Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode

NASA Astrophysics Data System (ADS)

Seibert, P.; Frank, A.

2003-04-01

A method for the calculation of source-receptor (s-r) relationships (sensitivity of a trace substance concentration at some place and time to emission at some place and time) with Lagrangian particle models has been derived and presented previously (Air Pollution Modeling and its Application XIV, Proc. of ITM Boulder 2000). Now, the generalisation to any linear s-r relationship, including dry and wet deposition, decay etc., is presented. It was implemented in the model FLEXPART and tested extensively in idealised set-ups. These tests turned out to be very useful for finding minor model bugs and inaccuracies, and can be recommended generally for model testing. Recently, a convection scheme has been integrated in FLEXPART which was also tested. Both source and receptor can be specified in mass mixing ratio or mass units. Properly taking care of this is quite relevant for sources and receptors at different levels in the atmosphere. Furthermore, we present a test with the transport of aerosol-bound Caesium-137 from the areas contaminated by the Chernobyl disaster to Stockholm during one month.

SOURCE APPORTIONMENT OF EXPOSURES TO VOLATILE ORGANIC COMPOUNDS: II. APPLICATION OF RECEPTOR MODELS TO TEAM STUDY DATA. (R826788)

EPA Science Inventory

Four receptor-oriented source apportionment models were applied to personal exposure measurements for toxic volatile organic compounds (VOCs). The measurements are from the total exposure assessment methodology studies conducted from 1980 to 1984 in New Jersey (NJ) and Califor...

Air Pollution Source/receptor Relationships in South Coast Air Basin, CA

NASA Astrophysics Data System (ADS)

Gao, Ning

This research project includes the application of some existing receptor models to study the air pollution source/receptor relationships in the South Coast Air Basin (SoCAB) of southern California, the development of a new receptor model and the testing and the modifications of some existing models. These existing receptor models used include principal component factor analysis (PCA), potential source contribution function (PSCF) analysis, Kohonen's neural network combined with Prim's minimal spanning tree (TREE-MAP), and direct trilinear decomposition followed by a matrix reconstruction. The ambient concentration measurements used in this study are a subset of the data collected during the 1987 field exercise of Southern California Air Quality Study (SCAQS). It consists of a number of gaseous and particulate pollutants analyzed from samples collected by SCAQS samplers at eight sampling sites, Anaheim, Azusa, Burbank, Claremont, Downtown Los Angeles, Hawthorne, Long Beach, and Rubidoux. Based on the information of emission inventories, meteorology and ambient concentrations, this receptor modeling study has revealed mechanisms that influence the air quality in SoCAB. Some of the mechanisms affecting the air quality in SoCAB that were revealed during this study include the following aspects. The SO_2 collected at sampling sites is mainly contributed by refineries in the coastal area and the ships equipped with oil-fired boilers off shore. Combustion of fossil fuel by automobiles dominates the emission of NO_{rm x} that is subsequently transformed and collected at sampling sites. Electric power plants also contribute HNO_3 to the sampling sites. A large feedlot in the eastern region of SoCAB has been identified as the major source of NH_3. Possible contributions from other industrial sources such as smelters and incinerators were also revealed. The results of this study also suggest the possibility of DMS (dimethylsulfide) and NH_3 emissions from off-shore sediments that have been contaminated by waste sludge disposal. The study also discovered that non-anthropogenic sources account for the observation of many chemical components being brought to the sampling sites, such as seasalt particles, soil particles, and Cl emission from Mojave Desert. The potential and limitation of the receptor models have been evaluated and some modifications have been made to improve the value of the models. A source apportionment method has been developed based on the application results of the potential source contribution function (PSCF) analysis.

Fine particle receptor modeling in the atmosphere of Mexico City.

PubMed

Vega, Elizabeth; Lowenthal, Douglas; Ruiz, Hugo; Reyes, Elizabeth; Watson, John G; Chow, Judith C; Viana, Mar; Querol, Xavier; Alastuey, Andrés

2009-12-01

Source apportionment analyses were carried out by means of receptor modeling techniques to determine the contribution of major fine particulate matter (PM2.5) sources found at six sites in Mexico City. Thirty-six source profiles were determined within Mexico City to establish the fingerprints of particulate matter sources. Additionally, the profiles under the same source category were averaged using cluster analysis and the fingerprints of 10 sources were included. Before application of the chemical mass balance (CMB), several tests were carried out to determine the best combination of source profiles and species used for the fitting. CMB results showed significant spatial variations in source contributions among the six sites that are influenced by local soil types and land use. On average, 24-hr PM2.5 concentrations were dominated by mobile source emissions (45%), followed by secondary inorganic aerosols (16%) and geological material (17%). Industrial emissions representing oil combustion and incineration contributed less than 5%, and their contribution was higher at the industrial areas of Tlalnepantla (11%) and Xalostoc (8%). Other sources such as cooking, biomass burning, and oil fuel combustion were identified at lower levels. A second receptor model (principal component analysis, [PCA]) was subsequently applied to three of the monitoring sites for comparison purposes. Although differences were obtained between source contributions, results evidence the advantages of the combined use of different receptor modeling techniques for source apportionment, given the complementary nature of their results. Further research is needed in this direction to reach a better agreement between the estimated source contributions to the particulate matter mass.

Part 2. Development of Enhanced Statistical Methods for Assessing Health Effects Associated with an Unknown Number of Major Sources of Multiple Air Pollutants.

PubMed

Park, Eun Sug; Symanski, Elaine; Han, Daikwon; Spiegelman, Clifford

2015-06-01

A major difficulty with assessing source-specific health effects is that source-specific exposures cannot be measured directly; rather, they need to be estimated by a source-apportionment method such as multivariate receptor modeling. The uncertainty in source apportionment (uncertainty in source-specific exposure estimates and model uncertainty due to the unknown number of sources and identifiability conditions) has been largely ignored in previous studies. Also, spatial dependence of multipollutant data collected from multiple monitoring sites has not yet been incorporated into multivariate receptor modeling. The objectives of this project are (1) to develop a multipollutant approach that incorporates both sources of uncertainty in source-apportionment into the assessment of source-specific health effects and (2) to develop enhanced multivariate receptor models that can account for spatial correlations in the multipollutant data collected from multiple sites. We employed a Bayesian hierarchical modeling framework consisting of multivariate receptor models, health-effects models, and a hierarchical model on latent source contributions. For the health model, we focused on the time-series design in this project. Each combination of number of sources and identifiability conditions (additional constraints on model parameters) defines a different model. We built a set of plausible models with extensive exploratory data analyses and with information from previous studies, and then computed posterior model probability to estimate model uncertainty. Parameter estimation and model uncertainty estimation were implemented simultaneously by Markov chain Monte Carlo (MCMC*) methods. We validated the methods using simulated data. We illustrated the methods using PM2.5 (particulate matter ≤ 2.5 μm in aerodynamic diameter) speciation data and mortality data from Phoenix, Arizona, and Houston, Texas. The Phoenix data included counts of cardiovascular deaths and daily PM2.5 speciation data from 1995-1997. The Houston data included respiratory mortality data and 24-hour PM2.5 speciation data sampled every six days from a region near the Houston Ship Channel in years 2002-2005. We also developed a Bayesian spatial multivariate receptor modeling approach that, while simultaneously dealing with the unknown number of sources and identifiability conditions, incorporated spatial correlations in the multipollutant data collected from multiple sites into the estimation of source profiles and contributions based on the discrete process convolution model for multivariate spatial processes. This new modeling approach was applied to 24-hour ambient air concentrations of 17 volatile organic compounds (VOCs) measured at nine monitoring sites in Harris County, Texas, during years 2000 to 2005. Simulation results indicated that our methods were accurate in identifying the true model and estimated parameters were close to the true values. The results from our methods agreed in general with previous studies on the source apportionment of the Phoenix data in terms of estimated source profiles and contributions. However, we had a greater number of statistically insignificant findings, which was likely a natural consequence of incorporating uncertainty in the estimated source contributions into the health-effects parameter estimation. For the Houston data, a model with five sources (that seemed to be Sulfate-Rich Secondary Aerosol, Motor Vehicles, Industrial Combustion, Soil/Crustal Matter, and Sea Salt) showed the highest posterior model probability among the candidate models considered when fitted simultaneously to the PM2.5 and mortality data. There was a statistically significant positive association between respiratory mortality and same-day PM2.5 concentrations attributed to one of the sources (probably industrial combustion). The Bayesian spatial multivariate receptor modeling approach applied to the VOC data led to a highest posterior model probability for a model with five sources (that seemed to be refinery, petrochemical production, gasoline evaporation, natural gas, and vehicular exhaust) among several candidate models, with the number of sources varying between three and seven and with different identifiability conditions. Our multipollutant approach assessing source-specific health effects is more advantageous than a single-pollutant approach in that it can estimate total health effects from multiple pollutants and can also identify emission sources that are responsible for adverse health effects. Our Bayesian approach can incorporate not only uncertainty in the estimated source contributions, but also model uncertainty that has not been addressed in previous studies on assessing source-specific health effects. The new Bayesian spatial multivariate receptor modeling approach enables predictions of source contributions at unmonitored sites, minimizing exposure misclassification and providing improved exposure estimates along with their uncertainty estimates, as well as accounting for uncertainty in the number of sources and identifiability conditions.

Source apportionments of PM2.5 organic carbon using molecular marker Positive Matrix Factorization and comparison of results from different receptor models

NASA Astrophysics Data System (ADS)

Heo, Jongbae; Dulger, Muaz; Olson, Michael R.; McGinnis, Jerome E.; Shelton, Brandon R.; Matsunaga, Aiko; Sioutas, Constantinos; Schauer, James J.

2013-07-01

Four hundred fine particulate matter (PM2.5) samples collected over a 1-year period at two sites in the Los Angeles Basin were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC) and organic molecular markers. The results were used in a Positive Matrix Factorization (PMF) receptor model to obtain daily, monthly and annual average source contributions to PM2.5 OC. Results of the PMF model showed similar source categories with comparable year-long contributions to PM2.5 OC across the sites. Five source categories providing reasonably stable profiles were identified: mobile, wood smoke, primary biogenic, and two types of secondary organic carbon (SOC) (i.e., anthropogenic and biogenic emissions). Total primary emission factors and total SOC factors contributed approximately 60% and 40%, respectively, to the annual-average OC concentrations. Primary sources showed strong seasonal patterns with high winter peaks and low summer peaks, while SOC showed a reverse pattern with highs in the spring and summer in the region. Interestingly, smoke from forest fires which occurred episodically in California during the summer and fall of 2009 was identified and combined with the primary biogenic source as one distinct factor to the OC budget. The PMF resolved factors were further investigated and compared to a chemical mass balance (CMB) model and a second multi-variant receptor model (UNMIX) using molecular markers considered in the PMF. Good agreement between the source contribution from mobile sources and biomass burning for three models were obtained, providing additional weight of evidence that these source apportionment techniques are sufficiently accurate for policy development. However, the CMB model did not quantify primary biogenic emissions, which were included in other sources with the SOC. Both multivariate receptor models, the PMF and the UNMIX, were unable to separate source contributions from diesel and gasoline engines.

Quantification of source impact to PM using three-dimensional weighted factor model analysis on multi-site data

NASA Astrophysics Data System (ADS)

Shi, Guoliang; Peng, Xing; Huangfu, Yanqi; Wang, Wei; Xu, Jiao; Tian, Yingze; Feng, Yinchang; Ivey, Cesunica E.; Russell, Armistead G.

2017-07-01

Source apportionment technologies are used to understand the impacts of important sources of particulate matter (PM) air quality, and are widely used for both scientific studies and air quality management. Generally, receptor models apportion speciated PM data from a single sampling site. With the development of large scale monitoring networks, PM speciation are observed at multiple sites in an urban area. For these situations, the models should account for three factors, or dimensions, of the PM, including the chemical species concentrations, sampling periods and sampling site information, suggesting the potential power of a three-dimensional source apportionment approach. However, the principle of three-dimensional Parallel Factor Analysis (Ordinary PARAFAC) model does not always work well in real environmental situations for multi-site receptor datasets. In this work, a new three-way receptor model, called "multi-site three way factor analysis" model is proposed to deal with the multi-site receptor datasets. Synthetic datasets were developed and introduced into the new model to test its performance. Average absolute error (AAE, between estimated and true contributions) for extracted sources were all less than 50%. Additionally, three-dimensional ambient datasets from a Chinese mega-city, Chengdu, were analyzed using this new model to assess the application. Four factors are extracted by the multi-site WFA3 model: secondary source have the highest contributions (64.73 and 56.24 μg/m3), followed by vehicular exhaust (30.13 and 33.60 μg/m3), crustal dust (26.12 and 29.99 μg/m3) and coal combustion (10.73 and 14.83 μg/m3). The model was also compared to PMF, with general agreement, though PMF suggested a lower crustal contribution.

Photochemical grid model performance with varying horizontal grid resolution and sub-grid plume treatment for the Martins Creek near-field SO2 study

NASA Astrophysics Data System (ADS)

Baker, Kirk R.; Hawkins, Andy; Kelly, James T.

2014-12-01

Near source modeling is needed to assess primary and secondary pollutant impacts from single sources and single source complexes. Source-receptor relationships need to be resolved from tens of meters to tens of kilometers. Dispersion models are typically applied for near-source primary pollutant impacts but lack complex photochemistry. Photochemical models provide a realistic chemical environment but are typically applied using grid cell sizes that may be larger than the distance between sources and receptors. It is important to understand the impacts of grid resolution and sub-grid plume treatments on photochemical modeling of near-source primary pollution gradients. Here, the CAMx photochemical grid model is applied using multiple grid resolutions and sub-grid plume treatment for SO2 and compared with a receptor mesonet largely impacted by nearby sources approximately 3-17 km away in a complex terrain environment. Measurements are compared with model estimates of SO2 at 4- and 1-km resolution, both with and without sub-grid plume treatment and inclusion of finer two-way grid nests. Annual average estimated SO2 mixing ratios are highest nearest the sources and decrease as distance from the sources increase. In general, CAMx estimates of SO2 do not compare well with the near-source observations when paired in space and time. Given the proximity of these sources and receptors, accuracy in wind vector estimation is critical for applications that pair pollutant predictions and observations in time and space. In typical permit applications, predictions and observations are not paired in time and space and the entire distributions of each are directly compared. Using this approach, model estimates using 1-km grid resolution best match the distribution of observations and are most comparable to similar studies that used dispersion and Lagrangian modeling systems. Model-estimated SO2 increases as grid cell size decreases from 4 km to 250 m. However, it is notable that the 1-km model estimates using 1-km meteorological model input are higher than the 1-km model simulation that used interpolated 4-km meteorology. The inclusion of sub-grid plume treatment did not improve model skill in predicting SO2 in time and space and generally acts to keep emitted mass aloft.

Proceedings from the Workshop on Research Needs for Assessment and Management of Non-Point Air Emissions from Department of Defense Activities held in Research Triangle Park, North Carolina on 19-21 February 2008

DTIC Science & Technology

2008-10-01

Chow, J.C. (2006). Feasibility of soil dust source apportionment by the pyrolysis-gas chromatography/mass spectrometry method. J. Air Waste Manage...receptor-oriented source apportionment models. • Develop monitoring methods to determine source and fence line amounts of fugitive dust emissions for...offsite impact, including evaluation with receptor- oriented source apportionment models 76 8.8.1 Background 76 8.8.2 Significance 77 8.8.3

A GIS-based atmospheric dispersion model for pollutants emitted by complex source areas.

PubMed

Teggi, Sergio; Costanzini, Sofia; Ghermandi, Grazia; Malagoli, Carlotta; Vinceti, Marco

2018-01-01

Gaussian dispersion models are widely used to simulate the concentrations and deposition fluxes of pollutants emitted by source areas. Very often, the calculation time limits the number of sources and receptors and the geometry of the sources must be simple and without holes. This paper presents CAREA, a new GIS-based Gaussian model for complex source areas. CAREA was coded in the Python language, and is largely based on a simplified formulation of the very popular and recognized AERMOD model. The model allows users to define in a GIS environment thousands of gridded or scattered receptors and thousands of complex sources with hundreds of vertices and holes. CAREA computes ground level, or near ground level, concentrations and dry deposition fluxes of pollutants. The input/output and the runs of the model can be completely managed in GIS environment (e.g. inside a GIS project). The paper presents the CAREA formulation and its applications to very complex test cases. The tests shows that the processing time are satisfactory and that the definition of sources and receptors and the output retrieval are quite easy in a GIS environment. CAREA and AERMOD are compared using simple and reproducible test cases. The comparison shows that CAREA satisfactorily reproduces AERMOD simulations and is considerably faster than AERMOD. Copyright © 2017 Elsevier B.V. All rights reserved.

Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode

NASA Astrophysics Data System (ADS)

Seibert, P.; Frank, A.

2004-01-01

The possibility to calculate linear-source receptor relationships for the transport of atmospheric trace substances with a Lagrangian particle dispersion model (LPDM) running in backward mode is shown and presented with many tests and examples. This mode requires only minor modifications of the forward LPDM. The derivation includes the action of sources and of any first-order processes (transformation with prescribed rates, dry and wet deposition, radioactive decay, etc.). The backward mode is computationally advantageous if the number of receptors is less than the number of sources considered. The combination of an LPDM with the backward (adjoint) methodology is especially attractive for the application to point measurements, which can be handled without artificial numerical diffusion. Practical hints are provided for source-receptor calculations with different settings, both in forward and backward mode. The equivalence of forward and backward calculations is shown in simple tests for release and sampling of particles, pure wet deposition, pure convective redistribution and realistic transport over a short distance. Furthermore, an application example explaining measurements of Cs-137 in Stockholm as transport from areas contaminated heavily in the Chernobyl disaster is included.

Source apportionment for fine particulate matter in a Chinese city using an improved gas-constrained method and comparison with multiple receptor models.

PubMed

Shi, Guoliang; Liu, Jiayuan; Wang, Haiting; Tian, Yingze; Wen, Jie; Shi, Xurong; Feng, Yinchang; Ivey, Cesunica E; Russell, Armistead G

2018-02-01

PM 2.5 is one of the most studied atmospheric pollutants due to its adverse impacts on human health and welfare and the environment. An improved model (the chemical mass balance gas constraint-Iteration: CMBGC-Iteration) is proposed and applied to identify source categories and estimate source contributions of PM 2.5. The CMBGC-Iteration model uses the ratio of gases to PM as constraints and considers the uncertainties of source profiles and receptor datasets, which is crucial information for source apportionment. To apply this model, samples of PM 2.5 were collected at Tianjin, a megacity in northern China. The ambient PM 2.5 dataset, source information, and gas-to-particle ratios (such as SO 2 /PM 2.5 , CO/PM 2.5 , and NOx/PM 2.5 ratios) were introduced into the CMBGC-Iteration to identify the potential sources and their contributions. Six source categories were identified by this model and the order based on their contributions to PM 2.5 was as follows: secondary sources (30%), crustal dust (25%), vehicle exhaust (16%), coal combustion (13%), SOC (7.6%), and cement dust (0.40%). In addition, the same dataset was also calculated by other receptor models (CMB, CMB-Iteration, CMB-GC, PMF, WALSPMF, and NCAPCA), and the results obtained were compared. Ensemble-average source impacts were calculated based on the seven source apportionment results: contributions of secondary sources (28%), crustal dust (20%), coal combustion (18%), vehicle exhaust (17%), SOC (11%), and cement dust (1.3%). The similar results of CMBGC-Iteration and ensemble method indicated that CMBGC-Iteration can produce relatively appropriate results. Copyright © 2017 Elsevier Ltd. All rights reserved.

INPUFF: A SINGLE SOURCE GAUSSIAN PUFF DISPERSION ALGORITHM. USER'S GUIDE

EPA Science Inventory

INPUFF is a Gaussian INtegrated PUFF model. The Gaussian puff diffusion equation is used to compute the contribution to the concentration at each receptor from each puff every time step. Computations in INPUFF can be made for a single point source at up to 25 receptor locations. ...

Source-receptor matrix calculation with a Source-receptor matrix calculation with a backward mode

NASA Astrophysics Data System (ADS)

Seibert, P.; Frank, A.

2003-08-01

The possibility to calculate linear-source receptor relationships for the transport of atmospheric trace substances with a Lagrangian particle dispersion model (LPDM) running in backward mode is shown and presented with many tests and examples. The derivation includes the action of sources and of any first-order processes (transformation with prescribed rates, dry and wet deposition, radioactive decay, ...). The backward mode is computationally advantageous if the number of receptors is less than the number of sources considered. The combination of an LPDM with the backward (adjoint) methodology is especially attractive for the application to point measurements, which can be handled without artificial numerical diffusion. Practical hints are provided for source-receptor calculations with different settings, both in forward and backward mode. The equivalence of forward and backward calculations is shown in simple tests for release and sampling of particles, pure wet deposition, pure convective redistribution and realistic transport over a short distance. Furthermore, an application example explaining measurements of Cs-137 in Stockholm as transport from areas contaminated heavily in the Chernobyl disaster is included.

A Novel Approach for Determining Source–Receptor Relationships in Model Simulations: A Case Study of Black Carbon Transport in Northern Hemisphere Winter

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

Ma, Po-Lun; Gattiker, J. R.; Liu, Xiaohong

2013-06-27

A Gaussian process (GP) emulator is applied to quantify the contribution of local and remote emissions of black carbon (BC) on the BC concentrations in different regions using a Latin Hypercube sampling strategy for emission perturbations in the offline version of the Community Atmosphere Model Version 5.1 (CAM5) simulations. The source-receptor relationships are computed based on simulations constrained by a standard free-running CAM5 simulation and the ERA-Interim reanalysis product. The analysis demonstrates that the emulator is capable of retrieving the source-receptor relationships based on a small number of CAM5 simulations. Most regions are found susceptible to their local emissions. Themore » emulator also finds that the source-receptor relationships retrieved from the model-driven and the reanalysis-driven simulations are very similar, suggesting that the simulated circulation in CAM5 resembles the assimilated meteorology in ERA-Interim. The robustness of the results provides confidence for applying the emulator to detect dose-response signals in the climate system.« less

SPECIATE--EPA'S DATABASE OF SPECIATED EMISSION PROFILES

EPA Science Inventory

SPECIATE is EPA's repository of Total Organic Compound and Particulate Matter speciated profiles for a wide variety of sources. The profiles in this system are provided for air quality dispersion modeling and as a library for source-receptor and source apportionment type models. ...

DEVELOPMENT AND EVALUATION OF PM 2.5 SOURCE APPORTIONMENT METHODOLOGIES

EPA Science Inventory

The receptor model called Positive Matrix Factorization (PMF) has been extensively used to apportion sources of ambient fine particulate matter (PM_2.5), but the accuracy of source apportionment results currently remains unknown. In addition, air quality forecast model...

Water quality assessment and apportionment of pollution sources using APCS-MLR and PMF receptor modeling techniques in three major rivers of South Florida.

PubMed

Haji Gholizadeh, Mohammad; Melesse, Assefa M; Reddi, Lakshmi

2016-10-01

In this study, principal component analysis (PCA), factor analysis (FA), and the absolute principal component score-multiple linear regression (APCS-MLR) receptor modeling technique were used to assess the water quality and identify and quantify the potential pollution sources affecting the water quality of three major rivers of South Florida. For this purpose, 15years (2000-2014) dataset of 12 water quality variables covering 16 monitoring stations, and approximately 35,000 observations was used. The PCA/FA method identified five and four potential pollution sources in wet and dry seasons, respectively, and the effective mechanisms, rules and causes were explained. The APCS-MLR apportioned their contributions to each water quality variable. Results showed that the point source pollution discharges from anthropogenic factors due to the discharge of agriculture waste and domestic and industrial wastewater were the major sources of river water contamination. Also, the studied variables were categorized into three groups of nutrients (total kjeldahl nitrogen, total phosphorus, total phosphate, and ammonia-N), water murkiness conducive parameters (total suspended solids, turbidity, and chlorophyll-a), and salt ions (magnesium, chloride, and sodium), and average contributions of different potential pollution sources to these categories were considered separately. The data matrix was also subjected to PMF receptor model using the EPA PMF-5.0 program and the two-way model described was performed for the PMF analyses. Comparison of the obtained results of PMF and APCS-MLR models showed that there were some significant differences in estimated contribution for each potential pollution source, especially in the wet season. Eventually, it was concluded that the APCS-MLR receptor modeling approach appears to be more physically plausible for the current study. It is believed that the results of apportionment could be very useful to the local authorities for the control and management of pollution and better protection of important riverine water quality. Copyright © 2016 Elsevier B.V. All rights reserved.

DUALITY IN MULTIVARIATE RECEPTOR MODEL. (R831078)

EPA Science Inventory

Multivariate receptor models are used for source apportionment of multiple observations of compositional data of air pollutants that obey mass conservation. Singular value decomposition of the data leads to two sets of eigenvectors. One set of eigenvectors spans a space in whi...

Source apportionment of soil heavy metals using robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR) receptor model.

PubMed

Qu, Mingkai; Wang, Yan; Huang, Biao; Zhao, Yongcun

2018-06-01

The traditional source apportionment models, such as absolute principal component scores-multiple linear regression (APCS-MLR), are usually susceptible to outliers, which may be widely present in the regional geochemical dataset. Furthermore, the models are merely built on variable space instead of geographical space and thus cannot effectively capture the local spatial characteristics of each source contributions. To overcome the limitations, a new receptor model, robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR), was proposed based on the traditional APCS-MLR model. Then, the new method was applied to the source apportionment of soil metal elements in a region of Wuhan City, China as a case study. Evaluations revealed that: (i) RAPCS-RGWR model had better performance than APCS-MLR model in the identification of the major sources of soil metal elements, and (ii) source contributions estimated by RAPCS-RGWR model were more close to the true soil metal concentrations than that estimated by APCS-MLR model. It is shown that the proposed RAPCS-RGWR model is a more effective source apportionment method than APCS-MLR (i.e., non-robust and global model) in dealing with the regional geochemical dataset. Copyright © 2018 Elsevier B.V. All rights reserved.

Taking potential probability function maps to the local scale and matching them with land use maps

NASA Astrophysics Data System (ADS)

Garg, Saryu; Sinha, Vinayak; Sinha, Baerbel

2013-04-01

Source-Receptor models have been developed using different methods. Residence-time weighted concentration back trajectory analysis and Potential Source Contribution Function (PSCF) are the two most popular techniques for identification of potential sources of a substance in a defined geographical area. Both techniques use back trajectories calculated using global models and assign values of probability/concentration to various locations in an area. These values represent the probability of threshold exceedances / the average concentration measured at the receptor in air masses with a certain residence time over a source area. Both techniques, however, have only been applied to regional and long-range transport phenomena due to inherent limitation with respect to both spatial accuracy and temporal resolution of the of back trajectory calculations. Employing the above mentioned concepts of residence time weighted concentration back-trajectory analysis and PSCF, we developed a source-receptor model capable of identifying local and regional sources of air pollutants like Particulate Matter (PM), NOx, SO2 and VOCs. We use 1 to 30 minute averages of concentration values and wind direction and speed from a single receptor site or from multiple receptor sites to trace the air mass back in time. The model code assumes all the atmospheric transport to be Lagrangian and linearly extrapolates air masses reaching the receptor location, backwards in time for a fixed number of steps. We restrict the model run to the lifetime of the chemical species under consideration. For long lived species the model run is limited to < 4 hrs as spatial uncertainty increases the longer an air mass is linearly extrapolated back in time. The final model output is a map, which can be compared with the local land use map to pinpoint sources of different chemical substances and estimate their source strength. Our model has flexible space- time grid extrapolation steps of 1-5 minutes and 1-5 km grid resolution. By making use of high temporal resolution data, our model can produce maps for different times of the day, thus accounting for temporal changes and activity profiles of different sources. The main advantage of our approach compared to geostationary numerical methods that interpolate measured concentration values of multiple measurement sites to produce maps (gridding) is that the maps produced are more accurate in terms of spatial identification of sources. The model was applied to isoprene and meteorological data recorded during clean post-monsoon season (1 October- 7 October, 2012) between 11 am and 4 pm at a receptor site in the North-West Indo-Gangetic Plains (IISER Mohali, 30.665° N, 76.729°E, 300 m asl), near the foothills of the Himalayan range. Considering the lifetime of isoprene, the model was run only 2 hours backward in time. The map shows highest residence time weighted concentration of isoprene (up to 3.5 ppbv) over agricultural land with high number of trees (>180 trees/gridsquare); moderate concentrations for agricultural lands with low tree density (1.5-2.5 ppbv for 250 μg/m3 for traffic hotspots in Chandigarh City are observed. Based on the validation against the land use maps, the model appears to do an excellent job in source apportionment and identifying emission hotspots. Acknowledgement: We thank the IISER Mohali Atmospheric Chemistry Facility for data and the Ministry of Human Resource Development (MHRD), India and IISER Mohali for funding the facility. Chinmoy Sarkar is acknowledged for technical support, Saryu Garg thanks the Max Planck-DST India Partner Group on Tropospheric OH reactivity and VOCs for funding the research.

A Bayesian Multivariate Receptor Model for Estimating Source Contributions to Particulate Matter Pollution using National Databases.

PubMed

Hackstadt, Amber J; Peng, Roger D

2014-11-01

Time series studies have suggested that air pollution can negatively impact health. These studies have typically focused on the total mass of fine particulate matter air pollution or the individual chemical constituents that contribute to it, and not source-specific contributions to air pollution. Source-specific contribution estimates are useful from a regulatory standpoint by allowing regulators to focus limited resources on reducing emissions from sources that are major contributors to air pollution and are also desired when estimating source-specific health effects. However, researchers often lack direct observations of the emissions at the source level. We propose a Bayesian multivariate receptor model to infer information about source contributions from ambient air pollution measurements. The proposed model incorporates information from national databases containing data on both the composition of source emissions and the amount of emissions from known sources of air pollution. The proposed model is used to perform source apportionment analyses for two distinct locations in the United States (Boston, Massachusetts and Phoenix, Arizona). Our results mirror previous source apportionment analyses that did not utilize the information from national databases and provide additional information about uncertainty that is relevant to the estimation of health effects.

A Modeling System to Examine Near-Road and Near-Source Air Toxics for Community-Scale Cumulative Assessments.

EPA Science Inventory

Cumulative assessments consider a range of potential stressors that might impact the health of a receptor, such as a local neighborhood or wetland area. When receptors are located near pollution sources such as highways or ports (within 500-1,000 m), then they could be at risk of...

A Regional Assessment of Marine Vessel PM2.5 Impacts in the U.S. Pacific Northwest Using a Receptor Based Source Apportionment Method

EPA Science Inventory

This work reports the results of a regional receptor-based source apportionment analysis using the Positive Matrix Factorization (PMF) model on chemically speciated PM2.5 data from 36 urban and rural monitoring sites within the U.S. Pacific Northwest. The approach taken is to mo...

Development of Source-Receptor matrix over South Korea in support of GAINS-Korea model

NASA Astrophysics Data System (ADS)

Choi, K. C.; Woo, J. H.; Kim, H. K.; Lee, Y. M.; Kim, Y.; Heyes, C.; Lee, J. B.; Song, C. K.; Han, J.

2014-12-01

A comprehensive and combined analysis of air pollution and climate change could reveal important synergies of emission control measures, which could be of high policy relevance. IIASA's GAINS model (The Greenhouse gas - Air pollution Interactions and Synergies) has been developed as a tool to identify emission control strategies that achieve given targets on air quality and greenhouse gas emissions at least costs. The GAINS-Korea Model, which is being jointly developed by Konkuk University and IIASA, should play an important role in understanding the impact of air quality improvements across the regions in Korea. Source-Receptor relationships (S-R) is an useful methodology in air pollution studies to determine the areas of origin of chemical compounds at receptor point, and thus be able to target actions to reduce pollutions. The GAINS model can assess the impact of emission reductions of sources on air quality in receptor regions based on S-R matrix, derived from chemical transport model. In order to develop S-R matrix for GAINS-Korea, the CAMx model with PSAT/OSAT tools was applied in this study. The coarse domain covers East Asia, and a nesting domain as main research area was used for Korea peninsula. To evaluate of S-R relationships, a modeling domain is divided into sixteen regions over South Korea with three outside of S. Korea countries (China, N. Korea and Japan) for estimating transboundary contributions. The results of our analysis will be presented at the conference.

SOURCE APPORTIONMENT RESULTS, UNCERTAINTIES, AND MODELING TOOLS

EPA Science Inventory

Advanced multivariate receptor modeling tools are available from the U.S. Environmental Protection Agency (EPA) that use only speciated sample data to identify and quantify sources of air pollution. EPA has developed both EPA Unmix and EPA Positive Matrix Factorization (PMF) and ...

EVALUATION OF VADOSE ZONE AND SOURCE MODELS FOR MULTI-MEDIA, MULTI-PATHWAY, MULTI-RECEPTOR RISK ASSESSMENT USING LARGE SOIL COLUMN EXPERIMENT DATA

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) is developing a comprehensive environmental exposure and risk analysis software system for agency-wide application using the methodology of a Multi-media, Multi-pathway, Multi-receptor Risk Assessment (3MRA) model. This software sys...

Determining the contribution of long-range transport, regional and local source areas, to PM10 mass loading in Hessen, Germany using a novel multi-receptor based statistical approach

NASA Astrophysics Data System (ADS)

Garg, Saryu; Sinha, Baerbel

2017-10-01

This study uses two newly developed statistical source apportionment models, MuSAM and MuReSAM, to perform quantitative statistical source apportionment of PM10 at multiple receptor sites in South Hessen. MuSAM uses multi-site back trajectory data to quantify the contribution of long-range transport, while MuReSAM uses wind speed and direction as proxy for regional transport and quantifies the contribution of regional source areas. On average, between 7.8 and 9.1 μg/m3 of PM10 (∼50%) at receptor sites in South Hessen is contributed by long-range transport. The dominant source regions are Eastern, South Eastern, and Southern Europe. 32% of the PM10 at receptor sites in South Hessen is contributed by regional source areas (2.8-9.41 μg/m3). This fraction varies from <20% at remote sites to >40% for urban stations. Sources located within a 2 km radius around the receptor site are responsible for 7%-20% of the total PM10 mass (0.7-4.4 μg/m3). The perturbation study of the traffic flow due to the closing and reopening of the Schiersteiner Brücke revealed that the contribution of the bridge to PM10 mass loadings at two nearby receptor sites increased by approximately 120% after it reopened and became a bottleneck, although in absolute terms, the increase is small.

Comparison of hybrid receptor models to locate PCB sources in Chicago

NASA Astrophysics Data System (ADS)

Hsu, Ying-Kuang; Holsen, Thomas M.; Hopke, Philip K.

Results of three hybrid receptor models, potential source contribution function (PSCF), concentration weighted trajectory (CWT), and residence time weighted concentration (RTWC), were compared for locating polychlorinated biphenyl (PCB) sources contributing to the atmospheric concentrations in Chicago. Variations of these models, including PSCF using mean and 75% criterion concentrations, joint probability PSCF (JP-PSCF), changes of point filters and grid cell sizes for RTWC, and PSCF using wind trajectories started at different altitudes, are also discussed. Modeling results were relatively consistent between models. However, no single model provided as complete information as was obtained by using all of them. CWT and 75% PSCF appears to be able to distinguish between larger sources and moderate ones. RTWC resolved high potential source areas. RTWC and JP-PSCF pooling data from all sampling sites removed the trailing effect often seen in PSCF modeling. PSCF results using average concentration criteria, appears to identify both moderate and major sources. Each model has advantages and disadvantages. However, used in combination, they provide information that is not available if only one of them is used. For short-range atmospheric transport, PSCF results were consistent when using wind trajectories starting at different heights. Based on the archived PCB data, the modeling results indicate there is a large potential source area between Joliet and Kankakee, IL, and two moderate sources to the northwest and south of Chicago. On the south side of Chicago in the neighborhood of Lake Calumet, several PCB sources were identified. Other unidentified potential source location(s) will require additional upwind/downwind field sampling to verify modeling results.

Source Region Identification Using Kernel Smoothing

EPA Science Inventory

As described in this paper, Nonparametric Wind Regression is a source-to-receptor source apportionment model that can be used to identify and quantify the impact of possible source regions of pollutants as defined by wind direction sectors. It is described in detail with an exam...

Dispersion modeling of polycyclic aromatic hydrocarbons from combustion of biomass and fossil fuels and production of coke in Tianjin, China.

PubMed

Tao, Shu; Li, Xinrong; Yang, Yu; Coveney, Raymond M; Lu, Xiaoxia; Chen, Haitao; Shen, Weiran

2006-08-01

A USEPA, procedure, ISCLT3 (Industrial Source Complex Long-Term), was applied to model the spatial distribution of polycyclic aromatic hydrocarbons (PAHs) emitted from various sources including coal, petroleum, natural gas, and biomass into the atmosphere of Tianjin, China. Benzo[a]pyrene equivalent concentrations (BaPeq) were calculated for risk assessment. Model results were provisionally validated for concentrations and profiles based on the observed data at two monitoring stations. The dominant emission sources in the area were domestic coal combustion, coke production, and biomass burning. Mainly because of the difference in the emission heights, the contributions of various sources to the average concentrations at receptors differ from proportions emitted. The shares of domestic coal increased from approximately 43% at the sources to 56% at the receptors, while the contributions of coking industry decreased from approximately 23% at the sources to 7% at the receptors. The spatial distributions of gaseous and particulate PAHs were similar, with higher concentrations occurring within urban districts because of domestic coal combustion. With relatively smaller contributions, the other minor sources had limited influences on the overall spatial distribution. The calculated average BaPeq value in air was 2.54 +/- 2.87 ng/m3 on an annual basis. Although only 2.3% of the area in Tianjin exceeded the national standard of 10 ng/m3, 41% of the entire population lives within this area.

Aerosol Source Attributions and Source-Receptor Relationships Across the Northern Hemisphere

NASA Technical Reports Server (NTRS)

Bian, Huisheng; Chin, Mian; Kucsera, Tom; Pan, Xiaohua; Darmenov, Anton; Colarco, Peter; Torres, Omar; Shults, Michael

2014-01-01

Emissions and long-range transport of air pollution pose major concerns on air quality and climate change. To better assess the impact of intercontinental transport of air pollution on regional and global air quality, ecosystems, and near-term climate change, the UN Task Force on Hemispheric Transport of Air Pollution (HTAP) is organizing a phase II activity (HTAP2) that includes global and regional model experiments and data analysis, focusing on ozone and aerosols. This study presents the initial results of HTAP2 global aerosol modeling experiments. We will (a) evaluate the model results with surface and aircraft measurements, (b) examine the relative contributions of regional emission and extra-regional source on surface PM concentrations and column aerosol optical depth (AOD) over several NH pollution and dust source regions and the Arctic, and (c) quantify the source-receptor relationships in the pollution regions that reflect the sensitivity of regional aerosol amount to the regional and extra-regional emission reductions.

Source apportionment of ambient non-methane hydrocarbons in Hong Kong: application of a principal component analysis/absolute principal component scores (PCA/APCS) receptor model.

PubMed

Guo, H; Wang, T; Louie, P K K

2004-06-01

Receptor-oriented source apportionment models are often used to identify sources of ambient air pollutants and to estimate source contributions to air pollutant concentrations. In this study, a PCA/APCS model was applied to the data on non-methane hydrocarbons (NMHCs) measured from January to December 2001 at two sampling sites: Tsuen Wan (TW) and Central & Western (CW) Toxic Air Pollutants Monitoring Stations in Hong Kong. This multivariate method enables the identification of major air pollution sources along with the quantitative apportionment of each source to pollutant species. The PCA analysis identified four major pollution sources at TW site and five major sources at CW site. The extracted pollution sources included vehicular internal engine combustion with unburned fuel emissions, use of solvent particularly paints, liquefied petroleum gas (LPG) or natural gas leakage, and industrial, commercial and domestic sources such as solvents, decoration, fuel combustion, chemical factories and power plants. The results of APCS receptor model indicated that 39% and 48% of the total NMHCs mass concentrations measured at CW and TW were originated from vehicle emissions, respectively. 32% and 36.4% of the total NMHCs were emitted from the use of solvent and 11% and 19.4% were apportioned to the LPG or natural gas leakage, respectively. 5.2% and 9% of the total NMHCs mass concentrations were attributed to other industrial, commercial and domestic sources, respectively. It was also found that vehicle emissions and LPG or natural gas leakage were the main sources of C(3)-C(5) alkanes and C(3)-C(5) alkenes while aromatics were predominantly released from paints. Comparison of source contributions to ambient NMHCs at the two sites indicated that the contribution of LPG or natural gas at CW site was almost twice that at TW site. High correlation coefficients (R(2) > 0.8) between the measured and predicted values suggested that the PCA/APCS model was applicable for estimation of sources of NMHCs in ambient air.

Identification and elucidation of anthropogenic source contribution in PM10 pollutant: Insight gain from dispersion and receptor models.

PubMed

Roy, Debananda; Singh, Gurdeep; Yadav, Pankaj

2016-10-01

Source apportionment study of PM 10 (Particulate Matter) in a critically polluted area of Jharia coalfield, India has been carried out using Dispersion model, Principle Component Analysis (PCA) and Chemical Mass Balance (CMB) techniques. Dispersion model Atmospheric Dispersion Model (AERMOD) was introduced to simplify the complexity of sources in Jharia coalfield. PCA and CMB analysis indicates that monitoring stations near the mining area were mainly affected by the emission from open coal mining and its associated activities such as coal transportation, loading and unloading of coal. Mine fire emission also contributed a considerable amount of particulate matters in monitoring stations. Locations in the city area were mostly affected by vehicular, Liquid Petroleum Gas (LPG) & Diesel Generator (DG) set emissions, residential, and commercial activities. The experimental data sampling and their analysis could aid understanding how dispersion based model technique along with receptor model based concept can be strategically used for quantitative analysis of Natural and Anthropogenic sources of PM 10 . Copyright © 2016. Published by Elsevier B.V.

Advanced receptor models for exploiting highly time-resolved data acquired in the EPA supersite preject

NASA Astrophysics Data System (ADS)

Ke, Haohao

Receptor models have been widely used in air quality studies to identify pollution sources and estimate their contributions. A common problem for most current receptor models is insufficient consideration of realistic constraints such as can be obtained from emission inventories, chemical composition profiles of the sources, and the physics of plume dispersion. In addition, poor resolving of collinear sources was often found. With the high quality time-, composition-, and size-resolved measurements during the EPA Supersite project, efforts towards resolving nearby industrial sources were made by combinative use of Positive Matrix Factorization (PMF) and the Pseudo-Deterministic Receptor Model (PDRM). The PMF modeling of Baltimore data in September 2001 revealed coal-fired and oil-fired power plants (CFPP and OFPP, respectively) with significant cross contamination, as indicated by the high Se/Ni ratio in the OFPP profile. Nevertheless, the PMF results provided a good estimate of background and the PMF-constrained emission rates well seeded the trajectory-driven PDRM modeling. Using NOx as the tracer gas for chi/Q tuning, ultimately resolved emissions from individual stacks exhibited acceptable tracer ratios and the emission rates of metals generally agreed with the TRI estimates. This approach was later applied to two metal pollution episodes in St. Louis during in November 2001 and March 2002 and met a similar success. As NOx measurements were unavailable at those metal-production facilities, highly-specific tracer metals (i.e., Cd, Zn, and Cu) for the corresponding units were used to tune chi/Qs and their contributions were well resolved with the PMF-seeded PDRM. Opportunistically a PM2.5 excursion during a windless morning in November 2002 allowed the extraction of an in-situ profile of vehicular emissions in Baltimore. The profiles obtained by direct peak observation, windless model linear regression (WMA), PMF, and UNMIX were comparable and the WMA profile showed the best predictions for non-traffic tracers. Besides, an approach to evaluate vehicular emission factors was developed by receptor measurements under windless conditions. Using SVOC tracers, seasonal variations of traffic and other sources including coal burning, heating, biomass burning, and vegetation were investigated by PMF and in particular the November traffic profile was consistent with the WMA profile obtained earlier.

Source apportionment of PM10 and PM2.5 in major urban Greek agglomerations using a hybrid source-receptor modeling process.

PubMed

Argyropoulos, G; Samara, C; Diapouli, E; Eleftheriadis, K; Papaoikonomou, K; Kungolos, A

2017-12-01

A hybrid source-receptor modeling process was assembled, to apportion and infer source locations of PM 10 and PM 2.5 in three heavily-impacted urban areas of Greece, during the warm period of 2011, and the cold period of 2012. The assembled process involved application of an advanced computational procedure, the so-called Robotic Chemical Mass Balance (RCMB) model. Source locations were inferred using two well-established probability functions: (a) the Conditional Probability Function (CPF), to correlate the output of RCMB with local wind directional data, and (b) the Potential Source Contribution Function (PSCF), to correlate the output of RCMB with 72h air-mass back-trajectories, arriving at the receptor sites, during sampling. Regarding CPF, a higher-level conditional probability function was defined as well, from the common locus of CPF sectors derived for neighboring receptor sites. With respect to PSCF, a non-parametric bootstrapping method was applied to discriminate the statistically significant values. RCMB modeling showed that resuspended dust is actually one of the main barriers for attaining the European Union (EU) limit values in Mediterranean urban agglomerations, where the drier climate favors build-up. The shift in the energy mix of Greece (caused by the economic recession) was also evidenced, since biomass burning was found to contribute more significantly to the sampling sites belonging to the coldest climatic zone, particularly during the cold period. The CPF analysis showed that short-range transport of anthropogenic emissions from urban traffic to urban background sites was very likely to have occurred, within all the examined urban agglomerations. The PSCF analysis confirmed that long-range transport of primary and/or secondary aerosols may indeed be possible, even from distances over 1000km away from study areas. Copyright © 2017 Elsevier B.V. All rights reserved.

PM₁₀ and PM₂.₅ sources at an insular location in the western Mediterranean by using source apportionment techniques.

PubMed

Pey, Jorge; Alastuey, Andrés; Querol, Xavier

2013-07-01

PM₁₀ and PM₂.₅ chemical composition has been determined at a suburban insular site in the Balearic Islands (Spain) during almost one and a half year. As a result, 200 samples with more than 50 chemical parameters analyzed have been obtained. The whole database has been analyzed by two receptor modelling techniques (Principal Component Analysis and Positive Matrix Factorisation) in order to identify the main PM sources. After that, regression analyses with respect to the PM mass concentrations were conducted to quantify the daily contributions of each source. Four common sources were identified by both receptor models: secondary nitrate coupled with vehicular emissions, secondary sulphate influenced by fuel-oil combustion, aged marine aerosols and mineral dust. In addition, PCA isolated harbour emissions and a mixed anthropogenic factor containing industrial emissions; whereas PMF isolated an additional mineral factor interpreted as road dust+harbour emissions, and a vehicular abrasion products factor. The use of both methodologies appeared complementary. Nevertheless, PMF sources by themselves were better differentiated. Besides these receptor models, a specific methodology to quantify African dust was also applied. The combination of these three source apportionment tools allowed the identification of 8 sources, being 4 of them mineral (African, regional, urban and harbour dusts). As a summary, 29% of PM₁₀ was attributed to natural sources (African dust, regional dust and sea spray), whereas the proportion diminished to 11% in PM₂.₅. Furthermore, the secondary sulphate source, which accounted for about 22 and 32% of PM₁₀ and PM₂.₅, is strongly linked to the aged polluted air masses residing over the western Mediterranean in the warm period. Copyright © 2013 Elsevier B.V. All rights reserved.

Mapping Emissions that Contribute to Air Pollution Using Adjoint Sensitivity Analysis

NASA Astrophysics Data System (ADS)

Bastien, L. A. J.; Mcdonald, B. C.; Brown, N. J.; Harley, R.

2014-12-01

The adjoint of the Community Multiscale Air Quality model (CMAQ) is used to map emissions that contribute to air pollution at receptors of interest. Adjoint tools provide an efficient way to calculate the sensitivity of a model response to a large number of model inputs, a task that would require thousands of simulations using a more traditional forward sensitivity approach. Initial applications of this technique, demonstrated here, are to benzene and directly-emitted diesel particulate matter, for which atmospheric reactions are neglected. Emissions of these pollutants are strongly influenced by light-duty gasoline vehicles and heavy-duty diesel trucks, respectively. We study air quality responses in three receptor areas where populations have been identified as especially susceptible to, and adversely affected by air pollution. Population-weighted air basin-wide responses for each pollutant are also evaluated for the entire San Francisco Bay area. High-resolution (1 km horizontal grid) emission inventories have been developed for on-road motor vehicle emission sources, based on observed traffic count data. Emission estimates represent diurnal, day of week, and seasonal variations of on-road vehicle activity, with separate descriptions for gasoline and diesel sources. Emissions that contribute to air pollution at each receptor have been mapped in space and time using the adjoint method. Effects on air quality of both relative (multiplicative) and absolute (additive) perturbations to underlying emission inventories are analyzed. The contributions of local versus upwind sources to air quality in each receptor area are quantified, and weekday/weekend and seasonal variations in the influence of emissions from upwind areas are investigated. The contribution of local sources to the total air pollution burden within the receptor areas increases from about 40% in the summer to about 50% in the winter due to increased atmospheric stagnation. The effectiveness of control strategies based on region-wide exposure metrics is compared with strategies that focus on improving air quality at specific receptors.

A Methodology for Assessing the Impact of Sea Level Rise on Representative Military Installation in the Southwestern United States (RC-1703)

DTIC Science & Technology

2015-04-01

escarpments, relic sediment fans off river mouths , and submarine canyons (courtesy of the Coastal Data Information Program http://cdip.ucsd.edu...with the Source- Pathway-Receptor model. In other words , the question should specify the source of the vulnerability, the receptor that is impacted...works and other infrastructure, renewable and subsistence resources, tourism , recreation, transportation functions, cultural resources, agriculture

RECENT APPLICATIONS OF SOURCE APPORTIONMENT METHODS AND RELATED NEEDS

EPA Science Inventory

Traditional receptor modeling studies have utilized factor analysis (like principal component analysis, PCA) and/or Chemical Mass Balance (CMB) to assess source influences. The limitations with these approaches is that PCA is qualitative and CMB requires the input of source pr...

A shift in emission time profiles of fossil fuel combustion due to energy transitions impacts source receptor matrices for air quality.

PubMed

Hendriks, Carlijn; Kuenen, Jeroen; Kranenburg, Richard; Scholz, Yvonne; Schaap, Martijn

2015-03-01

Effective air pollution and short-lived climate forcer mitigation strategies can only be designed when the effect of emission reductions on pollutant concentrations and health and ecosystem impacts are quantified. Within integrated assessment modeling source-receptor relationships (SRRs) based on chemistry transport modeling are used to this end. Currently, these SRRs are made using invariant emission time profiles. The LOTOS-EUROS model equipped with a source attribution module was used to test this assumption for renewable energy scenarios. Renewable energy availability and thereby fossil fuel back up are strongly dependent on meteorological conditions. We have used the spatially and temporally explicit energy model REMix to derive time profiles for backup power generation. These time profiles were used in LOTOS-EUROS to investigate the effect of emission timing on air pollutant concentrations and SRRs. It is found that the effectiveness of emission reduction in the power sector is significantly lower when accounting for the shift in the way emissions are divided over the year and the correlation of emissions with synoptic situations. The source receptor relationships also changed significantly. This effect was found for both primary and secondary pollutants. Our results indicate that emission timing deserves explicit attention when assessing the impacts of system changes on air quality and climate forcing from short lived substances.

Probability model for atmospheric sulfur dioxide concentrations in the area of Venice

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

Buttazzoni, C.; Lavagnini, I.; Marani, A.

1986-09-01

This paper deals with a comparative screening of existing air quality models based on their ability to simulate the distribution of sulfur dioxide data in the Venetian area. Investigations have been carried out on sulfur dioxide dispersion in the atmosphere of the Venetian area. The studies have been mainly focused on transport models (Gaussian, plume and K-models) aiming at meaningful correlations of sources and receptors. Among the results, a noteworthy disagreement of simulated and experimental data, due to the lack of thorough knowledge of source field conditions and of local meteorology of the sea-land transition area, has been shown. Investigationsmore » with receptor oriented models (based, e.g., on time series analysis, Fourier analysis, or statistical distributions) have also been performed.« less

Regional source identification using Lagrangian stochastic particle dispersion and HYSPLIT backward-trajectory models.

PubMed

Koracin, Darko; Vellore, Ramesh; Lowenthal, Douglas H; Watson, John G; Koracin, Julide; McCord, Travis; DuBois, David W; Chen, L W Antony; Kumar, Naresh; Knipping, Eladio M; Wheeler, Neil J M; Craig, Kenneth; Reid, Stephen

2011-06-01

The main objective of this study was to investigate the capabilities of the receptor-oriented inverse mode Lagrangian Stochastic Particle Dispersion Model (LSPDM) with the 12-km resolution Mesoscale Model 5 (MM5) wind field input for the assessment of source identification from seven regions impacting two receptors located in the eastern United States. The LSPDM analysis was compared with a standard version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) single-particle backward-trajectory analysis using inputs from MM5 and the Eta Data Assimilation System (EDAS) with horizontal grid resolutions of 12 and 80 km, respectively. The analysis included four 7-day summertime events in 2002; residence times in the modeling domain were computed from the inverse LSPDM runs and HYPSLIT-simulated backward trajectories started from receptor-source heights of 100, 500, 1000, 1500, and 3000 m. Statistics were derived using normalized values of LSPDM- and HYSPLIT-predicted residence times versus Community Multiscale Air Quality model-predicted sulfate concentrations used as baseline information. From 40 cases considered, the LSPDM identified first- and second-ranked emission region influences in 37 cases, whereas HYSPLIT-MM5 (HYSPLIT-EDAS) identified the sources in 21 (16) cases. The LSPDM produced a higher overall correlation coefficient (0.89) compared with HYSPLIT (0.55-0.62). The improvement of using the LSPDM is also seen in the overall normalized root mean square error values of 0.17 for LSPDM compared with 0.30-0.32 for HYSPLIT. The HYSPLIT backward trajectories generally tend to underestimate near-receptor sources because of a lack of stochastic dispersion of the backward trajectories and to overestimate distant sources because of a lack of treatment of dispersion. Additionally, the HYSPLIT backward trajectories showed a lack of consistency in the results obtained from different single vertical levels for starting the backward trajectories. To alleviate problems due to selection of a backward-trajectory starting level within a large complex set of 3-dimensional winds, turbulence, and dispersion, results were averaged from all heights, which yielded uniform improvement against all individual cases.

Bayesian Immunological Model Development from the Literature: Example Investigation of Recent Thymic Emigrants†

PubMed Central

Holmes, Tyson H.; Lewis, David B.

2014-01-01

Bayesian estimation techniques offer a systematic and quantitative approach for synthesizing data drawn from the literature to model immunological systems. As detailed here, the practitioner begins with a theoretical model and then sequentially draws information from source data sets and/or published findings to inform estimation of model parameters. Options are available to weigh these various sources of information differentially per objective measures of their corresponding scientific strengths. This approach is illustrated in depth through a carefully worked example for a model of decline in T-cell receptor excision circle content of peripheral T cells during development and aging. Estimates from this model indicate that 21 years of age is plausible for the developmental timing of mean age of onset of decline in T-cell receptor excision circle content of peripheral T cells. PMID:25179832

SOURCE APPORTIONMENT OF PM2.5 AT AN URBAN IMPROVE SITE IN SEATTLE, WA

EPA Science Inventory

The multivariate receptor models Positive Matrix Factorization (PMF) and Unmix were used along with EPA's Chemical Mass Balance model to deduce the sources of PM2.5 at a centrally located urban site in Seattle, Washington. A total of 289 filter samples were obtained with an IM...

Models, Measurements, and Local Decisions: Assessing and ...

EPA Pesticide Factsheets

This presentation includes a combination of modeling and measurement results to characterize near-source air quality in Newark, New Jersey with consideration of how this information could be used to inform decision making to reduce risk of health impacts. Decisions could include either exposure or emissions reduction, and a host of stakeholders, including residents, academics, NGOs, local and federal agencies. This presentation includes results from the C-PORT modeling system, and from a citizen science project from the local area. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Receptor model-based source apportionment of particulate pollution in Hyderabad, India.

PubMed

Guttikunda, Sarath K; Kopakka, Ramani V; Dasari, Prasad; Gertler, Alan W

2013-07-01

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2 ± 24.6, 96.2 ± 12.1, and 64.3 ± 21.2 μg/m(3) of PM10, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m(3). In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM10 and PM2.5 size fractions for three seasons. The receptor modeling results indicated that the PM10 pollution is dominated by the direct vehicular exhaust and road dust (more than 60%). PM2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.

MULTI-MEDIA MODELING : RESEARCH AND DEVELOPMENT

EPA Science Inventory

Developed by ORD in collaboration with OSW, the Multimedia, Multi-pathway, Multi-receptor Risk Assessment (3MRA) national risk assessment methodology is designed to assess risks at sites containing source(s) of contamination that may release contaminants to the environment. Or...

EVALUATION OF THE CMB AND PMF MODELS USING ORGANIC MOLECULAR MARKERS IN FINE PARTICULATE MATTER COLLECTED DURING THE PITTSBURGH AIR QUALITY STUDY

EPA Science Inventory

This research investigated different strategies for source apportionment of airborne fine particulate matter (PM2.5) collected as part of the Pittsburgh Air Quality Study. Two source receptor models were used, the EPA Chemical Mass Balance 8.2 (CMB) and EPA Positive Matrix Facto...

A modified receptor model for source apportionment of heavy metal pollution in soil.

PubMed

Huang, Ying; Deng, Meihua; Wu, Shaofu; Japenga, Jan; Li, Tingqiang; Yang, Xiaoe; He, Zhenli

2018-07-15

Source apportionment is a crucial step toward reduction of heavy metal pollution in soil. Existing methods are generally based on receptor models. However, overestimation or underestimation occurs when they are applied to heavy metal source apportionment in soil. Therefore, a modified model (PCA-MLRD) was developed, which is based on principal component analysis (PCA) and multiple linear regression with distance (MLRD). This model was applied to a case study conducted in a peri-urban area in southeast China where soils were contaminated by arsenic (As), cadmium (Cd), mercury (Hg) and lead (Pb). Compared with existing models, PCA-MLRD is able to identify specific sources and quantify the extent of influence for each emission. The zinc (Zn)-Pb mine was identified as the most important anthropogenic emission, which affected approximately half area for Pb and As accumulation, and approximately one third for Cd. Overall, the influence extent of the anthropogenic emissions decreased in the order of mine (3 km) > dyeing mill (2 km) ≈ industrial hub (2 km) > fluorescent factory (1.5 km) > road (0.5 km). Although algorithm still needs to improved, the PCA-MLRD model has the potential to become a useful tool for heavy metal source apportionment in soil. Copyright © 2018 Elsevier B.V. All rights reserved.

Chemical characterization and receptor modeling of PM10 in the surroundings of the opencast lignite mines of Western Macedonia, Greece.

PubMed

Samara, Constantini; Argyropoulos, George; Grigoratos, Theodoros; Kouras, Αthanasios; Manoli, Εvangelia; Andreadou, Symela; Pavloudakis, Fragkiskos; Sahanidis, Chariton

2018-05-01

The Western Macedonian Lignite Center (WMLC) in northwestern Greece is the major lignite center in the Balkans feeding four major power plants of total power exceeding 4 GW. Concentrations of PM 10 (i.e., particulate matters with diameters ≤10 μm) are the main concern in the region, and the high levels observed are often attributed to the activities related to power generation. In this study, the contribution of fugitive dust emissions from the opencast lignite mines to the ambient levels of PM 10 in the surroundings was estimated by performing chemical mass balance (CMB) receptor modeling. For this purpose, PM 10 samples were concurrently collected at four receptor sites located in the periphery of the mine area during the cold and the warm periods of the year (November-December 2011 and August-September 2012), and analyzed for a total of 26 macro- and trace elements and ionic species (sulfate, nitrate, chloride). The robotic chemical mass balance (RCMB) model was employed for source identification/apportionment of PM 10 at each receptor site using as inputs the ambient concentrations and the chemical profiles of various sources including the major mine operations, the fly ash escaping the electrostatic filters of the power plants, and other primary and secondary sources. Mean measured PM 10 concentrations at the different sites ranged from 38 to 72 μg m -3 . The estimated total contribution of mines ranged between 9 and 22% in the cold period increasing to 36-42% in the dry warm period. Other significant sources were vehicular traffic, biomass burning, and secondary sulfate and nitrate aerosol. These results imply that more efficient measures to prevent and suppress fugitive dust emissions from the mines are needed.

Conceptual site models as a tool in evaluating ecological health: the case of the Department of Energy's Amchitka Island nuclear test site.

PubMed

Burger, Joanna; Mayer, Henry J; Greenberg, Michael; Powers, Charles W; Volz, Conrad D; Gochfeld, Michael

2006-07-01

Managers of contaminated sites are faced with options ranging from monitoring natural attenuation to complete removal of contaminants to meet residential health standards. Conceptual site models (CSMs) are one tool used by the U.S. Department of Energy (DOE) and other environmental managers to understand, track, help with decisions, and communicate with the public about the risk from contamination. CSMs are simplified graphical representations of the sources, releases, transport and exposure pathways, and receptors, along with possible barriers to interdict pathways and reduce exposure. In this article, three CSMs are created using Amchitka Island, where the remaining contamination is from underground nuclear test shot cavities containing large quantities of numerous radionuclides in various physical and chemical forms: (1) a typical underground nuclear test shot CSM (modeled after other sites), (2) an expanded CSM with more complex receptors, and (3) a regional CSM that takes into account contaminant pathways from sources other than Amchitka. The objective was to expand the CSM used by DOE to be more responsive to different types of receptors. Amchitka Island differs from other DOE test shot sites because it is surrounded by a marine environment that is highly productive and has a high biodiversity, and the source of contamination is underground, not on the surface. The surrounding waters of the Bering Sea and North Pacific Ocean are heavily exploited by commercial fisheries and provide the United States and other countries with a significant proportion of its seafood. It is proposed that the CSMs on Amchitka Island should focus more on the pathways of exposure and critical receptors, rather than sources and blocks. Further, CSMs should be incorporated within a larger regional model because of the potentially rapid transport within ocean ecosystems. The large number of migratory or highly mobile species that pass by Amchitka provide the potential for a direct pathway to the local human population, known as Aleut, and commercial fisheries, which are remote from the island itself. The exposure matrix for receptors requires expansion for the Amchitka Island ecosystem because of the valuable marine and seafood resources in the region. CSMs with an expanded exposure/receptor matrix can be used effectively to clarify the conceptualization of the problem for scientists, regulators, and the general public.

A simulation study to quantify the impacts of exposure ...

EPA Pesticide Factsheets

A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Positive Matrix Factorization Model for environmental data analyses

EPA Pesticide Factsheets

Positive Matrix Factorization is a receptor model developed by EPA to provide scientific support for current ambient air quality standards and implement those standards by identifying and quantifying the relative contributions of air pollution sources.

Tropospheric ozone using an emission tagging technique in the CAM-Chem and WRF-Chem models

NASA Astrophysics Data System (ADS)

Lupascu, A.; Coates, J.; Zhu, S.; Butler, T. M.

2017-12-01

Tropospheric ozone is a short-lived climate forcing pollutant. High concentration of ozone can affect human health (cardiorespiratory and increased mortality due to long-term exposure), and also it damages crops. Attributing ozone concentrations to the contributions from different sources would indicate the effects of locally emitted or transported precursors on ozone levels in specific regions. This information could be used as an important component of the design of emissions reduction strategies by indicating which emission sources could be targeted for effective reductions, thus reducing the burden of ozone pollution. Using a "tagging" approach within the CAM-Chem (global) and WRF-Chem (regional) models, we can quantify the contribution of individual emission of NOx and VOC precursors on air quality. Hence, when precursor emissions of NOx are tagged, we have seen that the largest contributors on ozone levels are the anthropogenic sources, while in the case of precursor emissions of VOCs, the biogenic sources and methane account for more than 50% of ozone levels. Further, we have extended the NOx tagging method in order to investigate continental source region contributions to concentrations of ozone over various receptor regions over the globe, with a zoom over Europe. In general, summertime maximum ozone in most receptor regions is largely attributable to local emissions of anthropogenic NOx and biogenic VOC. During the rest of the year, especially during springtime, ozone in most receptor regions shows stronger influences from anthropogenic emissions of NOx and VOC in remote source regions.

Impact of input data uncertainty on environmental exposure assessment models: A case study for electromagnetic field modelling from mobile phone base stations.

PubMed

Beekhuizen, Johan; Heuvelink, Gerard B M; Huss, Anke; Bürgi, Alfred; Kromhout, Hans; Vermeulen, Roel

2014-11-01

With the increased availability of spatial data and computing power, spatial prediction approaches have become a standard tool for exposure assessment in environmental epidemiology. However, such models are largely dependent on accurate input data. Uncertainties in the input data can therefore have a large effect on model predictions, but are rarely quantified. With Monte Carlo simulation we assessed the effect of input uncertainty on the prediction of radio-frequency electromagnetic fields (RF-EMF) from mobile phone base stations at 252 receptor sites in Amsterdam, The Netherlands. The impact on ranking and classification was determined by computing the Spearman correlations and weighted Cohen's Kappas (based on tertiles of the RF-EMF exposure distribution) between modelled values and RF-EMF measurements performed at the receptor sites. The uncertainty in modelled RF-EMF levels was large with a median coefficient of variation of 1.5. Uncertainty in receptor site height, building damping and building height contributed most to model output uncertainty. For exposure ranking and classification, the heights of buildings and receptor sites were the most important sources of uncertainty, followed by building damping, antenna- and site location. Uncertainty in antenna power, tilt, height and direction had a smaller impact on model performance. We quantified the effect of input data uncertainty on the prediction accuracy of an RF-EMF environmental exposure model, thereby identifying the most important sources of uncertainty and estimating the total uncertainty stemming from potential errors in the input data. This approach can be used to optimize the model and better interpret model output. Copyright © 2014 Elsevier Inc. All rights reserved.

Catchment Models and Management Tools for diffuse Contaminants (Sediment, Phosphorus and Pesticides): DIFFUSE Project

NASA Astrophysics Data System (ADS)

Mockler, Eva; Reaney, Simeon; Mellander, Per-Erik; Wade, Andrew; Collins, Adrian; Arheimer, Berit; Bruen, Michael

2017-04-01

The agricultural sector is the most common suspected source of nutrient pollution in Irish rivers. However, it is also often the most difficult source to characterise due to its predominantly diffuse nature. Particulate phosphorus in surface water and dissolved phosphorus in groundwater are of particular concern in Irish water bodies. Hence the further development of models and indices to assess diffuse sources of contaminants are required for use by the Irish Environmental Protection Agency (EPA) to provide support for river basin planning. Understanding connectivity in the landscape is a vital component of characterising the source-pathway-receptor relationships for water-borne contaminants, and hence is a priority in this research. The DIFFUSE Project will focus on connectivity modelling and incorporation of connectivity into sediment, nutrient and pesticide risk mapping. The Irish approach to understanding and managing natural water bodies has developed substantially in recent years assisted by outputs from multiple research projects, including modelling and analysis tools developed during the Pathways and CatchmentTools projects. These include the Pollution Impact Potential (PIP) maps, which are an example of research output that is used by the EPA to support catchment management. The PIP maps integrate an understanding of the pollution pressures and mobilisation pathways and, using the source-pathways-receptor model, provide a scientific basis for evaluation of mitigation measures. These maps indicate the potential risk posed by nitrate and phosphate from diffuse agricultural sources to surface and groundwater receptors and delineate critical source areas (CSAs) as a means of facilitating the targeting of mitigation measures. Building on this previous research, the DIFFUSE Project will develop revised and new catchment managements tools focused on connectivity, sediment, phosphorus and pesticides. The DIFFUSE project will strive to identify the state-of-the-art methods and models that are most applicable to Irish conditions and management challenges. All styles of modelling considered useful for water resources management are relevant to this project and a balance of technical sophistication, data availability and operational practicalities is the ultimate goal. Achievement of this objective will be measured by comparing the performance of the new models developed in the project with models used in other countries. The models and tools developed in the course of the project will be evaluated by comparison with Irish catchment data and with other state-of-the-art models in a model-inter-comparison workshop which will be open to other models and the wider research community.

IMPROVING SOURCE PROFILES AND APPORTIONMENT OF COMBUSTION SOURCES USING THERMAL CARBON FRACTIONS IN MULTIVARIATE RECEPTOR MODELS

EPA Science Inventory

The purpose of this study was to improve combustion source profiles and apportionment of a PM2.5 urban aerosol by using 7 individual organic and elemental carbon thermal fractions in place of total organic and elemental carbon. This study used 3 years (96-99) of speciated data...

Coupling chemical transport model source attributions with positive matrix factorization: application to two IMPROVE sites impacted by wildfires.

PubMed

Sturtz, Timothy M; Schichtel, Bret A; Larson, Timothy V

2014-10-07

Source contributions to total fine particle carbon predicted by a chemical transport model (CTM) were incorporated into the positive matrix factorization (PMF) receptor model to form a receptor-oriented hybrid model. The level of influence of the CTM versus traditional PMF was varied using a weighting parameter applied to an object function as implemented in the Multilinear Engine (ME-2). The methodology provides the ability to separate features that would not be identified using PMF alone, without sacrificing fit to observations. The hybrid model was applied to IMPROVE data taken from 2006 through 2008 at Monture and Sula Peak, Montana. It was able to separately identify major contributions of total carbon (TC) from wildfires and minor contributions from biogenic sources. The predictions of TC had a lower cross-validated RMSE than those from either PMF or CTM alone. Two unconstrained, minor features were identified at each site, a soil derived feature with elevated summer impacts and a feature enriched in sulfate and nitrate with significant, but sporadic contributions across the sampling period. The respective mean TC contributions from wildfires, biogenic emissions, and other sources were 1.18, 0.12, and 0.12 ugC/m(3) at Monture and 1.60, 0.44, and 0.06 ugC/m(3) at Sula Peak.

Application of receptor models on water quality data in source apportionment in Kuantan River Basin

PubMed Central

2012-01-01

Recent techniques in the management of surface river water have been expanding the demand on the method that can provide more representative of multivariate data set. A proper technique of the architecture of artificial neural network (ANN) model and multiple linear regression (MLR) provides an advance tool for surface water modeling and forecasting. The development of receptor model was applied in order to determine the major sources of pollutants at Kuantan River Basin, Malaysia. Thirteen water quality parameters were used in principal component analysis (PCA) and new variables of fertilizer waste, surface runoff, anthropogenic input, chemical and mineral changes and erosion are successfully developed for modeling purposes. Two models were compared in terms of efficiency and goodness-of-fit for water quality index (WQI) prediction. The results show that APCS-ANN model gives better performance with high R2 value (0.9680) and small root mean square error (RMSE) value (2.6409) compared to APCS-MLR model. Meanwhile from the sensitivity analysis, fertilizer waste acts as the dominant pollutant contributor (59.82%) to the basin studied followed by anthropogenic input (22.48%), surface runoff (13.42%), erosion (2.33%) and lastly chemical and mineral changes (1.95%). Thus, this study concluded that receptor modeling of APCS-ANN can be used to solve various constraints in environmental problem that exist between water distribution variables toward appropriate water quality management. PMID:23369363

Assessment of source-specific health effects associated with an unknown number of major sources of multiple air pollutants: a unified Bayesian approach.

PubMed

Park, Eun Sug; Hopke, Philip K; Oh, Man-Suk; Symanski, Elaine; Han, Daikwon; Spiegelman, Clifford H

2014-07-01

There has been increasing interest in assessing health effects associated with multiple air pollutants emitted by specific sources. A major difficulty with achieving this goal is that the pollution source profiles are unknown and source-specific exposures cannot be measured directly; rather, they need to be estimated by decomposing ambient measurements of multiple air pollutants. This estimation process, called multivariate receptor modeling, is challenging because of the unknown number of sources and unknown identifiability conditions (model uncertainty). The uncertainty in source-specific exposures (source contributions) as well as uncertainty in the number of major pollution sources and identifiability conditions have been largely ignored in previous studies. A multipollutant approach that can deal with model uncertainty in multivariate receptor models while simultaneously accounting for parameter uncertainty in estimated source-specific exposures in assessment of source-specific health effects is presented in this paper. The methods are applied to daily ambient air measurements of the chemical composition of fine particulate matter ([Formula: see text]), weather data, and counts of cardiovascular deaths from 1995 to 1997 for Phoenix, AZ, USA. Our approach for evaluating source-specific health effects yields not only estimates of source contributions along with their uncertainties and associated health effects estimates but also estimates of model uncertainty (posterior model probabilities) that have been ignored in previous studies. The results from our methods agreed in general with those from the previously conducted workshop/studies on the source apportionment of PM health effects in terms of number of major contributing sources, estimated source profiles, and contributions. However, some of the adverse source-specific health effects identified in the previous studies were not statistically significant in our analysis, which probably resulted because we incorporated parameter uncertainty in estimated source contributions that has been ignored in the previous studies into the estimation of health effects parameters. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Source contribution analysis of surface particulate polycyclic aromatic hydrocarbon concentrations in northeastern Asia by source-receptor relationships.

PubMed

Inomata, Yayoi; Kajino, Mizuo; Sato, Keiichi; Ohara, Toshimasa; Kurokawa, Jun-ichi; Ueda, Hiromasa; Tang, Ning; Hayakawa, Kazuichi; Ohizumi, Tsuyoshi; Akimoto, Hajime

2013-11-01

We analyzed the source-receptor relationships for particulate polycyclic aromatic hydrocarbon (PAH) concentrations in northeastern Asia using an aerosol chemical transport model. The model successfully simulated the observed concentrations. In Beijing (China) benzo[a]pyren (BaP) concentrations are due to emissions from its own domain. In Noto, Oki and Tsushima (Japan), transboundary transport from northern China (>40 °N, 40-60%) and central China (30-40 °N, 10-40%) largely influences BaP concentrations from winter to spring, whereas the relative contribution from central China is dominant (90%) in Hedo. In the summer, the contribution from Japanese domestic sources increases (40-80%) at the 4 sites. Contributions from Japan and Russia are additional source of BaP over the northwestern Pacific Ocean in summer. The contribution rates for the concentrations from each domain are different among PAH species depending on their particulate phase oxidation rates. Reaction with O3 on particulate surfaces may be an important component of the PAH oxidation processes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Impact of Measurement Uncertainties on Receptor Modeling of Speciated Atmospheric Mercury.

PubMed

Cheng, I; Zhang, L; Xu, X

2016-02-09

Gaseous oxidized mercury (GOM) and particle-bound mercury (PBM) measurement uncertainties could potentially affect the analysis and modeling of atmospheric mercury. This study investigated the impact of GOM measurement uncertainties on Principal Components Analysis (PCA), Absolute Principal Component Scores (APCS), and Concentration-Weighted Trajectory (CWT) receptor modeling results. The atmospheric mercury data input into these receptor models were modified by combining GOM and PBM into a single reactive mercury (RM) parameter and excluding low GOM measurements to improve the data quality. PCA and APCS results derived from RM or excluding low GOM measurements were similar to those in previous studies, except for a non-unique component and an additional component extracted from the RM dataset. The percent variance explained by the major components from a previous study differed slightly compared to RM and excluding low GOM measurements. CWT results were more sensitive to the input of RM than GOM excluding low measurements. Larger discrepancies were found between RM and GOM source regions than those between RM and PBM. Depending on the season, CWT source regions of RM differed by 40-61% compared to GOM from a previous study. No improvement in correlations between CWT results and anthropogenic mercury emissions were found.

Impact of Measurement Uncertainties on Receptor Modeling of Speciated Atmospheric Mercury

PubMed Central

Cheng, I.; Zhang, L.; Xu, X.

2016-01-01

Gaseous oxidized mercury (GOM) and particle-bound mercury (PBM) measurement uncertainties could potentially affect the analysis and modeling of atmospheric mercury. This study investigated the impact of GOM measurement uncertainties on Principal Components Analysis (PCA), Absolute Principal Component Scores (APCS), and Concentration-Weighted Trajectory (CWT) receptor modeling results. The atmospheric mercury data input into these receptor models were modified by combining GOM and PBM into a single reactive mercury (RM) parameter and excluding low GOM measurements to improve the data quality. PCA and APCS results derived from RM or excluding low GOM measurements were similar to those in previous studies, except for a non-unique component and an additional component extracted from the RM dataset. The percent variance explained by the major components from a previous study differed slightly compared to RM and excluding low GOM measurements. CWT results were more sensitive to the input of RM than GOM excluding low measurements. Larger discrepancies were found between RM and GOM source regions than those between RM and PBM. Depending on the season, CWT source regions of RM differed by 40–61% compared to GOM from a previous study. No improvement in correlations between CWT results and anthropogenic mercury emissions were found. PMID:26857835

Global and Regional Modeling of Long-Range Transport and Intercontinental Source-Receptor Linkages

EPA Science Inventory

In this study, we compare air quality over North America simulated by the C-IFS global model and the CMAQ regional model driven by boundary conditions from C-IFS against surface and upper air observations. Results indicate substantial differences in model performance for surface ...

Determining Spatial Variability in PM2.5 Source Impacts across Detroit, MI

EPA Science Inventory

Intra-urban variability in air pollution source impacts was investigated using receptor modeling of daily speciated PM_2.5 measurements collected at residential outdoor locations across Detroit, MI (Wayne County) as part of the Detroit Exposure and Aerosol Research Stud...

