposition during drug development often includes investigations in non-human primate models. In many cases, mAb exhibit non-linear disposition that relates to mAb-target binding [i.e., target-mediated disposition (TMD)]. The goal of this work was to develop a physiologically-based pharmacokinetic (PBPK) model to predict non-linear mAb disposition in plasma and in tissues in monkeys. Physiological parameters for monkeys were collected from several sources, and plasma data for several mAbs associated with linear pharmacokinetics were digitized from prior literature reports. The digitized data displayed great variability; therefore, parameters describing inter-antibody variability in the rates of pinocytosis and convection were estimated. For prediction of the disposition of individual antibodies, we incorporated tissue concentrations of target proteins, where concentrations were estimated based on categorical immunohistochemistry scores, and with assumed localization of target within the interstitial space of each organ. Kinetics of target-mAb binding and target turnover, in the presence or absence of mAb, were implemented. The model was then employed to predict concentration versus time data, via Monte Carlo simulation, for two mAb that have been shown to exhibit TMD (2F8 and tocilizumab). Model predictions, performed a priori with no parameter fitting, were found to provide good prediction of dose-dependencies in plasma clearance, the areas under plasma concentration versu time curves, and the time-course of plasma concentration data. This PBPK model may find utility in predicting plasma and tissue concentration versus time data and, potentially, the time-course of receptor occupancy (i.e., mAb-target binding) to support the design and interpretation of preclinical pharmacokinetic-pharmacodynamic investigations in non-human primates.

Comparing Broad-Band and Red Edge-Based Spectral Vegetation Indices to Estimate Nitrogen Concentration of Crops Using Casi Data

NASA Astrophysics Data System (ADS)

Wang, Yanjie; Liao, Qinhong; Yang, Guijun; Feng, Haikuan; Yang, Xiaodong; Yue, Jibo

2016-06-01

In recent decades, many spectral vegetation indices (SVIs) have been proposed to estimate the leaf nitrogen concentration (LNC) of crops. However, most of these indices were based on the field hyperspectral reflectance. To test whether they can be used in aerial remote platform effectively, in this work a comparison of the sensitivity between several broad-band and red edge-based SVIs to LNC is investigated over different crop types. By using data from experimental LNC values over 4 different crop types and image data acquired using the Compact Airborne Spectrographic Imager (CASI) sensor, the extensive dataset allowed us to evaluate broad-band and red edge-based SVIs. The result indicated that NDVI performed the best among the selected SVIs while red edge-based SVIs didn't show the potential for estimating the LNC based on the CASI data due to the spectral resolution. In order to search for the optimal SVIs, the band combination algorithm has been used in this work. The best linear correlation against the experimental LNC dataset was obtained by combining the 626.20nm and 569.00nm wavebands. These wavelengths correspond to the maximal chlorophyll absorption and reflection position region, respectively, and are known to be sensitive to the physiological status of the plant. Then this linear relationship was applied to the CASI image for generating an LNC map, which can guide farmers in the accurate application of their N fertilization strategies.

The effects of retail concentration on retail dairy product prices in the United States.

PubMed

Hovhannisyan, V; Bozic, M

2016-06-01

This study provides an empirical investigation of the relationship between grocery retail concentration and retail dairy product prices in the United States. The analysis was performed based on a unique data set on store-level retail prices provided by the Information Resources Inc. Further, alternative measures of retail concentration were considered, which included revenue and store selling space-based Herfindahl-Hirschman Index that were computed based on a Nielsen TDLinx data set on store characteristics. Results from a reduced-form empirical framework estimated via panel data techniques indicated that grocery retail concentration had a positive statistically significant effect on retail dairy product prices in the analyzed locations during the analyzed period of time. Specifically, a 10% increase in concentration was found to lead to a 0.46% rise in retail dairy product prices. This central result was robust to the way in which retail concentration was measured and was consistent with broader empirical evidence in the literature on retail market power. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

An aeration control strategy for oxidation ditch processes based on online oxygen requirement estimation.

PubMed

Zhan, J X; Ikehata, M; Mayuzumi, M; Koizumi, E; Kawaguchi, Y; Hashimoto, T

2013-01-01

A feedforward-feedback aeration control strategy based on online oxygen requirements (OR) estimation is proposed for oxidation ditch (OD) processes, and it is further developed for intermittent aeration OD processes, which are the most popular type in Japan. For calculating OR, concentrations of influent biochemical oxygen demand (BOD) and total Kjeldahl nitrogen (TKN) are estimated online by the measurement of suspended solids (SS) and sometimes TKN is estimated by NH4-N. Mixed liquor suspended solids (MLSS) and temperature are used to estimate the required oxygen for endogenous respiration. A straightforward parameter named aeration coefficient, Ka, is introduced as the only parameter that can be tuned automatically by feedback control or manually by the operators. Simulation with an activated sludge model was performed in comparison to fixed-interval aeration and satisfying result of OR control strategy was obtained. The OR control strategy has been implemented at seven full-scale OD plants and improvements in nitrogen removal are obtained in all these plants. Among them, the results obtained in Yumoto wastewater treatment plant were presented, in which continuous aeration was applied previously. After implementing intermittent OR control, the total nitrogen concentration was reduced from more than 5 mg/L to under 2 mg/L, and the electricity consumption was reduced by 61.2% for aeration or 21.5% for the whole plant.

Parameter estimation for stiff deterministic dynamical systems via ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Arnold, Andrea; Calvetti, Daniela; Somersalo, Erkki

2014-10-01

A commonly encountered problem in numerous areas of applications is to estimate the unknown coefficients of a dynamical system from direct or indirect observations at discrete times of some of the components of the state vector. A related problem is to estimate unobserved components of the state. An egregious example of such a problem is provided by metabolic models, in which the numerous model parameters and the concentrations of the metabolites in tissue are to be estimated from concentration data in the blood. A popular method for addressing similar questions in stochastic and turbulent dynamics is the ensemble Kalman filter (EnKF), a particle-based filtering method that generalizes classical Kalman filtering. In this work, we adapt the EnKF algorithm for deterministic systems in which the numerical approximation error is interpreted as a stochastic drift with variance based on classical error estimates of numerical integrators. This approach, which is particularly suitable for stiff systems where the stiffness may depend on the parameters, allows us to effectively exploit the parallel nature of particle methods. Moreover, we demonstrate how spatial prior information about the state vector, which helps the stability of the computed solution, can be incorporated into the filter. The viability of the approach is shown by computed examples, including a metabolic system modeling an ischemic episode in skeletal muscle, with a high number of unknown parameters.

Urinary Concentrations of Parabens and Other Antimicrobial Chemicals and Their Association with Couples’ Fecundity

PubMed Central

Smarr, Melissa M.; Sundaram, Rajeshwari; Honda, Masato; Kannan, Kurunthachalam; Louis, Germaine M. Buck

2016-01-01

Background: Human exposure to parabens and other antimicrobial chemicals is continual and pervasive. The hormone-disrupting properties of these environmental chemicals may adversely affect human reproduction. Objective: We aimed to prospectively assess couples’ urinary concentrations of antimicrobial chemicals in the context of fecundity, measured as time to pregnancy (TTP). Methods: In a prospective cohort of 501 couples, we examined preconception urinary chemical concentrations of parabens, triclosan and triclorcarban in relation to TTP; chemical concentrations were modeled both continuously and in quartiles. Cox’s proportional odds models for discrete survival time were used to estimate fecundability odds ratios (FORs) and 95% confidence intervals (CIs) adjusting for a priori–defined confounders. In light of TTP being a couple-dependent outcome, both partner and couple-based exposure models were analyzed. In all models, FOR estimates < 1.0 denote diminished fecundity (longer TTP). Results: Overall, 347 (69%) couples became pregnant. The highest quartile of female urinary methyl paraben (MP) concentrations relative to the lowest reflected a 34% reduction in fecundity (aFOR = 0.66; 95% CI: 0.45, 0.97) and remained so when accounting for couples’ concentrations (aFOR = 0.63; 95% CI: 0.41, 0.96). Similar associations were observed between ethyl paraben (EP) and couple fecundity for both partner and couple-based models (p-trend = 0.02 and p-trend = 0.05, respectively). No associations were observed with couple fecundity when chemicals were modeled continuously. Conclusions: Higher quartiles of preconception urinary concentrations of MP and EP among female partners were associated with reduced couple fecundity in partner-specific and couple-based exposure models. Citation: Smarr MM, Sundaram R, Honda M, Kannan K, Buck Louis GM. 2016. Urinary concentrations of parabens and other antimicrobial chemicals and their association with couples’ fecundity. Environ Health Perspect 124:730–736; http://dx.doi.org/10.1289/EHP189 PMID:27286252

Estimating the confidence bounds for projected ozone design values under different emissions control options

EPA Science Inventory

In current regulatory applications, regional air quality model is applied for a base year and a future year with reduced emissions using the same meteorological conditions. The base year design value is multiplied by the ratio of the average of the top 10 ozone concentrations fo...

MOVING FROM EXTERNAL EXPOSURE CONCENTRATION TO INTERNAL DOSE: DURATION EXTRAPOLATION BASED ON PHYSIOLOGICALLY-BASED PHARMACOKINETIC-MODEL DERIVED ESTIMATES OF INTERNAL DOSE

EPA Science Inventory

The potential human health risk(s) from exposure to chemicals under conditions for which adequate human or animal data are not available must frequently be assessed. Exposure scenario is particularly important for the acute neurotoxic effects of volatile organic compounds (VOCs)...

Development of scan analysis techniques employing a small computer. Final report, February 1, 1963--July 31, 1976

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuhl, D.E.

1976-08-05

During the thirteen year duration of this contract the goal has been to develop and apply computer based analysis of radionuclide scan data so as to make available improved diagnostic information based on a knowledge of localized quantitative estimates of radionuclide concentration. Results are summarized. (CH)

A simple model for calculating air pollution within street canyons

NASA Astrophysics Data System (ADS)

Venegas, Laura E.; Mazzeo, Nicolás A.; Dezzutti, Mariana C.

2014-04-01

This paper introduces the Semi-Empirical Urban Street (SEUS) model. SEUS is a simple mathematical model based on the scaling of air pollution concentration inside street canyons employing the emission rate, the width of the canyon, the dispersive velocity scale and the background concentration. Dispersive velocity scale depends on turbulent motions related to wind and traffic. The parameterisations of these turbulent motions include two dimensionless empirical parameters. Functional forms of these parameters have been obtained from full scale data measured in street canyons at four European cities. The sensitivity of SEUS model is studied analytically. Results show that relative errors in the evaluation of the two dimensionless empirical parameters have less influence on model uncertainties than uncertainties in other input variables. The model estimates NO2 concentrations using a simple photochemistry scheme. SEUS is applied to estimate NOx and NO2 hourly concentrations in an irregular and busy street canyon in the city of Buenos Aires. The statistical evaluation of results shows that there is a good agreement between estimated and observed hourly concentrations (e.g. fractional bias are -10.3% for NOx and +7.8% for NO2). The agreement between the estimated and observed values has also been analysed in terms of its dependence on wind speed and direction. The model shows a better performance for wind speeds >2 m s-1 than for lower wind speeds and for leeward situations than for others. No significant discrepancies have been found between the results of the proposed model and that of a widely used operational dispersion model (OSPM), both using the same input information.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deng, Min; Kollias, Pavlos; Feng, Zhe

The motivation for this research is to develop a precipitation classification and rain rate estimation method using cloud radar-only measurements for Atmospheric Radiation Measurement (ARM) long-term cloud observation analysis, which are crucial and unique for studying cloud lifecycle and precipitation features under different weather and climate regimes. Based on simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two precipitation radars (NCAR S-PolKa and Texas A&M University SMART-R), and surface precipitation during the DYNAMO/AMIE field campaign, a new cloud radar-only based precipitation classification and rain rate estimation method has been developed and evaluated. The resulting precipitation classification ismore » equivalent to those collocated SMART-R and S-PolKa observations. Both cloud and precipitation radars detected about 5% precipitation occurrence during this period. The convective (stratiform) precipitation fraction is about 18% (82%). The 2-day collocated disdrometer observations show an increased number concentration of large raindrops in convective rain compared to dominant concentration of small raindrops in stratiform rain. The composite distributions of KAZR reflectivity and Doppler velocity also show two distinct structures for convective and stratiform rain. These indicate that the method produces physically consistent results for two types of rain. The cloud radar-only rainfall estimation is developed based on the gradient of accumulative radar reflectivity below 1 km, near-surface Ze, and collocated surface rainfall (R) measurement. The parameterization is compared with the Z-R exponential relation. The relative difference between estimated and surface measured rainfall rate shows that the two-parameter relation can improve rainfall estimation.« less

Observation-based estimation of aerosol-induced reduction of planetary boundary layer height

NASA Astrophysics Data System (ADS)

Zou, Jun; Sun, Jianning; Ding, Aijun; Wang, Minghuai; Guo, Weidong; Fu, Congbin

2017-09-01

Radiative aerosols are known to influence the surface energy budget and hence the evolution of the planetary boundary layer. In this study, we develop a method to estimate the aerosol-induced reduction in the planetary boundary layer height (PBLH) based on two years of ground-based measurements at a site, the Station for Observing Regional Processes of the Earth System (SORPES), at Nanjing University, China, and radiosonde data from the meteorological station of Nanjing. The observations show that increased aerosol loads lead to a mean decrease of 67.1 W m-2 for downward shortwave radiation (DSR) and a mean increase of 19.2 W m-2 for downward longwave radiation (DLR), as well as a mean decrease of 9.6 Wm-2 for the surface sensible heat flux (SHF) in the daytime. The relative variations of DSR, DLR and SHF are shown as a function of the increment of column mass concentration of particulate matter (PM2.5). High aerosol loading can significantly increase the atmospheric stability in the planetary boundary layer during both daytime and nighttime. Based on the statistical relationship between SHF and PM2.5 column mass concentrations, the SHF under clean atmospheric conditions (same as the background days) is derived. In this case, the derived SHF, together with observed SHF, are then used to estimate changes in the PBLH related to aerosols. Our results suggest that the PBLH decreases more rapidly with increasing aerosol loading at high aerosol loading. When the daytime mean column mass concentration of PM2.5 reaches 200 mg m-2, the decrease in the PBLH at 1600 LST (local standard time) is about 450 m.

Quantifying public health benefits of environmental strategy of PM2.5 air quality management in Beijing-Tianjin-Hebei region, China.