Identification of biased sectors in emission data using a combination of chemical transport model and receptor model

NASA Astrophysics Data System (ADS)

Uranishi, Katsushige; Ikemori, Fumikazu; Nakatsubo, Ryohei; Shimadera, Hikari; Kondo, Akira; Kikutani, Yuki; Asano, Katsuyoshi; Sugata, Seiji

2017-10-01

This study presented a comparison approach with multiple source apportionment methods to identify which sectors of emission data have large biases. The source apportionment methods for the comparison approach included both receptor and chemical transport models, which are widely used to quantify the impacts of emission sources on fine particulate matter of less than 2.5 μm in diameter (PM2.5). We used daily chemical component concentration data in the year 2013, including data for water-soluble ions, elements, and carbonaceous species of PM2.5 at 11 sites in the Kinki-Tokai district in Japan in order to apply the Positive Matrix Factorization (PMF) model for the source apportionment. Seven PMF factors of PM2.5 were identified with the temporal and spatial variation patterns and also retained features of the sites. These factors comprised two types of secondary sulfate, road transportation, heavy oil combustion by ships, biomass burning, secondary nitrate, and soil and industrial dust, accounting for 46%, 17%, 7%, 14%, 13%, and 3% of the PM2.5, respectively. The multiple-site data enabled a comprehensive identification of the PM2.5 sources. For the same period, source contributions were estimated by air quality simulations using the Community Multiscale Air Quality model (CMAQ) with the brute-force method (BFM) for four source categories. Both models provided consistent results for the following three of the four source categories: secondary sulfates, road transportation, and heavy oil combustion sources. For these three target categories, the models' agreement was supported by the small differences and high correlations between the CMAQ/BFM- and PMF-estimated source contributions to the concentrations of PM2.5, SO42-, and EC. In contrast, contributions of the biomass burning sources apportioned by CMAQ/BFM were much lower than and little correlated with those captured by the PMF model, indicating large uncertainties in the biomass burning emissions used in the CMAQ simulations. Thus, this comparison approach using the two antithetical models enables us to identify which sectors of emission data have large biases for improvement of future air quality simulations.

Global and Regional Modeling of Long-Range Transport and Intercontinental Source-Receptor Linkages (presentation)

EPA Science Inventory

Because long-range transport has been shown to affect air quality in downwind continents, there is a growing realization that these effects may need to be considered in air quality management efforts by distinguishing between the contributions of local and regional emission sourc...

IMPROVING PARTICULATE MATTER SOURCE APPORTIONMENT FOR HEALTH STUDIES: A TRAINED RECEPTOR MODELING APPROACH WITH SENSITIVITY, UNCERTAINTY AND SPATIAL ANALYSES

EPA Science Inventory

An approach for conducting PM source apportionment will be developed, tested, and applied that directly addresses limitations in current SA methods, in particular variability, biases, and intensive resource requirements. Uncertainties in SA results and sensitivities to SA inpu...

Characterization of VOC sources in an urban area based on PTR-MS measurements and receptor modelling.

PubMed

Stojić, A; Stojić, S Stanišić; Šoštarić, A; Ilić, L; Mijić, Z; Rajšić, S

2015-09-01

In this study, the concentrations of volatile organic compounds were measured by the use of proton transfer reaction mass spectrometry, together with NO x , NO, NO2, SO2, CO and PM10 and meteorological parameters in an urban area of Belgrade during winter 2014. The multivariate receptor model US EPA Unmix was applied to the obtained dataset resolving six source profiles, which can be attributed to traffic-related emissions, gasoline evaporation/oil refineries, petrochemical industry/biogenic emissions, aged plumes, solid-fuel burning and local laboratories. Besides the vehicle exhaust, accounting for 27.6 % of the total mixing ratios, industrial emissions, which are present in three out of six resolved profiles, exert a significant impact on air quality in the urban area. The major contribution of regional and long-range transport was determined for source profiles associated with petrochemical industry/biogenic emissions (40 %) and gasoline evaporation/oil refineries (29 %) using trajectory sector analysis. The concentration-weighted trajectory model was applied with the aim of resolving the spatial distribution of potential distant sources, and the results indicated that emission sources from neighbouring countries, as well as from Slovakia, Greece, Poland and Scandinavian countries, significantly contribute to the observed concentrations.

A Novel Approach for Determining Source-Receptor Relationships of Aerosols in Model Simulations

NASA Astrophysics Data System (ADS)

Ma, P.; Gattiker, J.; Liu, X.; Rasch, P. J.

2013-12-01

The climate modeling community usually performs sensitivity studies in the 'one-factor-at-a-time' fashion. However, owing to the a-priori unknown complexity and nonlinearity of the climate system and simulation response, it is computationally expensive to systematically identify the cause-and-effect of multiple factors in climate models. In this study, we use a Gaussian Process emulator, based on a small number of Community Atmosphere Model Version 5.1 (CAM5) simulations (constrained by meteorological reanalyses) using a Latin Hypercube experimental design, to demonstrate that it is possible to characterize model behavior accurately and very efficiently without any modifications to the model itself. We use the emulator to characterize the source-receptor relationships of black carbon (BC), focusing specifically on describing the constituent burden and surface deposition rates from emissions in various regions. Our results show that the emulator is capable of quantifying the contribution of aerosol burden and surface deposition from different source regions, finding that most of current Arctic BC comes from remote sources. We also demonstrate that the sensitivity of the BC burdens to emission perturbations differs for various source regions. For example, the emission growth in Africa where dry convections are strong results in a moderate increase of BC burden over the globe while the same emission growth in the Arctic leads to a significant increase of local BC burdens and surface deposition rates. These results provide insights into the dynamical, physical, and chemical processes of the climate model, and the conclusions may have policy implications for making cost-effective global and regional pollution management strategies.

Importance of a Global Approach to Using Regional Models in the Assessment of Source-Receptor Relationships of Mercury

EPA Science Inventory

Regional atmospheric models simulate their pertinent processes over a limited portion of the global atmosphere. This portion of the atmosphere can be a large fraction, as in the case of continental-scale modeling, or small fraction, as in the case of urban-scale modeling. Regio...

RECEPTOR MODEL COMPARISONS AND WIND DIRECTION ANALYSES OF VOLATILE ORGANIC COMPOUNDS AND SUBMICROMETER PARTICLES IN AN ARID, BINATIONAL, URBAN AIRSHED

EPA Science Inventory

The relationship between continuous measurements of volatile organic compounds sources and particle number was evaluated at a Photochemical Assessment Monitoring Station Network (PAMS) site located near the U.S.-Mexico Border in central El Paso, TX. Sources of volatile organic...

Separating the Air Quality Impact of a Major Highway and Nearby Sources by Nonparametric Trajectory Analysis

EPA Science Inventory

Nonparametric Trajectory Analysis (NTA), a receptor-oriented model, was used to assess the impact of local sources of air pollution at monitoring sites located adjacent to highway I-15 in Las Vegas, NV. Measurements of black carbon, carbon monoxide, nitrogen oxides, and sulfur di...

Local and regional factors affecting atmospheric mercury speciation at a remote location

USGS Publications Warehouse

Manolopoulos, H.; Schauer, J.J.; Purcell, M.D.; Rudolph, T.M.; Olson, M.L.; Rodger, B.; Krabbenhoft, D.P.

2007-01-01

Atmospheric concentrations of elemental (Hg0), reactive gaseous (RGM), and particulate (PHg) mercury were measured at two remote sites in the midwestern United States. Concurrent measurements of Hg0, PHg, and RGM obtained at Devil's Lake and Mt. Horeb, located approximately 65 km apart, showed that Hg0 and PHg concentrations were affected by regional, as well as local sources, while RGM was mainly impacted by local sources. Plumes reaching the Devil's Lake site from a nearby coal-fired power plant significantly impacted SO2 and RGM concentrations at Devil's Lake, but had little impact on Hg0. Our findings suggest that traditional modeling approaches to assess sources of mercury deposited that utilize source emissions and large-scale grids may not be sufficient to predict mercury deposition at sensitive locations due to the importance of small-scale sources and processes. We suggest the use of a receptor-based monitoring to better understand mercury source-receptor relationships. ?? 2007 NRC Canada.

Estimation of source locations of total gaseous mercury measured in New York State using trajectory-based models

NASA Astrophysics Data System (ADS)

Han, Young-Ji; Holsen, Thomas M.; Hopke, Philip K.

Ambient gaseous phase mercury concentrations (TGM) were measured at three locations in NY State including Potsdam, Stockton, and Sterling from May 2000 to March 2005. Using these data, three hybrid receptor models incorporating backward trajectories were used to identify source areas for TGM. The models used were potential source contribution function (PSCF), residence time weighted concentration (RTWC), and simplified quantitative transport bias analysis (SQTBA). Each model was applied using multi-site measurements to resolve the locations of important mercury sources for New York State. PSCF results showed that southeastern New York, Ohio, Indiana, Tennessee, Louisiana, and Virginia were important TGM source areas for these sites. RTWC identified Canadian sources including the metal production facilities in Ontario and Quebec, but US regional sources including the Ohio River Valley were also resolved. Sources in southeastern NY, Massachusetts, western Pennsylvania, Indiana, and northern Illinois were identified to be significant by SQTBA. The three modeling results were combined to locate the most important probable source locations, and those are Ohio, Indiana, Illinois, and Wisconsin. The Atlantic Ocean was suggested to be a possible source as well.

Reported emissions of organic gases are not consistent with observations

PubMed Central

Henry, Ronald C.; Spiegelman, Clifford H.; Collins, John F.; Park, EunSug

1997-01-01

Regulatory agencies and photochemical models of ozone rely on self-reported industrial emission rates of organic gases. Incorrect self-reported emissions can severely impact on air quality models and regulatory decisions. We compared self-reported emissions of organic gases in Houston, Texas, to measurements at a receptor site near the Houston ship channel, a major petrochemical complex. We analyzed hourly observations of total nonmethane organic carbon and 54 hydrocarbon compounds from C-2 to C-9 for the period June through November, 1993. We were able to demonstrate severe inconsistencies between reported emissions and major sources as derived from the data using a multivariate receptor model. The composition and the location of the sources as deduced from the data are not consistent with the reported industrial emissions. On the other hand, our observationally based methods did correctly identify the location and composition of a relatively small nearby chemical plant. This paper provides strong empirical evidence that regulatory agencies and photochemical models are making predictions based on inaccurate industrial emissions. PMID:11038551

User's guide for RAM. Volume II. Data preparation and listings

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

Turner, D.B.; Novak, J.H.

1978-11-01

The information presented in this user's guide is directed to air pollution scientists having an interest in applying air quality simulation models. RAM is a method of estimating short-term dispersion using the Gaussian steady-state model. These algorithms can be used for estimating air quality concentrations of relatively nonreactive pollutants for averaging times from an hour to a day from point and area sources. The algorithms are applicable for locations with level or gently rolling terrain where a single wind vector for each hour is a good approximation to the flow over the source area considered. Calculations are performed for eachmore » hour. Hourly meteorological data required are wind direction, wind speed, temperature, stability class, and mixing height. Emission information required of point sources consists of source coordinates, emission rate, physical height, stack diameter, stack gas exit velocity, and stack gas temperature. Emission information required of area sources consists of southwest corner coordinates, source side length, total area emission rate and effective area source-height. Computation time is kept to a minimum by the manner in which concentrations from area sources are estimated using a narrow plume hypothesis and using the area source squares as given rather than breaking down all sources into an area of uniform elements. Options are available to the user to allow use of three different types of receptor locations: (1) those whose coordinates are input by the user, (2) those whose coordinates are determined by the model and are downwind of significant point and area sources where maxima are likely to occur, and (3) those whose coordinates are determined by the model to give good area coverage of a specific portion of the region. Computation time is also decreased by keeping the number of receptors to a minimum. Volume II presents RAM example outputs, typical run streams, variable glossaries, and Fortran source codes.« less

Sources and geographic origin of particulate matter in urban areas of the Danube macro-region: The cases of Zagreb (Croatia), Budapest (Hungary) and Sofia (Bulgaria).

PubMed

Perrone, M G; Vratolis, S; Georgieva, E; Török, S; Šega, K; Veleva, B; Osán, J; Bešlić, I; Kertész, Z; Pernigotti, D; Eleftheriadis, K; Belis, C A

2018-04-01

The contribution of main PM pollution sources and their geographic origin in three urban sites of the Danube macro-region (Zagreb, Budapest and Sofia) were determined by combining receptor and Lagrangian models. The source contribution estimates were obtained with the Positive Matrix Factorization (PMF) receptor model and the results were further examined using local wind data and backward trajectories obtained with FLEXPART. Potential Source Contribution Function (PSCF) analysis was applied to identify the geographical source areas for the PM sources subject to long-range transport. Gas-to-particle transformation processes and primary emissions from biomass burning are the most important contributors to PM in the studied sites followed by re-suspension of soil (crustal material) and traffic. These four sources can be considered typical of the Danube macro-region because they were identified in all the studied locations. Long-range transport was observed of: a) sulphate-enriched aged aerosols, deriving from SO 2 emissions in combustion processes in the Balkans and Eastern Europe and b) dust from the Saharan and Karakum deserts. The study highlights that PM pollution in the studied urban areas of the Danube macro-region is the result of both local sources and long-range transport from both EU and no-EU areas. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

An inter-comparison of PM10 source apportionment using PCA and PMF receptor models in three European sites.

PubMed

Cesari, Daniela; Amato, F; Pandolfi, M; Alastuey, A; Querol, X; Contini, D

2016-08-01

Source apportionment of aerosol is an important approach to investigate aerosol formation and transformation processes as well as to assess appropriate mitigation strategies and to investigate causes of non-compliance with air quality standards (Directive 2008/50/CE). Receptor models (RMs) based on chemical composition of aerosol measured at specific sites are a useful, and widely used, tool to perform source apportionment. However, an analysis of available studies in the scientific literature reveals heterogeneities in the approaches used, in terms of "working variables" such as the number of samples in the dataset and the number of chemical species used as well as in the modeling tools used. In this work, an inter-comparison of PM10 source apportionment results obtained at three European measurement sites is presented, using two receptor models: principal component analysis coupled with multi-linear regression analysis (PCA-MLRA) and positive matrix factorization (PMF). The inter-comparison focuses on source identification, quantification of source contribution to PM10, robustness of the results, and how these are influenced by the number of chemical species available in the datasets. Results show very similar component/factor profiles identified by PCA and PMF, with some discrepancies in the number of factors. The PMF model appears to be more suitable to separate secondary sulfate and secondary nitrate with respect to PCA at least in the datasets analyzed. Further, some difficulties have been observed with PCA in separating industrial and heavy oil combustion contributions. Commonly at all sites, the crustal contributions found with PCA were larger than those found with PMF, and the secondary inorganic aerosol contributions found by PCA were lower than those found by PMF. Site-dependent differences were also observed for traffic and marine contributions. The inter-comparison of source apportionment performed on complete datasets (using the full range of available chemical species) and incomplete datasets (with reduced number of chemical species) allowed to investigate the sensitivity of source apportionment (SA) results to the working variables used in the RMs. Results show that, at both sites, the profiles and the contributions of the different sources calculated with PMF are comparable within the estimated uncertainties indicating a good stability and robustness of PMF results. In contrast, PCA outputs are more sensitive to the chemical species present in the datasets. In PCA, the crustal contributions are higher in the incomplete datasets and the traffic contributions are significantly lower for incomplete datasets.

The Air Quality Model Evaluation International Initiative ...

EPA Pesticide Factsheets

This presentation provides an overview of the Air Quality Model Evaluation International Initiative (AQMEII). It contains a synopsis of the three phases of AQMEII, including objectives, logistics, and timelines. It also provides a number of examples of analyses conducted through AQMEII with a particular focus on past and future analyses of deposition. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Evaluation of relative response factor methodology for demonstrating attainment of ozone in Houston, Texas.

PubMed

Vizuete, William; Biton, Leiran; Jeffries, Harvey E; Couzo, Evan

2010-07-01

In 2007, the U.S. Environmental Protection Agency (EPA) released guidance on demonstrating attainment of the federal ozone (O3) standard. This guidance recommended a change in the use of air quality model (AQM) predictions from an absolute to a relative way. This was accomplished by using a ratio, and not the absolute difference of AQM O3 predictions from a historical year to an attainment year. This ratio of O3 concentrations, labeled the relative response factor (RRF), is multiplied by an average of observed concentrations at every monitor. In this analysis, whether the methodology used to calculate RRFs is severing the source-receptor relationship for a given monitor was investigated. Model predictions were generated with a regulatory AQM system used to support the 2004 Houston-Galveston-Brazoria State Implementation Plan. Following the procedures in the EPA guidance, an attainment demonstration was completed using regulatory AQM predictions and measurements from the Houston ground-monitoring network. Results show that the model predictions used for the RRF calculation were often based on model conditions that were geographically remote from observations and counter to wind flow. Many of the monitors used the same model predictions for an RRF, even if that O3 plume did not impact it. The RRF methodology resulted in severing the true source-receptor relationship for a monitor. This analysis also showed that model performance could influence RRF values, and values at monitoring sites appear to be sensitive to model bias. Results indicate an inverse linear correlation of RRFs with model bias at each monitor (R2 = 0.47), resulting in a change in future O3 design values up to 5 parts per billion (ppb). These results suggest that the application of RRF methodology in Houston, TX, should be changed from using all model predictions above 85 ppb to a method that removes any predictions that are not relevant to the observed source-receptor relationship.

Tracer dispersion experiments carried out in London during 2003 and 2004 as part of the DAPPLE project

NASA Astrophysics Data System (ADS)

Martin, D.; Shallcross, D.; Nickless, G.; White, I.

2005-12-01

Transport, dispersion and ultimate fate of pollutants has very important implications for the environment at the urban, regional and global scales. Localised emissions of both man-made and naturally produced pollutants can both directly and indirectly impact the health of the inhabitants. The DAPPLE (Dispersion of Air Pollutants and their Penetration into the Local Environment) consortium consists of six universities, which comprises of a multidisciplinary approach to study relatively small-scale urban atmospheric dispersion. Wind tunnel modelling studies, computer fluid dynamical simulations, fieldwork studies using tracers and dispersion modelling were all carried out in an attempt to achieve this. In this paper we report on tracer dispersion experiments carried out in May 2003 and June 2004. These involve the release of various perfluorocarbon (PFC) tracers centred on Marylebone Road in London. These compounds are inert, non-reactive and have a very low atmospheric background concentration with little variability. These properties make them the ideal atmospheric tracer and this combined with an ultra sensitive analytical technique (sample pre-concentration on carbon based adsorbents followed with detection by Negative Ion Chemical Ionization Mass Spectrometry) makes very small release amounts feasible. The source-receptor relationship is studied for various source and receptor positions and distances. Source receptor relationships for both rooftop and indoor positions were evaluated as part of the project. Results of concurrent meteorological measurements are also presented as well as comparison with a number of simple dispersion models.

SOURCE APPORTIONMENT OF PM2.5 IN SEATTLE, WA URBAN IMPROVE SITE: COMPARISON OF THREE RECEPTOR MODELS AND SOURCE PROFILES

EPA Science Inventory

IMPROVE protocol data were collected at the urban Beacon Hill monitoring site in Seattle, WA from 1996-99. The 289 sets of PM2.5 filters were analyzed for: metals using PIXIE and XRF, anions using ion chromatography, elemental hydrogen (H) by proton scattering, and elemental an...

Constraining Carbonaceous Aerosol Sources in a Receptor Model Using Combined 14C, Redox Species, Organic Tracers, and Elementary/Organic Carbon Measurements

EPA Science Inventory

Sources of carbonaceous PM_2.5 were quantified in downtown Cleveland, OH and Chippewa Lake, OH located ~40 miles southwest of Cleveland during the Cleveland Multiple Air Pollutant Study (CMAPS). PM_2.5 filter samples were collected daily during July-August 200...

Atmospheric transport modelling in support of CTBT verification—overview and basic concepts

NASA Astrophysics Data System (ADS)

Wotawa, Gerhard; De Geer, Lars-Erik; Denier, Philippe; Kalinowski, Martin; Toivonen, Harri; D'Amours, Real; Desiato, Franco; Issartel, Jean-Pierre; Langer, Matthias; Seibert, Petra; Frank, Andreas; Sloan, Craig; Yamazawa, Hiromi

Under the provisions of the Comprehensive Nuclear-Test-Ban Treaty (CTBT), a global monitoring system comprising different verification technologies is currently being set up. The network will include 80 radionuclide (RN) stations distributed all over the globe that measure treaty-relevant radioactive species. While the seismic subsystem cannot distinguish between chemical and nuclear explosions, RN monitoring would provide the "smoking gun" of a possible treaty violation. Atmospheric transport modelling (ATM) will be an integral part of CTBT verification, since it provides a geo-temporal location capability for the RN technology. In this paper, the basic concept for the future ATM software system to be installed at the International Data Centre is laid out. The system is based on the operational computation of multi-dimensional source-receptor sensitivity fields for all RN samples by means of adjoint tracer transport modelling. While the source-receptor matrix methodology has already been applied in the past, the system that we suggest will be unique and unprecedented, since it is global, real-time and aims at uncovering source scenarios that are compatible with measurements. Furthermore, it has to deal with source dilution ratios that are by orders of magnitude larger than in typical transport model applications. This new verification software will need continuous scientific attention, and may well provide a prototype system for future applications in areas of environmental monitoring, emergency response and verification of other international agreements and treaties.

Screening tool to evaluate the vulnerability of down-gradient receptors to groundwater contaminants from uncapped landfills

USGS Publications Warehouse

Baker, Ronald J.; Reilly, Timothy J.; Lopez, Anthony R.; Romanok, Kristin M.; Wengrowski, Edward W

2015-01-01

A screening tool for quantifying levels of concern for contaminants detected in monitoring wells on or near landfills to down-gradient receptors (streams, wetlands and residential lots) was developed and evaluated. The tool uses Quick Domenico Multi-scenario (QDM), a spreadsheet implementation of Domenico-based solute transport, to estimate concentrations of contaminants reaching receptors under steady-state conditions from a constant-strength source. Unlike most other available Domenico-based model applications, QDM calculates the time for down-gradient contaminant concentrations to approach steady state and appropriate dispersivity values, and allows for up to fifty simulations on a single spreadsheet. Sensitivity of QDM solutions to critical model parameters was quantified. The screening tool uses QDM results to categorize landfills as having high, moderate and low levels of concern, based on contaminant concentrations reaching receptors relative to regulatory concentrations. The application of this tool was demonstrated by assessing levels of concern (as defined by the New Jersey Pinelands Commission) for thirty closed, uncapped landfills in the New Jersey Pinelands National Reserve, using historic water-quality data from monitoring wells on and near landfills and hydraulic parameters from regional flow models. Twelve of these landfills are categorized as having high levels of concern, indicating a need for further assessment. This tool is not a replacement for conventional numerically-based transport model or other available Domenico-based applications, but is suitable for quickly assessing the level of concern posed by a landfill or other contaminant point source before expensive and lengthy monitoring or remediation measures are taken. In addition to quantifying the level of concern using historic groundwater-monitoring data, the tool allows for archiving model scenarios and adding refinements as new data become available.

RECEPTOR MODELING OF AMBIENT AND PERSONAL EXPOSURE SAMPLES: 1998 BALTIMORE PARTICULATE MATTER EPIDEMIOLOGY-EXPOSURE STUDY

EPA Science Inventory

Sources of particulate matter exposure for an elderly population in a city north of Baltimore, MD were evaluated using advanced factor analysis models. Data collected with Versatile Air Pollutant Samplers (VAPS) positioned at a community site, outside and inside of an elderly ...

Atmospheric Aerosol Source-Receptor Relationships: The Role of Coal-Fired Power Plants

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

Allen L. Robinson; Spyros N. Pandis; Cliff I. Davidson

2005-12-01

This report describes the technical progress made on the Pittsburgh Air Quality Study (PAQS) during the period of March 2005 through August 2005. Significant progress was made this project period on the source characterization, source apportionment, and deterministic modeling activities. This report highlights new data on road dust, vegetative detritus and motor vehicle emissions. For example, the results show significant differences in the composition in urban and rural road dust. A comparison of the organic of the fine particulate matter in the tunnel with the ambient provides clear evidence of the significant contribution of vehicle emissions to ambient PM. Themore » source profiles developed from this work are being used by the source-receptor modeling activities. The report presents results on the spatial distribution of PMF-factors. The results can be grouped into three different categories: regional sources, local sources, or potentially both regional and local sources. Examples of the regional sources are the sulfate and selenium PMF-factors which most likely-represent coal fired power plants. Examples of local sources are the specialty steel and lead factors. There is reasonable correspondence between these apportionments and data from the EPA TRI and AIRS emission inventories. Detailed comparisons between PMCAMx predictions and measurements by the STN and IMPROVE measurements in the Eastern US are presented. Comparisons were made for the major aerosol components and PM{sub 2.5} mass in July 2001, October 2001, January 2002, and April 2002. The results are encouraging with average fraction biases for most species less than 0.25. The improvement of the model performance during the last two years was mainly due to the comparison of the model predictions with the continuous measurements in the Pittsburgh Supersite. Major improvements have included the descriptions: of ammonia emissions (CMU inventory), night time nitrate chemistry, EC emissions and their diurnal variation, and nitric acid dry removal.« less

CityFlux perfluorocarbon tracer experiments

NASA Astrophysics Data System (ADS)

Petersson, F. K.; Martin, D.; White, I. R.; Henshaw, S. J.; Nickless, G.; Longley, I.; Percival, C. J.; Gallagher, M.; Shallcross, D. E.

2010-01-01

In June 2006, two perfluorocarbon tracer experiments were conducted in central Manchester UK as part of the CityFlux campaign. The main aim was to investigate vertical dispersion in an urban area during convective conditions, but dispersion mechanisms within the street network were also studied. Paired receptors were used in most cases where one receptor was located at ground level and one at roof level. One receptor was located on the roof of Portland Tower which is an 80 m high building in central Manchester. Source receptor distances in the two experiments varied between 120 and 600 m. The results reveal that maximum concentration was sometimes found at roof level rather than at ground level implying the effectiveness of convective forces on dispersion. The degree of vertical dispersion was found to be dependent on source receptor distance as well as on building height in proximity to the release site. Evidence of flow channelling in a street canyon was also found. Both a Gaussian profile and a street network model were applied and the results show that the urban topography may lead to highly effective flow channelling which therefore may be a very important dispersion mechanism should the right meteorological conditions prevail. The experimental results from this campaign have also been compared with a simple urban dispersion model that was developed during the DAPPLE framework and show good agreement with this. The results presented here are some of the first published regarding vertical dispersion. More tracer experiments are needed in order to further characterise vertical concentration profiles and their dependence on, for instance, atmospheric stability. The impact of urban topography on pollutant dispersion is important to focus on in future tracer experiments in order to improve performance of models as well as for our understanding of the relationship between air quality and public health.

CityFlux perfluorocarbon tracer experiments

NASA Astrophysics Data System (ADS)

Petersson, F. K.; Martin, D.; White, I. R.; Henshaw, S. J.; Nickless, G.; Longley, I.; Percival, C. J.; Gallagher, M.; Shallcross, D. E.

2010-07-01

In June 2006, two perfluorocarbon tracer experiments were conducted in central Manchester UK as part of the CityFlux campaign. The main aim was to investigate vertical dispersion in an urban area during convective conditions, but dispersion mechanisms within the street network were also studied. Paired receptors were used in most cases where one receptor was located at ground level and one at roof level. One receptor was located on the roof of Portland Tower which is an 80 m high building in central Manchester. Source receptor distances in the two experiments varied between 120 and 600 m. The results reveal that maximum concentration was sometimes found at roof level rather than at ground level implying the effectiveness of convective forces on dispersion. The degree of vertical dispersion was found to be dependent on source receptor distance as well as on building height in proximity to the release site. Evidence of flow channelling in a street canyon was also found. Both a Gaussian profile and a street network model were applied and the results show that the urban topography may lead to highly effective flow channelling which therefore may be a very important dispersion mechanism should the right meteorological conditions prevail. The experimental results from this campaign have also been compared with a simple urban dispersion model that was developed during the DAPPLE framework and show good agreement with this. The results presented here are some of the first published regarding vertical dispersion. More tracer experiments are needed in order to further characterise vertical concentration profiles and their dependence on, for instance, atmospheric stability. The impact of urban topography on pollutant dispersion is important to focus on in future tracer experiments in order to improve performance of models as well as for our understanding of the relationship between air quality and public health.

Comparing pharmacophore models derived from crystallography and NMR ensembles

NASA Astrophysics Data System (ADS)

Ghanakota, Phani; Carlson, Heather A.

2017-11-01

NMR and X-ray crystallography are the two most widely used methods for determining protein structures. Our previous study examining NMR versus X-Ray sources of protein conformations showed improved performance with NMR structures when used in our Multiple Protein Structures (MPS) method for receptor-based pharmacophores (Damm, Carlson, J Am Chem Soc 129:8225-8235, 2007). However, that work was based on a single test case, HIV-1 protease, because of the rich data available for that system. New data for more systems are available now, which calls for further examination of the effect of different sources of protein conformations. The MPS technique was applied to Growth factor receptor bound protein 2 (Grb2), Src SH2 homology domain (Src-SH2), FK506-binding protein 1A (FKBP12), and Peroxisome proliferator-activated receptor-γ (PPAR-γ). Pharmacophore models from both crystal and NMR ensembles were able to discriminate between high-affinity, low-affinity, and decoy molecules. As we found in our original study, NMR models showed optimal performance when all elements were used. The crystal models had more pharmacophore elements compared to their NMR counterparts. The crystal-based models exhibited optimum performance only when pharmacophore elements were dropped. This supports our assertion that the higher flexibility in NMR ensembles helps focus the models on the most essential interactions with the protein. Our studies suggest that the "extra" pharmacophore elements seen at the periphery in X-ray models arise as a result of decreased protein flexibility and make very little contribution to model performance.

Caffeine, Adenosine Receptors and Estrogen in Toxin Models of Parkinson’s Disease

DTIC Science & Technology

2009-10-01

including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and...dopaminergic neurotransmission in the basal ganglia,[3] raising the possibility (together with other data [4]) of altered risk for PD in this group. In...receptors could fully account for the hypothesized benefits of A2A antagonists against neurodegeneration in PD. The astrocyte A2A cKO data were

Impacts of Lateral Boundary Conditions on US Ozone ...

EPA Pesticide Factsheets

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, we perform annual simulations over North America with chemical boundary conditions prepared from two global models (GEOS-CHEM and Hemispheric CMAQ). Results indicate that the impacts of different boundary conditions on ozone can be significant throughout the year. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Chemical bridges for enhancing hydrogen storage by spillover and methods for forming the same

DOEpatents

Yang, Ralph T.; Li, Yingwei; Qi, Gongshin; Lachawiec, Jr., Anthony J.

2012-12-25

A composition for hydrogen storage includes a source of hydrogen atoms, a receptor, and a chemical bridge formed between the source and the receptor. The chemical bridge is formed from a precursor material. The receptor is adapted to receive hydrogen spillover from the source.

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.

Estimation of the local and long-range contributions to particulate matter levels using continuous measurements in a single urban background site

NASA Astrophysics Data System (ADS)

Diamantopoulou, Marianna; Skyllakou, Ksakousti; Pandis, Spyros N.

2016-06-01

The Particulate Matter Source Apportionment Technology (PSAT) algorithm is used together with PMCAMx, a regional chemical transport model, to develop a simple observation-based method (OBM) for the estimation of local and regional contributions of sources of primary and secondary pollutants in urban areas. We test the hypothesis that the minimum of the diurnal average concentration profile of the pollutant is a good estimate of the average contribution of long range transport levels. We use PMCAMx to generate "pseudo-observations" for four different European cities (Paris, London, Milan, and Dusseldorf) and PSAT to estimate the corresponding "true" local and regional contributions. The predictions of the proposed OBM are compared to the "true" values for different definitions of the source area. During winter, the estimates by the OBM for the local contributions to the concentrations of total PM2.5, primary pollutants, and sulfate are within 25% of the "true" contributions of the urban area sources. For secondary organic aerosol the OBM overestimates the importance of the local sources and it actually estimates the contributions of sources within 200 km from the receptor. During summer for primary pollutants and cities with low nearby emissions (ratio of emissions in an area extending 100 km from the city over local emissions lower than 10) the OBM estimates correspond to the city emissions within 25% or so. For cities with relatively high nearby emissions the OBM estimates correspond to emissions within 100 km from the receptor. For secondary PM2.5 components like sulfate and secondary organic aerosol the OBM's estimates correspond to sources within 200 km from the receptor. Finally, for total PM2.5 the OBM provides approximately the contribution of city emissions during the winter and the contribution of sources within 100 km from the receptor during the summer.

Development and application of air quality models at the US ...

EPA Pesticide Factsheets

Overview of the development and application of air quality models at the U.S. EPA, particularly focused on the development and application of the Community Multiscale Air Quality (CMAQ) model developed within the Computation Exposure Division (CED) of the National Exposure Research Laboratory (NERL). This presentation will provide a simple overview of air quality model development and application geared toward a non-technical student audience. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Pieces of the Puzzle: Tracking the Chemical Component of the ...

EPA Pesticide Factsheets

This presentation provides an overview of the risk assessment conducted at the U.S. EPA, as well as some research examples related to the exposome concept. This presentation also provides the recommendation of using two organizational and predictive frameworks for tracking chemical components in the exposome. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

PAST, PRESENT AND FUTURE AIR QUALITY MODELING AND ITS APPLICATIONS IN THE UNITED STATES

EPA Science Inventory

Since the inception of the Clean Air Act (CAA) in 1969, atmospheric models have been used to assess source-receptor relationships for sulfur dioxide and total suspended particulate matter (TSP) in the urban areas. The focus through the 1970's has been on the Gaussian dispersio...

Chemical compositions and source identification of PM₂.₅ aerosols for estimation of a diesel source surrogate.

PubMed

Sahu, Manoranjan; Hu, Shaohua; Ryan, Patrick H; Le Masters, Grace; Grinshpun, Sergey A; Chow, Judith C; Biswas, Pratim

2011-06-01

Exposure to traffic-related pollution during childhood has been associated with asthma exacerbation, and asthma incidence. The objective of the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) is to determine if the development of allergic and respiratory disease is associated with exposure to diesel engine exhaust particles. A detailed receptor model analyses was undertaken by applying positive matrix factorization (PMF) and UNMIX receptor models to two PM₂.₅ data sets: one consisting of two carbon fractions and the other of eight temperature-resolved carbon fractions. Based on the source profiles resolved from the analyses, markers of traffic-related air pollution were estimated: the elemental carbon attributed to traffic (ECAT) and elemental carbon attributed to diesel vehicle emission (ECAD). Application of UNMIX to the two data sets generated four source factors: combustion related sulfate, traffic, metal processing and soil/crustal. The PMF application generated six source factors derived from analyzing two carbon fractions and seven factors from temperature-resolved eight carbon fractions. The source factors (with source contribution estimates by mass concentrations in parentheses) are: combustion sulfate (46.8%), vegetative burning (15.8%), secondary sulfate (12.9%), diesel vehicle emission (10.9%), metal processing (7.5%), gasoline vehicle emission (5.6%) and soil/crustal (0.7%). Diesel and gasoline vehicle emission sources were separated using eight temperature-resolved organic and elemental carbon fractions. Application of PMF to both datasets also differentiated the sulfate rich source from the vegetative burning source, which are combined in a single factor by UNMIX modeling. Calculated ECAT and ECAD values at different locations indicated that traffic source impacts depend on factors such as traffic volumes, meteorological parameters, and the mode of vehicle operation apart from the proximity of the sites to highways. The difference in ECAT and ECAD, however, was less than one standard deviation. Thus, a cost benefit consideration should be used when deciding on the benefits of an eight or two carbon approach. Published by Elsevier B.V.

3D-QSAR comparative molecular field analysis on opioid receptor antagonists: pooling data from different studies.

PubMed

Peng, Youyi; Keenan, Susan M; Zhang, Qiang; Kholodovych, Vladyslav; Welsh, William J

2005-03-10

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) on a series of opioid receptor antagonists. To obtain statistically significant and robust CoMFA models, a sizable data set of naltrindole and naltrexone analogues was assembled by pooling biological and structural data from independent studies. A process of "leave one data set out", similar to the traditional "leave one out" cross-validation procedure employed in partial least squares (PLS) analysis, was utilized to study the feasibility of pooling data in the present case. These studies indicate that our approach yields statistically significant and highly predictive CoMFA models from the pooled data set of delta, mu, and kappa opioid receptor antagonists. All models showed excellent internal predictability and self-consistency: q(2) = 0.69/r(2) = 0.91 (delta), q(2) = 0.67/r(2) = 0.92 (mu), and q(2) = 0.60/r(2) = 0.96 (kappa). The CoMFA models were further validated using two separate test sets: one test set was selected randomly from the pooled data set, while the other test set was retrieved from other published sources. The overall excellent agreement between CoMFA-predicted and experimental binding affinities for a structurally diverse array of ligands across all three opioid receptor subtypes gives testimony to the superb predictive power of these models. CoMFA field analysis demonstrated that the variations in binding affinity of opioid antagonists are dominated by steric rather than electrostatic interactions with the three opioid receptor binding sites. The CoMFA steric-electrostatic contour maps corresponding to the delta, mu, and kappa opioid receptor subtypes reflected the characteristic similarities and differences in the familiar "message-address" concept of opioid receptor ligands. Structural modifications to increase selectivity for the delta over mu and kappa opioid receptors have been predicted on the basis of the CoMFA contour maps. The structure-activity relationships (SARs) together with the CoMFA models should find utility for the rational design of subtype-selective opioid receptor antagonists.

Using air quality modeling to study source-receptor relationships between nitrogen oxides emissions and ozone exposures over the United States.

PubMed

Tong, Daniel Q; Muller, Nicholas Z; Kan, Haidong; Mendelsohn, Robert O

2009-11-01

Human exposure to ambient ozone (O(3)) has been linked to a variety of adverse health effects. The ozone level at a location is contributed by local production, regional transport, and background ozone. This study combines detailed emission inventory, air quality modeling, and census data to investigate the source-receptor relationships between nitrogen oxides (NO(x)) emissions and population exposure to ambient O(3) in 48 states over the continental United States. By removing NO(x) emissions from each state one at a time, we calculate the change in O(3) exposures by examining the difference between the base and the sensitivity simulations. Based on the 49 simulations, we construct state-level and census region-level source-receptor matrices describing the relationships among these states/regions. We find that, for 43 receptor states, cumulative NO(x) emissions from upwind states contribute more to O(3) exposures than the state's own emissions. In-state emissions are responsible for less than 15% of O(3) exposures in 90% of U.S. states. A state's NO(x) emissions can influence 2 to 40 downwind states by at least a 0.1 ppbv change in population-averaged O(3) exposure. The results suggest that the U.S. generally needs a regional strategy to effectively reduce O(3) exposures. But the current regional emission control program in the U.S. is a cap-and-trade program that assumes the marginal damage of every ton of NO(x) is equal. In this study, the average O(3) exposures caused by one ton of NO(x) emissions ranges from -2.0 to 2.3 ppm-people-hours depending on the state. The actual damage caused by one ton of NO(x) emissions varies considerably over space.

Historical evolution of sources identification by means of Receptor Modeling in the Metropolitan Area of São Paulo, Brazil.

NASA Astrophysics Data System (ADS)

Miranda, R. M.; Andrade, M. D. F.; Marien, Y., Sr.

2017-12-01

The atmospheric aerosols sources have been identified in Sao Paulo since the 80´s with the use of receptor models. The Metropolitan Area of São Paulo (MASP) is a megacity with a population of 21 million, corresponding to more than 11% of the total population of Brazil. The first results for the identification of sources of particles were obtained with the application of Absolute Principal Component Analysis, Factor Analysis and Chemical Mass Balance. More recently the Positive Matrix Factorization has been used in combination with the other receptor models. With the improvement of the aerosol composition analytical determination (more elements and better resolution) the source identification has became more accurate. But, in spite of that, the main sources are the same for fine particles: vehicular emission, secondary formation and biomass burning. The large amount of biofuels used in the MASP makes this region an important example of the atmospheric chemistry of fossil fuel and biofuel emissions. The 7 million vehicles can run on gasohol, ethanol (95% ethanol + 5% gasoline) and biodiesel (mostly for trucks and buses). We have considered the Black Carbon as the tracer for diesel engines and biomass burning, being this last source associated not only with burning of sugar cane plantation and forest fires, but also with wood and charcoal used in restaurant and domestic cooking and residues burning. The responsibility of the vehicular emission to the fine particles has been maintained in approximately 50% of the mass. The soil resuspension was associated with 8% of the fine particles origin. We are presenting the data obtained from experiments performed from 1983 to 2014, not continuously and mainly performed in the winter time. It is a long period of data that is going to be considered. The previous results obtained with the application of PCA were compared to that obtained with PMF applied to the historical data collected at MASP, showing the evolution of the participation of mobile and biomass burning.

Application of genetic algorithm for the simultaneous identification of atmospheric pollution sources

NASA Astrophysics Data System (ADS)

Cantelli, A.; D'Orta, F.; Cattini, A.; Sebastianelli, F.; Cedola, L.

2015-08-01

A computational model is developed for retrieving the positions and the emission rates of unknown pollution sources, under steady state conditions, starting from the measurements of the concentration of the pollutants. The approach is based on the minimization of a fitness function employing a genetic algorithm paradigm. The model is tested considering both pollutant concentrations generated through a Gaussian model in 25 points in a 3-D test case domain (1000m × 1000m × 50 m) and experimental data such as the Prairie Grass field experiments data in which about 600 receptors were located along five concentric semicircle arcs and the Fusion Field Trials 2007. The results show that the computational model is capable to efficiently retrieve up to three different unknown sources.

Ligands for Ionotropic Glutamate Receptors

PubMed Central

Swanson, Geoffrey T.; Sakai, Ryuichi

2010-01-01

Marine-derived small molecules and peptides have played a central role in elaborating pharmacological specificities and neuronal functions of mammalian ionotropic glutamate receptors (iGluRs), the primary mediators of excitatory synaptic transmission in the central nervous system (CNS). As well, the pathological sequelae elicited by one class of compounds (the kainoids) constitute a widely-used animal model for human mesial temporal lobe epilepsy (mTLE). New and existing molecules could prove useful as lead compounds for the development of therapeutics for neuropathologies that have aberrant glutamatergic signaling as a central component. In this chapter we discuss natural source origins and pharmacological activities of those marine compounds that target ionotropic glutamate receptors. PMID:19184587

Ligands for Ionotropic Glutamate Receptors

NASA Astrophysics Data System (ADS)

Swanson, Geoffrey T.; Sakai, Ryuichi

Marine-derived small molecules and peptides have played a central role in elaborating pharmacological specificities and neuronal functions of mammalian ionotropic glutamate receptors (iGluRs), the primary mediators of excitatory syn-aptic transmission in the central nervous system (CNS). As well, the pathological sequelae elicited by one class of compounds (the kainoids) constitute a widely-used animal model for human mesial temporal lobe epilepsy (mTLE). New and existing molecules could prove useful as lead compounds for the development of therapeutics for neuropathologies that have aberrant glutamatergic signaling as a central component. In this chapter we discuss natural source origins and pharmacological activities of those marine compounds that target ionotropic glutamate receptors.

PM2.5 Source Apportionment: Reconciling Receptor Models for U.S. Nonurban and Urban Long-Term Networks.

PubMed

Chen, L-W Antony; Watson, John G; Chow, Judith C; DuBois, Dave W; Herschberger, Lisa

2011-11-01

Chemical mass balance (CMB) and trajectory receptor models were applied to speciated particulate matter with aerodynamic diameter ≤2.5 μm (PM 2.5 ) measurements from Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network across the state of Minnesota as part of the Minnesota PM 2.5 Source Apportionment Study (MPSAS). CMB equations were solved by the Unmix, positive matrix factorization (PMF), and effective variance (EV) methods, giving collective source contribution and uncertainty estimates. Geological source profiles developed from local dust materials were either incorporated into the EV-CMB model or used to verify factors derived from Unmix and PMF. Common sources include soil dust, calcium (Ca)-rich dust, diesel and gasoline vehicle exhausts, biomass burning, secondary sulfate, and secondary nitrate. Secondary sulfate and nitrate aerosols dominate PM 2.5 mass (50-69%). Mobile sources outweigh area sources at urban sites, and vice versa at rural sites due to traffic emissions. Gasoline and diesel contributions can be separated using data from the STN, despite significant uncertainties. Major differences between MPSAS and earlier studies on similar environments appear to be the type and magnitude of stationary sources, but these sources are generally minor (<7%) in this and other studies. Ensemble back-trajectory analysis shows that the lower Midwestern states are the predominant source region for secondary ammoniated sulfate in Minnesota. It also suggests substantial contributions of biomass burning and soil dust from out-of-state on occasions, although a quantitative separation of local and regional contributions was not achieved in the current study. Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for a summary of input data, Unmix and PMF factor profiles, and additional maps. [Box: see text].

Sensitivity tests to define the source apportionment performance criteria in the DeltaSA tool

NASA Astrophysics Data System (ADS)

Pernigotti, Denise; Belis, Claudio A.

2017-04-01

Identification and quantification of the contribution of emission sources to a given area is a key task for the design of abatement strategies. Moreover, European member states are obliged to report this kind of information for zones where the pollution levels exceed the limit values. At present, little is known about the performance and uncertainty of the variety of methodologies used for source apportionment and the comparability between the results of studies using different approaches. The source apportionment Delta (SA Delta) is a tool developed by the EC-JRC to support the particulate matter source apportionment modellers in the identification of sources (for factor analysis studies) and/or in the measure of their performance. The source identification is performed by the tool measuring the proximity of any user chemical profile to preloaded repository data (SPECIATE and SPECIEUROPE). The model performances criteria are based on standard statistical indexes calculated by comparing participants' source contribute estimates and their time series with preloaded references data. Those preloaded data refer to previous European SA intercomparison exercises: the first with real world data (22 participants), the second with synthetic data (25 participants) and the last with real world data which was also extended to Chemical Transport Models (38 receptor models and 4 CTMs). The references used for the model performances are 'true' (predefined by JRC) for the synthetic while they are calculated as ensemble average of the participants' results in real world intercomparisons. The candidates used for each source ensemble reference calculation were selected among participants results based on a number of consistency checks plus the similarity between their chemical profiles to the repository measured data. The estimation of the ensemble reference uncertainty is crucial in order to evaluate the users' performances against it. For this reason a sensitivity analysis on different methods to estimate the ensemble references' uncertainties was performed re-analyzing the synthetic intercomparison dataset, the only one where 'true' reference and ensemble reference contributions were both present. The Delta SA is now available on-line and will be presented, with a critical discussion of the sensitivity analysis on the ensemble reference uncertainty. In particular the grade of among participants mutual agreement on the presence of a certain source should be taken into account. Moreover also the importance of the synthetic intercomparisons in order to catch receptor models common biases will be stressed.

Enhanced global Radionuclide Source Attribution for the Nuclear-Test-Ban Verification by means of the Adjoint Ensemble Dispersion Modeling Technique applied at the IDC/CTBTO.

NASA Astrophysics Data System (ADS)

Becker, A.; Wotawa, G.; de Geer, L.

2006-05-01

The Provisional Technical Secretariat (PTS) of the CTBTO Preparatory Commission maintains and permanently updates a source-receptor matrix (SRM) describing the global monitoring capability of a highly sensitive 80 stations radionuclide (RN) network in order to verify states signatories' compliance of the comprehensive nuclear-test-ban treaty (CTBT). This is done by means of receptor-oriented Lagrangian particle dispersion modeling (LPDM) to help determine the region from which suspicious radionuclides may originate. In doing so the LPDM FLEXPART5.1 is integrated backward in time based on global analysis wind fields yielding global source-receptor sensitivity (SRS) fields stored in three-hour frequency and at 1º horizontal resolution. A database of these SRS fields substantially helps in improving the interpretation of the RN samples measurements and categorizations because it enables the testing of source-hypothesis's later on in a pure post-processing (SRM inversion) step being feasible on hardware with specifications comparable to currently sold PC's or Notebooks and at any place (decentralized), provided access to the SRS fields is warranted. Within the CTBT environment it is important to quickly achieve decision-makers confidence in the SRM based backtracking products issued by the PTS in the case of the occurrence of treaty relevant radionuclides. Therefore the PTS has set up a highly automated response system together with the Regional Specialized Meteorological Centers of the World Meteorological Organization in the field of dispersion modeling who committed themselves to provide the PTS with the same standard SRS fields as calculated by their systems for CTBT relevant cases. This system was twice utilized in 2005 in order to perform adjoint ensemble dispersion modeling (EDM) and demonstrated the potential of EDM based backtracking to improve the accuracy of the source location related to singular nuclear events thus serving the backward analogue to the findings of the ensemble dispersion modeling (EDM) technique No. 5 efforts performed by Galmarini et al, 2004 (Atmos. Env. 38, 4607-4617). As the scope of the adjoint EDM methodology is not limited to CTBT verification but can be applied to any kind of nuclear event monitoring and location it bears the potential to improve the design of manifold emergency response systems towards preparedness concepts as needed for mitigation of disasters (like Chernobyl) and pre-emptive estimation of pollution hazards.

Impact of source collinearity in simulated PM 2.5 data on the PMF receptor model solution

NASA Astrophysics Data System (ADS)

Habre, Rima; Coull, Brent; Koutrakis, Petros

2011-12-01

Positive Matrix Factorization (PMF) is a factor analytic model used to identify particle sources and to estimate their contributions to PM 2.5 concentrations observed at receptor sites. Collinearity in source contributions due to meteorological conditions introduces uncertainty in the PMF solution. We simulated datasets of speciated PM 2.5 concentrations associated with three ambient particle sources: "Motor Vehicle" (MV), "Sodium Chloride" (NaCl), and "Sulfur" (S), and we varied the correlation structure between their mass contributions to simulate collinearity. We analyzed the datasets in PMF using the ME-2 multilinear engine. The Pearson correlation coefficients between the simulated and PMF-predicted source contributions and profiles are denoted by " G correlation" and " F correlation", respectively. In sensitivity analyses, we examined how the means or variances of the source contributions affected the stability of the PMF solution with collinearity. The % errors in predicting the average source contributions were 23, 80 and 23% for MV, NaCl, and S, respectively. On average, the NaCl contribution was overestimated, while MV and S contributions were underestimated. The ability of PMF to predict the contributions and profiles of the three sources deteriorated significantly as collinearity in their contributions increased. When the mean of NaCl or variance of NaCl and MV source contributions was increased, the deterioration in G correlation with increasing collinearity became less significant, and the ability of PMF to predict the NaCl and MV loading profiles improved. When the three factor profiles were simulated to share more elements, the decrease in G and F correlations became non-significant. Our findings agree with previous simulation studies reporting that correlated sources are predicted with higher error and bias. Consequently, the power to detect significant concentration-response estimates in health effect analyses weakens.

Docking-based Screening of Ficus religiosa Phytochemicals as Inhibitors of Human Histamine H2 Receptor.

PubMed

Chaudhary, Amit; Yadav, Birendra Singh; Singh, Swati; Maurya, Pramod Kumar; Mishra, Alok; Srivastva, Shweta; Varadwaj, Pritish Kumar; Singh, Nand Kumar; Mani, Ashutosh

2017-10-01

Ficus religiosa L. is generally known as Peepal and belongs to family Moraceae . The tree is a source of many compounds having high medicinal value. In gastrointestinal tract, histamine H2 receptors have key role in histamine-stimulated gastric acid secretion. Their over stimulation causes its excessive production which is responsible for gastric ulcer. This study aims to screen the range of phytochemicals present in F. religiosa for binding with human histamine H2 and identify therapeutics for a gastric ulcer from the plant. In this work, a 3D-structure of human histamine H2 receptor was modeled by using homology modeling and the predicted model was validated using PROCHECK. Docking studies were also performed to assess binding affinities between modeled receptor and 34 compounds. Molecular dynamics simulations were done to identify most stable receptor-ligand complexes. Absorption, distribution, metabolism, excretion, and screening was done to evaluate pharmacokinetic properties of compounds. The results suggest that seven ligands, namely, germacrene, bergaptol, lanosterol, Ergost-5-en-3beta-ol, α-amyrin acetate, bergapten, and γ-cadinene showed better binding affinities. Among seven phytochemicals, lanosterol and α-amyrin acetate were found to have greater stability during simulation studies. These two compounds may be a suitable therapeutic agent against histamine H2 receptor. This study was performed to screen antiulcer compounds from F. religiosa . Molecular modeling, molecular docking and MD simulation studies were performed with selected phytochemicals from F. religiosa . The analysis suggests that Lanosterol and α-amyrin may be a suitable therapeutic agent against histamine H2 receptor. This study facilitates initiation of the herbal drug discovery process for the antiulcer activity. Abbreviations used: ADMET: Absorption, distribution, metabolism, excretion and toxicity, DOPE: Discrete Optimized Potential Energy, OPLS: Optimized potential for liquid simulations, RMSD: Root-mean-square deviation, HOA: Human oral absorption, MW: Molecular weight, SP: Standard-precision, XP: Extra-precision, GPCRs: G protein-coupled receptors, SASA: Solvent accessible surface area, Rg: Radius of gyration, NHB: Number of hydrogen bond.

Historical and Future Trends in Global Source-receptor Relationships of Mercury

NASA Astrophysics Data System (ADS)

Chen, L.; Zhang, W.; Wang, X.

2017-12-01

Growing concerns about the risk associated with increasing environmental Mercury (Hg) levels have resulted in a focus on the relationships between intercontinental emitted and accumulated Hg. We use a global biogeochemical Hg model with eight continental regions and a global ocean to evaluate the legacy impacts of historical anthropogenic releases (2000 BC to 2008 AD) on global source-receptor relationships of Hg. The legacy impacts of historical anthropogenic releases are confirmed to be significant on the source-receptor relationships according to our results. Historical anthropogenic releases from Asia account for 8% of total soil Hg in North America, which is smaller than the proportion ( 17%) from previous studies. The largest contributors to the global oceanic Hg are historical anthropogenic releases from North America (26%), Asia (16%), Europe (14%) and South America (14%). Although anthropogenic releases from Asia have exceeded North America since the 1970s, source contributions to global Hg receptors from Asia have not exceeded North America so far. Future projections indicate that if Hg emissions are not effectively controlled, Asia will exceed North America as the largest contributor to the global ocean in 2019 and this has a long-term adverse impact on the future environment. For the Arctic Ocean, historical anthropogenic release from North America contributes most to the oceanic Hg reservoir and future projections reveal that the legacy impacts of historical releases from mid-latitudes would lead to the potential of rising Hg in the Arctic Ocean in the future decades, which calls for more effective Hg controls on mid-latitude releases.

Historical and future trends in global source-receptor relationships of mercury.

PubMed

Chen, Long; Zhang, Wei; Zhang, Yanxu; Tong, Yindong; Liu, Maodian; Wang, Huanhuan; Xie, Han; Wang, Xuejun

2018-01-01

Growing concern about the risk associated with increasing environmental mercury (Hg) concentrations has resulted in a focus on the relationships between intercontinental emitted and accumulated Hg. We use a global biogeochemical Hg model with 8 continental regions and a global ocean to evaluate the legacy impacts of historical anthropogenic releases (2000BCE to 2008AD) on global source-receptor relationships of Hg. Legacy impacts of historical anthropogenic releases are confirmed to be significant on the source-receptor relationships according to our results. Historical anthropogenic releases from Asia account for 8% of total soil Hg in North America, which is smaller than the proportion (~17%) from previous studies. The largest contributors to the global oceanic Hg are historical anthropogenic releases from North America (26%), Asia (16%), Europe (14%) and South America (14%). Although anthropogenic releases from Asia have exceeded North America since the 1970s, source contributions to global Hg receptors from Asia have not exceeded North America so far. Future projections indicate that if Hg emissions are not effectively controlled, Asia will exceed North America as the largest contributor to the global ocean in 2019 and this has a long-term adverse impact on the future environment. For the Arctic Ocean, historical anthropogenic release from North America contributes most to the oceanic Hg reservoir and future projections reveal that the legacy impacts of historical releases from mid-latitudes would lead to the potential of rising Hg in the Arctic Ocean in the future decades, which calls for more effective Hg controls on mid-latitude releases. Copyright © 2017 Elsevier B.V. All rights reserved.

WRF/CMAQ AQMEII3 Simulations of US Regional-Scale ...

EPA Pesticide Factsheets

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, performed during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), we perform annual simulations over North America with chemical boundary conditions prepared from four different global models. Results indicate that the impacts of different boundary conditions are significant for ozone throughout the year and most pronounced outside the summer season. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Seasonal changes, identification and source apportionment of PAH in PM1.0

NASA Astrophysics Data System (ADS)

Agudelo-Castañeda, Dayana Milena; Teixeira, Elba Calesso

2014-10-01

The objective of this research was to evaluate the seasonal variation of PAHs in PM1.0, as well as to identify and quantify the contributions of each source profile using the PMF receptor model. PM1.0 samples were collected on PTFE filters from August 2011 to July 2013 in the Metropolitan Area of Porto Alegre, Rio Grande do Sul, Brazil. The samples were extracted using the EPA method TO-13A and 16 Polycyclic Aromatic Hydrocarbons (PAHs) were analyzed using a gaseous chromatograph coupled with a mass spectrometer (GC-MS). Also, the data discussed in this study were analyzed to identify the relations of the PAHs concentrations with NOx, NO, O3 and meteorological parameters (temperature, solar radiation, wind speed, relative humidity). The results showed that in winter, concentrations of total PAHs were significantly higher than in summer, thus showing their seasonal variation. The identification of emission sources by applying diagnostic ratios confirmed that PAHs in the study area originate from mobile sources, especially, from diesel and gasoline emissions. The analysis by PMF receptor model showed the contribution of these two main sources of emissions, too, followed by coal combustion, incomplete combustion/unburned petroleum and wood combustion. The toxic equivalent factors were calculated to characterize the risk of cancer from PAH exposure to PM1.0 samples, and BaP and DahA dominated BaPeq levels.

Response of dissolved trace metals to land use/land cover and their source apportionment using a receptor model in a subtropic river, China.

PubMed

Li, Siyue; Zhang, Quanfa

2011-06-15

Water samples were collected for determination of dissolved trace metals in 56 sampling sites throughout the upper Han River, China. Multivariate statistical analyses including correlation analysis, stepwise multiple linear regression models, and principal component and factor analysis (PCA/FA) were employed to examine the land use influences on trace metals, and a receptor model of factor analysis-multiple linear regression (FA-MLR) was used for source identification/apportionment of anthropogenic heavy metals in the surface water of the River. Our results revealed that land use was an important factor in water metals in the snow melt flow period and land use in the riparian zone was not a better predictor of metals than land use away from the river. Urbanization in a watershed and vegetation along river networks could better explain metals, and agriculture, regardless of its relative location, however slightly explained metal variables in the upper Han River. FA-MLR analysis identified five source types of metals, and mining, fossil fuel combustion, and vehicle exhaust were the dominant pollutions in the surface waters. The results demonstrated great impacts of human activities on metal concentrations in the subtropical river of China. Copyright © 2011 Elsevier B.V. All rights reserved.

A new conceptual model for quantifying transboundary contribution of atmospheric pollutants in the East Asian Pacific rim region.

PubMed

Lai, I-Chien; Lee, Chon-Lin; Huang, Hu-Ching

2016-03-01

Transboundary transport of air pollution is a serious environmental concern as pollutant affects both human health and the environment. Many numerical approaches have been utilized to quantify the amounts of pollutants transported to receptor regions, based on emission inventories from possible source regions. However, sparse temporal-spatial observational data and uncertainty in emission inventories might make the transboundary transport contribution difficult to estimate. This study presents a conceptual quantitative approach that uses transport pathway classification in combination with curve fitting models to simulate an air pollutant concentration baseline for pollution background concentrations. This approach is used to investigate the transboundary transport contribution of atmospheric pollutants to a metropolitan area in the East Asian Pacific rim region. Trajectory analysis categorized pollution sources for the study area into three regions: East Asia, Southeast Asia, and Taiwan cities. The occurrence frequency and transboundary contribution results suggest the predominant source region is the East Asian continent. This study also presents an application to evaluate heavy pollution cases for health concerns. This new baseline construction model provides a useful tool for the study of the contribution of transboundary pollution delivered to receptors, especially for areas deficient in emission inventories and regulatory monitoring data for harmful air pollutants. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modelling of deposited black carbon with the Lagrangian particle dispersion model FLEXPART in backward mode

NASA Astrophysics Data System (ADS)

Eckhardt, Sabine; Cassiani, Massimo; Sollum, Espen; Evangeliou, Nikolaos; Stohl, Andreas

2017-04-01

Lagrangian particle dispersion models are popular tools to simulate the dispersion of trace gases, aerosols or radionuclides in the atmosphere. If they consider only linear processes, they are self-adjoint, i.e., they can be run forward and backward in time without changes to the source code. Backward simulations are very efficient if the number of receptors is smaller than the number of sources, and they are well suited to establish source-receptor (s-r) relationships for measurements of various trace substances in air. However, not only the air concentrations are of interest, but also the s-r relationships for deposition are important for interpreting measurement data. E.g., deposition of dust is measured regularly in ice cores, partly also as a proxy to understand changes in aridity in dust source regions. Contamination of snow by black carbon (BC) aerosols has recently become a hot topic because of the potential impact of BC on the snow albedo. To interpret such deposition measurements and study the sources of the deposited substance, it would be convenient to have a model that is capable of efficient s-r relationship calculations for such types of measurements. We present here the implementation of such an algorithm into the Lagrangian particle dispersion model FLEXPART, and test the new scheme by comparisons with results from forward simulations as well as comparisons with measurements. As an application, we analyse source regions for elemental carbon (EC) measured in snow over the years 2014-2016 in the Russian Arctic. Simulations using an annual constant black carbon inventory based on ECLIPSE V5 and GFED (Global Fire Emission Database), have been performed. The meteorological data used in the simulation are 3 hourly operational data from the European Centre of Medium Range Weather Forecast (ECMWF) on a 1 degree grid resolution and 138 vertical levels. The model is able to capture very well the measured concentrations. Gas flaring and residential/commercial combustion can be identified as the most important sources. High concentrations measured near the Ob River (up to 170 ng g-1) can be associated with air masses coming from Europe.

Inter-comparison of source apportionment of PM10 using PMF and CMB in three sites nearby an industrial area in central Italy

NASA Astrophysics Data System (ADS)

Cesari, Daniela; Donateo, Antonio; Conte, Marianna; Contini, Daniele

2016-12-01

Receptor models (RMs), based on chemical composition of particulate matter (PM), such as Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF), represent useful tools for determining the impact of PM sources to air quality. This information is useful, especially in areas influenced by anthropogenic activities, to plan mitigation strategies for environmental management. Recent inter-comparison of source apportionment (SA) results showed that one of the difficulties in the comparison of estimated source contributions is the compatibility of the sources, i.e. the chemical profiles of factor/sources used in receptor models. This suggests that SA based on integration of several RMs could give more stable and reliable solutions with respect to a single model. The aim of this work was to perform inter-comparison of PMF (using PMF3.0 and PMF5.0 codes) and CMB outputs, focusing on both source chemical profiles and estimates of source contributions. The dataset included 347 daily PM10 samples collected in three sites in central Italy located near industrial emissions. Samples were chemically analysed for the concentrations of 21 chemical species (NH4+, Ca2 +, Mg2 +, Na+, K+, Mg2 +, SO42 -, NO3-, Cl-, Si, Al, Ti, V, Mn, Fe, Ni, Cu, Zn, Br, EC, and OC) used as input of RMs. The approach identified 9 factor/sources: marine, traffic, resuspended dust, biomass burning, secondary sulphate, secondary nitrate, crustal, coal combustion power plant and harbour-industrial. Results showed that the application of constraints in PMF5.0 improved interpretability of profiles and comparability of estimated source contributions with stoichiometric calculations. The inter-comparison of PMF and CMB gave significant differences for secondary nitrate, biomass burning, and harbour-industrial sources, due to non-compatibility of these source profiles that have local specificities. When these site-dependent specificities were taken into account, optimising the input source profiles of CMB, a significant improvement in the comparison of the estimated source contributions with PMF was obtained.

Source attribution of black carbon in Arctic snow.

PubMed

Hegg, Dean A; Warren, Stephen G; Grenfell, Thomas C; Doherty, Sarah J; Larson, Timothy V; Clarke, Antony D

2009-06-01

Snow samples obtained at 36 sites in Alaska, Canada, Greenland, Russia, and the Arctic Ocean in early 2007 were analyzed for light-absorbing aerosol concentration together with a suite of associated chemical species. The light absorption data, interpreted as black carbon concentrations, and other chemical data were input into the EPA PMF 1.1 receptor model to explore the sources for black carbon in the snow. The analysis found four factors or sources: two distinct biomass burning sources, a pollution source, and a marine source. The first three of these were responsible for essentially all of the black carbon, with the two biomass sources (encompassing both open and closed combustion) together accounting for >90% of the black carbon.

Computational toxicology and in silico modeling of embryogenesis

EPA Science Inventory

High-throughput screening (HTS) is providing a rich source of in vitro data for predictive toxicology. ToxCast™ HTS data presently covers 1060 broad-use chemicals and captures >650 in vitro features for diverse biochemical and receptor binding activities, multiplexed reporter gen...

PARTITION COEFFICIENTS FOR METALS IN SURFACE WATER, SOIL, AND WASTE

EPA Science Inventory

This report presents metal partition coefficients for the surface water pathway and for the source model used in the Multimedia, Multi-pathway, Multi-receptor Exposure and Risk Assessment (3MRA) technology under development by the U.S. Environmental Protection Agency. Partition ...

Characterizing and sourcing ambient PM2.5 over key emission regions in China II: Organic molecular markers and CMB modeling

NASA Astrophysics Data System (ADS)

Zhou, Jiabin; Xiong, Ying; Xing, Zhenyu; Deng, Junjun; Du, Ke

2017-08-01

From November 2012 to July 2013, a sampling campaign was completed for comprehensive characterization of PM2.5 over four key emission regions in China: Beijing-Tianjin-Hebei (BTH), Yangzi River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SB). A multi-method approach, adopting different analytical and receptor modeling methods, was employed to determine the relative abundances of region-specific air pollution constituents and contributions of emission sources. This paper is focused on organic molecular marker based source apportionment using chemical mass balance (CMB) receptor modeling. Analyses of the organic molecular markers revealed that vehicle emission, coal combustion, biomass burning, meat cooking and natural gas combustion were the major contributors to organic carbon (OC) in PM2.5. The vehicle emission dominated the sources contributing to OC in spring at four sampling sites. During wintertime, the coal combustion had highest contribution to OC at BTH site, while the major source contributing to OC at YRD and PRD sites was vehicle emission. In addition, the relative contributions of different emission sources to PM2.5 mass at a specific location site and in a specific season revealed seasonal and spatial variations across all four sampling locations. The largest contributor to PM2.5 mass was secondary sulfate (14-17%) in winter at the four sites. The vehicle emission was found to be the major source (14-21%) for PM2.5 mass at PRD site. The secondary ammonium has minor variation (4-5%) across the sites, confirming the influences of regional emission sources on these sites. The distinct patterns of seasonal and spatial variations of source apportionment observed in this study were consistent with the findings in our previous paper based upon water-soluble ions and carbonaceous fractions. This makes it essential for the local government to make season- and region-specific mitigation strategies for abating PM2.5 pollution in China.

Global Source-Receptor Relationships for Mercury Deposition Under Present-Day and 2050 Emissions Scenarios

PubMed Central

Corbitt, Elizabeth S.; Jacob, Daniel J.; Holmes, Christopher D.; Streets, David G.; Sunderland, Elsie M.

2011-01-01

Global policies regulating anthropogenic mercury require an understanding of the relationship between emitted and deposited mercury on intercontinental scales. Here we examine source-receptor relationships for present-day conditions and for four 2050 IPCC scenarios encompassing a range of economic development and environmental regulation projections. We use the GEOS-Chem global model to track mercury from its point of emission through rapid cycling in surface ocean and land reservoirs to its accumulation in longer-lived ocean and soil pools. Deposited mercury has a local component (emitted HgII, lifetime of 3.7 days against deposition) and a global component (emitted Hg0, lifetime of 6 months against deposition). Fast recycling of deposited mercury through photoreduction of HgII and re-emission of Hg0 from surface reservoirs (ice, land, surface ocean) increases the effective lifetime of anthropogenic mercury to 9 months against loss to legacy reservoirs (soil pools and the subsurface ocean). This lifetime is still sufficiently short that source-receptor relationships have a strong hemispheric signature. Asian emissions are the largest source of anthropogenic deposition to all ocean basins, though there is also regional source influence from upwind continents. Current anthropogenic emissions account for only about one-third of mercury deposition to the global ocean with the remainder from natural and legacy sources. However, controls on anthropogenic emissions would have the added benefit of reducing the legacy mercury re-emitted to the atmosphere. Better understanding is needed of the timescales for transfer of mercury from active pools to stable geochemical reservoirs. PMID:22050654

Two Model-Based Methods for Policy Analyses of Fine Particulate Matter Control in China: Source Apportionment and Source Sensitivity

NASA Astrophysics Data System (ADS)

Li, X.; Zhang, Y.; Zheng, B.; Zhang, Q.; He, K.

2013-12-01

Anthropogenic emissions have been controlled in recent years in China to mitigate fine particulate matter (PM2.5) pollution. Recent studies show that sulfate dioxide (SO2)-only control cannot reduce total PM2.5 levels efficiently. Other species such as nitrogen oxide, ammonia, black carbon, and organic carbon may be equally important during particular seasons. Furthermore, each species is emitted from several anthropogenic sectors (e.g., industry, power plant, transportation, residential and agriculture). On the other hand, contribution of one emission sector to PM2.5 represents contributions of all species in this sector. In this work, two model-based methods are used to identify the most influential emission sectors and areas to PM2.5. The first method is the source apportionment (SA) based on the Particulate Source Apportionment Technology (PSAT) available in the Comprehensive Air Quality Model with extensions (CAMx) driven by meteorological predictions of the Weather Research and Forecast (WRF) model. The second method is the source sensitivity (SS) based on an adjoint integration technique (AIT) available in the GEOS-Chem model. The SA method attributes simulated PM2.5 concentrations to each emission group, while the SS method calculates their sensitivity to each emission group, accounting for the non-linear relationship between PM2.5 and its precursors. Despite their differences, the complementary nature of the two methods enables a complete analysis of source-receptor relationships to support emission control policies. Our objectives are to quantify the contributions of each emission group/area to PM2.5 in the receptor areas and to intercompare results from the two methods to gain a comprehensive understanding of the role of emission sources in PM2.5 formation. The results will be compared in terms of the magnitudes and rankings of SS or SA of emitted species and emission groups/areas. GEOS-Chem with AIT is applied over East Asia at a horizontal grid resolution of 0.5° (Lat) × 0.67° (Lon). WRF/CAMx with PSAT is applied to nested grids: 36-km × 36-km over China and 12-km × 12-km over northern China. These simulations are performed for 2006 and 2011. Beijing and northern Hebei are selected as representative receptor areas. Simulated surface concentrations by both models are evaluated with available observations in China. Focusing on inorganic aerosols (sulfate, nitrate and ammonium), preliminary SS results from GEOS-Chem/AIT at Beijing identify the top three major emission sectors to be agriculture, residential, and transportation in winter and agriculture, industry and power plant in summer. The top four source areas are northern Hebei, local, Neimenggu, and Liaoning in winter and northern Hebei, local, Shandong, and southern Hebei in summer. The synthesis of SS and SA for influential emission groups or areas from this work will provide a quantitative basis for emission control strategy development and policy making for PM2.5 control in China.

RECEPTOR MODELING OF AMBIENT PARTICULATE MATTER DATA USING POSITIVE MATRIX FACTORIZATION REVIEW OF EXISTING METHODS

EPA Science Inventory

Methods for apportioning sources of ambient particulate matter (PM) using the positive matrix factorization (PMF) algorithm are reviewed. Numerous procedural decisions must be made and algorithmic parameters selected when analyzing PM data with PMF. However, few publications docu...

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

Identification of atmospheric mercury sources and transport pathways on local and regional sales

NASA Astrophysics Data System (ADS)

Gratz, Lynne E.

Mercury (Hg) is a hazardous air pollutant and bioaccumulative neurotoxin whose intricate atmospheric chemistry complicates our ability to define Hg source-receptor relationships on all scales. Our detailed measurements of Hg in its different forms together with atmospheric tracers have improved our understanding of Hg chemistry and transport. Daily-event precipitation samples collected from 1995 to 2006 in Underhill, VT were examined to identify Hg wet deposition trends and source influences. Analysis revealed that annual Hg deposition at this fairly remote location did not vary significantly over the 12-year period. While a decreasing trend in volume-weighted mean Hg concentration was observed, Hg wet deposition did not decline as transport of emissions from the Midwest and along the Atlantic Coast consistently contributed to the largest observed Hg wet deposition events. Receptor modeling of Hg and trace elements in precipitation indicated that ---60% of Hg wet deposition at Underhill could be attributed to emissions from coal-fired utility boilers (CFUBs), and their contribution to Hg wet deposition did not change significantly over time. Hybrid-receptor modeling further defined these CFUBs to be located predominantly in the Midwestern U.S. Atmospheric Hg chemistry and transport from the Chicago urban/industrial area was the focus of speciated Hg measurements performed in the southern Lake Michigan basin during summer 2007. Transport from Chicago, IL to Holland, MI occurred during 27% of the study period, resulting in a five-fold increase in divalent reactive gaseous Hg (RGM) at the downwind Holland site. Dispersion modeling of case study periods demonstrated that under southwesterly flow approximately half of the RGM in Holland could be attributed to primary RGM emissions from Chicago after transport and dispersion, with the remainder due to Hg0 oxidation in the atmosphere en route. Precipitation and ambient vapor phase samples were also collected in Chicago, Holland, and Dexter, MI and analyzed for Hg isotopes. The Hg isotopic fractionation observed in atmospheric samples was in contrast to a recently published report which predicted that aqueous photoreduction may be a dominant source of atmospheric Hg. Our results suggest that other redox reactions and source related processes likely contribute to isotopic fractionation of atmospheric Hg.

Source apportionment of airborne particulate matter using organic compounds as tracers

NASA Astrophysics Data System (ADS)

Schauer, James J.; Rogge, Wolfgang F.; Hildemann, Lynn M.; Mazurek, Monica A.; Cass, Glen R.; Simoneit, Bernd R. T.

A chemical mass balance receptor model based on organic compounds has been developed that relates source contributions to airborne fine particle mass concentrations. Source contributions to the concentrations of specific organic compounds are revealed as well. The model is applied to four air quality monitoring sites in southern California using atmospheric organic compound concentration data and source test data collected specifically for the purpose of testing this model. The contributions of up to nine primary particle source types can be separately identified in ambient samples based on this method, and approximately 85% of the organic fine aerosol is assigned to primary sources on an annual average basis. The model provides information on source contributions to fine mass concentrations, fine organic aerosol concentrations and individual organic compound concentrations. The largest primary source contributors to fine particle mass concentrations in Los Angeles are found to include diesel engine exhaust, paved road dust, gasoline-powered vehicle exhaust, plus emissions from food cooking and wood smoke, with smaller contribution from tire dust, plant fragments, natural gas combustion aerosol, and cigarette smoke. Once these primary aerosol source contributions are added to the secondary sulfates, nitrates and organics present, virtually all of the annual average fine particle mass at Los Angeles area monitoring sites can be assigned to its source.

Size-segregated aerosol in a hot-spot pollution urban area: Chemical composition and three-way source apportionment.

PubMed

Bernardoni, V; Elser, M; Valli, G; Valentini, S; Bigi, A; Fermo, P; Piazzalunga, A; Vecchi, R

2017-12-01

In this work, a comprehensive characterisation and source apportionment of size-segregated aerosol collected using a multistage cascade impactor was performed. The samples were collected during wintertime in Milan (Italy), which is located in the Po Valley, one of the main pollution hot-spot areas in Europe. For every sampling, size-segregated mass concentration, elemental and ionic composition, and levoglucosan concentration were determined. Size-segregated data were inverted using the program MICRON to identify and quantify modal contributions of all the measured components. The detailed chemical characterisation allowed the application of a three-way (3-D) receptor model (implemented using Multilinear Engine) for size-segregated source apportionment and chemical profiles identification. It is noteworthy that - as far as we know - this is the first time that three-way source apportionment is attempted using data of aerosol collected by traditional cascade impactors. Seven factors were identified: wood burning, industry, resuspended dust, regional aerosol, construction works, traffic 1, and traffic 2. Further insights into size-segregated factor profiles suggested that the traffic 1 factor can be associated to diesel vehicles and traffic 2 to gasoline vehicles. The regional aerosol factor resulted to be the main contributor (nearly 50%) to the droplet mode (accumulation sub-mode with modal diameter in the range 0.5-1 μm), whereas the overall contribution from the two factors related to traffic was the most important one in the other size modes (34-41%). The results showed that applying a 3-D receptor model to size-segregated samples allows identifying factors of local and regional origin while receptor modelling on integrated PM fractions usually singles out factors characterised by primary (e.g. industry, traffic, soil dust) and secondary (e.g. ammonium sulphate and nitrate) origin. Furthermore, the results suggested that the information on size-segregated chemical composition in different size classes was exploited by the model to relate primary emissions to rapidly-formed secondary compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sources of hydrocarbons in urban road dust: Identification, quantification and prediction.