PubMed

Chen, Li; Shi, Mengshuang; Li, Suhuan; Gao, Shuang; Zhang, Hui; Sun, Yanling; Mao, Jian; Bai, Zhipeng; Wang, Zhongliang; Zhou, Jiang

2017-07-01

In 2013, China issued "Air Pollution Prevention and Control Action Plan (Action Plan)" to improve air quality. To assess the benefits of this program in Beijing-Tianjin-Hebei (BTH) region, where the density of population and emissions vary greatly, we simulated the air quality benefit based on BenMAP to satisfy the Action Plan. In this study, we estimate PM 2.5 concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1×1km 2 . Combined with the exposure-response function between PM 2.5 concentration and health endpoints, health effects of PM 2.5 exposure are analyzed. The economic loss is assessed by using the willingness to pay (WTP) method and human capital (HC) method. When the PM 2.5 concentration falls by 25% in BTH and reached 60μg/m 3 in Beijing, the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year. Of the estimated mortality attributable to all causes, 3117 annual deaths were due to lung cancer, 1924 - 6318 annual deaths were due to cardiovascular, and 343 - 1697 annual deaths were due to respiratory. Based on WTP, the estimated monetary values for the avoided cases of all cause mortality, cardiovascular mortality, respiratory mortality and lung cancer ranged from 1110 to 29632, 673 to 13325, 120 to 3579, 1091 to 6574 million yuan, respectively. Based on HC, the corresponding values for the avoided cases of these four mortalities were 267 to 1178, 161 to 529, 29 to 143 and 261 million yuan, respectively. Copyright © 2016. Published by Elsevier B.V.

Characterizing Air Pollution Exposure Misclassification Errors Using Detailed Cell Phone Location Data

NASA Astrophysics Data System (ADS)

Yu, H.; Russell, A. G.; Mulholland, J. A.

2017-12-01

In air pollution epidemiologic studies with spatially resolved air pollution data, exposures are often estimated using the home locations of individual subjects. Due primarily to lack of data or logistic difficulties, the spatiotemporal mobility of subjects are mostly neglected, which are expected to result in exposure misclassification errors. In this study, we applied detailed cell phone location data to characterize potential exposure misclassification errors associated with home-based exposure estimation of air pollution. The cell phone data sample consists of 9,886 unique simcard IDs collected on one mid-week day in October, 2013 from Shenzhen, China. The Community Multi-scale Air Quality model was used to simulate hourly ambient concentrations of six chosen pollutants at 3 km spatial resolution, which were then fused with observational data to correct for potential modeling biases and errors. Air pollution exposure for each simcard ID was estimated by matching hourly pollutant concentrations with detailed location data for corresponding IDs. Finally, the results were compared with exposure estimates obtained using the home location method to assess potential exposure misclassification errors. Our results show that the home-based method is likely to have substantial exposure misclassification errors, over-estimating exposures for subjects with higher exposure levels and under-estimating exposures for those with lower exposure levels. This has the potential to lead to a bias-to-the-null in the health effect estimates. Our findings suggest that the use of cell phone data has the potential for improving the characterization of exposure and exposure misclassification in air pollution epidemiology studies.

Thermal Profile of the Lunar Interior Constrained by Revised Estimates of Concentrations of Heat Producing Elements

NASA Astrophysics Data System (ADS)

Fuqua-Haviland, H.; Panovska, S.; Mallik, A.; Bremner, P. M.; McDonough, W. F.

2017-12-01

Constraining the heat producing element (HPE) concentrations of the Moon is important for understanding the thermal state of the interior. The lunar HPE budget is debated to be suprachondritic [1] to chondritic [2]. The Moon is differentiated, thus, each reservoir has a distinct HPE signature complicating this effort. The thermal profile of the lunar interior has been constructed using HPE concentrations of an ordinary chondrite (U = 0.0068 ppm; Th = 0.025 ppm; K = 17 ppm) which yields a conservative low estimate [2, 3, 4]. A later study estimated the bulk lunar mantle HPE concentrations (U = 0.039 ppm; Th = 0.15 ppm; K = 212 ppm) based on measurements of Apollo pyroclastic glasses [5] assuming that these glasses represent the least fractionated, near-primary lunar mantle melts, hence, are the best proxies for capturing mantle composition. In this study, we independently validate the revised estimate by using HPE concentrations [5] to construct a conductive lunar thermal profile, or selenotherm. We compare our conductive profile to the range of valid temperatures. We demonstrate the HPE concentrations reported by [5], when used in a simple 1D spherical thermal conduction equation, yield an impossibly hot mantle with temperatures in excess of 4,000 K (Fig 1). This confirms their revised estimate is not representative of the bulk lunar mantle, and perhaps only representative of a locally enriched mantle domain. We believe that their Low-Ti avg. source estimate (Th = 0.055 ppm, Th/U=4; K/U=1700), with the least KREEP assimilation is the closest representation of the bulk lunar mantle, producing 3E-12 W/kg of heat. This estimate is close to that of the Earth (5E-12 W/kg), indicating that the bulk Earth and lunar mantles are similar in their HPE constituents. We have used the lunar mantle heat production, in conjunction with HPE estimates of the Fe-Ti-rich cumulates (high Ti-source estimate from [5]) and measurements of crustal ferroan anorthite [6], to capture the present-day lunar interior thermal state. We also present plausible internal structures that best match the mass, moment of inertia and bulk silicate Moon composition along this conductive selenotherm. [1] Wanke et al (1973) LPSC; [2] Warren et al (1979) Rev Geophy; [3] Wieczorek et al (2000) JGR; [4] Grimm (2013) JGRP; [5] Hagerty et al (2006) GCA; [6] Peplowski et al (2016) JGR.

Biogeochemical evidence of vigorous mixing in the abyssal ocean

NASA Astrophysics Data System (ADS)

Lampitt, Richard S.; Popova, Ekaterina E.; Tyrrell, Toby

2003-05-01

The metabolic activities of biological communities living at the abyssal seabed create a strong source of nutrients and a sink for oxygen. If the published estimates of vertical mixing based on instantaneous microstructure measurements are correct, near to the abyssal seabed away from rough topographic features there should be enhanced concentrations of nitrate and phosphate and depletion of oxygen. Recent data on the vertical concentration profiles of inorganic nutrients and oxygen over the bottom 1000 m of the water column (World Ocean Circulation Experiment - WOCE) provide no such evidence. It is concluded that the effective vertical mixing rates are much more vigorous than previously indicated and may even be higher than estimates of average basin scale rates based on temperature and salinity distributions. We propose that the enhanced mixing associated with rough topography influences the entire volume of the abyssal ocean on short time scales (e.g., one month - one year).

Estimated fecal coliform bacteria concentrations using near real-time continuous water-quality and streamflow data from five stream sites in Chester County, Pennsylvania, 2007–16

USGS Publications Warehouse

Senior, Lisa A.

2017-09-15

Several streams used for recreational activities, such as fishing, swimming, and boating, in Chester County, Pennsylvania, are known to have periodic elevated concentrations of fecal coliform bacteria, a type of bacteria used to indicate the potential presence of fecally related pathogens that may pose health risks to humans exposed through water contact. The availability of near real-time continuous stream discharge, turbidity, and other water-quality data for some streams in the county presents an opportunity to use surrogates to estimate near real-time concentrations of fecal coliform (FC) bacteria and thus provide some information about associated potential health risks during recreational use of streams.The U.S. Geological Survey (USGS), in cooperation with the Chester County Health Department (CCHD) and the Chester County Water Resources Authority (CCWRA), has collected discrete stream samples for analysis of FC concentrations during March–October annually at or near five gaging stations where near real-time continuous data on stream discharge, turbidity, and water temperature have been collected since 2007 (or since 2012 at 2 of the 5 stations). In 2014, the USGS, in cooperation with the CCWRA and CCHD, began to develop regression equations to estimate FC concentrations using available near real-time continuous data. Regression equations included possible explanatory variables of stream discharge, turbidity, water temperature, and seasonal factors calculated using Julian Day with base-10 logarithmic (log) transformations of selected variables.The regression equations were developed using the data from 2007 to 2015 (101–106 discrete bacteria samples per site) for three gaging stations on Brandywine Creek (West Branch Brandywine Creek at Modena, East Branch Brandywine Creek below Downingtown, and Brandywine Creek at Chadds Ford) and from 2012 to 2015 (37–38 discrete bacteria samples per site) for one station each on French Creek near Phoenixville and White Clay Creek near Strickersville. Fecal coliform bacteria data collected by USGS in 2016 (about nine samples per site) were used to validate the equations. The best-fit regression equations included log turbidity and seasonality factors computed using Julian Day as explanatory variables to estimate log FC concentrations at all five stream sites. The adjusted coefficient of determination for the equations ranged from 0.61 to 0.76, with the strength of the regression equations likely affected in part by the limited amount and variability of FC bacteria data. During summer months, the estimated and measured FC concentrations commonly were greater than the Pennsylvania Department of Environmental Protection established standards of 200 and 400 colonies per 100 milliliters for water contact from May through September at the 5 stream sites, with concentrations typically higher at 2 sites (White Clay Creek and West Branch Brandywine Creek at Modena) than at the other 3 sites. The estimated concentrations of FC bacteria during the summer months commonly were higher than measured concentrations and therefore could be considered cautious estimates of potential human-health risk. Additional water-quality data are needed to maintain and (or) improve the ability of regression equations to estimate FC concentrations by use of surrogate data.

Benefit-cost estimation for alternative drinking water maximum contaminant levels

NASA Astrophysics Data System (ADS)

Gurian, Patrick L.; Small, Mitchell J.; Lockwood, John R.; Schervish, Mark J.

2001-08-01

A simulation model for estimating compliance behavior and resulting costs at U.S. Community Water Suppliers is developed and applied to the evaluation of a more stringent maximum contaminant level (MCL) for arsenic. Probability distributions of source water arsenic concentrations are simulated using a statistical model conditioned on system location (state) and source water type (surface water or groundwater). This model is fit to two recent national surveys of source waters, then applied with the model explanatory variables for the population of U.S. Community Water Suppliers. Existing treatment types and arsenic removal efficiencies are also simulated. Utilities with finished water arsenic concentrations above the proposed MCL are assumed to select the least cost option compatible with their existing treatment from among 21 available compliance strategies and processes for meeting the standard. Estimated costs and arsenic exposure reductions at individual suppliers are aggregated to estimate the national compliance cost, arsenic exposure reduction, and resulting bladder cancer risk reduction. Uncertainties in the estimates are characterized based on uncertainties in the occurrence model parameters, existing treatment types, treatment removal efficiencies, costs, and the bladder cancer dose-response function for arsenic.

Estimation of Microbial Concentration in Food Products from Qualitative, Microbiological Test Data with the MPN Technique.

PubMed

Fujikawa, Hiroshi

2017-01-01

Microbial concentration in samples of a food product lot has been generally assumed to follow the log-normal distribution in food sampling, but this distribution cannot accommodate the concentration of zero. In the present study, first, a probabilistic study with the most probable number (MPN) technique was done for a target microbe present at a low (or zero) concentration in food products. Namely, based on the number of target pathogen-positive samples in the total samples of a product found by a qualitative, microbiological examination, the concentration of the pathogen in the product was estimated by means of the MPN technique. The effects of the sample size and the total sample number of a product were then examined. Second, operating characteristic (OC) curves for the concentration of a target microbe in a product lot were generated on the assumption that the concentration of a target microbe could be expressed with the Poisson distribution. OC curves for Salmonella and Cronobacter sakazakii in powdered formulae for infants and young children were successfully generated. The present study suggested that the MPN technique and the Poisson distribution would be useful for qualitative microbiological test data analysis for a target microbe whose concentration in a lot is expected to be low.

Concentrations and Risks of p-Dichlorobenzene in Indoor and Outdoor Air

PubMed Central

Chin, Jo-Yu; Godwin, Christopher; Jia, Chunrong; Robins, Thomas; Lewis, Toby; Parker, Edith; Max, Paul; Batterman, Stuart

2012-01-01

p-Dichlorobenzene (PDCB) is a chlorinated volatile organic compound (VOC) that can be encountered at high concentrations in buildings due to its use as pest repellent and deodorant. This study characterizes PDCB concentrations in four communities in southeast Michigan. The median concentration outside 145 homes was 0.04 µg m−3, and the median concentration inside 287 homes was 0.36 µg m−3. The distribution of indoor concentrations was extremely skewed. For example, 30% of the homes exceeded 0.91 µg m−3, which corresponds to a cancer risk level of 10−5 based on the California unit risk estimate, and 4% of homes exceeded 91 µg m−3, equivalent to a 10−3 risk level. The single highest measurement was 4,100 µg m−3. Estimates of whole house emission rates were largely consistent with chamber test results in the literature. Indoor concentrations that exceed a few µg m−3 indicate use of PDCB products. PDCB concentrations differed among households and the four cities, suggesting the importance of locational, cultural and behavioral factors in the use patterns of this chemical. The high PDCB levels found suggest the need for policies and actions to lower exposures, e.g., sales or use restrictions, improved labeling, and consumer education. PMID:22725685

Hanford Site Composite Analysis Technical Approach Description: Groundwater

DOE Office of Scientific and Technical Information (OSTI.GOV)

Budge, T. J.

The groundwater facet of the revised CA is responsible for generating predicted contaminant concentration values over the entire analysis spatial and temporal domain. These estimates will be used as part of the groundwater pathway dose calculation facet to estimate dose for exposure scenarios. Based on the analysis of existing models and available information, the P2R Model was selected as the numerical simulator to provide these estimates over the 10,000-year temporal domain of the CA. The P2R Model will use inputs from initial plume distributions, updated for a start date of 1/1/2017, and inputs from the vadose zone facet, created bymore » a tool under development as part of the ICF, to produce estimates of hydraulic head, transmissivity, and contaminant concentration over time. A recommendation of acquiring 12 computer processors and 2 TB of hard drive space is made to ensure that the work can be completed within the anticipated schedule of the revised CA.« less

Simulation of daily pesticide concentrations from watershed characteristics and monthly climatic data

USGS Publications Warehouse

Vecchia, Aldo V.; Crawford, Charles G.

2006-01-01

A time-series model was developed to simulate daily pesticide concentrations for streams in the coterminous United States. The model was based on readily available information on pesticide use, climatic variability, and watershed charac-teristics and was used to simulate concentrations for four herbicides [atrazine, ethyldipropylthiocarbamate (EPTC), metolachlor, and trifluralin] and three insecticides (carbofuran, ethoprop, and fonofos) that represent a range of physical and chemical properties, application methods, national application amounts, and areas of use in the United States. The time-series model approximates the probability distributions, seasonal variability, and serial correlation characteristics in daily pesticide concentration data from a national network of monitoring stations. The probability distribution of concentrations for a particular pesticide and station was estimated using the Watershed Regressions for Pesticides (WARP) model. The WARP model, which was developed in previous studies to estimate the probability distribution, was based on selected nationally available watershed-characteristics data, such as pesticide use and soil characteristics. Normality transformations were used to ensure that the annual percentiles for the simulated concentrations agree closely with the percentiles estimated from the WARP model. Seasonal variability in the transformed concentrations was maintained by relating the transformed concentration to precipitation and temperature data from the United States Historical Climatology Network. The monthly precipitation and temperature values were estimated for the centroids of each watershed. Highly significant relations existed between the transformed concentrations, concurrent monthly precipitation, and concurrent and lagged monthly temperature. The relations were consistent among the different pesticides and indicated the transformed concentrations generally increased as precipitation increased but the rate of increase depended on a temperature-dependent growing-season effect. Residual variability of the transformed concentrations, after removal of the effects of precipitation and temperature, was partitioned into a signal (systematic variability that is related from one day to the next) and noise (random variability that is not related from one day to the next). Variograms were used to evaluate measurement error, seasonal variability, and serial correlation of the historical data. The variogram analysis indicated substantial noise resulted, at least in part, from measurement errors (the differences between the actual concen-trations and the laboratory concentrations). The variogram analysis also indicated the presence of a strongly correlated signal, with an exponentially decaying serial correlation function and a correlation time scale (the time required for the correlation to decay to e-1 equals 0.37) that ranged from about 18 to 66 days, depending on the pesticide type. Simulated daily pesticide concentrations from the time-series model indicated the simulated concentrations for the stations located in the northeastern quadrant of the United States where most of the monitoring stations are located generally were in good agreement with the data. The model neither consistently overestimated or underestimated concentrations for streams that are located in this quadrant and the magnitude and timing of high or low concentrations generally coincided reasonably well with the data. However, further data collection and model development may be necessary to determine whether the model should be used for areas for which few historical data are available.

Dispersion of a Passive Scalar Fluctuating Plume in a Turbulent Boundary Layer. Part III: Stochastic Modelling

NASA Astrophysics Data System (ADS)

Marro, Massimo; Salizzoni, Pietro; Soulhac, Lionel; Cassiani, Massimo

2018-06-01

We analyze the reliability of the Lagrangian stochastic micromixing method in predicting higher-order statistics of the passive scalar concentration induced by an elevated source (of varying diameter) placed in a turbulent boundary layer. To that purpose we analyze two different modelling approaches by testing their results against the wind-tunnel measurements discussed in Part I (Nironi et al., Boundary-Layer Meteorology, 2015, Vol. 156, 415-446). The first is a probability density function (PDF) micromixing model that simulates the effects of the molecular diffusivity on the concentration fluctuations by taking into account the background particles. The second is a new model, named VPΓ, conceived in order to minimize the computational costs. This is based on the volumetric particle approach providing estimates of the first two concentration moments with no need for the simulation of the background particles. In this second approach, higher-order moments are computed based on the estimates of these two moments and under the assumption that the concentration PDF is a Gamma distribution. The comparisons concern the spatial distribution of the first four moments of the concentration and the evolution of the PDF along the plume centreline. The novelty of this work is twofold: (i) we perform a systematic comparison of the results of micro-mixing Lagrangian models against experiments providing profiles of the first four moments of the concentration within an inhomogeneous and anisotropic turbulent flow, and (ii) we show the reliability of the VPΓ model as an operational tool for the prediction of the PDF of the concentration.

Dispersion of a Passive Scalar Fluctuating Plume in a Turbulent Boundary Layer. Part III: Stochastic Modelling

NASA Astrophysics Data System (ADS)

Marro, Massimo; Salizzoni, Pietro; Soulhac, Lionel; Cassiani, Massimo

2018-01-01

We analyze the reliability of the Lagrangian stochastic micromixing method in predicting higher-order statistics of the passive scalar concentration induced by an elevated source (of varying diameter) placed in a turbulent boundary layer. To that purpose we analyze two different modelling approaches by testing their results against the wind-tunnel measurements discussed in Part I (Nironi et al., Boundary-Layer Meteorology, 2015, Vol. 156, 415-446). The first is a probability density function (PDF) micromixing model that simulates the effects of the molecular diffusivity on the concentration fluctuations by taking into account the background particles. The second is a new model, named VPΓ, conceived in order to minimize the computational costs. This is based on the volumetric particle approach providing estimates of the first two concentration moments with no need for the simulation of the background particles. In this second approach, higher-order moments are computed based on the estimates of these two moments and under the assumption that the concentration PDF is a Gamma distribution. The comparisons concern the spatial distribution of the first four moments of the concentration and the evolution of the PDF along the plume centreline. The novelty of this work is twofold: (i) we perform a systematic comparison of the results of micro-mixing Lagrangian models against experiments providing profiles of the first four moments of the concentration within an inhomogeneous and anisotropic turbulent flow, and (ii) we show the reliability of the VPΓ model as an operational tool for the prediction of the PDF of the concentration.

Dioxin inhalation doses from wood combustion in indoor cookfires

NASA Astrophysics Data System (ADS)

Northcross, Amanda L.; Katharine Hammond, S.; Canuz, Eduardo; Smith, Kirk R.

2012-03-01

Approximately 3 billion people worldwide rely on solid biomass fuels for household cooking and space heating, and approximately 50-60% use wood, often indoors in poorly ventilated situations. Daily exposures to high concentrations of smoke from cookstoves inside kitchens create large smoke exposures for women cooks and their small children. The smoke from burning the wood fuel contains hundred of toxic compounds, including dioxins and furans some of the most toxic compounds known to science. Health effects from exposure to dioxins include reproductive and developmental problems, damage the immune system, interference with hormones and also cause cancer. This study measured concentrations of dioxins and furans in a typical Guatemalan village home during open cookfires. Measured concentrations averaged 0.32 ± 0.07 ng m-3 over 31 fires. A Monte Carlo simulation was conducted using parameter estimates based on 8 years of research experience in the study area. The estimated total daily intake of 17 particle phase dioxin and furans for women, a 5-year-old child and a 6-month-old infant were 1.2 (S.D. = 0.4), 1.7 (S.D. = 0.7) and 2.0 (S.D. = 0.5) respectively. The 46% of babies have and estimated total daily intake (TDI) which exceed the WHO TDI guideline for dioxins and furans, 3% of women and 26% of 5-year-old children based solely inhalation of particle phase dioxins in woodsmoke from an open cooking fire. These values maybe underestimates, as they did not include gas phase concentrations or ingestion of dioxins and furans through food, which is the largest route of exposure in the developed world.

Low-level Environmental Metals and Metalloids and Incident Pregnancy Loss

PubMed Central

Buck Louis, Germaine M.; Smarr, Melissa M.; Sundaram, Rajeshwari; Steuerwald, Amy J.; Sapra, Katherine J.; Lu, Zhaohui; Parsons, Patrick J.

2017-01-01

Environmental exposure to metals and metalloids is associated with pregnancy loss in some but not all studies. We assessed arsenic, cadmium, mercury, and lead concentrations in 501 couples upon trying for pregnancy and followed them throughout pregnancy to estimate the risk of incident pregnancy loss. Using Cox proportional hazard models, we estimated hazard ratios (HR) and 95% confidence intervals (CIs) for pregnancy loss after covariate adjustment for each partner modeled individually then we jointly modeled both partners’ concentrations. Incidence of pregnancy loss was 28%. In individual partner models, the highest adjusted HRs were observed for female and male blood cadmium (HR=1.08; CI 0.81, 1.44; HR=1.09; 95% CI 0.84, 1.41, respectively). In couple based models, neither partner’s blood cadmium concentrations were associated with loss (HR=1.01; 95% CI 0.75, 1.37; HR=0.92; CI 0.68, 1.25, respectively). We observed no evidence of a significant relation between metal(loids) at environmentally relevant concentrations and pregnancy loss. PMID:28163209

Low-level environmental metals and metalloids and incident pregnancy loss.

PubMed

Buck Louis, Germaine M; Smarr, Melissa M; Sundaram, Rajeshwari; Steuerwald, Amy J; Sapra, Katherine J; Lu, Zhaohui; Parsons, Patrick J

2017-04-01

Environmental exposure to metals and metalloids is associated with pregnancy loss in some but not all studies. We assessed arsenic, cadmium, mercury, and lead concentrations in 501 couples upon trying for pregnancy and followed them throughout pregnancy to estimate the risk of incident pregnancy loss. Using Cox proportional hazard models, we estimated hazard ratios (HR) and 95% confidence intervals (CIs) for pregnancy loss after covariate adjustment for each partner modeled individually then we jointly modeled both partners' concentrations. Incidence of pregnancy loss was 28%. In individual partner models, the highest adjusted HRs were observed for female and male blood cadmium (HR=1.08; CI 0.81, 1.44; HR=1.09; 95% CI 0.84, 1.41, respectively). In couple based models, neither partner's blood cadmium concentrations were associated with loss (HR=1.01; 95% CI 0.75, 1.37; HR=0.92; CI 0.68, 1.25, respectively). We observed no evidence of a significant relation between metal(loids) at these environmentally relevant concentrations and pregnancy loss. Published by Elsevier Inc.

Chemical composition of ambient PM2. 5 over China and relationship to precursor emissions during 2005-2012

NASA Astrophysics Data System (ADS)

Geng, Guannan; Zhang, Qiang; Tong, Dan; Li, Meng; Zheng, Yixuan; Wang, Siwen; He, Kebin

2017-07-01

In this work, we presented the characteristics of PM2. 5 chemical composition over China for the period of 2005-2012 by synthesis of in situ measurement data collected from literatures and satellite-based estimates using aerosol optical depth (AOD) data and the GEOS-Chem chemical transport model. We revealed the spatiotemporal variations in PM2. 5 composition during 2005-2012 and investigated the driving forces behind the variations by examining the changes in precursor emissions using a bottom-up emission inventory. Both in situ observations and satellite-based estimates identified that secondary inorganic aerosols (i.e., sulfate, nitrate, and ammonium; SNA) ranked as the highest fraction of dust-free PM2. 5 concentrations, followed by organic matter (OM) and black carbon (BC). For instance, satellite-based estimates found that SNA, OM, and BC contributed to 59, 33, and 8 %, respectively, of national population-weighted mean dust-free PM2. 5 concentrations during 2005-2012. National population-weighted mean PM2. 5 concentration increased from 63.9 µg m-3 in 2005 to 75.2 µg m-3 in 2007 and subsequently decreased to 66.9 µg m-3 from 2007 to 2012. Variations in PM2. 5 concentrations are mainly driven by the decrease in sulfate and the increase in nitrate. Population-weighted mean sulfate concentration decreased by 2.4 % yr-1 during 2005-2012 (from 14.4 to 12.9 µg m-3), while population-weighted mean nitrate concentration increased by 3.4 % yr-1 during 2005-2012 (from 9.8 to 12.2 µg m-3), largely offsetting the decrease in sulfate concentrations. By examining the emission data from the Multi-resolution Emission Inventory for China (MEIC), we found that the changes in sulfate and nitrate concentrations were in line with the decrease in SO2 emissions and the increase in NOx emissions during the same period. The desulfurization regulation in power plants enforced around 2005 has been the primary contributor to the SO2 emission reduction since 2006. In contrast, growth of energy consumption and lack of control measures for NOx resulted in a persistent increase in NOx emissions until the installation of denitrification devices on power plants late in 2011, which began to take effect in 2012. The results of this work indicate that the synchronized abatement of emissions for multipollutants is necessary for reducing ambient PM2. 5 concentrations over China.

Marsh wrens as bioindicators of mercury in wetlands of Great Salt Lake: do blood and feathers reflect site-specific exposure risk to bird reproduction?

USGS Publications Warehouse

Hartman, C. Alex; Ackerman, Joshua T.; Herring, Garth; Isanhart, John; Herzog, Mark P.

2013-01-01

Nonlethal sampling of bird blood and feathers are among the more common ways of estimating the risk of mercury exposure to songbird reproduction. The implicit assumption is that mercury concentrations in blood or feathers of individuals captured in a given area are correlated with mercury concentrations in eggs from the same area. Yet, this assumption is rarely tested. We evaluated mercury concentrations in blood, feathers, and eggs of marsh wrens in wetlands of Great Salt Lake, Utah, and, at two spatial scales, specifically tested the assumption that mercury concentrations in blood and feather samples from birds captured in a defined area were predictive of mercury concentrations in eggs collected in the same area. Mercury concentrations in blood were not correlated with mercury concentrations in eggs collected within the same wetland unit, and were poorly correlated with mercury concentrations in eggs collected at the smaller home range spatial scale of analysis. Moreover, mercury exposure risk, as estimated via tissue concentrations, differed among wetland units depending upon whether blood or egg mercury concentrations were sampled. Mercury concentrations in feathers also were uncorrelated with mercury concentrations in eggs, and were poorly correlated with mercury concentrations in blood. These results demonstrate the potential for contrasting management actions that may be implemented based solely on the specific avian tissue that is sampled, and highlight the importance of developing avian tissues as biomonitoring tools for assessing local risk of mercury exposure to bird reproduction.

Ozone Production and Control Strategies for Southern Taiwan

NASA Astrophysics Data System (ADS)

Shiu, C.; Liu, S.; Chang, C.; Chen, J.; Chou, C. C.; Lin, C.

2006-12-01

An observation-based modeling (OBM) approach is used to estimate the ozone production efficiency and production rate of O3 (P(O3)) in southern Taiwan. The approach can also provide an indirect estimate of the concentration of OH. Measured concentrations of two aromatic hydrocarbons, i.e. ethylbenzene/m,p-xylene, are used to estimate the degree of photochemical processing and the amounts of photochemically consumed NOx and NMHCs. In addition, a one-dimensional (1d) photochemical model is used to compare with the OBM results. The average ozone production efficiency during the field campaign in Kaohsiung-Pingtung area in Fall 2003 is found to be about 5, comparable to previous works. The relationship of P(O3) with NOx is examined in detail and compared to previous studies. The derived OH concentrations from this approach are in fair agreement with values calculated from the 1d photochemical model. The relationship of total oxidants (e.g. O3+NO2) versus initial NOx and NMHCs suggests that reducing NMHCs are more effective in controlling total oxidants than reducing NOx. For O3 control, reducing NMHC is even more effective than NOx due to the NO titration effect. This observation-based approach provides a good alternative for understanding the production of ozone and formulating ozone control strategy in urban and suburban environment without measurements of peroxy radicals.

Vitamin B-12 Concentrations in Breast Milk Are Low and Are Not Associated with Reported Household Hunger, Recent Animal-Source Food, or Vitamin B-12 Intake in Women in Rural Kenya.

PubMed

Williams, Anne M; Chantry, Caroline J; Young, Sera L; Achando, Beryl S; Allen, Lindsay H; Arnold, Benjamin F; Colford, John M; Dentz, Holly N; Hampel, Daniela; Kiprotich, Marion C; Lin, Audrie; Null, Clair A; Nyambane, Geoffrey M; Shahab-Ferdows, Setti; Stewart, Christine P

2016-05-01

Breast milk vitamin B-12 concentration may be inadequate in regions in which animal-source food consumption is low or infrequent. Vitamin B-12 deficiency causes megaloblastic anemia and impairs growth and development in children. We measured vitamin B-12 in breast milk and examined its associations with household hunger, recent animal-source food consumption, and vitamin B-12 intake. In a cross-sectional substudy nested within a cluster-randomized trial assessing water, sanitation, hygiene, and nutrition interventions in Kenya, we sampled 286 women 1-6 mo postpartum. Mothers hand-expressed breast milk 1 min into a feeding after 90 min observed nonbreastfeeding. The Household Hunger Scale was used to measure hunger, food intake in the previous week was measured with the use of a food-frequency questionnaire (FFQ), and vitamin B-12 intake was estimated by using 24-h dietary recall. An animal-source food score was based on 10 items from the FFQ (range: 0-70). Breast milk vitamin B-12 concentration was measured with the use of a solid-phase competitive chemiluminescent enzyme immunoassay and was modeled with linear regression. Generalized estimating equations were used to account for correlated observations at the cluster level. Median (IQR) vitamin B-12 intake was 1.5 μg/d (0.3, 9.7 μg/d), and 60% of women consumed <2.4 μg/d, the estimated average requirement during lactation. Median (IQR) breast milk vitamin B-12 concentration was 113 pmol/L (61, 199 pmol/L); 89% had concentrations <310 pmol/L, the estimated adequate concentration. Moderate or severe hunger prevalence was 27%; the animal-source food score ranged from 0 to 30 item-d/wk. Hunger and recent animal-source food and vitamin B-12 intake were not associated with breast milk vitamin B-12 concentrations. Maternal age was negatively associated with breast milk vitamin B-12 concentrations. Most lactating Kenyan women consumed less than the estimated average requirement of vitamin B-12 and had low breast milk vitamin B-12 concentrations. We recommend interventions that improve vitamin B-12 intake in lactating Kenyan women to foster maternal health and child development. The main trial was registered at clinicaltrials.gov as NCT01704105. © 2016 American Society for Nutrition.