PubMed

Mummullage, Sandya; Egodawatta, Prasanna; Ayoko, Godwin A; Goonetilleke, Ashantha

2016-09-01

Among urban stormwater pollutants, hydrocarbons are a significant environmental concern due to their toxicity and relatively stable chemical structure. This study focused on the identification of hydrocarbon contributing sources to urban road dust and approaches for the quantification of pollutant loads to enhance the design of source control measures. The study confirmed the validity of the use of mathematical techniques of principal component analysis (PCA) and hierarchical cluster analysis (HCA) for source identification and principal component analysis/absolute principal component scores (PCA/APCS) receptor model for pollutant load quantification. Study outcomes identified non-combusted lubrication oils, non-combusted diesel fuels and tyre and asphalt wear as the three most critical urban hydrocarbon sources. The site specific variabilities of contributions from sources were replicated using three mathematical models. The models employed predictor variables of daily traffic volume (DTV), road surface texture depth (TD), slope of the road section (SLP), effective population (EPOP) and effective impervious fraction (EIF), which can be considered as the five governing parameters of pollutant generation, deposition and redistribution. Models were developed such that they can be applicable in determining hydrocarbon contributions from urban sites enabling effective design of source control measures. Copyright © 2016 Elsevier Ltd. All rights reserved.

A nontoxic pain killer designed by modeling of pathological receptor conformations.

PubMed

Spahn, V; Del Vecchio, G; Labuz, D; Rodriguez-Gaztelumendi, A; Massaly, N; Temp, J; Durmaz, V; Sabri, P; Reidelbach, M; Machelska, H; Weber, M; Stein, C

2017-03-03

Indiscriminate activation of opioid receptors provides pain relief but also severe central and intestinal side effects. We hypothesized that exploiting pathological (rather than physiological) conformation dynamics of opioid receptor-ligand interactions might yield ligands without adverse actions. By computer simulations at low pH, a hallmark of injured tissue, we designed an agonist that, because of its low acid dissociation constant, selectively activates peripheral μ-opioid receptors at the source of pain generation. Unlike the conventional opioid fentanyl, this agonist showed pH-sensitive binding, heterotrimeric guanine nucleotide-binding protein (G protein) subunit dissociation by fluorescence resonance energy transfer, and adenosine 3',5'-monophosphate inhibition in vitro . It produced injury-restricted analgesia in rats with different types of inflammatory pain without exhibiting respiratory depression, sedation, constipation, or addiction potential. Copyright © 2017, American Association for the Advancement of Science.

REVIEW OF VOLATILE ORGANIC COMPOUND SOURCE APPORTIONMENT BY CHEMICAL MASS BALANCE. (R826237)

EPA Science Inventory

The chemical mass balance (CMB) receptor model has apportioned volatile organic compounds (VOCs) in more than 20 urban areas, mostly in the United States. These applications differ in terms of the total fraction apportioned, the calculation method, the chemical compounds used ...

The simulated effects of wastewater-management actions on the hydrologic system and nitrogen-loading rates to wells and ecological receptors, Popponesset Bay Watershed, Cape Cod, Massachusetts

USGS Publications Warehouse

Walter, Donald A.

2013-01-01

The discharge of excess nitrogen into Popponesset Bay, an estuarine system on western Cape Cod, has resulted in eutrophication and the loss of eel grass habitat within the estuaries. Septic-system return flow in residential areas within the watershed is the primary source of nitrogen. Total Maximum Daily Loads (TMDLs) for nitrogen have been assigned to the six estuaries that compose the system, and local communities are in the process of implementing the TMDLs by the partial sewering, treatment, and disposal of treated wastewater at wastewater-treatment facilities (WTFs). Loads of waste-derived nitrogen from both current (1997–2001) and future sources can be estimated implicitly from parcel-scale water-use data and recharge areas delineated by a groundwater-flow model. These loads are referred to as “instantaneous” loads because it is assumed that the nitrogen from surface sources is delivered to receptors instantaneously and that there is no traveltime through the aquifer. The use of a solute-transport model to explicitly simulate the transport of mass through the aquifer from sources to receptors can improve implementation of TMDLs by (1) accounting for traveltime through the aquifer, (2) avoiding limitations associated with the estimation of loads from static recharge areas, (3) accounting more accurately for the effect of surface waters on nitrogen loads, and (4) determining the response of waste-derived nitrogen loads to potential wastewater-management actions. The load of nitrogen to Popponesset Bay on western Cape Cod, which was estimated by using current sources as input to a solute-transport model based on a steady-state flow model, is about 50 percent of the instantaneous load after about 7 years of transport (loads to estuary are equal to loads discharged from sources); this estimate is consistent with simulated advective traveltimes in the aquifer, which have a median of 5 years. Model-calculated loads originating from recharge areas reach 80 percent of the instantaneous load within 30 years; this result indicates that loads estimated from recharge areas likely are reasonable for estimating current instantaneous loads. However, recharge areas are assumed to remain static as stresses and hydrologic conditions change in response to wastewater-management actions. Sewering of the Popponesset Bay watershed would not change hydraulic gradients and recharge areas to receptors substantially; however, disposal of wastewater from treatment facilities can change hydraulic gradients and recharge areas to nearby receptors, particularly if the facilities are near the boundary of the recharge area. In these cases, nitrogen loads implicitly estimated by using current recharge areas that do not accurately represent future hydraulic stresses can differ significantly from loads estimated with recharge areas that do represent those stresses. Nitrogen loads to two estuaries in the Popponesset Bay system estimated by using recharge areas delineated for future hydrologic conditions and nitrogen sources were about 3 and 9 times higher than loads estimated by using current recharge areas; for this reason, reliance on static recharge areas can present limitations for effective TMDL implementation by means of a hypothetical, but realistic, wastewater-management action. A solute-transport model explicitly represents nitrogen transport from surface sources and does not rely on the use of recharge areas; because changes in gradients resulting from wastewater-management actions are accounted for in transport simulations, they provide more reliable predictions of future nitrogen loads. Explicitly representing the mass transport of nitrogen can better account for the mechanisms by which nitrogen enters the estuary and improve estimates of the attenuation of nitrogen concentrations in fresh surface waters. Water and associated nitrogen can enter an estuary as either direct groundwater discharge or as surface-water inflow. Two estuaries in the Popponesset Bay watershed receive surface-water inflows: Shoestring Bay receives water from the Santuit River, and the tidal reach of the Mashpee River receives water (and associated nitrogen) from the nontidal reach of the Mashpee River. Much of the water discharging into these streams passes through ponds prior to discharge. The additional attenuation of nitrogen in groundwater that has passed through a pond and discharged into a stream prior to entering an estuary is about 3 kilograms per day. Advective-transport times in the aquifer generally are small—median traveltimes are about 4.5 years—and nitrogen loads at receptors respond quickly to wastewater-management actions. The simulated decreases in nitrogen loads were 50 and 80 percent of the total decreases within 5 and 15 years, respectively, after full sewering of the watershed and within 3 and 10 years, for sequential phases of partial sewering and disposal at WTFs. The results show that solute-transport models can be used to assess the responses of nitrogen loads to wastewater-management actions, and that loads at ecological receptors (receiving waters—ponds, streams or coastal waters—that support ecosystems) will respond within a few years to those actions. The responses vary for individual receptors as functions of hydrologic setting, traveltimes in the aquifer, and the unique set of nitrogen sources representing current and future wastewater-disposal actions within recharge areas. Changes in nitrogen loads from groundwater discharge to individual estuaries range from a decrease of 90 percent to an increase of 80 percent following sequential phases of hypothetical but realistic wastewater-management actions. The ability to explicitly represent the transport of mass through the aquifer allows for the evaluation of complex responses that include the effects of surface waters, traveltimes, and complex changes in sources. Most of the simulated decreases in nitrogen loads to Shoestring Bay and the tidal portion of the Mashpee River, 79 and 69 percent, respectively, were caused by decreases in the nitrogen loads from surface-water inflow.

Source apportionment of airborne particulate matter using organic compounds as tracers

NASA Astrophysics Data System (ADS)

Schauer, James J.; Rogge, Wolfgang F.; Hildemann, Lynn M.; Mazurek, Monica A.; Cass, Glen R.; Simoneit, Bernd R. T.

A chemical mass balance receptor model based on organic compounds has been developed that relates sours; contributions to airborne fine particle mass concentrations. Source contributions to the concentrations of specific organic compounds are revealed as well. The model is applied to four air quality monitoring sites in southern California using atmospheric organic compound concentration data and source test data collected specifically for the purpose of testing this model. The contributions of up to nine primary particle source types can be separately identified in ambient samples based on this method, and approximately 85% of the organic fine aerosol is assigned to primary sources on an annual average basis. The model provides information on source contributions to fine mass concentrations, fine organic aerosol concentrations and individual organic compound concentrations. The largest primary source contributors to fine particle mass concentrations in Los Angeles are found to include diesel engine exhaust, paved road dust, gasoline-powered vehicle exhaust, plus emissions from food cooking and wood smoke, with smaller contribution:; from tire dust, plant fragments, natural gas combustion aerosol, and cigarette smoke. Once these primary aerosol source contributions are added to the secondary sulfates, nitrates and organics present, virtually all of the annual average fine particle mass at Los Angeles area monitoring sites can be assigned to its source.

A Workflow to Model Microbial Loadings in Watersheds ...

EPA Pesticide Factsheets

Many watershed models simulate overland and instream microbial fate and transport, but few actually provide loading rates on land surfaces and point sources to the water body network. This paper describes the underlying general equations for microbial loading rates associated with 1) land-applied manure on undeveloped areas from domestic animals; 2) direct shedding on undeveloped lands by domestic animals and wildlife; 3) urban or engineered areas; and 4) point sources that directly discharge to streams from septic systems and shedding by domestic animals. A microbial source module, which houses these formulations, is linked within a workflow containing eight models and a set of databases that form a loosely configured modeling infrastructure which supports watershed-scale microbial source-to-receptor modeling by focusing on animal-impacted catchments. A hypothetical example application – accessing, retrieving, and using real-world data – demonstrates the ability of the infrastructure to automate many of the manual steps associated with a standard watershed assessment, culminating with calibrated flow and microbial densities at the pour point of a watershed. Presented at 2016 Biennial Conference, International Environmental Modelling & Software Society.

Interannual Variability in Intercontinental Transport

NASA Technical Reports Server (NTRS)

Gupta, Mohan; Douglass, Anne; Kawa, S. Randy; Pawson, Steven

2003-01-01

We have investigated the importance of intercontinental transport using source-receptor relationship. A global radon-like and seven regional tracers were used in three-dimensional model simulations to quantify their contributions to column burdens and vertical profiles at world-wide receptors. Sensitivity of these contributions to meteorological input was examined using different years of meteorology in two atmospheric simulations. Results show that Asian emission influences tracer distributions in its eastern downwind regions extending as far as Europe with major contributions in mid- and upper troposphere. On the western and eastern sides of the US, Asian contribution to annual average column burdens are 37% and 5% respectively with strong monthly variations. At an altitude of 10 km, these contributions are 75% and 25% respectively. North American emissions contribute more than 15% to annual average column burden and about 50% at 8 km altitude over the European region. Contributions from tropical African emissions are wide-spread in both the hemispheres. Differences in meteorological input cause non-uniform redistribution of tracer mass throughout the troposphere at all receptors. We also show that in model-model and model-data comparison, correlation analysis of tracer's spatial gradients provides an added measure of model's performance.

Expression profiling of G-protein-coupled receptors in human urothelium and related cell lines.

PubMed

Ochodnický, Peter; Humphreys, Sian; Eccles, Rachel; Poljakovic, Mirjana; Wiklund, Peter; Michel, Martin C

2012-09-01

What's known on the subject? and What does the study add? Urothelium emerged as a crucial integrator of sensory inputs and outputs in the bladder wall, and urothelial G-protein-coupled receptors (GPCRs) may represent plausible targets for treatment of various bladder pathologies. Urothelial cell lines provide a useful tool to study urothelial receptor function, but their validity as models for native human urothelium remains unclear. We characterize the mRNA expression of genes coding for GPCRs in human freshly isolated urothelium and compare the expression pattern with those in human urothelial cell lines. To characterize the mRNA expression pattern of genes coding for G-protein-coupled receptors (GPCRs) in human freshly isolated urothelium. To compare GPCR expression in human urothelium-derived cell lines to explore the suitability of these cell lines as model systems to study urothelial function. Native human urothelium (commercially sourced) and human urothelium-derived non-cancer (UROtsa and TERT-NHUC) and cancer (J82) cell lines were used. For mRNA expression profiling we used custom-designed real-time polymerase chain reaction array for 40 receptors and several related genes. Native urothelium expressed a wide variety of GPCRs, including α(1A), α(1D) and all subtypes of α(2) and β adrenoceptors. In addition, M(2) and M(3) cholinergic muscarinic receptors, angiotensin II AT(1) receptor, serotonin 5-HT(2A) receptor and all subtypes of bradykinin, endothelin, cannabinoid, tachykinin and sphingosine-1-phosphate receptors were detected. Nerve growth factor and both its low- and high-affinity receptors were also expressed in urothelium. In all cell lines expression of most GPCRs was markedly downregulated, with few exceptions. In UROtsa cells, but much less in other cell lines, the expression of β(2) adrenoceptors, M(3) muscarinic receptors, B(1) and B(2) bradykinin receptors, ET(B) endothelin receptors and several subtypes of sphingosine-1-phosphate receptors was largely retained. Human urothelium expresses a wide range of receptors which enables sensing and integration of various extracellular signals. Human urothelium-derived cell lines, especially UROtsa cells, show comparable mRNA expression to native tissue for several physiologically relevant GPCRs, but lose expression of many other receptors. The use of cell lines as model systems of human urothelium requires careful validation of suitability for the genes of interest. © 2012 BJU INTERNATIONAL.

Chemical mass balance source apportionment of TSP in a lignite-burning area of Western Macedonia, Greece

NASA Astrophysics Data System (ADS)

Samara, Constantini

Total suspended particle mass concentrations (TSP) were determined in the Kozani-Ptolemais-Florina basin (western Macedonia, Greece), an area with intensive lignite burning for power generation. The study was conducted over a 1-year period (November 2000-November 2001) at 10 receptor sites located at variable distances from the power plants. Ambient TSP samples were analyzed for 27 major, minor and trace elements. Particulate emissions were also collected from a variety of sources including fly ash, lignite dust, automobile traffic, domestic heating, and open-air burning of agricultural biomass and refuse, and analyzed for the same chemical components. Ambient and source chemical profiles were used for source identification and apportionment of TSP by employing a chemical mass balance (CMB) receptor model. Diesel burning in vehicular traffic and in the power plants for generator start up was found to be the major contributor to ambient TSP levels at all 10 sites. Other sources with significant contributions were domestic coal burning, vegetative burning (wood combustion and agricultural burns) and refuse open-air burning. Fly ash escaping the electrostatic precipitators of the power plants was a minor contributor to ambient TSP.

A clustering algorithm for sample data based on environmental pollution characteristics

NASA Astrophysics Data System (ADS)

Chen, Mei; Wang, Pengfei; Chen, Qiang; Wu, Jiadong; Chen, Xiaoyun

2015-04-01

Environmental pollution has become an issue of serious international concern in recent years. Among the receptor-oriented pollution models, CMB, PMF, UNMIX, and PCA are widely used as source apportionment models. To improve the accuracy of source apportionment and classify the sample data for these models, this study proposes an easy-to-use, high-dimensional EPC algorithm that not only organizes all of the sample data into different groups according to the similarities in pollution characteristics such as pollution sources and concentrations but also simultaneously detects outliers. The main clustering process consists of selecting the first unlabelled point as the cluster centre, then assigning each data point in the sample dataset to its most similar cluster centre according to both the user-defined threshold and the value of similarity function in each iteration, and finally modifying the clusters using a method similar to k-Means. The validity and accuracy of the algorithm are tested using both real and synthetic datasets, which makes the EPC algorithm practical and effective for appropriately classifying sample data for source apportionment models and helpful for better understanding and interpreting the sources of pollution.

INTERACTION BETWEEN DELTA OPIOID RECEPTORS AND BENZODIAZEPINES IN CO2- INDUCED RESPIRATORY RESPONSES IN MICE

PubMed Central

Borkowski, Anne H.; Barnes, Dylan C.; Blanchette, Derek R.; Castellanos, F. Xavier; Klein, Donald F.; Wilson, Donald A.

2011-01-01

The false-suffocation hypothesis of panic disorder (Klein, 1993) suggested δ-opioid receptors as a possible source of the respiratory dysfunction manifested in panic attacks occurring in panic disorder (Preter and Klein, 2008). This study sought to determine if a lack of δ-opioid receptors in a mouse model affects respiratory response to elevated CO2, and whether the response is modulated by benzodiazepines, which are widely used to treat panic disorder. In a whole-body plethysmograph, respiratory responses to 5% CO2 were compared between δ-opioid receptor knockout mice and wild-type mice after saline, diazepam (1 mg/kg), and alprazolam (0.3 mg/kg) injection. The results show that lack of δ-opioid receptors does not affect normal response to elevated CO2, but does prevent benzodiazepines from modulating that response. Thus, in the presence of benzodiazepine agonists, respiratory responses to elevated CO2 were enhanced in δ-opioid receptor knockout mice compared to wild-type mice. This suggests an interplay between benzodiazepine receptors and δ-opioid receptors in regulating the respiratory effects of elevated CO2, which might be related to CO2 induced panic. PMID:21561601

ATMOSPHERIC AEROSOL SOURCE-RECEPTOR RELATIONSHIPS: THE ROLE OF COAL-FIRED POWER PLANTS

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

Allen L. Robinson; Spyros N. Pandis; Cliff I. Davidson

2004-12-01

This report describes the technical progress made on the Pittsburgh Air Quality Study (PAQS) during the period of March 2004 through August 2004. Significant progress was made this project period on the analysis of ambient data, source apportionment, and deterministic modeling activities. Results highlighted in this report include evaluation of the performance of PMCAMx+ for an air pollution episode in the Eastern US, an emission profile for a coke production facility, ultrafine particle composition during a nucleation event, and a new hybrid approach for source apportionment. An agreement was reached with a utility to characterize fine particle and mercury emissionsmore » from a commercial coal fired power. Research in the next project period will include source testing of a coal fired power plant, source apportionment analysis, emission scenario modeling with PMCAMx+, and writing up results for submission as journal articles.« less

[Study on atmospheric VOCs in Gongga Mountain base station].

PubMed

Zhang, Jun-Ke; Wang, Yue-Si; Wu, Fang-Kun; Sun, Jie

2012-12-01

Volatile organic compounds (VOCs) play important roles in the atmosphere as precursors of secondary air pollutants. The regional background concentrations and variation characteristics of VOCs in the atmosphere of southwestern China were studied. Meanwhile, a receptor model based on principal component analysis (PCA) was used to identify the major sources of VOCs. Weekly samples were collected in 2007 in the Gongga Mountain base station and analyzed with a three-stage preconcentration method coupled with GC-MS. The annual mean concentration of TVOCs and NMHCs were 9.40 x 10(-9) +/- 4.55 x 10(-9) and 7.73 x 10(-9) +/- 4.43 x 10(-9), respectively. Aromatic hydrocarbons provided the largest contribution to TVOCs (37.3%), follow by alkanes (30.0%) and halogenated hydrocarbons (19.8%), the smallest contribution was from alkenes (12.9%). Three major sources were resolved by the receptor model, traffic sources, biogenic sources and combustion sources. The seasonal variation of TVOCs in this area was obviously, and the order was autumn > winter > spring > summer. TVOCs concentration in autumn was very significantly higher than that in summer (P < 0.01). The seasonal variation of the four types of VOCs showed different characteristics due to the differences in photochemical properties. Isoprene emissions were from biogenic sources. Regression analysis revealed a good exponential relationship between the isoprene concentration and temperature. High temperatures increased the isoprene concentrations. However, the isoprene concentration remained constant when the ambient air temperature was below 20 degrees C. The TVOCs in Gongga Mountain were at a medium level comparing with the results of other regions, and there was a clear background station emission characteristic.

Origins of fine aerosol mass in the Baltimore-Washington corridor: implications from observation, factor analysis, and ensemble air parcel back trajectories

NASA Astrophysics Data System (ADS)

Antony Chen, L.-W.; Doddridge, Bruce G.; Dickerson, Russell R.; Chow, Judith C.; Henry, Ronald C.

Chemically speciated fine particulate matter (PM 2.5) and trace gases (including NH 3, HNO 3, CO, SO 2, NO y) have been sampled at Fort Meade (FME: 39.10°N, 76.74°W; elevation 46 m MSL), Maryland, since July 1999. FME is suburban, located in the middle of the Baltimore-Washington corridor, and generally downwind of the highly industrialized Midwest. The PM 2.5 at FME is expected to be of both local and regional sources. Measurements over a 2-year period include eight seasonally representative months. The PM 2.5 shows an annual mean of 13 μg m -3 and primarily consists of sulfate, nitrate, ammonium, and carbonaceous material. Day-to-day and seasonal variations in the PM 2.5 chemical composition reflect changes of contribution from various sources. UNMIX, an innovative receptor model, is used to retrieve potential sources of the PM 2.5. A six-factor model, including regional sulfate, local sulfate, wood smoke, copper/iron processing industry, mobile, and secondary nitrate, is constructed and compared with reported source emission profiles. The six factors are studied further using an ensemble back trajectory method to identify possible source locations. Sources of local sulfate, mobile, and secondary nitrate are more localized around the receptor than those of other factors. Regional sulfate and wood smoke are more regional and associated with westerly and southerly transport, respectively. This study suggests that the local contribution to PM 2.5 mass can vary from <30% in summer to >60% in winter.

Source-receptor reconciliation of fine-particulate emissions from residential wood combustion in the southeastern United States

EPA Science Inventory

An extensive collection of speciated PM2.5 measurements including organic tracers permitted a detailed examination of the emissions from residential wood combustion (RWC) in the southeastern United States over an entire year (2007). The Community Multiscale Air Quality model-base...

SOURCE APPORTIONMENT OF FINE PARTICULATE MATTER BY CLUSTERING SINGLE-PARTICLE DATA: TESTS OF RECEPTOR MODEL ACCURACY. (R826371C001)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Assessment of light extinction at a European polluted urban area during wintertime: Impact of PM1 composition and sources.

PubMed

Vecchi, R; Bernardoni, V; Valentini, S; Piazzalunga, A; Fermo, P; Valli, G

2018-02-01

In this paper, results from receptor modelling performed on a well-characterised PM 1 dataset were combined to chemical light extinction data (b ext ) with the aim of assessing the impact of different PM 1 components and sources on light extinction and visibility at a European polluted urban area. It is noteworthy that, at the state of the art, there are still very few papers estimating the impact of different emission sources on light extinction as we present here, although being among the major environmental challenges at many polluted areas. Following the concept of the well-known IMPROVE algorithm, here a tailored site-specific approach (recently developed by our group) was applied to assess chemical light extinction due to PM 1 components and major sources. PM 1 samples collected separately during daytime and nighttime at the urban area of Milan (Italy) were chemically characterised for elements, major ions, elemental and organic carbon, and levoglucosan. Chemical light extinction was estimated and results showed that at the investigated urban site it is heavily impacted by ammonium nitrate and organic matter. Receptor modelling (i.e. Positive Matrix Factorization, EPA-PMF 5.0) was effective to obtain source apportionment; the most reliable solution was found with 7 factors which were tentatively assigned to nitrates, sulphates, wood burning, traffic, industry, fine dust, and a Pb-rich source. The apportionment of aerosol light extinction (b ext,aer ) according to resolved sources showed that considering all samples together nitrate contributed at most (on average 41.6%), followed by sulphate, traffic, and wood burning accounting for 18.3%, 17.8% and 12.4%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

UNMIX Methods Applied to Characterize Sources of Volatile Organic Compounds in Toronto, Ontario

PubMed Central

Porada, Eugeniusz; Szyszkowicz, Mieczysław

2016-01-01

UNMIX, a sensor modeling routine from the U.S. Environmental Protection Agency (EPA), was used to model volatile organic compound (VOC) receptors in four urban sites in Toronto, Ontario. VOC ambient concentration data acquired in 2000–2009 for 175 VOC species in four air quality monitoring stations were analyzed. UNMIX, by performing multiple modeling attempts upon varying VOC menus—while rejecting the results that were not reliable—allowed for discriminating sources by their most consistent chemical characteristics. The method assessed occurrences of VOCs in sources typical of the urban environment (traffic, evaporative emissions of fuels, banks of fugitive inert gases), industrial point sources (plastic-, polymer-, and metalworking manufactures), and in secondary sources (releases from water, sediments, and contaminated urban soil). The remote sensing and robust modeling used here produces chemical profiles of putative VOC sources that, if combined with known environmental fates of VOCs, can be used to assign physical sources’ shares of VOCs emissions into the atmosphere. This in turn provides a means of assessing the impact of environmental policies on one hand, and industrial activities on the other hand, on VOC air pollution. PMID:29051416

Source Contributions of Urban PM2.5 in the Beijing-Tianjin-Hebei Region: Changes between 2006 and 2013 and Relative Impacts of Emissions and Meteorology

NASA Astrophysics Data System (ADS)

Li, X.; Zhang, Q.; Zhang, Y.; Zheng, B.; Li, M.; Wang, K.; Chen, Y.; Wallington, T. J.; Han, W.; Shen, W.; Zhang, X.; He, K.

2015-12-01

Anthropogenic emissions in China have been controlled for years to improve ambient air quality. However, severe haze events caused by atmospheric aerosols with aerodynamic diameter less than or equal to 2.5 μm (PM2.5) have continued to occur, especially in the Beijing-Tianjin-Hebei (BTH) region. The Chinese government has set an ambitious goal to reduce urban PM2.5 concentrations by 25% in BTH by 2017 relative to the 2012 levels. Source apportionment (SA) is necessary to the development of the effective emission control strategies. In this work, the Comprehensive Air Quality Model with extensions (CAMx) with the Particulate Source Apportionment Technology (PSAT) is applied to the China domain for the years 2006 and 2013. Ambient surface concentrations of PM2.5 and its components are generally well reproduced. To quantify the contributions of each emission category or region to PM2.5 in BTH, the total emissions are divided into 7 emission categories and 11 source regions. The source contributions determined in this work are generally consistent with results from previous work. In 2013, the industrial (44%) and residential (27%) sectors are the dominant contributors to urban PM2.5 in BTH. The residential sector is the largest contributor in winter; the industry sector dominates in other seasons. A slight increasing trend (+3% for industry and +6% for residential) is found in 2013 relative to 2006, necessitating more attention to these two sectors. Local emissions make the largest contribution (40%-60%) for all receptors. Change of source contribution of PM2.5 in Beijing and northern Hebei are dominate by change of local emission. However, for Tianjin, and central and southern Hebei, change of meteorology condition are as important as change of emission, because regional inflow in these areas is more important than in Beijing and northern Hebei and can increase under unfavorable weather conditions, indicating a strong need for regional joint emission control efforts. The results in this study enhance the quantitative understanding of the source-receptor relationships and provide an important basis for policymaking to advance the control of PM2.5 pollution in China. Both sector-based and fuel-based source apportionment will be available to further improve the comparability with receptor model results.

Source-Receptor Relationship Analysis of the Atmospheric Deposition of PAHs Subject to Long-Range Transport in Northeast Asia.

PubMed

Inomata, Yayoi; Kajino, Mizuo; Sato, Keiichi; Kurokawa, Junichi; Tang, Ning; Ohara, Toshimasa; Hayakawa, Kazuichi; Ueda, Hiromasa

2017-07-18

The source-receptor relationship analysis of PAH deposition in Northeast Asia was investigated using an Eulerian regional-scale aerosol chemical transport model. Dry deposition (DD) of PAH was controlled by wind flow patterns, whereas wet deposition (WD) depended on precipitation in addition to wind flow patterns. The contribution of WD was approximately 50-90% of the total deposition, except during winter in Northern China (NCHN) and Eastern Russia (ERUS) because of the low amount of precipitation. The amount of PAH deposition showed clear seasonal variation and was high in winter and low in summer in downwind (South Korea, Japan) and oceanic-receptor regions. In the downwind region, the contributions from NCHN (WD 28-52%; DD 54-55%) and Central China (CCHN) (WD 43-65%; DD 33-38%) were large in winter, whereas self-contributions (WD 20-51%; DD 79-81%) were relatively high in summer. In the oceanic-receptor region, the deposition amount decreased with distance from the Asian continent. The amount of DD was strongly influenced by emissions from neighboring domains. The contributions of WD from NCHN (16-20%) and CCHN (28-35%) were large. The large contributions from China in summer to the downwind region were linked to vertical transport of PAHs over the Asian continent associated with convection.

Glutamate-mediated excitotoxicity in neonatal hippocampal neurons is mediated by mGluR-induced release of Ca++ from intracellular stores and is prevented by estradiol

PubMed Central

Hilton, Genell D.; Nunez, Joseph L.; Bambrick, Linda; Thompson, Scott M.; McCarthy, Margaret M.

2008-01-01

Hypoxic/ischemic (HI) brain injury in newborn full-term and premature infants is a common and pervasive source of life time disabilities in cognitive and locomotor function. In the adult, HI induces glutamate release and excitotoxic cell death dependent on NMDA receptor activation. In animal models of the premature human infant, glutamate is also released following HI, but neurons are largely insensitive to NMDA or AMPA/kainic acid (KA) receptor-mediated damage. Using primary cultured hippocampal neurons we have determined that glutamate increases intracellular calcium much more than kainic acid. Moreover, glutamate induces cell death by activating Type I metabotropic glutamate receptors (mGluRs). Pretreatment of neurons with the gonadal steroid estradiol reduces the level of the Type I metabotropic glutamate receptors and completely prevents cell death, suggesting a novel therapeutic approach to excitotoxic brain damage in the neonate. PMID:17156362

Two Coincidence Detectors for Spike Timing-Dependent Plasticity in Somatosensory Cortex

PubMed Central

Bender, Vanessa A.; Bender, Kevin J.; Brasier, Daniel J.; Feldman, Daniel E.

2011-01-01

Many cortical synapses exhibit spike timing-dependent plasticity (STDP) in which the precise timing of presynaptic and postsynaptic spikes induces synaptic strengthening [long-term potentiation (LTP)] or weakening [long-term depression (LTD)]. Standard models posit a single, postsynaptic, NMDA receptor-based coincidence detector for LTP and LTD components of STDP. We show instead that STDP at layer 4 to layer 2/3 synapses in somatosensory (S1) cortex involves separate calcium sources and coincidence detection mechanisms for LTP and LTD. LTP showed classical NMDA receptor dependence. LTD was independent of postsynaptic NMDA receptors and instead required group I metabotropic glutamate receptors and calcium from voltage-sensitive channels and IP3 receptor-gated stores. Downstream of postsynaptic calcium, LTD required retrograde endocannabinoid signaling, leading to presynaptic LTD expression, and also required activation of apparently presynaptic NMDA receptors. These LTP and LTD mechanisms detected firing coincidence on ~25 and ~125 ms time scales, respectively, and combined to implement the overall STDP rule. These findings indicate that STDP is not a unitary process and suggest that endocannabinoid-dependent LTD may be relevant to cortical map plasticity. PMID:16624937

Towards Interpreting the Signal of CO2 Emissions from Megacities by Applying a Lagrangian Receptor-oriented Model to OCO-2 XCO2 data

NASA Astrophysics Data System (ADS)

Wu, D.; Lin, J. C.; Oda, T.; Ye, X.; Lauvaux, T.; Yang, E. G.; Kort, E. A.

2017-12-01

Urban regions are large emitters of CO2 whose emission inventories are still associated with large uncertainties. Therefore, a strong need exists to better quantify emissions from megacities using a top-down approach. Satellites — e.g., the Orbiting Carbon Observatory 2 (OCO-2), provide a platform for monitoring spatiotemporal column CO2 concentrations (XCO2). In this study, we present a Lagrangian receptor-oriented model framework and evaluate "model-retrieved" XCO2 by comparing against OCO-2-retrieved XCO2, for three megacities/regions (Riyadh, Cairo and Pearl River Delta). OCO-2 soundings indicate pronounced XCO2 enhancements (dXCO2) when crossing Riyadh, which are successfully captured by our model with a slight latitude shift. From this model framework, we can identify and compare the relative contributions of dXCO2 resulted from anthropogenic emission versus biospheric fluxes. In addition, to impose constraints on emissions for Riyadh through inversion methods, three uncertainties sources are addressed in this study, including 1) transport errors, 2) receptor and model setups in atmospheric models, and 3) urban emission uncertainties. For 1), we calculate transport errors by adding a wind error component to randomize particle distributions. For 2), a set of sensitivity tests using bootstrap method is performed to describe proper ways to setup receptors in Lagrangian models. For 3), both emission uncertainties from the Fossil Fuel Data Assimilation System (FFDAS) and the spread among three emission inventories are used to approximate an overall fractional uncertainty in modeled anthropogenic signal (dXCO2.anthro). Lastly, we investigate the definition of background (clean) XCO2 for megacities from retrieved XCO2 by means of statistical tools and our model framework.

Multi-criteria analysis for PM10 planning

NASA Astrophysics Data System (ADS)

Pisoni, Enrico; Carnevale, Claudio; Volta, Marialuisa

To implement sound air quality policies, Regulatory Agencies require tools to evaluate outcomes and costs associated to different emission reduction strategies. These tools are even more useful when considering atmospheric PM10 concentrations due to the complex nonlinear processes that affect production and accumulation of the secondary fraction of this pollutant. The approaches presented in the literature (Integrated Assessment Modeling) are mainly cost-benefit and cost-effective analysis. In this work, the formulation of a multi-objective problem to control particulate matter is proposed. The methodology defines: (a) the control objectives (the air quality indicator and the emission reduction cost functions); (b) the decision variables (precursor emission reductions); (c) the problem constraints (maximum feasible technology reductions). The cause-effect relations between air quality indicators and decision variables are identified tuning nonlinear source-receptor models. The multi-objective problem solution provides to the decision maker a set of not-dominated scenarios representing the efficient trade-off between the air quality benefit and the internal costs (emission reduction technology costs). The methodology has been implemented for Northern Italy, often affected by high long-term exposure to PM10. The source-receptor models used in the multi-objective analysis are identified processing long-term simulations of GAMES multiphase modeling system, performed in the framework of CAFE-Citydelta project.

A Workflow to Model Microbial Loadings in Watersheds ...

EPA Pesticide Factsheets

Many watershed models simulate overland and instream microbial fate and transport, but few actually provide loading rates on land surfaces and point sources to the water body network. This paper describes the underlying general equations for microbial loading rates associated with 1) land-applied manure on undeveloped areas from domestic animals; 2) direct shedding on undeveloped lands by domestic animals and wildlife; 3) urban or engineered areas; and 4) point sources that directly discharge to streams from septic systems and shedding by domestic animals. A microbial source module, which houses these formulations, is linked within a workflow containing eight models and a set of databases that form a loosely configured modeling infrastructure which supports watershed-scale microbial source-to-receptor modeling by focusing on animal-impacted catchments. A hypothetical example application – accessing, retrieving, and using real-world data – demonstrates the ability of the infrastructure to automate many of the manual steps associated with a standard watershed assessment, culminating with calibrated flow and microbial densities at the pour point of a watershed. In the Proceedings of the International Environmental Modelling and Software Society (iEMSs), 8th International Congress on Environmental Modelling and Software, Toulouse, France

Identification of source locations for atmospheric dry deposition of heavy metals during yellow-sand events in Seoul, Korea in 1998 using hybrid receptor models

NASA Astrophysics Data System (ADS)

Han, Young-Ji; Holsen, Thomas M.; Hopke, Philip K.; Cheong, Jang-Pyo; Kim, Ho; Yi, Seung-Muk

2004-10-01

Elemental dry deposition fluxes were measured using dry deposition plates from March to June 1998 in Seoul, Korea. During this spring sampling period several yellow-sand events characterized by long-range transport from China and Mongolia impacted the area. Understanding the impact of yellow-sand events on atmospheric dry deposition is critical to managing the heavy metal levels in the environment in Korea. In this study, the measured flux of a primarily crustal metal, Al and an anthropogenic metal, Pb was used with two hybrid receptor models, potential source contribution function (PSCF) and residence time weighted concentration (RTWC) for locating sources of heavy metals associated with atmospheric dry deposition fluxes during the yellow-sand events in Seoul, Korea. The PSCF using a criterion value of the 75th percentile of the measured dry deposition fluxes and RTWC results using the measured elemental dry deposition fluxes agreed well and consistently showed that there were large potential source areas in the Gobi Desert in China and Mongolia and industrial areas near Tianjin, Tangshan, and Shenyang in China. Major industrial areas of Shenyang, Fushun, and Anshan, the Central China loess plateau, the Gobi Desert, and the Alashan semi-desert in China were identified to be major source areas for the measured Pb flux in Seoul, Korea. For Al, the main industrial areas of Tangshan, Tianjin and Beijing, the Gobi Desert, the Alashan semi-desert, and the Central China loess plateau were found to be the major source areas. These results indicate that both anthropogenic sources such as industrial areas and natural sources such as deserts contribute to the high dry deposition fluxes of both Pb and Al in Seoul, Korea during yellow-sand events. RTWC resolved several high potential source areas. Modeling results indicated that the long-range transport of Al and Pb from China during yellow-sand events as well as non-yellow-sand spring daytimes increased atmospheric dry deposition of heavy metals in Korea.

Using a source-receptor approach to characterise VOC behaviour in a French urban area influenced by industrial emissions. Part II: source contribution assessment using the Chemical Mass Balance (CMB) model.

PubMed

Badol, Caroline; Locoge, Nadine; Galloo, Jean-Claude

2008-01-25

In Part I of this study (Badol C, Locoge N, Leonardis T, Gallo JC. Using a source-receptor approach to characterise VOC behaviour in a French urban area influenced by industrial emissions, Part I: Study area description, data set acquisition and qualitative data analysis of the data set. Sci Total Environ 2007; submitted as companion manuscript.) the study area, acquisition of the one-year data set and qualitative analysis of the data set have been described. In Part II a source profile has been established for each activity present in the study area: 6 profiles (urban heating, solvent use, natural gas leakage, biogenic emissions, gasoline evaporation and vehicle exhaust) have been extracted from literature to characterise urban sources, 7 industrial profiles have been established via canister sampling around industrial plants (hydrocarbon cracking, oil refinery, hydrocarbon storage, lubricant storage, lubricant refinery, surface treatment and metallurgy). The CMB model is briefly described and its implementation is discussed through the selection of source profiles and fitting species. Main results of CMB modellings for the Dunkerque area are presented. (1) The daily evolution of source contributions for the urban wind sector shows that the vehicle exhaust source contribution varies between 40 and 55% and its relative increase at traffic rush hours is hardly perceptible. (2) The relative contribution of vehicle exhaust varies from 55% in winter down to 30% in summer. This decrease is due to the increase of the relative contribution of hydrocarbon storage source reaching up to 20% in summer. (3) The evolution of source contributions with wind directions has confirmed that in urban wind sectors the contribution of vehicle exhaust dominate with around 45-55%. For the other wind sectors that include some industrial plants, the contribution of industrial sources is around 60% and could reach 80% for the sector 280-310 degrees , which corresponds to the most dense industrial area. (4) The pollution in Dunkerque has been globally characterised taking into account the frequency of wind directions and contributions of sources in each wind direction for the whole year. It has been concluded that contribution of industrial sources is below 20% whereas vehicle exhaust contribution is superior to 40%.

Fine particulates over South Asia: Review and meta-analysis of PM2.5 source apportionment through receptor model.

PubMed

Singh, Nandita; Murari, Vishnu; Kumar, Manish; Barman, S C; Banerjee, Tirthankar

2017-04-01

Fine particulates (PM 2.5 ) constitute dominant proportion of airborne particulates and have been often associated with human health disorders, changes in regional climate, hydrological cycle and more recently to food security. Intrinsic properties of particulates are direct function of sources. This initiates the necessity of conducting a comprehensive review on PM 2.5 sources over South Asia which in turn may be valuable to develop strategies for emission control. Particulate source apportionment (SA) through receptor models is one of the existing tool to quantify contribution of particulate sources. Review of 51 SA studies were performed of which 48 (94%) were appeared within a span of 2007-2016. Almost half of SA studies (55%) were found concentrated over few typical urban stations (Delhi, Dhaka, Mumbai, Agra and Lahore). Due to lack of local particulate source profile and emission inventory, positive matrix factorization and principal component analysis (62% of studies) were the primary choices, followed by chemical mass balance (CMB, 18%). Metallic species were most regularly used as source tracers while use of organic molecular markers and gas-to-particle conversion were minimum. Among all the SA sites, vehicular emissions (mean ± sd: 37 ± 20%) emerged as most dominating PM 2.5 source followed by industrial emissions (23 ± 16%), secondary aerosols (22 ± 12%) and natural sources (20 ± 15%). Vehicular emissions (39 ± 24%) also identified as dominating source for highly polluted sites (PM 2.5 >100 μgm -3 , n = 15) while site specific influence of either or in combination of industrial, secondary aerosols and natural sources were recognized. Source specific trends were considerably varied in terms of region and seasonality. Both natural and industrial sources were most influential over Pakistan and Afghanistan while over Indo-Gangetic plain, vehicular, natural and industrial emissions appeared dominant. Influence of vehicular emission was found single dominating source over southern part while over Bangladesh, both vehicular, biomass burning and industrial sources were significant. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Review of Advancements in Particulate Matter Sampling and Analysis and its Application to Identifying Source Impacts at Receptor Locations

EPA Science Inventory

Time-integrated (typically 24-hr) filter-based methods (historical methods) form the underpinning of our understanding of the fate, impact of source emissions at receptor locations (source impacts), and potential health and welfare effects of particulate matter (PM) in air. Over...

Source Apportionment of PM2.5 in Delhi, India Using PMF Model.

PubMed

Sharma, S K; Mandal, T K; Jain, Srishti; Saraswati; Sharma, A; Saxena, Mohit

2016-08-01

Chemical characterization of PM2.5 [organic carbon, elemental carbon, water soluble inorganic ionic components, and major and trace elements] was carried out for a source apportionment study of PM2.5 at an urban site of Delhi, India from January, 2013, to December, 2014. The annual average mass concentration of PM2.5 was 122 ± 94.1 µg m(-3). Strong seasonal variation was observed in PM2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon. A receptor model, positive matrix factorization (PMF) was applied for source apportionment of PM2.5 mass concentration. The PMF model resolved the major sources of PM2.5 as secondary aerosols (21.3 %), followed by soil dust (20.5 %), vehicle emissions (19.7 %), biomass burning (14.3 %), fossil fuel combustion (13.7 %), industrial emissions (6.2 %) and sea salt (4.3 %).

SOURCE APPORTIONMENT OF SEATTLE PM 2.5: A COMPARISON OF IMPROVE AND ENHANCED STN DATA SETS

EPA Science Inventory

Seattle, WA, STN and IMPROVE data sets with STN temperature resolved carbon peaks were analyzed with both the PMF and Unmix receptor models. In addition, the IMPROVE trace element data was combined with the major STN species to examine the role of IMPROVE metals. To compare the ...

Receptor Modeling of Epiphytic Lichens to Elucidate the Sources and SpatialDistribution of Inorganic Air Pollution in the Athabasca Oil Sands Region

EPA Science Inventory

The contribution of inorganic air pollutant emissions to atmospheric deposition in the Athabasca Oil Sands Region (AOSR) of Alberta, Canada was investigated in the surrounding boreal forests, using a common epiphytic lichen bio-indicator species (Hypogymnia physodes) and applyi...

Screening tool to evaluate the vulnerability of down-gradient receptors to groundwater contaminants from uncapped landfills

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

Baker, Ronald J.; Reilly, Timothy J.; Lopez, Anthony

2015-09-15

Highlights: • A spreadsheet-based risk screening tool for groundwater affected by landfills is presented. • Domenico solute transport equations are used to estimate downgradient contaminant concentrations. • Landfills are categorized as presenting high, moderate or low risks. • Analysis of parameter sensitivity and examples of the method’s application are given. • The method has value to regulators and those considering redeveloping closed landfills. - Abstract: A screening tool for quantifying levels of concern for contaminants detected in monitoring wells on or near landfills to down-gradient receptors (streams, wetlands and residential lots) was developed and evaluated. The tool uses Quick Domenicomore » Multi-scenario (QDM), a spreadsheet implementation of Domenico-based solute transport, to estimate concentrations of contaminants reaching receptors under steady-state conditions from a constant-strength source. Unlike most other available Domenico-based model applications, QDM calculates the time for down-gradient contaminant concentrations to approach steady state and appropriate dispersivity values, and allows for up to fifty simulations on a single spreadsheet. Sensitivity of QDM solutions to critical model parameters was quantified. The screening tool uses QDM results to categorize landfills as having high, moderate and low levels of concern, based on contaminant concentrations reaching receptors relative to regulatory concentrations. The application of this tool was demonstrated by assessing levels of concern (as defined by the New Jersey Pinelands Commission) for thirty closed, uncapped landfills in the New Jersey Pinelands National Reserve, using historic water-quality data from monitoring wells on and near landfills and hydraulic parameters from regional flow models. Twelve of these landfills are categorized as having high levels of concern, indicating a need for further assessment. This tool is not a replacement for conventional numerically-based transport model or other available Domenico-based applications, but is suitable for quickly assessing the level of concern posed by a landfill or other contaminant point source before expensive and lengthy monitoring or remediation measures are taken. In addition to quantifying the level of concern using historic groundwater-monitoring data, the tool allows for archiving model scenarios and adding refinements as new data become available.« less

Sources of ambient volatile organic compounds and their contributions to photochemical ozone formation at a site in the Pearl River Delta, southern China.

PubMed

Ling, Z H; Guo, H; Cheng, H R; Yu, Y F

2011-10-01

The Positive Matrix Factorization (PMF) receptor model and the Observation Based Model (OBM) were combined to analyze volatile organic compound (VOC) data collected at a suburban site (WQS) in the PRD region. The purposes are to estimate the VOC source apportionment and investigate the contributions of these sources and species of these sources to the O(3) formation in PRD. Ten VOC sources were identified. We further applied the PMF-extracted concentrations of these 10 sources into the OBM and found "solvent usage 1", "diesel vehicular emissions" and "biomass/biofuel burning" contributed most to the O(3) formation at WQS. Among these three sources, higher Relative Incremental Reactivity (RIR)-weighted values of ethene, toluene and m/p-xylene indicated that they were mainly responsible for local O(3) formation in the region. Sensitivity analysis revealed that the sources of "diesel vehicular emissions", "biomass/biofuel burning" and "solvent usage 1" had low uncertainties whereas "gasoline evaporation" showed the highest uncertainty. Copyright © 2011 Elsevier Ltd. All rights reserved.

Bayesian probabilistic approach for inverse source determination from limited and noisy chemical or biological sensor concentration measurements

NASA Astrophysics Data System (ADS)

Yee, Eugene

2007-04-01

Although a great deal of research effort has been focused on the forward prediction of the dispersion of contaminants (e.g., chemical and biological warfare agents) released into the turbulent atmosphere, much less work has been directed toward the inverse prediction of agent source location and strength from the measured concentration, even though the importance of this problem for a number of practical applications is obvious. In general, the inverse problem of source reconstruction is ill-posed and unsolvable without additional information. It is demonstrated that a Bayesian probabilistic inferential framework provides a natural and logically consistent method for source reconstruction from a limited number of noisy concentration data. In particular, the Bayesian approach permits one to incorporate prior knowledge about the source as well as additional information regarding both model and data errors. The latter enables a rigorous determination of the uncertainty in the inference of the source parameters (e.g., spatial location, emission rate, release time, etc.), hence extending the potential of the methodology as a tool for quantitative source reconstruction. A model (or, source-receptor relationship) that relates the source distribution to the concentration data measured by a number of sensors is formulated, and Bayesian probability theory is used to derive the posterior probability density function of the source parameters. A computationally efficient methodology for determination of the likelihood function for the problem, based on an adjoint representation of the source-receptor relationship, is described. Furthermore, we describe the application of efficient stochastic algorithms based on Markov chain Monte Carlo (MCMC) for sampling from the posterior distribution of the source parameters, the latter of which is required to undertake the Bayesian computation. The Bayesian inferential methodology for source reconstruction is validated against real dispersion data for two cases involving contaminant dispersion in highly disturbed flows over urban and complex environments where the idealizations of horizontal homogeneity and/or temporal stationarity in the flow cannot be applied to simplify the problem. Furthermore, the methodology is applied to the case of reconstruction of multiple sources.

Behavior of the main sources that contribute to ambient PM2.5 in Santiago since 1998

NASA Astrophysics Data System (ADS)

Barraza, F.; Lambert, F.; Jorquera, H.; Villalobos, A. M.; Gallardo, L.

2016-12-01

Santiago's inhabitants have been exposed to high concentrations of fine particle matter (PM2.5) for decades. To contribute to a solution for this long-standing problem it is necessary to clearly identify and quantify the agents that contribute to ambient levels of PM2.5. We present an analysis of a long historical elemental concentrations database measured in air filter particles taken in central Santiago from April 1998 to August 2012 (1243 daily samples). We identify and quantify the main sources that contribute to PM2.5 levels using the source-receptor models PMF 5.0 and UNMIX 6.0. . The 6 main sources that contribute to outdoor PM2.5 levels were: vehicles (13.26±0.42 µg/m3), industrial sulfates (6.60±0.0.47 µg/m3), copper smelters (5.12±0.29 µg/m3), residential wood burning (4.38±0.36 µg/m3), marine aerosols (3.39±0.24 µg/m3), and urban dust (1.07±0.42 µg/m3). The unexplained fraction amounts to 1.76±0.90 µg/m3). The similar results obtained with both receptor models suggest a robust estimation of the main Santiago PM2.5 source apportionment. The analysis of the time series of these sources shows that their absolute contribution to PM2.5 levels has been decreasing during the last decade (except for urban dust which is increasing), and shows the effectiveness of government emission reduction policies. However, these improvements have not been sufficient to reduce PM2.5 concentrations to daily levels below the Chilean standard of 50 µg/m3, let alone the WHO standard of 25 µg/m3.

Multi-Decadal Variation of Aerosols: Sources, Transport, and Climate Effects

NASA Technical Reports Server (NTRS)

Chin, Mian; Diehl, Thomas; Bian, Huisheng; Streets, David

2008-01-01

We present a global model study of multi-decadal changes of atmospheric aerosols and their climate effects using a global chemistry transport model along with the near-term to longterm data records. We focus on a 27-year time period of satellite era from 1980 to 2006, during which a suite of aerosol data from satellite observations, ground-based measurements, and intensive field experiments have become available. We will use the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which involves a time-varying, comprehensive global emission dataset that we put together in our previous investigations and will be improved/extended in this project. This global emission dataset includes emissions of aerosols and their precursors from fuel combustion, biomass burning, volcanic eruptions, and other sources from 1980 to the present. Using the model and satellite data, we will analyze (1) the long-term global and regional aerosol trends and their relationship to the changes of aerosol and precursor emissions from anthropogenic and natural sources, (2) the intercontinental source-receptor relationships controlled by emission, transport pathway, and climate variability.

Source apportionment of the carcinogenic potential of polycyclic aromatic hydrocarbons (PAH) associated to airborne PM10 by a PMF model.

PubMed

Callén, M S; Iturmendi, A; López, J M; Mastral, A M

2014-02-01

In order to perform a study of the carcinogenic potential of polycyclic aromatic hydrocarbons (PAH), benzo(a)pyrene equivalent (BaP-eq) concentration was calculated and modelled by a receptor model based on positive matrix factorization (PMF). Nineteen PAH associated to airborne PM10 of Zaragoza, Spain, were quantified during the sampling period 2001-2009 and used as potential variables by the PMF model. Afterwards, multiple linear regression analysis was used to quantify the potential sources of BaP-eq. Five sources were obtained as the optimal solution and vehicular emission was identified as the main carcinogenic source (35 %) followed by heavy-duty vehicles (28 %), light-oil combustion (18 %), natural gas (10 %) and coal combustion (9 %). Two of the most prevailing directions contributing to this carcinogenic character were the NE and N directions associated with a highway, industrial parks and a paper factory. The lifetime lung cancer risk exceeded the unit risk of 8.7 x 10(-5) per ng/m(3) BaP in both winter and autumn seasons and the most contributing source was the vehicular emission factor becoming an important issue in control strategies.

Sources of atmospheric aerosols in Ankara (Turkey) atmosphere

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

Tuncel, S.G.; Yatin, M.; Aras, N.K.

1996-12-31

Ankara was heavily polluted owing to combustion of coal and fuel oil for space heating. Air quality over the city improved after 1993 due to use of low sulfur coal and natural gas for residential heating. These regulatory actions resulted in a dramatic decrease in SO{sub 2} concentrations measured in the air quality network, after 1990. Although concentration of particulate matter also decreased in the same period, the decrease was not as dramatic as that observed in SO{sub 2} concentrations, suggesting that sources other than space heating also contribute on observed aerosol concentrations. Currently, the concentrations of suspended particles aremore » slightly below the air quality standards effective in Turkey. A better source receptor relation must be established to reduce atmospheric levels of particulate matter. In this study, sources contributing to the observed levels of particles was determined through a receptor modeling approach. Factors controlling the observed concentrations of elements and ions were determined by relating their concentrations, to source strengths and determined by relating their concentrations, to source strengths and meteorological parameters. Residential heating was found out to be the main source of anthropogenic elements in Ankara. In the second part of the study, sources contributing on observed concentrations of elements were determined by a principal component analysis and relative contribution of each source were determined by Chemical Mass Balance study. The results indicated that, the airborne soil is the most important source of aerosol in the Ankara atmosphere during summer season, but emissions from coal combustion dominates aerosol mass during winter months.« less

The source of high signal cooperativity in bacterial chemosensory arrays

PubMed Central

Piñas, Germán E.; Frank, Vered; Vaknin, Ady; Parkinson, John S.

2016-01-01

The Escherichia coli chemosensory system consists of large arrays of transmembrane chemoreceptors associated with a dedicated histidine kinase, CheA, and a linker protein, CheW, that couples CheA activity to receptor control. The kinase activity responses to receptor ligand occupancy changes can be highly cooperative, reflecting allosteric coupling of multiple CheA and receptor molecules. Recent structural and functional studies have led to a working model in which receptor core complexes, the minimal units of signaling, are linked into hexagonal arrays through a unique interface 2 interaction between CheW and the P5 domain of CheA. To test this array model, we constructed and characterized CheA and CheW mutants with amino acid replacements at key interface 2 residues. The mutant proteins proved defective in interface 2-specific in vivo cross-linking assays, and formed signaling complexes that were dispersed around the cell membrane rather than clustered at the cell poles as in wild type chemosensory arrays. Interface 2 mutants down-regulated CheA activity in response to attractant stimuli in vivo, but with much less cooperativity than the wild type. Moreover, mutant cells containing fluorophore-tagged receptors exhibited greater basal anisotropy that changed rapidly in response to attractant stimuli, consistent with facile changes in loosely packed receptors. We conclude that interface 2 lesions disrupt important network connections between core complexes, preventing receptors from operating in large, allosteric teams. This work confirms the critical role of interface 2 in organizing the chemosensory array, in directing the clustered array to the cell poles, and in producing its highly cooperative signaling properties. PMID:26951681

[Method of traditional Chinese medicine formula design based on 3D-database pharmacophore search and patent retrieval].

PubMed

He, Yu-su; Sun, Zhi-yi; Zhang, Yan-ling

2014-11-01

By using the pharmacophore model of mineralocorticoid receptor antagonists as a starting point, the experiment stud- ies the method of traditional Chinese medicine formula design for anti-hypertensive. Pharmacophore models were generated by 3D-QSAR pharmacophore (Hypogen) program of the DS3.5, based on the training set composed of 33 mineralocorticoid receptor antagonists. The best pharmacophore model consisted of two Hydrogen-bond acceptors, three Hydrophobic and four excluded volumes. Its correlation coefficient of training set and test set, N, and CAI value were 0.9534, 0.6748, 2.878, and 1.119. According to the database screening, 1700 active compounds from 86 source plant were obtained. Because of lacking of available anti-hypertensive medi cation strategy in traditional theory, this article takes advantage of patent retrieval in world traditional medicine patent database, in order to design drug formula. Finally, two formulae was obtained for antihypertensive.

Source identification and apportionment of heavy metals in urban soil profiles.

PubMed

Luo, Xiao-San; Xue, Yan; Wang, Yan-Ling; Cang, Long; Xu, Bo; Ding, Jing

2015-05-01

Because heavy metals (HMs) occurring naturally in soils accumulate continuously due to human activities, identifying and apportioning their sources becomes a challenging task for pollution prevention in urban environments. Besides the enrichment factors (EFs) and principal component analysis (PCA) for source classification, the receptor model (Absolute Principal Component Scores-Multiple Linear Regression, APCS-MLR) and Pb isotopic mixing model were also developed to quantify the source contribution for typical HMs (Cd, Co, Cr, Cu, Mn, Ni, Pb, Zn) in urban park soils of Xiamen, a representative megacity in southeast China. Furthermore, distribution patterns of their concentrations and sources in 13 soil profiles (top 20 cm) were investigated by different depths (0-5, 5-10, 10-20 cm). Currently the principal anthropogenic source for HMs in urban soil of China is atmospheric deposition from coal combustion rather than vehicle exhaust. Specifically for Pb source by isotopic model ((206)Pb/(207)Pb and (208)Pb/(207)Pb), the average contributions were natural (49%)>coal combustion (45%)≫traffic emissions (6%). Although the urban surface soils are usually more contaminated owing to recent and current human sources, leaching effects and historic vehicle emissions can also make deep soil layer contaminated by HMs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Source Apportionment of Atmospheric Particles by Electron Probe X-Ray Microanalysis and Receptor Models.

NASA Astrophysics Data System (ADS)

van Borm, Werner August

Electron probe X-ray microanalysis (EPXMA) in combination with an automation system and an energy-dispersive X-ray detection system was used to analyse thousands of microscopical particles, originating from the ambient atmosphere. The huge amount of data was processed by a newly developed X-ray correction method and a number of data reduction procedures. A standardless ZAF procedure for EPXMA was developed for quick semi-quantitative analysis of particles starting from simple corrections, valid for bulk samples and modified taking into account the particle finit diameter, assuming a spherical shape. Tested on a limited database of bulk and particulate samples, the compromise between calculation speed and accuracy yielded for elements with Z > 14 accuracies on concentrations less than 10% while absolute deviations remained below 4 weight%, thus being only important for low concentrations. Next, the possibilities for the use of supervised and unsupervised multivariate particle classification were investigated for source apportionment of individual particles. In a detailed study of the unsupervised cluster analysis technique several aspects were considered, that have a severe influence on the final cluster analysis results, i.e. data acquisition, X-ray peak identification, data normalization, scaling, variable selection, similarity measure, cluster strategy, cluster significance and error propagation. A supervised approach was developed using an expert system-like approach in which identification rules are builded to describe the particle classes in a unique manner. Applications are presented for particles sampled (1) near a zinc smelter (Vieille-Montagne, Balen, Belgium), analyzed for heavy metals, (2) in an urban aerosol (Antwerp, Belgium), analyzed for over 20 elements and (3) in a rural aerosol originating from a swiss mountain area (Bern). Thus is was possible to pinpoint a number of known and unknown sources and characterize their emissions in terms of particles abundance and particle composition. Alternatively, the bulk analysis of filters (total, fine and coarse mode) using Particle Induced X -Ray Emission (PIXE) and the application of a receptor modeling approach provided for complementary information on a macroscopical level. A computer program was developed incorporating an absolute factor analysis based receptor modeling procedure. Source profiles and contributions are described by elemental concentrations and an atmospheric mass balance is put forward. The latter method was applied in a two year study of the Antwerp urban aerosol and for the swiss aerosol, revealing a number of previously known and unknown sources. Both methods were successfully combined to increase the source resolution.

Using an Explicit Emission Tagging Method in Global Modeling of Source-Receptor Relationships for Black Carbon in the Arctic: Variations, Sources and Transport Pathways

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

Wang, Hailong; Rasch, Philip J.; Easter, Richard C.

2014-11-27

We introduce an explicit emission tagging technique in the Community Atmosphere Model to quantify source-region-resolved characteristics of black carbon (BC), focusing on the Arctic. Explicit tagging of BC source regions without perturbing the emissions makes it straightforward to establish source-receptor relationships and transport pathways, providing a physically consistent and computationally efficient approach to produce a detailed characterization of the destiny of regional BC emissions and the potential for mitigation actions. Our analysis shows that the contributions of major source regions to the global BC burden are not proportional to the respective emissions due to strong region-dependent removal rates and lifetimes,more » while the contributions to BC direct radiative forcing show a near-linear dependence on their respective contributions to the burden. Distant sources contribute to BC in remote regions mostly in the mid- and upper troposphere, having much less impact on lower-level concentrations (and deposition) than on burden. Arctic BC concentrations, deposition and source contributions all have strong seasonal variations. Eastern Asia contributes the most to the wintertime Arctic burden. Northern Europe emissions are more important to both surface concentration and deposition in winter than in summer. The largest contribution to Arctic BC in the summer is from Northern Asia. Although local emissions contribute less than 10% to the annual mean BC burden and deposition within the Arctic, the per-emission efficiency is much higher than for major non-Arctic sources. The interannual variability (1996-2005) due to meteorology is small in annual mean BC burden and radiative forcing but is significant in yearly seasonal means over the Arctic. When a slow aging treatment of BC is introduced, the increase of BC lifetime and burden is source-dependent. Global BC forcing-per-burden efficiency also increases primarily due to changes in BC vertical distributions. The relative contribution from major non-Arctic sources to the Arctic BC burden increases only slightly, although the contribution of Arctic local sources is reduced by a factor of 2 due to the slow aging treatment.« less

Receptor model source attributions for Utah’s Salt Lake City airshed and the impacts of wintertime secondary ammonium nitrate and ammonium chloride aerosol.

EPA Science Inventory

Communities along Utah’s Wasatch Front are currently developing strategies to reduce daily average PM2.5 levels to below National Ambient Air Quality Standards during wintertime, persistent, multi-day stable atmospheric conditions or cold-air pools. Speciated PM2.5 data from the ...

High-frequency gamma oscillations coexist with low-frequency gamma oscillations in the rat visual cortex in vitro.

PubMed

Oke, Olaleke O; Magony, Andor; Anver, Himashi; Ward, Peter D; Jiruska, Premysl; Jefferys, John G R; Vreugdenhil, Martin

2010-04-01

Synchronization of neuronal activity in the visual cortex at low (30-70 Hz) and high gamma band frequencies (> 70 Hz) has been associated with distinct visual processes, but mechanisms underlying high-frequency gamma oscillations remain unknown. In rat visual cortex slices, kainate and carbachol induce high-frequency gamma oscillations (fast-gamma; peak frequency approximately 80 Hz at 37 degrees C) that can coexist with low-frequency gamma oscillations (slow-gamma; peak frequency approximately 50 Hz at 37 degrees C) in the same column. Current-source density analysis showed that fast-gamma was associated with rhythmic current sink-source sequences in layer III and slow-gamma with rhythmic current sink-source sequences in layer V. Fast-gamma and slow-gamma were not phase-locked. Slow-gamma power fluctuations were unrelated to fast-gamma power fluctuations, but were modulated by the phase of theta (3-8 Hz) oscillations generated in the deep layers. Fast-gamma was spatially less coherent than slow-gamma. Fast-gamma and slow-gamma were dependent on gamma-aminobutyric acid (GABA)(A) receptors, alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors and gap-junctions, their frequencies were reduced by thiopental and were weakly dependent on cycle amplitude. Fast-gamma and slow-gamma power were differentially modulated by thiopental and adenosine A(1) receptor blockade, and their frequencies were differentially modulated by N-methyl-D-aspartate (NMDA) receptors, GluK1 subunit-containing receptors and persistent sodium currents. Our data indicate that fast-gamma and slow-gamma both depend on and are paced by recurrent inhibition, but have distinct pharmacological modulation profiles. The independent co-existence of fast-gamma and slow-gamma allows parallel processing of distinct aspects of vision and visual perception. The visual cortex slice provides a novel in vitro model to study cortical high-frequency gamma oscillations.

Estimating Air-Manganese Exposures in Two Ohio Towns ...

EPA Pesticide Factsheets

Manganese (Mn), a nutrient required for normal metabolic function, is also a persistent air pollutant and a known neurotoxin at high concentrations. Elevated exposures can result in a number of motor and cognitive deficits. Quantifying chronic personal exposures in residential populations studied by environmental epidemiologists can be time-consuming and expensive. We developed an approach for quantifying chronic exposures for two towns (Marietta and East Liverpool, Ohio) with elevated air Mn concentrations (air-Mn) related to ambient emissions from industrial processes. This was accomplished through the use of measured and modeled data in the communities studied. A novel approach was developed because one of the facilities lacked emissions data for the purposes of modeling. A unit emission rate was assumed over the surface area of both source facilities, and offsite concentrations at receptor residences and air monitoring sites were estimated with the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD). Ratios of all modeled receptor points were created, and a long-running air monitor was identified as a reference location. All ratios were normalized to the reference location. Long-term averages at all residential receptor points were calculated using modeled ratios and data from the reference monitoring location. Modeled five-year average air-Mn exposures ranged from 0.03-1.61 µg/m3 in Marietta and 0.01-6.32 µg/m3 in E

A Five- Year CMAQ Model Performance for Wildfires and ...

EPA Pesticide Factsheets

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. Two components of the biomass burning inventory, wildfires and prescribed fires are routinely estimated in the national emissions inventory. However, there is a large amount of uncertainty in the development of these emission inventory sectors. We have completed a 5 year set of CMAQ model simulations (2008-2012) in which we have simulated regional air quality with and without the wildfire and prescribed fire inventory. We will examine CMAQ model performance over regions with significant PM2.5 and Ozone contribution from prescribed fires and wildfires. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

An novel identification method of the environmental risk sources for surface water pollution accidents in chemical industrial parks.

PubMed

Peng, Jianfeng; Song, Yonghui; Yuan, Peng; Xiao, Shuhu; Han, Lu

2013-07-01

The chemical industry is a major source of various pollution accidents. Improving the management level of risk sources for pollution accidents has become an urgent demand for most industrialized countries. In pollution accidents, the released chemicals harm the receptors to some extent depending on their sensitivity or susceptibility. Therefore, identifying the potential risk sources from such a large number of chemical enterprises has become pressingly urgent. Based on the simulation of the whole accident process, a novel and expandable identification method for risk sources causing water pollution accidents is presented. The newly developed approach, by analyzing and stimulating the whole process of a pollution accident between sources and receptors, can be applied to identify risk sources, especially on the nationwide scale. Three major types of losses, such as social, economic and ecological losses, were normalized, analyzed and used for overall consequence modeling. A specific case study area, located in a chemical industry park (CIP) along the Yangtze River in Jiangsu Province, China, was selected to test the potential of the identification method. The results showed that there were four risk sources for pollution accidents in this CIP. Aniline leakage in the HS Chemical Plant would lead to the most serious impact on the surrounding water environment. This potential accident would severely damage the ecosystem up to 3.8 km downstream of Yangtze River, and lead to pollution over a distance stretching to 73.7 km downstream. The proposed method is easily extended to the nationwide identification of potential risk sources.

A study on the uncertainty based on Meteorological fields on Source-receptor Relationships for Total Nitrate in the Northeast Asia

NASA Astrophysics Data System (ADS)

Sunwoo, Y.; Park, J.; Kim, S.; Ma, Y.; Chang, I.

2010-12-01

Northeast Asia hosts more than one third of world population and the emission of pollutants trends to increase rapidly, because of economic growth and the increase of the consumption in high energy intensity. In case of air pollutants, especially, its characteristics of emissions and transportation become issued nationally, in terms of not only environmental aspects, but also long-range transboundary transportation. In meteorological characteristics, westerlies area means what air pollutants that emitted from China can be delivered to South Korea. Therefore, considering meteorological factors can be important to understand air pollution phenomena. In this study, we used MM5(Fifth-Generation Mesoscale Model) and WRF(Weather Research and Forecasting Model) to produce the meteorological fields. We analyzed the feature of physics option in each model and the difference due to characteristic of WRF and MM5. We are trying to analyze the uncertainty of source-receptor relationships for total nitrate according to meteorological fields in the Northeast Asia. We produced the each meteorological fields that apply the same domain, same initial and boundary conditions, the best similar physics option. S-R relationships in terms of amount and fractional number for total nitrate (sum of N from HNO3, nitrate and PAN) were calculated by EMEP method 3.

Estimating accidental pollutant releases in the built environment from turbulent concentration signals

NASA Astrophysics Data System (ADS)

Ben Salem, N.; Salizzoni, P.; Soulhac, L.

2017-01-01

We present an inverse atmospheric model to estimate the mass flow rate of an impulsive source of pollutant, whose position is known, from concentration signals registered at receptors placed downwind of the source. The originality of this study is twofold. Firstly, the inversion is performed using high-frequency fluctuating, i.e. turbulent, concentration signals. Secondly, the inverse algorithm is applied to a dispersion process within a dense urban canopy, at the district scale, and a street network model, SIRANERISK, is adopted. The model, which is tested against wind tunnel experiments, simulates the dispersion of short-duration releases of pollutant in different typologies of idealised urban geometries. Results allow us to discuss the reliability of the inverse model as an operational tool for crisis management and the risk assessments related to the accidental release of toxic and flammable substances.

Source-to-exposure assessment with the Pangea multi-scale framework - case study in Australia.

PubMed

Wannaz, Cedric; Fantke, Peter; Lane, Joe; Jolliet, Olivier

2018-01-24

Effective planning of airshed pollution mitigation is often constrained by a lack of integrative analysis able to relate the relevant emitters to the receptor populations at risk. Both emitter and receptor perspectives are therefore needed to consistently inform emission and exposure reduction measures. This paper aims to extend the Pangea spatial multi-scale multimedia framework to evaluate source-to-receptor relationships of industrial sources of organic pollutants in Australia. Pangea solves a large compartmental system in parallel by block to determine arrays of masses at steady-state for 100 000+ compartments and 4000+ emission scenarios, and further computes population exposure by inhalation and ingestion. From an emitter perspective, radial spatial distributions of population intakes show high spatial variation in intake fractions from 0.68 to 33 ppm for benzene, and from 0.006 to 9.5 ppm for formaldehyde, contrasting urban, rural, desert, and sea source locations. Extending analyses to the receptor perspective, population exposures from the combined emissions of 4101 Australian point sources are more extended for benzene that travels over longer distances, versus formaldehyde that has a more local impact. Decomposing exposure per industrial sector shows petroleum and steel industry as the highest contributing industrial sectors for benzene, whereas the electricity sector and petroleum refining contribute most to formaldehyde exposures. The source apportionment identifies the main sources contributing to exposure at five locations. Overall, this paper demonstrates high interest in addressing exposures from both an emitter perspective well-suited to inform product oriented approaches such as LCA, and from a receptor perspective for health risk mitigation.

Impact of Emissions and Long-Range Transport on Multi-Decadal Aerosol Trends: Implications for Air Quality and Climate

NASA Technical Reports Server (NTRS)

Chin, Mian

2012-01-01

We present a global model analysis of the impact of long-range transport and anthropogenic emissions on the aerosol trends in the major pollution regions in the northern hemisphere and in the Arctic in the past three decades. We will use the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model to analyze the multi-spatial and temporal scale data, including observations from Terra, Aqua, and CALIPSO satellites and from the long-term surface monitoring stations. We will analyze the source attribution (SA) and source-receptor (SR) relationships in North America, Europe, East Asia, South Asia, and the Arctic at the surface and free troposphere and establish the quantitative linkages between emissions from different source regions. We will discuss the implications for regional air quality and climate change.

Groundwater vulnerability and risk mapping using GIS, modeling and a fuzzy logic tool.

PubMed

Nobre, R C M; Rotunno Filho, O C; Mansur, W J; Nobre, M M M; Cosenza, C A N

2007-12-07

A groundwater vulnerability and risk mapping assessment, based on a source-pathway-receptor approach, is presented for an urban coastal aquifer in northeastern Brazil. A modified version of the DRASTIC methodology was used to map the intrinsic and specific groundwater vulnerability of a 292 km(2) study area. A fuzzy hierarchy methodology was adopted to evaluate the potential contaminant source index, including diffuse and point sources. Numerical modeling was performed for delineation of well capture zones, using MODFLOW and MODPATH. The integration of these elements provided the mechanism to assess groundwater pollution risks and identify areas that must be prioritized in terms of groundwater monitoring and restriction on use. A groundwater quality index based on nitrate and chloride concentrations was calculated, which had a positive correlation with the specific vulnerability index.

Source apportionment of fine particles and its chemical components over the Yangtze River Delta, China during a heavy haze pollution episode

NASA Astrophysics Data System (ADS)

Li, L.; An, J. Y.; Zhou, M.; Yan, R. S.; Huang, C.; Lu, Q.; Lin, L.; Wang, Y. J.; Tao, S. K.; Qiao, L. P.; Zhu, S. H.; Chen, C. H.

2015-12-01

An extremely high PM2.5 pollution episode occurred over the eastern China in January 2013. In this paper, the particulate matter source apportionment technology (PSAT) method coupled within the Comprehensive air quality model with extensions (CAMx) is applied to study the source contributions to PM2.5 and its major components at six receptors (Urban Shanghai, Chongming, Dianshan Lake, Urban Suzhou, Hangzhou and Zhoushan) in the Yangtze River Delta (YRD) region. Contributions from 4 source areas (including Shanghai, South Jiangsu, North Zhejiang and Super-region) and 9 emission sectors (including power plants, industrial boilers and kilns, industrial processing, mobile source, residential, volatile emissions, dust, agriculture and biogenic emissions) to PM2.5 and its major components (sulfate, nitrate, ammonia, organic carbon and elemental carbon) at the six receptors in the YRD region are quantified. Results show that accumulation of local pollution was the largest contributor during this air pollution episode in urban Shanghai (55%) and Suzhou (46%), followed by long-range transport (37% contribution to Shanghai and 44% to Suzhou). Super-regional emissions play an important role in PM2.5 formation at Hangzhou (48%) and Zhoushan site (68%). Among the emission sectors contributing to the high pollution episode, the major source categories include industrial processing (with contributions ranging between 12.7 and 38.7% at different receptors), combustion source (21.7-37.3%), mobile source (7.5-17.7%) and fugitive dust (8.4-27.3%). Agricultural contribution is also very significant at Zhoushan site (24.5%). In terms of the PM2.5 major components, it is found that industrial boilers and kilns are the major source contributor to sulfate and nitrate. Volatile emission source and agriculture are the major contributors to ammonia; transport is the largest contributor to elemental carbon. Industrial processing, volatile emissions and mobile source are the most significant contributors to organic carbon. Results show that the Yangtze River Delta region should focus on the joint pollution control of industrial processing, combustion emissions, mobile source emissions, and fugitive dust. Regional transport of air pollution among the cities are prominent, and the implementation of regional joint prevention and control of air pollution will help to alleviate fine particulate matter concentrations under heavy pollution case significantly.

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.

Identifying PM2.5 and PM0.1 sources for epidemiological studies in California.

PubMed

Hu, Jianlin; Zhang, Hongliang; Chen, Shuhua; Ying, Qi; Wiedinmyer, Christine; Vandenberghe, Francois; Kleeman, Michael J

2014-05-06

The University of California-Davis_Primary (UCD_P) model was applied to simultaneously track ∼ 900 source contributions to primary particulate matter (PM) in California for seven continuous years (January 1st, 2000 to December 31st, 2006). Predicted source contributions to primary PM2.5 mass, PM1.8 elemental carbon (EC), PM1.8 organic carbon (OC), PM0.1 EC, and PM0.1 OC were in general agreement with the results from previous source apportionment studies using receptor-based techniques. All sources were further subjected to a constraint check based on model performance for PM trace elemental composition. A total of 151 PM2.5 sources and 71 PM0.1 sources contained PM elements that were predicted at concentrations in general agreement with measured values at nearby monitoring sites. Significant spatial heterogeneity was predicted among the 151 PM2.5 and 71 PM0.1 source concentrations, and significantly different seasonal profiles were predicted for PM2.5 and PM0.1 in central California vs southern California. Population-weighted concentrations of PM emitted from various sources calculated using the UCD_P model spatial information differed from the central monitor estimates by up to 77% for primary PM2.5 mass and 148% for PM2.5 EC because the central monitor concentration is not representative of exposure for nearby population. The results from the UCD_P model provide enhanced source apportionment information for epidemiological studies to examine the relationship between health effects and concentrations of primary PM from individual sources.

Projected 2050 Model Simulations for the Chesapeake Bay ...

EPA Pesticide Factsheets

The Chesapeake Bay Program as has been tasked with assessing how changes in climate systems are expected to alter key variables and processes within the Watershed in concurrence with land use changes. EPA’s Office of Research and Development will be conducting historic and future, 2050, Weather Research and Forecast (WRF) metrological and Community Multiscale Air Quality (CMAQ) chemical transport model simulations to provide meteorological and nutrient deposition estimates for inclusion of the Chesapeake Bay Program’s assessment of how climate and land use change may impact water quality and ecosystem health. This presentation will present the timeline and research updates. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

PM2.5 source apportionment in a French urban coastal site under steelworks emission influences using constrained non-negative matrix factorization receptor model.

PubMed

Kfoury, Adib; Ledoux, Frédéric; Roche, Cloé; Delmaire, Gilles; Roussel, Gilles; Courcot, Dominique

2016-02-01

The constrained weighted-non-negative matrix factorization (CW-NMF) hybrid receptor model was applied to study the influence of steelmaking activities on PM2.5 (particulate matter with equivalent aerodynamic diameter less than 2.5 μm) composition in Dunkerque, Northern France. Semi-diurnal PM2.5 samples were collected using a high volume sampler in winter 2010 and spring 2011 and were analyzed for trace metals, water-soluble ions, and total carbon using inductively coupled plasma--atomic emission spectrometry (ICP-AES), ICP--mass spectrometry (ICP-MS), ionic chromatography and micro elemental carbon analyzer. The elemental composition shows that NO3(-), SO4(2-), NH4(+) and total carbon are the main PM2.5 constituents. Trace metals data were interpreted using concentration roses and both influences of integrated steelworks and electric steel plant were evidenced. The distinction between the two sources is made possible by the use Zn/Fe and Zn/Mn diagnostic ratios. Moreover Rb/Cr, Pb/Cr and Cu/Cd combination ratio are proposed to distinguish the ISW-sintering stack from the ISW-fugitive emissions. The a priori knowledge on the influencing source was introduced in the CW-NMF to guide the calculation. Eleven source profiles with various contributions were identified: 8 are characteristics of coastal urban background site profiles and 3 are related to the steelmaking activities. Between them, secondary nitrates, secondary sulfates and combustion profiles give the highest contributions and account for 93% of the PM2.5 concentration. The steelwork facilities contribute in about 2% of the total PM2.5 concentration and appear to be the main source of Cr, Cu, Fe, Mn, Zn. Copyright © 2015. Published by Elsevier B.V.

Contamination characteristics and source apportionment of trace metals in soils around Miyun Reservoir.

PubMed

Chen, Haiyang; Teng, Yanguo; Chen, Ruihui; Li, Jiao; Wang, Jinsheng

2016-08-01

Due to their toxicity and bioaccumulation, trace metals in soils can result in a wide range of toxic effects on animals, plants, microbes, and even humans. Recognizing the contamination characteristics of soil metals and especially apportioning their potential sources are the necessary preconditions for pollution prevention and control. Over the past decades, several receptor models have been developed for source apportionment. Among them, positive matrix factorization (PMF) has gained popularity and was recommended by the US Environmental Protection Agency as a general modeling tool. In this study, an extended chemometrics model, multivariate curve resolution-alternating least squares based on maximum likelihood principal component analysis (MCR-ALS/MLPCA), was proposed for source apportionment of soil metals and applied to identify the potential sources of trace metals in soils around Miyun Reservoir. Similar to PMF, the MCR-ALS/MLPCA model can incorporate measurement error information and non-negativity constraints in its calculation procedures. Model validation with synthetic dataset suggested that the MCR-ALS/MLPCA could extract acceptable recovered source profiles even considering relatively larger error levels. When applying to identify the sources of trace metals in soils around Miyun Reservoir, the MCR-ALS/MLPCA model obtained the highly similar profiles with PMF. On the other hand, the assessment results of contamination status showed that the soils around reservoir were polluted by trace metals in slightly moderate degree but potentially posed acceptable risks to the public. Mining activities, fertilizers and agrochemicals, and atmospheric deposition were identified as the potential anthropogenic sources with contributions of 24.8, 14.6, and 13.3 %, respectively. In order to protect the drinking water source of Beijing, special attention should be paid to the metal inputs to soils from mining and agricultural activities.

Dynamic Optical Filtration

NASA Technical Reports Server (NTRS)

Chretien, Jean-Loup (Inventor); Lu, Edward T. (Inventor)

2005-01-01

A dynamic optical filtration system and method effectively blocks bright light sources without impairing view of the remainder of the scene. A sensor measures light intensity and position so that selected cells of a shading matrix may interrupt the view of the bright light source by a receptor. A beamsplitter may be used so that the sensor may be located away from the receptor. The shading matrix may also be replaced by a digital micromirror device, which selectively sends image data to the receptor.

Dynamic optical filtration

NASA Technical Reports Server (NTRS)

Chretien, Jean-Loup (Inventor); Lu, Edward T. (Inventor)

2005-01-01

A dynamic optical filtration system and method effectively blocks bright light sources without impairing view of the remainder of the scene. A sensor measures light intensity and position so that selected cells of a shading matrix may interrupt the view of the bright light source by a receptor. A beamsplitter may be used so that the sensor may be located away from the receptor. The shading matrix may also be replaced by a digital micromirror device, which selectively sends image data to the receptor.

Source apportionment of PM₁₀ and PM₂.₅ in a desert region in northern Chile.

PubMed

Jorquera, Héctor; Barraza, Francisco

2013-02-01

Estimating contributions of anthropogenic sources to ambient particulate matter (PM) in desert regions is a challenging issue because wind erosion contributions are ubiquitous, significant and difficult to quantify by using source-oriented, dispersion models. A receptor modeling analysis has been applied to ambient PM(10) and PM(2.5) measured in an industrial zone ~20 km SE of Antofagasta (23.63°S, 70.39°W), a midsize coastal city in northern Chile; the monitoring site is within a desert region that extends from northern Chile to southern Perú. Integrated 24-hour ambient samples of PM(10) and PM(2.5) were taken with Harvard Impactors; samples were analyzed by X Ray Fluorescence, ionic chromatography (NO(3)(-) and SO(4)(=)), atomic absorption (Na(+), K(+)) and thermal optical transmission for elemental and organic carbon determination. Receptor modeling was carried out using Positive Matrix Factorization (US EPA Version 3.0); sources were identified by looking at specific tracers, tracer ratios, local winds and wind trajectories computed from NOAA's HYSPLIT model. For the PM(2.5) fraction, six contributions were found - cement plant, 33.7 ± 1.3%; soil dust, 22.4 ± 1.6%; sulfates, 17.8 ± 1.7%; mineral stockpiles and brine plant, 12.4 ± 1.2%; Antofagasta, 8.5 ± 1.3% and copper smelter, 5.3 ± 0.8%. For the PM(10) fraction five sources were identified - cement plant, 38.2 ± 1.5%; soil dust, 31.2 ± 2.3%; mineral stockpiles and brine plant, 12.7 ± 1.7%; copper smelter, 11.5 ± 1.6% and marine aerosol, 6.5 ± 2.4%. Therefore local sources contribute to ambient PM concentrations more than distant sources (Antofagasta, marine aerosol) do. Soil dust is enriched with deposition of marine aerosol and calcium, sulfates and heavy metals from surrounding industrial activities. The mean contribution of suspended soil dust to PM(10) is 50 μg/m(3) and the peak daily value is 104 μg/m(3). For the PM(2.5) fraction, suspended soil dust contributes with an average of 9.3 μg/m(3) and a peak daily value of 31.5 μg/m(3). Copyright © 2012 Elsevier B.V. All rights reserved.

Coarse and fine aerosol source apportionment in Rio de Janeiro, Brazil

NASA Astrophysics Data System (ADS)

Godoy, Maria Luiza D. P.; Godoy, José Marcus; Roldão, Luiz Alfredo; Soluri, Daniela S.; Donagemma, Raquel A.

The metropolitan area of Rio de Janeiro is one of the twenty biggest urban agglomerations in the world, with 11 million inhabitants in the metropolitan area, and has a high population density, with 1700 hab. km -2. For this aerosol source apportionment study, the atmospheric aerosol sampling was performed at ten sites distributed in different locations of the metropolitan area from September/2003 to December/2005, with sampling during 24 h on a weekly basis. Stacked filter units (SFU) were used to collect fine and coarse aerosol particles with a flow rate of 17 L min -1. In both size fractions trace elements were analyzed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) as well as water-soluble species by Ion-Chromatography (IC). Also gravimetric analysis and reflectance measurements provided aerosol mass and black carbon concentrations. Very good detection limits for up to 42 species were obtained. Mean annual PM 10 mass concentration ranged from 20 to 37 μg m -3, values that are within the Brazilian air quality standards. Receptor models such as principal factor analysis, cluster analysis and absolute principal factor analysis were applied in order to identify and quantify the aerosol sources. For fine and coarse modes, circa of 100% of the measured mass was quantitatively apportioned to relatively few identified aerosol sources. A very similar and consistent source apportionment was obtained for both fine and coarse modes for all 10 sampling sites. Soil dust is an important component, accounting for 22-72% and for 25-48% of the coarse and fine mass respectively. On the other hand, anthropogenic sources as vehicle traffic and oil combustion represent a relatively high contribution (52-75%) of the fine aerosol mass. The joint use of ICP-MS and IC analysis of species in aerosols has proven to be reliable and feasible for the analysis of large amount of samples, and the coupling with receptor models provided an excellent method for quantitative aerosol source apportionment in large urban areas.

Ergot alkaloids: From witchcraft till in silico analysis. Multi-receptor analysis of ergotamine metabolites.

PubMed

Dellafiora, Luca; Dall'Asta, Chiara; Cozzini, Pietro

2015-01-01

The term Ergot is referred to the sclerotium of ascomycetes - a protective kernel produced during resting stage of some fungi - which replaces seeds of susceptible cereals and plants intended for human and animal diet. It contains various composition of tryptophan-derived toxins defined ergot alkaloids. Since sclerotia can be harvested and milled together with cereals, they represent a source of food and feed contamination after breakage and spreading of mycotoxins into the various milling fractions. The effects of ergot alkaloids, including those adverse for human health, have been known since the Middle Ages. Nevertheless, as recently stated by the European Food Safety Authority, further information is needed on metabolism and target receptors-binding of common alkaloids in food. Unfortunately, the experimental investigation is challenging due to the high costs in terms of time and money. This study was thus aimed at assessing whether the in silico modeling can be an effective tool to investigate the interaction between multiple serotonin receptors and a wide set of ergotamine metabolites, including experimentally detected molecules and predicted derivatives. Validated models provided precious insights about the effects exerted by metabolic modifications on the receptor-ligand interaction. Such structural information may be useful to support the design of further experimental analysis.

Emission sources estimation of size-segregated suburban aerosols measured in continental part of Balkan region using PMF5.0 multivariate receptor model

NASA Astrophysics Data System (ADS)

Petrovic, Srdjan; Đuričić-Milanković, Jelena; Anđelković, Ivan; Pantelić, Ana; Gambaro, Andrea; Đorđević, Dragana

2017-04-01

Using Low-Pressure Cascade Impactors by Dr Berner size segregated particulate matter in the size ranges: 0.27 ≤ Dp ≤ 0.53 μm, 0.53 ≤ Dp ≤ 1.06 μm, 1.06 ≤ Dp ≤ 2.09 μm, 2.09 ≤ Dp ≤ 4.11 μm, 4.11 ≤ Dp ≤ 8.11 μm and 8.11 ≤ Dp ≤ 16 μm were collected. Forty-eight-hour size segregated particulate matter samples from atmospheric aerosols in the sub-urban site of Belgrade were measured during two years (in 2012th to 2013in). ICP-MS was used to quantify next elements: Ag, Al, As, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, K, Hg, Na, Ni, Mg, Mn, Mo, Pb, Se, Sb, Ti, Tl, V and Zn. In order to examine the number of sources and their fingerprints, EPA PMF 5.0 multivariate receptor tool was used. Error estimation methods (bootstrap, displacement, and bootstrap enhanced by displacement) in the analysis of the obtained solutions have enabled proper detection of the number and types of sources. This analysis of the results indicated the existence of four main sources that contribute to air pollution in the suburban area of Belgrade.

Assimilation of concentration measurements for retrieving multiple point releases in atmosphere: A least-squares approach to inverse modelling

NASA Astrophysics Data System (ADS)

Singh, Sarvesh Kumar; Rani, Raj

2015-10-01

The study addresses the identification of multiple point sources, emitting the same tracer, from their limited set of merged concentration measurements. The identification, here, refers to the estimation of locations and strengths of a known number of simultaneous point releases. The source-receptor relationship is described in the framework of adjoint modelling by using an analytical Gaussian dispersion model. A least-squares minimization framework, free from an initialization of the release parameters (locations and strengths), is presented to estimate the release parameters. This utilizes the distributed source information observable from the given monitoring design and number of measurements. The technique leads to an exact retrieval of the true release parameters when measurements are noise free and exactly described by the dispersion model. The inversion algorithm is evaluated using the real data from multiple (two, three and four) releases conducted during Fusion Field Trials in September 2007 at Dugway Proving Ground, Utah. The release locations are retrieved, on average, within 25-45 m of the true sources with the distance from retrieved to true source ranging from 0 to 130 m. The release strengths are also estimated within a factor of three to the true release rates. The average deviations in retrieval of source locations are observed relatively large in two release trials in comparison to three and four release trials.

Development of a methodology examining the behaviours of VOCs source apportionment with micro-meteorology analysis in an urban and industrial area.

PubMed

Xiang, Yang; Delbarre, Hervé; Sauvage, Stéphane; Léonardis, Thierry; Fourmentin, Marc; Augustin, Patrick; Locoge, Nadine

2012-03-01

During summer 2009, online measurements of 25 Volatile Organic Compounds (VOCs) from C6 to C10 as well as micro-meteorological parameters were simultaneously performed in the industrial city of Dunkerque. With the obtained data set, we developed a methodology to examine how the contributions of different source categories depend on atmospheric turbulences, and the results provided identification of emission modes. Eight factors were resolved by using Positive Matrix Factorization model and three of them were associated with mixed sources. The observed behaviours of contributions with turbulences lead to attribute some factors with sources at ground level, and some other factors with sources in the upper part of surface layer. The impact of vertical turbulence on the pollutant dispersion is also affected by the distance between sources and receptor site. Copyright © 2011 Elsevier Ltd. All rights reserved.

Characterization of the porcine neonatal Fc receptor—potential use for trans-epithelial protein delivery

PubMed Central

Stirling, Catrina M A; Charleston, Bryan; Takamatsu, Haru; Claypool, Steven; Lencer, Wayne; Blumberg, Richard S; Wileman, Thomas E

2005-01-01

The neonatal Fc receptor transports maternal immunoglobulin across the gut wall and has the potential to deliver genetically engineered proteins bearing immunoglobulin Fc domains across the gut to the mucosal immune system. Here we have characterized the porcine neonatal Fc receptor and tested its utility as a model system to study this kind of protein delivery. The complete DNA sequence obtained from an EST revealed 70–80% homology to mouse and human receptors, respectively, and tyrptophan and di-leucine endocytosis motifs were identified in the cytoplasmic tail. Reverse transcription–polymerase chain reaction analysis showed expression of the receptor mRNA in gut, liver, kidney and spleen tissue, aortic endothelial cells and monocytes. Pig kidney cell lines showed saturable pH-dependent binding and uptake of porcine immunoglobulin G (IgG) and also bovine, mouse and human IgG. Polyclonal antibodies raised against the receptor immunoprecipitated a protein of 40 000 MW when the cDNA was expressed in cells and the receptor required assembly with porcine β2-microglobulin for transport from the endoplasmic reticulum to recycling and early endosomes. Immunohistochemical analysis showed the receptor expressed in epithelial cells of the gut of young and adult animals. The ability of the receptor to deliver immunoglobulin across the gut was demonstrated by feeding piglets bovine colostrum as a source of bovine IgG. Bovine IgG was delivered into the pig circulation. Pigs express the neonatal Fc receptor and the receptor has the potential to deliver protein antigens to the pig immune system. PMID:15804291

The two-state dimer receptor model: a general model for receptor dimers.

PubMed

Franco, Rafael; Casadó, Vicent; Mallol, Josefa; Ferrada, Carla; Ferré, Sergi; Fuxe, Kjell; Cortés, Antoni; Ciruela, Francisco; Lluis, Carmen; Canela, Enric I

2006-06-01

Nonlinear Scatchard plots are often found for agonist binding to G-protein-coupled receptors. Because there is clear evidence of receptor dimerization, these nonlinear Scatchard plots can reflect cooperativity on agonist binding to the two binding sites in the dimer. According to this, the "two-state dimer receptor model" has been recently derived. In this article, the performance of the model has been analyzed in fitting data of agonist binding to A(1) adenosine receptors, which are an example of receptor displaying concave downward Scatchard plots. Analysis of agonist/antagonist competition data for dopamine D(1) receptors using the two-state dimer receptor model has also been performed. Although fitting to the two-state dimer receptor model was similar to the fitting to the "two-independent-site receptor model", the former is simpler, and a discrimination test selects the two-state dimer receptor model as the best. This model was also very robust in fitting data of estrogen binding to the estrogen receptor, for which Scatchard plots are concave upward. On the one hand, the model would predict the already demonstrated existence of estrogen receptor dimers. On the other hand, the model would predict that concave upward Scatchard plots reflect positive cooperativity, which can be neither predicted nor explained by assuming the existence of two different affinity states. In summary, the two-state dimer receptor model is good for fitting data of binding to dimeric receptors displaying either linear, concave upward, or concave downward Scatchard plots.

Human health risk assessment: models for predicting the effective exposure duration of on-site receptors exposed to contaminated groundwater.

PubMed

Baciocchi, Renato; Berardi, Simona; Verginelli, Iason

2010-09-15

Clean-up of contaminated sites is usually based on a risk-based approach for the definition of the remediation goals, which relies on the well known ASTM-RBCA standard procedure. In this procedure, migration of contaminants is described through simple analytical models and the source contaminants' concentration is supposed to be constant throughout the entire exposure period, i.e. 25-30 years. The latter assumption may often result over-protective of human health, leading to unrealistically low remediation goals. The aim of this work is to propose an alternative model taking in account the source depletion, while keeping the original simplicity and analytical form of the ASTM-RBCA approach. The results obtained by the application of this model are compared with those provided by the traditional ASTM-RBCA approach, by a model based on the source depletion algorithm of the RBCA ToolKit software and by a numerical model, allowing to assess its feasibility for inclusion in risk analysis procedures. The results discussed in this work are limited to on-site exposure to contaminated water by ingestion, but the approach proposed can be extended to other exposure pathways. Copyright 2010 Elsevier B.V. All rights reserved.

A comparison of PCA and PMF models for source identification of fugitive methane emissions

NASA Astrophysics Data System (ADS)

Assan, Sabina; Baudic, Alexia; Bsaibes, Sandy; Gros, Valerie; Ciais, Philippe; Staufer, Johannes; Robinson, Rod; Vogel, Felix

2017-04-01

Methane (CH_4) is a greenhouse gas with a global warming potential 28-32 times that of carbon dioxide (CO_2) on a 100 year period, and even greater on shorter timescales [Etminan, et al., 2016, Allen, 2014]. Thus, despite its relatively short life time and smaller emission quantities compared to CO_2, CH4 emissions contribute to approximately 20{%} of today's anthropogenic greenhouse gas warming [Kirschke et al., 2013]. Major anthropogenic sources include livestock (enteric fermentation), oil and gas production and distribution, landfills, and wastewater emissions [EPA, 2011]. Especially in densely populated areas multiple CH4 sources can be found in close vicinity. Thus, when measuring CH4 emissions at local scales it is necessary to distinguish between different CH4 source categories to effectively quantify the contribution of each sector and aid the implementation of greenhouse gas reduction strategies. To this end, source apportionment models can be used to aid the interpretation of spatial and temporal patterns in order to identify and characterise emission sources. The focus of this study is to evaluate two common linear receptor models, namely Principle Component Analysis (PCA) and Positive Matrix Factorisation (PMF) for CH4 source apportionment. The statistical models I will present combine continuous in-situ CH4 , C_2H_6, δ^1^3CH4 measured using a Cavity Ring Down Spectroscopy (CRDS) instrument [Assan et al. 2016] with volatile organic compound (VOC) observations performed using Gas Chromatography (GC) in order to explain the underlying variance of the data. The strengths and weaknesses of both models are identified for data collected in multi-source environments in the vicinity of four different types of sites; an agricultural farm with cattle, a natural gas compressor station, a wastewater treatment plant, and a pari-urban location in the Ile de France region impacted by various sources. To conclude, receptor model results to separate statistically the different sources from the variability of atmospheric observations are compared with an independent source identification method using stable methane isotopic analysis and simple CH_4/VOC ratios. Allen, D. T. (2014). Methane emissions from natural gas production and use: reconciling bottom-up and top-down measurements. Current Opinion in Chemical Engineering, 5, 78-83. Assan, S., Baudic, A., Guemri, A., Ciais, P., Gros, V., and Vogel, F. R.: Characterisation of interferences to in-situ observations of δ13CH4 and C2H6 when using a Cavity Ring Down Spectrometer at industrial sites, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2016-261, in review, 2016. Etminan, M., G. Myhre, E. J. Highwood and K. P. Shine (2016), Radiative forcing of carbon dioxide, methane, and nitrous oxide: A significant revision of the methane radiative forcing, Geophys. Res.Lett,43. Kirschke, S., Bousquet, P., Ciais, P., Saunois, M., Canadell, J. G., Dlugokencky, E. et al. (2013). Three decades of global methane sources and sinks. Nature Geoscience, 6(10), 813-823. U.S. Environmental Protection Agency's (U.S. EPA's). (2011) Global Anthropogenic Emissions of Non-CO2 Greenhouse Gases: 1990-2030. EPA 430-D-11-003

Elucidating determinants of aerosol composition through particle-type-based receptor modeling

NASA Astrophysics Data System (ADS)

McGuire, M. L.; Jeong, C.-H.; Slowik, J. G.; Chang, R. Y.-W.; Corbin, J. C.; Lu, G.; Mihele, C.; Rehbein, P. J. G.; Sills, D. M. L.; Abbatt, J. P. D.; Brook, J. R.; Evans, G. J.

2011-03-01

An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed at a semi-rural site in Southern Ontario to characterize the size and chemical composition of individual particles. Particle-type-based receptor modelling of these data was used to investigate the determinants of aerosol chemical composition in this region. Individual particles were classified into particle-types and positive matrix factorization (PMF) was applied to their temporal trends to separate and cross-apportion particle-types to factors. The extent of chemical processing for each factor was assessed by evaluating the internal and external mixing state of the characteristic particle-types. The nine factors identified helped to elucidate the coupled interactions of these determinants. Nitrate-laden dust was found to be the dominant type of locally emitted particles measured by ATOFMS. Several factors associated with aerosol transported to the site from intermediate local-to-regional distances were identified: the Organic factor was associated with a combustion source to the north-west; the ECOC Day factor was characterized by nearby local-to-regional carbonaceous emissions transported from the south-west during the daytime; and the Fireworks factor consisted of pyrotechnic particles from the Detroit region following holiday fireworks displays. Regional aerosol from farther emissions sources were reflected through three factors: two biomass burning factors and a highly chemically processed long range transport factor. The biomass burning factors were separated by PMF due to differences in chemical processing which were caused in part by the passage of two thunderstorm gust fronts with different air mass histories. The remaining two factors, ECOC Night and Nitrate Background, represented the night-time partitioning of nitrate to pre-existing particles of different origins. The distinct meteorological conditions observed during this month-long study in the summer of 2007 provided a unique range of temporal variability, enabling the elucidation of the determinants of aerosol chemical composition, including source emissions, chemical processing, and transport, at the Canada-US border. This paper presents the first study to characterize the coupled influences of these determinants on temporal variability in aerosol chemical composition using single particle-type-based receptor modelling.

Elucidating determinants of aerosol composition through particle-type-based receptor modeling

NASA Astrophysics Data System (ADS)

McGuire, M. L.; Jeong, C.-H.; Slowik, J. G.; Chang, R. Y.-W.; Corbin, J. C.; Lu, G.; Mihele, C.; Rehbein, P. J. G.; Sills, D. M. L.; Abbatt, J. P. D.; Brook, J. R.; Evans, G. J.

2011-08-01

An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed at a semi-rural site in southern Ontario to characterize the size and chemical composition of individual particles. Particle-type-based receptor modelling of these data was used to investigate the determinants of aerosol chemical composition in this region. Individual particles were classified into particle-types and positive matrix factorization (PMF) was applied to their temporal trends to separate and cross-apportion particle-types to factors. The extent of chemical processing for each factor was assessed by evaluating the internal and external mixing state of the characteristic particle-types. The nine factors identified helped to elucidate the coupled interactions of these determinants. Nitrate-laden dust was found to be the dominant type of locally emitted particles measured by ATOFMS. Several factors associated with aerosol transported to the site from intermediate local-to-regional distances were identified: the Organic factor was associated with a combustion source to the north-west; the ECOC Day factor was characterized by nearby local-to-regional carbonaceous emissions transported from the south-west during the daytime; and the Fireworks factor consisted of pyrotechnic particles from the Detroit region following holiday fireworks displays. Regional aerosol from farther emissions sources was reflected through three factors: two Biomass Burning factors and a highly chemically processed Long Range Transport factor. The Biomass Burning factors were separated by PMF due to differences in chemical processing which were in part elucidated by the passage of two thunderstorm gust fronts with different air mass histories. The remaining two factors, ECOC Night and Nitrate Background, represented the night-time partitioning of nitrate to pre-existing particles of different origins. The distinct meteorological conditions observed during this month-long study in the summer of 2007 provided a unique range of temporal variability, enabling the elucidation of the determinants of aerosol chemical composition, including source emissions, chemical processing, and transport, at the Canada-US border. This paper presents the first study to elucidate the coupled influences of these determinants on temporal variability in aerosol chemical composition using single particle-type-based receptor modelling.

PMF5.0 vs. CMB8.2: An inter-comparison study based on the new European SPECIEUROPE database

NASA Astrophysics Data System (ADS)

Bove, Maria Chiara; Massabò, Dario; Prati, Paolo

2018-03-01

Receptor Models are tools widely adopted in source apportionment studies. We describe here an experiment in which we integrated two different approaches, i.e. Positive Matrix Factorization (PMF) and Chemical Mass Balance (CMB) to apportion a set of PM10 (i.e. Particulate Matter with aerodynamic diameter lower than 10 μm) concentration values. The study was performed in the city of Genoa (Italy): a sampling campaign was carried out collecting daily PM10 samples for about two months in an urban background site. PM10 was collected on Quartz fiber filters by a low-volume sampler. A quite complete speciation of PM samples was obtained via Energy Dispersive-X Ray Fluorescence (ED-XRF, for elements), Ionic Chromatography (IC, for major ions and levoglucosan), thermo-optical Analysis (TOT, for organic and elemental carbon). The chemical analyses provided the input database for source apportionment by both PMF and CMB. Source profiles were directly calculated from the input data by PMF while in the CMB runs they were first calculated by averaging the profiles of similar sources collected in the European database SPECIEUROPE. Differences between the two receptor models emerged in particular with PM10 sources linked to very local processes. For this reason, PMF source profiles were adopted in refined CMB runs thus testing a new hybrid approach. Finally, PMF and the "tuned" CMB showed a better agreement even if some discrepancies could not completely been resolved. In this work, we compared the results coming from the last available PMF and CMB versions applied on a set of PM10 samples. Input profiles used in CMB analysis were obtained by averaging the profiles of the new European SPECIEUROPE database. The main differences between PMF and CMB results were linked to very local processes: we obtained the best solution by integrating the two different approaches with the implementation of some output PMF profiles to CMB runs.

Diversity in GABAergic signaling.

PubMed

Vogt, Kaspar

2015-01-01

GABA(A) receptor-mediated synaptic transmission is responsible for inhibitory control of neural function in the brain. Recent progress has shown that GABA(A) receptors also provide a wide range of additional functions beyond simple inhibition. This diversity of functions is mediated by a large variety of different interneuron classes acting on a diverse population of receptor subtypes. Here, I will focus on an additional source of GABAergic signaling diversity, caused by the highly variable ion signaling mechanism of GABA(A) receptors. In concert with the other two sources of GABAergic heterogeneity, this variability in signaling allows for a wide array of GABAergic effects that are crucial for the development of the brain and its function. © 2015 Elsevier Inc. All rights reserved.

Serotonin and brain function: a tale of two receptors.

PubMed

Carhart-Harris, R L; Nutt, D J

2017-09-01

Previous attempts to identify a unified theory of brain serotonin function have largely failed to achieve consensus. In this present synthesis, we integrate previous perspectives with new and older data to create a novel bipartite model centred on the view that serotonin neurotransmission enhances two distinct adaptive responses to adversity, mediated in large part by its two most prevalent and researched brain receptors: the 5-HT1A and 5-HT2A receptors. We propose that passive coping (i.e. tolerating a source of stress) is mediated by postsynaptic 5-HT1AR signalling and characterised by stress moderation. Conversely, we argue that active coping (i.e. actively addressing a source of stress) is mediated by 5-HT2AR signalling and characterised by enhanced plasticity (defined as capacity for change). We propose that 5-HT1AR-mediated stress moderation may be the brain's default response to adversity but that an improved ability to change one's situation and/or relationship to it via 5-HT2AR-mediated plasticity may also be important - and increasingly so as the level of adversity reaches a critical point. We propose that the 5-HT1AR pathway is enhanced by conventional 5-HT reuptake blocking antidepressants such as the selective serotonin reuptake inhibitors (SSRIs), whereas the 5-HT2AR pathway is enhanced by 5-HT2AR-agonist psychedelics. This bipartite model purports to explain how different drugs (SSRIs and psychedelics) that modulate the serotonergic system in different ways, can achieve complementary adaptive and potentially therapeutic outcomes.

Serotonin and brain function: a tale of two receptors

PubMed Central

Carhart-Harris, RL; Nutt, DJ

2017-01-01

Previous attempts to identify a unified theory of brain serotonin function have largely failed to achieve consensus. In this present synthesis, we integrate previous perspectives with new and older data to create a novel bipartite model centred on the view that serotonin neurotransmission enhances two distinct adaptive responses to adversity, mediated in large part by its two most prevalent and researched brain receptors: the 5-HT1A and 5-HT2A receptors. We propose that passive coping (i.e. tolerating a source of stress) is mediated by postsynaptic 5-HT1AR signalling and characterised by stress moderation. Conversely, we argue that active coping (i.e. actively addressing a source of stress) is mediated by 5-HT2AR signalling and characterised by enhanced plasticity (defined as capacity for change). We propose that 5-HT1AR-mediated stress moderation may be the brain’s default response to adversity but that an improved ability to change one’s situation and/or relationship to it via 5-HT2AR-mediated plasticity may also be important – and increasingly so as the level of adversity reaches a critical point. We propose that the 5-HT1AR pathway is enhanced by conventional 5-HT reuptake blocking antidepressants such as the selective serotonin reuptake inhibitors (SSRIs), whereas the 5-HT2AR pathway is enhanced by 5-HT2AR-agonist psychedelics. This bipartite model purports to explain how different drugs (SSRIs and psychedelics) that modulate the serotonergic system in different ways, can achieve complementary adaptive and potentially therapeutic outcomes. PMID:28858536

Validation of a novel air toxic risk model with air monitoring.

PubMed

Pratt, Gregory C; Dymond, Mary; Ellickson, Kristie; Thé, Jesse

2012-01-01

Three modeling systems were used to estimate human health risks from air pollution: two versions of MNRiskS (for Minnesota Risk Screening), and the USEPA National Air Toxics Assessment (NATA). MNRiskS is a unique cumulative risk modeling system used to assess risks from multiple air toxics, sources, and pathways on a local to a state-wide scale. In addition, ambient outdoor air monitoring data were available for estimation of risks and comparison with the modeled estimates of air concentrations. Highest air concentrations and estimated risks were generally found in the Minneapolis-St. Paul metropolitan area and lowest risks in undeveloped rural areas. Emissions from mobile and area (nonpoint) sources created greater estimated risks than emissions from point sources. Highest cancer risks were via ingestion pathway exposures to dioxins and related compounds. Diesel particles, acrolein, and formaldehyde created the highest estimated inhalation health impacts. Model-estimated air concentrations were generally highest for NATA and lowest for the AERMOD version of MNRiskS. This validation study showed reasonable agreement between available measurements and model predictions, although results varied among pollutants, and predictions were often lower than measurements. The results increased confidence in identifying pollutants, pathways, geographic areas, sources, and receptors of potential concern, and thus provide a basis for informing pollution reduction strategies and focusing efforts on specific pollutants (diesel particles, acrolein, and formaldehyde), geographic areas (urban centers), and source categories (nonpoint sources). The results heighten concerns about risks from food chain exposures to dioxins and PAHs. Risk estimates were sensitive to variations in methodologies for treating emissions, dispersion, deposition, exposure, and toxicity. © 2011 Society for Risk Analysis.

Concentrations and sources of non-methane hydrocarbons (NMHCs) from 2005 to 2013 in Hong Kong: A multi-year real-time data analysis

NASA Astrophysics Data System (ADS)

Ou, Jiamin; Guo, Hai; Zheng, Junyu; Cheung, Kalam; Louie, Peter K. K.; Ling, Zhenhao; Wang, Dawei

2015-02-01

To understand the long-term variations of nonmethane hydrocarbons (NMHCs) and their emission sources, real-time speciated NMHCs have been monitored in Hong Kong since 2005. Data analysis showed that the concentrations of C3-C5 and C6-C7 alkanes slightly increased from 2005 to 2013 at a rate of 0.0015 and 0.0005 μg m-3 yr-1 (p < 0.05), respectively, while aromatics decreased at a rate of 0.006 μg m-3 yr-1 (p < 0.05). Positive Matrix Factorization (PMF) model was applied to identify and quantify the NMHC sources. Vehicular exhaust, gasoline evaporation and liquefied petroleum gas (LPG) usage, consumer product and printing, architectural paints, and biogenic emissions were identified and on average accounted for 20.2 ± 6.2%, 25.4 ± 6.3%, 32.6 ± 5.8%, 21.5 ± 4.5%, and 3.3 ± 1.5% of the ambient NMHC concentrations, respectively. From 2005 to 2013, the contributions of both traffic-related sources and solvent-related sources showed no significant changes, different from the trends in emission inventory. On O3 episode days dominated by local air masses, the increase ratio of NMHC species from non-episode to episode days was found to be a natural function of the reactivity of NMHC species, suggesting that photochemical reaction would significantly change the NMHCs composition between emission sources and the receptors. Effect of photochemical reaction loss on receptor-oriented source apportionment analysis needs to be quantified in order to identify the NMHCs emission sources on O3 episode days.

SIZE DISTRIBUTION AND DIURNAL CHARACTERISTICS OF PARTICLE-BOUND METALS IN SOURCE AND RECEPTOR SITES OF THE LOS ANGELES BASIN. (R827352C006)

EPA Science Inventory

Measurement of daily size-fractionated ambient PM₁₀ mass, metals, inorganic ions (nitrate and sulfate) and elemental and organic carbon were conducted at source (Downey) and receptor (Riverside) sites within the Los Angeles Basin. In addition to 24-h concentration m...

Kappa-receptor selective binding of opioid ligands with a heterocyclic bicyclo[3.3.1]nonan-9-one structure.

PubMed

Benyhe, S; Márki, A; Nachtsheim, Corina; Holzgrabe, Ulrike; Borsodi, Anna

2003-01-01

Previous pharmacological results have suggested that members of the heterocyclic bicyclo[3.3.1]nonan-9-one-like compounds are potent kappa-opioid receptor specific agonists. One lead molecule of this series. called compound 1 (dimethyl 7-methyl-2,4-di-2-pyridyl-3.7-diazabicyclo[3.3.1]nonan-9-one-1,5-dicarboxylate) exhibited high affinity for [3H]ethylketocyclazocine and [3H]U-69.593 binding sites in guinea pig cerebellar membranes which known to be a good source for kappa1 receptors. It was shown by molecular modelling that heterocyclic bicyclo[3.3.1]nonan-9-ones fit very well with the structure of ketazocine, a prototypic kappa-selective benzomorphan compound; when compared to the arylacetamide structure of U-69.593, a specific kappa1-receptor agonist, a similar geometry was found with a slightly different distribution of the charges. It is postulated, that the essential structural skeleton involved in the opioid activity is an aryl-propyl-amine element distributed along the N7-C6-C5-C4-aryl bonds.

Hormonally active phytochemicals from macroalgae: A largely untapped source of ligands to deorphanize nuclear receptors in emerging marine animal models.

PubMed

Markov, Gabriel V; Girard, Jean; Laudet, Vincent; Leblanc, Catherine

2018-06-15

Hormonally active phytochemicals (HAPs) are signaling molecules produced by plants that alter hormonal signaling in animals, due to consumption or environmental exposure. To date, HAPs have been investigated mainly in terrestrial ecosystems. To gain a full understanding of the origin and evolution of plant-animal interactions, it is necessary also to study these interactions in the marine environment, where the major photosynthetic lineages are very distant from the terrestrial plants. Here we focus on chemicals from red and brown macroalgae and point out their potential role as modulators of the endocrine system of aquatic animals through nuclear hormone receptors. We show that, regarding steroids and oxylipins, there are already some candidates available for further functional investigations of ligand-receptor interactions. Furthermore, several carotenoids, produced by cyanobacteria provide candidates that could be investigated with respect to their presence in macroalgae. Finally, regarding halogenated compounds, it is not clear yet which molecules could bridge the gap to explain the transition from lipid sensing to thyroid hormone high affinity binding among nuclear receptors. Copyright © 2018 Elsevier Inc. All rights reserved.

Potential insight for drug discovery from high fidelity receptor-mediated transduction mechanisms in insects

PubMed Central

Raffa, Robert B.; Raffa, Kenneth F.

2011-01-01

Introduction There is a pervasive and growing concern about the small number of new pharmaceutical agents. There are many proposed explanations for this trend that do not involve the drug-discovery process per se, but the discovery process itself has also come under scrutiny. If the current paradigms are indeed not working, where are novel ideas to come from? Perhaps it is time to look to novel sources. Areas covered The receptor-signaling and 2nd-messenger transduction processes present in insects are quite similar to those in mammals (involving G proteins, ion channels, etc.). However, a review of these systems reveals an unprecedented degree of high potency and receptor selectivity to an extent greater than that modeled in most current drug-discovery approaches. Expert opinion A better understanding of insect receptor pharmacology could stimulate novel theoretical and practical ideas in mammalian pharmacology (drug discovery) and, conversely, the application of pharmacology and medicinal chemistry principles could stimulate novel advances in entomology (safer and more targeted control of pest species). PMID:21984882

A Data-Driven Framework for Incorporating New Tools for ...

EPA Pesticide Factsheets

This talk was given during the “Exposure-Based Toxicity Testing” session at the annual meeting of the International Society for Exposure Science. It provided an update on the state of the science and tools that may be employed in risk-based prioritization efforts. It outlined knowledge gained from the data provided using these high-throughput tools to assess chemical bioactivity and to predict chemical exposures and also identified future needs. It provided an opportunity to showcase ongoing research efforts within the National Exposure Research Laboratory and the National Center for Computational Toxicology within the Office of Research and Development to an international audience. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Dynamic Evaluation of Two Decades of CMAQ Simulations ...

EPA Pesticide Factsheets

This presentation focuses on the dynamic evaluation of the CMAQ model over the continental United States using multi-decadal simulations for the period from 1990 to 2010 to examine how well the changes in observed ozone air quality induced by variations in meteorology and/or emissions are simulated by the model. We applied spectral decomposition of the ozone time-series using the KZ filter to assess the variations in the strengths of synoptic (weather-induced variations) and baseline (long-term variation) forcings, embedded in the simulated and observed concentrations. The results reveal that CMAQ captured the year-to-year variability (more so in the later years than the earlier years) and the synoptic forcing in accordance with what the observations are showing. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Calcium responses to synaptically activated bursts of action potentials and their synapse-independent replay in cultured networks of hippocampal neurons.

PubMed

Bengtson, C Peter; Kaiser, Martin; Obermayer, Joshua; Bading, Hilmar

2013-07-01

Both synaptic N-methyl-d-aspartate (NMDA) receptors and voltage-operated calcium channels (VOCCs) have been shown to be critical for nuclear calcium signals associated with transcriptional responses to bursts of synaptic input. However the direct contribution to nuclear calcium signals from calcium influx through NMDA receptors and VOCCs has been obscured by their concurrent roles in action potential generation and synaptic transmission. Here we compare calcium responses to synaptically induced bursts of action potentials with identical bursts devoid of any synaptic contribution generated using the pre-recorded burst as the voltage clamp command input to replay the burst in the presence of blockers of action potentials or ionotropic glutamate receptors. Synapse independent replays of bursts produced nuclear calcium responses with amplitudes around 70% of their original synaptically generated signals and were abolished by the L-type VOCC blocker, verapamil. These results identify a major direct source of nuclear calcium from local L-type VOCCs whose activation is boosted by NMDA receptor dependent depolarization. The residual component of synaptically induced nuclear calcium signals which was both VOCC independent and NMDA receptor dependent showed delayed kinetics consistent with a more distal source such as synaptic NMDA receptors or internal stores. The dual requirement of NMDA receptors and L-type VOCCs for synaptic activity-induced nuclear calcium dependent transcriptional responses most likely reflects a direct somatic calcium influx from VOCCs whose activation is amplified by synaptic NMDA receptor-mediated depolarization and whose calcium signal is boosted by a delayed input from distal calcium sources mostly likely entry through NMDA receptors and release from internal stores. This article is part of a Special Issue entitled: 12th European Symposium on Calcium. Copyright © 2013 Elsevier B.V. All rights reserved.

Contributions of local and regional anthropogenic sources of metals in PM2.5 at an urban site in northern France.

PubMed

Ledoux, Frédéric; Kfoury, Adib; Delmaire, Gilles; Roussel, Gilles; El Zein, Atallah; Courcot, Dominique

2017-08-01

PM 2.5 have been related to various adverse health effects, mainly due to their ability to penetrate deeply and to convey harmful chemical components, such as metals inside the body. In this work, PM 2.5 were sampled at Saint-Omer, a medium-sized city located in northern France, in March-April 2011 and analyzed for their total carbon, water-soluble ions, major and trace elements. More specifically, the origin of 15 selected elements was examined using different tools including enrichment factors, conditional bivariate probability function (CBPF) representations, diagnostic ratios and receptor modelling. The results indicated that PM 2.5 metal composition is affected by both emissions of a local glassmaking factory and an integrated steelworks located at a distance of 35 km from the sampling site. For the first time, diagnostic ratios were proposed for the glassmaking activity. Therefore, metals in PM 2.5 could be attributed to the following anthropogenic sources: (i) local glassmaking industry for Sn, As, Cu and Cr, (ii) distant integrated steelworks for Ag, Fe, Cd, Mn, Rb and Pb, (iii) heavy fuel oil combustion for Ni, V and Co and (iv) non-exhaust traffic for Zn, Pb, Mn, Sb, and Cu. The impact of such sources on metal concentrations in PM 2.5 was assessed using a constrained receptor model. Despite their low participation to PM 2.5 concentration (2.7%), the latter sources were found as the main contributors (80%) to the overall concentration levels of the 15 selected elements in PM 2.5 . Copyright © 2017 Elsevier Ltd. All rights reserved.

Minimalist hybrid ligand/receptor-based pharmacophore model for CXCR4 applied to a small-library of marine natural products led to the identification of phidianidine a as a new CXCR4 ligand exhibiting antagonist activity.

PubMed

Vitale, Rosa Maria; Gatti, Monica; Carbone, Marianna; Barbieri, Federica; Felicità, Vera; Gavagnin, Margherita; Florio, Tullio; Amodeo, Pietro

2013-12-20

Here, we present a minimal hybrid ligand/receptor-based pharmacophore model (PM) for CXCR4, a chemokine receptor deeply involved in several pathologies, such as HIV infection, rheumatoid arthritis, cancer development/progression, and metastasization. This model, considerably simpler than those thus far proposed for this receptor, has been used to search for new CXCR4 inhibitors in a small marine natural product library available at ICB-CNR Institute (Pozzuoli, NA, Italy), since natural products, with their naturally selected chemical and functional diversity, represent a rich source of bioactive scaffolds; computational approaches allow searching for new scaffolds with a minimal waste of possibly precious natural product samples; and our "stripped-down" model substantially increases the probabilities of identifying potential hits even in small-sized libraries. This search, also validated by a systematic virtual screening of the same library, has led to the identification of a new CXCR4 ligand, phidianidine A (PHIA). Docking studies supported PHIA activity and suggested its possible binding modes to CXCR4. Using the CXCR4-expressing/CXCR7-negative GH4C1 cell line we show that PHIA inhibits CXCL12-induced DNA synthesis, cell migration, and ERK1/2 activation. The specificity of these effects was confirmed by the lack of PHIA activity in GH4C1 cells, in which siRNA highly reduces CXCR4 expression and the lack of cytoxicity of PHIA was also verified. Thus, PHIA represents a promising lead for a new family of CXCR4 modulators with wide margins of improvement in potency and specificity offered by the small and very simple underlying PM.

Comparison among model estimates of critical loads of acidic deposition using different sources and scales of input data

Treesearch

T.C. McDonnell; B.J. Cosby; T.J. Sullivan; S.G. McNulty; E.C. Cohen

2010-01-01

The critical load (CL) of acidic atmospheric deposition represents the load of acidity deposited from the atmosphere to the earth’s surface at which harmful acidification effects on sensitive biological receptors are thought to occur. In this study, the CL for forest soils was estimated for 27 watersheds throughout the United States using a steady-state mass balance...

Ground-Based Aerosol Measurements | Science Inventory ...

EPA Pesticide Factsheets

Atmospheric particulate matter (PM) is a complex chemical mixture of liquid and solid particles suspended in air (Seinfeld and Pandis 2016). Measurements of this complex mixture form the basis of our knowledge regarding particle formation, source-receptor relationships, data to test and verify complex air quality models, and how PM impacts human health, visibility, global warming, and ecological systems (EPA 2009). Historically, PM samples have been collected on filters or other substrates with subsequent chemical analysis in the laboratory and this is still the major approach for routine networks (Chow 2005; Solomon et al. 2014) as well as in research studies. In this approach, air, at a specified flow rate and time period, is typically drawn through an inlet, usually a size selective inlet, and then drawn through filters, 1 INTRODUCTION Atmospheric particulate matter (PM) is a complex chemical mixture of liquid and solid particles suspended in air (Seinfeld and Pandis 2016). Measurements of this complex mixture form the basis of our knowledge regarding particle formation, source-receptor relationships, data to test and verify complex air quality models, and how PM impacts human health, visibility, global warming, and ecological systems (EPA 2009). Historically, PM samples have been collected on filters or other substrates with subsequent chemical analysis in the laboratory and this is still the major approach for routine networks (Chow 2005; Solomo

WRF dynamically downscaling PCM data for climate change impacts in California & application of a signal technique to the source-receptor relationship in WRF

NASA Astrophysics Data System (ADS)

Zhao, Zhan

2009-12-01

My dissertation consists of three parts. Parts I and II are focused on the climate change impacts on meteorology and air quality conditions in California (CA), while Part III is focused on the source-receptor relationship. The WRF model is applied to dynamically downscaled PCM data, with a horizontal resolution of approximately 2.8°x2.8°, to 4km resolution under the Business as Usual (BAU) scenario. The dynamical downscaling method could retain the large-scale features of the global simulations with more meso-scale details. A seven year simulation is conducted for both present (2000˜2006) and future (2047˜2053) in order to avoid the El Nino related inter-annual variation. In order to assess the PCM data quality and estimate the simulation error inherited from the PCM data bias, the present seven year simulations are driven by NCEP's Global Forecast System (GFS) data with the same model configuration. Part I is focused on the comparisons of the present time climatology from the two sets of simulations and the driving global datasets (i.e., PCM vs. GFS), which illustrate that the biases of the downscaling results are mostly inherited from the driving GCM. The imprecise prediction for the location and strength of the Pacific Subtropical High (PSH) is a main source of the PCM data bias. The analysis also implies that using the simulation results driven by PCM data as the input of the air quality model will underrate the air pollution problems in CA. The regional averaged statistics of the downscaling results compared to observational data show that both the surface temperature and wind speed were overestimate for most times of the year, and WRF preformed better during summer than winter. The low summer PBLH in the San Joaquin Valley (SJV) is addressed, and two reasons causing this are the dominance of a high pressure system over the valley and, to a lesser extent, the valley wind at daytime during summer. Part II is focused on the future change of meteorology and air quality in CA and comparisons are made between future and present simulations driven by the PCM data. Both the duration and strength of stagnant events, during which most air pollution problems occur in SJV, are increased during summer and winter. The seven-year averaged spatial distribution of the air-pollution related meteorological variables, such as surface wind, temperature, PBLH, etc., indicate that the future summer ozone problem would be mitigated in the coast region of Los Angeles County (LAC), while both the summer ozone and winter particulate matter (PM) problem in SJV and other parts of the Southern California Air Basin (SoCAB) will be exacerbated in the future. The impact on the land-sea breeze, which plays a big role in California's climate, is also explored in this part. Part III of the thesis is to investigate the potential of applying a signal technique on the source-receptor relationship. This approach is more economical in terms of computational time and memory than the conventional tracer method. The signal technique was implemented into the WRF model, and an idealized supercell case and a real case in Turkey were used to investigate the potential of the technique. Emissions from different source locations were tagged with different frequencies, which were added onto the emitted pollutants, with a specific frequency from each location. The time series of the pollutant concentration collected at receptors were then projected onto the frequency space using the Fourier transform and short-time Fourier transform methods to identify the source locations. During the model integration, a particular constant tracer was also emitted from each pollutant source location to validate and evaluate the signal technique. Results show that the frequencies could be slightly shifted after signals were transported over a long distance and evident secondary frequencies (i.e., beats) could be generated due to nonlinear effects. Although these could potentially confuse the identification of signals released from source points, signals were still distinguishable in this study.

Characterization of air manganese exposure estimates for residents in two Ohio towns

PubMed Central

Colledge, Michelle A.; Julian, Jaime R.; Gocheva, Vihra V.; Beseler, Cheryl L.; Roels, Harry A.; Lobdell, Danelle T.; Bowler, Rosemarie M.

2016-01-01

This study was conducted to derive receptor-specific outdoor exposure concentrations of total suspended particulate (TSP) and respirable (dae ≤ 10 μm) air manganese (air-Mn) for East Liverpool and Marietta (Ohio) in the absence of facility emissions data, but where long-term air measurements were available. Our “site-surface area emissions method” used U.S. Environmental Protection Agency’s (EPA) AERMOD (AMS/EPA Regulatory Model) dispersion model and air measurement data to estimate concentrations for residential receptor sites in the two communities. Modeled concentrations were used to create ratios between receptor points and calibrated using measured data from local air monitoring stations. Estimated outdoor air-Mn concentrations were derived for individual study subjects in both towns. The mean estimated long-term air-Mn exposure levels for total suspended particulate were 0.35 μg/m3 (geometric mean [GM]) and 0.88 μg/m3 (arithmetic mean [AM]) in East Liverpool (range: 0.014–6.32 μg/m3) and 0.17 μg/m3 (GM) and 0.21 μg/m3 (AM) in Marietta (range: 0.03–1.61 μg/m3). Modeled results compared well with averaged ambient air measurements from local air monitoring stations. Exposure to respirable Mn particulate matter (PM10; PM <10 μm) was higher in Marietta residents. Implications Few available studies evaluate long-term health outcomes from inhalational manganese (Mn) exposure in residential populations, due in part to challenges in measuring individual exposures. Local long-term air measurements provide the means to calibrate models used in estimating long-term exposures. Furthermore, this combination of modeling and ambient air sampling can be used to derive receptor-specific exposure estimates even in the absence of source emissions data for use in human health outcome studies. PMID:26211636

Modeling Multivalent Ligand-Receptor Interactions with Steric Constraints on Configurations of Cell-Surface Receptor Aggregates

PubMed Central

Monine, Michael I.; Posner, Richard G.; Savage, Paul B.; Faeder, James R.; Hlavacek, William S.

2010-01-01

Abstract We use flow cytometry to characterize equilibrium binding of a fluorophore-labeled trivalent model antigen to bivalent IgE-FcεRI complexes on RBL cells. We find that flow cytometric measurements are consistent with an equilibrium model for ligand-receptor binding in which binding sites are assumed to be equivalent and ligand-induced receptor aggregates are assumed to be acyclic. However, this model predicts extensive receptor aggregation at antigen concentrations that yield strong cellular secretory responses, which is inconsistent with the expectation that large receptor aggregates should inhibit such responses. To investigate possible explanations for this discrepancy, we evaluate four rule-based models for interaction of a trivalent ligand with a bivalent cell-surface receptor that relax simplifying assumptions of the equilibrium model. These models are simulated using a rule-based kinetic Monte Carlo approach to investigate the kinetics of ligand-induced receptor aggregation and to study how the kinetics and equilibria of ligand-receptor interaction are affected by steric constraints on receptor aggregate configurations and by the formation of cyclic receptor aggregates. The results suggest that formation of linear chains of cyclic receptor dimers may be important for generating secretory signals. Steric effects that limit receptor aggregation and transient formation of small receptor aggregates may also be important. PMID:20085718

Modeling the Influence of Hemispheric Transport on Trends in ...

EPA Pesticide Factsheets

We describe the development and application of the hemispheric version of the CMAQ to examine the influence of long-range pollutant transport on trends in surface level O3 distributions. The WRF-CMAQ model is expanded to hemispheric scales and multi-decadal model simulations were recently performed for the period spanning 1990-2010 to examine changes in hemispheric air pollution resulting from changes in emissions over this period. Simulated trends in ozone and precursor species concentrations across the U.S. and the northern hemisphere over the past two decades are compared with those inferred from available measurements during this period. Additionally, the decoupled direct method (DDM) in CMAQ is used to estimate the sensitivity of O3 to emissions from different source regions across the northern hemisphere. The seasonal variations in source region contributions to background O3 is then estimated from these sensitivity calculations and will be discussed. A reduced form model combining these source region sensitivities estimated from DDM with the multi-decadal simulations of O3 distributions and emissions trends, is then developed to characterize the changing contributions of different source regions to background O3 levels across North America. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas

Application of hierarchical Bayesian unmixing models in river sediment source apportionment

NASA Astrophysics Data System (ADS)

Blake, Will; Smith, Hugh; Navas, Ana; Bodé, Samuel; Goddard, Rupert; Zou Kuzyk, Zou; Lennard, Amy; Lobb, David; Owens, Phil; Palazon, Leticia; Petticrew, Ellen; Gaspar, Leticia; Stock, Brian; Boeckx, Pacsal; Semmens, Brice

2016-04-01

Fingerprinting and unmixing concepts are used widely across environmental disciplines for forensic evaluation of pollutant sources. In aquatic and marine systems, this includes tracking the source of organic and inorganic pollutants in water and linking problem sediment to soil erosion and land use sources. It is, however, the particular complexity of ecological systems that has driven creation of the most sophisticated mixing models, primarily to (i) evaluate diet composition in complex ecological food webs, (ii) inform population structure and (iii) explore animal movement. In the context of the new hierarchical Bayesian unmixing model, MIXSIAR, developed to characterise intra-population niche variation in ecological systems, we evaluate the linkage between ecological 'prey' and 'consumer' concepts and river basin sediment 'source' and sediment 'mixtures' to exemplify the value of ecological modelling tools to river basin science. Recent studies have outlined advantages presented by Bayesian unmixing approaches in handling complex source and mixture datasets while dealing appropriately with uncertainty in parameter probability distributions. MixSIAR is unique in that it allows individual fixed and random effects associated with mixture hierarchy, i.e. factors that might exert an influence on model outcome for mixture groups, to be explored within the source-receptor framework. This offers new and powerful ways of interpreting river basin apportionment data. In this contribution, key components of the model are evaluated in the context of common experimental designs for sediment fingerprinting studies namely simple, nested and distributed catchment sampling programmes. Illustrative examples using geochemical and compound specific stable isotope datasets are presented and used to discuss best practice with specific attention to (1) the tracer selection process, (2) incorporation of fixed effects relating to sample timeframe and sediment type in the modelling process, (3) deriving and using informative priors in sediment fingerprinting context and (4) transparency of the process and replication of model results by other users.

Dose Modeling Evaluations and Technical Support Document For the Authorized Limits Request for the DOE-Owned Property Outside the Limited Area, Paducah Gaseous Diffusion Plant Paducah, Kentucky

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

Boerner, A. J.; Maldonado, D. G.; Hansen, Tom

2012-09-01

Environmental assessments and remediation activities are being conducted by the U.S. Department of Energy (DOE) at the Paducah Gaseous Diffusion Plant (PGDP), Paducah, Kentucky. The Oak Ridge Institute for Science and Education (ORISE), a DOE prime contractor, was contracted by the DOE Portsmouth/Paducah Project Office (DOE-PPPO) to conduct radiation dose modeling analyses and derive single radionuclide soil guidelines (soil guidelines) in support of the derivation of Authorized Limits (ALs) for 'DOE-Owned Property Outside the Limited Area' ('Property') at the PGDP. The ORISE evaluation specifically included the area identified by DOE restricted area postings (public use access restrictions) and areas licensedmore » by DOE to the West Kentucky Wildlife Management Area (WKWMA). The licensed areas are available without restriction to the general public for a variety of (primarily) recreational uses. Relevant receptors impacting current and reasonably anticipated future use activities were evaluated. In support of soil guideline derivation, a Conceptual Site Model (CSM) was developed. The CSM listed radiation and contamination sources, release mechanisms, transport media, representative exposure pathways from residual radioactivity, and a total of three receptors (under present and future use scenarios). Plausible receptors included a Resident Farmer, Recreational User, and Wildlife Worker. single radionuclide soil guidelines (outputs specified by the software modeling code) were generated for three receptors and thirteen targeted radionuclides. These soil guidelines were based on satisfying the project dose constraints. For comparison, soil guidelines applicable to the basic radiation public dose limit of 100 mrem/yr were generated. Single radionuclide soil guidelines from the most limiting (restrictive) receptor based on a target dose constraint of 25 mrem/yr were then rounded and identified as the derived soil guidelines. An additional evaluation using the derived soil guidelines as inputs into the code was also performed to determine the maximum (peak) dose for all receptors. This report contains the technical basis in support of the DOE?s derivation of ALs for the 'Property.' A complete description of the methodology, including an assessment of the input parameters, model inputs, and results is provided in this report. This report also provides initial recommendations on applying the derived soil guidelines.« less

Bayesian estimation of a source term of radiation release with approximately known nuclide ratios

NASA Astrophysics Data System (ADS)

Tichý, Ondřej; Šmídl, Václav; Hofman, Radek

2016-04-01

We are concerned with estimation of a source term in case of an accidental release from a known location, e.g. a power plant. Usually, the source term of an accidental release of radiation comprises of a mixture of nuclide. The gamma dose rate measurements do not provide a direct information on the source term composition. However, physical properties of respective nuclide (deposition properties, decay half-life) can be used when uncertain information on nuclide ratios is available, e.g. from known reactor inventory. The proposed method is based on linear inverse model where the observation vector y arise as a linear combination y = Mx of a source-receptor-sensitivity (SRS) matrix M and the source term x. The task is to estimate the unknown source term x. The problem is ill-conditioned and further regularization is needed to obtain a reasonable solution. In this contribution, we assume that nuclide ratios of the release is known with some degree of uncertainty. This knowledge is used to form the prior covariance matrix of the source term x. Due to uncertainty in the ratios the diagonal elements of the covariance matrix are considered to be unknown. Positivity of the source term estimate is guaranteed by using multivariate truncated Gaussian distribution. Following Bayesian approach, we estimate all parameters of the model from the data so that y, M, and known ratios are the only inputs of the method. Since the inference of the model is intractable, we follow the Variational Bayes method yielding an iterative algorithm for estimation of all model parameters. Performance of the method is studied on simulated 6 hour power plant release where 3 nuclide are released and 2 nuclide ratios are approximately known. The comparison with method with unknown nuclide ratios will be given to prove the usefulness of the proposed approach. This research is supported by EEA/Norwegian Financial Mechanism under project MSMT-28477/2014 Source-Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling (STRADI).

Environmental Assessment of Installation Development at McConnell Air Force Base, Kansas

DTIC Science & Technology

2007-05-01

characteristics of the noise source, distance between source and receptor, receptor sensitivity, weather , and time of day. Sound is measured with...bulk fuel storage and transfer, fuel dispensing, service stations , solvent degreasing, surface coating, and chemical usage/fugitive emissions. The...and weathered Permian bedrock. The deeper aquifer is within calcareous shales of the Wellington Formation. Groundwater flow follows the local

Testosterone and 17β-estradiol have opposite effects on podocyte apoptosis that precedes glomerulosclerosis in female estrogen receptor knockout mice

PubMed Central

Doublier, Sophie; Lupia, Enrico; Catanuto, Paola; Periera-Simon, Simone; Xia, Xiaomei; Korach, Ken; Berho, Mariana; Elliot, Sharon J.; Karl, Michael

2016-01-01

Podocyte damage and apoptosis are thought to be important if not essential in the development of glomerulosclerosis. Female estrogen receptor knockout mice develop glomerulosclerosis at 9 months of age due to excessive ovarian testosterone production and secretion. Here, we studied the pathogenesis of glomerulosclerosis in this mouse model to determine whether testosterone and/or 17β-estradiol directly affect the function and survival of podocytes. Glomerulosclerosis in these mice was associated with the expression of desmin and the loss of nephrin, markers of podocyte damage and apoptosis. Ovariectomy preserved the function and survival of podocytes by eliminating the source of endogenous testosterone production. In contrast, testosterone supplementation induced podocyte apoptosis in ovariectomized wild-type mice. Importantly, podocytes express functional androgen and estrogen receptors, which, upon stimulation by their respective ligands, have opposing effects. Testosterone induced podocyte apoptosis in vitro by androgen receptor activation, but independent of the TGF-β1 signaling pathway. Pretreatment with 17β-estradiol prevented testosterone-induced podocyte apoptosis, an estrogen receptor-dependent effect mediated by activation of the ERK signaling pathway, and protected podocytes from TGF-β1- or TNF-α-induced apoptosis. Thus, podocytes are target cells for testosterone and 17β-estradiol. These hormones modulate podocyte damage and apoptosis. PMID:20962747

Testosterone and 17β-estradiol have opposite effects on podocyte apoptosis that precedes glomerulosclerosis in female estrogen receptor knockout mice.

PubMed

Doublier, Sophie; Lupia, Enrico; Catanuto, Paola; Periera-Simon, Simone; Xia, Xiaomei; Korach, Ken; Berho, Mariana; Elliot, Sharon J; Karl, Michael

2011-02-01

Podocyte damage and apoptosis are thought to be important if not essential in the development of glomerulosclerosis. Female estrogen receptor knockout mice develop glomerulosclerosis at 9 months of age due to excessive ovarian testosterone production and secretion. Here, we studied the pathogenesis of glomerulosclerosis in this mouse model to determine whether testosterone and/or 17β-estradiol directly affect the function and survival of podocytes. Glomerulosclerosis in these mice was associated with the expression of desmin and the loss of nephrin, markers of podocyte damage and apoptosis. Ovariectomy preserved the function and survival of podocytes by eliminating the source of endogenous testosterone production. In contrast, testosterone supplementation induced podocyte apoptosis in ovariectomized wild-type mice. Importantly, podocytes express functional androgen and estrogen receptors, which, upon stimulation by their respective ligands, have opposing effects. Testosterone induced podocyte apoptosis in vitro by androgen receptor activation, but independent of the TGF-β1 signaling pathway. Pretreatment with 17β-estradiol prevented testosterone-induced podocyte apoptosis, an estrogen receptor-dependent effect mediated by activation of the ERK signaling pathway, and protected podocytes from TGF-β1- or TNF-α-induced apoptosis. Thus, podocytes are target cells for testosterone and 17β-estradiol. These hormones modulate podocyte damage and apoptosis.

Can positive matrix factorization help to understand patterns of organic trace gases at the continental Global Atmosphere Watch site Hohenpeissenberg?

NASA Astrophysics Data System (ADS)

Leuchner, M.; Gubo, S.; Schunk, C.; Wastl, C.; Kirchner, M.; Menzel, A.; Plass-Dülmer, C.

2015-02-01

From the rural Global Atmosphere Watch (GAW) site Hohenpeissenberg in the pre-alpine area of southern Germany, a data set of 24 C2-C8 non-methane hydrocarbons over a period of 7 years was analyzed. Receptor modeling was performed by positive matrix factorization (PMF) and the resulting factors were interpreted with respect to source profiles and photochemical aging. Differing from other studies, no direct source attribution was intended because, due to chemistry along transport, mass conservation from source to receptor is not given. However, at remote sites such as Hohenpeissenberg, the observed patterns of non-methane hydrocarbons can be derived from combinations of factors determined by PMF. A six-factor solution showed high stability and the most plausible results. In addition to a biogenic and a background factor of very stable compounds, four additional anthropogenic factors were resolved that could be divided into two short- and two long-lived patterns from evaporative sources/natural gas leakage and incomplete combustion processes. The volume or mass contribution at the site over the entire period was, in decreasing order, from the following factor categories: background, gas leakage and long-lived evaporative, residential heating and long-lived combustion, short-lived evaporative, short-lived combustion, and biogenic. The importance with respect to reactivity contribution was generally in reverse order, with the biogenic and the short-lived combustion factors contributing most. The seasonality of the factors was analyzed and compared to results of a simple box model using constant emissions and the photochemical decay calculated from the measured annual cycles of OH radicals and ozone. Two of the factors, short-lived combustion and gas leakage/long-lived evaporative, showed winter/summer ratios of about 9 and 7, respectively, as expected from constant source estimations. Contrarily, the short-lived evaporative emissions were about 3 times higher in summer than in winter, while residential heating/long-lived combustion emissions were about 2 times higher in winter than in summer.

Contribution of PAHs from coal-tar pavement sealcoat and other sources to 40 U.S. lakes

USGS Publications Warehouse

Van Metre, Peter C.; Mahler, Barbara J.

2010-01-01

Contamination of urban lakes and streams by polycyclic aromatic hydrocarbons (PAHs) has increased in the United States during the past 40 years. We evaluated sources of PAHs in post-1990 sediments in cores from 40 lakes in urban areas across the United States using a contaminant mass-balance receptor model and including as a potential source coal-tar-based (CT) sealcoat, a recently recognized source of urban PAH. Other PAH sources considered included several coal- and vehicle-related sources, wood combustion, and fuel-oil combustion. The four best modeling scenarios all indicate CT sealcoat is the largest PAH source when averaged across all 40 lakes, contributing about one-half of PAH in sediment, followed by vehicle-related sources and coal combustion. PAH concentrations in the lakes were highly correlated with PAH loading from CT sealcoat (Spearman's rho=0.98), and the mean proportional PAH profile for the 40 lakes was highly correlated with the PAH profile for dust from CT-sealed pavement (r=0.95). PAH concentrations and mass and fractional loading from CT sealcoat were significantly greater in the central and eastern United States than in the western United States, reflecting regional differences in use of different sealcoat product types. The model was used to calculate temporal trends in PAH source contributions during the last 40 to 100 years to eight of the 40 lakes. In seven of the lakes, CT sealcoat has been the largest source of PAHs since the 1960s, and in six of those lakes PAH trends are upward. Traffic is the largest source to the eighth lake, located in southern California where use of CT sealcoat is rare.

Uncertainty propagation for SPECT/CT-based renal dosimetry in 177Lu peptide receptor radionuclide therapy

NASA Astrophysics Data System (ADS)

Gustafsson, Johan; Brolin, Gustav; Cox, Maurice; Ljungberg, Michael; Johansson, Lena; Sjögreen Gleisner, Katarina

2015-11-01

A computer model of a patient-specific clinical 177Lu-DOTATATE therapy dosimetry system is constructed and used for investigating the variability of renal absorbed dose and biologically effective dose (BED) estimates. As patient models, three anthropomorphic computer phantoms coupled to a pharmacokinetic model of 177Lu-DOTATATE are used. Aspects included in the dosimetry-process model are the gamma-camera calibration via measurement of the system sensitivity, selection of imaging time points, generation of mass-density maps from CT, SPECT imaging, volume-of-interest delineation, calculation of absorbed-dose rate via a combination of local energy deposition for electrons and Monte Carlo simulations of photons, curve fitting and integration to absorbed dose and BED. By introducing variabilities in these steps the combined uncertainty in the output quantity is determined. The importance of different sources of uncertainty is assessed by observing the decrease in standard deviation when removing a particular source. The obtained absorbed dose and BED standard deviations are approximately 6% and slightly higher if considering the root mean square error. The most important sources of variability are the compensation for partial volume effects via a recovery coefficient and the gamma-camera calibration via the system sensitivity.

Separating the air quality impact of a major highway and nearby sources by nonparametric trajectory analysis.

PubMed

Henry, Ronald C; Vette, Alan; Norris, Gary; Vedantham, Ram; Kimbrough, Sue; Shores, Richard C

2011-12-15

Nonparametric Trajectory Analysis (NTA), a receptor-oriented model, was used to assess the impact of local sources of air pollution at monitoring sites located adjacent to highway I-15 in Las Vegas, NV. Measurements of black carbon, carbon monoxide, nitrogen oxides, and sulfur dioxide concentrations were collected from December 2008 to December 2009. The purpose of the study was to determine the impact of the highway at three downwind monitoring stations using an upwind station to measure background concentrations. NTA was used to precisely determine the contribution of the highway to the average concentrations measured at the monitoring stations accounting for the spatially heterogeneous contributions of other local urban sources. NTA uses short time average concentrations, 5 min in this case, and constructed local back-trajectories from similarly short time average wind speed and direction to locate and quantify contributions from local source regions. Averaged over an entire year, the decrease of concentrations with distance from the highway was found to be consistent with previous studies. For this study, the NTA model is shown to be a reliable approach to quantify the impact of the highway on local air quality in an urban area with other local sources.

Identification of Major Risk Sources for Surface Water Pollution by Risk Indexes (RI) in the Multi-Provincial Boundary Region of the Taihu Basin, China

PubMed Central

Yao, Hong; Li, Weixin; Qian, Xin

2015-01-01

Environmental safety in multi-district boundary regions has been one of the focuses in China and is mentioned many times in the Environmental Protection Act of 2014. Five types were categorized concerning the risk sources for surface water pollution in the multi-provincial boundary region of the Taihu basin: production enterprises, waste disposal sites, chemical storage sites, agricultural non-point sources and waterway transportations. Considering the hazard of risk sources, the purification property of environmental medium and the vulnerability of risk receptors, 52 specific attributes on the risk levels of each type of risk source were screened out. Continuous piecewise linear function model, expert consultation method and fuzzy integral model were used to calculate the integrated risk indexes (RI) to characterize the risk levels of pollution sources. In the studied area, 2716 pollution sources were characterized by RI values. There were 56 high-risk sources screened out as major risk sources, accounting for about 2% of the total. The numbers of sources with high-moderate, moderate, moderate-low and low pollution risk were 376, 1059, 101 and 1124, respectively, accounting for 14%, 38%, 5% and 41% of the total. The procedure proposed could be included in the integrated risk management systems of the multi-district boundary region of the Taihu basin. It could help decision makers to identify major risk sources in the risk prevention and reduction of surface water pollution. PMID:26308032

Identification of Major Risk Sources for Surface Water Pollution by Risk Indexes (RI) in the Multi-Provincial Boundary Region of the Taihu Basin, China.

PubMed

Yao, Hong; Li, Weixin; Qian, Xin

2015-08-21

Environmental safety in multi-district boundary regions has been one of the focuses in China and is mentioned many times in the Environmental Protection Act of 2014. Five types were categorized concerning the risk sources for surface water pollution in the multi-provincial boundary region of the Taihu basin: production enterprises, waste disposal sites, chemical storage sites, agricultural non-point sources and waterway transportations. Considering the hazard of risk sources, the purification property of environmental medium and the vulnerability of risk receptors, 52 specific attributes on the risk levels of each type of risk source were screened out. Continuous piecewise linear function model, expert consultation method and fuzzy integral model were used to calculate the integrated risk indexes (RI) to characterize the risk levels of pollution sources. In the studied area, 2716 pollution sources were characterized by RI values. There were 56 high-risk sources screened out as major risk sources, accounting for about 2% of the total. The numbers of sources with high-moderate, moderate, moderate-low and low pollution risk were 376, 1059, 101 and 1124, respectively, accounting for 14%, 38%, 5% and 41% of the total. The procedure proposed could be included in the integrated risk management systems of the multi-district boundary region of the Taihu basin. It could help decision makers to identify major risk sources in the risk prevention and reduction of surface water pollution.

Adding spatial flexibility to source-receptor relationships for air quality modeling.

PubMed

Pisoni, E; Clappier, A; Degraeuwe, B; Thunis, P

2017-04-01

To cope with computing power limitations, air quality models that are used in integrated assessment applications are generally approximated by simpler expressions referred to as "source-receptor relationships (SRR)". In addition to speed, it is desirable for the SRR also to be spatially flexible (application over a wide range of situations) and to require a "light setup" (based on a limited number of full Air Quality Models - AQM simulations). But "speed", "flexibility" and "light setup" do not naturally come together and a good compromise must be ensured that preserves "accuracy", i.e. a good comparability between SRR results and AQM. In this work we further develop a SRR methodology to better capture spatial flexibility. The updated methodology is based on a cell-to-cell relationship, in which a bell-shape function links emissions to concentrations. Maintaining a cell-to-cell relationship is shown to be the key element needed to ensure spatial flexibility, while at the same time the proposed approach to link emissions and concentrations guarantees a "light set-up" phase. Validation has been repeated on different areas and domain sizes (countries, regions, province throughout Europe) for precursors reduced independently or contemporarily. All runs showed a bias around 10% between the full AQM and the SRR. This methodology allows assessing the impact on air quality of emission scenarios applied over any given area in Europe (regions, set of regions, countries), provided that a limited number of AQM simulations are performed for training.

"Silent" NMDA Synapses Enhance Motion Sensitivity in a Mature Retinal Circuit.

PubMed

Sethuramanujam, Santhosh; Yao, Xiaoyang; deRosenroll, Geoff; Briggman, Kevin L; Field, Greg D; Awatramani, Gautam B

2017-12-06

Retinal direction-selective ganglion cells (DSGCs) have the remarkable ability to encode motion over a wide range of contrasts, relying on well-coordinated excitation and inhibition (E/I). E/I is orchestrated by a diverse set of glutamatergic bipolar cells that drive DSGCs directly, as well as indirectly through feedforward GABAergic/cholinergic signals mediated by starburst amacrine cells. Determining how direction-selective responses are generated across varied stimulus conditions requires understanding how glutamate, acetylcholine, and GABA signals are precisely coordinated. Here, we use a combination of paired patch-clamp recordings, serial EM, and large-scale multi-electrode array recordings to show that a single high-sensitivity source of glutamate is processed differentially by starbursts via AMPA receptors and DSGCs via NMDA receptors. We further demonstrate how this novel synaptic arrangement enables DSGCs to encode direction robustly near threshold contrasts. Together, these results reveal a space-efficient synaptic circuit model for direction computations, in which "silent" NMDA receptors play critical roles. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of Ethylene Receptors: Ethylene-Binding Assays.

PubMed

Binder, Brad M; Schaller, G Eric

2017-01-01

Plant ethylene receptors bind ethylene with high affinity. Most of the characterization of ethylene binding to the receptors has been carried out using a radioligand-binding assay on functional receptors expressed in yeast. In this chapter, we describe methods for expressing ethylene receptors in yeast and conducting ethylene-binding assays on intact yeast and yeast membranes. The ethylene-binding assays can be modified to analyze ethylene binding to intact plants and other organisms as well as membranes isolated from any biological source.

Critical levels of atmospheric pollution: criteria and concepts for operational modelling of mercury in forest and lake ecosystems.

PubMed

Meili, Markus; Bishop, Kevin; Bringmark, Lage; Johansson, Kjell; Munthe, John; Sverdrup, Harald; de Vries, Wim

2003-03-20

Mercury (Hg) is regarded as a major environmental concern in many regions, traditionally because of high concentrations in freshwater fish, and now also because of potential toxic effects on soil microflora. The predominant source of Hg in most watersheds is atmospheric deposition, which has increased 2- to >20-fold over the past centuries. A promising approach for supporting current European efforts to limit transboundary air pollution is the development of emission-exposure-effect relationships, with the aim of determining the critical level of atmospheric pollution (CLAP, cf. critical load) causing harm or concern in sensitive elements of the environment. This requires a quantification of slow ecosystem dynamics from short-term collections of data. Aiming at an operational tool for assessing the past and future metal contamination of terrestrial and aquatic ecosystems, we present a simple and flexible modelling concept, including ways of minimizing requirements for computation and data collection, focusing on the exposure of biota in forest soils and lakes to Hg. Issues related to the complexity of Hg biogeochemistry are addressed by (1) a model design that allows independent validation of each model unit with readily available data, (2) a process- and scale-independent model formulation based on concentration ratios and transfer factors without requiring loads and mass balance, and (3) an equilibration concept that accounts for relevant dynamics in ecosystems without long-term data collection or advanced calculations. Based on data accumulated in Sweden over the past decades, we present a model to determine the CLAP-Hg from standardized values of region- or site-specific synoptic concentrations in four key matrices of boreal watersheds: precipitation (atmospheric source), large lacustrine fish (aquatic receptor and vector), organic soil layers (terrestrial receptor proxy and temporary reservoir), as well as new and old lake sediments (archives of response dynamics). Key dynamics in watersheds are accounted for by quantifying current states of equilibration in both soils and lakes based on comparison of contamination factors in sediment cores. Future steady-state concentrations in soils and fish in single watersheds or entire regions are then determined by corresponding projection of survey data. A regional-scale application to southern Sweden suggests that the response of environmental Hg levels to changes in atmospheric Hg pollution is delayed by centuries and initially not proportional among receptors (atmosphere > soils not equal sediments>fish; clearwater lakes > humic lakes). This has implications for the interpretation of common survey data as well as for the implementation of pollution control strategies. Near Hg emission sources, the pollution of organic soils and clearwater lakes deserves attention. Critical receptors, however, even in remote areas, are humic waters, in which biotic Hg levels are naturally high, most likely to increase further, and at high long-term risk of exceeding the current levels of concern:

Inverse modeling of April 2013 radioxenon detections

NASA Astrophysics Data System (ADS)

Hofman, Radek; Seibert, Petra; Philipp, Anne

2014-05-01

Significant concentrations of radioactive xenon isotopes (radioxenon) were detected by the International Monitoring System (IMS) for verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) in April 2013 in Japan. Particularly, three detections of Xe-133 made between 2013-04-07 18:00 UTC and 2013-04-09 06:00 UTC at the station JPX38 are quite notable with respect to the measurement history of the station. Our goal is to analyze the data and perform inverse modeling under different assumptions. This work is useful with respect to nuclear test monitoring as well as for the analysis of and response to nuclear emergencies. Two main scenarios will be pursued: (i) Source location is assumed to be known (DPRK test site). (ii) Source location is considered unknown. We attempt to estimate the source strength and the source strength along with its plausible location compatible with the data in scenario (i) and (ii), respectively. We are considering also the possibility of a vertically distributed source. Calculations of source-receptor sensitivity (SRS) fields and the subsequent inversion are aimed at going beyond routine calculations performed by the CTBTO. For SRS calculations, we employ the Lagrangian particle dispersion model FLEXPART with high resolution ECMWF meteorological data (grid cell sizes of 0.5, 0.25 and ca. 0.125 deg). This is important in situations where receptors or sources are located in complex terrain which is the case of the likely source of detections-the DPRK test site. SRS will be calculated with convection enabled in FLEXPART which will also increase model accuracy. In the variational inversion procedure attention will be paid not only to all significant detections and their uncertainties but also to non-detections which can have a large impact on inversion quality. We try to develop and implement an objective algorithm for inclusion of relevant data where samples from temporal and spatial vicinity of significant detections are added in an iterative manner and the inversion is recalculated in each iteration. This procedure should gradually narrow down the set of hypotheses on the source term, where the source term is here understood as an emission in both spatial and temporal domains. Especially in scenario (ii) we expect a strong impact of non-detections for the reduction of possible solutions. For these and also other purposes like statistical quantification of typical background values, measurements from all IMS noble gas stations north of 30 deg S for a period from January to June 2013 were extracted from vDEC platform. We would like to acknowledge the Preparatory Commission for the CTBTO for kindly providing limited access to the IMS data. This work contains only opinions of the authors, which can not in any case establish legal engagement of the Provisional Technical Secretariat of the CTBTO. This work is partially financed through the project "PREPARE: Innovative integrated tools and platforms for radiological emergency preparedness and post-accident response in Europe" (FP7, Grant 323287).