Sequential weighted Wiener estimation for extraction of key tissue parameters in color imaging: a phantom study

NASA Astrophysics Data System (ADS)

Chen, Shuo; Lin, Xiaoqian; Zhu, Caigang; Liu, Quan

2014-12-01

Key tissue parameters, e.g., total hemoglobin concentration and tissue oxygenation, are important biomarkers in clinical diagnosis for various diseases. Although point measurement techniques based on diffuse reflectance spectroscopy can accurately recover these tissue parameters, they are not suitable for the examination of a large tissue region due to slow data acquisition. The previous imaging studies have shown that hemoglobin concentration and oxygenation can be estimated from color measurements with the assumption of known scattering properties, which is impractical in clinical applications. To overcome this limitation and speed-up image processing, we propose a method of sequential weighted Wiener estimation (WE) to quickly extract key tissue parameters, including total hemoglobin concentration (CtHb), hemoglobin oxygenation (StO2), scatterer density (α), and scattering power (β), from wide-band color measurements. This method takes advantage of the fact that each parameter is sensitive to the color measurements in a different way and attempts to maximize the contribution of those color measurements likely to generate correct results in WE. The method was evaluated on skin phantoms with varying CtHb, StO2, and scattering properties. The results demonstrate excellent agreement between the estimated tissue parameters and the corresponding reference values. Compared with traditional WE, the sequential weighted WE shows significant improvement in the estimation accuracy. This method could be used to monitor tissue parameters in an imaging setup in real time.

Use of an exchange method to estimate the association and dissociation rate constants of cadmium complexes formed with low-molecular-weight organic acids commonly exuded by plant roots.

PubMed

Schneider, André; Nguyen, Christophe

2011-01-01

Organic acids released from plant roots can form complexes with cadmium (Cd) in the soil solution and influence metal bioavailability not only due to the nature and concentration of the complexes but also due to their lability. The lability of a complex influences its ability to buffer changes in the concentration of free ions (Cd); it depends on the association (, m mol s) and dissociation (, s) rate constants. A resin exchange method was used to estimate and (m mol s), which is the conditional estimate of depending on the calcium (Ca) concentration in solution. The constants were estimated for oxalate, citrate, and malate, three low-molecular-weight organic acids commonly exuded by plant roots and expected to strongly influence Cd uptake by plants. For all three organic acids, the and estimates were around 2.5 10 m mol s and 1.3 × 10 s, respectively. Based on the literature, these values indicate that the Cd- low-molecular-weight organic acids complexes formed between Cd and low-molecular-weight organic acids may be less labile than complexes formed with soil soluble organic matter but more labile than those formed with aminopolycarboxylic chelates. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Uncertainty Estimation for the Determination of Ni, Pb and Al in Natural Water Samples by SPE-ICP-OES

NASA Astrophysics Data System (ADS)

Ghorbani, A.; Farahani, M. Mahmoodi; Rabbani, M.; Aflaki, F.; Waqifhosain, Syed

2008-01-01

In this paper we propose uncertainty estimation for the analytical results we obtained from determination of Ni, Pb and Al by solidphase extraction and inductively coupled plasma optical emission spectrometry (SPE-ICP-OES). The procedure is based on the retention of analytes in the form of 8-hydroxyquinoline (8-HQ) complexes on a mini column of XAD-4 resin and subsequent elution with nitric acid. The influence of various analytical parameters including the amount of solid phase, pH, elution factors (concentration and volume of eluting solution), volume of sample solution, and amount of ligand on the extraction efficiency of analytes was investigated. To estimate the uncertainty of analytical result obtained, we propose assessing trueness by employing spiked sample. Two types of bias are calculated in the assessment of trueness: a proportional bias and a constant bias. We applied Nested design for calculating proportional bias and Youden method to calculate the constant bias. The results we obtained for proportional bias are calculated from spiked samples. In this case, the concentration found is plotted against the concentration added and the slop of standard addition curve is an estimate of the method recovery. Estimated method of average recovery in Karaj river water is: (1.004±0.0085) for Ni, (0.999±0.010) for Pb and (0.987±0.008) for Al.

On the hardness of high carbon ferrous martensite

NASA Astrophysics Data System (ADS)

Mola, J.; Ren, M.

2018-06-01

Due to the presence of retained austenite in martensitic steels, especially steels with high carbon concentrations, it is difficult to estimate the hardness of martensite independent of the hardness of the coexisting austenite. In the present work, the hardness of ferrous martensite with carbon concentrations in the range 0.23-1.46 mass-% was estimated by the regression analysis of hardnesses for hardened martensitic-austenitic steels containing various martensite fractions. For a given carbon concentration, the hardness of martensitic-austenitic steels was found to increase exponentially with an increase in the fraction of the martensitic constituent. The hardness of the martensitic constituent was subsequently estimated by the exponential extrapolation of the hardness of phase mixtures to 100 vol.% martensite. For martensite containing 1.46 mass-% carbon, the hardness was estimated to be 1791 HV. This estimate of martensite hardness is significantly higher than the experimental hardness of 822 HV for a phase mixture of 68 vol.% martensite and 32 vol.% austenite. The hardness obtained by exponential extrapolation is also much higher than the hardness of 1104 HV based on the rule of mixtures. The underestimated hardness of high carbon martensite in the presence of austenite is due to the non-linear dependence of hardness on the martensite fraction. The latter is also a common observation in composite materials with a soft matrix and hard reinforcing particles.

The impact of variation in scaling factors on the estimation of ...

EPA Pesticide Factsheets

Many physiologically based pharmacokinetic (PBPK) models include values for metabolic rate parameters extrapolated from in vitro metabolism studies using scaling factors such as mg of microsomal protein per gram of liver (MPPGL) and liver mass (FVL). Variation in scaling factor values impacts metabolic rate parameter estimates (Vmax) and hence estimates of internal dose used in dose response analysis. The impacts of adult human variation in MPPGL and FVL on estimates of internal dose were assessed using a human PBPK model for BDCM for several internal dose metrics for two exposure scenarios (single 0.25 liter drink of water or 10 minute shower) under plausible (5 micrograms/L) and high level (20 micrograms/L) water concentrations. For both concentrations, all internal dose metrics were changed less than 5% for the showering scenario (combined inhalation and dermal exposure). In contrast, a 27-fold variation in area under the curve for BDCM in venous blood was observed at both oral exposure concentrations, whereas total amount of BDCM metabolized in liver was relatively unchanged. This analysis demonstrates that variability in the scaling factors used for in vitro to in vivo extrapolation (IVIVE) for metabolic rate parameters can have a significant route-dependent impact on estimates of internal dose under environmentally relevant exposure scenarios. This indicates the need to evaluate both uncertainty and variability for scaling factors used for IVIVE. Sca

Change of exposure response over time and long-term risk of silicosis among a cohort of Chinese pottery workers.

PubMed

Sun, Yi; Bochmann, Frank; Morfeld, Peter; Ulm, Kurt; Liu, Yuewei; Wang, Heijiao; Yang, Lei; Chen, Weihong

2011-07-01

An analysis was conducted on a cohort of Chinese pottery workers to estimate the exposure-response relationship between respirable crystalline silica dust exposure and the incidence of radiographically diagnosed silicosis, and to estimate the long-term risk of developing silicosis until the age of 65. The cohort comprised 3,250 employees with a median follow-up duration of around 37 years. Incident cases of silicosis were identified via silicosis registries (Chinese X-ray stage I, similar to International Labor Organisation classification scheme profusion category 1/1). Individual exposure to respirable crystalline silica dust was estimated based on over 100,000 historical dust measurements. The association between dust exposure, incidence and long-time risk of silicosis was quantified by Poisson regression analysis adjusted for age and smoking. The risk of silicosis depended not only on the cumulative respirable crystalline silica dust exposures, but also on the time-dependent respirable crystalline silica dust exposure pattern (long-term average concentration, highest annual concentration ever experienced and time since first exposure). A long-term "excess" risk of silicosis of approximately 1.5/1,000 was estimated among workers with all annual respirable crystalline silica dust concentration estimates less than 0.1 mg/m(3), using the German measurement strategy. This study indicates the importance of proper consideration of exposure information in risk quantification in epidemiological studies.

On the methane paradox: Transport from shallow water zones rather than in situ methanogenesis is the major source of CH4 in the open surface water of lakes

NASA Astrophysics Data System (ADS)

Encinas Fernández, Jorge; Peeters, Frank; Hofmann, Hilmar

2016-10-01

Estimates of global methane (CH4) emissions from lakes and the contributions of different pathways are currently under debate. In situ methanogenesis linked to algae growth was recently suggested to be the major source of CH4 fluxes from aquatic systems. However, based on our very large data set on CH4 distributions within lakes, we demonstrate here that methane-enriched water from shallow water zones is the most likely source of the basin-wide mean CH4 concentrations in the surface water of lakes. Consistently, the mean surface CH4 concentrations are significantly correlated with the ratio between the surface area of the shallow water zone and the entire lake, fA,s/t, but not with the total surface area. The categorization of CH4 fluxes according to fA,s/t may therefore improve global estimates of CH4 emissions from lakes. Furthermore, CH4 concentrations increase substantially with water temperature, indicating that seasonally resolved data are required to accurately estimate annual CH4 emissions.

Estimating occupancy and abundance of stream amphibians using environmental DNA from filtered water samples

USGS Publications Warehouse

Pilliod, David S.; Goldberg, Caren S.; Arkle, Robert S.; Waits, Lisette P.

2013-01-01

Environmental DNA (eDNA) methods for detecting aquatic species are advancing rapidly, but with little evaluation of field protocols or precision of resulting estimates. We compared sampling results from traditional field methods with eDNA methods for two amphibians in 13 streams in central Idaho, USA. We also evaluated three water collection protocols and the influence of sampling location, time of day, and distance from animals on eDNA concentration in the water. We found no difference in detection or amount of eDNA among water collection protocols. eDNA methods had slightly higher detection rates than traditional field methods, particularly when species occurred at low densities. eDNA concentration was positively related to field-measured density, biomass, and proportion of transects occupied. Precision of eDNA-based abundance estimates increased with the amount of eDNA in the water and the number of replicate subsamples collected. eDNA concentration did not vary significantly with sample location in the stream, time of day, or distance downstream from animals. Our results further advance the implementation of eDNA methods for monitoring aquatic vertebrates in stream habitats.

Estimation of concentration of radionuclides in skeletal muscle from blood, based on the data from abandoned animals in Fukushima.

PubMed

Fukuda, Tomokazu

2018-06-01

The damage caused by the earthquake on 11 March, 2011 resulted in a serious nuclear accident in Japan. Due to the damage to the Fukushima Daiichi Nuclear Power Plant (FNPP), large amounts of radioactive substances were released into the environment. In particular, one of the largest safety concerns is radioactive cesium ( 134 Cs and 137 Cs). Due to the FNPP nuclear accident, a 20 km area was restricted from human activity, and various types of domestic animals were left in the zone. We collected the organs and tissues from sacrificed animals to obtain scientific data to evaluate the internal deposition of radioactive compounds. At first, we found there is a strong correlation between blood 137 Cs and organ 137 Cs with data from 44 cattle, indicating that skeletal muscle is the target organ of deposition of radioactive cesium. Second, we analyzed the relationship between blood 137 Cs and muscle 137 Cs within relatively lower radioactive concentration, suggesting that estimation of concentration of 137 Cs is possible from blood concentration of 137 Cs. Finally, we developed computer software to estimate the muscle 137 Cs concentration from blood samples. Our study contributes to the food safety of livestock products. © 2018 The Authors. Animal Science Journal published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Animal Science.

Evaluation of near field atmospheric dispersion around nuclear facilities using a Lorentzian distribution methodology.

PubMed

Hawkley, Gavin

2014-12-01

Atmospheric dispersion modeling within the near field of a nuclear facility typically applies a building wake correction to the Gaussian plume model, whereby a point source is modeled as a plane source. The plane source results in greater near field dilution and reduces the far field effluent concentration. However, the correction does not account for the concentration profile within the near field. Receptors of interest, such as the maximally exposed individual, may exist within the near field and thus the realm of building wake effects. Furthermore, release parameters and displacement characteristics may be unknown, particularly during upset conditions. Therefore, emphasis is placed upon the need to analyze and estimate an enveloping concentration profile within the near field of a release. This investigation included the analysis of 64 air samples collected over 128 wk. Variables of importance were then derived from the measurement data, and a methodology was developed that allowed for the estimation of Lorentzian-based dispersion coefficients along the lateral axis of the near field recirculation cavity; the development of recirculation cavity boundaries; and conservative evaluation of the associated concentration profile. The results evaluated the effectiveness of the Lorentzian distribution methodology for estimating near field releases and emphasized the need to place air-monitoring stations appropriately for complete concentration characterization. Additionally, the importance of the sampling period and operational conditions were discussed to balance operational feedback and the reporting of public dose.

Soil concentrations and soil-atmosphere exchange of alkylamines in a boreal Scots pine forest

NASA Astrophysics Data System (ADS)

Kieloaho, Antti-Jussi; Pihlatie, Mari; Launiainen, Samuli; Kulmala, Markku; Riekkola, Marja-Liisa; Parshintsev, Jevgeni; Mammarella, Ivan; Vesala, Timo; Heinonsalo, Jussi

2017-03-01

Alkylamines are important precursors in secondary aerosol formation in the boreal forest atmosphere. To better understand the behavior and sources of two alkylamines, dimethylamine (DMA) and diethylamine (DEA), we estimated the magnitudes of soil-atmosphere fluxes of DMA and DEA using a gradient-diffusion approximation based on measured concentrations in soil solution and in the canopy air space. The ambient air concentration of DMA used in this study was a sum of DMA and ethylamine. To compute the amine fluxes, we first estimated the soil air space concentration from the measured soil solution amine concentration using soil physical (temperature, soil water content) and chemical (pH) state variables. Then, we used the resistance analogy to account for gas transport mechanisms in the soil, soil boundary layer, and canopy air space. The resulting flux estimates revealed that the boreal forest soil with a typical long-term mean pH 5.3 is a possible source of DMA (170 ± 51 nmol m-2 day-1) and a sink of DEA (-1.2 ± 1.2 nmol m-2 day-1). We also investigated the potential role of fungi as a reservoir for alkylamines in boreal forest soil. We found high DMA and DEA concentrations both in fungal hyphae collected from field humus samples and in fungal pure cultures. The highest DMA and DEA concentrations were found in fungal strains belonging to decay and ectomycorrhizal fungal groups, indicating that boreal forest soil and, in particular, fungal biomass may be important reservoirs for these alkylamines.