Source apportionment of PAHs and n-alkanes bound to PM1 collected near the Venice highway.

PubMed

Valotto, Gabrio; Rampazzo, Giancarlo; Gonella, Francesco; Formenton, Gianni; Ficotto, Silvia; Giraldo, Giorgia

2017-04-01

n-Alkanes and polycyclic aromatic hydrocarbons (PAHs) bound to atmospheric particulate matter (PM 1 ) were investigated in a traffic site located in an urban area of Venice Province (Eastern Po Valley, Italy) during the cold season. Considering the critical situation affecting the Veneto Region concerning the atmospheric pollution and the general lack of information on PM 1 composition and emission in this area, this experimental study aims at determining the source profile, their relative contributions and the dispersion of finer particles. Four sources were identified and quantified using the Positive Matrix Factorization receptor model: (1) mixed combustions related to the residential activities, (2) agricultural biomass burning in addition to the resuspension of anthropogenic and natural debris carried by the wind, (3) gasoline and (4) diesel traffic-related combustions. The role of local atmospheric circulation was also investigated to identify the pollutant sources. Copyright © 2016. Published by Elsevier B.V.

Evaluation of the Community Multi-scale Air Quality (CMAQ) ...

EPA Pesticide Factsheets

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In the fall of 2015, CMAQ version 5.1 was released. This new version of CMAQ will contain important bug fixes to several issues that were identified in CMAQv5.0.2 and additionally include updates to other portions of the code. Several annual, and numerous episodic, CMAQv5.1 simulations were performed to assess the impact of these improvements on the model results. These results will be presented, along with a base evaluation of the performance of the CMAQv5.1 modeling system against available surface and upper-air measurements available during the time period simulated. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, proces

Source Attribution of Tropospheric Ozone using a Global Model

NASA Astrophysics Data System (ADS)

Coates, J.; Lupascu, A.; Butler, T. M.; Zhu, S.

2016-12-01

Tropospheric ozone is both a short-lived climate forcing pollutant and a radiatively active greenhouse gas. Ozone is not directly emitted into the troposphere but photochemically produced from chemical reactions involving nitrogen oxides (NOx) and volatile organic compounds (VOCs). Emissions of ozone precursors (NOx and VOCs) have both natural and anthropogenic sources and may be transported away from their sources to produce ozone downwind. Also, transport of ozone from the stratosphere into the troposphere also influences tropospheric ozone levels in some regions. Attributing ozone concentrations to the contributions from different sources would indicate the effects of locally emitted or transported precursors on ozone levels in specific regions. This information could be used to inform the emission reduction strategies of ozone precursors by indicating which emission sources could be targeted for effective reductions thus reducing the burden of ozone pollution. We use a "tagging" approach within the CESM global model to attribute ozone levels to their source emissions. We use different tags to quantify the impact from natural (soils, lightning, stratospheric transport) and anthropogenic (aircraft, biomass burning) sources of NOx and VOCs (including methane) on ozone levels. These source sectors of different global regions are assigned based on the global emissions specified by HTAPv2.2. Using these results, we develop a transboundary source-receptor relationship of ozone concentration to its precursor emission regions. Additionally, the transport of ozone precursors from regional anthropogenic sources is analysed to illustrate the extent to which mitigation strategies of regional emissions aid in mitigating global ozone levels.

Airborne exposure patterns from a passenger source in aircraft cabins

PubMed Central

Bennett, James S.; Jones, Byron W.; Hosni, Mohammad H.; Zhang, Yuanhui; Topmiller, Jennifer L.; Dietrich, Watts L.

2015-01-01

Airflow is a critical factor that influences air quality, airborne contaminant distribution, and disease transmission in commercial airliner cabins. The general aircraft-cabin air-contaminant transport effect model seeks to build exposure-spatial relationships between contaminant sources and receptors, quantify the uncertainty, and provide a platform for incorporation of data from a variety of studies. Knowledge of infection risk to flight crews and passengers is needed to form a coherent response to an unfolding epidemic, and infection risk may have an airborne pathogen exposure component. The general aircraf-tcabin air-contaminant transport effect model was applied to datasets from the University of Illinois and Kansas State University and also to case study information from a flight with probable severe acute respiratory syndrome transmission. Data were fit to regression curves, where the dependent variable was contaminant concentration (normalized for source strength and ventilation rate), and the independent variable was distance between source and measurement locations. The data-driven model showed exposure to viable small droplets and post-evaporation nuclei at a source distance of several rows in a mock-up of a twin-aisle airliner with seven seats per row. Similar behavior was observed in tracer gas, particle experiments, and flight infection data for severe acute respiratory syndrome. The study supports the airborne pathway as part of the matrix of possible disease transmission modes in aircraft cabins. PMID:26526769

Design, synthesis and biological evaluation of a bivalent micro opiate and adenosine A1 receptor antagonist.

PubMed

Mathew, Smitha C; Ghosh, Nandita; By, Youlet; Berthault, Aurélie; Virolleaud, Marie-Alice; Carrega, Louis; Chouraqui, Gaëlle; Commeiras, Laurent; Condo, Jocelyne; Attolini, Mireille; Gaudel-Siri, Anouk; Ruf, Jean; Parrain, Jean-Luc; Rodriguez, Jean; Guieu, Régis

2009-12-01

The cross talk between different membrane receptors is the source of increasing research. We designed and synthesized a new hetero-bivalent ligand that has antagonist properties on both A(1) adenosine and mu opiate receptors with a K(i) of 0.8+/-0.05 and 0.7+/-0.03 microM, respectively. This hybrid molecule increases cAMP production in cells that over express the mu receptor as well as those over expressing the A(1) adenosine receptor and reverses the antalgic effects of mu and A(1) adenosine receptor agonists in animals.

Catchment-scale evaluation of environmental regulations in the agricultural sector in Ireland (Invited)

NASA Astrophysics Data System (ADS)

Melland, A. R.; Jordan, P.; Mellander, P.; Wall, D. J.; Buckley, C.; Mechan, S.; Shortle, G.

2010-12-01

The European Union (EU) Nitrates Directive regulations in Ireland limits the use of agricultural fertilisers to agronomic optima and aims to minimise surplus phosphorus (P) and nitrogen (N) losses to the aquatic environment. The legislated measures include limits on nutrient application according to soil P status, crop type and livestock intensity and restricts chemical and organic fertiliser spreading and ploughing to periods of the year with typically lower exposure of nutrients to runoff and leaching. These agricultural policies are being evaluated in an Agricultural Catchments Programme in six representative catchments dominated by moderate to high intensity grassland and arable enterprises across Ireland (Fealy et al., 2010). An experimental programme has been established to provide a baseline of farm nutrient management and water body quality during the early years of the measures and to provide estimates of trajectories towards (or otherwise) water quality targets. A ‘nutrient transfer continuum’ from source, through pathways, to delivery and impact in a water body receptor describes the different phases of diffuse pollution and is being used as a framework for evaluation. Compliance with Irish standards at different levels of the continuum is being evaluated and demonstrative studies are being conducted to provide evidence of linkages between source and delivery to validate conceptual models of P and N transfers in time and space in each catchment. Source compliance is being evaluated through census soil testing and a survey of nutrient management practice and farmyard infrastructure. Mobilisation and pathways of nutrient transfers do not have chemical standards except where a groundwater body acts as both a receptor and a pathway. To demonstrate these linkages, however, representative groundwater pathways are being monitored through piezometer, chemical end-member and tracer studies, and surface water pathways are being evaluated through subcatchment storm sampling and terrain analysis modelling. Delivery and impact compliance are being assessed against EU and Irish chemical and biological standards for water body receptors. Trajectories of change will be considered. For example the time for current policies to have an impact on biological water quality may be dependant on soil P status decline rates, mobilisation rates for P stores in waterways and rates of ecological response to change in the trophic status of water body receptors. The attitudes of farmer stakeholders towards the measures and the economic impacts of investment in infrastructure and changed management are also being evaluated. Some preliminary data are presented including scenarios that suggest a lack of connectivity between farm source and water quality compliance standards. Fealy, R.M., Buckley, C., Mechan, S., Melland, A., Mellander, P.-E., Shortle, G., Wall, D. and Jordan, P. 2010. The Irish Agricultural Catchments Programme: catchment selection using spatial multi-criteria decision analysis. Soil Use and Management.23:225-236

Multiple site receptor modeling with a minimal spanning tree combined with a Kohonen neural network

NASA Astrophysics Data System (ADS)

Hopke, Philip K.

1999-12-01

A combination of two pattern recognition methods has been developed that allows the generation of geographical emission maps form multivariate environmental data. In such a projection into a visually interpretable subspace by a Kohonen Self-Organizing Feature Map, the topology of the higher dimensional variables space can be preserved, but parts of the information about the correct neighborhood among the sample vectors will be lost. This can partly be compensated for by an additional projection of Prim's Minimal Spanning Tree into the trained neural network. This new environmental receptor modeling technique has been adapted for multiple sampling sites. The behavior of the method has been studied using simulated data. Subsequently, the method has been applied to mapping data sets from the Southern California Air Quality Study. The projection of a 17 chemical variables measured at up to 8 sampling sites provided a 2D, visually interpretable, geometrically reasonable arrangement of air pollution source sin the South Coast Air Basin.

VOCs emission rate estimate for complicated industrial area source using an inverse-dispersion calculation method: A case study on a petroleum refinery in Northern China.

PubMed

Wei, Wei; Lv, Zhaofeng; Yang, Gan; Cheng, Shuiyuan; Li, Yue; Wang, Litao

2016-11-01

This study aimed to apply an inverse-dispersion calculation method (IDM) to estimate the emission rate of volatile organic compounds (VOCs) for the complicated industrial area sources, through a case study on a petroleum refinery in Northern China. The IDM was composed of on-site monitoring of ambient VOCs concentrations and meteorological parameters around the source, calculation of the relationship coefficient γ between the source's emission rate and the ambient VOCs concentration by the ISC3 model, and estimation of the actual VOCs emission rate from the source. Targeting the studied refinery, 10 tests and 8 tests were respectively conducted in March and in June of 2014. The monitoring showed large differences in VOCs concentrations between background and downwind receptors, reaching 59.7 ppbv in March and 248.6 ppbv in June, on average. The VOCs increases at receptors mainly consisted of ethane (3.1%-22.6%), propane (3.8%-11.3%), isobutane (8.5%-10.2%), n-butane (9.9%-13.2%), isopentane (6.1%-12.9%), n-pentane (5.1%-9.7%), propylene (6.1-11.1%) and 1-butylene (1.6%-5.4%). The chemical composition of the VOCs increases in this field monitoring was similar to that of VOCs emissions from China's refineries reported, which revealed that the ambient VOCs increases were predominantly contributed by this refinery. So, we used the ISC3 model to create the relationship coefficient γ for each receptor of each test. In result, the monthly VOCs emissions from this refinery were calculated to be 183.5 ± 89.0 ton in March and 538.3 ± 281.0 ton in June. The estimate in June was greatly higher than in March, chiefly because the higher environmental temperature in summer produced more VOCs emissions from evaporation and fugitive process of the refinery. Finally, the VOCs emission factors (g VOCs/kg crude oil refined) of 0.73 ± 0.34 (in March) and 2.15 ± 1.12 (in June) were deduced for this refinery, being in the same order with previous direct-measurement results (1.08-2.65 g VOCs/kg crude oil refined). An inverse-dispersion calculation method was applied to estimate VOCs emission rate for a petroleum refinery, being 183.5 ton/month (March) and 538.3 ton/month (June). Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessment of a robust model protocol with accelerated throughput for a human recombinant full length estrogen receptor-alpha binding assay: protocol optimization and intralaboratory assay performance as initial steps towards validation.

PubMed

Freyberger, Alexius; Wilson, Vickie; Weimer, Marc; Tan, Shirlee; Tran, Hoai-Son; Ahr, Hans-Jürgen

2010-08-01

Despite about two decades of research in the field of endocrine active compounds, still no validated human recombinant (hr) estrogen receptor-alpha (ERalpha) binding assay is available, although hr-ERalpha is available from several sources. In a joint effort, US EPA and Bayer Schering Pharma with funding from the EU-sponsored 6th framework project, ReProTect, developed a model protocol for such a binding assay. Important features of this assay are the use of a full length hr-ERalpha and performance in a 96-well plate format. A full length hr-ERalpha was chosen, as it was considered to provide the most accurate and human-relevant results, whereas truncated receptors could perform differently. Besides three reference compounds [17beta-estradiol, norethynodrel, dibutylphthalate] nine test compounds with different affinities for the ERalpha [diethylstilbestrol (DES), ethynylestradiol, meso-hexestrol, equol, genistein, o,p'-DDT, nonylphenol, n-butylparaben, and corticosterone] were used to explore the performance of the assay. Three independent experiments per compound were performed on different days, and dilutions of test compounds from deep-frozen stocks, solutions of radiolabeled ligand and receptor preparation were freshly prepared for each experiment. The ERalpha binding properties of reference and test compounds were well detected. As expected dibutylphthalate and corticosterone were non-binders in this assay. In terms of the relative ranking of binding affinities, there was good agreement with published data obtained from experiments using a human recombinant ERalpha ligand binding domain. Irrespective of the chemical nature of the compound, individual IC(50)-values for a given compound varied by not more than a factor of 2.5. Our data demonstrate that the assay was robust and reliably ranked compounds with strong, weak, and no affinity for the ERalpha with high accuracy. It avoids the manipulation and use of animals, i.e., the preparation of uterine cytosol as receptor source from ovariectomized rats, as a recombinant protein is used and thus contributes to the 3R concept (reduce, replace, and refine). Furthermore, in contrast to other assays, this assay could be adjusted to an intermediate/high throughput format. On the whole, this assay is a promising candidate for further validation. Copyright 2010 Elsevier Inc. All rights reserved.

An unusual case of ectopic ACTH syndrome.

PubMed

Willhauck, M J; Pöpperl, G; Rachinger, W; Giese, A; Auernhammer, C J; Spitzweg, C

2012-02-01

Ectopic ACTH-syndrome is a rare cause of Cushing's disease. Despite extensive diagnostic procedures the source of ACTH secretion often remains occult. This case describes a 45-year old woman with an ectopic Cushing's syndrome. Extensive imaging procedures including CT scan of chest and abdomen, octreotide scan and MRI of the chest and pituitary did not reveal the source of ACTH secretion. In consideration of an occult source of ACTH secretion we started a therapeutic trial with cabergoline (0.5 mg/d), a dopamine receptor agonist, which has been shown to be effective in ectopic Cushing's syndrome. 2 months after cabergoline treatment had been initiated, ACTH and cortisol levels normalized in association with significant improvement of the clinical symptoms. During follow-up a [(68)Ga-DOTA-dPhe(1), Tyr(3)]-octreotate ([(68)Ga-DOTA]-TATE) PET-CT was performed revealing a somatostatin receptor positive lesion in the right sphenoidal sinus suggesting the source of ACTH secretion. The patient was cured by transnasal resection of the polypoid lesion, which was immunohistochemically characterized as an ACTH-positive neuroendocrine tumor. This case report demonstrates the management of ectopic ACTH-syndrome by molecularly -targeted therapy with dopamine receptor -agonists as well as improved detection of the ectopic ACTH source by novel imaging modalities, such as [(68)Ga-DOTA]-TATE PET specifically targeting somatostatin receptor subtype-2 with high affinity. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart · New York.

Seasonal and spatial variation in reactive oxygen species activity of quasi-ultrafine particles (PM0.25) in the Los Angeles metropolitan area and its association with chemical composition

NASA Astrophysics Data System (ADS)

Saffari, Arian; Daher, Nancy; Shafer, Martin M.; Schauer, James J.; Sioutas, Constantinos

2013-11-01

Seasonal and spatial variation in redox activity of quasi-ultrafine particles (PM0.25) and its association with chemical species was investigated at 9 distinct sampling sites across the Los Angeles metropolitan area. Biologically reactive oxygen species (ROS) assay (generation of ROS in rat alveolar macrophage cells) was employed in order to assess the redox activity of PM0.25 samples. Seasonally, fall and summer displayed higher volume-based ROS activity (i.e. ROS activity per unit volume of air) compared to spring and winter. ROS levels were generally higher at near source and urban background sites compared to rural receptor locations, except for summer when comparable ROS activity was observed at the rural receptor sites. Univariate linear regression analysis indicated association (R > 0.7) between ROS activity and organic carbon (OC), water soluble organic carbon (WSOC) and water soluble transition metals (including Fe, V, Cr, Cd, Ni, Zn, Mn, Pb and Cu). A multivariate regression method was also used to obtain a model to predict the ROS activity of PM0.25, based on its water-soluble components. The most important species associated with ROS were Cu and La at the source site of Long Beach, and Fe and V at urban Los Angeles sites. These metals are tracers of road dust enriched with vehicular emissions (Fe and Cu) and residual oil combustion (V and La). At Riverside, a rural receptor location, WSOC and Ni (tracers of secondary organic aerosol and metal plating, respectively) were the dominant species driving the ROS activity. At Long Beach, the multivariate model was able to reconstruct the ROS activity with a high coefficient of determination (R2 = 0.82). For Los Angeles and Riverside, however, the regression models could only explain 63% and 68% of the ROS activity, respectively. The unexplained portion of the measured ROS activity is likely attributed to the nature of organic species not captured in the organic carbon (OC) measurement as well as non-linear effects, which were not included in our linear model.

Molecular modeling study of the differential ligand-receptor interaction at the μ, δ and κ opioid receptors

NASA Astrophysics Data System (ADS)

Filizola, Marta; Carteni-Farina, Maria; Perez, Juan J.

1999-07-01

3D models of the opioid receptors μ, δ and κ were constructed using BUNDLE, an in-house program to build de novo models of G-protein coupled receptors at the atomic level. Once the three opioid receptors were constructed and before any energy refinement, models were assessed for their compatibility with the results available from point-site mutations carried out on these receptors. In a subsequent step, three selective antagonists to each of three receptors (naltrindole, naltrexone and nor-binaltorphamine) were docked onto each of the three receptors and subsequently energy minimized. The nine resulting complexes were checked for their ability to explain known results of structure-activity studies. Once the models were validated, analysis of the distances between different residues of the receptors and the ligands were computed. This analysis permitted us to identify key residues tentatively involved in direct interaction with the ligand.

Binding modes of dihydroquinoxalinones in a homology model of bradykinin receptor 1.

PubMed

Ha, Sookhee N; Hey, Pat J; Ransom, Rick W; Harrell, C Meacham; Murphy, Kathryn L; Chang, Ray; Chen, Tsing-Bau; Su, Dai-Shi; Markowitz, M Kristine; Bock, Mark G; Freidinger, Roger M; Hess, Fred J

2005-05-27

We report the first homology model of human bradykinin receptor B1 generated from the crystal structure of bovine rhodopsin as a template. Using an automated docking procedure, two B1 receptor antagonists of the dihydroquinoxalinone structural class were docked into the receptor model. Site-directed mutagenesis data of the amino acid residues in TM1, TM3, TM6, and TM7 were incorporated to place the compounds in the binding site of the homology model of the human B1 bradykinin receptor. The best pose in agreement with the mutation data was selected for detailed study of the receptor-antagonist interaction. To test the model, the calculated antagonist-receptor binding energy was correlated with the experimentally measured binding affinity (K(i)) for nine dihydroquinoxalinone analogs. The model was used to gain insight into the molecular mechanism for receptor function and to optimize the dihydroquinoxalinone analogs.

Source apportionment of atmospheric bulk deposition in the Belgrade urban area using Positive Matrix factorization

NASA Astrophysics Data System (ADS)

Tasić, M.; Mijić, Z.; Rajšić, S.; Stojić, A.; Radenković, M.; Joksić, J.

2009-04-01

The primary objective of the present study was to assess anthropogenic impacts of heavy metals to the environment by determination of total atmospheric deposition of heavy metals. Atmospheric depositions (wet + dry) were collected monthly, from June 2002 to December 2006, at three urban locations in Belgrade, using bulk deposition samplers. Concentrations of Fe, Al, Pb, Zn, Cu, Ni, Mn, Cr, V, As and Cd were analyzed using atomic absorption spectrometry. Based upon these results, the study attempted to examine elemental associations in atmospheric deposition and to elucidate the potential sources of heavy metal contaminants in the region by the use of multivariate receptor model Positive Matrix Factorization (PMF).

Object localization through the lateral line system of fish: theory and experiment.

PubMed

Goulet, Julie; Engelmann, Jacob; Chagnaud, Boris P; Franosch, Jan-Moritz P; Suttner, Maria D; van Hemmen, J Leo

2008-01-01

Fish acquire information about their aquatic environment by means of their mechanosensory lateral-line system. This system consists of superficial and canal neuromasts that sense perturbations in the water surrounding them. Based on a hydrodynamic model presented here, we propose a mechanism through which fish can localize the source of these perturbations. In doing so we include the curvature of the fish body, a realistic lateral line canal inter-pore distance for the lateral-line canals, and the surface boundary layer. Using our model to explore receptor behavior based on experimental data of responses to dipole stimuli we suggest that superficial and canal neuromasts employ the same mechanism, hence provide the same type of input to the central nervous system. The analytical predictions agree well with spiking responses recorded experimentally from primary lateral-line nerve fibers. From this, and taking into account the central organization of the lateral-line system, we present a simple biophysical model for determining the distance to a source.

Effect of interior door position on room-to-room differences in residential pollutant concentrations after short-term releases

NASA Astrophysics Data System (ADS)

Ferro, Andrea R.; Klepeis, Neil E.; Ott, Wayne R.; Nazaroff, William W.; Hildemann, Lynn M.; Switzer, Paul

Residential interior door positions influence the pollutant concentrations that result from short-term indoor sources, such as cigarettes, candles, and incense. To elucidate this influence, we reviewed past studies and conducted new experiments in three residences: a single-story 714 m 3 ranch-style house, a 510 m 3 two-story split-level house, and a 200 m 3 two-story house. During the experiments, we released sulfur hexafluoride or carbon monoxide tracer gas over short periods (≤30 min) and measured concentrations in the source room and at least one other (receptor) room for various interior door opening positions. We found that closing a door between rooms effectively prevented transport of air pollutants, reducing the average concentration in the receptor room relative to the source room by 57-100% over exposure periods of 1-8 h. When intervening doors were partially or fully open, the reduction in average concentrations ranged from 3% to 99%, varying as a function of door opening width and the distance between source and receptor rooms.

The project MOHAVE tracer study: study design, data quality, and overview of results

NASA Astrophysics Data System (ADS)

Green, Mark C.

In the winter and summer of 1992, atmospheric tracer studies were conducted in support of project MOHAVE, a visibility study in the southwestern United States. The primary goal of project MOHAVE is to determine the effects of the Mohave power plant and other sources upon visibility at Grand Canyon National Park. Perfluorocarbon tracers (PFTs) were released from the Mohave power plant and other locations and monitored at about 30 sites. The tracer data are being used for source attribution analysis and for evaluation of transport and dispersion models and receptor models. Collocated measurements showed the tracer data to be of high quality and suitable for source attribution analysis and model evaluation. The results showed strong influences of channeling by the Colorado River canyon during both winter and summer. Flow from the Mohave power plant was usually to the south, away from the Grand Canyon in winter and to the northeast, toward the Grand Canyon in summer. Tracer released at Lake Powell in winter was found to often travel downstream through the entire length of the Grand Canyon. Data from summer tracer releases in southern California demonstrated the existence of a convergence zone in the western Mohave Desert.

Three multimedia models used at hazardous and radioactive waste sites

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

Moskowitz, P.D.; Pardi, R.; Fthenakis, V.M.

1996-02-01

Multimedia models are used commonly in the initial phases of the remediation process where technical interest is focused on determining the relative importance of various exposure pathways. This report provides an approach for evaluating and critically reviewing the capabilities of multimedia models. This study focused on three specific models MEPAS Version 3.0, MMSOILS Version 2.2, and PRESTO-EPA-CPG Version 2.0. These models evaluate the transport and fate of contaminants from source to receptor through more than a single pathway. The presence of radioactive and mixed wastes at a site poses special problems. Hence, in this report, restrictions associated with the selectionmore » and application of multimedia models for sites contaminated with radioactive and mixed wastes are highlighted. This report begins with a brief introduction to the concept of multimedia modeling, followed by an overview of the three models. The remaining chapters present more technical discussions of the issues associated with each compartment and their direct application to the specific models. In these analyses, the following components are discussed: source term; air transport; ground water transport; overland flow, runoff, and surface water transport; food chain modeling; exposure assessment; dosimetry/risk assessment; uncertainty; default parameters. The report concludes with a description of evolving updates to the model; these descriptions were provided by the model developers.« less

Dimer-based model for heptaspanning membrane receptors.

PubMed

Franco, Rafael; Casadó, Vicent; Mallol, Josefa; Ferré, Sergi; Fuxe, Kjell; Cortés, Antonio; Ciruela, Francisco; Lluis, Carmen; Canela, Enric I

2005-07-01

The existence of intramembrane receptor-receptor interactions for heptaspanning membrane receptors is now fully accepted, but a model considering dimers as the basic unit that binds to two ligand molecules is lacking. Here, we propose a two-state-dimer model in which the ligand-induced conformational changes from one component of the dimer are communicated to the other. Our model predicts cooperativity in binding, which is relevant because the other current models fail to address this phenomenon satisfactorily. Our two-state-dimer model also predicts the variety of responses elicited by full or partial agonists, neutral antagonists and inverse agonists. This model can aid our understanding of the operation of heptaspanning receptors and receptor channels, and, potentially, be important for improving the treatment of cardiovascular, neurological and neuropsychyatric diseases.

Quantifying sources of black carbon in western North America using observationally based analysis and an emission tagging technique in the Community Atmosphere Model

DOE PAGES

Zhang, Rudong; Wang, Hailong; Hegg, D. A.; ...

2015-11-18

The Community Atmosphere Model (CAM5), equipped with a technique to tag black carbon (BC) emissions by source regions and types, has been employed to establish source–receptor relationships for atmospheric BC and its deposition to snow over western North America. The CAM5 simulation was conducted with meteorological fields constrained by reanalysis for year 2013 when measurements of BC in both near-surface air and snow are available for model evaluation. We find that CAM5 has a significant low bias in predicted mixing ratios of BC in snow but only a small low bias in predicted atmospheric concentrations over northwestern USA and westernmore » Canada. Even with a strong low bias in snow mixing ratios, radiative transfer calculations show that the BC-in-snow darkening effect is substantially larger than the BC dimming effect at the surface by atmospheric BC. Local sources contribute more to near-surface atmospheric BC and to deposition than distant sources, while the latter are more important in the middle and upper troposphere where wet removal is relatively weak. Fossil fuel (FF) is the dominant source type for total column BC burden over the two regions. FF is also the dominant local source type for BC column burden, deposition, and near-surface BC, while for all distant source regions combined the contribution of biomass/biofuel (BB) is larger than FF. An observationally based positive matrix factorization (PMF) analysis of the snow-impurity chemistry is conducted to quantitatively evaluate the CAM5 BC source-type attribution. Furthermore, while CAM5 is qualitatively consistent with the PMF analysis with respect to partitioning of BC originating from BB and FF emissions, it significantly underestimates the relative contribution of BB. In addition to a possible low bias in BB emissions used in the simulation, the model is likely missing a significant source of snow darkening from local soil found in the observations.« less

Source tagging modeling study of regional contributions to acid rain in summer over Liaoning Province, Northeastern China.

PubMed

Gbaguidi, Alex E; Wang, Zifa; Wang, Wei; Yang, Ting; Chen, Huan-Sheng

2018-04-01

Strong acid rain was recently observed over Northeastern China, particularly in summer in Liaoning Province where alkaline dust largely neutralized acids in the past. This seems to be related to the regional transboundary pollution and poses new challenges in acid rain control scheme in China. In order to delve into the regional transport impact, and quantify its potential contributions to such an "eruption" of acid rain over Liaoning, this paper employs an online source tagging model in coupling with the Nested Air Quality Prediction Modeling System (NAQPMS). Validation of predictions shows the model capability in reproducing key meteorological and chemical features. Acid concentration over Liaoning is more pronounced in August (average of 0.087 mg/m 3 ) with strong pollutant import from regional sources against significant depletion of basic species. Seasonal mean contributions from regional sources are assessed at both lower and upper boundary layers to elucidate the main pathways of the impact of regional sources on acid concentration over Liaoning. At the upper layer (1.2 km), regional sources contribute to acid concentration over Liaoning by 67%, mainly from Shandong (16%), Hebei (13%), Tianjin (11%) and Korean Peninsula (9%). Identified main city-receptors in Liaoning are Dandong, Dalian, Chaohu, Yingkou, Liaoyang, Jinfu, Shengyang, Panjin, Tieling, Benxi, Anshan and Fushun. At lower layer (120 m) where Liaoning local contribution is dominant (58%), regional sources account for 39% in acid concentration. However, inter-municipal acid exchanges are prominent at this layer and many cities in Liaoning are revealed as important sources of local acid production. Seasonal acid contribution average within 1.2 km-120 m attains 55%, suggesting dominance of vertical pollutant transport from regional sources towards lower boundary layer in Liaoning. As direct environmental implication, this study provides policy makers with a perspective of regulating the regional transboundary environmental impact assessment in China with application to acid rain control. Copyright © 2018 Elsevier Ltd. All rights reserved.

Homology Models of Melatonin Receptors: Challenges and Recent Advances

PubMed Central

Pala, Daniele; Lodola, Alessio; Bedini, Annalida; Spadoni, Gilberto; Rivara, Silvia

2013-01-01

Melatonin exerts many of its actions through the activation of two G protein-coupled receptors (GPCRs), named MT1 and MT2. So far, a number of different MT1 and MT2 receptor homology models, built either from the prototypic structure of rhodopsin or from recently solved X-ray structures of druggable GPCRs, have been proposed. These receptor models differ in the binding modes hypothesized for melatonin and melatonergic ligands, with distinct patterns of ligand-receptor interactions and putative bioactive conformations of ligands. The receptor models will be described, and they will be discussed in light of the available information from mutagenesis experiments and ligand-based pharmacophore models. The ability of these ligand-receptor complexes to rationalize structure-activity relationships of known series of melatonergic compounds will be commented upon. PMID:23584026

A conservative evaluation of the transport of TCE from the confined aquifer beneath J-Field, Aberdeen Proving Ground, Maryland, to a hypothetical receptor.

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

Martino, L. E.; Patton, T. L.; Quinn, J. J.

1999-01-04

Past disposal operations at the Toxic Burn Pits (TBP) area of J-Field, Aberdeen Proving Ground, Maryland, have resulted in volatile organic compound (VOC) contamination of groundwater. Although the contaminant concentration is highest in the surficial aquifer, VOCs are also present in the confined aquifer, which is approximately 30 m (100 ft) deep at the TBP area. This study focuses on the confined aquifer, a sandy valley-fill Pleistocene unit in a paleochannel cut into Cretaceous sands and clays. This report documents the locations of the region's pumping wells, which are over 6 km (4 mi) away from the TBP. The distancesmore » to the pumping wells and the complex stratigraphy limit the likelihood of any contamination reaching a receptor well. Nonetheless, a worst-case scenario was evaluated with a model designed to simulate the transport of trichloroethylene (TCE), the main chemical of concern, from the confined aquifer beneath the TBP along a hypothetical, direct flowpath to a receptor well. The model was designed to be highly conservative (i.e., based on assumptions that promote the transport of contaminants). In addition to the direct flowpath assumption, the model uses the lowest literature value for the biodegradation rate of TCE, a low degree of sorption, a continuous-strength source, and a high flow velocity. Results from this conservative evaluation indicate that the simulated contaminant plume extends into areas offshore from J-Field, but decays before reaching a receptor well. The 5-ppb contour, for example, travels approximately 5 km (3 mi) before stagnating. Recent field analyses have documented that complete biodegradation of TCE to ethene and ethane is occurring directly below the TBP; therefore, the likelihood of TCE or its daughter products reaching a pumping well appears negligible. Thus, the model results may be useful in proposing either a no action or a natural attenuation alternative for the confined aquifer.« less

Vulnerability Assessment of Groundwater Resources by Nutrient Source Apportionment to Individual Groundwater Wells: A Case Study in North Carolina

NASA Astrophysics Data System (ADS)

Ayub, R.; Obenour, D. R.; Keyworth, A. J.; Genereux, D. P.; Mahinthakumar, K.

2016-12-01

Groundwater contamination by nutrients (nitrogen and phosphorus) is a major concern in water table aquifers that underlie agricultural areas in the mid-Atlantic Coastal Plain of the United States. High nutrient concentrations leaching into shallow groundwater can lead to human health problems and eutrophication of receiving surface waters. Liquid manure from concentrated animal feeding operations (CAFOs) stored in open-air lagoons and applied to spray fields can be a significant source of nutrients to groundwater, along with septic waste. In this study, we developed a model-based methodology for source apportionment and vulnerability assessment using sparse groundwater quality sampling measurements for Duplin County, North Carolina (NC), obtained by the NC Department of Environmental Quality (NC DEQ). This model provides information relevant to management by estimating the nutrient transport through the aquifer from different sources and addressing the uncertainty of nutrient contaminant propagation. First, the zones of influence (dependent on nutrient pathways) for individual groundwater monitoring wells were identified using a two-dimensional vertically averaged groundwater flow and transport model incorporating geologic uncertainty for the surficial aquifer system. A multiple linear regression approach is then applied to estimate the contribution weights for different nutrient source types using the nutrient measurements from monitoring wells and the potential sources within each zone of influence. Using the source contribution weights and their uncertainty, a probabilistic vulnerability assessment of the study area due to nutrient contamination is performed. Knowledge of the contribution of different nutrient sources to contamination at receptor locations (e.g., private wells, municipal wells, stream beds etc.) will be helpful in planning and implementation of appropriate mitigation measures.

Non-methane hydrocarbons source apportionment at different sites in Mexico City during 2002-2003

NASA Astrophysics Data System (ADS)

Vega, E.; Sanchez, G.; Molina, L.

2007-09-01

The atmospheric concentrations of a variety of non-methane hydrocarbons (NMHC) collected at different sites, representing urban and rural environments within Mexico City Metropolitan Area (MCMA) during 1997, 2002 and 2003 field campaigns, were compared and used as an input for the Chemical Mass Balance (CMB) receptor model to determine the source contribution of NMHC to the atmosphere. A common feature at all the locations was the dominance of alkenes (59%), aromatics (16%) and olefins (9%) in the average NMHC burden. At the urban sites the interquartile range of NMHC concentrations showed stabilization over this period with a slight increase in the concentrations of propane and butanes in the southwest site of the MCMA in 2003 due to the increased use of liquefied petroleum gas (LPG). The receptor model CMB version 8.0 was used to apportion the NMHC sources at six locations within the MCMA, representing the heavily industrialized, commercial, residential and rural areas. For the 2003 field campaign, the contribution of vehicular emissions dominated the NMHC concentrations (19.7%±7.1% for gasoline vehicles and 35.4%±17.5% for diesel vehicles) followed by the emissions of marketing and handling of LPG (29.9%±8.0%). The NMHC concentrations showed a weekly cycle with the highest levels towards the end of the week and lowest at weekend and beginning of the week, suggesting that both emissions and accumulations process play a key role in building up NMHC levels. The toluene to benzene ratio was used to determine photochemical ageing of the air samples during the 2003 field campaign. The database was divided into periods with similar wind circulation pattern; the results suggest that ageing process within the MCMA is generally suppressed by the amount of fresh emissions.

Characterization and source apportionment of particulate matter < or = 2.5 micrometer in Sumatra, Indonesia, during a recent peat fire episode.

PubMed

See, Siao Wei; Balasubramanian, Rajasekhar; Rianawati, Elisabeth; Karthikeyan, Sathrugnan; Streets, David G

2007-05-15

An intensive field study was conducted in Sumatra, Indonesia, during a peat fire episode to investigate the physical and chemical characteristics of particulate emissions in peat smoke and to provide necessary data for source-receptor analyses. Ambient air sampling was carried out at three different sites located at varying distances from the peatfires to determine changes in mass and number concentrations of PM2.5 and its chemical composition (carbonaceous and nitrogenous materials, polycyclic aromatic hydrocarbons, water-soluble inorganic and organic ions, and total and water-soluble metals). The three sites represent a rural site directly affected by the local peat combustion, a semirural site, and an urban site situated downwind of the peat fires. The mass concentration of PM2.5 and the number concentration of airborne particles were as high as 1600 microg/m3 and 1.7 x 10(5) cm(-3), respectively, in the vicinity of peat fires. The major components of PM2.5 in peat smoke haze were carbonaceous particles, particularly organic carbon, NO3-, and SO4(2-), while the less abundant constituents included ions such as NH4+, NO2-, Na+, K+, organic acids, and metals such as Al, Fe, and Ti. Source apportionment by chemical mass balance receptor modeling indicates that peat smoke can travel long distances and significantly affect the air quality at locations downwind.

Characterising the pollutant ventilation characteristics of street canyons using the tracer age and age spectrum

NASA Astrophysics Data System (ADS)

Lo, K. W.; Ngan, K.

2015-12-01

The age of air, which measures the time elapsed between the emission of a chemical constituent and its arrival at a receptor location, has many applications in urban air quality. Typically it has been estimated for special cases, e.g. the local mean age of air for a spatially homogeneous source. An alternative approach uses the response to a point source to determine the distribution of transit times or tracer ages connecting the source and receptor. The distribution (age spectrum) and first moment (mean tracer age) have proven to be useful diagnostics in stratospheric modelling because they can be related to observations and do not require a priori assumptions. The tracer age and age spectrum are applied to the pollutant ventilation of street canyons in this work. Using large-eddy simulations of flow over a single isolated canyon and an uneven, non-uniform canyon array, it is shown that the structure of the tracer age is dominated by the central canyon ;vortex;; small variations in the building height have a significant influence on the structure of the tracer age and the pollutant ventilation. The age spectrum is broad, with a long exponential tail whose slope depends on the canyon geometry. The mean tracer age, which roughly characterises the ventilation strength, is much greater than the local mean age of air.

Apportionment of urban aerosol sources in Chongqing (China) using synergistic on-line techniques

NASA Astrophysics Data System (ADS)

Chen, Yang; Yang, Fumo

2016-04-01

The sources of ambient fine particulate matter (PM2.5) during wintertime at a background urban location in Chongqing (southwestern China) have been determined. Aerosol chemical composition analyses were performed using multiple on-line techniques, such as single particle aerosol mass spectrometer (SPAMS) for single particle chemical composition, on-line elemental carbon-organic carbon analyzer (on-line OC-EC), on-line X-ray fluorescence (XRF) for elements, and in-situ Gas and Aerosol Compositions monitor (IGAC) for water-soluble ions in PM2.5. All the datasets from these techniques have been adjusted to a 1-h time resolution for receptor model input. Positive matrix factorization (PMF) has been used for resolving aerosol sources. At least six sources, including domestic coal burning, biomass burning, dust, traffic, industrial and secondary/aged factors have been resolved and interpreted. The synergistic on-line techniques were helpful for identifying aerosol sources more clearly than when only employing the results from the individual techniques. This results are useful for better understanding of aerosol sources and atmospheric processes.

Source apportionment of speciated PM10 in the United Kingdom in 2008: Episodes and annual averages

NASA Astrophysics Data System (ADS)

Redington, A. L.; Witham, C. S.; Hort, M. C.

2016-11-01

The Lagrangian atmospheric dispersion model NAME (Numerical Atmospheric-dispersion Modelling Environment), has been used to simulate the formation and transport of PM10 over North-West Europe in 2008. The model has been evaluated against UK measurement data and been shown to adequately represent the observed PM10 at rural and urban sites on a daily basis. The Lagrangian nature of the model allows information on the origin of pollutants (and hence their secondary products) to be retained to allow attribution of pollutants at receptor sites back to their sources. This source apportionment technique has been employed to determine whether the different components of the modelled PM10 have originated from UK, shipping, European (excluding the UK) or background sources. For the first time this has been done to evaluate the composition during periods of elevated PM10 as well as the annual average composition. The episode data were determined by selecting the model data for each hour when the corresponding measurement data was >50 μg/m3. All the modelled sites show an increase in European pollution contribution and a decrease in the background contribution in the episode case compared to the annual average. The European contribution is greatest in southern and eastern parts of the UK and decreases moving northwards and westwards. Analysis of the speciated attribution data over the selected sites reveals that for 2008, as an annual average, the top three contributors to total PM10 are UK primary PM10 (17-25%), UK origin nitrate aerosol (18-21%) and background PM10 (11-16%). Under episode conditions the top three contributors to modelled PM10 are UK origin nitrate aerosol (12-33%), European origin nitrate aerosol (11-19%) and UK primary PM10 (12-18%).

Development, Evaluation, and Application of a Primary Aerosol Model.

PubMed

Wang, I T; Chico, T; Huang, Y H; Farber, R J

1999-09-01

The Segmented-Plume Primary Aerosol Model (SPPAM) has been developed over the past several years. The earlier model development goals were simply to generalize the widely used Industrial Source Complex Short-Term (ISCST) model to simulate plume transport and dispersion under light wind conditions and to handle a large number of roadway or line sources. The goals have been expanded to include development of improved algorithm for effective plume transport velocity, more accurate and efficient line and area source dispersion algorithms, and recently, a more realistic and computationally efficient algorithm for plume depletion due to particle dry deposition. A performance evaluation of the SPPAM has been carried out using the 1983 PNL dual tracer experimental data. The results show the model predictions to be in good agreement with observations in both plume advection-dispersion and particulate matter (PM) depletion by dry deposition. For PM 2.5 impact analysis, the SPPAM has been applied to the Rubidoux area of California. Emission sources included in the modeling analysis are: paved road dust, diesel vehicular exhaust, gasoline vehicular exhaust, and tire wear particles from a large number of roadways in Rubidoux and surrounding areas. For the selected modeling periods, the predicted primary PM 2.5 to primary PM10 concentration ratios for the Rubidoux sampling station are in the range of 0.39-0.46. The organic fractions of the primary PM 2.5 impacts are estimated to be at least 34-41%. Detailed modeling results indicate that the relatively high organic fractions are primarily due to the proximity of heavily traveled roadways north of the sampling station. The predictions are influenced by a number of factors; principal among them are the receptor locations relative to major roadways, the volume and composition of traffic on these roadways, and the prevailing meteorological conditions.

Influence of ionotropic receptor location on their dynamics at glutamatergic synapses.

PubMed

Allam, Sushmita L; Bouteiller, Jean-Marie C; Hu, Eric; Greget, Renaud; Ambert, Nicolas; Bischoff, Serge; Baudry, Michel; Berger, Theodore W

2012-01-01

In this paper we study the effects of the location of ionotropic receptors, especially AMPA and NMDA receptors, on their function at excitatory glutamatergic synapses. As few computational models only allow to evaluate the influence of receptor location on state transition and receptor dynamics, we present an elaborate computational model of a glutamatergic synapse that takes into account detailed parametric models of ionotropic receptors along with glutamate diffusion within the synaptic cleft. Our simulation results underscore the importance of the wide spread distribution of AMPA receptors which is required to avoid massive desensitization of these receptors following a single glutamate release event while NMDA receptor location is potentially optimal relative to the glutamate release site thus, emphasizing the contribution of location dependent effects of the two major ionotropic receptors to synaptic efficacy.

Carbonaceous aerosols recorded in a southeastern Tibetan glacier: analysis of temporal variations and model estimates of sources and radiative forcing

DOE PAGES

Wang, Mo; Xu, B.; Cao, J.; ...

2015-02-02

High temporal resolution measurements of black carbon (BC) and organic carbon (OC) covering the time period of 1956–2006 in an ice core over the southeastern Tibetan Plateau show a distinct seasonal dependence of BC and OC with higher respective concentrations but a lower OC / BC ratio in the non-monsoon season than during the summer monsoon. We use a global aerosol-climate model, in which BC emitted from different source regions can be explicitly tracked, to quantify BC source–receptor relationships between four Asian source regions and the southeastern Tibetan Plateau as a receptor. The model results show that South Asia hasmore » the largest contribution to the present-day (1996–2005) mean BC deposition at the ice-core drilling site during the non-monsoon season (October to May) (81%) and all year round (74%), followed by East Asia (14% to the non-monsoon mean and 21% to the annual mean). The ice-core record also indicates stable and relatively low BC and OC deposition fluxes from the late 1950s to 1980, followed by an overall increase to recent years. This trend is consistent with the BC and OC emission inventories and the fuel consumption of South Asia (as the primary contributor to annual mean BC deposition). Moreover, the increasing trend of the OC / BC ratio since the early 1990s indicates a growing contribution of coal combustion and/or biomass burning to the emissions. The estimated radiative forcing induced by BC and OC impurities in snow has increased since 1980, suggesting an increasing potential influence of carbonaceous aerosols on the Tibetan glacier melting and the availability of water resources in the surrounding regions. Our study indicates that more attention to OC is merited because of its non-negligible light absorption and the recent rapid increases evident in the ice-core record.« less

Acetylcholine Receptors in Model Membranes: Structure/Function Correlates.

DTIC Science & Technology

1985-12-01

8217-ASSIFICAT1CN’r.OlrNC7-..OINC 6. 04STPl3U7lCh STATE)III (a. -,41. Revlon) Approved for public release;, distribution unlimited D T 18. SUPPLENENTARY NOTES *Annual...of California, San Diego B-019 La Jolla, California 92093 Approved for public release; distribution unlimited The findings in this report are not to be...electrodes E-255 and E 206 (In Vivo Metric Systems Metric Systems, Healdsburg, CA). DC source ( Omnical 2001, WPI Instruments, New Haven, CT). RACAL

Modelling the urban air quality in Hamburg with the new city-scale chemistry transport model CityChem

NASA Astrophysics Data System (ADS)

Karl, Matthias; Ramacher, Martin; Aulinger, Armin; Matthias, Volker; Quante, Markus

2017-04-01

Air quality modelling plays an important role by providing guidelines for efficient air pollution abatement measures. Currently, most urban dispersion models treat air pollutants as passive tracer substances or use highly simplified chemistry when simulating air pollutant concentrations on the city-scale. The newly developed urban chemistry-transport model CityChem has the capability of modelling the photochemical transformation of multiple pollutants along with atmospheric diffusion to produce pollutant concentration fields for the entire city on a horizontal resolution of 100 m or even finer and a vertical resolution of 24 layers up to 4000 m height. CityChem is based on the Eulerian urban dispersion model EPISODE of the Norwegian Institute for Air Research (NILU). CityChem treats the complex photochemistry in cities using detailed EMEP chemistry on an Eulerian 3-D grid, while using simple photo-stationary equilibrium on a much higher resolution grid (receptor grid), i.e. close to industrial point sources and traffic sources. The CityChem model takes into account that long-range transport contributes to urban pollutant concentrations. This is done by using 3-D boundary concentrations for the city domain derived from chemistry-transport simulations with the regional air quality model CMAQ. For the study of the air quality in Hamburg, CityChem was set-up with a main grid of 30×30 grid cells of 1×1 km2 each and a receptor grid of 300×300 grid cells of 100×100 m2. The CityChem model was driven with meteorological data generated by the prognostic meteorology component of the Australian chemistry-transport model TAPM. Bottom-up inventories of emissions from traffic, industry, households were based on data of the municipality of Hamburg. Shipping emissions for the port of Hamburg were taken from the Clean North Sea Shipping project. Episodes with elevated ozone (O3) were of specific interest for this study, as these are associated with exceedances of the World Health Organization (WHO) guideline concentration limits for O3 and of the regulatory limits for NO2. Model tests were performed with CityChem to study the ozone formation rate with simultaneous variation of emissions of nitrogen oxides (NOx) and volatile organic compounds (VOC). Emissions of VOC in urban areas are not well quantified as they may originate from various sources, including solvent usage, industry, combustion plants and vehicular traffic. The employed chemical mechanism contains large uncertainties with respect to ozone formation. Observed high-O3 episodes were analyzed by comparing modelled pollutant concentrations with concentration data from the Hamburg air quality surveillance network (http://luft.hamburg.de/). The analysis inspected possible reasons for too low modelled O3 in summer such as missing emissions of VOC from natural sources like green parks and the vertical exchange of O3 towards the surface.

Structural and Molecular Modeling Features of P2X Receptors

PubMed Central

Alves, Luiz Anastacio; da Silva, João Herminio Martins; Ferreira, Dinarte Neto Moreira; Fidalgo-Neto, Antonio Augusto; Teixeira, Pedro Celso Nogueira; de Souza, Cristina Alves Magalhães; Caffarena, Ernesto Raúl; de Freitas, Mônica Santos

2014-01-01

Currently, adenosine 5′-triphosphate (ATP) is recognized as the extracellular messenger that acts through P2 receptors. P2 receptors are divided into two subtypes: P2Y metabotropic receptors and P2X ionotropic receptors, both of which are found in virtually all mammalian cell types studied. Due to the difficulty in studying membrane protein structures by X-ray crystallography or NMR techniques, there is little information about these structures available in the literature. Two structures of the P2X4 receptor in truncated form have been solved by crystallography. Molecular modeling has proven to be an excellent tool for studying ionotropic receptors. Recently, modeling studies carried out on P2X receptors have advanced our knowledge of the P2X receptor structure-function relationships. This review presents a brief history of ion channel structural studies and shows how modeling approaches can be used to address relevant questions about P2X receptors. PMID:24637936

Modelling the interdependence between the stoichiometry of receptor oligomerization and ligand binding for a coexisting dimer/tetramer receptor system.

PubMed

Rovira, X; Vivó, M; Serra, J; Roche, D; Strange, P G; Giraldo, J

2009-01-01

Many G protein-coupled receptors have been shown to exist as oligomers, but the oligomerization state and the effects of this on receptor function are unclear. For some G protein-coupled receptors, in ligand binding assays, different radioligands provide different maximal binding capacities. Here we have developed mathematical models for co-expressed dimeric and tetrameric species of receptors. We have considered models where the dimers and tetramers are in equilibrium and where they do not interconvert and we have also considered the potential influence of the ligands on the degree of oligomerization. By analogy with agonist efficacy, we have considered ligands that promote, inhibit or have no effect on oligomerization. Cell surface receptor expression and the intrinsic capacity of receptors to oligomerize are quantitative parameters of the equations. The models can account for differences in the maximal binding capacities of radioligands in different preparations of receptors and provide a conceptual framework for simulation and data fitting in complex oligomeric receptor situations.

Estimation of the contributions of long range transported aerosol in East Asia to carbonaceous aerosol and PM concentrations in Seoul, Korea using highly time resolved measurements: a PSCF model approach.

PubMed

Jeong, Ukkyo; Kim, Jhoon; Lee, Hanlim; Jung, Jinsang; Kim, Young J; Song, Chul H; Koo, Ja-Ho

2011-07-01

The contributions of long range transported aerosol in East Asia to carbonaceous aerosol and particulate matter (PM) concentrations in Seoul, Korea were estimated with potential source contribution function (PSCF) calculations. Carbonaceous aerosol (organic carbon (OC) and elemental carbon (EC)), PM(2.5), and PM(10) concentrations were measured from April 2007 to March 2008 in Seoul, Korea. The PSCF and concentration weighted trajectory (CWT) receptor models were used to identify the spatial source distributions of OC, EC, PM(2.5), and coarse particles. Heavily industrialized areas in Northeast China such as Harbin and Changchun and East China including the Pearl River Delta region, the Yangtze River Delta region, and the Beijing-Tianjin region were identified as high OC, EC and PM(2.5) source areas. The conditional PSCF analysis was introduced so as to distinguish the influence of aerosol transported from heavily polluted source areas on a receptor site from that transported from relatively clean areas. The source contributions estimated using the conditional PSCF analysis account for not only the aerosol concentrations of long range transported aerosols but also the number of transport days effective on the measurement site. Based on the proposed algorithm, the condition of airmass pathways was classified into two types: one condition where airmass passed over the source region (PS) and another condition where airmass did not pass over the source region (NPS). For most of the seasons during the measurement period, 249.5-366.2% higher OC, EC, PM(2.5), and coarse particle concentrations were observed at the measurement site under PS conditions than under NPS conditions. Seasonal variations in the concentrations of OC, EC, PM(2.5), and coarse particles under PS, NPS, and background aerosol conditions were quantified. The contributions of long range transported aerosols on the OC, EC, PM(2.5), and coarse particle concentrations during several Asian dust events were also estimated. We also investigated the performance of the PSCF results obtained from combining highly time resolved measurement data and backward trajectory calculations via comparison with those from data in low resolutions. Reduced tailing effects and the larger coverage over the area of interest were observed in the PSCF results obtained from using the highly time resolved data and trajectories.

Neuron-specific (pro)renin receptor knockout prevents the development of salt-sensitive hypertension

PubMed Central

Li, Wencheng; Peng, Hua; Mehaffey, Eamonn P.; Kimball, Christie D.; Grobe, Justin L.; van Gool, Jeanette M.G.; Sullivan, Michelle N.; Earley, Scott; Danser, A.H. Jan; Ichihara, Atsuhiro; Feng, Yumei

2013-01-01

The (pro)renin receptor, which binds both renin and prorenin, is a newly discovered component of the renin angiotensin system that is highly expressed in the central nervous system. The significance of brain PRRs in mediating local angiotensin II formation and regulating blood pressure remains unclear. The current study was performed to test the hypothesis that PRR-mediated, non-proteolytic activation of prorenin is the main source of angiotensin II in the brain. Thus, PRR knockout in the brain is expected to prevent angiotensin II formation and development of deoxycorticosterone acetate salt induced hypertension. A neuron-specific PRR (ATP6AP2) knockout mouse model was generated using the Cre-LoxP system. Physiological parameters were recorded by telemetry. (Pro)renin receptor expression, detected by immunostaining and RT-PCR, was significantly decreased in the brains of knockout compared with wide-type mice. Intracerebroventricular infusion of mouse prorenin increased blood pressure and angiotensin II formation in wild type mice. This hypertensive response was abolished in (pro)renin receptor knockout mice in association with a reduction in angiotensin II levels. Deoxycorticosterone acetate salt increased (pro)renin receptor expression and angiotensin II formation in the brains of wild-type mice, an effect that was attenuated in (pro)renin receptor knockout mice. (Pro)renin receptor knockout in neurons prevented the development of Deoxycorticosterone acetate salt-induced hypertension as well as activation of cardiac and vasomotor sympathetic tone. In conclusion, non-proteolytic activation of prorenin through binding to the PRR mediates angiotensin II formation in the brain. Neuron-specific PRR knockout prevents the development of deoxycorticosterone acetate salt-induced hypertension, possibly through diminished angiotensin II formation. PMID:24246383

Thermosensory perception regulates speed of movement in response to temperature changes in Drosophila melanogaster.

PubMed

Soto-Padilla, Andrea; Ruijsink, Rick; Sibon, Ody C M; van Rijn, Hedderik; Billeter, Jean-Christophe

2018-04-12

Temperature influences physiology and behavior of all organisms. For ectotherms, which lack central temperature regulation, temperature adaptation requires sheltering from or moving to a heat source. As temperature constrains the rate of metabolic reactions, it can directly affect ectotherm physiology and thus behavioral performance. This direct effect is particularly relevant for insects whose small body readily equilibrates with ambient temperature. In fact, models of enzyme kinetics applied to insect behavior predict performance at different temperatures, suggesting that thermal physiology governs behavior. However, insects also possess thermosensory neurons critical for locating preferred temperatures, showing cognitive control. This suggests that temperature-related behavior can emerge directly from a physiological effect, indirectly as consequence of thermosensory processing, or through both. To separate the roles of thermal physiology and cognitive control, we developed an arena that allows fast temperature changes in time and space, and in which animals' movements are automatically quantified. We exposed wild-type and thermosensory receptor mutants Drosophila melanogaster to a dynamic temperature environment and tracked their movements. The locomotor speed of wild-type flies closely matched models of enzyme kinetics, but the behavior of thermosensory mutants did not. Mutations in thermosensory receptor dTrpA1 ( Transient receptor potential ) expressed in the brain resulted in a complete lack of response to temperature changes, while mutation in peripheral thermosensory receptor Gr28b(D) resulted in diminished response. We conclude that flies react to temperature through cognitive control, informed by interactions between various thermosensory neurons, whose behavioral output resembles that of enzyme kinetics. © 2018. Published by The Company of Biologists Ltd.

Combined analysis of modeled and monitored SO2 concentrations at a complex smelting facility.

PubMed

Rehbein, Peter J G; Kennedy, Michael G; Cotsman, David J; Campeau, Madonna A; Greenfield, Monika M; Annett, Melissa A; Lepage, Mike F

2014-03-01

Vale Canada Limited owns and operates a large nickel smelting facility located in Sudbury, Ontario. This is a complex facility with many sources of SO2 emissions, including a mix of source types ranging from passive building roof vents to North America's tallest stack. In addition, as this facility performs batch operations, there is significant variability in the emission rates depending on the operations that are occurring. Although SO2 emission rates for many of the sources have been measured by source testing, the reliability of these emission rates has not been tested from a dispersion modeling perspective. This facility is a significant source of SO2 in the local region, making it critical that when modeling the emissions from this facility for regulatory or other purposes, that the resulting concentrations are representative of what would actually be measured or otherwise observed. To assess the accuracy of the modeling, a detailed analysis of modeled and monitored data for SO2 at the facility was performed. A mobile SO2 monitor sampled at five locations downwind of different source groups for different wind directions resulting in a total of 168 hr of valid data that could be used for the modeled to monitored results comparison. The facility was modeled in AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model) using site-specific meteorological data such that the modeled periods coincided with the same times as the monitored events. In addition, great effort was invested into estimating the actual SO2 emission rates that would likely be occurring during each of the monitoring events. SO2 concentrations were modeled for receptors around each monitoring location so that the modeled data could be directly compared with the monitored data. The modeled and monitored concentrations were compared and showed that there were no systematic biases in the modeled concentrations. This paper is a case study of a Combined Analysis of Modelled and Monitored Data (CAMM), which is an approach promulgated within air quality regulations in the Province of Ontario, Canada. Although combining dispersion models and monitoring data to estimate or refine estimates of source emission rates is not a new technique, this study shows how, with a high degree of rigor in the design of the monitoring and filtering of the data, it can be applied to a large industrial facility, with a variety of emission sources. The comparison of modeled and monitored SO2 concentrations in this case study also provides an illustration of the AERMOD model performance for a large industrial complex with many sources, at short time scales in comparison with monitored data. Overall, this analysis demonstrated that the AERMOD model performed well.

Developmental Programming in Response to Intrauterine Growth Restriction Impairs Myoblast Function and Skeletal Muscle Metabolism

PubMed Central

Yates, D. T.; Macko, A. R.; Nearing, M.; Chen, X.; Rhoads, R. P.; Limesand, S. W.

2012-01-01

Fetal adaptations to placental insufficiency alter postnatal metabolic homeostasis in skeletal muscle by reducing glucose oxidation rates, impairing insulin action, and lowering the proportion of oxidative fibers. In animal models of intrauterine growth restriction (IUGR), skeletal muscle fibers have less myonuclei at birth. This means that myoblasts, the sole source for myonuclei accumulation in fibers, are compromised. Fetal hypoglycemia and hypoxemia are complications that result from placental insufficiency. Hypoxemia elevates circulating catecholamines, and chronic hypercatecholaminemia has been shown to reduce fetal muscle development and growth. We have found evidence for adaptations in adrenergic receptor expression profiles in myoblasts and skeletal muscle of IUGR sheep fetuses with placental insufficiency. The relationship of β-adrenergic receptors shifts in IUGR fetuses because Adrβ2 expression levels decline and Adrβ1 expression levels are unaffected in myofibers and increased in myoblasts. This adaptive response would suppress insulin signaling, myoblast incorporation, fiber hypertrophy, and glucose oxidation. Furthermore, this β-adrenergic receptor expression profile persists for at least the first month in IUGR lambs and lowers their fatty acid mobilization. Developmental programming of skeletal muscle adrenergic receptors partially explains metabolic and endocrine differences in IUGR offspring, and the impact on metabolism may result in differential nutrient utilization. PMID:22900186

Structure-based discovery and binding site analysis of histamine receptor ligands.

PubMed

Kiss, Róbert; Keserű, György M

2016-12-01

The application of structure-based drug discovery in histamine receptor projects was previously hampered by the lack of experimental structures. The publication of the first X-ray structure of the histamine H1 receptor has been followed by several successful virtual screens and binding site analysis studies of H1-antihistamines. This structure together with several other recently solved aminergic G-protein coupled receptors (GPCRs) enabled the development of more realistic homology models for H2, H3 and H4 receptors. Areas covered: In this paper, the authors review the development of histamine receptor models and their application in drug discovery. Expert opinion: In the authors' opinion, the application of atomistic histamine receptor models has played a significant role in understanding key ligand-receptor interactions as well as in the discovery of novel chemical starting points. The recently solved H1 receptor structure is a major milestone in structure-based drug discovery; however, our analysis also demonstrates that for building H3 and H4 receptor homology models, other GPCRs may be more suitable as templates. For these receptors, the authors envisage that the development of higher quality homology models will significantly contribute to the discovery and optimization of novel H3 and H4 ligands.

Adding Four- Dimensional Data Assimilation (aka grid ...

EPA Pesticide Factsheets

Adding four-dimensional data assimilation (a.k.a. grid nudging) to MPAS.The U.S. Environmental Protection Agency is investigating the use of MPAS as the meteorological driver for its next-generation air quality model. To function as such, MPAS needs to operate in a diagnostic mode in much the same manner as the current meteorological driver, the Weather Research and Forecasting (WRF) model. The WRF operates in diagnostic mode using Four-Dimensional Data Assimilation, also known as "grid nudging". MPAS version 4.0 has been modified with the addition of an FDDA routine to the standard physics drivers to nudge the state variables for wind, temperature and water vapor towards MPAS initialization fields defined at 6-hour intervals from GFS-derived data. The results to be shown demonstrate the ability to constrain MPAS simulations to known historical conditions and thus provide the U.S. EPA with a practical meteorological driver for global-scale air quality simulations. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use bo

Association between Toll-like receptor 4 Asp299Gly polymorphism and coronary heart disease susceptibility.

PubMed

Wu, B W; Zhu, J; Shi, H M; Jin, B; Wen, Z C

2017-08-07

Published data on the association between Toll-like receptor 4 (TLR4) Asp299Gly polymorphism and coronary heart disease (CHD) susceptibility are inconclusive. To derive a more precise estimation of the relationship, a meta-analysis was performed. English-language studies were identified by searching PubMed and Embase databases (up to November 2016). All epidemiological studies were regarding Caucasians because no TLR4 Asp/Gly and Gly/Gly genotypes have been detected in Asians. A total of 20 case-control studies involving 14,416 cases and 10,764 controls were included in the meta-analysis. Overall, no significant associations were found between TLR4 Asp299Gly polymorphism and CHD susceptibility in the dominant model (OR=0.89; 95%CI=0.74 to 1.06; P=0.20) pooled in the meta-analysis. In the subgroup analysis by CHD, non-significant associations were found in cases compared to controls. When stratified by control source, no significantly decreased risk was found in the additive model or dominant model. The present meta-analysis suggests that the TLR4 Asp299Gly polymorphism was not associated with decreased CHD risk in Caucasians.

In silico prediction of the G-protein coupled receptors expressed during the metamorphic molt of Sagmariasus verreauxi (Crustacea: Decapoda) by mining transcriptomic data: RNA-seq to repertoire.

PubMed

Buckley, Sean J; Fitzgibbon, Quinn P; Smith, Gregory G; Ventura, Tomer

2016-03-01

Against a backdrop of food insecurity, the farming of decapod crustaceans is a rapidly expanding and globally significant source of food protein. Sagmariasus verreauxi spiny lobster, the subject of this study, are decapods of underdeveloped aquaculture potential. Crustacean neuropeptide G-protein coupled receptors (GPCRs) mediate endocrine pathways that are integral to animal fecundity, growth and survival. The potential use of novel biotechnologies to enhance GPCR-mediated physiology may assist in improving the health and productivity of farmed decapod populations. This study catalogues the GPCRs expressed in the early developmental stages, as well as adult tissues, with a view to illuminating key neuropeptide receptors. De novo assembled contiguous sequences generated from transcriptomic reads of metamorphic and post metamorphic S. verreauxi were filtered for seven transmembrane domains, and used as a reference for iterative re-mapping. Subsequent putative GPCR open reading frames (ORFs) were BLAST annotated, categorised, and compared to published orthologues based on phylogenetic analysis. A total of 85 GPCRs were digitally predicted, that represented each of the four arthropod subfamilies. They generally displayed low-level and non-differential metamorphic expression with few exceptions that we examined using RT-PCR and qPCR. Two putative CHH-like neuropeptide receptors were annotated. Three dimensional structural modelling suggests that these receptors exhibit a conserved extracellular ligand binding pocket, providing support to the notion that these receptors co-evolved with their ligands across Decapoda. This perhaps narrows the search for means to increase productivity of farmed decapod populations. Copyright © 2016 Elsevier Inc. All rights reserved.

Special report on transboundary air quality issues

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

NONE

1998-12-31

The International Air Quality Board was created in 1996 to provide advice to the International Joint Commission in fulfilling an air quality alerting function requested by governments in that year. The Board undertook a review of the many issues affecting transboundary air quality along the Canada-US border. This report reflects on issues previously addressed by the Board in its reporting to the Commission. Section 1 discusses the need for Canada and the US to adopt a seamless border approach to address pollution sources and receptors in a holistic manner. Section 2 discusses nitrogen oxides as a key contaminant because ofmore » its direct impact on the ecosystem and its effects on future levels of other secondary pollutants. Section 3 outlines the deficiencies of emission inventories regarding persistent toxic substances such as mercury, which must be addressed if source-to-receptor relationships are to be established. Section 4 covers the need to develop monitoring and modelling tools to further examine pollutant transport and concentration, and the resulting human and ecological exposure. Section 5 describes issues in individual regions along the border. Section 6 is directed at the harmonization of standards, which would assist in the effective control of transboundary pollutants such as ozone. Section 7 discusses collaboration with other organizations in addressing transboundary air pollution issues. Section 8 describes various feedback mechanisms for verifying that the elimination or management of air pollution is achieving improvement and benefits. Section 9 considers emissions and preventive strategies for major source sectors, including coal-fired utilities and mobile sources. The final section outlines future Board activities.« less

Towards structural models of molecular recognition in olfactory receptors.

PubMed

Afshar, M; Hubbard, R E; Demaille, J

1998-02-01

The G protein coupled receptors (GPCR) are an important class of proteins that act as signal transducers through the cytoplasmic membrane. Understanding the structure and activation mechanism of these proteins is crucial for understanding many different aspects of cellular signalling. The olfactory receptors correspond to the largest family of GPCRs. Very little is known about how the structures of the receptors govern the specificity of interaction which enables identification of particular odorant molecules. In this paper, we review recent developments in two areas of molecular modelling: methods for modelling the configuration of trans-membrane helices and methods for automatic docking of ligands into receptor structures. We then show how a subset of these methods can be combined to construct a model of a rat odorant receptor interacting with lyral for which experimental data are available. This modelling can help us make progress towards elucidating the specificity of interactions between receptors and odorant molecules.

Predicting receptor-ligand pairs through kernel learning

PubMed Central

2011-01-01

Background Regulation of cellular events is, often, initiated via extracellular signaling. Extracellular signaling occurs when a circulating ligand interacts with one or more membrane-bound receptors. Identification of receptor-ligand pairs is thus an important and specific form of PPI prediction. Results Given a set of disparate data sources (expression data, domain content, and phylogenetic profile) we seek to predict new receptor-ligand pairs. We create a combined kernel classifier and assess its performance with respect to the Database of Ligand-Receptor Partners (DLRP) 'golden standard' as well as the method proposed by Gertz et al. Among our findings, we discover that our predictions for the tgfβ family accurately reconstruct over 76% of the supported edges (0.76 recall and 0.67 precision) of the receptor-ligand bipartite graph defined by the DLRP "golden standard". In addition, for the tgfβ family, the combined kernel classifier is able to relatively improve upon the Gertz et al. work by a factor of approximately 1.5 when considering that our method has an F-measure of 0.71 while that of Gertz et al. has a value of 0.48. Conclusions The prediction of receptor-ligand pairings is a difficult and complex task. We have demonstrated that using kernel learning on multiple data sources provides a stronger alternative to the existing method in solving this task. PMID:21834994

Source apportionment of VOCs in the Los Angeles area using positive matrix factorization

NASA Astrophysics Data System (ADS)

Brown, Steven G.; Frankel, Anna; Hafner, Hilary R.

Eight 3-h speciated hydrocarbon measurements were collected daily by the South Coast Air Quality Management District (SCAQMD) as part of the Photochemical Assessment Monitoring Stations (PAMS) program during the summers of 2001-03 at two sites in the Los Angeles air basin, Azusa and Hawthorne. Over 30 hydrocarbons from over 500 samples at Azusa and 600 samples at Hawthorne were subsequently analyzed using the multivariate receptor model positive matrix factorization (PMF). At Azusa and Hawthorne, five and six factors were identified, respectively, with a good comparison between predicted and measured mass. At Azusa, evaporative emissions (a median of 31% of the total mass), motor vehicle exhaust (22%), liquid/unburned gasoline (27%), coatings (17%), and biogenic emissions (3%) factors were identified. Factors identified at Hawthorne were evaporative emissions (a median of 34% of the total mass), motor vehicle exhaust (24%), industrial process losses (15%), natural gas (13%), liquid/unburned gasoline (13%), and biogenic emissions (1%). Together, the median contribution from mobile source-related factors (exhaust, evaporative emissions, and liquid/unburned gasoline) was 80% and 71% at Azusa and Hawthorne, respectively, similar to previous source apportionment results using the chemical mass balance (CMB) model. There is a difference in the distribution among mobile source factors compared to the CMB work, with an increase in the contribution from evaporative emissions, though the cause (changes in emissions or differences between models) is unknown.

Source apportionment of Baltimore aerosol from combined size distribution and chemical composition data

NASA Astrophysics Data System (ADS)

Ogulei, David; Hopke, Philip K.; Zhou, Liming; Patrick Pancras, J.; Nair, Narayanan; Ondov, John M.

Several multivariate data analysis methods have been applied to a combination of particle size and composition measurements made at the Baltimore Supersite. Partial least squares (PLS) was used to investigate the relationship (linearity) between number concentrations and the measured PM2.5 mass concentrations of chemical species. The data were obtained at the Ponca Street site and consisted of six days' measurements: 6, 7, 8, 18, 19 July, and 21 August 2002. The PLS analysis showed that the covariance between the data could be explained by 10 latent variables (LVs), but only the first four of these were sufficient to establish the linear relationship between the two data sets. More LVs could not make the model better. The four LVs were found to better explain the covariance between the large sized particles and the chemical species. A bilinear receptor model, PMF2, was then used to simultaneously analyze the size distribution and chemical composition data sets. The resolved sources were identified using information from number and mass contributions from each source (source profiles) as well as meteorological data. Twelve sources were identified: oil-fired power plant emissions, secondary nitrate I, local gasoline traffic, coal-fired power plant, secondary nitrate II, secondary sulfate, diesel emissions/bus maintenance, Quebec wildfire episode, nucleation, incinerator, airborne soil/road-way dust, and steel plant emissions. Local sources were mostly characterized by bi-modal number distributions. Regional sources were characterized by transport mode particles (0.2- 0.5μm).

Source identification of coarse particles in the Desert ...

EPA Pesticide Factsheets

The Desert Southwest Coarse Particulate Matter Study was undertaken to further our understanding of the spatial and temporal variability and sources of fine and coarse particulate matter (PM) in rural, arid, desert environments. Sampling was conducted between February 2009 and February 2010 in Pinal County, AZ near the town of Casa Grande where PM concentrations routinely exceed the U.S. National Ambient Air Quality Standards (NAAQS) for both PM10 and PM2.5. In this desert region, exceedances of the PM10 NAAQS are dominated by high coarse particle concentrations, a common occurrence in this region of the United States. This work expands on previously published measurements of PM mass and chemistry by examining the sources of fine and coarse particles and the relative contribution of each to ambient PM mass concentrations using the Positive Matrix Factorization receptor model (Clements et al., 2014). Highlights • Isolation of coarse particles from fine particle sources. • Unique chemical composition of coarse particles. • Role of primary biological particles on aerosol loadings.

Preclinical Testing of Novel Oxytocin Receptor Activators in Models of Autism Phenotypes

DTIC Science & Technology

2014-09-01

AD_________________ Award Number: TITLE: Preclinical Testing of Novel Oxytocin Receptor Activators in Models of Autism ...AUG 2013-7 Aug 2014 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Preclinical Testing of Novel Oxytocin Receptor Activators in Models of Autism ...a genetic mouse model of autism -like phenotypes, the Grin1 knockdown mouse. The Grin1 gene encodes the NR1 subunit of the NMDA receptor . In the

Bayesian inverse modeling and source location of an unintended 131I release in Europe in the fall of 2011

NASA Astrophysics Data System (ADS)

Tichý, Ondřej; Šmídl, Václav; Hofman, Radek; Šindelářová, Kateřina; Hýža, Miroslav; Stohl, Andreas

2017-10-01

In the fall of 2011, iodine-131 (131I) was detected at several radionuclide monitoring stations in central Europe. After investigation, the International Atomic Energy Agency (IAEA) was informed by Hungarian authorities that 131I was released from the Institute of Isotopes Ltd. in Budapest, Hungary. It was reported that a total activity of 342 GBq of 131I was emitted between 8 September and 16 November 2011. In this study, we use the ambient concentration measurements of 131I to determine the location of the release as well as its magnitude and temporal variation. As the location of the release and an estimate of the source strength became eventually known, this accident represents a realistic test case for inversion models. For our source reconstruction, we use no prior knowledge. Instead, we estimate the source location and emission variation using only the available 131I measurements. Subsequently, we use the partial information about the source term available from the Hungarian authorities for validation of our results. For the source determination, we first perform backward runs of atmospheric transport models and obtain source-receptor sensitivity (SRS) matrices for each grid cell of our study domain. We use two dispersion models, FLEXPART and Hysplit, driven with meteorological analysis data from the global forecast system (GFS) and from European Centre for Medium-range Weather Forecasts (ECMWF) weather forecast models. Second, we use a recently developed inverse method, least-squares with adaptive prior covariance (LS-APC), to determine the 131I emissions and their temporal variation from the measurements and computed SRS matrices. For each grid cell of our simulation domain, we evaluate the probability that the release was generated in that cell using Bayesian model selection. The model selection procedure also provides information about the most suitable dispersion model for the source term reconstruction. Third, we select the most probable location of the release with its associated source term and perform a forward model simulation to study the consequences of the iodine release. Results of these procedures are compared with the known release location and reported information about its time variation. We find that our algorithm could successfully locate the actual release site. The estimated release period is also in agreement with the values reported by IAEA and the reported total released activity of 342 GBq is within the 99 % confidence interval of the posterior distribution of our most likely model.

Microglial cells and peritoneal macrophages release activin A upon stimulation with Toll-like receptor agonists.

PubMed

Ebert, Sandra; Zeretzke, Moritz; Nau, Roland; Michel, Uwe

2007-02-21

Activin A levels are elevated in the cerebrospinal fluid (CSF) of patients with meningitis and in the sera of patients with sepsis. The source(s) of the elevated concentrations of activin A in CSF and serum have not yet been discovered. Here we demonstrate that primary mouse microglial cells and peritoneal macrophages release activin A after treatment with agonists of Toll-like receptor (TLR) 2, 4, and 9. These findings provide further evidence for a role of activin in the innate immune response and suggest that microglial cells and macrophages are a source of elevated activin A concentrations observed in the CSF during bacterial meningitis and in the systemic circulation during sepsis.

Exact solutions to a spatially extended model of kinase-receptor interaction.

PubMed

Szopa, Piotr; Lipniacki, Tomasz; Kazmierczak, Bogdan

2011-10-01

B and Mast cells are activated by the aggregation of the immune receptors. Motivated by this phenomena we consider a simple spatially extended model of mutual interaction of kinases and membrane receptors. It is assumed that kinase activates membrane receptors and in turn the kinase molecules bound to the active receptors are activated by transphosphorylation. Such a type of interaction implies positive feedback and may lead to bistability. In this study we apply the Steklov eigenproblem theory to analyze the linearized model and find exact solutions in the case of non-uniformly distributed membrane receptors. This approach allows us to determine the critical value of receptor dephosphorylation rate at which cell activation (by arbitrary small perturbation of the inactive state) is possible. We found that cell sensitivity grows with decreasing kinase diffusion and increasing anisotropy of the receptor distribution. Moreover, these two effects are cooperating. We showed that the cell activity can be abruptly triggered by the formation of the receptor aggregate. Since the considered activation mechanism is not based on receptor crosslinking by polyvalent antigens, the proposed model can also explain B cell activation due to receptor aggregation following binding of monovalent antigens presented on the antigen presenting cell.

Public health impacts of the severe haze in Equatorial Asia in September-October 2015: demonstration of a new framework for informing fire management strategies to reduce downwind smoke exposure

NASA Astrophysics Data System (ADS)

Koplitz, Shannon N.; Mickley, Loretta J.; Marlier, Miriam E.; Buonocore, Jonathan J.; Kim, Patrick S.; Liu, Tianjia; Sulprizio, Melissa P.; DeFries, Ruth S.; Jacob, Daniel J.; Schwartz, Joel; Pongsiri, Montira; Myers, Samuel S.

2016-09-01

In September-October 2015, El Niño and positive Indian Ocean Dipole conditions set the stage for massive fires in Sumatra and Kalimantan (Indonesian Borneo), leading to persistently hazardous levels of smoke pollution across much of Equatorial Asia. Here we quantify the emission sources and health impacts of this haze episode and compare the sources and impacts to an event of similar magnitude occurring under similar meteorological conditions in September-October 2006. Using the adjoint of the GEOS-Chem chemical transport model, we first calculate the influence of potential fire emissions across the domain on smoke concentrations in three receptor areas downwind—Indonesia, Malaysia, and Singapore—during the 2006 event. This step maps the sensitivity of each receptor to fire emissions in each grid cell upwind. We then combine these sensitivities with 2006 and 2015 fire emission inventories from the Global Fire Assimilation System (GFAS) to estimate the resulting population-weighted smoke exposure. This method, which assumes similar smoke transport pathways in 2006 and 2015, allows near real-time assessment of smoke pollution exposure, and therefore the consequent morbidity and premature mortality, due to severe haze. Our approach also provides rapid assessment of the relative contribution of fire emissions generated in a specific province to smoke-related health impacts in the receptor areas. We estimate that haze in 2015 resulted in 100 300 excess deaths across Indonesia, Malaysia and Singapore, more than double those of the 2006 event, with much of the increase due to fires in Indonesia’s South Sumatra Province. The model framework we introduce in this study can rapidly identify those areas where land use management to reduce and/or avoid fires would yield the greatest benefit to human health, both nationally and regionally.

Application of human induced pluripotent stem cells to model fibrodysplasia ossificans progressiva.

PubMed

Barruet, Emilie; Hsiao, Edward C

2018-04-01

Fibrodysplasia ossificans progressiva (FOP) is a genetic condition characterized by massive heterotopic ossification. FOP patients have mutations in the Activin A type I receptor (ACVR1), a bone morphogenetic protein (BMP) receptor. FOP is a progressive and debilitating disease characterized by bone formation flares that often occur after trauma. Since it is often difficult or impossible to obtain large amounts of tissue from human donors due to the risks of inciting more heterotopic bone formation, human induced pluripotent stem cells (hiPSCs) provide an attractive source for establishing in vitro disease models and for applications in drug screening. hiPSCs have the ability to self-renew, allowing researchers to obtain large amounts of starting material. hiPSCs also have the potential to differentiate into any cell type in the body. In this review, we discuss how the application of hiPSC technology to studying FOP has changed our perspectives on FOP disease pathogenesis. We also consider ongoing challenges and emerging opportunities for the use of human iPSCs in drug discovery and regenerative medicine. Copyright © 2017 Elsevier Inc. All rights reserved.

Establishment of A431 cell membrane chromatography-RPLC method for screening target components from Radix Caulophylli.

PubMed

Hou, Xiaofang; Wang, Sicen; Hou, Jingjing; He, Langchong

2011-03-01

We describe here an analytical method of A431 cell membrane chromatography (A431/CMC) (CMC, cell membrane chromatography) combined with RPLC for recognition, separation, and identification of target components from traditional Chinese medicines (TCMs) Radix Caulophylli. The A431 cells with high expressed epidermal growth factor receptor (EGFR) were used to prepare the stationary phase in the CMC model. Retention fractions on the A431-CMC model were collected using an automated fraction collection and injection module (FC/I). Each fraction was analyzed by RPLC under the optimized conditions. Gefitinib and erlotinib were used as standard compounds to investigate the suitability and reliability of the A431 cell membrane chromatography-RPLC method prior to screening target component from Radix Caulophylli total alkaloids. The results indicated that caulophine and taspine were the target component acting on the epidermal growth factor receptor. This method could be an efficient way in drug discovery using natural medicinal herbs as a source of novel compounds. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

EXPOSURE ASSESSMENT AND FUTURE DIRECTIONS IN EXPOSURE SCIENCE

EPA Science Inventory

Exposure is the contact between a stressor and a human or ecological receptor. Risk analysis step in which receptor interaction with the exposure stressor of concern is evaluated. To assess exposure to a particular stressor we need to know - Properties of the stressor; Sources, p...

Source apportionment of PAH in Hamilton Harbour suspended sediments: comparison of two factor analysis methods.

PubMed

Sofowote, Uwayemi M; McCarry, Brian E; Marvin, Christopher H

2008-08-15

A total of 26 suspended sediment samples collected over a 5-year period in Hamilton Harbour, Ontario, Canada and surrounding creeks were analyzed for a suite of polycyclic aromatic hydrocarbons and sulfur heterocycles. Hamilton Harbour sediments contain relatively high levels of polycyclic aromatic compounds and heavy metals due to emissions from industrial and mobile sources. Two receptor modeling methods using factor analyses were compared to determine the profiles and relative contributions of pollution sources to the harbor; these methods are principal component analyses (PCA) with multiple linear regression analysis (MLR) and positive matrix factorization (PMF). Both methods identified four factors and gave excellent correlation coefficients between predicted and measured levels of 25 aromatic compounds; both methods predicted similar contributions from coal tar/coal combustion sources to the harbor (19 and 26%, respectively). One PCA factor was identified as contributions from vehicular emissions (61%); PMF was able to differentiate vehicular emissions into two factors, one attributed to gasoline emissions sources (28%) and the other to diesel emissions sources (24%). Overall, PMF afforded better source identification than PCA with MLR. This work constitutes one of the few examples of the application of PMF to the source apportionment of sediments; the addition of sulfur heterocycles to the analyte list greatly aided in the source identification process.

Quantifying sources, transport, deposition, and radiative forcing of black carbon over the Himalayas and Tibetan Plateau

DOE PAGES

Zhang, Rudong; Wang, Hailong; Qian, Yun; ...

2015-06-08

Black carbon (BC) particles over the Himalayas and Tibetan Plateau (HTP), both airborne and those deposited on snow, have been shown to affect snowmelt and glacier retreat. Since BC over the HTP may originate from a variety of geographical regions and emission sectors, it is essential to quantify the source–receptor relationships of BC in order to understand the contributions of natural and anthropogenic emissions and provide guidance for potential mitigation actions. In this study, we use the Community Atmosphere Model version 5 (CAM5) with a newly developed source-tagging technique, nudged towards the MERRA meteorological reanalysis, to characterize the fate ofmore » BC particles emitted from various geographical regions and sectors. Evaluated against observations over the HTP and surrounding regions, the model simulation shows a good agreement in the seasonal variation in the near-surface airborne BC concentrations, providing confidence to use this modeling framework for characterizing BC source–receptor relationships. Our analysis shows that the relative contributions from different geographical regions and source sectors depend on season and location in the HTP. The largest contribution to annual mean BC burden and surface deposition in the entire HTP region is from biofuel and biomass (BB) emissions in South Asia, followed by fossil fuel (FF) emissions from South Asia, then FF from East Asia. The same roles hold for all the seasonal means except for the summer, when East Asia FF becomes more important. For finer receptor regions of interest, South Asia BB and FF have the largest impact on BC in the Himalayas and central Tibetan Plateau, while East Asia FF and BB contribute the most to the northeast plateau in all seasons and southeast plateau in the summer. Central Asia and Middle East FF emissions have relatively more important contributions to BC reaching the northwest plateau, especially in the summer. Although local emissions only contribute about 10% of BC in the HTP, this contribution is extremely sensitive to local emission changes. Lastly, we show that the annual mean radiative forcing (0.42 W m -2) due to BC in snow outweighs the BC dimming effect (-0.3 W m -2) at the surface over the HTP. We also find strong seasonal and spatial variation with a peak value of 5 W m -2 in the spring over the northwest plateau. Such a large forcing of BC in snow is sufficient to cause earlier snow melting and potentially contribute to the acceleration of glacier retreat.« less

Quantifying sources, transport, deposition, and radiative forcing of black carbon over the Himalayas and Tibetan Plateau

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

Zhang, Rudong; Wang, Hailong; Qian, Yun

Black carbon (BC) particles over the Himalayas and Tibetan Plateau (HTP), both airborne and those deposited on snow, have been shown to affect snowmelt and glacier retreat. Since BC over the HTP may originate from a variety of geographical regions and emission sectors, it is essential to quantify the source–receptor relationships of BC in order to understand the contributions of natural and anthropogenic emissions and provide guidance for potential mitigation actions. In this study, we use the Community Atmosphere Model version 5 (CAM5) with a newly developed source-tagging technique, nudged towards the MERRA meteorological reanalysis, to characterize the fate ofmore » BC particles emitted from various geographical regions and sectors. Evaluated against observations over the HTP and surrounding regions, the model simulation shows a good agreement in the seasonal variation in the near-surface airborne BC concentrations, providing confidence to use this modeling framework for characterizing BC source–receptor relationships. Our analysis shows that the relative contributions from different geographical regions and source sectors depend on season and location in the HTP. The largest contribution to annual mean BC burden and surface deposition in the entire HTP region is from biofuel and biomass (BB) emissions in South Asia, followed by fossil fuel (FF) emissions from South Asia, then FF from East Asia. The same roles hold for all the seasonal means except for the summer, when East Asia FF becomes more important. For finer receptor regions of interest, South Asia BB and FF have the largest impact on BC in the Himalayas and central Tibetan Plateau, while East Asia FF and BB contribute the most to the northeast plateau in all seasons and southeast plateau in the summer. Central Asia and Middle East FF emissions have relatively more important contributions to BC reaching the northwest plateau, especially in the summer. Although local emissions only contribute about 10% of BC in the HTP, this contribution is extremely sensitive to local emission changes. Lastly, we show that the annual mean radiative forcing (0.42 W m -2) due to BC in snow outweighs the BC dimming effect (-0.3 W m -2) at the surface over the HTP. We also find strong seasonal and spatial variation with a peak value of 5 W m -2 in the spring over the northwest plateau. Such a large forcing of BC in snow is sufficient to cause earlier snow melting and potentially contribute to the acceleration of glacier retreat.« less

T cell costimulation by chemokine receptors.

PubMed

Molon, Barbara; Gri, Giorgia; Bettella, Monica; Gómez-Moutón, Concepción; Lanzavecchia, Antonio; Martínez-A, Carlos; Mañes, Santos; Viola, Antonella

2005-05-01

Signals mediated by chemokine receptors may compete with T cell receptor stop signals and determine the duration of T cell-antigen-presenting cell interactions. Here we show that during T cell stimulation by antigen-presenting cells, T cell chemokine receptors coupled to G(q) and/or G(11) protein were recruited to the immunological synapse by a G(i)-independent mechanism. When chemokine receptors were sequestered at the immunological synapse, T cells became insensitive to chemotactic gradients, formed more stable conjugates and finally responded with enhanced proliferation and cytokine production. We suggest that chemokine receptor trapping at the immunological synapse enhances T cell activation by improving T cell-antigen-presenting cell attraction and impeding the 'distraction' of successfully engaged T cells by other chemokine sources.

Multiple templates-based homology modeling enhances structure quality of AT1 receptor: validation by molecular dynamics and antagonist docking.

PubMed

Sokkar, Pandian; Mohandass, Shylajanaciyar; Ramachandran, Murugesan

2011-07-01

We present a comparative account on 3D-structures of human type-1 receptor (AT1) for angiotensin II (AngII), modeled using three different methodologies. AngII activates a wide spectrum of signaling responses via the AT1 receptor that mediates physiological control of blood pressure and diverse pathological actions in cardiovascular, renal, and other cell types. Availability of 3D-model of AT1 receptor would significantly enhance the development of new drugs for cardiovascular diseases. However, templates of AT1 receptor with low sequence similarity increase the complexity in straightforward homology modeling, and hence there is a need to evaluate different modeling methodologies in order to use the models for sensitive applications such as rational drug design. Three models were generated for AT1 receptor by, (1) homology modeling with bovine rhodopsin as template, (2) homology modeling with multiple templates and (3) threading using I-TASSER web server. Molecular dynamics (MD) simulation (15 ns) of models in explicit membrane-water system, Ramachandran plot analysis and molecular docking with antagonists led to the conclusion that multiple template-based homology modeling outweighs other methodologies for AT1 modeling.

Is receptor oligomerization causally linked to activation of the EGF receptor kinase?

NASA Technical Reports Server (NTRS)

Rintoul, D. A.; Spooner, B. S. (Principal Investigator)

1992-01-01

Transduction of a signal from an extracellular peptide hormone to produce an intracellular response is often mediated by a cell surface receptor, which is usually a glycoprotein. The secondary intracellular signal(s) generated after hormone binding to the receptor have been intensively studied. The nature of the primary signal generated by ligand binding to the receptor is understood less well in most cases. The particular case of the epidermal growth factor (EGF) receptor is analyzed, and evidence for or against two dissimilar models of primary signal transduction is reviewed. Evidence for the most widely accepted current model is found to be unconvincing. Evidence for the other model is substantial but indirect; a direct test of this model remains to be done.

Generalized receptor law governs phototaxis in the phytoplankton Euglena gracilis

PubMed Central

Giometto, Andrea; Altermatt, Florian; Maritan, Amos; Stocker, Roman; Rinaldo, Andrea

2015-01-01

Phototaxis, the process through which motile organisms direct their swimming toward or away from light, is implicated in key ecological phenomena (including algal blooms and diel vertical migration) that shape the distribution, diversity, and productivity of phytoplankton and thus energy transfer to higher trophic levels in aquatic ecosystems. Phototaxis also finds important applications in biofuel reactors and microbiopropellers and is argued to serve as a benchmark for the study of biological invasions in heterogeneous environments owing to the ease of generating stochastic light fields. Despite its ecological and technological relevance, an experimentally tested, general theoretical model of phototaxis seems unavailable to date. Here, we present accurate measurements of the behavior of the alga Euglena gracilis when exposed to controlled light fields. Analysis of E. gracilis’ phototactic accumulation dynamics over a broad range of light intensities proves that the classic Keller–Segel mathematical framework for taxis provides an accurate description of both positive and negative phototaxis only when phototactic sensitivity is modeled by a generalized “receptor law,” a specific nonlinear response function to light intensity that drives algae toward beneficial light conditions and away from harmful ones. The proposed phototactic model captures the temporal dynamics of both cells’ accumulation toward light sources and their dispersion upon light cessation. The model could thus be of use in integrating models of vertical phytoplankton migrations in marine and freshwater ecosystems, and in the design of bioreactors. PMID:25964338

Generalized receptor law governs phototaxis in the phytoplankton Euglena gracilis.

PubMed

Giometto, Andrea; Altermatt, Florian; Maritan, Amos; Stocker, Roman; Rinaldo, Andrea

2015-06-02

Phototaxis, the process through which motile organisms direct their swimming toward or away from light, is implicated in key ecological phenomena (including algal blooms and diel vertical migration) that shape the distribution, diversity, and productivity of phytoplankton and thus energy transfer to higher trophic levels in aquatic ecosystems. Phototaxis also finds important applications in biofuel reactors and microbiopropellers and is argued to serve as a benchmark for the study of biological invasions in heterogeneous environments owing to the ease of generating stochastic light fields. Despite its ecological and technological relevance, an experimentally tested, general theoretical model of phototaxis seems unavailable to date. Here, we present accurate measurements of the behavior of the alga Euglena gracilis when exposed to controlled light fields. Analysis of E. gracilis' phototactic accumulation dynamics over a broad range of light intensities proves that the classic Keller-Segel mathematical framework for taxis provides an accurate description of both positive and negative phototaxis only when phototactic sensitivity is modeled by a generalized "receptor law," a specific nonlinear response function to light intensity that drives algae toward beneficial light conditions and away from harmful ones. The proposed phototactic model captures the temporal dynamics of both cells' accumulation toward light sources and their dispersion upon light cessation. The model could thus be of use in integrating models of vertical phytoplankton migrations in marine and freshwater ecosystems, and in the design of bioreactors.

Characterizing and locating air pollution sources in a complex industrial district using optical remote sensing technology and multivariate statistical modeling.

PubMed

Chang, Pao-Erh Paul; Yang, Jen-Chih Rena; Den, Walter; Wu, Chang-Fu

2014-09-01

Emissions of volatile organic compounds (VOCs) are most frequent environmental nuisance complaints in urban areas, especially where industrial districts are nearby. Unfortunately, identifying the responsible emission sources of VOCs is essentially a difficult task. In this study, we proposed a dynamic approach to gradually confine the location of potential VOC emission sources in an industrial complex, by combining multi-path open-path Fourier transform infrared spectrometry (OP-FTIR) measurement and the statistical method of principal component analysis (PCA). Close-cell FTIR was further used to verify the VOC emission source by measuring emitted VOCs from selected exhaust stacks at factories in the confined areas. Multiple open-path monitoring lines were deployed during a 3-month monitoring campaign in a complex industrial district. The emission patterns were identified and locations of emissions were confined by the wind data collected simultaneously. N,N-Dimethyl formamide (DMF), 2-butanone, toluene, and ethyl acetate with mean concentrations of 80.0 ± 1.8, 34.5 ± 0.8, 103.7 ± 2.8, and 26.6 ± 0.7 ppbv, respectively, were identified as the major VOC mixture at all times of the day around the receptor site. As the toxic air pollutant, the concentrations of DMF in air samples were found exceeding the ambient standard despite the path-average effect of OP-FTIR upon concentration levels. The PCA data identified three major emission sources, including PU coating, chemical packaging, and lithographic printing industries. Applying instrumental measurement and statistical modeling, this study has established a systematic approach for locating emission sources. Statistical modeling (PCA) plays an important role in reducing dimensionality of a large measured dataset and identifying underlying emission sources. Instrumental measurement, however, helps verify the outcomes of the statistical modeling. The field study has demonstrated the feasibility of using multi-path OP-FTIR measurement. The wind data incorporating with the statistical modeling (PCA) may successfully identify the major emission source in a complex industrial district.

Ozanimod (RPC1063), a selective S1PR1 and S1PR5 modulator, reduces chronic inflammation and alleviates kidney pathology in murine systemic lupus erythematosus.

PubMed

Taylor Meadows, Kristen R; Steinberg, Marcos W; Clemons, Bryan; Stokes, Matthew E; Opiteck, Gregory J; Peach, Robert; Scott, Fiona L

2018-01-01

Ozanimod (RPC1063) is a specific and potent small molecule modulator of the sphingosine 1-phosphate receptor 1 (S1PR1) and receptor 5 (S1PR5), which has shown therapeutic benefit in clinical trials of relapsing multiple sclerosis and ulcerative colitis. Ozanimod and its active metabolite, RP-101075, exhibit a similar specificity profile at the S1P receptor family in vitro and pharmacodynamic profile in vivo. The NZBWF1 mouse model was used in therapeutic dosing mode to assess the potential benefit of ozanimod and RP-101075 in an established animal model of systemic lupus erythematosus. Compared with vehicle-treated animals, ozanimod and RP-101075 reduced proteinuria over the duration of the study and serum blood urea nitrogen at termination. Additionally, ozanimod and RP-101075 reduced kidney disease in a dose-dependent manner, as measured by histological assessment of mesangial expansion, endo- and exo-capillary proliferation, interstitial infiltrates and fibrosis, glomerular deposits, and tubular atrophy. Further exploration into gene expression changes in the kidney demonstrate that RP-101075 also significantly reduced expression of fibrotic and immune-related genes in the kidneys. Of note, RP-101075 lowered the number of plasmacytoid dendritic cells, a major source of interferon alpha in lupus patients, and reduced all B and T cell subsets in the spleen. Given the efficacy demonstrated by ozanimod and its metabolite RP-101075 in the NZBWF1 preclinical animal model, ozanimod may warrant clinical evaluation as a potential treatment for systemic lupus erythematosus.

Ozanimod (RPC1063), a selective S1PR1 and S1PR5 modulator, reduces chronic inflammation and alleviates kidney pathology in murine systemic lupus erythematosus

PubMed Central

Taylor Meadows, Kristen R.; Steinberg, Marcos W.; Clemons, Bryan; Stokes, Matthew E.; Opiteck, Gregory J.; Peach, Robert; Scott, Fiona L.

2018-01-01

Ozanimod (RPC1063) is a specific and potent small molecule modulator of the sphingosine 1-phosphate receptor 1 (S1PR1) and receptor 5 (S1PR5), which has shown therapeutic benefit in clinical trials of relapsing multiple sclerosis and ulcerative colitis. Ozanimod and its active metabolite, RP-101075, exhibit a similar specificity profile at the S1P receptor family in vitro and pharmacodynamic profile in vivo. The NZBWF1 mouse model was used in therapeutic dosing mode to assess the potential benefit of ozanimod and RP-101075 in an established animal model of systemic lupus erythematosus. Compared with vehicle-treated animals, ozanimod and RP-101075 reduced proteinuria over the duration of the study and serum blood urea nitrogen at termination. Additionally, ozanimod and RP-101075 reduced kidney disease in a dose-dependent manner, as measured by histological assessment of mesangial expansion, endo- and exo-capillary proliferation, interstitial infiltrates and fibrosis, glomerular deposits, and tubular atrophy. Further exploration into gene expression changes in the kidney demonstrate that RP-101075 also significantly reduced expression of fibrotic and immune-related genes in the kidneys. Of note, RP-101075 lowered the number of plasmacytoid dendritic cells, a major source of interferon alpha in lupus patients, and reduced all B and T cell subsets in the spleen. Given the efficacy demonstrated by ozanimod and its metabolite RP-101075 in the NZBWF1 preclinical animal model, ozanimod may warrant clinical evaluation as a potential treatment for systemic lupus erythematosus. PMID:29608575

Pharmacokinetic–pharmacodynamic modelling in anaesthesia

PubMed Central

Gambús, Pedro L; Trocóniz, Iñaki F

2015-01-01

Anaesthesiologists adjust drug dosing, administration system and kind of drug to the characteristics of the patient. They then observe the expected response and adjust dosing to the specific requirements according to the difference between observed response, expected response and the context of the surgery and the patient. The approach above can be achieved because on one hand quantification technology has made significant advances allowing the anaesthesiologist to measure almost any effect by using noninvasive, continuous measuring systems. On the other the knowledge on the relations between dosing, concentration, biophase dynamics and effect as well as detection of variability sources has been achieved as being the benchmark specialty for pharmacokinetic–pharmacodynamic (PKPD) modelling. The aim of the review is to revisit the most common PKPD models applied in the field of anaesthesia (i.e. effect compartmental, turnover, drug–receptor binding and drug interaction models) through representative examples. The effect compartmental model has been widely used in this field and there are multiple applications and examples. The use of turnover models has been limited mainly to describe respiratory effects. Similarly, cases in which the dissociation process of the drug–receptor complex is slow compared with other processes relevant to the time course of the anaesthetic effect are not frequent in anaesthesia, where in addition to a rapid onset, a fast offset of the response is required. With respect to the characterization of PD drug interactions different response surface models are discussed. Relevant applications that have changed the way modern anaesthesia is practiced are also provided. PMID:24251846

Sources and processes contributing to nitrogen deposition: an adjoint model analysis applied to biodiversity hotspots worldwide.

PubMed

Paulot, Fabien; Jacob, Daniel J; Henze, Daven K

2013-04-02

Anthropogenic enrichment of reactive nitrogen (Nr) deposition is an ecological concern. We use the adjoint of a global 3-D chemical transport model (GEOS-Chem) to identify the sources and processes that control Nr deposition to an ensemble of biodiversity hotspots worldwide and two U.S. national parks (Cuyahoga and Rocky Mountain). We find that anthropogenic sources dominate deposition at all continental sites and are mainly regional (less than 1000 km) in origin. In Hawaii, Nr supply is controlled by oceanic emissions of ammonia (50%) and anthropogenic sources (50%), with important contributions from Asia and North America. Nr deposition is also sensitive in complicated ways to emissions of SO2, which affect Nr gas-aerosol partitioning, and of volatile organic compounds (VOCs), which affect oxidant concentrations and produce organic nitrate reservoirs. For example, VOC emissions generally inhibit deposition of locally emitted NOx but significantly increase Nr deposition downwind. However, in polluted boreal regions, anthropogenic VOC emissions can promote Nr deposition in winter. Uncertainties in chemical rate constants for OH + NO2 and NO2 hydrolysis also complicate the determination of source-receptor relationships for polluted sites in winter. Application of our adjoint sensitivities to the representative concentration pathways (RCPs) scenarios for 2010-2050 indicates that future decreases in Nr deposition due to NOx emission controls will be offset by concurrent increases in ammonia emissions from agriculture.

Source contributions to PM10 and arsenic concentrations in Central Chile using positive matrix factorization

NASA Astrophysics Data System (ADS)

Hedberg, Emma; Gidhagen, Lars; Johansson, Christer

Sampling of particles (PM10) was conducted during a one-year period at two rural sites in Central Chile, Quillota and Linares. The samples were analyzed for elemental composition. The data sets have undergone source-receptor analyses in order to estimate the sources and their abundance's in the PM10 size fraction, by using the factor analytical method positive matrix factorization (PMF). The analysis showed that PM10 was dominated by soil resuspension at both sites during the summer months, while during winter traffic dominated the particle mass at Quillota and local wood burning dominated the particle mass at Linares. Two copper smelters impacted the Quillota station, and contributed to 10% and 16% of PM10 as an average during summer and winter, respectively. One smelter impacted Linares by 8% and 19% of PM10 in the summer and winter, respectively. For arsenic the two smelters accounted for 87% of the monitored arsenic levels at Quillota and at Linares one smelter contributed with 72% of the measured mass. In comparison with PMF, the use of a dispersion model tended to overestimate the smelter contribution to arsenic levels at both sites. The robustness of the PMF model was tested by using randomly reduced data sets, where 85%, 70%, 50% and 33% of the samples were included. In this way the ability of the model to reconstruct the sources initially found by the original data set could be tested. On average for all sources the relative standard deviation increased from 7% to 25% for the variables identifying the sources, when decreasing the data set from 85% to 33% of the samples, indicating that the solution initially found was very stable to begin with. But it was also noted that sources due to industrial or combustion processes were more sensitive for the size of the data set, compared to the natural sources as local soil and sea spray sources.

Source apportionment of PM2.5 organic carbon in the San Joaquin Valley using monthly and daily observations and meteorological clustering.

PubMed

Skiles, Matthew J; Lai, Alexandra M; Olson, Michael R; Schauer, James J; de Foy, Benjamin

2018-06-01

Two hundred sixty-three fine particulate matter (PM 2.5 ) samples collected on 3-day intervals over a 14-month period at two sites in the San Joaquin Valley (SJV) were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC), and organic molecular markers. A unique source profile library was applied to a chemical mass balance (CMB) source apportionment model to develop monthly and seasonally averaged source apportionment results. Five major OC sources were identified: mobile sources, biomass burning, meat smoke, vegetative detritus, and secondary organic carbon (SOC), as inferred from OC not apportioned by CMB. The SOC factor was the largest source contributor at Fresno and Bakersfield, contributing 44% and 51% of PM mass, respectively. Biomass burning was the only source with a statistically different average mass contribution (95% CI) between the two sites. Wintertime peaks of biomass burning, meat smoke, and total OC were observed at both sites, with SOC peaking during the summer months. Exceptionally strong seasonal variation in apportioned meat smoke mass could potentially be explained by oxidation of cholesterol between source and receptor and trends in wind transport outlined in a Residence Time Analysis (RTA). Fast moving nighttime winds prevalent during warmer months caused local emissions to be replaced by air mass transported from the San Francisco Bay Area, consisting of mostly diluted, oxidized concentrations of molecular markers. Good agreement was observed between SOC derived from the CMB model and from non-biomass burning WSOC mass, suggesting the CMB model is sufficiently accurate to assist in policy development. In general, uncertainty in monthly mass values derived from daily CMB apportionments were lower than that of CMB results produced with monthly marker composites, further validating daily sampling methodologies. Strong seasonal trends were observed for biomass and meat smoke OC apportionment, and monthly mass averages had lowest uncertainty when derived from daily CMB apportionments. Copyright © 2018 Elsevier Ltd. All rights reserved.

Size distribution, directional source contributions and pollution status of PM from Chengdu, China during a long-term sampling campaign.

PubMed

Shi, Guo-Liang; Tian, Ying-Ze; Ma, Tong; Song, Dan-Lin; Zhou, Lai-Dong; Han, Bo; Feng, Yin-Chang; Russell, Armistead G

2017-06-01

Long-term and synchronous monitoring of PM 10 and PM 2.5 was conducted in Chengdu in China from 2007 to 2013. The levels, variations, compositions and size distributions were investigated. The sources were quantified by two-way and three-way receptor models (PMF2, ME2-2way and ME2-3way). Consistent results were found: the primary source categories contributed 63.4% (PMF2), 64.8% (ME2-2way) and 66.8% (ME2-3way) to PM 10 , and contributed 60.9% (PMF2), 65.5% (ME2-2way) and 61.0% (ME2-3way) to PM 2.5 . Secondary sources contributed 31.8% (PMF2), 32.9% (ME2-2way) and 31.7% (ME2-3way) to PM 10 , and 35.0% (PMF2), 33.8% (ME2-2way) and 36.0% (ME2-3way) to PM 2.5 . The size distribution of source categories was estimated better by the ME2-3way method. The three-way model can simultaneously consider chemical species, temporal variability and PM sizes, while a two-way model independently computes datasets of different sizes. A method called source directional apportionment (SDA) was employed to quantify the contributions from various directions for each source category. Crustal dust from east-north-east (ENE) contributed the highest to both PM 10 (12.7%) and PM 2.5 (9.7%) in Chengdu, followed by the crustal dust from south-east (SE) for PM 10 (9.8%) and secondary nitrate & secondary organic carbon from ENE for PM 2.5 (9.6%). Source contributions from different directions are associated with meteorological conditions, source locations and emission patterns during the sampling period. These findings and methods provide useful tools to better understand PM pollution status and to develop effective pollution control strategies. Copyright © 2016. Published by Elsevier B.V.

The cubic ternary complex receptor-occupancy model. III. resurrecting efficacy.

PubMed

Weiss, J M; Morgan, P H; Lutz, M W; Kenakin, T P

1996-08-21

Early work in pharmacology characterized the interaction of receptors and ligands in terms of two parameters, affinity and efficacy, an approach we term the bipartite view. A precise formulation of efficacy only exists for very simple pharmacological models. Here we extend the notion of efficacy to models that incorporate receptor activation and G-protein coupling. Using the cubic ternary complex model, we show that efficacy is not purely a property of the ligand-receptor interaction; it also depends upon the distributional details of the receptor species in the native receptor ensemble. This suggests a distinction between what we call potential efficacy (a vector) and realized efficacy (a scalar). To each receptor species in the native receptor ensemble we assign a part-worth utility; taken together these utilities comprise the potential efficacy vector. Realized efficacy is the expectation of these part-worth utilities with respect to the frequency distribution of receptor species in the native receptor ensemble. In the parlance of statistical decision theory, the binding of a ligand to a receptor ensemble is a random prospect and realized efficacy is the utility of this prospect. We explore the implications that our definition of efficacy has for understanding agonism and in assessing the legitimacy of the bipartite view in pharmacology.

Structure-activity relationships of seco-prezizaane and picrotoxane/picrodendrane terpenoids by Quasar receptor-surface modeling.

PubMed

Schmidt, Thomas J; Gurrath, Marion; Ozoe, Yoshihisa

2004-08-01

The seco-prezizaane-type sesquiterpenes pseudoanisatin and parviflorolide from Illicium are noncompetitive antagonists at housefly (Musca domestica) gamma-aminobutyric acid (GABA) receptors. They show selectivity toward the insect receptor and thus represent new leads toward selective insecticides. Based on the binding data for 13 seco-prezizaane terpenoids and 17 picrotoxane and picrodendrane-type terpenoids to housefly and rat GABA receptors, a QSAR study was conducted by quasi-atomistic receptor-surface modeling (Quasar). The resulting models provide insight into the structural basis of selectivity and properties of the binding sites at GABA receptor-coupled chloride channels of insects and mammals.

CB1 receptor mediated analgesia from the Nucleus Reticularis Gigantocellularis pars alpha is activated in an animal model of neuropathic pain.

PubMed

Monhemius, R; Azami, J; Green, D L; Roberts, M H

2001-07-20

Cannabinoids are known to suppress responses to noxious stimulation in animals and man. Recent research has suggested a role for endogenous cannabinoids in the descending inhibition of dorsal horn cells via a supraspinal site of action. We have recently demonstrated [J. Physiol. 506(2) (1998) 459] that the nucleus reticularis gigantocellularis pars alpha (GiA) is a major source of such descending modulation, and importantly, that this system is activated in response to noxious stimulation. We have therefore investigated the role of CB1 receptor activation in mediating the antinociceptive effects of activation of GiA in models of acute and chronic pain. Microinjections (0.5 microl 60% DMSO) of either WIN 55,212-2 (5 microg, selective CB1 agonist), SR141716A (50 microg, competitive CB1 antagonist), both compounds together, or vehicle alone into GiA were performed prior to these tests in a randomised, blind manner. In control animals, WIN 55,212-2 markedly increased withdrawal latencies in the tail flick test and reduced responses to subcutaneous formalin. These effects were blocked by co-administration of SR141716A. These data suggest that activation of cannabinoid CB1 receptor subtypes in GiA leads to behavioural analgesia. In animals with partial sciatic nerve ligation, microinjection of drugs and injection of formalin were performed contralaterally to the site of ligation. Partial sciatic nerve ligation significantly reduced behavioural responses to contralaterally applied formalin. Microinjection of SR141716A to GiA reversed this inhibition of responses to formalin in animals with partial sciatic nerve ligation. These data provide evidence that endogenous CB1 receptor ligands are involved in GiA mediated antinociception, and that this system is important for the modulation of nociceptive transmission in an animal model of chronic neuropathic pain.

Customizing G Protein-coupled receptor models for structure-based virtual screening.

PubMed

de Graaf, Chris; Rognan, Didier

2009-01-01

This review will focus on the construction, refinement, and validation of G Protein-coupled receptor models for the purpose of structure-based virtual screening. Practical tips and tricks derived from concrete modeling and virtual screening exercises to overcome the problems and pitfalls associated with the different steps of the receptor modeling workflow will be presented. These examples will not only include rhodopsin-like (class A), but also secretine-like (class B), and glutamate-like (class C) receptors. In addition, the review will present a careful comparative analysis of current crystal structures and their implication on homology modeling. The following themes will be discussed: i) the use of experimental anchors in guiding the modeling procedure; ii) amino acid sequence alignments; iii) ligand binding mode accommodation and binding cavity expansion; iv) proline-induced kinks in transmembrane helices; v) binding mode prediction and virtual screening by receptor-ligand interaction fingerprint scoring; vi) extracellular loop modeling; vii) virtual filtering schemes. Finally, an overview of several successful structure-based screening shows that receptor models, despite structural inaccuracies, can be efficiently used to find novel ligands.

Exploration of N-arylpiperazine Binding Sites of D2 Dopaminergic Receptor.

PubMed

Soskic, Vukic; Sukalovic, Vladimir; Kostic-Rajacic, Sladjana

2015-01-01

The crystal structures of the D3 dopamine receptor and several other G-protein coupled receptors (GPCRs) were published in recent times. Those 3D structures are used by us and other scientists as a template for the homology modeling and ligand docking analysis of related GPCRs. Our main scientific interest lies in the field of pharmacologically active N-arylpiperazines that exhibit antipsychotic and/or antidepressant properties, and as such are dopaminergic and serotonergic receptor ligands. In this short review article we are presenting synthesis and biological data on the new N-arylpipereazine as well our results on molecular modeling of the interactions of those N-arylpiperazines with the model of D2 dopamine receptors. To obtain that model the crystal structure of the D3 dopamine receptor was used. Our results show that the N-arylpiperazines binding site consists of two pockets: one is the orthosteric binding site where the N-arylpiperazine part of the ligand is docked and the second is a non-canonical accessory binding site for N-arylpipereazine that is formed by a second extracellular loop (ecl2) of the receptor. Until now, the structure of this receptor region was unresolved in crystal structure analyses of the D3 dopamine receptor. To get a more complete picture of the ligand - receptor interaction, DFT quantum mechanical calculations on N-arylpiperazine were performed and the obtained models were used to examine those interactions.

SU-G-IeP3-11: On the Utility of Pixel Variance to Characterize Noise for Image Receptors of Digital Radiography Systems

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

Finley, C; Dave, J

Purpose: To characterize noise for image receptors of digital radiography systems based on pixel variance. Methods: Nine calibrated digital image receptors associated with nine new portable digital radiography systems (Carestream Health, Inc., Rochester, NY) were used in this study. For each image receptor, thirteen images were acquired with RQA5 beam conditions for input detector air kerma ranging from 0 to 110 µGy, and linearized ‘For Processing’ images were extracted. Mean pixel value (MPV), standard deviation (SD) and relative noise (SD/MPV) were obtained from each image using ROI sizes varying from 2.5×2.5 to 20×20 mm{sup 2}. Variance (SD{sup 2}) was plottedmore » as a function of input detector air kerma and the coefficients of the quadratic fit were used to derive structured, quantum and electronic noise coefficients. Relative noise was also fitted as a function of input detector air kerma to identify noise sources. The fitting functions used least-squares approach. Results: The coefficient of variation values obtained using different ROI sizes was less than 1% for all the images. The structured, quantum and electronic coefficients obtained from the quadratic fit of variance (r>0.97) were 0.43±0.10, 3.95±0.27 and 2.89±0.74 (mean ± standard deviation), respectively, indicating that overall the quantum noise was the dominant noise source. However, for one system electronic noise coefficient (3.91) was greater than quantum noise coefficient (3.56) indicating electronic noise to be dominant. Using relative noise values, the power parameter of the fitting equation (|r|>0.93) showed a mean and standard deviation of 0.46±0.02. A 0.50 value for this power parameter indicates quantum noise to be the dominant noise source whereas values around 0.50 indicate presence of other noise sources. Conclusion: Characterizing noise from pixel variance assists in identifying contributions from various noise sources that, eventually, may affect image quality. This approach may be integrated during periodic quality assessments of digital image receptors.« less

Evaluation of Intercontinental Transport of Ozone Using Full-tagged, Tagged-N and Sensitivity Methods

NASA Astrophysics Data System (ADS)

Guo, Y.; Liu, J.; Mauzerall, D. L.; Emmons, L. K.; Horowitz, L. W.; Fan, S.; Li, X.; Tao, S.

2014-12-01

Long-range transport of ozone is of great concern, yet the source-receptor relationships derived previously depend strongly on the source attribution techniques used. Here we describe a new tagged ozone mechanism (full-tagged), the design of which seeks to take into account the combined effects of emissions of ozone precursors, CO, NOx and VOCs, from a particular source, while keeping the current state of chemical equilibrium unchanged. We label emissions from the target source (A) and background (B). When two species from A and B sources react with each other, half of the resulting products are labeled A, and half B. Thus the impact of a given source on downwind regions is recorded through tagged chemistry. We then incorporate this mechanism into the Model for Ozone and Related chemical Tracers (MOZART-4) to examine the impact of anthropogenic emissions within North America, Europe, East Asia and South Asia on ground-level ozone downwind of source regions during 1999-2000. We compare our results with two previously used methods -- the sensitivity and tagged-N approaches. The ozone attributed to a given source by the full-tagged method is more widely distributed spatially, but has weaker seasonal variability than that estimated by the other methods. On a seasonal basis, for most source/receptor pairs, the full-tagged method estimates the largest amount of tagged ozone, followed by the sensitivity and tagged-N methods. In terms of trans-Pacific influence of ozone pollution, the full-tagged method estimates the strongest impact of East Asian (EA) emissions on the western U.S. (WUS) in MAM and JJA (~3 ppbv), which is substantially different in magnitude and seasonality from tagged-N and sensitivity studies. This difference results from the full-tagged method accounting for the maintenance of peroxy radicals (e.g., CH3O2, CH3CO3, and HO2), in addition to NOy, as effective reservoirs of EA source impact across the Pacific, allowing for a significant contribution to ozone formation over WUS (particularly in summer). Thus, the full-tagged method, with its clear discrimination of source and background contributions on a per-reaction basis, provides unique insights into the critical role of VOCs (and additional reactive nitrogen species) in determining the nonlinear inter-continental influence of ozone pollution.

Dimensionality of Motion and Binding Valency Govern Receptor-Ligand Kinetics As Revealed by Agent-Based Modeling.

PubMed

Lehnert, Teresa; Figge, Marc Thilo

2017-01-01

Mathematical modeling and computer simulations have become an integral part of modern biological research. The strength of theoretical approaches is in the simplification of complex biological systems. We here consider the general problem of receptor-ligand binding in the context of antibody-antigen binding. On the one hand, we establish a quantitative mapping between macroscopic binding rates of a deterministic differential equation model and their microscopic equivalents as obtained from simulating the spatiotemporal binding kinetics by stochastic agent-based models. On the other hand, we investigate the impact of various properties of B cell-derived receptors-such as their dimensionality of motion, morphology, and binding valency-on the receptor-ligand binding kinetics. To this end, we implemented an algorithm that simulates antigen binding by B cell-derived receptors with a Y-shaped morphology that can move in different dimensionalities, i.e., either as membrane-anchored receptors or as soluble receptors. The mapping of the macroscopic and microscopic binding rates allowed us to quantitatively compare different agent-based model variants for the different types of B cell-derived receptors. Our results indicate that the dimensionality of motion governs the binding kinetics and that this predominant impact is quantitatively compensated by the bivalency of these receptors.

Progesterone from the Cumulus Cells Is the Sperm Chemoattractant Secreted by the Rabbit Oocyte Cumulus Complex

PubMed Central

Guidobaldi, Héctor Alejandro; Teves, María Eugenia; Uñates, Diego Rafael; Anastasía, Agustín; Giojalas, Laura Cecilia

2008-01-01

Sperm chemotaxis in mammals have been identified towards several female sources as follicular fluid (FF), oviduct fluid, and conditioned medium from the cumulus oophorus (CU) and the oocyte (O). Though several substances were confirmed as sperm chemoattractant, Progesterone (P) seems to be the best chemoattractant candidate, because: 1) spermatozoa express a cell surface P receptor, 2) capacitated spermatozoa are chemotactically attracted in vitro by gradients of low quantities of P; 3) the CU cells produce and secrete P after ovulation; 4) a gradient of P may be kept stable along the CU; and 5) the most probable site for sperm chemotaxis in vivo could be near and/or inside the CU. The aim of this study was to verify whether P is the sperm chemoattractant secreted by the rabbit oocyte-cumulus complex (OCC) in the rabbit, as a mammalian animal model. By means of videomicroscopy and computer image analysis we observed that only the CU are a stable source of sperm attractants. The CU produce and secrete P since the hormone was localized inside these cells by immunocytochemistry and in the conditioned medium by enzyme immunoassay. In addition, rabbit spermatozoa express a cell surface P receptor detected by western blot and localized over the acrosomal region by immunocytochemistry. To confirm that P is the sperm chemoattractant secreted by the CU, the sperm chemotactic response towards the OCC conditioned medium was inhibited by three different approaches: P from the OCC conditioned medium was removed with an anti-P antibody, the attractant gradient of the OCC conditioned medium was disrupted by a P counter gradient, and the sperm P receptor was blocked with a specific antibody. We concluded that only the CU but not the oocyte secretes P, and the latter chemoattract spermatozoa by means of a cell surface receptor. Our findings may be of interest in assisted reproduction procedures in humans, animals of economic importance and endangered species. PMID:18725941

The Biogenic Amine Tyramine and its Receptor (AmTyr1) in Olfactory Neuropils in the Honey Bee (Apis mellifera) Brain

PubMed Central

Sinakevitch, Irina T.; Daskalova, Sasha M.; Smith, Brian H.

2017-01-01

This article describes the cellular sources for tyramine and the cellular targets of tyramine via the Tyramine Receptor 1 (AmTyr1) in the olfactory learning and memory neuropils of the honey bee brain. Clusters of approximately 160 tyramine immunoreactive neurons are the source of tyraminergic fibers with small varicosities in the optic lobes, antennal lobes, lateral protocerebrum, mushroom body (calyces and gamma lobes), tritocerebrum and subesophageal ganglion (SEG). Our tyramine mapping study shows that the primary sources of tyramine in the antennal lobe and calyx of the mushroom body are from at least two Ventral Unpaired Median neurons (VUMmd and VUMmx) with cell bodies in the SEG. To reveal AmTyr1 receptors in the brain, we used newly characterized anti-AmTyr1 antibodies. Immunolocalization studies in the antennal lobe with anti-AmTyr1 antibodies showed that the AmTyr1 expression pattern is mostly in the presynaptic sites of olfactory receptor neurons (ORNs). In the mushroom body calyx, anti-AmTyr1 mapped the presynaptic sites of uniglomerular Projection Neurons (PNs) located primarily in the microglomeruli of the lip and basal ring calyx area. Release of tyramine/octopamine from VUM (md and mx) neurons in the antennal lobe and mushroom body calyx would target AmTyr1 expressed on ORN and uniglomerular PN presynaptic terminals. The presynaptic location of AmTyr1, its structural similarity with vertebrate alpha-2 adrenergic receptors, and previous pharmacological evidence suggests that it has an important role in the presynaptic inhibitory control of neurotransmitter release. PMID:29114209

Application of chemometric analysis and self Organizing Map-Artificial Neural Network as source receptor modeling for metal speciation in river sediment.

PubMed

Pandey, Mayank; Pandey, Ashutosh Kumar; Mishra, Ashutosh; Tripathi, B D

2015-09-01

Present study deals with the river Ganga water quality and its impact on metal speciation in its sediments. Concentration of physico-chemical parameters was highest in summer season followed by winter and lowest in rainy season. Metal speciation study in river sediments revealed that exchangeable, reducible and oxidizable fractions were dominant in all the studied metals (Cr, Ni, Cu, Zn, Cd, Pb) except Mn and Fe. High pollution load index (1.64-3.89) recommends urgent need of mitigation measures. Self-organizing Map-Artificial Neural Network (SOM-ANN) was applied to the data set for the prediction of major point sources of pollution in the river Ganga. Copyright © 2015 Elsevier Ltd. All rights reserved.

Saccharomyces cerevisiae Produces a Yeast Substance that Exhibits Estrogenic Activity in Mammalian Systems

NASA Astrophysics Data System (ADS)

Feldman, David; Stathis, Peter A.; Hirst, Margaret A.; Price Stover, E.; Do, Yung S.; Kurz, Walter

1984-06-01

Partially purified lipid extracts of Saccharomyces cerevisiae contain a substance that displaces tritiated estradiol from rat uterine cytosol estrogen receptors. The yeast product induces estrogenic bioresponses in mammalian systems as measured by induction of progesterone receptors in cultured MCF-7 human breast cancer cells and by a uterotrophic response and progesterone receptor induction after administration to ovariectomized mice. The findings raise the possibility that bakers' yeast may be a source of environmental estrogens.

Sources and atmospheric transformations of semivolatile organic aerosols

NASA Astrophysics Data System (ADS)

Grieshop, Andrew P.

Fine atmospheric particulate matter (PM2.5) is associated with increased mortality, a fact which led the EPA to promulgate a National Ambient Air Quality Standard (NAAQS) for PM2.5 in 1997. Organic material contributes a substantial portion of the PM2.5 mass; organic aerosols (OA) are either directly emitted (primary OA or POA) or formed via the atmospheric oxidation of volatile precursor compounds as secondary OA (SOA). The relative contributions of POA and SOA to atmospheric OA are uncertain, as are the contributions from various source classes (e.g. motor vehicles, biomass burning). This dissertation first assesses the importance of organic PM within the context of current US air pollution regulations. Most control efforts to date have focused on the inorganic component of PM. Although growing evidence strongly implicates OA, especially which from motor vehicles, in the health effects of PM, uncertain and complex source-receptor relationships for OA discourage its direct control for NAAQS compliance. Analysis of both ambient data and chemical transport modeling results indicate that OA does not play a dominant role in NAAQS violations in most areas of the country under current and likely future regulations. Therefore, new regulatory approaches will likely be required to directly address potential health impacts associated with OA. To help develop the scientific understanding needed to better regulate OA, this dissertation examined the evolution of organic aerosol emitted by combustion systems. The current conceptual model of POA is that it is non-volatile and non-reactive. Both of these assumptions were experimental investigated in this dissertation. Novel dilution measurements were carried out to investigate the gas-particle partitioning of OA at atmospherically-relevant conditions. The results demonstrate that POA from combustion sources is semivolatile. Therefore its gas-particle partitioning depends on temperature and atmospheric concentrations; heating and dilution both cause it to evaporate. Gas-particle partitioning was parameterized using absorptive partitioning theory and the volatility basis-set framework. The dynamics of particle evaporation proved to be much slower than expected and measurements of aerosol composition indicate that particle composition varies with partitioning. These findings have major implications for the measurement and modeling of POA from combustion sources. Source tests need to be conducted at atmospheric concentrations and temperatures. Upon entering the atmosphere, organic aerosol emissions are aged via photochemical reactions. Experiments with dilute wood-smoke demonstrate the dramatic evolution these emissions undergo within hours of emission. Aging produced substantial new OA (doubling or tripling OA levels within hours) and changed particle composition and volatility. These changes are consistent with model predictions based on the partitioning and aging (via gas-phase photochemistry) of semi-volatile species represented with the basis-set framework. Aging of wood-smoke OA made created a much more oxygenated aerosol and formed material spectrally similar to oxygenated OA found widely in the atmosphere. The oxygenated aerosol is also similar that formed with similar experiments conducted with diesel engine emissions. Therefore, aging of emissions from diverse sources may produce chemically similar OA, complicating the establishment of robust source-receptor relationships.

Mu-Opioid (MOP) receptor mediated G-protein signaling is impaired in specific brain regions in a rat model of schizophrenia.

PubMed

Szűcs, Edina; Büki, Alexandra; Kékesi, Gabriella; Horváth, Gyöngyi; Benyhe, Sándor

2016-04-21

Schizophrenia is a complex mental health disorder. Clinical reports suggest that many patients with schizophrenia are less sensitive to pain than other individuals. Animal models do not interpret schizophrenia completely, but they can model a number of symptoms of the disease, including decreased pain sensitivities and increased pain thresholds of various modalities. Opioid receptors and endogenous opioid peptides have a substantial role in analgesia. In this biochemical study we investigated changes in the signaling properties of the mu-opioid (MOP) receptor in different brain regions, which are involved in the pain transmission, i.e., thalamus, olfactory bulb, prefrontal cortex and hippocampus. Our goal was to compare the transmembrane signaling mediated by MOP receptors in control rats and in a recently developed rat model of schizophrenia. Regulatory G-protein activation via MOP receptors were measured in [(35)S]GTPγS binding assays in the presence of a highly selective MOP receptor peptide agonist, DAMGO. It was found that the MOP receptor mediated activation of G-proteins was substantially lower in membranes prepared from the 'schizophrenic' model rats than in control animals. The potency of DAMGO to activate MOP receptor was also decreased in all brain regions studied. Taken together in our rat model of schizophrenia, MOP receptor mediated G-proteins have a reduced stimulatory activity compared to membrane preparations taken from control animals. The observed distinct changes of opioid receptor functions in different areas of the brain do not explain the augmented nociceptive threshold described in these animals. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Multiscale Modeling of Virus Entry via Receptor-Mediated Endocytosis

NASA Astrophysics Data System (ADS)

Liu, Jin

2012-11-01

Virus infections are ubiquitous and remain major threats to human health worldwide. Viruses are intracellular parasites and must enter host cells to initiate infection. Receptor-mediated endocytosis is the most common entry pathway taken by viruses, the whole process is highly complex and dictated by various events, such as virus motions, membrane deformations, receptor diffusion and ligand-receptor reactions, occurring at multiple length and time scales. We develop a multiscale model for virus entry through receptor-mediated endocytosis. The binding of virus to cell surface is based on a mesoscale three dimensional stochastic adhesion model, the internalization (endocytosis) of virus and cellular membrane deformation is based on the discretization of Helfrich Hamiltonian in a curvilinear space using Monte Carlo method. The multiscale model is based on the combination of these two models. We will implement this model to study the herpes simplex virus entry into B78 cells and compare the model predictions with experimental measurements.

An overview of particulate emissions from residential biomass combustion

NASA Astrophysics Data System (ADS)

Vicente, E. D.; Alves, C. A.

2018-01-01

Residential biomass burning has been pointed out as one of the largest sources of fine particles in the global troposphere with serious impacts on air quality, climate and human health. Quantitative estimations of the contribution of this source to the atmospheric particulate matter levels are hard to obtain, because emission factors vary greatly with wood type, combustion equipment and operating conditions. Updated information should improve not only regional and global biomass burning emission inventories, but also the input for atmospheric models. In this work, an extensive tabulation of particulate matter emission factors obtained worldwide is presented and critically evaluated. Existing quantifications and the suitability of specific organic markers to assign the input of residential biomass combustion to the ambient carbonaceous aerosol are also discussed. Based on these organic markers or other tracers, estimates of the contribution of this sector to observed particulate levels by receptor models for different regions around the world are compiled. Key areas requiring future research are highlighted and briefly discussed.

DockoMatic 2.0: high throughput inverse virtual screening and homology modeling.

PubMed

Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T; McDougal, Owen M; Andersen, Timothy L

2013-08-26

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly graphical user interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to (1) conduct high throughput inverse virtual screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELER programs and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education.

Structural Analysis of Chemokine Receptor–Ligand Interactions

PubMed Central

2017-01-01

This review focuses on the construction and application of structural chemokine receptor models for the elucidation of molecular determinants of chemokine receptor modulation and the structure-based discovery and design of chemokine receptor ligands. A comparative analysis of ligand binding pockets in chemokine receptors is presented, including a detailed description of the CXCR4, CCR2, CCR5, CCR9, and US28 X-ray structures, and their implication for modeling molecular interactions of chemokine receptors with small-molecule ligands, peptide ligands, and large antibodies and chemokines. These studies demonstrate how the integration of new structural information on chemokine receptors with extensive structure–activity relationship and site-directed mutagenesis data facilitates the prediction of the structure of chemokine receptor–ligand complexes that have not been crystallized. Finally, a review of structure-based ligand discovery and design studies based on chemokine receptor crystal structures and homology models illustrates the possibilities and challenges to find novel ligands for chemokine receptors. PMID:28165741

Association between p75 neurotrophin receptor gene expression and cell apoptosis in tissues surrounding hematomas in rat models of intracerebral hemorrhage.

PubMed

He, Baixiang; Bao, Gang; Guo, Shiwen; Xu, Gaofeng; Li, Qi; Wang, Ning

2012-03-15

Animal models of intracerebral hemorrhage were established by injection of autologous blood into the caudate nucleus in rats. Cell apoptosis was measured by flow cytometry and immunohistochemical staining of the p75 neurotrophin receptor. p75 neurotrophin receptor protein was detected by immunohistochemistry. p75 neurotrophin receptor mRNA was examined by quantitative real-time polymerase chain reactions. At 24 hours after modeling, cellular apoptosis occured around hematoma with upregulation of p75 neurotrophin receptor protein and mRNA was observed, which directly correlated to apoptosis. This observation indicated that p75 neurotrophin receptor upregulation was associated with cell apoptosis around hematomas after intracerebral hemorrhage.

Further evidence of no linkage between schizophrenia and the dopamine D{sub 3} receptor gene locus

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

Nanko, S.; Fukuda, R.; Hattori, M.

The dopamine hypothesis of schizophrenia proposed that dopaminergic pathways are involved in the etiology of the disease. In particular, interest among psychiatrists has focused on the D{sub 2} receptor because of its affinity to antipsychotic drugs. Recently a new dopamine receptor gene has been cloned and named the dopamine D{sub 3} receptor. The D{sub 3} receptor is a potential site for antipsychotic drug action and may be involved in the pathophysiology of schizophrenia. We have carried out a linkage study between the susceptibility gene for schizophrenia and polymorphism of the dopamine D{sub 3} receptor gene in two Japanese pedigrees. Themore » LOD scores were negative for all genetic models and for all affective status at a recombination fraction {theta} = 0. Linkage of DRD{sub 3} has been excluded for the model 1 (dominant model) and the model 3 (recessive model). The LOD score was -3.43 at {theta} = 0 for model 1 (dominant model) and broad definition of affected status. These results were consistent with previous studies. 19 refs., 2 figs., 3 tabs.« less

Source apportionment of heavy metals in agricultural soil based on PMF: A case study in Hexi Corridor, northwest China.

PubMed

Guan, Qingyu; Wang, Feifei; Xu, Chuanqi; Pan, Ninghui; Lin, Jinkuo; Zhao, Rui; Yang, Yanyan; Luo, Haiping

2018-02-01

Hexi Corridor is the most important base of commodity grain and producing area for cash crops. However, the rapid development of agriculture and industry has inevitably led to heavy metal contamination in the soils. Multivariate statistical analysis, GIS-based geostatistical methods and Positive Matrix Factorization (PMF) receptor modeling techniques were used to understand the levels of heavy metals and their source apportionment for agricultural soil in Hexi Corridor. The results showed that the average concentrations of Cr, Cu, Ni, Pb and Zn were lower than the secondary standard of soil environmental quality; however, the concentrations of eight metals (Cr, Cu, Mn, Ni, Pb, Ti, V and Zn) were higher than background values, and their corresponding enrichment factor values were significantly greater than 1. Different degrees of heavy metal pollution occurred in the agricultural soils; specifically, Ni had the most potential for impacting human health. The results from the multivariate statistical analysis and GIS-based geostatistical methods indicated both natural sources (Co and W) and anthropogenic sources (Cr, Cu, Mn, Ni, Pb, Ti, V and Zn). To better identify pollution sources of heavy metals in the agricultural soils, the PMF model was applied. Further source apportionment revealed that enrichments of Pb and Zn were attributed to traffic sources; Cr and Ni were closely related to industrial activities, including mining, smelting, coal combustion, iron and steel production and metal processing; Zn and Cu originated from agricultural activities; and V, Ti and Mn were derived from oil- and coal-related activities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Role of spatial inhomogenity in GPCR dimerisation predicted by receptor association-diffusion models

NASA Astrophysics Data System (ADS)

Deshpande, Sneha A.; Pawar, Aiswarya B.; Dighe, Anish; Athale, Chaitanya A.; Sengupta, Durba

2017-06-01

G protein-coupled receptor (GPCR) association is an emerging paradigm with far reaching implications in the regulation of signalling pathways and therapeutic interventions. Recent super resolution microscopy studies have revealed that receptor dimer steady state exhibits sub-second dynamics. In particular the GPCRs, muscarinic acetylcholine receptor M1 (M1MR) and formyl peptide receptor (FPR), have been demonstrated to exhibit a fast association/dissociation kinetics, independent of ligand binding. In this work, we have developed a spatial kinetic Monte Carlo model to investigate receptor homo-dimerisation at a single receptor resolution. Experimentally measured association/dissociation kinetic parameters and diffusion coefficients were used as inputs to the model. To test the effect of membrane spatial heterogeneity on the simulated steady state, simulations were compared to experimental statistics of dimerisation. In the simplest case the receptors are assumed to be diffusing in a spatially homogeneous environment, while spatial heterogeneity is modelled to result from crowding, membrane micro-domains and cytoskeletal compartmentalisation or ‘corrals’. We show that a simple association-diffusion model is sufficient to reproduce M1MR association statistics, but fails to reproduce FPR statistics despite comparable kinetic constants. A parameter sensitivity analysis is required to reproduce the association statistics of FPR. The model reveals the complex interplay between cytoskeletal components and their influence on receptor association kinetics within the features of the membrane landscape. These results constitute an important step towards understanding the factors modulating GPCR organisation.

Characterisation of traffic-generated particulate matter in Copenhagen

NASA Astrophysics Data System (ADS)

Wåhlin, Peter; Berkowicz, Ruwim; Palmgren, Finn

Fine and coarse fraction PM was simultaneously sampled with Dichotomous Stacked Filter Units at a road site and at an urban background site during both summer and winter periods. The collected mass was determined gravimetrically, and the contents of 26 elements were measured by Proton-Induced X-ray Emission (PIXE). NO x was monitored continuously at both sites. The road increments (road concentrations minus urban background concentrations) of PIXE elements, PM and NO x were analysed using the Constrained Physical Receptor Model (COPREM). Good agreement between the measured data and the model was achieved in both size fractions using four well-separated source profiles representing the emissions from exhaust, road/tyres, brakes and road salt. The analysis showed that the particles created by brake abrasion have aerodynamic diameters in the inhalable size range around 2.8 μm. This particle diameter is common mass median for a long list of heavy metals that are apportioned to the brakes source: Cr, Fe, Cu, Zn, Zr, Mo, Sn, Sb, Ba and Pb. Other significant contributions of Al, Si, K, Ca, Ti, Mn, Fe, Zn and Sr, mostly in the coarse particle fraction, are apportioned to the road/tyres source.

Integrated Experimental and Model-based Analysis Reveals the Spatial Aspects of EGFR Activation Dynamics

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

Shankaran, Harish; Zhang, Yi; Chrisler, William B.

2012-10-02

The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models for deconvolving the contributions of receptor dimerizationmore » and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor dephosphorylation rates at the cell surface and early endosomes are comparable. We validated the last finding by measuring EGFR dephosphorylation rates at various times following ligand addition both in whole cells, and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. Further, the mathematical model described here can be extended to determine receptor dimer abundances in cells co-expressing various levels of ErbB receptors. This study demonstrates that an iterative cycle of experiments and modeling can be used to gain mechanistic insight regarding complex cell signaling networks.« less

Health Risk-Based Assessment and Management of Heavy Metals-Contaminated Soil Sites in Taiwan

PubMed Central

Lai, Hung-Yu; Hseu, Zeng-Yei; Chen, Ting-Chien; Chen, Bo-Ching; Guo, Horng-Yuh; Chen, Zueng-Sang

2010-01-01

Risk-based assessment is a way to evaluate the potential hazards of contaminated sites and is based on considering linkages between pollution sources, pathways, and receptors. These linkages can be broken by source reduction, pathway management, and modifying exposure of the receptors. In Taiwan, the Soil and Groundwater Pollution Remediation Act (SGWPR Act) uses one target regulation to evaluate the contamination status of soil and groundwater pollution. More than 600 sites contaminated with heavy metals (HMs) have been remediated and the costs of this process are always high. Besides using soil remediation techniques to remove contaminants from these sites, the selection of possible remediation methods to obtain rapid risk reduction is permissible and of increasing interest. This paper discusses previous soil remediation techniques applied to different sites in Taiwan and also clarified the differences of risk assessment before and after soil remediation obtained by applying different risk assessment models. This paper also includes many case studies on: (1) food safety risk assessment for brown rice growing in a HMs-contaminated site; (2) a tiered approach to health risk assessment for a contaminated site; (3) risk assessment for phytoremediation techniques applied in HMs-contaminated sites; and (4) soil remediation cost analysis for contaminated sites in Taiwan. PMID:21139851

Serial femtosecond crystallography datasets from G protein-coupled receptors

PubMed Central

White, Thomas A.; Barty, Anton; Liu, Wei; Ishchenko, Andrii; Zhang, Haitao; Gati, Cornelius; Zatsepin, Nadia A.; Basu, Shibom; Oberthür, Dominik; Metz, Markus; Beyerlein, Kenneth R.; Yoon, Chun Hong; Yefanov, Oleksandr M.; James, Daniel; Wang, Dingjie; Messerschmidt, Marc; Koglin, Jason E.; Boutet, Sébastien; Weierstall, Uwe; Cherezov, Vadim

2016-01-01

We describe the deposition of four datasets consisting of X-ray diffraction images acquired using serial femtosecond crystallography experiments on microcrystals of human G protein-coupled receptors, grown and delivered in lipidic cubic phase, at the Linac Coherent Light Source. The receptors are: the human serotonin receptor 2B in complex with an agonist ergotamine, the human δ-opioid receptor in complex with a bi-functional peptide ligand DIPP-NH2, the human smoothened receptor in complex with an antagonist cyclopamine, and finally the human angiotensin II type 1 receptor in complex with the selective antagonist ZD7155. All four datasets have been deposited, with minimal processing, in an HDF5-based file format, which can be used directly for crystallographic processing with CrystFEL or other software. We have provided processing scripts and supporting files for recent versions of CrystFEL, which can be used to validate the data. PMID:27479354

Serial femtosecond crystallography datasets from G protein-coupled receptors.

PubMed

White, Thomas A; Barty, Anton; Liu, Wei; Ishchenko, Andrii; Zhang, Haitao; Gati, Cornelius; Zatsepin, Nadia A; Basu, Shibom; Oberthür, Dominik; Metz, Markus; Beyerlein, Kenneth R; Yoon, Chun Hong; Yefanov, Oleksandr M; James, Daniel; Wang, Dingjie; Messerschmidt, Marc; Koglin, Jason E; Boutet, Sébastien; Weierstall, Uwe; Cherezov, Vadim

2016-08-01

We describe the deposition of four datasets consisting of X-ray diffraction images acquired using serial femtosecond crystallography experiments on microcrystals of human G protein-coupled receptors, grown and delivered in lipidic cubic phase, at the Linac Coherent Light Source. The receptors are: the human serotonin receptor 2B in complex with an agonist ergotamine, the human δ-opioid receptor in complex with a bi-functional peptide ligand DIPP-NH2, the human smoothened receptor in complex with an antagonist cyclopamine, and finally the human angiotensin II type 1 receptor in complex with the selective antagonist ZD7155. All four datasets have been deposited, with minimal processing, in an HDF5-based file format, which can be used directly for crystallographic processing with CrystFEL or other software. We have provided processing scripts and supporting files for recent versions of CrystFEL, which can be used to validate the data.

Human Umbilical Cord Perivascular Cells Exhibited Enhanced Migration Capacity towards Hepatocellular Carcinoma in Comparison with Bone Marrow Mesenchymal Stromal Cells: A Role for Autocrine Motility Factor Receptor

PubMed Central

Aquino, Jorge B.; Malvicini, Mariana; Bolontrade, Marcela; Podhajcer, Osvaldo; Garcia, Mariana G.; Mazzolini, Guillermo

2014-01-01

Hepatocellular carcinoma (HCC) is the third cause of cancer-related death worldwide. Unfortunately, the incidence and mortality associated with HCC are increasing. Therefore, new therapeutic strategies are urgently needed and the use of mesenchymal stromal cells (MSCs) as carrier of therapeutic genes is emerging as a promising option. Different sources of MSCs are being studied for cell therapy and bone marrow-derived cells are the most extensively explored; however, birth associated-tissues represent a very promising source. The aim of this work was to compare the in vitro and in vivo migration capacity between bone marrow MSCs (BM-MSCs) and human umbilical cord perivascular cells (HUCPVCs) towards HCC. We observed that HUCPVCs presented higher in vitro and in vivo migration towards factors released by HCC. The expression of autocrine motility factor (AMF) receptor, genes related with the availability of the receptor on the cell surface (caveolin-1 and -2) and metalloproteinase 3, induced by the receptor activation and important for cell migration, was increased in HUCPVCs. The chemotactic response towards recombinant AMF was increased in HUCPVCs compared to BM-MSCs, and its inhibition in the conditioned medium from HCC induced higher decrease in HUCPVC migration than in BM-MSC. Our results indicate that HUCPVCs could be a useful cellular source to deliver therapeutic genes to HCC. PMID:25147818

Human umbilical cord perivascular cells exhibited enhanced migration capacity towards hepatocellular carcinoma in comparison with bone marrow mesenchymal stromal cells: a role for autocrine motility factor receptor.

PubMed

Bayo, Juan; Fiore, Esteban; Aquino, Jorge B; Malvicini, Mariana; Rizzo, Manglio; Peixoto, Estanislao; Alaniz, Laura; Piccioni, Flavia; Bolontrade, Marcela; Podhajcer, Osvaldo; Garcia, Mariana G; Mazzolini, Guillermo

2014-01-01

Hepatocellular carcinoma (HCC) is the third cause of cancer-related death worldwide. Unfortunately, the incidence and mortality associated with HCC are increasing. Therefore, new therapeutic strategies are urgently needed and the use of mesenchymal stromal cells (MSCs) as carrier of therapeutic genes is emerging as a promising option. Different sources of MSCs are being studied for cell therapy and bone marrow-derived cells are the most extensively explored; however, birth associated-tissues represent a very promising source. The aim of this work was to compare the in vitro and in vivo migration capacity between bone marrow MSCs (BM-MSCs) and human umbilical cord perivascular cells (HUCPVCs) towards HCC. We observed that HUCPVCs presented higher in vitro and in vivo migration towards factors released by HCC. The expression of autocrine motility factor (AMF) receptor, genes related with the availability of the receptor on the cell surface (caveolin-1 and -2) and metalloproteinase 3, induced by the receptor activation and important for cell migration, was increased in HUCPVCs. The chemotactic response towards recombinant AMF was increased in HUCPVCs compared to BM-MSCs, and its inhibition in the conditioned medium from HCC induced higher decrease in HUCPVC migration than in BM-MSC. Our results indicate that HUCPVCs could be a useful cellular source to deliver therapeutic genes to HCC.

Bayesian source term determination with unknown covariance of measurements

NASA Astrophysics Data System (ADS)

Belal, Alkomiet; Tichý, Ondřej; Šmídl, Václav

2017-04-01

Determination of a source term of release of a hazardous material into the atmosphere is a very important task for emergency response. We are concerned with the problem of estimation of the source term in the conventional linear inverse problem, y = Mx, where the relationship between the vector of observations y is described using the source-receptor-sensitivity (SRS) matrix M and the unknown source term x. Since the system is typically ill-conditioned, the problem is recast as an optimization problem minR,B(y - Mx)TR-1(y - Mx) + xTB-1x. The first term minimizes the error of the measurements with covariance matrix R, and the second term is a regularization of the source term. There are different types of regularization arising for different choices of matrices R and B, for example, Tikhonov regularization assumes covariance matrix B as the identity matrix multiplied by scalar parameter. In this contribution, we adopt a Bayesian approach to make inference on the unknown source term x as well as unknown R and B. We assume prior on x to be a Gaussian with zero mean and unknown diagonal covariance matrix B. The covariance matrix of the likelihood R is also unknown. We consider two potential choices of the structure of the matrix R. First is the diagonal matrix and the second is a locally correlated structure using information on topology of the measuring network. Since the inference of the model is intractable, iterative variational Bayes algorithm is used for simultaneous estimation of all model parameters. The practical usefulness of our contribution is demonstrated on an application of the resulting algorithm to real data from the European Tracer Experiment (ETEX). This research is supported by EEA/Norwegian Financial Mechanism under project MSMT-28477/2014 Source-Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling (STRADI).

Development of 7TM receptor-ligand complex models using ligand-biased, semi-empirical helix-bundle repacking in torsion space: application to the agonist interaction of the human dopamine D2 receptor.

PubMed

Malo, Marcus; Persson, Ronnie; Svensson, Peder; Luthman, Kristina; Brive, Lars

2013-03-01

Prediction of 3D structures of membrane proteins, and of G-protein coupled receptors (GPCRs) in particular, is motivated by their importance in biological systems and the difficulties associated with experimental structure determination. In the present study, a novel method for the prediction of 3D structures of the membrane-embedded region of helical membrane proteins is presented. A large pool of candidate models are produced by repacking of the helices of a homology model using Monte Carlo sampling in torsion space, followed by ranking based on their geometric and ligand-binding properties. The trajectory is directed by weak initial restraints to orient helices towards the original model to improve computation efficiency, and by a ligand to guide the receptor towards a chosen conformational state. The method was validated by construction of the β1 adrenergic receptor model in complex with (S)-cyanopindolol using bovine rhodopsin as template. In addition, models of the dopamine D2 receptor were produced with the selective and rigid agonist (R)-N-propylapomorphine ((R)-NPA) present. A second quality assessment was implemented by evaluating the results from docking of a library of 29 ligands with known activity, which further discriminated between receptor models. Agonist binding and recognition by the dopamine D2 receptor is interpreted using the 3D structure model resulting from the approach. This method has a potential for modeling of all types of helical transmembrane proteins for which a structural template with sequence homology sufficient for homology modeling is not available or is in an incorrect conformational state, but for which sufficient empirical information is accessible.

Presence and distribution of leptin and leptin receptor in the canine gallbladder.

PubMed

Lee, Sungin; Lee, Aeri; Kweon, Oh-Kyeong; Kim, Wan Hee

2016-09-01

The hormone leptin is produced by mature adipocytes and plays an important role in regulating food intake and energy metabolism through its interaction with the leptin receptor. In addition to roles in obesity and obesity-related diseases, leptin has been reported to affect the components and secretion of bile in leptin-deficient mice. Furthermore, gallbladder diseases such as cholelithiasis are known to be associated with serum leptin concentrations in humans. We hypothesized that the canine gallbladder is a source of leptin and that the leptin receptor may be localized in the gallbladder, where it plays a role in regulating the function of this organ. The aim of this study was to demonstrate the presence and expression patterns of leptin and its receptors in normal canine gallbladders using reverse transcriptase-PCR (RT-PCR) and immunohistochemistry. Clinically normal gallbladder tissue samples were obtained from four healthy beagle dogs with similar body condition scores. RT-PCR and sequencing of the amplified PCR products revealed the presence of leptin mRNA and its receptors in the gallbladder. Immunohistochemical investigations demonstrated the expression of leptin and its receptors in the luminal single columnar and tubuloalveolar glandular epithelial cells. In conclusion, the results of this study demonstrated the presence of leptin and its receptors in the gallbladders of dogs. Leptin and its receptor were both localized throughout the cytoplasm of luminal and glandular epithelial cells. These results suggested that the gallbladder is not only a source of leptin, but also a target of leptin though autocrine/paracrine mechanisms. The results of this study could increase the understanding of both the normal physiological functions of the gallbladder and the pathophysiological mechanisms of gallbladder diseases characterized by leptin system dysfunction. Copyright © 2016 The Authors. Published by Elsevier GmbH.. All rights reserved.

Constitutively active 5-HT2/α1 receptors facilitate muscle spasms after human spinal cord injury

PubMed Central

D'Amico, Jessica M.; Murray, Katherine C.; Li, Yaqing; Chan, K. Ming; Finlay, Mark G.; Bennett, David J.

2013-01-01

In animals, the recovery of motoneuron excitability in the months following a complete spinal cord injury is mediated, in part, by increases in constitutive serotonin (5-HT2) and norepinephrine (α1) receptor activity, which facilitates the reactivation of calcium-mediated persistent inward currents (CaPICs) without the ligands serotonin and norepinephrine below the injury. In this study we sought evidence for a similar role of constitutive monoamine receptor activity in the development of spasticity in human spinal cord injury. In chronically injured participants with partially preserved sensory and motor function, the serotonin reuptake inhibitor citalopram facilitated long-lasting reflex responses (spasms) previously shown to be mediated by CaPICs, suggesting that in incomplete spinal cord injury, functional descending sources of monoamines are present to activate monoamine receptors below the lesion. However, in participants with motor or motor/sensory complete injuries, the inverse agonist cyproheptadine, which blocks both ligand and constitutive 5-HT2/α1 receptor activity, decreased long-lasting reflexes, whereas the neutral antagonist chlorpromazine, which only blocks ligand activation of these receptors, had no effect. When tested in noninjured control participants having functional descending sources of monoamines, chlorpromazine was effective in reducing CaPIC-mediated motor unit activity. On the basis of these combined results, it appears that in severe spinal cord injury, facilitation of persistent inward currents and muscle spasms is mainly mediated by the activation of constitutive 5-HT2 and α1 receptor activity. Drugs that more selectively block these constitutively active monoamine receptors may provide better oral control of spasticity, especially in motor complete spinal cord injury where reducing motoneuron excitability is the primary goal. PMID:23221402

Homology Modeling of Class A G Protein-Coupled Receptors

PubMed Central

Costanzi, Stefano

2012-01-01

G protein-coupled receptors (GPCRs) are a large superfamily of membrane bound signaling proteins that hold great pharmaceutical interest. Since experimentally elucidated structures are available only for a very limited number of receptors, homology modeling has become a widespread technique for the construction of GPCR models intended to study the structure-function relationships of the receptors and aid the discovery and development of ligands capable of modulating their activity. Through this chapter, various aspects involved in the constructions of homology models of the serpentine domain of the largest class of GPCRs, known as class A or rhodopsin family, are illustrated. In particular, the chapter provides suggestions, guidelines and critical thoughts on some of the most crucial aspect of GPCR modeling, including: collection of candidate templates and a structure-based alignment of their sequences; identification and alignment of the transmembrane helices of the query receptor to the corresponding domains of the candidate templates; selection of one or more templates receptor; election of homology or de novo modeling for the construction of specific extracellular and intracellular domains; construction of the three-dimensional models, with special consideration to extracellular regions, disulfide bridges, and interhelical cavity; validation of the models through controlled virtual screening experiments. PMID:22323225

Exploring the Interaction between TSC2, PTEN, and the NMDA Receptor in Animal Models of Tuberous Sclerosis

DTIC Science & Technology

2014-09-01

Sunnen CN, Crowell B, Lee GH, Anderson AE, and D’Arcangelo G. Examination of the Role of Pten in Ionotropic Glutamate Receptor Expression. National...PTEN, and the NMDA Receptor in Animal Models of Tuberous Sclerosis PRINCIPAL INVESTIGATOR: D’Arcangelo, Gabriella CONTRACTING...June 2014 4. TITLE AND SUBTITLE Exploring the Interaction between TSC2, PTEN, and the NMDA Receptor in Animal Models of Tuberous Sclerosis 5a

Odor Preference Learning and Memory Modify GluA1 Phosphorylation and GluA1 Distribution in the Neonate Rat Olfactory Bulb: Testing the AMPA Receptor Hypothesis in an Appetitive Learning Model

ERIC Educational Resources Information Center

Cui, Wen; Darby-King, Andrea; Grimes, Matthew T.; Howland, John G.; Wang, Yu Tian; McLean, John H.; Harley, Carolyn W.