Healthy neighborhoods: walkability and air pollution.

PubMed

Marshall, Julian D; Brauer, Michael; Frank, Lawrence D

2009-11-01

The built environment may influence health in part through the promotion of physical activity and exposure to pollution. To date, no studies have explored interactions between neighborhood walkability and air pollution exposure. We estimated concentrations of nitric oxide (NO), a marker for direct vehicle emissions), and ozone (O(3)) and a neighborhood walkability score, for 49,702 (89% of total) postal codes in Vancouver, British Columbia, Canada. NO concentrations were estimated from a land-use regression model, O(3) was estimated from ambient monitoring data; walkability was calculated based on geographic attributes such as land-use mix, street connectivity, and residential density. All three attributes exhibit an urban-rural gradient, with high walkability and NO concentrations, and low O(3) concentrations, near the city center. Lower-income areas tend to have higher NO concentrations and walkability and lower O(3) concentrations. Higher-income areas tend to have lower pollution (NO and O(3)). "Sweet-spot" neighborhoods (low pollution, high walkability) are generally located near but not at the city center and are almost exclusively higher income. Increased concentration of activities in urban settings yields both health costs and benefits. Our research identifies neighborhoods that do especially well (and especially poorly) for walkability and air pollution exposure. Work is needed to ensure that the poor do not bear an undue burden of urban air pollution and that neighborhoods designed for walking, bicycling, or mass transit do not adversely affect resident's exposure to air pollution. Analyses presented here could be replicated in other cities and tracked over time to better understand interactions among neighborhood walkability, air pollution exposure, and income level.

Spatially resolved estimation of ozone-related mortality in the United States under two representative concentration pathways (RCPs) and their uncertainty

DOE PAGES

Kim, Young-Min; Zhou, Ying; Gao, Yang; ...

2014-11-16

We report that the spatial pattern of the uncertainty in air pollution-related health impacts due to climate change has rarely been studied due to the lack of high-resolution model simulations, especially under the Representative Concentration Pathways (RCPs), the latest greenhouse gas emission pathways. We estimated future tropospheric ozone (O 3) and related excess mortality and evaluated the associated uncertainties in the continental United States under RCPs. Based on dynamically downscaled climate model simulations, we calculated changes in O 3 level at 12 km resolution between the future (2057 and 2059) and base years (2001–2004) under a low-to-medium emission scenario (RCP4.5)more » and a fossil fuel intensive emission scenario (RCP8.5). We then estimated the excess mortality attributable to changes in O 3. Finally, we analyzed the sensitivity of the excess mortality estimates to the input variables and the uncertainty in the excess mortality estimation using Monte Carlo simulations. O 3-related premature deaths in the continental U.S. were estimated to be 1312 deaths/year under RCP8.5 (95 % confidence interval (CI): 427 to 2198) and ₋2118 deaths/year under RCP4.5 (95 % CI: ₋3021 to ₋1216), when allowing for climate change and emissions reduction. The uncertainty of O 3-related excess mortality estimates was mainly caused by RCP emissions pathways. Finally, excess mortality estimates attributable to the combined effect of climate and emission changes on O 3 as well as the associated uncertainties vary substantially in space and so do the most influential input variables. Spatially resolved data is crucial to develop effective community level mitigation and adaptation policy.« less

Spatially resolved estimation of ozone-related mortality in the United States under two representative concentration pathways (RCPs) and their uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Young-Min; Zhou, Ying; Gao, Yang

We report that the spatial pattern of the uncertainty in air pollution-related health impacts due to climate change has rarely been studied due to the lack of high-resolution model simulations, especially under the Representative Concentration Pathways (RCPs), the latest greenhouse gas emission pathways. We estimated future tropospheric ozone (O 3) and related excess mortality and evaluated the associated uncertainties in the continental United States under RCPs. Based on dynamically downscaled climate model simulations, we calculated changes in O 3 level at 12 km resolution between the future (2057 and 2059) and base years (2001–2004) under a low-to-medium emission scenario (RCP4.5)more » and a fossil fuel intensive emission scenario (RCP8.5). We then estimated the excess mortality attributable to changes in O 3. Finally, we analyzed the sensitivity of the excess mortality estimates to the input variables and the uncertainty in the excess mortality estimation using Monte Carlo simulations. O 3-related premature deaths in the continental U.S. were estimated to be 1312 deaths/year under RCP8.5 (95 % confidence interval (CI): 427 to 2198) and ₋2118 deaths/year under RCP4.5 (95 % CI: ₋3021 to ₋1216), when allowing for climate change and emissions reduction. The uncertainty of O 3-related excess mortality estimates was mainly caused by RCP emissions pathways. Finally, excess mortality estimates attributable to the combined effect of climate and emission changes on O 3 as well as the associated uncertainties vary substantially in space and so do the most influential input variables. Spatially resolved data is crucial to develop effective community level mitigation and adaptation policy.« less

A joint data assimilation system (Tan-Tracker) to simultaneously estimate surface CO2 fluxes and 3-D atmospheric CO2 concentrations from observations

NASA Astrophysics Data System (ADS)

Tian, X.; Xie, Z.; Liu, Y.; Cai, Z.; Fu, Y.; Zhang, H.; Feng, L.

2014-12-01

We have developed a novel framework ("Tan-Tracker") for assimilating observations of atmospheric CO2 concentrations, based on the POD-based (proper orthogonal decomposition) ensemble four-dimensional variational data assimilation method (PODEn4DVar). The high flexibility and the high computational efficiency of the PODEn4DVar approach allow us to include both the atmospheric CO2 concentrations and the surface CO2 fluxes as part of the large state vector to be simultaneously estimated from assimilation of atmospheric CO2 observations. Compared to most modern top-down flux inversion approaches, where only surface fluxes are considered as control variables, one major advantage of our joint data assimilation system is that, in principle, no assumption on perfect transport models is needed. In addition, the possibility for Tan-Tracker to use a complete dynamic model to consistently describe the time evolution of CO2 surface fluxes (CFs) and the atmospheric CO2 concentrations represents a better use of observation information for recycling the analyses at each assimilation step in order to improve the forecasts for the following assimilations. An experimental Tan-Tracker system has been built based on a complete augmented dynamical model, where (1) the surface atmosphere CO2 exchanges are prescribed by using a persistent forecasting model for the scaling factors of the first-guess net CO2 surface fluxes and (2) the atmospheric CO2 transport is simulated by using the GEOS-Chem three-dimensional global chemistry transport model. Observing system simulation experiments (OSSEs) for assimilating synthetic in situ observations of surface CO2 concentrations are carefully designed to evaluate the effectiveness of the Tan-Tracker system. In particular, detailed comparisons are made with its simplified version (referred to as TT-S) with only CFs taken as the prognostic variables. It is found that our Tan-Tracker system is capable of outperforming TT-S with higher assimilation precision for both CO2 concentrations and CO2 fluxes, mainly due to the simultaneous estimation of CO2 concentrations and CFs in our Tan-Tracker data assimilation system. A experiment for assimilating the real dry-air column CO2 retrievals (XCO2) from the Japanese Greenhouse Gases Observation Satellite (GOSAT) further demonstrates its potential wide applications.

Iodine and Selenium Intakes of Postmenopausal Women in New Zealand.

PubMed

Brough, Louise; Gunn, Caroline A; Weber, Janet L; Coad, Jane; Jin, Ying; Thomson, Jasmine S; Mauze, Mathilde; Kruger, Marlena C

2017-03-09

Iodine and selenium are required for thyroid function. This study investigated iodine and selenium intakes in healthy, women aged 50-70 years ( n = 97) from three cities in the North Island of New Zealand, after mandatory fortification of bread with iodised salt. Iodine and selenium concentrations were determined in 24-h urine samples; daily intakes were extrapolated from amounts in urine (90% and 55% of daily intake, respectively). Three day diet diaries (3DDD) also estimated selenium and iodine (excluding iodised salt) intake. Median urinary iodine concentration (UIC) was 57 (41, 78) µg/L, indicating mild iodine deficiency. Estimated median iodine intake based on urine was 138 (100, 172) µg/day, below Recommended Dietary Intake (RDI) (150 µg/day) with 25% below Estimated Average Requirement (EAR) (100 µg/day). Estimated median selenium intake was 50 (36, 71) µg/day based on urine and 45 (36, 68) µg/day using 3DDD, below RDI (60 µg/day) with 49%-55% below EAR (50 µg/day). Median bread intakes were low at 1.8 (1.1, 2.7) serves/day; 25% consumed ≤1 serve/day. Although population iodine intakes improved following mandatory fortification, some had low intakes. Selenium intakes remain low. Further research should investigate thyroid function of low consumers of iodine fortified bread and/or selenium in New Zealand.

New screening approach for risk assessment of pesticides in ambient air

NASA Astrophysics Data System (ADS)

Yusà, Vicent; Coscollà, Clara; Millet, Maurice

2014-10-01

We present a novel screening approach for inhalation risk assessment of currently used pesticides (CUPs) in ambient air, based on the measurements of pesticide levels in the inhalable fraction of the particulate matter (PM10). Total concentrations in ambient air (gas + particle phases) were estimated using a theoretical model of distribution of semi-volatile organic compounds between the gas and the particulate phase based on the octanol-air partition (Koa) of each pesticide. The proposed approach was used in a pilot study conducted in a rural station in Valencia (Spain) from April through to October 2010. Twenty out of 82 analysed pesticides were detected in average concentrations ranging from 1.63 to 117.01 pg m-3. For adults, children and infants the estimated chronic inhalation risk, expressed as Hazard Quotient (HQ) was <1 for all pesticides. Likewise, the cumulative exposure for detected organophosphorus, pyrethroids and carbamates pesticides, was estimated using as metrics the Hazard Index (HI), which was less than 1 for the three families of pesticides assessed. The cancer risk estimated for the detected pesticides classified as Likely or Possible carcinogens was less than 1.15E-7 for infants. In our opinion, the screening approach proposed could be used in the monitoring and risk assessment of pesticides in ambient air.

Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine.

PubMed

Howard, Jeremy T; Ashwell, Melissa S; Baynes, Ronald E; Brooks, James D; Yeatts, James L; Maltecca, Christian

2018-01-01

In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs ( n = 198) that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK) parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope). The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite) was 0.15 (0.18) and 0.31 (0.40), respectively. For the parent drug (metabolite), the mean heritability across time was 0.27 (0.60) and 0.14 (0.44) for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug concentration across time resulted in estimates with a smaller standard error compared to models that utilized PK parameters. The current study found a low to moderate proportion of the phenotypic variation in metabolizing fenbendazole and flunixin meglumine that was explained by genetics in the current study.

Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine

PubMed Central

Howard, Jeremy T.; Ashwell, Melissa S.; Baynes, Ronald E.; Brooks, James D.; Yeatts, James L.; Maltecca, Christian

2018-01-01

In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs (n = 198) that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK) parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope). The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite) was 0.15 (0.18) and 0.31 (0.40), respectively. For the parent drug (metabolite), the mean heritability across time was 0.27 (0.60) and 0.14 (0.44) for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug concentration across time resulted in estimates with a smaller standard error compared to models that utilized PK parameters. The current study found a low to moderate proportion of the phenotypic variation in metabolizing fenbendazole and flunixin meglumine that was explained by genetics in the current study. PMID:29487615

Inputting history of heavy metals into the inland lake recorded in sediment profiles: Poyang Lake in China.

PubMed

Yuan, Guo-Li; Liu, Chen; Chen, Long; Yang, Zhongfang

2011-01-15

The temporal and spatial distribution of heavy metals (Cd, Hg, Pb, As and Cr) in Poyang Lake, the largest freshwater lake (3050 km(2)) in China, were studied based on the sedimentary profiles. For this purpose, eight sedimentary cores were selected which located at lake area, outfall of lake and the main branch rivers, respectively. High-resolution profiles with interval 2 cm were used for analyzing the concentration of metals, and the ages of them were determined by (210)Pb and (137)Cs isotopic dating. While studying the change of metals concentration with the age in profile, it is found that the concentration of them in sediments was influenced not only by the sources in history but also by the sediment types. Based on this detailed work, the inventory and burden of heavy metals per decade were estimated in lake area during the past 50 years. Significantly, rivers-contribution ratio per decade was estimated to distinguish each river's contribution of heavy metals into lake while river-flux in history and metals concentration in profiles were considered as calculating factors. So, our research provides a proof to well understand the sedimentary history and the inputting history of heavy metals from main rivers into an inland lake. Copyright © 2010 Elsevier B.V. All rights reserved.

An Ab Initio and Kinetic Monte Carlo Simulation Study of Lithium Ion Diffusion on Graphene

PubMed Central

Zhong, Kehua; Yang, Yanmin; Xu, Guigui; Zhang, Jian-Min; Huang, Zhigao

2017-01-01

The Li+ diffusion coefficients in Li+-adsorbed graphene systems were determined by combining first-principle calculations based on density functional theory with Kinetic Monte Carlo simulations. The calculated results indicate that the interactions between Li ions have a very important influence on lithium diffusion. Based on energy barriers directly obtained from first-principle calculations for single-Li+ and two-Li+ adsorbed systems, a new equation predicting energy barriers with more than two Li ions was deduced. Furthermore, it is found that the temperature dependence of Li+ diffusion coefficients fits well to the Arrhenius equation, rather than meeting the equation from electrochemical impedance spectroscopy applied to estimate experimental diffusion coefficients. Moreover, the calculated results also reveal that Li+ concentration dependence of diffusion coefficients roughly fits to the equation from electrochemical impedance spectroscopy in a low concentration region; however, it seriously deviates from the equation in a high concentration region. So, the equation from electrochemical impedance spectroscopy technique could not be simply used to estimate the Li+ diffusion coefficient for all Li+-adsorbed graphene systems with various Li+ concentrations. Our work suggests that interactions between Li ions, and among Li ion and host atoms will influence the Li+ diffusion, which determines that the Li+ intercalation dependence of Li+ diffusion coefficient should be changed and complex. PMID:28773122

Inhalation and Ingestion Intakes with Associated Dose Estimates for Level II and Level III Personnel Using Capstone Study Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Szrom, Fran; Falo, Gerald A.; Lodde, Gordon M.