2011-01-01

An increase in synaptic AMPA receptors is hypothesized to mediate learning and memory. AMPA receptor increases have been reported in aversive learning models, although it is not clear if they are seen with memory maintenance. Here we examine AMPA receptor changes in a cAMP/PKA/CREB-dependent appetitive learning model: odor preference learning in…

Source apportionment of ambient volatile organic compounds in the Pearl River Delta, China: Part II

NASA Astrophysics Data System (ADS)

Liu, Ying; Shao, Min; Lu, Sihua; Chang, Chih-Chung; Wang, Jia-Lin; Fu, Linlin

The chemical mass balance receptor model was applied to the source apportionment of 58 hydrocarbons measured at seven sites in a field campaign that examined regional air quality in the Pearl River Delta (PRD) region in the fall of 2004. A total of 12 volatile organic compound (VOC) emission sources were considered, including gasoline- and diesel-powered vehicle exhausts, headspace vapors of gasoline and diesel fuel, vehicle evaporative emissions, liquid petroleum gas (LPG) leakage, paint vapors, asphalt emissions from paved roads, biomass combustion, coal combustion, the chemical industry, and petroleum refineries. Vehicle exhaust was the largest source of VOCs, contributing to >50% of ambient VOCs at the three urban sites (Guangzhou, Foshan, and Zhongshan). LPG leakage played an important role, representing 8-16% of emissions at most sites in the PRD. Solvent usage was the biggest emitter of VOCs at Dongguan, an industrial site, contributing 33% of ambient VOCs. Similarly, at Xinken, a non-urban site, the evaporation of solvents and coatings was the largest emission source, accounting for 31% of emissions, probably because it was downwind of Dongguan. Local biomass combustion was a noticeable source of VOCs at Xinken; although its contribution was estimated at 14.3%, biomass combustion was the third largest VOC source at this site.

Benzene observations and source appointment in a region of oil and natural gas development

NASA Astrophysics Data System (ADS)

Halliday, Hannah Selene

Benzene is a primarily anthropogenic volatile organic compound (VOC) with a small number of well characterized sources. Atmospheric benzene affects human health and welfare, and low level exposure (< 0.5 ppbv) has been connected to measureable increases in cancer rates. Benzene measurements have been increasing in the region of oil and natural gas (O&NG) development located to the north of Denver. High time resolution measurements of VOCs were collected using a proton-transfer-reaction quadrupole mass spectrometry (PTR-QMS) instrument at the Platteville Atmospheric Observatory (PAO) in Colorado to investigate how O&NG development impacts air quality within the Wattenburg Gas Field (WGF) in the Denver-Julesburg Basin. The measurements were carried out in July and August 2014 as part of NASA's DISCOVER-AQ field campaign. The PTR-QMS data were supported by pressurized whole air canister samples and airborne vertical and horizontal surveys of VOCs. Unexpectedly high benzene mixing ratios were observed at PAO at ground level (mean benzene = 0.53 ppbv, maximum benzene = 29.3 ppbv), primarily at night (mean nighttime benzene = 0.73 ppbv). These high benzene levels were associated with southwesterly winds. The airborne measurements indicate that benzene originated from within the WGF, and typical source signatures detected in the canister samples implicate emissions from O&NG activities rather than urban vehicular emissions as primary benzene source. This conclusion is backed by a regional toluene-to-benzene ratio analysis which associated southerly flow with vehicular emissions from the Denver area. Weak benzene-to-CO correlations confirmed that traffic emissions were not responsible for the observed high benzene levels. Previous measurements at the Boulder Atmospheric Observatory (BAO) and our data obtained at PAO allow us to locate the source of benzene enhancements between the two atmospheric observatories. Fugitive emissions of benzene from O&NG operations in the Platteville area are discussed as the most likely causes of enhanced benzene levels at PAO. A limited information source attribution with the PAO dataset was completed using the EPA's positive matrix factorization (PMF) source receptor model. Six VOCs from the PTR-QMS measurement were used along with CO and NO for a total of eight chemical species. Six sources were identified in the PMF analysis: a primarily CO source, an aged vehicle emissions source, a diesel/compressed natural gas emissions source, a fugitive emissions source, and two sources that have the characteristics of a mix of fresh vehicle emissions and condensate fugitive emissions. 70% of the benzene measured at PAO on the PTR-QMS is attributed to fugitive emissions, primarily located to the SW of PAO. Comparing the PMF source attribution to source calculations done with a source array configured from the literature returns a contradictory result, with the expected sources indicting that aged vehicle emissions are the primary benzene source. However, analysis of the contradictory result indicates that the toluene to benzene ratio measured for PAO is much lower than the literature values, suggesting that the O&NG source emissions have a lower ratio of toluene to benzene than anticipated based on studies of other regions. Finally, we propose and investigate an alternative form of the source receptor model using a constrained optimization. Poor results of the proposed method are described with tests on a synthetic testing dataset, and further testing with the observation data from PAO indicate that the proposed method is not able to converge the best global solution to the system.

An integrated modelling framework for neural circuits with multiple neuromodulators.

PubMed

Joshi, Alok; Youssofzadeh, Vahab; Vemana, Vinith; McGinnity, T M; Prasad, Girijesh; Wong-Lin, KongFatt

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. © 2017 The Authors.

An integrated modelling framework for neural circuits with multiple neuromodulators

PubMed Central

Vemana, Vinith

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. PMID:28100828

No Effect of Nutritional Adenosine Receptor Antagonists on Exercise Performance in the Heat

DTIC Science & Technology

2008-11-01

358–363, 1996. 11. Cook NC, Samman S. Flavonoids — chemistry , metabolism, cardiopro- tective effects, and dietary sources. Nutr Biochem 7: 66–76, 1996...metabolism and health effects of dietary flavonoids in man. Biomed Pharmacother 51: 305–310, 1997. R400 ADENOSINE RECEPTOR ANTAGONISM AND EXERCISE IN THE HEAT...Interactions of flavonoids with adenosine receptors. J Med Chem 39: 781–788, 1996. 35. MacRae HS, Mefferd KM. Dietary antioxidant supplementation com

Fine Particulate Pollution and Source Apportionment in the Urban Centers for Africa, Asia and Latin America

NASA Astrophysics Data System (ADS)

Guttikunda, S. K.; Johnson, T. M.; Procee, P.

2004-12-01

Fossil fuel combustion for domestic cooking and heating, power generation, industrial processes, and motor vehicles are the primary sources of air pollution in the developing country cities. Over the past twenty years, major advances have been made in understanding the social and economic consequences of air pollution. In both industrialized and developing countries, it has been shown that air pollution from energy combustion has detrimental impacts on human health and the environment. Lack of information on the sectoral contributions to air pollution - especially fine particulates, is one of the typical constraints for an effective integrated urban air quality management program. Without such information, it is difficult, if not impossible, for decision makers to provide policy advice and make informed investment decisions related to air quality improvements in developing countries. This also raises the need for low-cost ways of determining the principal sources of fine PM for a proper planning and decision making. The project objective is to develop and verify a methodology to assess and monitor the sources of PM, using a combination of ground-based monitoring and source apportionment techniques. This presentation will focus on four general tasks: (1) Review of the science and current activities in the combined use of monitoring data and modeling for better understanding of PM pollution. (2) Review of recent advances in atmospheric source apportionment techniques (e.g., principal component analysis, organic markers, source-receptor modeling techniques). (3) Develop a general methodology to use integrated top-down and bottom-up datasets. (4) Review of a series of current case studies from Africa, Asia and Latin America and the methodologies applied to assess the air pollution and its sources.

Sources of personal exposure to fine particles in Toronto, Ontario, Canada.

PubMed

Kim, David; Sass-Kortsak, Andrea; Purdham, James T; Dales, Robert E; Brook, Jeffrey R

2005-08-01

Individuals are exposed to particulate matter from both indoor and outdoor sources. The aim of this study was to compare the relative contributions of three sources of personal exposure to fine particles (PM2.5) by using chemical tracers. The study design incorporated repeated 24-hr personal exposure measurements of air pollution from 28 cardiac-compromised residents of Toronto, Ontario, Canada. Each study participant wore the Rupprecht & Patashnick ChemPass Personal Sampling System 1 day a week for a maximum of 10 weeks. During their individual exposure measurement days the subjects reported to have spent an average of 89% of their time indoors. Particle phase elemental carbon, sulfate, and calcium personal exposure data were used in a mixed-effects model as tracers for outdoor PM2.5 from traffic-related combustion, regional, and local crustal materials, respectively. These three sources were found to contribute 13% +/- 10%, 17% +/- 16%, and 7% +/- 6% of PM2.5 exposures. The remaining fraction of the personal PM2.5 is hypothesized to be predominantly related to indoor sources. For comparison, central site outdoor PM2.5 measurements for the same dates as personal measurements were used to construct a receptor model using the same three tracers. In this case, traffic-related combustion, regional, and local crustal materials were found to contribute 19% +/- 17%, 52% +/- 22%, and 10% +/- 7%, respectively. Our results indicate that the three outdoor PM2.5 sources considered are statistically significant contributors to personal exposure to PM2.5. Our results also suggest that among the Toronto subjects, who spent a considerable amount of time indoors, exposure to outdoor PM2.5 includes a greater relative contribution from combustion sources compared with outdoor PM2.5 measurements where regional sources are the dominant contributor.

Dopamine receptor activity participates in hippocampal synaptic plasticity associated with novel object recognition.

PubMed

Yang, Kechun; Broussard, John I; Levine, Amber T; Jenson, Daniel; Arenkiel, Benjamin R; Dani, John A

2017-01-01

Physiological and behavioral evidence supports that dopamine (DA) receptor signaling influences hippocampal function. While several recent studies examined how DA influences CA1 plasticity and learning, there are fewer studies investigating the influence of DA signaling to the dentate gyrus. The dentate gyrus receives convergent cortical input through the perforant path fiber tracts and has been conceptualized to detect novelty in spatial memory tasks. To test whether DA-receptor activity influences novelty-detection, we used a novel object recognition (NOR) task where mice remember previously presented objects as an indication of learning. Although DA innervation arises from other sources and the main DA signaling may be from those sources, our molecular approaches verified that midbrain dopaminergic fibers also sparsely innervate the dentate gyrus. During the NOR task, wild-type mice spent significantly more time investigating novel objects rather than previously observed objects. Dentate granule cells in slices cut from those mice showed an increased AMPA/NMDA-receptor current ratio indicative of potentiated synaptic transmission. Post-training injection of a D1-like receptor antagonist not only effectively blocked the preference for the novel objects, but also prevented the increased AMPA/NMDA ratio. Consistent with that finding, neither NOR learning nor the increase in the AMPA/NMDA ratio were observed in DA-receptor KO mice under the same experimental conditions. The results indicate that DA-receptor signaling contributes to the successful completion of the NOR task and to the associated synaptic plasticity of the dentate gyrus that likely contributes to the learning. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Application of positive matrix factorization to on-road measurements for source apportionment of diesel- and gasoline-powered vehicle emissions in Mexico City

NASA Astrophysics Data System (ADS)

Thornhill, D. A.; Williams, A. E.; Onasch, T. B.; Wood, E.; Herndon, S. C.; Kolb, C. E.; Knighton, W. B.; Zavala, M.; Molina, L. T.; Marr, L. C.

2009-12-01

The goal of this research is to quantify diesel- and gasoline-powered motor vehicle emissions within the Mexico City Metropolitan Area (MCMA) using on-road measurements captured by a mobile laboratory combined with positive matrix factorization (PMF) receptor modeling. During the MCMA-2006 ground-based component of the MILAGRO field campaign, the Aerodyne Mobile Laboratory (AML) measured many gaseous and particulate pollutants, including carbon dioxide, carbon monoxide (CO), nitrogen oxides (NOx), benzene, toluene, alkylated aromatics, formaldehyde, acetaldehyde, acetone, ammonia, particle number, fine particulate mass (PM2.5), and black carbon (BC). These serve as inputs to the receptor model, which is able to resolve three factors corresponding to gasoline engine exhaust, diesel engine exhaust, and the urban background. Using the source profiles, we calculate fuel-based emission factors for each type of exhaust. The MCMA's gasoline-powered vehicles are considerably dirtier, on average, than those in the US with respect to CO and aldehydes. Its diesel-powered vehicles have similar emission factors of NOx and higher emission factors of aldehydes, particle number, and BC. In the fleet sampled during AML driving, gasoline-powered vehicles are responsible for 97% of mobile source emissions of CO, 22% of NOx, 95-97% of aromatics, 72-85% of carbonyls, 74% of ammonia, negligible amounts of particle number, 26% of PM2.5, and 2% of BC; diesel-powered vehicles account for the balance. Because the mobile lab spent 17% of its time waiting at stoplights, the results may overemphasize idling conditions, possibly resulting in an underestimate of NOx and overestimate of CO emissions. On the other hand, estimates of the inventory that do not correctly account for emissions during idling are likely to produce bias in the opposite direction. Nevertheless, the fuel-based inventory suggests that mobile source emissions of CO and NOx are overstated in the official inventory while emissions of VOCs may be understated. For NOx, the fuel-based inventory is lower for gasoline-powered vehicles but higher for diesel-powered ones compared to the official inventory.

The G protein-coupled receptors deorphanization landscape.

PubMed

Laschet, Céline; Dupuis, Nadine; Hanson, Julien

2018-07-01

G protein-coupled receptors (GPCRs) are usually highlighted as being both the largest family of membrane proteins and the most productive source of drug targets. However, most of the GPCRs are understudied and hence cannot be used immediately for innovative therapeutic strategies. Besides, there are still around 100 orphan receptors, with no described endogenous ligand and no clearly defined function. The race to discover new ligands for these elusive receptors seems to be less intense than before. Here, we present an update of the various strategies employed to assign a function to these receptors and to discover new ligands. We focus on the recent advances in the identification of endogenous ligands with a detailed description of newly deorphanized receptors. Replication being a key parameter in these endeavors, we also discuss the latest controversies about problematic ligand-receptor pairings. In this context, we propose several recommendations in order to strengthen the reporting of new ligand-receptor pairs. Copyright © 2018 Elsevier Inc. All rights reserved.

Operational models of pharmacological agonism.

PubMed

Black, J W; Leff, P

1983-12-22

The traditional receptor-stimulus model of agonism began with a description of drug action based on the law of mass action and has developed by a series of modifications, each accounting for new experimental evidence. By contrast, in this paper an approach to modelling agonism is taken that begins with the observation that experimental agonist-concentration effect, E/[A], curves are commonly hyperbolic and develops using the deduction that the relation between occupancy and effect must be hyperbolic if the law of mass action applies at the agonist-receptor level. The result is a general model that explicitly describes agonism by three parameters: an agonist-receptor dissociation constant, KA; the total receptor concentration, [R0]; and a parameter, KE, defining the transduction of agonist-receptor complex, AR, into pharmacological effect. The ratio, [R0]/KE, described here as the 'transducer ratio', tau, is a logical definition for the efficacy of an agonist in a system. The model may be extended to account for non-hyperbolic E/[A] curves with no loss of meaning. Analysis shows that an explicit formulation of the traditional receptor-stimulus model is one particular form of the general model but that it is not the simplest. An alternative model is proposed, representing the cognitive and transducer functions of a receptor, that describes agonist action with one fewer parameter than the traditional model. In addition, this model provides a chemical definition of intrinsic efficacy making this parameter experimentally accessible in principle. The alternative models are compared and contrasted with regard to their practical and conceptual utilities in experimental pharmacology.

Multifunctional and multispectral biosensor devices and methods of use

DOEpatents

Vo-Dinh, Tuan

2004-06-01

An integrated biosensor system for the simultaneously detection of a plurality of different types of targets includes at least one sampling platform, the sampling platform including a plurality of receptors for binding to the targets. The plurality of receptors include at least one protein receptor and at least one nucleic acid receptor. At least one excitation source of electromagnetic radiation at a first frequency is provided for irradiating the receptors, wherein electromagnetic radiation at a second frequency different from the first frequency is emitted in response to irradiating when at least one of the different types of targets are bound to the receptor probes. An integrated circuit detector system having a plurality of detection channels is also provided for detecting electromagnetic radiation at said second frequency, the detection channels each including at least one detector.

Modeling study of natural emissions, source apportionment, and emission control of atmospheric mercury

NASA Astrophysics Data System (ADS)

Shetty, Suraj K.

Mercury (Hg) is a toxic pollutant and is important to understand its cycling in the environment. In this dissertation, a number of modeling investigations were conducted to better understand the emission from natural surfaces, the source-receptor relationship of the emissions, and emission reduction of atmospheric mercury. The first part of this work estimates mercury emissions from vegetation, soil and water surfaces using a number of natural emission processors and detailed (LAI) Leaf Area Index data from GIS (Geographic Information System) satellite products. East Asian domain was chosen as it contributes nearly 50% of the global anthropogenic mercury emissions into the atmosphere. The estimated annual natural mercury emissions (gaseous elemental mercury) in the domain are 834 Mg yr-1 with 462 Mg yr-1 contributing from China. Compared to anthropogenic sources, natural sources show greater seasonal variability (highest in simmer). The emissions are significant, sometimes dominant, contributors to total mercury emission in the regions. The estimates provide possible explanation for the gaps between the anthropogenic emission estimates based on activity data and the emission inferred from field observations in the regions. To understand the contribution of domestic emissions to mercury deposition in the United States, the second part of the work applies the mercury model of Community Multi-scale Air Quality Modeling system (CMAQ-Hg v4.6) to apportion the various emission sources attributing to the mercury wet and dry deposition in the 6 United States receptor regions. Contributions to mercury deposition from electric generating units (EGU), iron and steel industry (IRST), industrial point sources excluding EGU and IRST (OIPM), the remaining anthropogenic sources (RA), natural processes (NAT), and out-of-boundary transport (BC) in domain was estimated. The model results for 2005 compared reasonably well to field observations made by MDN (Mercury Deposition Network) and CAMNet (Canadian Atmospheric Mercury Measurement Network). The model estimated a total deposition of 474 Mg yr-1 to the CONUS (Contiguous United States) domain, with two-thirds being dry deposited. Reactive gaseous mercury contributed the most to 60% of deposition. Emission speciation distribution is a key factor for local deposition as contribution from large point sources can be as high as 75% near (< 100 km) the emission sources, indicating that emission reduction may result in direct deposition decrease near the source locations. Among the sources, BC contributes to about 68% to 91% of total deposition. Excluding the BC's contribution, EGU contributes to nearly 50% of deposition caused by CONUS emissions in the Northeast, Southeast and East Central regions, while emissions from natural processes are more important in the Pacific and West Central regions (contributing up to 40% of deposition). The modeling results implies that implementation of the new emission standards proposed by USEPA (United States Environmental Protection Agency) would significantly benefit regions that have larger contributions from EGU sources. Control of mercury emissions from coal combustion processes has attracted great attention due to its toxicity and the emission-control regulations and has lead to advancement in state-of-the-art control technologies that alleviate the impact of mercury on ecosystem and human health. This part of the work applies a sorption model to simulate adsorption of mercury in flue gases, onto a confined-bed of activated carbon. The model's performances were studied at various flue gas flow rates, inlet mercury concentrations and adsorption bed temperatures. The process simulated a flue gas, with inlet mercury concentration of 300 ppb, entering at a velocity of 0.3 m s-1 from the bottom into a fixed bed (inside bed diameter of 1 m and 3 m bed height; bed temperature of 25 °C) of activated carbon (particle size of 0.004 m with density of 0.5 g cm-3 and surface area of 90.25 cm2 g -1). The model result demonstrated that a batch of activated carbon bed was capable of controlling mercury emission for approximately 275 days after which further mercury uptake starts to decrease till it reaches about 500 days when additional control ceases. An increase in bed temperature significantly reduces mercury sorption capacity of the activated carbon. Increase in flue gas flow rate may result in faster consumption of sorption capacity initially but at a later stage, the sorption rate decreases due to reduced sorption capacity. Thus, overall sorption rate remains unaffected. The activated carbon's effective life (time to reach saturation) is not affected by inlet mercury concentration, implying that the designing and operation of a mercury sorption process can be done independently. The results provide quantitative indication for designing efficient confined-bed process to remove mercury from flue gases.

Origin of soluble chemical species in bulk precipitation collected in Tokyo, Japan: Statistical evaluation of source materials

NASA Astrophysics Data System (ADS)

Tsurumi, Makoto; Takahashi, Akira; Ichikuni, Masami

An iterative least-squares method with a receptor model was applied to the analytical data of the precipitation samples collected at 23 points in the suburban area of Tokyo, and the number and composition of the source materials were determined. Thirty-nine monthly bulk precipitation samples were collected in the spring and summer of 1987 from the hilly and mountainous area of Tokyo and analyzed for Na +, K +, NH 4+, Mg 2+, Ca 2+, F -, Cl -, Br -, NO 3- and SO 42- by atomic absorption spectrometry and ion chromatography. The pH of the samples was also measured. A multivariate ion balance approach (Tsurumi, 1982, Anal. Chim. Acta138, 177-182) showed that the solutes in the precipitation were derived from just three major sources; sea salt, acid substance (a mixture of 53% HNO 3, 39% H 2SO 4 and 8% HCl in equivalent) and CaSO 4. The contributions of each source to the precipitation were calculated for every sampling site. Variations of the contributions with the distance from the coast were also discussed.

Source Apportionment and Risk Assessment of Emerging Contaminants: An Approach of Pharmaco-Signature in Water Systems

PubMed Central

Jiang, Jheng Jie; Lee, Chon Lin; Fang, Meng Der; Boyd, Kenneth G.; Gibb, Stuart W.

2015-01-01

This paper presents a methodology based on multivariate data analysis for characterizing potential source contributions of emerging contaminants (ECs) detected in 26 river water samples across multi-scape regions during dry and wet seasons. Based on this methodology, we unveil an approach toward potential source contributions of ECs, a concept we refer to as the “Pharmaco-signature.” Exploratory analysis of data points has been carried out by unsupervised pattern recognition (hierarchical cluster analysis, HCA) and receptor model (principal component analysis-multiple linear regression, PCA-MLR) in an attempt to demonstrate significant source contributions of ECs in different land-use zone. Robust cluster solutions grouped the database according to different EC profiles. PCA-MLR identified that 58.9% of the mean summed ECs were contributed by domestic impact, 9.7% by antibiotics application, and 31.4% by drug abuse. Diclofenac, ibuprofen, codeine, ampicillin, tetracycline, and erythromycin-H2O have significant pollution risk quotients (RQ>1), indicating potentially high risk to aquatic organisms in Taiwan. PMID:25874375

Molecular identification of organic compounds in atmospheric complex mixtures and relationship to atmospheric chemistry and sources.

PubMed

Mazurek, Monica A

2002-12-01

This article describes a chemical characterization approach for complex organic compound mixtures associated with fine atmospheric particles of diameters less than 2.5 m (PM2.5). It relates molecular- and bulk-level chemical characteristics of the complex mixture to atmospheric chemistry and to emission sources. Overall, the analytical approach describes the organic complex mixtures in terms of a chemical mass balance (CMB). Here, the complex mixture is related to a bulk elemental measurement (total carbon) and is broken down systematically into functional groups and molecular compositions. The CMB and molecular-level information can be used to understand the sources of the atmospheric fine particles through conversion of chromatographic data and by incorporation into receptor-based CMB models. Once described and quantified within a mass balance framework, the chemical profiles for aerosol organic matter can be applied to existing air quality issues. Examples include understanding health effects of PM2.5 and defining and controlling key sources of anthropogenic fine particles. Overall, the organic aerosol compositional data provide chemical information needed for effective PM2.5 management.

Platelet and Erythrocyte Sources of S1P Are Redundant for Vascular Development and Homeostasis, but Both Rendered Essential After Plasma S1P Depletion in Anaphylactic Shock.

PubMed

Gazit, Salomé L; Mariko, Boubacar; Thérond, Patrice; Decouture, Benoit; Xiong, Yuquan; Couty, Ludovic; Bonnin, Philippe; Baudrie, Véronique; Le Gall, Sylvain M; Dizier, Blandine; Zoghdani, Nesrine; Ransinan, Jessica; Hamilton, Justin R; Gaussem, Pascale; Tharaux, Pierre-Louis; Chun, Jerold; Coughlin, Shaun R; Bachelot-Loza, Christilla; Hla, Timothy; Ho-Tin-Noé, Benoit; Camerer, Eric

2016-09-30

Sphingosine-1-phosphate (S1P) signaling is essential for vascular development and postnatal vascular homeostasis. The relative importance of S1P sources sustaining these processes remains unclear. To address the level of redundancy in bioactive S1P provision to the developing and mature vasculature. S1P production was selectively impaired in mouse platelets, erythrocytes, endothelium, or smooth muscle cells by targeted deletion of genes encoding sphingosine kinases -1 and -2. S1P deficiency impaired aggregation and spreading of washed platelets and profoundly reduced their capacity to promote endothelial barrier function ex vivo. However, and in contrast to recent reports, neither platelets nor any other source of S1P was essential for vascular development, vascular integrity, or hemostasis/thrombosis. Yet rapid and profound depletion of plasma S1P during systemic anaphylaxis rendered both platelet- and erythrocyte-derived S1P essential for survival, with a contribution from blood endothelium observed only in the absence of circulating sources. Recovery was sensitive to aspirin in mice with but not without platelet S1P, suggesting that platelet activation and stimulus-response coupling is needed. S1P deficiency aggravated vasoplegia in this model, arguing a vital role for S1P in maintaining vascular resistance during recovery from circulatory shock. Accordingly, the S1P2 receptor mediated most of the survival benefit of S1P, whereas the endothelial S1P1 receptor was dispensable for survival despite its importance for maintaining vascular integrity. Although source redundancy normally secures essential S1P signaling in developing and mature blood vessels, profound depletion of plasma S1P renders both erythrocyte and platelet S1P pools necessary for recovery and high basal plasma S1P levels protective during anaphylactic shock. © 2016 American Heart Association, Inc.

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

Sondrup, Andrus Jeffrey

The Department of Energy Idaho Operations Office (DOE-ID) is applying for a synthetic minor, Sitewide, air quality permit to construct (PTC) with a facility emission cap (FEC) component from the Idaho Department of Environmental Quality (DEQ) for Idaho National Laboratory (INL) to limit its potential to emit to less than major facility limits for criteria air pollutants (CAPs) and hazardous air pollutants (HAPs) regulated under the Clean Air Act. This document is supplied as an appendix to the application, Idaho National Laboratory Application for a Synthetic Minor Sitewide Air Quality Permit to Construct with a Facility Emissions Cap Component, hereaftermore » referred to as “permit application” (DOE-ID 2015). Air dispersion modeling was performed as part of the permit application process to demonstrate pollutant emissions from the INL will not cause a violation of any ambient air quality standards. This report documents the modeling methodology and results for the air dispersion impact analysis. All CAPs regulated under Section 109 of the Clean Air Act were modeled with the exception of lead (Pb) and ozone, which are not required to be modeled by DEQ. Modeling was not performed for toxic air pollutants (TAPs) as uncontrolled emissions did not exceed screening emission levels for carcinogenic and non-carcinogenic TAPs. Modeling for CAPs was performed with the EPA approved AERMOD dispersion modeling system (Version 14134) (EPA 2004a) and five years (2000-2004) of meteorological data. The meteorological data set was produced with the companion AERMET model (Version 14134) (EPA 2004b) using surface data from the Idaho Falls airport, and upper-air data from Boise International Airport supplied by DEQ. Onsite meteorological data from the Grid 3 Mesonet tower located near the center of the INL (north of INTEC) and supplied by the local National Oceanic and Atmospheric Administration (NOAA) office was used for surface wind directions and wind speeds. Surface data (i.e., land use data that defines roughness, albedo, Bowen ratio, and other parameters) were processed using the AERSURFACE utility (Version 13016) (EPA 2013). Emission sources were modeled as point sources using actual stack locations and dimensions. Emissions, flow rates and exit temperatures were based on the design operating capacity of each source. All structures close enough to produce an area of wake effect were included for all sources. For multi-tiered structures, the heights of the tiers were included or the entire building height was assumed to be equal to the height of the tallest tier. Concentrations were calculated at 1,352 receptor locations provided by DEQ. All receptors were considered for each pollutant and averaging period. Maximum modeled CAP concentrations summed with average background concentration values were presented and compared to National Ambient Air Quality Standards (NAAQS). The background concentration values used were obtained using the Washington State University’s Laboratory for Atmospheric Research North West Airquest web-based retrieval tool (http://lar.wsu.edu/nw airquest/lookup.html). The air dispersion modeling results show the maximum impacts for CAPs are less than applicable standards and demonstrate the INL will not cause a violation of any ambient air quality standards.« less

Vesicular glutamate release from central axons contributes to myelin damage.

PubMed

Doyle, Sean; Hansen, Daniel Bloch; Vella, Jasmine; Bond, Peter; Harper, Glenn; Zammit, Christian; Valentino, Mario; Fern, Robert

2018-03-12

The axon myelin sheath is prone to injury associated with N-methyl-D-aspartate (NMDA)-type glutamate receptor activation but the source of glutamate in this context is unknown. Myelin damage results in permanent action potential loss and severe functional deficit in the white matter of the CNS, for example in ischemic stroke. Here, we show that in rats and mice, ischemic conditions trigger activation of myelinic NMDA receptors incorporating GluN2C/D subunits following release of axonal vesicular glutamate into the peri-axonal space under the myelin sheath. Glial sources of glutamate such as reverse transport did not contribute significantly to this phenomenon. We demonstrate selective myelin uptake and retention of a GluN2C/D NMDA receptor negative allosteric modulator that shields myelin from ischemic injury. The findings potentially support a rational approach toward a low-impact prophylactic therapy to protect patients at risk of stroke and other forms of excitotoxic injury.

Argyreia nervosa (Burm. f.): receptor profiling of lysergic acid amide and other potential psychedelic LSD-like compounds by computational and binding assay approaches.

PubMed

Paulke, Alexander; Kremer, Christian; Wunder, Cora; Achenbach, Janosch; Djahanschiri, Bardya; Elias, Anderson; Schwed, J Stefan; Hübner, Harald; Gmeiner, Peter; Proschak, Ewgenij; Toennes, Stefan W; Stark, Holger

2013-07-09

The convolvulacea Argyreia nervosa (Burm. f.) is well known as an important medical plant in the traditional Ayurvedic system of medicine and it is used in numerous diseases (e.g. nervousness, bronchitis, tuberculosis, arthritis, and diabetes). Additionally, in the Indian state of Assam and in other regions Argyreia nervosa is part of the traditional tribal medicine (e.g. the Santali people, the Lodhas, and others). In the western hemisphere, Argyreia nervosa has been brought in attention as so called "legal high". In this context, the seeds are used as source of the psychoactive ergotalkaloid lysergic acid amide (LSA), which is considered as the main active ingredient. As the chemical structure of LSA is very similar to that of lysergic acid diethylamide (LSD), the seeds of Argyreia nervosa (Burm. f.) are often considered as natural substitute of LSD. In the present study, LSA and LSD have been compared concerning their potential pharmacological profiles based on the receptor binding affinities since our recent human study with four volunteers on p.o. application of Argyreia nervosa seeds has led to some ambiguous effects. In an initial step computer-aided in silico prediction models on receptor binding were employed to screen for serotonin, norepinephrine, dopamine, muscarine, and histamine receptor subtypes as potential targets for LSA. In addition, this screening was extended to accompany ergotalkaloids of Argyreia nervosa (Burm. f.). In a verification step, selected LSA screening results were confirmed by in vitro binding assays with some extensions to LSD. In the in silico model LSA exhibited the highest affinity with a pKi of about 8.0 at α1A, and α1B. Clear affinity with pKi>7 was predicted for 5-HT1A, 5-HT1B, 5-HT1D, 5-HT6, 5-HT7, and D2. From these receptors the 5-HT1D subtype exhibited the highest pKi with 7.98 in the prediction model. From the other ergotalkaloids, agroclavine and festuclavine also seemed to be highly affine to the 5-HT1D-receptor with pKi>8. In general, the ergotalkaloids of Argyreia nervosa seem to prefer serotonin and dopamine receptors (pKi>7). However, with exception of ergometrine/ergometrinine only for 5-HT3A, and histamine H2 and H4 no affinities were predicted. Compared to LSD, LSA exhibited lower binding affinities in the in vitro binding assays for all tested receptor subtypes. However, with a pKi of 7.99, 7.56, and 7.21 a clear affinity for 5-HT1A, 5-HT2, and α2 could be demonstrated. For DA receptor subtypes and the α1-receptor the pKi ranged from 6.05 to 6.85. Since the psychedelic activity of LSA in the recent human study was weak and although LSA from Argyreia nervosa is often considered as natural exchange for LSD, LSA should not be regarded as LSD-like psychedelic drug. However, vegetative side effects and psychotropic effects may be triggered by serotonin or dopamine receptor subtypes. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Homology Modeling of Dopamine D2 and D3 Receptors: Molecular Dynamics Refinement and Docking Evaluation

PubMed Central

Platania, Chiara Bianca Maria; Salomone, Salvatore; Leggio, Gian Marco; Drago, Filippo; Bucolo, Claudio

2012-01-01

Dopamine (DA) receptors, a class of G-protein coupled receptors (GPCRs), have been targeted for drug development for the treatment of neurological, psychiatric and ocular disorders. The lack of structural information about GPCRs and their ligand complexes has prompted the development of homology models of these proteins aimed at structure-based drug design. Crystal structure of human dopamine D3 (hD3) receptor has been recently solved. Based on the hD3 receptor crystal structure we generated dopamine D2 and D3 receptor models and refined them with molecular dynamics (MD) protocol. Refined structures, obtained from the MD simulations in membrane environment, were subsequently used in molecular docking studies in order to investigate potential sites of interaction. The structure of hD3 and hD2L receptors was differentiated by means of MD simulations and D3 selective ligands were discriminated, in terms of binding energy, by docking calculation. Robust correlation of computed and experimental Ki was obtained for hD3 and hD2L receptor ligands. In conclusion, the present computational approach seems suitable to build and refine structure models of homologous dopamine receptors that may be of value for structure-based drug discovery of selective dopaminergic ligands. PMID:22970199

Homology modeling, binding site identification and docking study of human angiotensin II type I (Ang II-AT1) receptor.

PubMed

Vyas, Vivek K; Ghate, Manjunath; Patel, Kinjal; Qureshi, Gulamnizami; Shah, Surmil

2015-08-01

Ang II-AT1 receptors play an important role in mediating virtually all of the physiological actions of Ang II. Several drugs (SARTANs) are available, which can block the AT1 receptor effectively and lower the blood pressure in the patients with hypertension. Currently, there is no experimental Ang II-AT1 structure available; therefore, in this study we modeled Ang II-AT1 receptor structure using homology modeling followed by identification and characterization of binding sites and thereby assessing druggability of the receptor. Homology models were constructed using MODELLER and I-TASSER server, refined and validated using PROCHECK in which 96.9% of 318 residues were present in the favoured regions of the Ramachandran plots. Various Ang II-AT1 receptor antagonist drugs are available in the market as antihypertensive drug, so we have performed docking study with the binding site prediction algorithms to predict different binding pockets on the modeled proteins. The identification of 3D structures and binding sites for various known drugs will guide us for the structure-based drug design of novel compounds as Ang II-AT1 receptor antagonists for the treatment of hypertension. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Multi-criteria ranking and receptor modelling of airborne fine particles at three sites in the Pearl River Delta region of China.

PubMed

Friend, Adrian J; Ayoko, Godwin A; Guo, Hai

2011-01-15

The multi-criteria decision making methods, Preference Ranking Organization METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), and the two-way Positive Matrix Factorization (PMF) receptor model were applied to airborne fine particle compositional data collected at three sites in Hong Kong during two monitoring campaigns held from November 2000 to October 2001 and November 2004 to October 2005. PROMETHEE/GAIA indicated that the three sites were worse during the later monitoring campaign, and that the order of the air quality at the sites during each campaign was: rural site>urban site>roadside site. The PMF analysis on the other hand, identified 6 common sources at all of the sites (diesel vehicle, fresh sea salt, secondary sulphate, soil, aged sea salt and oil combustion) which accounted for approximately 68.8±8.7% of the fine particle mass at the sites. In addition, road dust, gasoline vehicle, biomass burning, secondary nitrate, and metal processing were identified at some of the sites. Secondary sulphate was found to be the highest contributor to the fine particle mass at the rural and urban sites with vehicle emission as a high contributor to the roadside site. The PMF results are broadly similar to those obtained in a previous analysis by PCA/APCS. However, the PMF analysis resolved more factors at each site than the PCA/APCS. In addition, the study demonstrated that combined results from multi-criteria decision making analysis and receptor modelling can provide more detailed information that can be used to formulate the scientific basis for mitigating air pollution in the region. Copyright © 2010 Elsevier B.V. All rights reserved.

Spring-Loaded Model Revisited: Paramyxovirus Fusion Requires Engagement of a Receptor Binding Protein beyond Initial Triggering of the Fusion Protein▿

PubMed Central

Porotto, Matteo; DeVito, Ilaria; Palmer, Samantha G.; Jurgens, Eric M.; Yee, Jia L.; Yokoyama, Christine C.; Pessi, Antonello; Moscona, Anne

2011-01-01

During paramyxovirus entry into a host cell, receptor engagement by a specialized binding protein triggers conformational changes in the adjacent fusion protein (F), leading to fusion between the viral and cell membranes. According to the existing paradigm of paramyxovirus membrane fusion, the initial activation of F by the receptor binding protein sets off a spring-loaded mechanism whereby the F protein progresses independently through the subsequent steps in the fusion process, ending in membrane merger. For human parainfluenza virus type 3 (HPIV3), the receptor binding protein (hemagglutinin-neuraminidase [HN]) has three functions: receptor binding, receptor cleaving, and activating F. We report that continuous receptor engagement by HN activates F to advance through the series of structural rearrangements required for fusion. In contrast to the prevailing model, the role of HN-receptor engagement in the fusion process is required beyond an initiating step, i.e., it is still required even after the insertion of the fusion peptide into the target cell membrane, enabling F to mediate membrane merger. We also report that for Nipah virus, whose receptor binding protein has no receptor-cleaving activity, the continuous stimulation of the F protein by a receptor-engaged binding protein is key for fusion. We suggest a general model for paramyxovirus fusion activation in which receptor engagement plays an active role in F activation, and the continued engagement of the receptor binding protein is essential to F protein function until the onset of membrane merger. This model has broad implications for the mechanism of paramyxovirus fusion and for strategies to prevent viral entry. PMID:21976650

Spring-loaded model revisited: paramyxovirus fusion requires engagement of a receptor binding protein beyond initial triggering of the fusion protein.

PubMed

Porotto, Matteo; Devito, Ilaria; Palmer, Samantha G; Jurgens, Eric M; Yee, Jia L; Yokoyama, Christine C; Pessi, Antonello; Moscona, Anne

2011-12-01

During paramyxovirus entry into a host cell, receptor engagement by a specialized binding protein triggers conformational changes in the adjacent fusion protein (F), leading to fusion between the viral and cell membranes. According to the existing paradigm of paramyxovirus membrane fusion, the initial activation of F by the receptor binding protein sets off a spring-loaded mechanism whereby the F protein progresses independently through the subsequent steps in the fusion process, ending in membrane merger. For human parainfluenza virus type 3 (HPIV3), the receptor binding protein (hemagglutinin-neuraminidase [HN]) has three functions: receptor binding, receptor cleaving, and activating F. We report that continuous receptor engagement by HN activates F to advance through the series of structural rearrangements required for fusion. In contrast to the prevailing model, the role of HN-receptor engagement in the fusion process is required beyond an initiating step, i.e., it is still required even after the insertion of the fusion peptide into the target cell membrane, enabling F to mediate membrane merger. We also report that for Nipah virus, whose receptor binding protein has no receptor-cleaving activity, the continuous stimulation of the F protein by a receptor-engaged binding protein is key for fusion. We suggest a general model for paramyxovirus fusion activation in which receptor engagement plays an active role in F activation, and the continued engagement of the receptor binding protein is essential to F protein function until the onset of membrane merger. This model has broad implications for the mechanism of paramyxovirus fusion and for strategies to prevent viral entry.

A combined ligand-based and target-based drug design approach for G-protein coupled receptors: application to salvinorin A, a selective kappa opioid receptor agonist

NASA Astrophysics Data System (ADS)

Singh, Nidhi; Chevé, Gwénaël; Ferguson, David M.; McCurdy, Christopher R.

2006-08-01

Combined ligand-based and target-based drug design approaches provide a synergistic advantage over either method individually. Therefore, we set out to develop a powerful virtual screening model to identify novel molecular scaffolds as potential leads for the human KOP (hKOP) receptor employing a combined approach. Utilizing a set of recently reported derivatives of salvinorin A, a structurally unique KOP receptor agonist, a pharmacophore model was developed that consisted of two hydrogen bond acceptor and three hydrophobic features. The model was cross-validated by randomizing the data using the CatScramble technique. Further validation was carried out using a test set that performed well in classifying active and inactive molecules correctly. Simultaneously, a bovine rhodopsin based "agonist-bound" hKOP receptor model was also generated. The model provided more accurate information about the putative binding site of salvinorin A based ligands. Several protein structure-checking programs were used to validate the model. In addition, this model was in agreement with the mutation experiments carried out on KOP receptor. The predictive ability of the model was evaluated by docking a set of known KOP receptor agonists into the active site of this model. The docked scores correlated reasonably well with experimental p K i values. It is hypothesized that the integration of these two independently generated models would enable a swift and reliable identification of new lead compounds that could reduce time and cost of hit finding within the drug discovery and development process, particularly in the case of GPCRs.

Insights into unbound-bound states of GPR142 receptor in a membrane-aqueous system using molecular dynamics simulations.

PubMed

Kaushik, Aman Chandra; Sahi, Shakti

2018-05-01

G protein coupled receptors (GPCRs) are source machinery in signal transduction pathways and being one of the major therapeutic targets play a significant in drug discovery. GPR142, an orphan GPCR, has been implicated in the regulation of insulin, thereby having a crucial role in Type II diabetes management. Deciphering of the structures of orphan, GPCRs (O-GPCRs) offer better prospects for advancements in research in ion translocation and transduction of extracellular signals. As the crystallographic structure of GPR142 is not available in PDB, therefore, threading and ab initio-based approaches were used for 3D modeling of GPR142. Molecular dynamic simulations (900 ns) were performed on the 3D model of GPR142 and complexes of GPR142 with top five hits, obtained through virtual screening, embedded in lipid bilayer with aqueous system using OPLS force field. Compound 1, 3, and 4 may act as scaffolds for designing potential lead agonists for GPR142. The finding of GPR142 MD simulation study provides more comprehensive representation of the functional properties. The concern for Type II diabetes is increasing worldwide and successful treatment of this disease demands novel drugs with better efficacy.

Molecular modelling studies on the ORL1-receptor and ORL1-agonists

NASA Astrophysics Data System (ADS)

Bröer, Britta M.; Gurrath, Marion; Höltje, Hans-Dieter

2003-11-01

The ORL1 ( opioid receptor like 1)- receptor is a member of the family of rhodopsin-like G protein-coupled receptors (GPCR) and represents an interesting new therapeutical target since it is involved in a variety of biomedical important processes, such as anxiety, nociception, feeding, and memory. In order to shed light on the molecular basis of the interactions of the GPCR with its ligands, the receptor protein and a dataset of specific agonists were examined using molecular modelling methods. For that purpose, the conformational space of a very potent non-peptide ORL1-receptor agonist (Ro 64-6198) with a small number of rotatable bonds was analysed in order to derive a pharmacophoric arrangement. The conformational analyses yielded a conformation that served as template for the superposition of a set of related analogues. Structural superposition was achieved by employing the program FlexS. Using the experimental binding data and the superposition of the ligands, a 3D-QSAR analysis applying the GRID/GOLPE method was carried out. After the ligand-based modelling approach, a 3D model of the ORL1-receptor has been constructed using homology modelling methods based on the crystal structure of bovine rhodopsin. A representative structure of the model taken from molecular dynamics simulations was used for a manual docking procedure. Asp-130 and Thr-305 within the ORL1-receptor model served as important hydrophilic interaction partners. Furthermore, a hydrophobic cavity was identified stabilizing the agonists within their binding site. The manual docking results were supported using FlexX, which identified the same protein-ligand interaction points.

CoMFA analyses of C-2 position salvinorin A analogs at the kappa-opioid receptor provides insights into epimer selectivity.

PubMed

McGovern, Donna L; Mosier, Philip D; Roth, Bryan L; Westkaemper, Richard B

2010-04-01

The highly potent and kappa-opioid (KOP) receptor-selective hallucinogen Salvinorin A and selected analogs have been analyzed using the 3D quantitative structure-affinity relationship technique Comparative Molecular Field Analysis (CoMFA) in an effort to derive a statistically significant and predictive model of salvinorin affinity at the KOP receptor and to provide additional statistical support for the validity of previously proposed structure-based interaction models. Two CoMFA models of Salvinorin A analogs substituted at the C-2 position are presented. Separate models were developed based on the radioligand used in the kappa-opioid binding assay, [(3)H]diprenorphine or [(125)I]6 beta-iodo-3,14-dihydroxy-17-cyclopropylmethyl-4,5 alpha-epoxymorphinan ([(125)I]IOXY). For each dataset, three methods of alignment were employed: a receptor-docked alignment derived from the structure-based docking algorithm GOLD, another from the ligand-based alignment algorithm FlexS, and a rigid realignment of the poses from the receptor-docked alignment. The receptor-docked alignment produced statistically superior results compared to either the FlexS alignment or the realignment in both datasets. The [(125)I]IOXY set (Model 1) and [(3)H]diprenorphine set (Model 2) gave q(2) values of 0.592 and 0.620, respectively, using the receptor-docked alignment, and both models produced similar CoMFA contour maps that reflected the stereoelectronic features of the receptor model from which they were derived. Each model gave significantly predictive CoMFA statistics (Model 1 PSET r(2)=0.833; Model 2 PSET r(2)=0.813). Based on the CoMFA contour maps, a binding mode was proposed for amine-containing Salvinorin A analogs that provides a rationale for the observation that the beta-epimers (R-configuration) of protonated amines at the C-2 position have a higher affinity than the corresponding alpha-epimers (S-configuration). (c) 2010. Published by Elsevier Inc.

Towards a Quantitative Framework for Evaluating Vulnerability of Drinking Water Wells to Contamination from Unconventional Oil & Gas Development

NASA Astrophysics Data System (ADS)

Soriano, M., Jr.; Deziel, N. C.; Saiers, J. E.

2017-12-01

The rapid expansion of unconventional oil and gas (UO&G) production, made possible by advances in hydraulic fracturing (fracking), has triggered concerns over risks this extraction poses to water resources and public health. Concerns are particularly acute within communities that host UO&G development and rely heavily on shallow aquifers as sources of drinking water. This research aims to develop a quantitative framework to evaluate the vulnerability of drinking water wells to contamination from UO&G activities. The concept of well vulnerability is explored through application of backwards travel time probability modeling to estimate the likelihood that capture zones of drinking water wells circumscribe source locations of UO&G contamination. Sources of UO&G contamination considered in this analysis include gas well pads and documented sites of UO&G wastewater and chemical spills. The modeling approach is illustrated for a portion of Susquehanna County, Pennsylvania, where more than one thousand shale gas wells have been completed since 2005. Data from a network of eight multi-level groundwater monitoring wells installed in the study site in 2015 are used to evaluate the model. The well vulnerability concept is proposed as a physically based quantitative tool for policy-makers dealing with the management of contamination risks of drinking water wells. In particular, the model can be used to identify adequate setback distances of UO&G activities from drinking water wells and other critical receptors.

Key issues in the computational simulation of GPCR function: representation of loop domains

NASA Astrophysics Data System (ADS)

Mehler, E. L.; Periole, X.; Hassan, S. A.; Weinstein, H.

2002-11-01

Some key concerns raised by molecular modeling and computational simulation of functional mechanisms for membrane proteins are discussed and illustrated for members of the family of G protein coupled receptors (GPCRs). Of particular importance are issues related to the modeling and computational treatment of loop regions. These are demonstrated here with results from different levels of computational simulations applied to the structures of rhodopsin and a model of the 5-HT2A serotonin receptor, 5-HT2AR. First, comparative Molecular Dynamics (MD) simulations are reported for rhodopsin in vacuum and embedded in an explicit representation of the membrane and water environment. It is shown that in spite of a partial accounting of solvent screening effects by neutralization of charged side chains, vacuum MD simulations can lead to severe distortions of the loop structures. The primary source of the distortion appears to be formation of artifactual H-bonds, as has been repeatedly observed in vacuum simulations. To address such shortcomings, a recently proposed approach that has been developed for calculating the structure of segments that connect elements of secondary structure with known coordinates, is applied to 5-HT2AR to obtain an initial representation of the loops connecting the transmembrane (TM) helices. The approach consists of a simulated annealing combined with biased scaled collective variables Monte Carlo technique, and is applied to loops connecting the TM segments on both the extra-cellular and the cytoplasmic sides of the receptor. Although this initial calculation treats the loops as independent structural entities, the final structure exhibits a number of interloop interactions that may have functional significance. Finally, it is shown here that in the case where a given loop from two different GPCRs (here rhodopsin and 5-HT2AR) has approximately the same length and some degree of sequence identity, the fold adopted by the loops can be similar. Thus, in such special cases homology modeling might be used to obtain initial structures of these loops. Notably, however, all other loops in these two receptors appear to be very different in sequence and structure, so that their conformations can be found reliably only by ab initio, energy based methods and not by homology modeling.

Kinetic operational models of agonism for G-protein-coupled receptors.

PubMed

Hoare, Samuel R J; Pierre, Nicolas; Moya, Arturo Gonzalez; Larson, Brad

2018-06-07

The application of kinetics to research and therapeutic development of G-protein-coupled receptors has become increasingly valuable. Pharmacological models provide the foundation of pharmacology, providing concepts and measurable parameters such as efficacy and potency that have underlain decades of successful drug discovery. Currently there are few pharmacological models that incorporate kinetic activity in such a way as to yield experimentally-accessible drug parameters. In this study, a kinetic model of pharmacological response was developed that provides a kinetic descriptor of efficacy (the transduction rate constant, k τ ) and allows measurement of receptor-ligand binding kinetics from functional data. The model assumes: (1) receptor interacts with a precursor of the response ("Transduction potential") and converts it to the response. (2) The response can decay. Familiar response vs time plots emerge, depending on whether transduction potential is depleted and/or response decays. These are the straight line, the "association" exponential curve, and the rise-and-fall curve. Convenient, familiar methods are described for measuring the model parameters and files are provided for the curve-fitting program Prism (GraphPad Software) that can be used as a guide. The efficacy parameter k τ is straightforward to measure and accounts for receptor reserve; all that is required is measurement of response over time at a maximally-stimulating concentration of agonist. The modular nature of the model framework allows it to be extended. Here this is done to incorporate antagonist-receptor binding kinetics and slow agonist-receptor equilibration. In principle, the modular framework can incorporate other cellular processes, such as receptor desensitization. The kinetic response model described here can be applied to measure kinetic pharmacological parameters than can be used to advance the understanding of GPCR pharmacology and optimize new and improved therapeutics. Copyright © 2018 Elsevier Ltd. All rights reserved.

A combined computational and structural model of the full-length human prolactin receptor

PubMed Central

Bugge, Katrine; Papaleo, Elena; Haxholm, Gitte W.; Hopper, Jonathan T. S.; Robinson, Carol V.; Olsen, Johan G.; Lindorff-Larsen, Kresten; Kragelund, Birthe B.

2016-01-01

The prolactin receptor is an archetype member of the class I cytokine receptor family, comprising receptors with fundamental functions in biology as well as key drug targets. Structurally, each of these receptors represent an intriguing diversity, providing an exceptionally challenging target for structural biology. Here, we access the molecular architecture of the monomeric human prolactin receptor by combining experimental and computational efforts. We solve the NMR structure of its transmembrane domain in micelles and collect structural data on overlapping fragments of the receptor with small-angle X-ray scattering, native mass spectrometry and NMR spectroscopy. Along with previously published data, these are integrated by molecular modelling to generate a full receptor structure. The result provides the first full view of a class I cytokine receptor, exemplifying the architecture of more than 40 different receptor chains, and reveals that the extracellular domain is merely the tip of a molecular iceberg. PMID:27174498

LS-APC v1.0: a tuning-free method for the linear inverse problem and its application to source-term determination

NASA Astrophysics Data System (ADS)

Tichý, Ondřej; Šmídl, Václav; Hofman, Radek; Stohl, Andreas

2016-11-01

Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. It is typically formalized as an inverse problem using a linear model that can explain observable quantities (e.g., concentrations or deposition values) as a product of the source-receptor sensitivity (SRS) matrix obtained from an atmospheric transport model multiplied by the unknown source-term vector. Since this problem is typically ill-posed, current state-of-the-art methods are based on regularization of the problem and solution of a formulated optimization problem. This procedure depends on manual settings of uncertainties that are often very poorly quantified, effectively making them tuning parameters. We formulate a probabilistic model, that has the same maximum likelihood solution as the conventional method using pre-specified uncertainties. Replacement of the maximum likelihood solution by full Bayesian estimation also allows estimation of all tuning parameters from the measurements. The estimation procedure is based on the variational Bayes approximation which is evaluated by an iterative algorithm. The resulting method is thus very similar to the conventional approach, but with the possibility to also estimate all tuning parameters from the observations. The proposed algorithm is tested and compared with the standard methods on data from the European Tracer Experiment (ETEX) where advantages of the new method are demonstrated. A MATLAB implementation of the proposed algorithm is available for download.

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.

The Development and Uses of EPA's SPECIATE Database

EPA Science Inventory

SPECIATE is the U.S. Environmental Protection Agency's (EPA) repository of volatile organic compounds (VOC) and particulate matter (PM) speciation profiles of air pollution sources. These source profiles can be used to (l) provide input to chemical mass balance (CMB) receptor mod...

All-Atom Structural Models of the Transmembrane Domains of Insulin and Type 1 Insulin-Like Growth Factor Receptors

PubMed Central

Mohammadiarani, Hossein; Vashisth, Harish

2016-01-01

The receptor tyrosine kinase superfamily comprises many cell-surface receptors including the insulin receptor (IR) and type 1 insulin-like growth factor receptor (IGF1R) that are constitutively homodimeric transmembrane glycoproteins. Therefore, these receptors require ligand-triggered domain rearrangements rather than receptor dimerization for activation. Specifically, binding of peptide ligands to receptor ectodomains transduces signals across the transmembrane domains for trans-autophosphorylation in cytoplasmic kinase domains. The molecular details of these processes are poorly understood in part due to the absence of structures of full-length receptors. Using MD simulations and enhanced conformational sampling algorithms, we present all-atom structural models of peptides containing 51 residues from the transmembrane and juxtamembrane regions of IR and IGF1R. In our models, the transmembrane regions of both receptors adopt helical conformations with kinks at Pro961 (IR) and Pro941 (IGF1R), but the C-terminal residues corresponding to the juxtamembrane region of each receptor adopt unfolded and flexible conformations in IR as opposed to a helix in IGF1R. We also observe that the N-terminal residues in IR form a kinked-helix sitting at the membrane–solvent interface, while homologous residues in IGF1R are unfolded and flexible. These conformational differences result in a larger tilt-angle of the membrane-embedded helix in IGF1R in comparison to IR to compensate for interactions with water molecules at the membrane–solvent interfaces. Our metastable/stable states for the transmembrane domain of IR, observed in a lipid bilayer, are consistent with a known NMR structure of this domain determined in detergent micelles, and similar states in IGF1R are consistent with a previously reported model of the dimerized transmembrane domains of IGF1R. Our all-atom structural models suggest potentially unique structural organization of kinase domains in each receptor. PMID:27379020

Interleukin-3 enhances the migration of human mesenchymal stem cells by regulating expression of CXCR4.

PubMed

Barhanpurkar-Naik, Amruta; Mhaske, Suhas T; Pote, Satish T; Singh, Kanupriya; Wani, Mohan R

2017-07-14

Mesenchymal stem cells (MSCs) represent an important source for cell therapy in regenerative medicine. MSCs have shown promising results for repair of damaged tissues in various degenerative diseases in animal models and also in human clinical trials. However, little is known about the factors that could enhance the migration and tissue-specific engraftment of exogenously infused MSCs for successful regenerative cell therapy. Previously, we have reported that interleukin-3 (IL-3) prevents bone and cartilage damage in animal models of rheumatoid arthritis and osteoarthritis. Also, IL-3 promotes the differentiation of human MSCs into functional osteoblasts and increases their in-vivo bone regenerative potential in immunocompromised mice. However, the role of IL-3 in migration of MSCs is not yet known. In the present study, we investigated the role of IL-3 in migration of human MSCs under both in-vitro and in-vivo conditions. MSCs isolated from human bone marrow, adipose and gingival tissues were used for in-vitro cell migration, motility and wound healing assays in the presence or absence of IL-3. The effect of IL-3 preconditioning on expression of chemokine receptors and integrins was examined by flow cytometry and real-time PCR. The in-vivo migration of IL-3-preconditioned MSCs was investigated using a subcutaneous matrigel-releasing stromal cell-derived factor-1 alpha (SDF-1α) model in immunocompromised mice. We observed that human MSCs isolated from all three sources express IL-3 receptor-α (IL-3Rα) both at gene and protein levels. IL-3 significantly enhances in-vitro migration, motility and wound healing abilities of MSCs. Moreover, IL-3 preconditioning upregulates expression of chemokine (C-X-C motif) receptor 4 (CXCR4) on MSCs, which leads to increased migration of cells towards SDF-1α. Furthermore, CXCR4 antagonist AMD3100 decreases the migration of IL-3-treated MSCs towards SDF-1α. Importantly, IL-3 also induces in-vivo migration of MSCs towards subcutaneously implanted matrigel-releasing-SDF-1α in immunocompromised mice. The present study demonstrates for the first time that IL-3 has an important role in enhancing the migration of human MSCs through regulation of the CXCR4/SDF-1α axis. These findings suggest a potential role of IL-3 in improving the efficacy of MSCs in regenerative cell therapy.

α7 nicotinic ACh receptors as a ligand-gated source of Ca(2+) ions: the search for a Ca(2+) optimum.

PubMed

Uteshev, Victor V

2012-01-01

The spatiotemporal distribution of cytosolic Ca(2+) ions is a key determinant of neuronal behavior and survival. Distinct sources of Ca(2+) ions including ligand- and voltage-gated Ca(2+) channels contribute to intracellular Ca(2+) homeostasis. Many normal physiological and therapeutic neuronal functions are Ca(2+)-dependent, however an excess of cytosolic Ca(2+) or a lack of the appropriate balance between Ca(2+) entry and clearance may destroy cellular integrity and cause cellular death. Therefore, the existence of optimal spatiotemporal patterns of cytosolic Ca(2+) elevations and thus, optimal activation of ligand- and voltage-gated Ca(2+) ion channels are postulated to benefit neuronal function and survival. Alpha7 nicotinic -acetylcholine receptors (nAChRs) are highly permeable to Ca(2+) ions and play an important role in modulation of neurotransmitter release, gene expression and neuroprotection in a variety of neuronal and non-neuronal cells. In this review, the focus is placed on α7 nAChR-mediated currents and Ca(2+) influx and how this source of Ca(2+) entry compares to NMDA receptors in supporting cytosolic Ca(2+) homeostasis, neuronal function and survival.

Functional dissociation in sweet taste receptor neurons between and within taste organs of Drosophila

PubMed Central

Thoma, Vladimiros; Knapek, Stephan; Arai, Shogo; Hartl, Marion; Kohsaka, Hiroshi; Sirigrivatanawong, Pudith; Abe, Ayako; Hashimoto, Koichi; Tanimoto, Hiromu

2016-01-01

Finding food sources is essential for survival. Insects detect nutrients with external taste receptor neurons. Drosophila possesses multiple taste organs that are distributed throughout its body. However, the role of different taste organs in feeding remains poorly understood. By blocking subsets of sweet taste receptor neurons, we show that receptor neurons in the legs are required for immediate sugar choice. Furthermore, we identify two anatomically distinct classes of sweet taste receptor neurons in the leg. The axonal projections of one class terminate in the thoracic ganglia, whereas the other projects directly to the brain. These two classes are functionally distinct: the brain-projecting neurons are involved in feeding initiation, whereas the thoracic ganglia-projecting neurons play a role in sugar-dependent suppression of locomotion. Distinct receptor neurons for the same taste quality may coordinate early appetitive responses, taking advantage of the legs as the first appendages to contact food. PMID:26893070

Neither Lys- and DAP-type peptidoglycans stimulate mouse or human innate immune cells via Toll-like receptor 2

PubMed Central

Langer, Marybeth; Girton, Alanson W.; Popescu, Narcis I.; Burgett, Tarea; Metcalf, Jordan P.

2018-01-01

Peptidoglycan (PGN), a major component of bacterial cell walls, is a pathogen-associated molecular pattern (PAMP) that causes innate immune cells to produce inflammatory cytokines that escalate the host response during infection. In order to better understand the role of PGN in infection, we wanted to gain insight into the cellular receptor for PGN. Although the receptor was initially identified as Toll-like receptor 2 (TLR2), this receptor has remained controversial and other PGN receptors have been reported. We produced PGN from live cultures of Bacillus anthracis and Staphylococcus aureus and tested samples of PGN isolated during the purification process to determine at what point TLR2 activity was removed, if at all. Our results indicate that although live B. anthracis and S. aureus express abundant TLR2 ligands, highly-purified PGN from either bacterial source is not recognized by TLR2. PMID:29474374

Integrated experimental and model-based analysis reveals the spatial aspects of EGFR activation dynamics

PubMed Central

Shankaran, Harish; Zhang, Yi; Chrisler, William B.; Ewald, Jonathan A.; Wiley, H. Steven; Resat, Haluk

2012-01-01

The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models to determine the contributions of receptor dimerization and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor phosphorylation kinetics at the cell surface and early endosomes are comparable. We validated the last finding by measuring the EGFR dephosphorylation rates at various times following ligand addition both in whole cells and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. This study demonstrates that an iterative cycle of experiments and modeling can be used to gain mechanistic insight regarding complex cell signaling networks. PMID:22952062

Receptor-based 3D QSAR analysis of estrogen receptor ligands - merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods

NASA Astrophysics Data System (ADS)

Sippl, Wolfgang

2000-08-01

One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient ( r 2 = 0.617, q 2 LOO = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained ( r 2 = 0.991, q 2 LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment ( r 2 = 0.951, q 2 LOO = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model.

Generalized paired-agent kinetic model for in vivo quantification of cancer cell-surface receptors under receptor saturation conditions

NASA Astrophysics Data System (ADS)

Sadeghipour, N.; Davis, S. C.; Tichauer, K. M.

2017-01-01

New precision medicine drugs oftentimes act through binding to specific cell-surface cancer receptors, and thus their efficacy is highly dependent on the availability of those receptors and the receptor concentration per cell. Paired-agent molecular imaging can provide quantitative information on receptor status in vivo, especially in tumor tissue; however, to date, published approaches to paired-agent quantitative imaging require that only ‘trace’ levels of imaging agent exist compared to receptor concentration. This strict requirement may limit applicability, particularly in drug binding studies, which seek to report on a biological effect in response to saturating receptors with a drug moiety. To extend the regime over which paired-agent imaging may be used, this work presents a generalized simplified reference tissue model (GSRTM) for paired-agent imaging developed to approximate receptor concentration in both non-receptor-saturated and receptor-saturated conditions. Extensive simulation studies show that tumor receptor concentration estimates recovered using the GSRTM are more accurate in receptor-saturation conditions than the standard simple reference tissue model (SRTM) (% error (mean  ±  sd): GSRTM 0  ±  1 and SRTM 50  ±  1) and match the SRTM accuracy in non-saturated conditions (% error (mean  ±  sd): GSRTM 5  ±  5 and SRTM 0  ±  5). To further test the approach, GSRTM-estimated receptor concentration was compared to SRTM-estimated values extracted from tumor xenograft in vivo mouse model data. The GSRTM estimates were observed to deviate from the SRTM in tumors with low receptor saturation (which are likely in a saturated regime). Finally, a general ‘rule-of-thumb’ algorithm is presented to estimate the expected level of receptor saturation that would be achieved in a given tissue provided dose and pharmacokinetic information about the drug or imaging agent being used, and physiological information about the tissue. These studies suggest that the GSRTM is necessary when receptor saturation exceeds 20% and highlight the potential for GSRTM to accurately measure receptor concentrations under saturation conditions, such as might be required during high dose drug studies, or for imaging applications where high concentrations of imaging agent are required to optimize signal-to-noise conditions. This model can also be applied to PET and SPECT imaging studies that tend to suffer from noisier data, but require one less parameter to fit if images are converted to imaging agent concentration (quantitative PET/SPECT).

An assessment of the effects of serotonin 6 (5-HT6) receptor antagonists in rodent models of learning.

PubMed

Lindner, Mark D; Hodges, Donald B; Hogan, John B; Orie, Anitra F; Corsa, Jason A; Barten, Donna M; Polson, Craig; Robertson, Barbara J; Guss, Valerie L; Gillman, Kevin W; Starrett, John E; Gribkoff, Valentin K

2003-11-01

Antagonists of serotonin 6 (5-HT6) receptors have been reported to enhance cognition in animal models of learning, although this finding has not been universal. We have assessed the therapeutic potential of the specific 5-HT6 receptor antagonists 4-amino-N-(2,6-bis-methylamino-pyrimidin-4-yl)-benzenesulfonamide (Ro 04-6790) and 5-chloro-N-(4-methoxy-3-piperazin-1-yl-phenyl)-3-methyl-2-benzothiophenesulfonamide (SB-271046) in rodent models of cognitive function. Although mice express the 5-HT6 receptor and the function of this receptor has been investigated in mice, all reports of activity with 5-HT6 receptor antagonists have used rat models. In the present study, receptor binding revealed that the pharmacological properties of the mouse receptor are different from the rat and human receptor: Ro 04-6790 does not bind to the mouse 5-HT6 receptor, so all in vivo testing included in the present report was conducted in rats. We replicated previous reports that 5-HT6 receptor antagonists produce a stretching syndrome previously shown to be mediated through cholinergic mechanisms, but Ro 04-6790 and SB-271046 failed to attenuate scopolamine-induced deficits in a test of contextual fear conditioning. We also failed to replicate the significant effects reported previously in both an autoshaping task and in a version of the Morris water maze. The results of our experiments are not consistent with previous reports that suggested that 5-HT6 antagonists might have therapeutic potential for cognitive disorders.

Melanocortin MC1 receptor in human genetics and model systems

PubMed Central

Beaumont, Kimberley A.; Wong, Shu S.; Ainger, Stephen A.; Liu, Yan Yan; Patel, Mira P.; Millhauser, Glenn L.; Smith, Jennifer J.; Alewood, Paul F.; Leonard, J. Helen; Sturm, Richard A.

2011-01-01

The melanocortin MC1 receptor is a G -protein coupled receptor expressed in melanocytes of the skin and hair and is known for its key role in regulation of human pigmentation. Melanocortin MC1 receptor activation after ultraviolet radiation exposure results in a switch from the red/yellow pheomelanin to the brown/black eumelanin pigment synthesis within cutaneous melanocytes; this pigment is then transferred to the surrounding keratinocytes of the skin. The increase in melanin maturation and uptake results in tanning of the skin, providing a physical protection of skin cells from ultraviolet radiation induced DNA damage. Melanocortin MC 1 receptor polymorphism is widespread within the Caucasian population and some variant alleles are associated with red hair colour, fair skin, poor tanning and increased risk of skin cancer. Here we will discuss the use of mouse coat colour models, human genetic association studies, and in vitro cell culture studies to determine the complex functions of the melanocortin MC1 receptor and the molecular mechanisms underlying the association between melanocortin MC1 receptor variant alleles and the red hair colour phenotype. Recent research indicates that melanocortin MC1 receptor has many non-pigmentary functions, and that the increased risk of skin cancer conferred by melanocortin MC1 receptor variant alleles is to some extent independent of pigmentation phenotypes. The use of new transgenic mouse models, the study of novel melanocortin MC1 receptor response genes and the use of more advanced human skin models such as 3D skin reconstruction may provide key elements in understanding the pharmacogenetics of human melanocortin MC1 receptor polymorphism . PMID:21199646

A competitive binding model predicts the response of mammalian olfactory receptors to mixtures

NASA Astrophysics Data System (ADS)

Singh, Vijay; Murphy, Nicolle; Mainland, Joel; Balasubramanian, Vijay

Most natural odors are complex mixtures of many odorants, but due to the large number of possible mixtures only a small fraction can be studied experimentally. To get a realistic understanding of the olfactory system we need methods to predict responses to complex mixtures from single odorant responses. Focusing on mammalian olfactory receptors (ORs in mouse and human), we propose a simple biophysical model for odor-receptor interactions where only one odor molecule can bind to a receptor at a time. The resulting competition for occupancy of the receptor accounts for the experimentally observed nonlinear mixture responses. We first fit a dose-response relationship to individual odor responses and then use those parameters in a competitive binding model to predict mixture responses. With no additional parameters, the model predicts responses of 15 (of 18 tested) receptors to within 10 - 30 % of the observed values, for mixtures with 2, 3 and 12 odorants chosen from a panel of 30. Extensions of our basic model with odorant interactions lead to additional nonlinearities observed in mixture response like suppression, cooperativity, and overshadowing. Our model provides a systematic framework for characterizing and parameterizing such mixing nonlinearities from mixture response data.

Modelling and simulation of biased agonism dynamics at a G protein-coupled receptor.

PubMed

Bridge, L J; Mead, J; Frattini, E; Winfield, I; Ladds, G

2018-04-07

Theoretical models of G protein-coupled receptor (GPCR) concentration-response relationships often assume an agonist producing a single functional response via a single active state of the receptor. These models have largely been analysed assuming steady-state conditions. There is now much experimental evidence to suggest that many GPCRs can exist in multiple receptor conformations and elicit numerous functional responses, with ligands having the potential to activate different signalling pathways to varying extents-a concept referred to as biased agonism, functional selectivity or pluri-dimensional efficacy. Moreover, recent experimental results indicate a clear possibility for time-dependent bias, whereby an agonist's bias with respect to different pathways may vary dynamically. Efforts towards understanding the implications of temporal bias by characterising and quantifying ligand effects on multiple pathways will clearly be aided by extending current equilibrium binding and biased activation models to include G protein activation dynamics. Here, we present a new model of time-dependent biased agonism, based on ordinary differential equations for multiple cubic ternary complex activation models with G protein cycle dynamics. This model allows simulation and analysis of multi-pathway activation bias dynamics at a single receptor for the first time, at the level of active G protein (α GTP ), towards the analysis of dynamic functional responses. The model is generally applicable to systems with N G G proteins and N* active receptor states. Numerical simulations for N G =N * =2 reveal new insights into the effects of system parameters (including cooperativities, and ligand and receptor concentrations) on bias dynamics, highlighting new phenomena including the dynamic inter-conversion of bias direction. Further, we fit this model to 'wet' experimental data for two competing G proteins (G i and G s ) that become activated upon stimulation of the adenosine A 1 receptor with adenosine derivative compounds. Finally, we show that our model can qualitatively describe the temporal dynamics of this competing G protein activation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

An Allosteric Coagonist Model for Propofol Effects on α1β2γ2L γ-Aminobutyric Acid Type A Receptors

PubMed Central

Ruesch, Dirk; Neumann, Elena; Wulf, Hinnerk; Forman, Stuart A.

2011-01-01

Background Propofol produces its major actions via γ-aminobutyric acid type A (GABAA) receptors. At low concentrations, propofol enhances agonist-stimulated GABAA receptor activity, and high propofol concentrations directly activate receptors. Etomidate produces similar effects, and there is convincing evidence that a single class of etomidate sites mediate both agonist modulation and direct GABAA receptor activation. It is unknown if the propofol binding site(s) on GABAA receptors that modulate agonist-induced activity also mediate direct activation. Methods GABAA α1β2γ2L receptors were heterologously expressed in Xenopus oocytes and activity was quantified using voltage clamp electrophysiology. We tested whether propofol and etomidate display the same linkage between agonist modulation and direct activation of GABAA receptors by identifying equi-efficacious drug solutions for direct activation. We then determined whether these drug solutions produce equal modulation of GABA-induced receptor activity. We also measured propofol-dependent direct activation and modulation of low GABA responses. Allosteric coagonist models similar to that established for etomidate, but with variable numbers of propofol sites, were fitted to combined data. Results Solutions of 19 μM propofol and 10 μM etomidate were found to equally activate GABAA receptors. These two drug solutions also produced indistinguishable modulation of GABA-induced receptor activity. Combined electrophysiological data behaved in a manner consistent with allosteric co-agonist models with more than one propofol site. The best fit was observed when the model assumed three equivalent propofol sites. Conclusions Our results support the hypothesis that propofol, like etomidate, acts at GABAA receptor sites mediating both GABA modulation and direct activation. PMID:22104494

Spatio-temporal patterns and source apportionment of pollution in Qiantang River (China) using neural-based modeling and multivariate statistical techniques

NASA Astrophysics Data System (ADS)

Su, Shiliang; Zhi, Junjun; Lou, Liping; Huang, Fang; Chen, Xia; Wu, Jiaping

Characterizing the spatio-temporal patterns and apportioning the pollution sources of water bodies are important for the management and protection of water resources. The main objective of this study is to describe the dynamics of water quality and provide references for improving river pollution control practices. Comprehensive application of neural-based modeling and different multivariate methods was used to evaluate the spatio-temporal patterns and source apportionment of pollution in Qiantang River, China. Measurement data were obtained and pretreated for 13 variables from 41 monitoring sites for the period of 2001-2004. A self-organizing map classified the 41 monitoring sites into three groups (Group A, B and C), representing different pollution characteristics. Four significant parameters (dissolved oxygen, biochemical oxygen demand, total phosphorus and total lead) were identified by discriminant analysis for distinguishing variations of different years, with about 80% correct assignment for temporal variation. Rotated principal component analysis (PCA) identified four potential pollution sources for Group A (domestic sewage and agricultural pollution, industrial wastewater pollution, mineral weathering, vehicle exhaust and sand mining), five for Group B (heavy metal pollution, agricultural runoff, vehicle exhaust and sand mining, mineral weathering, chemical plants discharge) and another five for Group C (vehicle exhaust and sand mining, chemical plants discharge, soil weathering, biochemical pollution, mineral weathering). The identified potential pollution sources explained 75.6% of the total variances for Group A, 75.0% for Group B and 80.0% for Group C, respectively. Receptor-based source apportionment was applied to further estimate source contributions for each pollution variable in the three groups, which facilitated and supported the PCA results. These results could assist managers to develop optimal strategies and determine priorities for river pollution control and effective water resources management.

Identifing Atmospheric Pollutant Sources Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Paes, F. F.; Campos, H. F.; Luz, E. P.; Carvalho, A. R.

2008-05-01

The estimation of the area source pollutant strength is a relevant issue for atmospheric environment. This characterizes an inverse problem in the atmospheric pollution dispersion. In the inverse analysis, an area source domain is considered, where the strength of such area source term is assumed unknown. The inverse problem is solved by using a supervised artificial neural network: multi-layer perceptron. The conection weights of the neural network are computed from delta rule - learning process. The neural network inversion is compared with results from standard inverse analysis (regularized inverse solution). In the regularization method, the inverse problem is formulated as a non-linear optimization approach, whose the objective function is given by the square difference between the measured pollutant concentration and the mathematical models, associated with a regularization operator. In our numerical experiments, the forward problem is addressed by a source-receptor scheme, where a regressive Lagrangian model is applied to compute the transition matrix. The second order maximum entropy regularization is used, and the regularization parameter is calculated by the L-curve technique. The objective function is minimized employing a deterministic scheme (a quasi-Newton algorithm) [1] and a stochastic technique (PSO: particle swarm optimization) [2]. The inverse problem methodology is tested with synthetic observational data, from six measurement points in the physical domain. The best inverse solutions were obtained with neural networks. References: [1] D. R. Roberti, D. Anfossi, H. F. Campos Velho, G. A. Degrazia (2005): Estimating Emission Rate and Pollutant Source Location, Ciencia e Natura, p. 131-134. [2] E.F.P. da Luz, H.F. de Campos Velho, J.C. Becceneri, D.R. Roberti (2007): Estimating Atmospheric Area Source Strength Through Particle Swarm Optimization. Inverse Problems, Desing and Optimization Symposium IPDO-2007, April 16-18, Miami (FL), USA, vol 1, p. 354-359.