2009-03-01

Depleted uranium (DU) intake rates and subsequent dose rates were estimated for personnel entering armored combat vehicles perforated with DU penetrators (level II and level III personnel) using data generated during the Capstone Depleted Uranium (DU) Aerosol Study. Inhalation intake rates and associated dose rates were estimated from cascade impactors worn by sample recovery personnel and from cascade impactors that served as area monitors. Ingestion intake rates and associated dose rates were estimated from cotton gloves worn by sample recovery personnel and from wipe test samples from the interior of vehicles perforated with large caliber DU munitions. The mean DUmore » inhalation intake rate for level II personnel ranged from 0.447 mg h-1 based on breathing zone monitor data (in and around a perforated vehicle) to 14.5 mg h-1 based on area monitor data (in a perforated vehicle). The mean DU ingestion intake rate for level II ranged from 4.8 mg h-1 to 38.9 mg h-1 based on the wipe test data including surface to glove transfer factors derived from the Capstone data. Based on glove contamination data, the mean DU ingestion intake rates for level II and level III personnel were 10.6 mg h-1 was and 1.78 mg h-1, respectively. Effective dose rates and peak kidney uranium concentration rates were calculated based on the intake rates. The peak kidney uranium concentration rate cannot be multiplied by the total exposure duration when multiple intakes occur because uranium will clear from the kidney between the exposures.« less

Reducing attenuation in exposure-response relationships by exposure modeling and grouping: the relationship between wood dust exposure and lung function.

PubMed

Teschke, Kay; Spierings, Judith; Marion, Stephen A; Demers, Paul A; Davies, Hugh W; Kennedy, Susan M

2004-12-01

In a study of wood dust exposure and lung function, we tested the effect on the exposure-response relationship of six different exposure metrics using the mean measured exposure of each subject versus the mean exposure based on various methods of grouping subjects, including job-based groups and groups based on an empirical model of the determinants of exposure. Multiple linear regression was used to examine the association between wood dust concentration and forced expiratory volume in 1s (FEV(1)), adjusting for age, sex, height, race, pediatric asthma, and smoking. Stronger point estimates of the exposure-response relationships were observed when exposures were based on increasing levels of aggregation, allowing the relationships to be found statistically significant in four of the six metrics. The strongest point estimates were found when exposures were based on the determinants of exposure model. Determinants of exposure modeling offers the potential for improvement in risk estimation equivalent to or beyond that from job-based exposure grouping.

Simultaneous estimation of transcutaneous bilirubin, hemoglobin, and melanin based on diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Abdul, Wares MD.; Ohtsu, Mizuki; Nakano, Kazuya; Haneishi, Hideaki

2018-02-01

We propose a method to estimate transcutaneous bilirubin, hemoglobin, and melanin based on the diffuse reflectance spectroscopy. In the proposed method, the Monte Carlo simulation-based multiple regression analysis for an absorbance spectrum in the visible wavelength region (460-590 nm) is used to specify the concentrations of bilirubin (Cbil), oxygenated hemoglobin (Coh), deoxygenated hemoglobin (Cdh), and melanin (Cm). Using the absorbance spectrum calculated from the measured diffuse reflectance spectrum as a response variable and the extinction coefficients of bilirubin, oxygenated hemoglobin, deoxygenated hemoglobin, and melanin, as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of bilirubin, oxygenated hemoglobin, deoxygenated hemoglobin, and melanin, are then determined from the regression coefficients using conversion vectors that are numerically deduced in advance by the Monte Carlo simulations for light transport in skin. Total hemoglobin concentration (Cth) and tissue oxygen saturation (StO2) are simply calculated from the oxygenated hemoglobin and deoxygenated hemoglobin. In vivo animal experiments with bile duct ligation in rats demonstrated that the estimated Cbil is increased after ligation of bile duct and reaches to around 20 mg/dl at 72 h after the onset of the ligation, which corresponds to the reference value of Cbil measured by a commercially available transcutaneous bilirubin meter. We also performed in vivo experiments with rats while varying the fraction of inspired oxygen (FiO2). Coh and Cdh decreased and increased, respectively, as FiO2 decreased. Consequently, StO2 was dramatically decreased. The results in this study indicate potential of the method for simultaneous evaluation of multiple chromophores in skin tissue.

Fault tree analysis for exposure to refrigerants used for automotive air conditioning in the United States.

PubMed

Jetter, J J; Forte, R; Rubenstein, R

2001-02-01

A fault tree analysis was used to estimate the number of refrigerant exposures of automotive service technicians and vehicle occupants in the United States. Exposures of service technicians can occur when service equipment or automotive air-conditioning systems leak during servicing. The number of refrigerant exposures of service technicians was estimated to be 135,000 per year. Exposures of vehicle occupants can occur when refrigerant enters passenger compartments due to sudden leaks in air-conditioning systems, leaks following servicing, or leaks caused by collisions. The total number of exposures of vehicle occupants was estimated to be 3,600 per year. The largest number of exposures of vehicle occupants was estimated for leaks caused by collisions, and the second largest number of exposures was estimated for leaks following servicing. Estimates used in the fault tree analysis were based on a survey of automotive air-conditioning service shops, the best available data from the literature, and the engineering judgement of the authors and expert reviewers from the Society of Automotive Engineers Interior Climate Control Standards Committee. Exposure concentrations and durations were estimated and compared with toxicity data for refrigerants currently used in automotive air conditioners. Uncertainty was high for the estimated numbers of exposures, exposure concentrations, and exposure durations. Uncertainty could be reduced in the future by conducting more extensive surveys, measurements of refrigerant concentrations, and exposure monitoring. Nevertheless, the analysis indicated that the risk of exposure of service technicians and vehicle occupants is significant, and it is recommended that no refrigerant that is substantially more toxic than currently available substitutes be accepted for use in vehicle air-conditioning systems, absent a means of mitigating exposure.

Nutrient and chlorophyll relations in selected streams of the New England Coastal Basins in Massachusetts and New Hampshire, June-September 2001

USGS Publications Warehouse

Riskin, Melissa L.; Deacon, J.R.; Liebman, M.L.; Robinson, K.W.

2003-01-01

The U.S. Environmental Protection Agency is developing guidance to assist states with defining nutrient criteria for rivers and streams and to better describe nutrient-algal relations. As part of this effort, 13 wadeable stream sites were selected, primarily in eastern Massachusetts, for a nutrient-assessment study during the summer of 2001. The sites represent a range of water-quality impairment conditions (reference, moderately impaired, impaired) based on state regulatory agency assessments and previously assessed nitrogen, phosphorus, and dissolved-oxygen data. In addition, a combination of open- and closed-canopy locations were sampled at six of the sites to investigate the effect of sunlight on algal growth. Samples for nutrients and for chlorophyll I from phytoplankton and periphyton were collected at all stream sites. Total nitrogen (dissolved nitrite + nitrate + total ammonia + organic nitrogen) and total phosphorus (phosphorus in an unfiltered water sample) concentrations were lowest at reference sites and highest at impaired sites. There were statistically significant differences (p < 0.05) among reference, moderately impaired, and impaired sites for total nitrogen and total phosphorus. Chlorophyll a concentrations from phytoplankton were not significantly different among site impairment designations. Concentrations of chlorophyll a from periphyton were highest at nutrient-impaired open-canopy sites. Chlorophyll a concentrations from periphyton samples were positively correlated with total nitrogen and total phosphorus at the open- and closed-canopy sites. Correlations were higher at open-canopy sites (p < 0.05, rho = 0.64 to 0.71) than at closed-canopy sites (p < 0.05, rho = 0.36 to 0.40). Statistically significant differences in the median concentrations of chlorophyll a from periphyton samples were observed between the open- and closed-canopy sites (p < 0.05). Total nitrogen and total phosphorus data from moderately impaired and impaired sites in this study exceeded the preliminary U.S. Environmental Protection Agency nutrient criteria values for the coastal region of New England. In an effort to establish more appropriate nutrient and chlorophyll criteria for streams in the New England coastal region, relations between total nitrogen and total phosphorus to periphyton chlorophyll a in wadeable streams from this study were quantified to present potential techniques for determining nutrient concentrations. Linear regression was used to estimate the total nitrogen and total phosphorus concentrations that corresponded to various chlorophyll a concentrations. On the basis of this relation, a median concentration for moderately enriched streams of 21 milligrams per square meter (mg/m2) of periphyton chlorophyll a from the literature corresponded to estimated concentrations of 1.3 milligrams per liter (mg/L) for total nitrogen and 0.12 mg/L for total phosphorus. The median concentration for periphyton chlorophyll a from the literature is similar to the 50th-percentile concentration of periphyton chlorophyll a (17 mg/m2) calculated with the data from open-canopy sites in this study. The 25th-percentile concentration for periphyton chlorophyll a of all open-canopy sites (5.2 mg/m2) and the 75th-percentile concentration for periphyton chlorophyll a of open-canopy reference sites (16 mg/m2) also were plotted to provide additional estimates and methods for developing total nitrogen and total phosphorus criteria. The 25th-percentile concentrations of total nitrogen and total phosphorus were calculated based on all sites in this study and were used as another potential criteria estimation. A concentration of 0.64 mg/L for total nitrogen and 0.030 mg/L for total phosphorus were calculated. As another possible method to develop threshold concentrations, the 10th-percentile concentrations of total nitrogen and total phosphorus were calculated based on all the impaired sites in this study. A concentration threshold of 0

Hydrogeology and water quality of the Pepacton Reservoir Watershed in southeastern New York. Part 4. Quantity and quality of ground-water and tributary contributions to stream base flow in selected main-valley reaches

USGS Publications Warehouse

Heisig, Paul M.

2004-01-01

Estimates of the quantity and quality of ground-water discharge from valley-fill deposits were calculated for nine valley reaches within the Pepacton watershed in southeastern New York in July and August of 2001. Streamflow and water quality at the upstream and downstream end of each reach and at intervening tributaries were measured under base-flow conditions and used in mass-balance equations to determine quantity and quality of ground-water discharge. These measurements and estimates define the relative magnitudes of upland (tributary inflow) and valley-fill (ground-water discharge) contributions to the main-valley streams and provide a basis for understanding the effects of hydrogeologic setting on these contributions. Estimates of the water-quality of ground-water discharge also provide an indication of the effects of road salt, manure, and human wastewater from villages on the water quality of streams that feed the Pepacton Reservoir. The most common contaminant in ground-water discharge was chloride from road salt; concentrations were less than 15 mg/L.Investigation of ground-water quality within a large watershed by measurement of stream base-flow quantity and quality followed by mass-balance calculations has benefits and drawbacks in comparison to direct ground-water sampling from wells. First, sampling streams is far less expensive than siting, installing, and sampling a watershed-wide network of wells. Second, base-flow samples represent composite samples of ground-water discharge from the most active part of the ground-water flow system across a drainage area, whereas a well network would only be representative of discrete points within local ground-water flow systems. Drawbacks to this method include limited reach selection because of unfavorable or unrepresentative hydrologic conditions, potential errors associated with a large number of streamflow and water-quality measurements, and limited ability to estimate concentrations of nonconservative constituents such as nutrients.The total gain in streamflow from the upper end to the lower end of each valley reach was positively correlated with the annual-runoff volume calculated for the drainage area of the reach. This correlation was not greatly affected by the proportions of ground-water and tributary contributions, except at two reaches that lost much of their tributary flow after the July survey. In these reaches, the gain in total streamflow showed a negative departure from this correlation.Calculated ground-water discharge exceeded the total tributary inflow in each valley reach in both surveys. Groundwater discharge, as a percentage of streamflow gain, was greatest among reaches in wide valleys (about 1,000-ft wide valley floors) that contain permeable valley fill because tributary flows were seasonally diminished or absent as a result of streambed infiltration. Tributary inflows, as a percentage of streamflow gain, were highest in reaches of narrow valleys (200-500-ft wide valley floors) with little valley fill and high annual runoff.Stream-water and ground-water quality were characterized by major-ion type as either (1) naturally occurring water types, relatively unaffected by road salt, or (2) road-salt-affected water types having elevated concentrations of chloride and sodium. The naturally occurring waters were typically the calcium-bicarbonate type, but some contained magnesium and (or) sulfate as secondary ions. Magnesium concentration in base flow is probably related to the amount of till and its carbonate content, or to the amount of lime used on cultivated fields within a drainage area. Sulfate was a defining ion only in dilute waters (with short or unreactive flow paths) with low concentrations of bicarbonate. Nearly all tributary waters were classified as naturally occurring water types.Ground-water discharge from nearly all valley reaches that contain State or county highways had elevated concentrations of chloride and sodsodium. The mean chloride concentrations of ground-water discharge--from 8 to 13 milligrams per liter--did not exceed Federal or State standards, but were about 5 times higher than naturally occurring levels. Application of road salt along a valley bottom probably affects only the shallow ground water in the area between a road and a stream. The elevated concentrations of chloride and sodium in the base-flow samples from such reaches indicate that the concentrations in the affected ground water were high enough to offset the low concentrations in all unaffected ground water entering the reach.Nutrient (nitrate and orthophosphate) concentrations in base-flow samples collected throughout the valleyreach network could not generally be used to estimate their concentrations in ground-water discharge because these constituents can be transformed or removed from water through biological uptake, transformation, or by adsorption on sediments. Base-flow samples from streams with upgradient manure sources or villages served by septic systems consistently had the highest concentrations of these nutrients.

The Diesel Exhaust in Miners Study: IV. Estimating historical exposures to diesel exhaust in underground non-metal mining facilities.

PubMed

Vermeulen, Roel; Coble, Joseph B; Lubin, Jay H; Portengen, Lützen; Blair, Aaron; Attfield, Michael D; Silverman, Debra T; Stewart, Patricia A

2010-10-01

We developed quantitative estimates of historical exposures to respirable elemental carbon (REC) for an epidemiologic study of mortality, including lung cancer, among diesel-exposed miners at eight non-metal mining facilities [the Diesel Exhaust in Miners Study (DEMS)]. Because there were no historical measurements of diesel exhaust (DE), historical REC (a component of DE) levels were estimated based on REC data from monitoring surveys conducted in 1998-2001 as part of the DEMS investigation. These values were adjusted for underground workers by carbon monoxide (CO) concentration trends in the mines derived from models of historical CO (another DE component) measurements and DE determinants such as engine horsepower (HP; 1 HP = 0.746 kW) and mine ventilation. CO was chosen to estimate historical changes because it was the most frequently measured DE component in our study facilities and it was found to correlate with REC exposure. Databases were constructed by facility and year with air sampling data and with information on the total rate of airflow exhausted from the underground operations in cubic feet per minute (CFM) (1 CFM = 0.0283 m³ min⁻¹), HP of the diesel equipment in use (ADJ HP), and other possible determinants. The ADJ HP purchased after 1990 (ADJ HP₁₉₉₀(+)) was also included to account for lower emissions from newer, cleaner engines. Facility-specific CO levels, relative to those in the DEMS survey year for each year back to the start of dieselization (1947-1967 depending on facility), were predicted based on models of observed CO concentrations and log-transformed (Ln) ADJ HP/CFM and Ln(ADJ HP₁₉₉₀(+)). The resulting temporal trends in relative CO levels were then multiplied by facility/department/job-specific REC estimates derived from the DEMS surveys personal measurements to obtain historical facility/department/job/year-specific REC exposure estimates. The facility-specific temporal trends of CO levels (and thus the REC estimates) generated from these models indicated that CO concentrations had been generally greater in the past than during the 1998-2001 DEMS surveys, with the highest levels ranging from 100 to 685% greater (median: 300%). These levels generally occurred between 1970 and the early 1980s. A comparison of the CO facility-specific model predictions with CO air concentration measurements from a 1976-1977 survey external to the modeling showed that our model predictions were slightly lower than those observed (median relative difference of 29%; range across facilities: 49 to -25%). In summary, we successfully modeled past CO concentration levels using selected determinants of DE exposure to derive retrospective estimates of REC exposure. The results suggested large variations in REC exposure levels both between and within the underground operations of the facilities and over time. These REC exposure estimates were in a plausible range and were used in the investigation of exposure-response relationships in epidemiologic analyses.

Optically-derived estimates of phytoplankton size class and taxonomic group biomass in the Eastern Subarctic Pacific Ocean

NASA Astrophysics Data System (ADS)

Zeng, Chen; Rosengard, Sarah Z.; Burt, William; Peña, M. Angelica; Nemcek, Nina; Zeng, Tao; Arrigo, Kevin R.; Tortell, Philippe D.

2018-06-01

We evaluate several algorithms for the estimation of phytoplankton size class (PSC) and functional type (PFT) biomass from ship-based optical measurements in the Subarctic Northeast Pacific Ocean. Using underway measurements of particulate absorption and backscatter in surface waters, we derived estimates of PSC/PFT based on chlorophyll-a concentrations (Chl-a), particulate absorption spectra and the wavelength dependence of particulate backscatter. Optically-derived [Chl-a] and phytoplankton absorption measurements were validated against discrete calibration samples, while the derived PSC/PFT estimates were validated using size-fractionated Chl-a measurements and HPLC analysis of diagnostic photosynthetic pigments (DPA). Our results showflo that PSC/PFT algorithms based on [Chl-a] and particulate absorption spectra performed significantly better than the backscatter slope approach. These two more successful algorithms yielded estimates of phytoplankton size classes that agreed well with HPLC-derived DPA estimates (RMSE = 12.9%, and 16.6%, respectively) across a range of hydrographic and productivity regimes. Moreover, the [Chl-a] algorithm produced PSC estimates that agreed well with size-fractionated [Chl-a] measurements, and estimates of the biomass of specific phytoplankton groups that were consistent with values derived from HPLC. Based on these results, we suggest that simple [Chl-a] measurements should be more fully exploited to improve the classification of phytoplankton assemblages in the Northeast Pacific Ocean.

Ground-based radar monitoring of volcanic ash: a novel approach for the estimation of the bulk microphysical parameters

NASA Astrophysics Data System (ADS)

Vulpiani, Gianfranco; Ripepe, Maurizio

2017-04-01

The detection and quantitative retrieval of ash plumes is of significant interest due to the environmental, climatic, and socioeconomic effects of ash fallout which might cause hardship and damages in areas surrounding volcanoes, representing a serious hazard to aircrafts. Real-time monitoring of such phenomena is crucial for initializing ash dispersion models. Ground-based and space-borne remote sensing observations provide essential information for scientific and operational applications. Satellite visible-infrared radiometric observations from geostationary platforms are usually exploited for long-range trajectory tracking and for measuring low-level eruptions. Their imagery is available every 10-30 min and suffers from a relatively poor spatial resolution. Moreover, the field of view of geostationary radiometric measurements may be blocked by water and ice clouds at higher levels and the observations' overall utility is reduced at night. Ground-based microwave weather radars may represent an important tool for detecting and, to a certain extent, mitigating the hazards presented by ash clouds. The possibility of monitoring in all weather conditions at a fairly high spatial resolution (less than a few hundred meters) and every few minutes after the eruption is the major advantage of using ground-based microwave radar systems. Ground-based weather radar systems can also provide data for estimating the ash volume, total mass, and height of eruption clouds. Previous methodological studies have investigated the possibility of using ground-based single- and dual-polarization radar system for the remote sensing of volcanic ash cloud. In the present work, methodology was revised to overcome some limitations related to the assumed microphysics. New scattering simulations based on the T-matrix solution technique were used to set up the parametric algorithms adopted to estimate the mass concentration and ash mean diameter. Furthermore, because quantitative estimation of the erupted materials in the proximity of the volcano's vent is crucial for initializing transportation models, a novel methodology for estimating a volcano eruption's mass discharge rate based on the combination of radar and a thermal camera was developed. We show how it is possible to calculate the mass flow using radar-derived ash concentration and particle diameter at the base of the eruption column using the exit velocity estimated by the thermal camera. The proposed procedure was tested on four Etna eruption episodes that occurred in December 2015 as observed by the available network of C and X band radar systems. The results are congruent with other independent methodologies and observations . The agreement between the total erupted mass derived by the retrieved MDR and the plume concentration can be considered as a self-consistent methodological assessment. Interestingly, the analysis of the polarimetric radar observations allowed us to derive some features of the ash plume, including the size of the eruption column and the height of the gas thrust region.

ESTIMATION OF EXPOSURE DOSES FOR THE SAFE MANAGEMENT OF NORM WASTE DISPOSAL.

PubMed

Jeong, Jongtae; Ko, Nak Yul; Cho, Dong-Keun; Baik, Min Hoon; Yoon, Ki-Hoon

2018-03-16

Naturally occurring radioactive materials (NORM) wastes with different radiological characteristics are generated in several industries. The appropriate options for NORM waste management including disposal options should be discussed and established based on the act and regulation guidelines. Several studies calculated the exposure dose and mass of NORM waste to be disposed in landfill site by considering the activity concentration level and exposure dose. In 2012, the Korean government promulgated an act on the safety control of NORM around living environments to protect human health and the environment. For the successful implementation of this act, we suggest a reference design for a landfill for the disposal of NORM waste. Based on this reference landfill, we estimate the maximum exposure doses and the relative impact of each pathway to exposure dose for three scenarios: a reference scenario, an ingestion pathway exclusion scenario, and a low leach rate scenario. Also, we estimate the possible quantity of NORM waste disposal into a landfill as a function of the activity concentration level of U series, Th series and 40K and two kinds of exposure dose levels, 1 and 0.3 mSv/y. The results of this study can be used to support the establishment of technical bases of the management strategy for the safe disposal of NORM waste.

How important is drinking water exposure for the risks of engineered nanoparticles to consumers?

PubMed

Tiede, Karen; Hanssen, Steffen Foss; Westerhoff, Paul; Fern, Gordon J; Hankin, Steven M; Aitken, Robert J; Chaudhry, Qasim; Boxall, Alistair B A

2016-01-01

This study explored the potential for engineered nanoparticles (ENPs) to contaminate the UK drinking water supplies and established the significance of the drinking water exposure route compared to other routes of human exposure. A review of the occurrence and quantities of ENPs in different product types on the UK market as well as release scenarios, their possible fate and behaviour in raw water and during drinking water treatment was performed. Based on the available data, all the ENPs which are likely to reach water sources were identified and categorized. Worst case concentrations of ENPs in raw water and treated drinking water, using a simple exposure model, were estimated and then qualitatively compared to available estimates for human exposure through other routes. A range of metal, metal oxide and organic-based ENPs were identified that have the potential to contaminate drinking waters. Worst case predicted concentrations in drinking waters were in the low- to sub-µg/l range and more realistic estimates were tens of ng/l or less. For the majority of product types, human exposure via drinking water was predicted to be less important than exposure via other routes. The exceptions were some clothing materials, paints and coatings and cleaning products containing Ag, Al, TiO2, Fe2O3 ENPs and carbon-based materials.

Water age and stream solute dynamics at the Hubbard Brook Experimental Forest (US)

NASA Astrophysics Data System (ADS)

Botter, Gianluca; Benettin, Paolo; McGuire, Kevin; Rinaldo, Andrea

2016-04-01

The contribution discusses experimental and modeling results from a headwater catchment at the Hubbard Brook Experimental Forest (New Hampshire, USA) to explore the link between stream solute dynamics and water age. A theoretical framework based on water age dynamics, which represents a general basis for characterizing solute transport at the catchment scale, is used to model both conservative and weathering-derived solutes. Based on the available information about the hydrology of the site, an integrated transport model was developed and used to estimate the relevant hydrochemical fluxes. The model was designed to reproduce the deuterium content of streamflow and allowed for the estimate of catchment water storage and dynamic travel time distributions (TTDs). Within this framework, dissolved silicon and sodium concentration in streamflow were simulated by implementing first-order chemical kinetics based explicitly on dynamic TTD, thus upscaling local geochemical processes to catchment scale. Our results highlight the key role of water stored within the subsoil glacial material in both the short-term and long-term solute circulation at Hubbard Brook. The analysis of the results provided by the calibrated model allowed a robust estimate of the emerging concentration-discharge relationship, streamflow age distributions (including the fraction of event water) and storage size, and their evolution in time due to hydrologic variability.

Environmental risk assessment of three selective serotonin reuptake inhibitors in the aquatic environment: a case study including a cocktail scenario.

PubMed

Styrishave, Bjarne; Halling-Sørensen, Bent; Ingerslev, Flemming

2011-01-01

We present an environmental risk assessment of three selective serotonin reuptake inhibitors (SSRIs; citalopram, sertraline, and fluoxetine) in the aquatic environment based on two case scenarios. Abiotic and biotic degradation experiments and sorption estimates were used to predict environmental concentrations of three SSRIs from the wastewater of two psychiatric hospitals, the primary sector, and wastewater entering and leaving wastewater treatment plants (WWTPs). Assuming a sewage treatment retention time of 8 h, abiotic degradation was low, for all three SSRIs inhibitors, ranging between 0 and 2% for hydrolysis and 0 and 6% for photolysis. The biodegradation was also slow, ranging from 0 to 3% within an 8-h period. In untreated sewage, citalopram (CIT) and sertraline (SER) concentrations may be high enough to exert effects on the aquatic biota (CIT: 0.19-10.3 µg/L; SER: 0.14-17.1 µg/L). Removal of the pharmaceuticals is due primarily to sorption in the WWTP. Sertraline was estimated to have the highest concentrations in the sewage effluents, 4.4 and 19.9 ng/L for the two cases, respectively. In treated wastewater, individual SSRI concentrations are probably too low to exert effects on biota. By using concentration addition, a cocktail exposure scenario was estimated. The predicted concentration in the biota calculated from the cocktail effect was 0.05 and 0.16 nmol/g for the two cases, respectively, and SER was found to give the highest contribution to this cocktail effect. The results indicate that the concentrations in the wastewater effluents are one to two orders of magnitude lower than the concentrations likely to cause an effect in the aquatic biota. © 2010 SETAC.

Retrieval of Atmospheric Particulate Matter Using Satellite Data Over Central and Eastern China

NASA Astrophysics Data System (ADS)

Chen, G. L.; Guang, J.; Li, Y.; Che, Y. H.; Gong, S. Q.

2018-04-01

Fine particulate matter (PM2.5) is a particle cluster with diameters less than or equal to 2.5 μm. Over the past few decades, regional air pollution composed of PM2.5 has frequently occurred over Central and Eastern China. In order to estimate the concentration, distribution and other properties of PM2.5, the general retrieval models built by establishing the relationship between aerosol optical depth (AOD) and PM2.5 has been widely used in many studies, including experimental models via statistics analysis and physical models with certain physical mechanism. The statistical experimental models can't be extended to other areas or historical period due to its dependence on the ground-based observations and necessary auxiliary data, which limits its further application. In this paper, a physically based model is applied to estimate the concentration of PM2.5 over Central and Eastern China from 2007 to 2016. The ground-based PM2.5 measurements were used to be as reference data to validate our retrieval results. Then annual variation and distribution of PM2.5 concentration in the Central and Eastern China was analysed. Results shows that the annual average PM2.5 show a trend of gradually increasing and then decreasing during 2007-2016, with the highest value in 2011.

Manufacturing cost analysis of a parabolic dish concentrator (General Electric design) for solar thermal electric power systems in selected production volumes

NASA Technical Reports Server (NTRS)

1981-01-01

The manufacturing cost of a General Electric 12 meter diameter concentrator was estimated. This parabolic dish concentrator for solar thermal system was costed in annual production volumes of 100 - 1,000 - 5,000 - 10,000 - 50,000 100,000 - 400,000 and 1,000,000 units. Presented for each volume are the costs of direct labor, material, burden, tooling, capital equipment and buildings. Also presented is the direct labor personnel and factory space requirements. All costs are based on early 1981 economics.

A simulation-based approach for estimating premining water quality: Red Mountain Creek, Colorado

USGS Publications Warehouse

Runkel, Robert L.; Kimball, Briant A; Walton-Day, Katherine; Verplanck, Philip L.

2007-01-01

Regulatory agencies are often charged with the task of setting site-specific numeric water quality standards for impaired streams. This task is particularly difficult for streams draining highly mineralized watersheds with past mining activity. Baseline water quality data obtained prior to mining are often non-existent and application of generic water quality standards developed for unmineralized watersheds is suspect given the geology of most watersheds affected by mining. Various approaches have been used to estimate premining conditions, but none of the existing approaches rigorously consider the physical and geochemical processes that ultimately determine instream water quality. An approach based on simulation modeling is therefore proposed herein. The approach utilizes synoptic data that provide spatially-detailed profiles of concentration, streamflow, and constituent load along the study reach. This field data set is used to calibrate a reactive stream transport model that considers the suite of physical and geochemical processes that affect constituent concentrations during instream transport. A key input to the model is the quality and quantity of waters entering the study reach. This input is based on chemical analyses available from synoptic sampling and observed increases in streamflow along the study reach. Given the calibrated model, additional simulations are conducted to estimate premining conditions. In these simulations, the chemistry of mining-affected sources is replaced with the chemistry of waters that are thought to be unaffected by mining (proximal, premining analogues). The resultant simulations provide estimates of premining water quality that reflect both the reduced loads that were present prior to mining and the processes that affect these loads as they are transported downstream. This simulation-based approach is demonstrated using data from Red Mountain Creek, Colorado, a small stream draining a heavily-mined watershed. Model application to the premining problem for Red Mountain Creek is based on limited field reconnaissance and chemical analyses; additional field work and analyses may be needed to develop definitive, quantitative estimates of premining water quality.

Effect of blood flow on near-the-wall mass transport of drugs and other bioactive agents: a simple formula to estimate boundary layer concentrations.

PubMed

Rugonyi, Sandra

2008-04-01

Transport of bioactive agents through the blood is essential for cardiovascular regulatory processes and drug delivery. Bioactive agents and other solutes infused into the blood through the wall of a blood vessel or released into the blood from an area in the vessel wall spread downstream of the infusion/release region and form a thin boundary layer in which solute concentration is higher than in the rest of the blood. Bioactive agents distributed along the vessel wall affect endothelial cells and regulate biological processes, such as thrombus formation, atherogenesis, and vascular remodeling. To calculate the concentration of solutes in the boundary layer, researchers have generally used numerical simulations. However, to investigate the effect of blood flow, infusion rate, and vessel geometry on the concentration of different solutes, many simulations are needed, leading to a time-consuming effort. In this paper, a relatively simple formula to quantify concentrations in a tube downstream of an infusion/release region is presented. Given known blood-flow rates, tube radius, solute diffusivity, and the length of the infusion region, this formula can be used to quickly estimate solute concentrations when infusion rates are known or to estimate infusion rates when solute concentrations at a point downstream of the infusion region are known. The developed formula is based on boundary layer theory and physical principles. The formula is an approximate solution of the advection-diffusion equations in the boundary layer region when solute concentration is small (dilute solution), infusion rate is modeled as a mass flux, and there is no transport of solute through the wall or chemical reactions downstream of the infusion region. Wall concentrations calculated using the formula developed in this paper were compared to the results from finite element models. Agreement between the results was within 10%. The developed formula could be used in experimental procedures to evaluate drug efficacy, in the design of drug-eluting stents, and to calculate rates of release of bioactive substances at active surfaces using downstream concentration measurements. In addition to being simple and fast to use, the formula gives accurate quantifications of concentrations and infusion rates under steady-state and oscillatory flow conditions, and therefore can be used to estimate boundary layer concentrations under physiological conditions.

Baseline toxicity of a chlorobenzene mixture and total body residues measured and estimated with solid-phase microextraction.

PubMed

Leslie, Heather A; Hermens, Joop L M; Kraak, Michiel H S

2004-08-01

Body residues of compounds with a narcotic mode of action that exceed critical levels result in baseline toxicity in organisms. Previous studies have shown that internal concentrations in organisms also can be estimated by way of passive sampling. In this experiment, solid-phase microextraction (SPME) fibers were used as a tool to estimate the body residues, which were then compared to measured levels. Past application of SPME fibers in the assessment of toxicity risk of samples has focused on separate exposure of fibers and organisms, often necessitated by the amount of agitation needed in order to achieve steady state in the fibers within a convenient time period. Uptake kinetic studies have shown that in SPME fibers with thin coatings, equilibrium concentrations can be reached without agitation within the time frame of a toxicity test. In contrast to toxicity experiments to date, the SPME fibers in the current study were exposed concomitantly to the test water with the organisms, ensuring an exposure under the exact same conditions. Fibers and two aquatic invertebrate species were exposed to a mixture of four chlorobenzenes with a narcotic mode of action. The total body residue of these compounds in the organisms was determined, as was the acute toxicity resulting from the accumulation. The total body residues of both species were correlated to the total concentrations in SPME fibers. It was concluded that toxicity could be predicted based on total body residue (TBR) estimates from fiber concentrations.

Detection and Estimation of 2-D Distributions of Greenhouse Gas Source Concentrations and Emissions over Complex Urban Environments and Industrial Sites

NASA Astrophysics Data System (ADS)

Zaccheo, T. S.; Pernini, T.; Dobler, J. T.; Blume, N.; Braun, M.

2017-12-01

This work highlights the use of the greenhouse-gas laser imaging tomography experiment (GreenLITETM) data in conjunction with a sparse tomography approach to identify and quantify both urban and industrial sources of CO2 and CH4. The GreenLITETM system provides a user-defined set of time-sequenced intersecting chords or integrated column measurements at a fixed height through a quasi-horizontal plane of interest. This plane, with unobstructed views along the lines of sight, may range from complex industrial facilities to a small city scale or urban sector. The continuous time phased absorption measurements are converted to column concentrations and combined with a plume based model to estimate the 2-D distribution of gas concentration over extended areas ranging from 0.04-25 km2. Finally, these 2-D maps of concentration are combined with ancillary meteorological and atmospheric data to identify potential emission sources and provide first order estimates of their associated fluxes. In this presentation, we will provide a brief overview of the systems and results from both controlled release experiments and a long-term system deployment in Paris, FR. These results provide a quantitative assessment of the system's ability to detect and estimate CO2 and CH4 sources, and demonstrate its ability to perform long-term autonomous monitoring and quantification of either persistent or sporadic emissions that may have both health and safety as well as environmental impacts.

Characterization and simulation of fate and transport of selected volatile organic compounds in the vicinities of the Hadnot Point Industrial Area and landfill: Chapter A Supplement 6 in Analyses and historical reconstruction of groundwater flow, contaminant fate and transport, and distribution of drinking water within the service areas of the Hadnot Point and Holcomb Boulevard Water Treatment Plants and vicinities, U.S. Marine Corps Base Camp Lejeune, North Carolina

USGS Publications Warehouse

Jones, L. Elliott; Suárez-Soto, René J.; Anderson, Barbara A.; Maslia, Morris L.

2013-01-01

This supplement of Chapter A (Supplement 6) describes the reconstruction (i.e. simulation) of historical concentrations of tetrachloroethylene (PCE), trichloroethylene (TCE), and benzene3 in production wells supplying water to the Hadnot Base (USMCB) Camp Lejeune, North Carolina (Figure S6.1). A fate and transport model (i.e., MT3DMS [Zheng and Wang 1999]) was used to simulate contaminant migration from source locations through the groundwater system and to estimate mean contaminant concentrations in water withdrawn from water-supply wells in the vicinity of the Hadnot Point Industrial Area (HPIA) and the Hadnot Point landfill (HPLF) area.4 The reconstructed contaminant concentrations were subsequently input into a flow-weighted, materials mass balance (mixing) model (Masters 1998) to estimate monthly mean concentrations of the contaminant in finished water 5 at the HPWTP (Maslia et al. 2013). The calibrated fate and transport models described herein were based on and used groundwater velocities derived from groundwater-flow models that are described in Suárez-Soto et al. (2013). Information data pertinent to historical operations of water-supply wells are described in Sautner et al. (2013) and Telci et al. (2013).

Estimation of the residual bromine concentration after disinfection of cooling water by statistical evaluation.

PubMed

Megalopoulos, Fivos A; Ochsenkuehn-Petropoulou, Maria T

2015-01-01

A statistical model based on multiple linear regression is developed, to estimate the bromine residual that can be expected after the bromination of cooling water. Make-up water sampled from a power plant in the Greek territory was used for the creation of the various cooling water matrices under investigation. The amount of bromine fed to the circuit, as well as other important operational parameters such as concentration at the cooling tower, temperature, organic load and contact time are taken as the independent variables. It is found that the highest contribution to the model's predictive ability comes from cooling water's organic load concentration, followed by the amount of bromine fed to the circuit, the water's mean temperature, the duration of the bromination period and finally its conductivity. Comparison of the model results with the experimental data confirms its ability to predict residual bromine given specific bromination conditions.

An ultrasound-guided fluorescence tomography system: design and specification

NASA Astrophysics Data System (ADS)

D'Souza, Alisha V.; Flynn, Brendan P.; Kanick, Stephen C.; Torosean, Sason; Davis, Scott C.; Maytin, Edward V.; Hasan, Tayyaba; Pogue, Brian W.

2013-03-01

An ultrasound-guided fluorescence molecular tomography system is under development for in vivo quantification of Protoporphyrin IX (PpIX) during Aminolevulinic Acid - Photodynamic Therapy (ALA-PDT) of Basal Cell Carcinoma. The system is designed to combine fiber-based spectral sampling of PPIX fluorescence emission with co-registered ultrasound images to quantify local fluorophore concentration. A single white light source is used to provide an estimate of the bulk optical properties of tissue. Optical data is obtained by sequential illumination of a 633nm laser source at 4 linear locations with parallel detection at 5 locations interspersed between the sources. Tissue regions from segmented ultrasound images, optical boundary data, white light-informed optical properties and diffusion theory are used to estimate the fluorophore concentration in these regions. Our system and methods allow interrogation of both superficial and deep tissue locations up to PpIX concentrations of 0.025ug/ml.

Reduction of shading-derived artifacts in skin chromophore imaging without measurements or assumptions about the shape of the subject

NASA Astrophysics Data System (ADS)

Yoshida, Kenichiro; Nishidate, Izumi; Ojima, Nobutoshi; Iwata, Kayoko

2014-01-01

To quantitatively evaluate skin chromophores over a wide region of curved skin surface, we propose an approach that suppresses the effect of the shading-derived error in the reflectance on the estimation of chromophore concentrations, without sacrificing the accuracy of that estimation. In our method, we use multiple regression analysis, assuming the absorbance spectrum as the response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as the predictor variables. The concentrations of melanin and total hemoglobin are determined from the multiple regression coefficients using compensation formulae (CF) based on the diffuse reflectance spectra derived from a Monte Carlo simulation. To suppress the shading-derived error, we investigated three different combinations of multiple regression coefficients for the CF. In vivo measurements with the forearm skin demonstrated that the proposed approach can reduce the estimation errors that are due to shading-derived errors in the reflectance. With the best combination of multiple regression coefficients, we estimated that the ratio of the error to the chromophore concentrations is about 10%. The proposed method does not require any measurements or assumptions about the shape of the subjects; this is an advantage over other studies related to the reduction of shading-derived errors.

Estimating the acute health effects of coarse particulate matter accounting for exposure measurement error.

PubMed

Chang, Howard H; Peng, Roger D; Dominici, Francesca

2011-10-01

In air pollution epidemiology, there is a growing interest in estimating the health effects of coarse particulate matter (PM) with aerodynamic diameter between 2.5 and 10 μm. Coarse PM concentrations can exhibit considerable spatial heterogeneity because the particles travel shorter distances and do not remain suspended in the atmosphere for an extended period of time. In this paper, we develop a modeling approach for estimating the short-term effects of air pollution in time series analysis when the ambient concentrations vary spatially within the study region. Specifically, our approach quantifies the error in the exposure variable by characterizing, on any given day, the disagreement in ambient concentrations measured across monitoring stations. This is accomplished by viewing monitor-level measurements as error-prone repeated measurements of the unobserved population average exposure. Inference is carried out in a Bayesian framework to fully account for uncertainty in the estimation of model parameters. Finally, by using different exposure indicators, we investigate the sensitivity of the association between coarse PM and daily hospital admissions based on a recent national multisite time series analysis. Among Medicare enrollees from 59 US counties between the period 1999 and 2005, we find a consistent positive association between coarse PM and same-day admission for cardiovascular diseases.

Population pharmacokinetics and maximum a posteriori probability Bayesian estimator of abacavir: application of individualized therapy in HIV-infected infants and toddlers.

PubMed

Zhao, Wei; Cella, Massimo; Della Pasqua, Oscar; Burger, David; Jacqz-Aigrain, Evelyne

2012-04-01

Abacavir is used to treat HIV infection in both adults and children. The recommended paediatric dose is 8 mg kg(-1) twice daily up to a maximum of 300 mg twice daily. Weight was identified as the central covariate influencing pharmacokinetics of abacavir in children. A population pharmacokinetic model was developed to describe both once and twice daily pharmacokinetic profiles of abacavir in infants and toddlers. Standard dosage regimen is associated with large interindividual variability in abacavir concentrations. A maximum a posteriori probability Bayesian estimator of AUC(0-) (t) based on three time points (0, 1 or 2, and 3 h) is proposed to support area under the concentration-time curve (AUC) targeted individualized therapy in infants and toddlers. To develop a population pharmacokinetic model for abacavir in HIV-infected infants and toddlers, which will be used to describe both once and twice daily pharmacokinetic profiles, identify covariates that explain variability and propose optimal time points to optimize the area under the concentration-time curve (AUC) targeted dosage and individualize therapy. The pharmacokinetics of abacavir was described with plasma concentrations from 23 patients using nonlinear mixed-effects modelling (NONMEM) software. A two-compartment model with first-order absorption and elimination was developed. The final model was validated using bootstrap, visual predictive check and normalized prediction distribution errors. The Bayesian estimator was validated using the cross-validation and simulation-estimation method. The typical population pharmacokinetic parameters and relative standard errors (RSE) were apparent systemic clearance (CL) 13.4 () h−1 (RSE 6.3%), apparent central volume of distribution 4.94 () (RSE 28.7%), apparent peripheral volume of distribution 8.12 () (RSE14.2%), apparent intercompartment clearance 1.25 () h−1 (RSE 16.9%) and absorption rate constant 0.758 h−1 (RSE 5.8%). The covariate analysis identified weight as the individual factor influencing the apparent oral clearance: CL = 13.4 × (weight/12)1.14. The maximum a posteriori probability Bayesian estimator, based on three concentrations measured at 0, 1 or 2, and 3 h after drug intake allowed predicting individual AUC0–t. The population pharmacokinetic model developed for abacavir in HIV-infected infants and toddlers accurately described both once and twice daily pharmacokinetic profiles. The maximum a posteriori probability Bayesian estimator of AUC(0-) (t) was developed from the final model and can be used routinely to optimize individual dosing. © 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.

Gas hydrate concentration estimated from P- and S-wave velocities

NASA Astrophysics Data System (ADS)

Carcione, J. M.; Gei, D.

2003-04-01

We estimate the concentration of gas hydrate at the Mallik 2L-38 research site, Mackenzie Delta, Canada, using P- and S-wave velocities obtained from well logging and vertical seismic profiles (VSP). The theoretical velocities are obtained from a poro-viscoelastic model based on a Biot-type approach. It considers the existence of two solids (grains and gas hydrate) and a fluid mixture and is based on the assumption that hydrate fills the pore space and shows interconnection. The moduli of the matrix formed by gas hydrate are obtained from the percolation model described by Leclaire et al., (1994). An empirical mixing law introduced by Brie et al., (1995) provides the effective bulk modulus of the fluid phase, giving Wood's modulus at low frequency and Voigt's modulus at high frequencies. The dry-rock moduli are estimated from the VSP profile where the rock is assumed to be fully saturated with water, and the quality factors are obtained from the velocity dispersion observed between the sonic and VSP velocities. Attenuation is described by using a constant-Q model for the dry rock moduli. The amount of dissipation is estimated from the difference between the seismic velocities and the sonic-log velocities. We estimate the amount of gas hydrate by fitting the sonic-log and seismic velocities to the theoretical velocities, using the concentration of gas hydrate as fitting parameter. We obtain hydrate concentrations up to 75 %, average values of 43 and 47 % from the VSP P- and S-wave velocities, respectively, and 47 and 42 % from the sonic-log P- and S-wave velocities, respectively. These averages are computed from 897 to 1110 m, excluding the zones where there is no gas hydrate. We found that modeling attenuation is important to obtain reliable results. largeReferences} begin{description} Brie, A., Pampuri, F., Marsala A.F., Meazza O., 1995, Shear Sonic Interpretation in Gas-Bearing Sands, SPE Annual Technical Conference and Exhibition, Dallas, 1995. Carcione, J.M. and Gei, D., Gas hydrate concentration estimated from P- and S-wave velocities at the Mallik 2L-38 research well, Mackenzie Delta, Canada, submitted to Geophysics. Gei, D. and Carcione, J.M., Acoustic properties of sediments saturated with gas hydrate, free gas and water, Geophysical Prospecting, in press. Leclarie, Ph., Cohen-Tenoudji, F., and Aguirre-Puente, J., 1994, Extension of Biot's theory of wave propagation to frozen porous media, J. Acoust. Soc. Am., 96, 6, 3753-3768.