Molecular modeling of ligand-receptor interactions in the OR5 olfactory receptor.

PubMed

Singer, M S; Shepherd, G M

1994-06-02

Olfactory receptors belong to the superfamily of seven transmembrane domain, G protein-coupled receptors. In order to begin analysis of mechanisms of receptor activation, a computer model of the OR5 olfactory receptor has been constructed and compared with other members of this superfamily. We have tested docking of the odor molecule lyral, which is known to activate the OR5 receptor. The results point to specific ligand-binding residues on helices III through VII that form a binding pocket in the receptor. Some of these residues occupy sequence positions identical to ligand-binding residues conserved among other superfamily members. The results provide new insights into possible molecular mechanisms of odor recognition and suggest hypotheses to guide future experimental studies using site-directed mutagenesis.

The heterodimeric sweet taste receptor has multiple potential ligand binding sites.

PubMed

Cui, Meng; Jiang, Peihua; Maillet, Emeline; Max, Marianna; Margolskee, Robert F; Osman, Roman

2006-01-01

The sweet taste receptor is a heterodimer of two G protein coupled receptors, T1R2 and T1R3. This discovery has increased our understanding at the molecular level of the mechanisms underlying sweet taste. Previous experimental studies using sweet receptor chimeras and mutants show that there are at least three potential binding sites in this heterodimeric receptor. Receptor activity toward the artificial sweeteners aspartame and neotame depends on residues in the amino terminal domain of human T1R2. In contrast, receptor activity toward the sweetener cyclamate and the sweet taste inhibitor lactisole depends on residues within the transmembrane domain of human T1R3. Furthermore, receptor activity toward the sweet protein brazzein depends on the cysteine rich domain of human T1R3. Although crystal structures are not available for the sweet taste receptor, useful homology models can be developed based on appropriate templates. The amino terminal domain, cysteine rich domain and transmembrane helix domain of T1R2 and T1R3 have been modeled based on the crystal structures of metabotropic glutamate receptor type 1, tumor necrosis factor receptor, and bovine rhodopsin, respectively. We have used homology models of the sweet taste receptors, molecular docking of sweet ligands to the receptors, and site-directed mutagenesis of the receptors to identify potential ligand binding sites of the sweet taste receptor. These studies have led to a better understanding of the structure and function of this heterodimeric receptor, and can act as a guide for rational structure-based design of novel non-caloric sweeteners, which can be used in the fighting against obesity and diabetes.

Quantitative in vivo receptor binding. III. Tracer kinetic modeling of muscarinic cholinergic receptor binding

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

Frey, K.A.; Hichwa, R.D.; Ehrenkaufer, R.L.

1985-10-01

A tracer kinetic method is developed for the in vivo estimation of high-affinity radioligand binding to central nervous system receptors. Ligand is considered to exist in three brain pools corresponding to free, nonspecifically bound, and specifically bound tracer. These environments, in addition to that of intravascular tracer, are interrelated by a compartmental model of in vivo ligand distribution. A mathematical description of the model is derived, which allows determination of regional blood-brain barrier permeability, nonspecific binding, the rate of receptor-ligand association, and the rate of dissociation of bound ligand, from the time courses of arterial blood and tissue tracer concentrations.more » The term ''free receptor density'' is introduced to describe the receptor population measured by this method. The technique is applied to the in vivo determination of regional muscarinic acetylcholine receptors in the rat, with the use of (TH)scopolamine. Kinetic estimates of free muscarinic receptor density are in general agreement with binding capacities obtained from previous in vivo and in vitro equilibrium binding studies. In the striatum, however, kinetic estimates of free receptor density are less than those in the neocortex--a reversal of the rank ordering of these regions derived from equilibrium determinations. A simplified model is presented that is applicable to tracers that do not readily dissociate from specific binding sites during the experimental period.« less

The neuropsychopharmacology of phencyclidine: from NMDA receptor hypofunction to the dopamine hypothesis of schizophrenia.

PubMed

Jentsch, J D; Roth, R H

1999-03-01

Administration of noncompetitive NMDA/glutamate receptor antagonists, such as phencyclidine (PCP) and ketamine, to humans induces a broad range of schizophrenic-like symptomatology, findings that have contributed to a hypoglutamatergic hypothesis of schizophrenia. Moreover, a history of experimental investigations of the effects of these drugs in animals suggests that NMDA receptor antagonists may model some behavioral symptoms of schizophrenia in nonhuman subjects. In this review, the usefulness of PCP administration as a potential animal model of schizophrenia is considered. To support the contention that NMDA receptor antagonist administration represents a viable model of schizophrenia, the behavioral and neurobiological effects of these drugs are discussed, especially with regard to differing profiles following single-dose and long-term exposure. The neurochemical effects of NMDA receptor antagonist administration are argued to support a neurobiological hypothesis of schizophrenia, which includes pathophysiology within several neurotransmitter systems, manifested in behavioral pathology. Future directions for the application of NMDA receptor antagonist models of schizophrenia to preclinical and pathophysiological research are offered.

DockoMatic 2.0: High Throughput Inverse Virtual Screening and Homology Modeling

PubMed Central

Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T.; McDougal, Owen M.; Andersen, Timothy L.

2013-01-01

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly Graphical User Interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to: (1) conduct high throughput Inverse Virtual Screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying a receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories, and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELLER programs, and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education. PMID:23808933

Long-Range Regulatory Polymorphisms Affecting a GABA Receptor Constitute a Quantitative Trait Locus (QTL) for Social Behavior in Caenorhabditis elegans

PubMed Central

Bendesky, Andres; Pitts, Jason; Rockman, Matthew V.; Chen, William C.; Tan, Man-Wah; Kruglyak, Leonid; Bargmann, Cornelia I.

2012-01-01

Aggregation is a social behavior that varies between and within species, providing a model to study the genetic basis of behavioral diversity. In the nematode Caenorhabditis elegans, aggregation is regulated by environmental context and by two neuromodulatory pathways, one dependent on the neuropeptide receptor NPR-1 and one dependent on the TGF-β family protein DAF-7. To gain further insight into the genetic regulation of aggregation, we characterize natural variation underlying behavioral differences between two wild-type C. elegans strains, N2 and CB4856. Using quantitative genetic techniques, including a survey of chromosome substitution strains and QTL analysis of recombinant inbred lines, we identify three new QTLs affecting aggregation in addition to the two known N2 mutations in npr-1 and glb-5. Fine-mapping with near-isogenic lines localized one QTL, accounting for 5%–8% of the behavioral variance between N2 and CB4856, 3′ to the transcript of the GABA neurotransmitter receptor gene exp-1. Quantitative complementation tests demonstrated that this QTL affects exp-1, identifying exp-1 and GABA signaling as new regulators of aggregation. exp-1 interacts genetically with the daf-7 TGF-β pathway, which integrates food availability and population density, and exp-1 mutations affect the level of daf-7 expression. Our results add to growing evidence that genetic variation affecting neurotransmitter receptor genes is a source of natural behavioral variation. PMID:23284308

A simple method to assess unsaturated zone time lag in the travel time from ground surface to receptor.

PubMed

Sousa, Marcelo R; Jones, Jon P; Frind, Emil O; Rudolph, David L

2013-01-01

In contaminant travel from ground surface to groundwater receptors, the time taken in travelling through the unsaturated zone is known as the unsaturated zone time lag. Depending on the situation, this time lag may or may not be significant within the context of the overall problem. A method is presented for assessing the importance of the unsaturated zone in the travel time from source to receptor in terms of estimates of both the absolute and the relative advective times. A choice of different techniques for both unsaturated and saturated travel time estimation is provided. This method may be useful for practitioners to decide whether to incorporate unsaturated processes in conceptual and numerical models and can also be used to roughly estimate the total travel time between points near ground surface and a groundwater receptor. This method was applied to a field site located in a glacial aquifer system in Ontario, Canada. Advective travel times were estimated using techniques with different levels of sophistication. The application of the proposed method indicates that the time lag in the unsaturated zone is significant at this field site and should be taken into account. For this case, sophisticated and simplified techniques lead to similar assessments when the same knowledge of the hydraulic conductivity field is assumed. When there is significant uncertainty regarding the hydraulic conductivity, simplified calculations did not lead to a conclusive decision. Copyright © 2012 Elsevier B.V. All rights reserved.

The effect of combination treatment with aliskiren and blockers of the renin-angiotensin system on hyperkalaemia and acute kidney injury: systematic review and meta-analysis

PubMed Central

Gilbert, Cameron; Wald, Ron; Bell, Chaim; Perl, Jeff; Juurlink, David; Beyene, Joseph; Shah, Prakesh S

2012-01-01

Objective To examine the safety of using aliskiren combined with agents used to block the renin-angiotensin system. Design Systematic review and meta-analysis of randomised controlled trials. Data sources Medline, Embase, the Cochrane Library, and two trial registries, published up to 7 May 2011. Study selection Published and unpublished randomised controlled trials that compared combined treatment using aliskiren and angiotensin converting enzyme inhibitors or angiotensin receptor blockers with monotherapy using these agents for at least four weeks and that provided numerical data on the adverse event outcomes of hyperkalaemia and acute kidney injury. A random effects model was used to calculate pooled risk ratios and 95% confidence intervals for these outcomes. Results 10 randomised controlled studies (4814 participants) were included in the analysis. Combination therapy with aliskiren and angiotensin converting enzyme inhibitors or angiotensin receptor blockers significantly increased the risk of hyperkalaemia compared with monotherapy using angiotensin converting enzymes or angiotensin receptor blockers (relative risk 1.58, 95% confidence interval 1.24 to 2.02) or aliskiren alone (1.67, 1.01 to 2.79). The risk of acute kidney injury did not differ significantly between the combined therapy and monotherapy groups (1.14, 0.68 to 1.89). Conclusion Use of aliskerin in combination with angiotensin converting enzyme inhibitors or angiotensin receptor blockers is associated with an increased risk for hyperkalaemia. The combined use of these agents warrants careful monitoring of serum potassium levels. PMID:22232539

Dynamic Receptor Team Formation Can Explain the High Signal Transduction Gain in Escherichia coli

NASA Astrophysics Data System (ADS)

Albert, R.; Chiu, Y.; Othmer, H.

2004-05-01

Evolution has provided many organisms with sophisticated sensory systems that enable them to respond to signals in their environment. The response frequently involves alteration in the pattern of movement, such as the chemokinesis of the bacterium Escherichia coli, which swims by rotating its flagella. When rotated counterclockwise (CCW) the flagella coalesce into a propulsive bundle, producing a relatively straight ``run'', and when rotated clockwise (CW) they fly apart, resulting in a ``tumble'' which reorients the cell with little translocation. A stochastic process generates the runs and tumbles, and in a chemoeffector gradient runs that carry the cell in a favorable direction are extended. The overall structure of the signal transduction pathways is well-characterized in E. coli, but important details are still not understood. Only recently has a source of gain in the signal transduction network been identified experimentally, and here we present a mathematical model based on dynamic assembly of receptor teams that can explain this observation.

The High-Resolution Structure of Activated Opsin Reveals a Conserved Solvent Network in the Transmembrane Region Essential for Activation.

PubMed

Blankenship, Elise; Vahedi-Faridi, Ardeschir; Lodowski, David T

2015-12-01

Rhodopsin, a light-activated G protein coupled receptor (GPCR), has been the subject of numerous biochemical and structural investigations, serving as a model receptor for GPCRs and their activation. We present the 2.3-Å resolution structure of native source rhodopsin stabilized in a conformation competent for G protein binding. An extensive water-mediated hydrogen bond network linking the chromophore binding site to the site of G protein binding is observed, providing connections to conserved motifs essential for GPCR activation. Comparison of this extensive solvent-mediated hydrogen-bonding network with the positions of ordered solvent in earlier crystallographic structures of rhodopsin photointermediates reveals both static structural and dynamic functional water-protein interactions present during the activation process. When considered along with observations that solvent occupies similar positions in the structures of other GPCRs, these analyses strongly support an integral role for this dynamic ordered water network in both rhodopsin and GPCR activation. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Investigation of the Impact of SO2 Emissions from the Hong Kong International Airport

NASA Astrophysics Data System (ADS)

Gray, J. P.; Lau, A. K.; Yuan, Z.

2009-12-01

A previous study of the emissions from Hong Kong’s International Airport (HKIA) utilized a semi-quantitative wind direction and speed technique and identified HKIA as a significant source of SO2 in the region. This study however was based on a single data point and the conclusions reached appeared to be inconsistent with accepted thinking regarding aircraft and airport emissions, prompting an in-depth look at airport emissions and their impact on neighbouring region. Varied modelling techniques, making use of a more complete dataset, were employed to ensure a more comprehensive and defensible result. A similar analysis technique and the same monitoring station used in the previous study (Tung Chung) were combined with three additional stations to provided coverage to reach more certain conclusions. While results at Tung Chung were similar to those in the previous study, information from the other three sensors pointed to a source further to the north in the direction of the Black Point Coal Power Station and other power plants further to the north in Mainland China. This conclusion was confirmed by use of the CALMET / CALPUFF model to reproduce emission plumes from major sources within the region on problem days. The modelled results clearly showed that, in the cases simulated, pollution events noted at Tung Chung were primarily influenced by emissions originating at Hong Kong’s and Mainland China’s power stations, and the impact from HKIA is small. This study reiterates the importance of proper identification of all major sources in wind receptor type studies.

BTEX exposures in an area impacted by industrial and mobile sources: Source attribution and impact of averaging time.

PubMed

Presto, Albert A; Dallmann, Timothy R; Gu, Peishi; Rao, Unnati

2016-04-01

The impacts of emissions plumes from major industrial sources on black carbon (BC) and BTEX (benzene, toluene, ethyl benzene, xylene isomers) exposures in communities located >10 km from the industrial source areas were identified with a combination of stationary measurements, source identification using positive matrix factorization (PMF), and dispersion modeling. The industrial emissions create multihour plume events of BC and BTEX at the measurement sites. PMF source apportionment, along with wind patterns, indicates that the observed pollutant plumes are the result of transport of industrial emissions under conditions of low boundary layer height. PMF indicates that industrial emissions contribute >50% of outdoor exposures of BC and BTEX species at the receptor sites. Dispersion modeling of BTEX emissions from known industrial sources predicts numerous overnight plumes and overall qualitative agreement with PMF analysis, but predicts industrial impacts at the measurement sites a factor of 10 lower than PMF. Nonetheless, exposures associated with pollutant plumes occur mostly at night, when residents are expected to be home but are perhaps unaware of the elevated exposure. Averaging data samples over long times typical of public health interventions (e.g., weekly or biweekly passive sampling) misapportions the exposure, reducing the impact of industrial plumes at the expense of traffic emissions, because the longer samples cannot resolve subdaily plumes. Suggestions are made for ways for future distributed pollutant mapping or intervention studies to incorporate high time resolution tools to better understand the potential impacts of industrial plumes. Emissions from industrial or other stationary sources can dominate air toxics exposures in communities both near the source and in downwind areas in the form of multihour plume events. Common measurement strategies that use highly aggregated samples, such as weekly or biweekly averages, are insensitive to such plume events and can lead to significant under apportionment of exposures from these sources.

Mechanistic analysis of the function of agonists and allosteric modulators: reconciling two-state and operational models

PubMed Central

Roche, David; Gil, Debora; Giraldo, Jesús

2013-01-01

Two-state and operational models of both agonism and allosterism are compared to identify and characterize common pharmacological parameters. To account for the receptor-dependent basal response, constitutive receptor activity is considered in the operational models. By arranging two-state models as the fraction of active receptors and operational models as the fractional response relative to the maximum effect of the system, a one-by-one correspondence between parameters is found. The comparative analysis allows a better understanding of complex allosteric interactions. In particular, the inclusion of constitutive receptor activity in the operational model of allosterism allows the characterization of modulators able to lower the basal response of the system; that is, allosteric modulators with negative intrinsic efficacy. Theoretical simulations and overall goodness of fit of the models to simulated data suggest that it is feasible to apply the models to experimental data and constitute one step forward in receptor theory formalism. Linked Articles Another recent review on allosteric modulation can be found at: Kenakin, T (2013). New concepts in pharmacological efficacy at 7TM receptors: IUPHAR Review 2. British Journal of Pharmacology 168: 554–575. doi: 10.1111/j.1476-5381.2012.02223.x And in this issue of BJP there is an article on a new allosteric modulator: Newman AS, Batis N, Grafton G, Caputo F, Brady CA, Lambert J, Peters JA, Gordon J, Brain KL, Powell AD and Barnes NM (2013). 5-Chloroindole: a potent allosteric modulator of the 5-HT3 receptor. British Journal of Pharmacology 169: 1228–1238. doi: 10.1111/bph.12213 PMID:23647200

Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering

NASA Astrophysics Data System (ADS)

Elangasinghe, M. A.; Singhal, N.; Dirks, K. N.; Salmond, J. A.; Samarasinghe, S.

2014-09-01

This paper uses artificial neural networks (ANN), combined with k-means clustering, to understand the complex time series of PM10 and PM2.5 concentrations at a coastal location of New Zealand based on data from a single site. Out of available meteorological parameters from the network (wind speed, wind direction, solar radiation, temperature, relative humidity), key factors governing the pattern of the time series concentrations were identified through input sensitivity analysis performed on the trained neural network model. The transport pathways of particulate matter under these key meteorological parameters were further analysed through bivariate concentration polar plots and k-means clustering techniques. The analysis shows that the external sources such as marine aerosols and local sources such as traffic and biomass burning contribute equally to the particulate matter concentrations at the study site. These results are in agreement with the results of receptor modelling by the Auckland Council based on Positive Matrix Factorization (PMF). Our findings also show that contrasting concentration-wind speed relationships exist between marine aerosols and local traffic sources resulting in very noisy and seemingly large random PM10 concentrations. The inclusion of cluster rankings as an input parameter to the ANN model showed a statistically significant (p < 0.005) improvement in the performance of the ANN time series model and also showed better performance in picking up high concentrations. For the presented case study, the correlation coefficient between observed and predicted concentrations improved from 0.77 to 0.79 for PM2.5 and from 0.63 to 0.69 for PM10 and reduced the root mean squared error (RMSE) from 5.00 to 4.74 for PM2.5 and from 6.77 to 6.34 for PM10. The techniques presented here enable the user to obtain an understanding of potential sources and their transport characteristics prior to the implementation of costly chemical analysis techniques or advanced air dispersion models.

Receptor modelling of fine particles in southern England using CMB including comparison with AMS-PMF factors

NASA Astrophysics Data System (ADS)

Yin, J.; Cumberland, S. A.; Harrison, R. M.; Allan, J.; Young, D. E.; Williams, P. I.; Coe, H.

2015-02-01

PM2.5 was collected during a winter campaign at two southern England sites, urban background North Kensington (NK) and rural Harwell (HAR), in January-February 2012. Multiple organic and inorganic source tracers were analysed and used in a Chemical Mass Balance (CMB) model, which apportioned seven separate primary sources, that explained on average 53% (NK) and 56% (HAR) of the organic carbon (OC), including traffic, woodsmoke, food cooking, coal combustion, vegetative detritus, natural gas and dust/soil. With the addition of source tracers for secondary biogenic aerosol at the NK site, 79% of organic carbon was accounted for. Secondary biogenic sources were represented by oxidation products of α-pinene and isoprene, but only the former made a substantial contribution to OC. Particle source contribution estimates for PM2.5 mass were obtained by the conversion of the OC estimates and combining with inorganic components ammonium nitrate, ammonium sulfate and sea salt. Good mass closure was achieved with 81% (92% with the addition of the secondary biogenic source) and 83% of the PM2.5 mass explained at NK and HAR respectively, with the remainder being secondary organic matter. While the most important sources of OC are vehicle exhaust (21 and 16%) and woodsmoke (15 and 28%) at NK and HAR respectively, food cooking emissions are also significant, particularly at the urban NK site (11% of OC), in addition to the secondary biogenic source, only measured at NK, which represented about 26%. In comparison, the major source components for PM2.5 at NK and HAR are inorganic ammonium salts (51 and 56%), vehicle exhaust emissions (8 and 6%), secondary biogenic (10% measured at NK only), woodsmoke (4 and 7%) and sea salt (7 and 8%), whereas food cooking (4 and 1%) showed relatively smaller contributions to PM2.5. Results from the CMB model were compared with source contribution estimates derived from the AMS-PMF method. The overall mass of organic matter accounted for is rather similar for the two methods. However, appreciably different concentrations were calculated for the individual primary organic matter contributions, although for most source categories the CMB and AMS-PMF results were highly correlated (r2 = 0.69-0.91). In comparison with the CMB model, the AMS appears to overestimate the biomass burning/coal and food cooking sources by a factor of around 1.5 to 2 while estimates of the traffic source are rather similar for each model. The largest divergence is in the primary/secondary organic matter split, with the AMS estimating an appreciably smaller secondary component. Possible reasons for these discrepancies are discussed, but despite these substantial divergences, the strong correlation of the two methods gives some confidence in their application.

Receptor modelling of fine particles in Southern England using CMB including comparison with AMS-PMF factors

NASA Astrophysics Data System (ADS)

Yin, J.; Cumberland, S. A.; Harrison, R. M.; Allan, J.; Young, D. E.; Williams, P. I.; Coe, H.

2014-09-01

PM2.5 was collected during a winter campaign at two southern England sites, urban background North Kensington (NK) and rural Harwell (HAR), in January-February 2012. Multiple organic and inorganic source tracers were analysed and used in a Chemical Mass Balance (CMB) model, which apportioned seven separate primary sources, that explained on average 53% (NK) and 56% (HAR) of the organic carbon (OC), including traffic, woodsmoke, food cooking, coal combustion, vegetative detritus, natural gas and dust/soil. With the addition of source tracers for secondary biogenic aerosol at the NK site, 79% of organic carbon was accounted for. Secondary biogenic sources were represented by oxidation products of α-pinene and isoprene, but only the former made a substantial contribution to OC. Particle source contribution estimates for PM2.5 mass were obtained by the conversion of the OC estimates and combining with inorganic components ammonium nitrate, ammonium sulphate and sea salt. Good mass closure was achieved with 8% (92% with the addition of the secondary biogenic source) and 83% of the PM2.5 mass explained at NK and HAR respectively, with the remainder being secondary organic matter. While the most important sources of OC are vehicle exhaust (21 and 16%) and woodsmoke (15% and 28%) at NK and HAR respectively, food cooking emissions are also significant, particularly at the urban NK site (11% of OC), in addition to the secondary biogenic source, only measured at NK, which represented about 26%. In comparison, the major source components for PM2.5 at NK and HAR are inorganic ammonium salts (51 and 56%), vehicle exhaust emissions (8 and 6%), secondary biogenic (10% measured at NK only), woodsmoke (4 and 7%) and sea salt (7 and 8%), whereas food cooking (4% and 1%) showed relatively smaller contributions to PM2.5. Results from the CMB model were compared with source contribution estimates derived from the AMS-PMF method. The overall mass of organic matter accounted for is rather similar for the two methods. However, appreciably different concentrations were calculated for the individual primary organic matter contributions, although for most source categories the CMB and AMS-PMF results were highly correlated (r2 = 0.69-0.91). In comparison with the CMB model, the AMS appears to over-estimate the biomass burning/coal and food cooking sources by a factor of around 1.5 to 2 while estimates of the traffic source are rather similar for each model. The largest divergence is in the primary/secondary organic matter split, with the AMS estimating an appreciably smaller secondary component. Possible reasons for these discrepancies are discussed, but despite these substantial divergences, the strong correlation of the two methods gives some confidence in their application.

In vitro bioanalysis of drinking water from source to tap.

PubMed

Rosenmai, Anna Kjerstine; Lundqvist, Johan; le Godec, Théo; Ohlsson, Åsa; Tröger, Rikard; Hellman, Björn; Oskarsson, Agneta

2018-08-01

The presence of chemical pollutants in sources of drinking water is a key environmental problem threatening public health. Efficient removal of pollutants in drinking water treatment plants (DWTPs) is needed as well as methods for assessment of the total impact of all present chemicals on water quality. In the present study we have analyzed the bioactivity of water samples from source to tap, including effects of various water treatments in a DWTP, using a battery of cell-based bioassays, covering health-relevant endpoints. Reporter gene assays were used to analyze receptor activity of the aryl hydrocarbon receptor (AhR), estrogen receptor (ER), androgen receptor (AR), peroxisome proliferator-activated receptor alpha (PPARα) and induction of oxidative stress by the nuclear factor erythroid 2-related factor 2 (Nrf2). DNA damage was determined by Comet assay. Grab water samples were concentrated by HLB or ENV solid phase extraction and the water samples assayed at a relative enrichment factor of 50. The enrichment procedure did not induce any bioactivity. No bioactivity was detected in Milli-Q water or drinking water control samples. Induction of AhR, ER and Nrf2 activities was revealed in source to tap water samples. No cytotoxicity, PPARα or AR antagonist activity, or DNA damage were observed in any of the water samples. A low AR agonist activity was detected in a few samples of surface water, but not in the samples from the DWTP. The treatment steps at the DWTP, coagulation, granulated activated carbon filtration, UV disinfection and NH 2 Cl dosing had little or no effect on the AhR, Nrf2 and ER bioactivity. However, nanofiltration and passage through the distribution network drastically decreased AhR activity, while the effect on Nrf2 activity was more modest and no apparent effect was observed on ER activity. The present results suggest that bioassays are useful tools for evaluation of the efficiency of different treatment steps in DWTPs in reducing toxic activities. Bioassays of AhR and Nrf2 are useful for screening of effects of a broad range of chemicals in drinking water and ER activity can be monitored with a high sensitivity. Copyright © 2018 Elsevier Ltd. All rights reserved.

(−) Arctigenin and (+) Pinoresinol Are Antagonists of the Human Thyroid Hormone Receptor β

PubMed Central

2015-01-01

Lignans are important biologically active dietary polyphenolic compounds. Consumption of foods that are rich in lignans is associated with positive health effects. Using modeling tools to probe the ligand-binding pockets of molecular receptors, we found that lignans have high docking affinity for the human thyroid hormone receptor β. Follow-up experimental results show that lignans (−) arctigenin and (+) pinoresinol are antagonists of the human thyroid hormone receptor β. The modeled complexes show key plausible interactions between the two ligands and important amino acid residues of the receptor. PMID:25383984

Chemokine and lymph node homing receptor expression on pDC vary by graft source.

PubMed

Hosoba, Sakura; Harris, Wayne Ac; Lin, Kaifeng L; Waller, Edmund K

2014-11-01

A randomized clinical trial of BM vs. blood stem cell transplants from unrelated donors showed that more plasmacytoid dendritic cells (pDCs) in BM grafts was associated with better post-transplant survival. Here, we describe differences in homing-receptor expression on pDC to explain observed differences following BM vs. blood stem cell transplantation.

Prediction of G-protein-coupled receptor classes in low homology using Chou's pseudo amino acid composition with approximate entropy and hydrophobicity patterns.

PubMed

Gu, Q; Ding, Y S; Zhang, T L

2010-05-01

We use approximate entropy and hydrophobicity patterns to predict G-protein-coupled receptors. Adaboost classifier is adopted as the prediction engine. A low homology dataset is used to validate the proposed method. Compared with the results reported, the successful rate is encouraging. The source code is written by Matlab.

Brian K. Kobilka and G-protein-coupled Receptors (GPCR)

Science.gov Websites

the laboratory's Advanced Photon Source (APS) to make the first discovery of the structure of a human the structure of β2AR at the exact moment that the protein-receptor complex signals across the carrying out its biological mission. ... In order to obtain the structure of a GPCR, Kobilka and his

Hippocampal LTP and contextual learning require surface diffusion of AMPA receptors.

PubMed

Penn, A C; Zhang, C L; Georges, F; Royer, L; Breillat, C; Hosy, E; Petersen, J D; Humeau, Y; Choquet, D

2017-09-21

Long-term potentiation (LTP) of excitatory synaptic transmission has long been considered a cellular correlate for learning and memory. Early LTP (less than 1 h) had initially been explained either by presynaptic increases in glutamate release or by direct modification of postsynaptic AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) receptor function. Compelling models have more recently proposed that synaptic potentiation can occur by the recruitment of additional postsynaptic AMPA receptors (AMPARs), sourced either from an intracellular reserve pool by exocytosis or from nearby extra-synaptic receptors pre-existing on the neuronal surface. However, the exact mechanism through which synapses can rapidly recruit new AMPARs during early LTP remains unknown. In particular, direct evidence for a pivotal role of AMPAR surface diffusion as a trafficking mechanism in synaptic plasticity is still lacking. Here, using AMPAR immobilization approaches, we show that interfering with AMPAR surface diffusion markedly impairs synaptic potentiation of Schaffer collaterals and commissural inputs to the CA1 area of the mouse hippocampus in cultured slices, acute slices and in vivo. Our data also identify distinct contributions of various AMPAR trafficking routes to the temporal profile of synaptic potentiation. In addition, AMPAR immobilization in vivo in the dorsal hippocampus inhibited fear conditioning, indicating that AMPAR diffusion is important for the early phase of contextual learning. Therefore, our results provide a direct demonstration that the recruitment of new receptors to synapses by surface diffusion is a critical mechanism for the expression of LTP and hippocampal learning. Since AMPAR surface diffusion is dictated by weak Brownian forces that are readily perturbed by protein-protein interactions, we anticipate that this fundamental trafficking mechanism will be a key target for modulating synaptic potentiation and learning.

Recent advances in the study on capsaicinoids and capsinoids.

PubMed

Luo, Xiu-Ju; Peng, Jun; Li, Yuan-Jian

2011-01-10

Chili peppers are the major source of nature capsaicinoids, which consist of capsaicin, dihydrocapsaicin, nordihydrocapsaicin, homodihydrocapsaicin, and homocapsaicin, etc. Capsaicinoids are found to exert multiple pharmacological and physiological effects including the activities of analgesia, anticancer, anti-inflammation, antioxidant and anti-obesity. Therefore, capsaicinoids may have the potential value in clinic for pain relief, cancer prevention and weight loss. In addition, capsaicinoids also display the benefits on cardiovascular and gastrointestinal system. It has been shown that capsaicinoids are potential agonists of capsaicin receptor or transient receptor potential vanilloid subfamily member 1 (TRPV1). They could exert the effects not only through the receptor-dependent pathway but also through the receptor-independent one. CH-19 Sweet peppers are the source of nature capsinoids, which share similar structure with capsaicinoids and consist of capsiate, dihydrocapsiate, and nordihydrocapsiate, etc, Comparing with capsaicinoids, capsinoids are less pungent and easily broken down in the normal aqueous conditions. So far, it has been found that capsinoids possess the biological properties of antitumor, antioxidant and anti-obesity. Since capsinoids are less toxic than capsaicinoids, therefore, capsinoids may have the advantages over capsaicinoids in clinical applications such as cancer prevention and weight loss. Copyright © 2010 Elsevier B.V. All rights reserved.

The CCK(-like) receptor in the animal kingdom: functions, evolution and structures.

PubMed

Staljanssens, Dorien; Azari, Elnaz Karimian; Christiaens, Olivier; Beaufays, Jérôme; Lins, Laurence; Van Camp, John; Smagghe, Guy

2011-03-01

In this review, the cholecystokinin (CCK)(-like) receptors throughout the animal kingdom are compared on the level of physiological functions, evolutionary basis and molecular structure. In vertebrates, the CCK receptor is an important member of the G-protein coupled receptors as it is involved in the regulation of many physiological functions like satiety, gastrointestinal motility, gastric acid secretion, gall bladder contraction, pancreatic secretion, panic, anxiety and memory and learning processes. A homolog for this receptor is also found in nematodes and arthropods, called CK receptor and sulfakinin (SK) receptor, respectively. These receptors seem to have evolved from a common ancestor which is probably still closely related to the nematode CK receptor. The SK receptor is more closely related to the CCK receptor and seems to have similar functions. A molecular 3D-model for the CCK receptor type 1 has been built together with the docking of the natural ligands for the CCK and SK receptors in the CCK receptor type 1. These molecular models can help to study ligand-receptor interactions, that can in turn be useful in the development of new CCK(-like) receptor agonists and antagonists with beneficial health effects in humans or potential for pest control. Copyright © 2010 Elsevier Inc. All rights reserved.

Sensitivity analysis of the near-road dispersion model RLINE - An evaluation at Detroit, Michigan

NASA Astrophysics Data System (ADS)

Milando, Chad W.; Batterman, Stuart A.

2018-05-01

The development of accurate and appropriate exposure metrics for health effect studies of traffic-related air pollutants (TRAPs) remains challenging and important given that traffic has become the dominant urban exposure source and that exposure estimates can affect estimates of associated health risk. Exposure estimates obtained using dispersion models can overcome many of the limitations of monitoring data, and such estimates have been used in several recent health studies. This study examines the sensitivity of exposure estimates produced by dispersion models to meteorological, emission and traffic allocation inputs, focusing on applications to health studies examining near-road exposures to TRAP. Daily average concentrations of CO and NOx predicted using the Research Line source model (RLINE) and a spatially and temporally resolved mobile source emissions inventory are compared to ambient measurements at near-road monitoring sites in Detroit, MI, and are used to assess the potential for exposure measurement error in cohort and population-based studies. Sensitivity of exposure estimates is assessed by comparing nominal and alternative model inputs using statistical performance evaluation metrics and three sets of receptors. The analysis shows considerable sensitivity to meteorological inputs; generally the best performance was obtained using data specific to each monitoring site. An updated emission factor database provided some improvement, particularly at near-road sites, while the use of site-specific diurnal traffic allocations did not improve performance compared to simpler default profiles. Overall, this study highlights the need for appropriate inputs, especially meteorological inputs, to dispersion models aimed at estimating near-road concentrations of TRAPs. It also highlights the potential for systematic biases that might affect analyses that use concentration predictions as exposure measures in health studies.

Fluctuation correlation models for receptor immobilization

NASA Astrophysics Data System (ADS)

Fourcade, B.

2017-12-01

Nanoscale dynamics with cycles of receptor diffusion and immobilization by cell-external-or-internal factors is a key process in living cell adhesion phenomena at the origin of a plethora of signal transduction pathways. Motivated by modern correlation microscopy approaches, the receptor correlation functions in physical models based on diffusion-influenced reaction is studied. Using analytical and stochastic modeling, this paper focuses on the hybrid regime where diffusion and reaction are not truly separable. The time receptor autocorrelation functions are shown to be indexed by different time scales and their asymptotic expansions are given. Stochastic simulations show that this analysis can be extended to situations with a small number of molecules. It is also demonstrated that this analysis applies when receptor immobilization is coupled to environmental noise.

Modeling the Origin of Anthropogenic Black Carbon and Its Climatic Effect Over the Tibetan Plateau and Surrounding Regions

NASA Astrophysics Data System (ADS)

Yang, Junhua; Kang, Shichang; Ji, Zhenming; Chen, Deliang

2018-01-01

Black carbon (BC) in snow/ice induces enhanced snow and glacier melting. As over 60% of atmospheric BC is emitted from anthropogenic sources, which directly impacts the distribution and concentration of BC in snow/ice, it is essential to assess the origin of anthropogenic BC transported to the Tibetan Plateau (TP) where there are few direct emissions attributable to local human activities. In this study, we used a regional climate-atmospheric chemistry model and a set of BC scenarios for quantitative evaluation of the impact of anthropogenic BC from various sources and its climate effects over the TP in 2013. The results showed that the model performed well in terms of climatology, aerosol optical properties, and near-surface concentrations, which indicates that this modeling framework is appropriate to characterize anthropogenic BC source-receptor relationships over the TP. The simulated surface concentration associated with the anthropogenic sources showed seasonal differences. In the monsoon season, the contribution of anthropogenic BC was less than in the nonmonsoon season. In the nonmonsoon season, westerly winds prevailed and transported BC from central Asia and north India to the western TP. In the monsoon season, BC aerosol was transported to the middle-upper troposphere over the Indo-Gangetic Plain and crossed the Himalayas via southwesterly winds. The majority of anthropogenic BC over the TP was transported from South Asia, which contributed to 40%-80% (mean of 61.3%) of surface BC in the nonmonsoon season, and 10%-50% (mean of 19.4%) in the monsoon season. For the northeastern TP, anthropogenic BC from eastern China accounted for less than 10% of the total in the nonmonsoon season but can be up to 50% in the monsoon season. Averaged over the TP, the eastern China anthropogenic sources accounted for 6.2% and 8.4% of surface BC in the nonmonsoon and monsoon seasons, respectively. The anthropogenic BC induced negative radiative forcing and cooling effects at the near surface over the TP.

NESHAP Dose-Release Factor Isopleths for Five Source-to-Receptor Distances from the Center of Site and H-Area for all Compass Sectors at SRS using CAP88-PC Version 4.0

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

Trimor, P.

The Environmental Protection Agency (EPA) requires the use of the computer model CAP88-PC to estimate the total effective doses (TED) for demonstrating compliance with 40 CFR 61, Subpart H (EPA 2006), the National Emission Standards for Hazardous Air Pollutants (NESHAP) regulations. As such, CAP88 Version 4.0 was used to calculate the receptor dose due to routine atmospheric releases at the Savannah River Site (SRS). For estimation, NESHAP dose-release factors (DRFs) have been supplied to Environmental Compliance and Area Closure Projects (EC&ACP) for many years. DRFs represent the dose to a maximum receptor exposed to 1 Ci of a specified radionuclidemore » being released into the atmosphere. They are periodically updated to include changes in the CAP88 version, input parameter values, site meteorology, and location of the maximally exposed individual (MEI). This report presents the DRFs of tritium oxide released at two onsite locations, center-of-site (COS) and H-Area, at 0 ft. elevation to maximally exposed individuals (MEIs) located 1000, 3000, 6000, 9000, and 12000 meters from the release areas for 16 compass sectors. The analysis makes use of area-specific meteorological data (Viner 2014).« less

Shifting physician prescribing to a preferred histamine-2-receptor antagonist. Effects of a multifactorial intervention in a mixed-model health maintenance organization.

PubMed

Brufsky, J W; Ross-Degnan, D; Calabrese, D; Gao, X; Soumerai, S B

1998-03-01

This study was undertaken to determine whether a program of education, therapeutic reevaluation of eligible patients, and performance feedback could shift prescribing to cimetidine from other histamine-2 receptor antagonists, which commonly are used in the management of ulcers and reflux, and reduce costs without increasing rates of ulcer-related hospital admissions. This study used an interrupted monthly time series with comparison series in a large mixed-model health maintenance organization. Physicians employed in health centers (staff model) and physicians in independent medical groups contracting to provide health maintenance organization services (group model) participated. The comparative percentage prescribed of specific histamine-2 receptor antagonists (market share), total histamine-2 receptor antagonist prescribing, cost per histamine-2 receptor antagonist prescription, and the rate of hospitalization for gastrointestinal illness were assessed. In the staff model, therapeutic reevaluation resulted in a sudden increase in market share of the preferred histamine-2 receptor antagonist cimetidine (+53.8%) and a sudden decrease in ranitidine (-44.7%) and famotidine (-4.8%); subsequently, cimetidine market share grew by 1.1% per month. In the group model, therapeutic reevaluation resulted in increased cimetidine market share (+9.7%) and decreased prescribing of other histamine-2 receptor antagonists (ranitidine -11.6%; famotidine -1.2%). Performance feedback did not result in further changes in prescribing in either setting. Use of omeprazole, an expensive alternative, essentially was unchanged by the interventions, as were overall histamine-2 receptor antagonist prescribing and hospital admissions for gastrointestinal illnesses. This intervention, which cost approximately $60,000 to implement, resulted in estimated annual savings in histamine-2 receptor antagonist expenditures of $1.06 million. Annual savings in histamine-2 receptor antagonist expenditures after this multifaceted intervention were more than implementation costs, with no discernible effects on numbers of hospitalizations. The magnitude of effect and cost savings were much greater in the staff model; organizational factors and economic incentives may have contributed to these differences. More research is needed to determine the generalizability of this approach to other technologies and managed care settings.

Stimulation of postsynapse adrenergic α2A receptor improves attention/cognition performance in an animal model of attention deficit hyperactivity disorder.

PubMed

Kawaura, Kazuaki; Karasawa, Jun-ichi; Chaki, Shigeyuki; Hikichi, Hirohiko

2014-08-15

A 5-trial inhibitory avoidance test using spontaneously hypertensive rat (SHR) pups has been used as an animal model of attention deficit hyperactivity disorder (ADHD). However, the roles of noradrenergic systems, which are involved in the pathophysiology of ADHD, have not been investigated in this model. In the present study, the effects of adrenergic α2 receptor stimulation, which has been an effective treatment for ADHD, on attention/cognition performance were investigated in this model. Moreover, neuronal mechanisms mediated through adrenergic α2 receptors were investigated. We evaluated the effects of both clonidine, a non-selective adrenergic α2 receptor agonist, and guanfacine, a selective adrenergic α2A receptor agonist, using a 5-trial inhibitory avoidance test with SHR pups. Juvenile SHR exhibited a shorter transfer latency, compared with juvenile Wistar Kyoto (WKY) rats. Both clonidine and guanfacine significantly prolonged the transfer latency of juvenile SHR. The effects of clonidine and guanfacine were significantly blocked by pretreatment with an adrenergic α2A receptor antagonist. In contrast, the effect of clonidine was not attenuated by pretreatment with an adrenergic α2B receptor antagonist, or an adrenergic α2C receptor antagonist, while it was attenuated by a non-selective adrenergic α2 receptor antagonist. Furthermore, the effects of neither clonidine nor guanfacine were blocked by pretreatment with a selective noradrenergic neurotoxin. These results suggest that the stimulation of the adrenergic α2A receptor improves the attention/cognition performance of juvenile SHR in the 5-trial inhibitory avoidance test and that postsynaptic, rather than presynaptic, adrenergic α2A receptor is involved in this effect. Copyright © 2014 Elsevier B.V. All rights reserved.

Are the Pyrenees a barrier for the transport of birch (Betula) pollen from Central Europe to the Iberian Peninsula?

PubMed

Izquierdo, Rebeca; Alarcón, Marta; Mazón, Jordi; Pino, David; De Linares, Concepción; Aguinagalde, Xabier; Belmonte, Jordina

2017-01-01

This work provides a first assessment of the possible barrier effect of the Pyrenees on the atmospheric transport of airborne pollen from Europe to the North of the Iberian Peninsula. Aerobiological data recorded in three Spanish stations located at the eastern, central and western base of the Pyrenees in the period 2004-2014 have been used to identify the possible long range transport episodes of Betula pollen. The atmospheric transport routes and the origin regions have been established by means of trajectory analysis and a source receptor model. Betula pollen outbreaks were associated with the meteorological scenario characterized by the presence of a high-pressure system overm over Morocco and Southern Iberian Peninsula. France and Central Europe have been identified as the probable source areas of Betula pollen that arrives to Northern Spain. However, the specific source areas are mainly determined by the particular prevailing atmospheric circulation of each location. Finally, the Weather Research and Forecasting model highlighted the effect of the orography on the atmospheric transport patterns, showing paths through the western and easternmost lowlands for Vitoria-Gasteiz and Bellaterra respectively, and the direct impact of air flows over Vielha through the Garona valley. Copyright © 2016 Elsevier B.V. All rights reserved.

Acetone in the atmosphere of Hong Kong: Abundance, sources and photochemical precursors

NASA Astrophysics Data System (ADS)

Guo, H.; Ling, Z. H.; Cheung, K.; Wang, D. W.; Simpson, I. J.; Blake, D. R.

2013-02-01

Intensive field measurements were carried out at a mountain site and an urban site at the foot of the mountain from September to November 2010 in Hong Kong. Acetone was monitored using both canister air samples and 2,4-dinitrophenylhydrazine cartridges. The spatiotemporal patterns of acetone showed no difference between the two sites (p > 0.05), and the mean acetone mixing ratios on O3 episode days were higher than those on non-O3 episode days at both sites (p < 0.05). The source contributions to ambient acetone at both sites were estimated using a receptor model i.e. Positive Matrix Factorization (PMF). The PMF results showed that vehicular emission and secondary formation made the most important contribution to ambient acetone, followed by the solvent use at both sites. However, the contribution of biogenic emission at the mountain site was significantly higher than that at the urban site, whereas biomass burning made more remarkable contribution at the urban site than that at the mountain site. The mechanism of oxidation formation of acetone was investigated using a photochemical box model. The results indicated that i-butene was the main precursor of secondary acetone at the mountain site, while the oxidation of i-butane was the major source of secondary acetone at the urban site.

Receptors as a master key for synchronization of rhythms

NASA Astrophysics Data System (ADS)

Nagano, Seido

2004-03-01

A simple, but general scheme to achieve synchronization of rhythms was derived. The scheme has been inductively generalized from the modelling study of cellular slime mold. It was clarified that biological receptors work as apparatuses that can convert external stimulus to the form of nonlinear interaction within individual oscillators. Namely, the mathematical model receptor works as a nonlinear coupling apparatus between nonlinear oscillators. Thus, synchronization is achieved as a result of competition between two kinds of non-linearities, and to achieve synchronization, even a small external stimulation via model receptors can change the characteristics of individual oscillators significantly. The derived scheme is very simple mathematically, but it is a very powerful scheme as numerically demonstrated. The biological receptor scheme should significantly help understanding of synchronization phenomena in biology since groups of limit cycle oscillators and receptors are ubiquitous in biological systems. Reference: S. Nagano, Phys Rev. E67, 056215(2003)

Revisiting chemoaffinity theory: Chemotactic implementation of topographic axonal projection

PubMed Central

2017-01-01

Neural circuits are wired by chemotactic migration of growth cones guided by extracellular guidance cue gradients. How growth cone chemotaxis builds the macroscopic structure of the neural circuit is a fundamental question in neuroscience. I addressed this issue in the case of the ordered axonal projections called topographic maps in the retinotectal system. In the retina and tectum, the erythropoietin-producing hepatocellular (Eph) receptors and their ligands, the ephrins, are expressed in gradients. According to Sperry’s chemoaffinity theory, gradients in both the source and target areas enable projecting axons to recognize their proper terminals, but how axons chemotactically decode their destinations is largely unknown. To identify the chemotactic mechanism of topographic mapping, I developed a mathematical model of intracellular signaling in the growth cone that focuses on the growth cone’s unique chemotactic property of being attracted or repelled by the same guidance cues in different biological situations. The model presented mechanism by which the retinal growth cone reaches the correct terminal zone in the tectum through alternating chemotactic response between attraction and repulsion around a preferred concentration. The model also provided a unified understanding of the contrasting relationships between receptor expression levels and preferred ligand concentrations in EphA/ephrinA- and EphB/ephrinB-encoded topographic mappings. Thus, this study redefines the chemoaffinity theory in chemotactic terms. PMID:28792499

Impact of Psychological Stress on Pain Perception in an Animal Model of Endometriosis.

PubMed

Hernandez, Siomara; Cruz, Myrella L; Seguinot, Inevy I; Torres-Reveron, Annelyn; Appleyard, Caroline B

2017-10-01

Pain in patients with endometriosis is considered a significant source of stress but does not always correlate with severity of the condition. We have demonstrated that stress can worsen endometriosis in an animal model. Here, we tested the impact of a psychological stress protocol on pain thresholds and pain receptors. Endometriosis was induced in female rats by suturing uterine horn tissue next to the intestinal mesentery. Sham rats had sutures only. Rats were exposed to water avoidance stress for 7 consecutive days or handled for 5 minutes (no stress). Fecal pellets and serum corticosterone (CORT) levels were measured as an index of anxiety. Pain perception was assessed using hot plate and Von Frey tests. Substance P, enkephalin, endomorphin-2, Mu opioid receptor (MOR), and neurokinin-1 receptor expression in the spinal cord were measured by immunohistochemistry. Fecal pellets and CORT were significantly higher in the endo-stress (ES) group than endo-no stress (ENS; P < .01) and sham-no stress groups (SNS; P < .01). The ES rats had more colonic damage ( P < .001 vs SNS; P < .05 vs ENS), vesicle mast cell infiltration ( P < .01 vs ENS), and more severe vesicles than ENS. The ES developed significant hyperalgesia ( P < .05) but stress reversed the allodynic effect caused by endo ( P < .001). The MOR expression was significantly reduced in ENS versus SNS ( P < .05) and more enkephalin expression was found in endo groups. Animals subjected to stress develop more severe symptoms but interestingly stress seems to have beneficial effects on abdominal allodynia, which could be a consequence of the stress-induced analgesia phenomenon.

Computer modeling of the neurotoxin binding site of acetylcholine receptor spanning residues 185 through 196

NASA Technical Reports Server (NTRS)

Garduno-Juarez, R.; Shibata, M.; Zielinski, T. J.; Rein, R.

1987-01-01

A model of the complex between the acetylcholine receptor and the snake neurotoxin, cobratoxin, was built by molecular model building and energy optimization techniques. The experimentally identified functionally important residues of cobratoxin and the dodecapeptide corresponding to the residues 185-196 of acetylcholine receptor alpha subunit were used to build the model. Both cis and trans conformers of cyclic L-cystine portion of the dodecapeptide were examined. Binding residues independently identified on cobratoxin are shown to interact with the dodecapeptide AChR model.

The impact of infrared radiation in flight control in the Australian "firebeetle" Merimna atrata.

PubMed

Hinz, Marcel; Klein, Adrian; Schmitz, Anke; Schmitz, Helmut

2018-01-01

Infrared (IR) receptors are rare in insects and have only been found in the small group of so-called pyrophilous insects, which approach forest fires. In previous work the morphology of the IR receptors and the physiology of the inherent sensory cells have been investigated. It was shown that receptors are located on the thorax and the abdomen respectively and show an astounding diversity with respect to structure and the presumed transduction mechanism. What is completely missing, however, is any behavioral evidence for the function of the IR receptors in pyrophilous insects. Here we describe the responses of the Australian "firebeetle", Merimna atrata to IR radiation. Beetles in a restrained flight were laterally stimulated with IR radiation of an intensity 20% above a previously determined electrophysiological threshold of the IR organs (40 mW/cm2). After exposure, beetles always showed an avoidance response away from the IR source. Reversible ablation experiments showed that the abdominal IR receptors are essential for the observed behavior. Tests with weaker IR radiation (11.4 mW/cm2) also induced avoidance reactions in some beetles pointing to a lower threshold. In contrast, beetles were never attracted by the IR source. Our results suggest that the IR receptors in Merimna atrata serve as an early warning system preventing an accidental landing on a hot surface. We also tested if another fire specific stimulus, the view of a large smoke plume, influenced the flight. However, due to an unexpected insensitivity of the flying beetles to most visual stimuli results were ambiguous.

The impact of infrared radiation in flight control in the Australian “firebeetle” Merimna atrata

PubMed Central

2018-01-01

Infrared (IR) receptors are rare in insects and have only been found in the small group of so-called pyrophilous insects, which approach forest fires. In previous work the morphology of the IR receptors and the physiology of the inherent sensory cells have been investigated. It was shown that receptors are located on the thorax and the abdomen respectively and show an astounding diversity with respect to structure and the presumed transduction mechanism. What is completely missing, however, is any behavioral evidence for the function of the IR receptors in pyrophilous insects. Here we describe the responses of the Australian “firebeetle”, Merimna atrata to IR radiation. Beetles in a restrained flight were laterally stimulated with IR radiation of an intensity 20% above a previously determined electrophysiological threshold of the IR organs (40 mW/cm2). After exposure, beetles always showed an avoidance response away from the IR source. Reversible ablation experiments showed that the abdominal IR receptors are essential for the observed behavior. Tests with weaker IR radiation (11.4 mW/cm2) also induced avoidance reactions in some beetles pointing to a lower threshold. In contrast, beetles were never attracted by the IR source. Our results suggest that the IR receptors in Merimna atrata serve as an early warning system preventing an accidental landing on a hot surface. We also tested if another fire specific stimulus, the view of a large smoke plume, influenced the flight. However, due to an unexpected insensitivity of the flying beetles to most visual stimuli results were ambiguous. PMID:29432476

Ionotropic and metabotropic mechanisms in chemoreception: 'chance or design'?

PubMed

Silbering, Ana Florencia; Benton, Richard

2010-03-01

Chemosensory receptors convert an enormous diversity of chemical signals from the external world into a common language of electrical activity in the brain. Mammals and insects use several families of transmembrane receptor proteins to recognize distinct classes of volatile and non-volatile chemicals that are produced by conspecifics or other environmental sources. A comparison of the signalling mechanisms of mammalian and insect receptors has revealed an unexpected functional distinction: mammals rely almost exclusively on metabotropic ligand-binding receptors, which use second messenger signalling cascades to indirectly activate ion channels, whereas insects use ionotropic receptors, which are gated directly by chemical stimuli, thereby leading to neuronal depolarization. In this review, we consider possible reasons for this dichotomy, taking into account biophysical, cell biological, ecological and evolutionary influences on how information is extracted from chemosensory cues by these animal classes.

Ionotropic and metabotropic mechanisms in chemoreception: ‘chance or design'?

PubMed Central

Silbering, Ana Florencia; Benton, Richard

2010-01-01

Chemosensory receptors convert an enormous diversity of chemical signals from the external world into a common language of electrical activity in the brain. Mammals and insects use several families of transmembrane receptor proteins to recognize distinct classes of volatile and non-volatile chemicals that are produced by conspecifics or other environmental sources. A comparison of the signalling mechanisms of mammalian and insect receptors has revealed an unexpected functional distinction: mammals rely almost exclusively on metabotropic ligand-binding receptors, which use second messenger signalling cascades to indirectly activate ion channels, whereas insects use ionotropic receptors, which are gated directly by chemical stimuli, thereby leading to neuronal depolarization. In this review, we consider possible reasons for this dichotomy, taking into account biophysical, cell biological, ecological and evolutionary influences on how information is extracted from chemosensory cues by these animal classes. PMID:20111052

Fob1 and Fob2 Proteins Are Virulence Determinants of Rhizopus oryzae via Facilitating Iron Uptake from Ferrioxamine

PubMed Central

Liu, Mingfu; Lin, Lin; Gebremariam, Teclegiorgis; Luo, Guanpingsheng; Skory, Christopher D.; French, Samuel W.; Chou, Tsui-Fen; Edwards, John E.; Ibrahim, Ashraf S.

2015-01-01

Dialysis patients with chronic renal failure receiving deferoxamine for treating iron overload are uniquely predisposed for mucormycosis, which is most often caused by Rhizopus oryzae. Although the deferoxamine siderophore is not secreted by Mucorales, previous studies established that Rhizopus species utilize iron from ferrioxamine (iron-rich form of deferoxamine). Here we determined that the CBS domain proteins of Fob1 and Fob2 act as receptors on the cell surface of R. oryzae during iron uptake from ferrioxamine. Fob1 and Fob2 cell surface expression was induced in the presence of ferrioxamine and bound radiolabeled ferrioxamine. A R. oryzae strain with targeted reduced Fob1/Fob2 expression was impaired for iron uptake, germinating, and growing on medium with ferrioxamine as the sole source of iron. This strain also exhibited reduced virulence in a deferoxamine-treated, but not the diabetic ketoacidotic (DKA), mouse model of mucormycosis. The mechanism by which R. oryzae obtains iron from ferrioxamine involves the reductase/permease uptake system since the growth on ferrioxamine supplemented medium is associated with elevated reductase activity and the use of the ferrous chelator bathophenanthroline disulfonate abrogates iron uptake and growth on medium supplemented with ferrioxamine as a sole source of iron. Finally, R. oryzae mutants with reduced copies of the high affinity iron permease (FTR1) or with decreased FTR1 expression had an impaired iron uptake from ferrioxamine in vitro and reduced virulence in the deferoxamine-treated mouse model of mucormycosis. These two receptors appear to be conserved in Mucorales, and can be the subject of future novel therapy to maintain the use of deferoxamine for treating iron-overload. PMID:25974051

Sediment Connectivity and Transport Pathways in Tidal Inlets: a Conceptual Framework with Application to Ameland Inlet

NASA Astrophysics Data System (ADS)

Pearson, S.; van Prooijen, B. C.; Zheng Bing, W.; Bak, J.

2017-12-01

Predicting the response of tidal inlets and adjacent coastlines to sea level rise and anthropogenic interventions (e.g. sand nourishments) requires understanding of sediment transport pathways. These pathways are strongly dependent on hydrodynamic forcing, grain size, underlying morphology, and the timescale considered. To map and describe these pathways, we considered the concept of sediment connectivity, which quantifies the degree to which sediment transport pathways link sources to receptors. In this study we established a framework for understanding sediment transport pathways in coastal environments, using Ameland Inlet in the Dutch Wadden Sea as a basis. We used the Delft3D morphodynamic model to assess the fate of sediment as it moved between specific morphological units defined in the model domain. Simulation data was synthesized in a graphical network and then graph theory used to analyze connectivity at different space and time scales. At decadal time scales, fine and very fine sand (<250μm) have greater connectivity with receptor areas further away from their sources. Conversely, medium sand (>250μm) shows lower connectivity, even in more energetic areas. Greater sediment connectivity was found under the influence of wind and waves when compared to purely tidal forcing. Connectivity shows considerable spatial variation in cross shore and alongshore directions, depending on proximity to the inlet and dominant wave direction. Furthermore, connectivity generally increases at longer timescales. Asymmetries in connectivity (i.e. unidirectional transport) can be used to explain long-term erosional or depositional trends. As such, an understanding of sediment connectivity as a function of grain size could yield useful insights for resolving sediment transport pathways and the fate of a nourishment in coastal environments.

Biokinetics and dosimetry in patients of 99mTc-EDDA/HYNIC-Tyr3-octreotide prepared from lyophilized kits.

PubMed

González-Vázquez, Armando; Ferro-Flores, Guillermina; Arteaga de Murphy, Consuelo; Gutiérrez-García, Zohar

2006-07-01

99mTc-EDDA/HYNIC-Tyr3-octreotide (99mTc-HYNIC-TOC) has shown high in vitro and in vivo stability, rapid background clearance and rapid detection of somatostatin receptor-positive tumors. The aim of this study was to establish a biokinetic model for 99mTc-HYNIC-TOC prepared from lyophilized kits, and to evaluate its dosimetry as a tumor imaging agent in patients with histologically confirmed neuroendocrine tumors. Whole-body images from eight patients were acquired at 5, 60, 90, 180 min and 24 h after 99mTc-HYNIC-TOC administration obtained from instant freeze-dried kit formulations with radiochemical purities >95%. Regions of interest (ROIs) were drawn around source organs on each time frame. The same set of ROIs was used for all eight scans and the count per minute (cpm) of each ROI was converted to activity using the conjugate view counting method. The image sequence was used to extrapolate 99mTc-HYNIC-TOC time-activity curves in each organ, to adjust a biokinetic model using the SAAM software, and to calculate the total number of disintegrations (N) that occurred in the source regions. N data were the input for the OLINDA/EXM code to calculate internal radiation dose estimates. Images showed an average tumor/blood (heart) ratio of 4.3+/-0.7 in receptor-positive tumors at 1 h. The mean radiation absorbed dose calculated for a study using 740 MBq was 24, 21.5, 5.5 and 1.0 mSv for spleen, kidneys, liver and bone marrow respectively and the effective dose was 4.4 mSv.

Application of agonist-receptor modeling to the sweetness synergy between high fructose corn syrup and sucralose, and between high-potency sweeteners.

PubMed

Wolf, P A; Bridges, J R; Wicklund, R

2010-03-01

The agonist-receptor-transducer model of D. Ennis is applied to beverage formulations sweetened with high fructose corn syrup, sucralose, and other high-potency sweeteners, confirming the utility of the model, and supports the growing volume of evidence for multiple binding sites on the sweetness receptor. The model is further simplified to require less parameters for other sweetener blend systems whenever potency information is available for the single sweeteners.

Comparison of Kinetic Models for Dual-Tracer Receptor Concentration Imaging in Tumors

PubMed Central

Hamzei, Nazanin; Samkoe, Kimberley S; Elliott, Jonathan T; Holt, Robert W; Gunn, Jason R; Hasan, Tayyaba; Pogue, Brian W; Tichauer, Kenneth M

2014-01-01

Molecular differences between cancerous and healthy tissue have become key targets for novel therapeutics specific to tumor receptors. However, cancer cell receptor expression can vary within and amongst different tumors, making strategies that can quantify receptor concentration in vivo critical for the progression of targeted therapies. Recently a dual-tracer imaging approach capable of providing quantitative measures of receptor concentration in vivo was developed. It relies on the simultaneous injection and imaging of receptor-targeted tracer and an untargeted tracer (to account for non-specific uptake of the targeted tracer). Early implementations of this approach have been structured on existing “reference tissue” imaging methods that have not been optimized for or validated in dual-tracer imaging. Using simulations and mouse tumor model experimental data, the salient findings in this study were that all widely used reference tissue kinetic models can be used for dual-tracer imaging, with the linearized simplified reference tissue model offering a good balance of accuracy and computational efficiency. Moreover, an alternate version of the full two-compartment reference tissue model can be employed accurately by assuming that the K1s of the targeted and untargeted tracers are similar to avoid assuming an instantaneous equilibrium between bound and free states (made by all other models). PMID:25414912

Is the Acute NMDA Receptor Hypofunction a Valid Model of Schizophrenia?

PubMed Central

Adell, Albert; Jiménez-Sánchez, Laura; López-Gil, Xavier; Romón, Tamara

2012-01-01

Several genetic, neurodevelopmental, and pharmacological animal models of schizophrenia have been established. This short review examines the validity of one of the most used pharmacological model of the illness, ie, the acute administration of N-methyl-D-aspartate (NMDA) receptor antagonists in rodents. In some cases, data on chronic or prenatal NMDA receptor antagonist exposure have been introduced for comparison. The face validity of acute NMDA receptor blockade is granted inasmuch as hyperlocomotion and stereotypies induced by phencyclidine, ketamine, and MK-801 are regarded as a surrogate for the positive symptoms of schizophrenia. In addition, the loss of parvalbumin-containing cells (which is one of the most compelling finding in postmortem schizophrenia brain) following NMDA receptor blockade adds construct validity to this model. However, the lack of changes in glutamic acid decarboxylase (GAD67) is at variance with human studies. It is possible that changes in GAD67 are more reflective of the neurodevelopmental condition of schizophrenia. Finally, the model also has predictive validity, in that its behavioral and transmitter activation in rodents are responsive to antipsychotic treatment. Overall, although not devoid of drawbacks, the acute administration of NMDA receptor antagonists can be considered as a good model of schizophrenia bearing a satisfactory degree of validity. PMID:21965469

Coupled stochastic spatial and non-spatial simulations of ErbB1 signaling pathways demonstrate the importance of spatial organization in signal transduction.

PubMed

Costa, Michelle N; Radhakrishnan, Krishnan; Wilson, Bridget S; Vlachos, Dionisios G; Edwards, Jeremy S

2009-07-23

The ErbB family of receptors activates intracellular signaling pathways that control cellular proliferation, growth, differentiation and apoptosis. Given these central roles, it is not surprising that overexpression of the ErbB receptors is often associated with carcinogenesis. Therefore, extensive laboratory studies have been devoted to understanding the signaling events associated with ErbB activation. Systems biology has contributed significantly to our current understanding of ErbB signaling networks. However, although computational models have grown in complexity over the years, little work has been done to consider the spatial-temporal dynamics of receptor interactions and to evaluate how spatial organization of membrane receptors influences signaling transduction. Herein, we explore the impact of spatial organization of the epidermal growth factor receptor (ErbB1/EGFR) on the initiation of downstream signaling. We describe the development of an algorithm that couples a spatial stochastic model of membrane receptors with a nonspatial stochastic model of the reactions and interactions in the cytosol. This novel algorithm provides a computationally efficient method to evaluate the effects of spatial heterogeneity on the coupling of receptors to cytosolic signaling partners. Mathematical models of signal transduction rarely consider the contributions of spatial organization due to high computational costs. A hybrid stochastic approach simplifies analyses of the spatio-temporal aspects of cell signaling and, as an example, demonstrates that receptor clustering contributes significantly to the efficiency of signal propagation from ligand-engaged growth factor receptors.

Kinetic modeling of benzodiazepine receptor binding with PET and high specific activity [(11)C]Iomazenil in healthy human subjects.

PubMed

Bremner, J D; Horti, A; Staib, L H; Zea-Ponce, Y; Soufer, R; Charney, D S; Baldwin, R

2000-01-01

Quantitation of the PET benzodiazepine receptor antagonist, [(11)C]Iomazenil, using low specific activity radioligand was recently described. The purpose of this study was to quantitate benzodiazepine receptor binding in human subjects using PET and high specific activity [(11)C]Iomazenil. Six healthy human subjects underwent PET imaging following a bolus injection of high specific activity (>100 Ci/mmol) [(11)C]iomazenil. Arterial samples were collected at multiple time points after injection for measurement of unmetabolized total and nonprotein-bound parent compound in plasma. Time activity curves of radioligand concentration in brain and plasma were analyzed using two and three compartment model. Kinetic rate constants of transfer of radioligand between plasma, nonspecifically bound brain tissue, and specifically bound brain tissue compartments were fitted to the model. Values for fitted kinetic rate constants were used in the calculation of measures of benzodiazepine receptor binding, including binding potential (the ratio of receptor density to affinity), and product of BP and the fraction of free nonprotein-bound parent compound (V(3)'). Use of the three compartment model improved the goodness of fit in comparison to the two compartment model. Values for kinetic rate constants and measures of benzodiazepine receptor binding, including BP and V(3)', were similar to results obtained with the SPECT radioligand [(123)I]iomazenil, and a prior report with low specific activity [(11)C]Iomazenil. Kinetic modeling using the three compartment model with PET and high specific activity [(11)C]Iomazenil provides a reliable measure of benzodiazepine receptor binding. Synapse 35:68-77, 2000. Published 2000 Wiley-Liss, Inc.

Ethylene Regulates Levels of Ethylene Receptor/CTR1 Signaling Complexes in Arabidopsis thaliana

DOE PAGES

Shakeel, Samina N.; Gao, Zhiyong; Amir, Madiha; ...

2015-03-26

The plant hormone ethylene is perceived by a five-member family of receptors in Arabidopsis thaliana. The receptors function in conjunction with the Raf-like kinase CTR1 to negatively regulate ethylene signal transduction. CTR1 interacts with multiple members of the receptor family based on co-purification analysis, interacting more strongly with receptors containing a receiver domain. Levels of membrane-associated CTR1 vary in response to ethylene, doing so in a post-transcriptional manner that correlates with ethylene-mediated changes in levels of the ethylene receptors ERS1, ERS2, EIN4, and ETR2. Interactions between CTR1 and the receptor ETR1 protect ETR1 from ethylene-induced turnover. Kinetic and dose-response analysesmore » support a model in which two opposing factors control levels of the ethylene receptor/CTR1 complexes. Ethylene stimulates the production of new complexes largely through transcriptional induction of the receptors. However, ethylene also induces turnover of receptors, such that levels of ethylene receptor/CTR1 complexes decrease at higher ethylene concentrations. Lastly, we discuss implications of this model for ethylene signaling.« less

Ethylene Regulates Levels of Ethylene Receptor/CTR1 Signaling Complexes in Arabidopsis thaliana*

PubMed Central

Shakeel, Samina N.; Gao, Zhiyong; Amir, Madiha; Chen, Yi-Feng; Rai, Muneeza Iqbal; Haq, Noor Ul; Schaller, G. Eric

2015-01-01

The plant hormone ethylene is perceived by a five-member family of receptors in Arabidopsis thaliana. The receptors function in conjunction with the Raf-like kinase CTR1 to negatively regulate ethylene signal transduction. CTR1 interacts with multiple members of the receptor family based on co-purification analysis, interacting more strongly with receptors containing a receiver domain. Levels of membrane-associated CTR1 vary in response to ethylene, doing so in a post-transcriptional manner that correlates with ethylene-mediated changes in levels of the ethylene receptors ERS1, ERS2, EIN4, and ETR2. Interactions between CTR1 and the receptor ETR1 protect ETR1 from ethylene-induced turnover. Kinetic and dose-response analyses support a model in which two opposing factors control levels of the ethylene receptor/CTR1 complexes. Ethylene stimulates the production of new complexes largely through transcriptional induction of the receptors. However, ethylene also induces turnover of receptors, such that levels of ethylene receptor/CTR1 complexes decrease at higher ethylene concentrations. Implications of this model for ethylene signaling are discussed. PMID:25814663

Pain-relieving prospects for adenosine receptors and ectonucleotidases

PubMed Central

Zylka, Mark J.

2010-01-01

Adenosine receptor agonists have potent antinociceptive effects in diverse preclinical models of chronic pain. In contrast, the efficacy of adenosine or adenosine receptor agonists at treating pain in humans is unclear. Two ectonucleotidases that generate adenosine in nociceptive neurons were recently identified. When injected spinally, these enzymes have long-lasting adenosine A1 receptor (A1R)-dependent antinociceptive effects in inflammatory and neuropathic pain models. Furthermore, recent findings indicate that spinal adenosine A2A receptor activation can enduringly inhibit neuropathic pain symptoms. Collectively, these studies suggest the possibility of treating chronic pain in humans by targeting specific adenosine receptor subtypes in anatomically defined regions with agonists or with ectonucleotidases that generate adenosine. PMID:21236731

Structural modeling of G-protein coupled receptors: An overview on automatic web-servers.

PubMed

Busato, Mirko; Giorgetti, Alejandro

2016-08-01

Despite the significant efforts and discoveries during the last few years in G protein-coupled receptor (GPCR) expression and crystallization, the receptors with known structures to date are limited only to a small fraction of human GPCRs. The lack of experimental three-dimensional structures of the receptors represents a strong limitation that hampers a deep understanding of their function. Computational techniques are thus a valid alternative strategy to model three-dimensional structures. Indeed, recent advances in the field, together with extraordinary developments in crystallography, in particular due to its ability to capture GPCRs in different activation states, have led to encouraging results in the generation of accurate models. This, prompted the community of modelers to render their methods publicly available through dedicated databases and web-servers. Here, we present an extensive overview on these services, focusing on their advantages, drawbacks and their role in successful applications. Future challenges in the field of GPCR modeling, such as the predictions of long loop regions and the modeling of receptor activation states are presented as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

Direct and inverse modelling for environmental risk assessment and emission control

NASA Astrophysics Data System (ADS)

Penenko, V.; Baklanov, A.; Tsvetova, E.; Mahura, A.

2009-04-01

A concept of environmental modelling and its applications for Siberian regions are presented. The regions are considered both as sources and receptors of pollution as elements of the global climatic system. A methodology has been developed to build the combined methods of forward and inverse modelling for the problems of the air quality, environmental risk assessment and control. It is based on variational principles and methods of adjoint sensitivity theory. This allows obtaining the optimal numerical schemes and universal algorithm of the forward-inverse modelling. Following the concept, the functionals (describing the generalised characteristics of the processes, data, and models) are considered together with the basic model components. To combine all these elements in the frames of forward and inverse relations, we suppose that each of them may contain uncertainty. In this case, it is naturally to formulate a weak-constraint variational principle for the augmented functional which contains the model description in the form of integral identity and the cost functional including the total measure of all uncertainties. The stationary conditions for the augmented functional with respect to the variations its functional arguments define the mutually agreed structure of numerical schemes for forward and adjoint problems, and sensitivity relations. For quantitative risk assessment the following characteristics are useful: (i) values of goal functionals and their variations in a form of sensitivity relations; (ii) risk and sensitivity functions to the variations of the sources. It is convenient to take the risk function multiplied by the source function as a distributed risk measure. The variational technique provides the backward propagation of information, contained in the target functionals, to parameters and sources of the models through the sensitivity and uncertainty functions. This gives a base for realisation of the feedback algorithms and methods of control theory, which are necessary for formulation of multi-criteria optimisation accounting different constraints of ecological, economical, and social essence while solving environmental problems such as air pollution control, placement design for new industrial units, etc. The problems of the long-term environmental forecasting demand revealing the dynamical active zones and the areas of increased sensitivity to the variations of forcings (model parameters). The proposed methodology of accounting the climatic data into environmental studies is suitable for studying such problems. Analysis of the long-term behaviour of the global climatic system and orthogonal decomposition of the multivariate series of meteorological data with respect to the scales of processes allows identifying the activity centers and using this information for construction of scenarios for assessment of risk/vulnerability for sources/receptors. Such analysis for Siberian regions showed that Siberia is situated in areas which separate circulation systems of high energy activity. For winter, they are the Pacific and Atlantic energy-active zones, whereas the Arctic and South-Asian zones withstand in Siberia in summer. These facts allow an interpretation of climatic instability inherent in the region. During the autumn-winter season, the instability expresses as sharp alteration of weather cycles. The formation of Altai-Sayan cyclogenesis (which is of the same intensity as the Mediterranean) is observed for the warm seasons in the southern Siberia. In climatology it is referred as a lee-type cyclogenesis. This is the large scale phenomenon in the climatic system of the central part of Eurasia. Such specific hydrodynamic background defines environment quality in Siberia. From the point of view of system analysis, the methods of sensitivity theory, risk assessment and control along with scenario approach offer a tool which allows bringing the results of the global atmospheric and climatic studies onto the regional level. Namely, this level puts the concrete questions on the environment quality and its changes such as a choice of plausible strategy for sources control and mitigation of the man-induced impact on environment. Some environmental problems for Siberian regions are discussed, and a number of forward, adjoint and inverse problems for different risk sites and goal functionals are presented.

Toxins and derivatives in molecular pharmaceutics: Drug delivery and targeted therapy.

PubMed

Zhan, Changyou; Li, Chong; Wei, Xiaoli; Lu, Wuyuan; Lu, Weiyue

2015-08-01

Protein and peptide toxins offer an invaluable source for the development of actively targeted drug delivery systems. They avidly bind to a variety of cognate receptors, some of which are expressed or even up-regulated in diseased tissues and biological barriers. Protein and peptide toxins or their derivatives can act as ligands to facilitate tissue- or organ-specific accumulation of therapeutics. Some toxins have evolved from a relatively small number of structural frameworks that are particularly suitable for addressing the crucial issues of potency and stability, making them an instrumental source of leads and templates for targeted therapy. The focus of this review is on protein and peptide toxins for the development of targeted drug delivery systems and molecular therapies. We summarize disease- and biological barrier-related toxin receptors, as well as targeted drug delivery strategies inspired by those receptors. The design of new therapeutics based on protein and peptide toxins is also discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

Simultaneous detection and functional response of testosterone and estradiol receptors in osteoblast plasma membranes.

PubMed

Armen, T A; Gay, C V

2000-09-14

Osteoblasts derived from the periosteal surfaces of two-three-week-old male broiler chicken tibias were cultured for eight days. The cells were then loaded with fura-2/AM ester to detect surges in intracellular Ca(2+). Treatment with 10(-7) M testosterone (T) or 17beta-estradiol (E) elicited a rapid (within seconds) response that was substantially reduced by introducing the calcium chelating agent EGTA or the calcium-channel blocker verapamil. The hormones were equally effective when covalently linked to bovine serum albumin (BSA), a procedure that ensures the hormone does not enter the cells. The rapid response to surface-bound steroids indicates that the responses were invoked through plasma-membrane receptors. The source of Ca(2+) was shown to be through entry from external sources, as well as from intracellular stores. Flow cytometry of fluorescein-tagged T-BSA and E-BSA revealed that osteoblasts derived from male chickens had similar and substantial levels of both receptors. Copyright 2000 Wiley-Liss, Inc.

A Spontaneous Mutation in Taar1 Impacts Methamphetamine-Related Traits Exclusively in DBA/2 Mice from a Single Vendor

PubMed Central

Reed, Cheryl; Baba, Harue; Zhu, Zhen; Erk, Jason; Mootz, John R.; Varra, Nicholas M.; Williams, Robert W.; Phillips, Tamara J.

2018-01-01

Major gene effects on traits associated with substance use disorders are rare. Previous findings in methamphetamine drinking (MADR) lines of mice, bred for high or low voluntary MA intake, and in null mutants demonstrate a major impact of the trace amine-associated receptor 1 (Taar1) gene on a triad of MA-related traits: MA consumption, MA-induced conditioned taste aversion and MA-induced hypothermia. While inbred strains are fundamentally genetically stable, rare spontaneous mutations can become fixed and result in new or aberrant phenotypes. A single nucleotide polymorphism in Taar1 that encodes a missense proline to threonine mutation in the second transmembrane domain (Taar1m1J) has been identified in the DBA/2J strain. MA is an agonist at this receptor, but the receptor produced by Taar1m1J does not respond to MA or endogenous ligands. In the present study, we used progeny of the C57BL/6J × DBA/2J F2 cross, the MADR lines, C57BL/6J × DBA/2J recombinant inbred strains, and DBA/2 mice sourced from four vendors to further examine Taar1-MA phenotype relations and to define the chronology of the fixation of the Taar1m1J mutation. Mice homozygous for Taar1m1J were found at high frequency early in selection for high MA intake in multiple replicates of the high MADR line, whereas Taar1m1J homozygotes were absent in the low MADR line. The homozygous Taar1m1J genotype is causally linked to increased MA intake, reduced MA-induced conditioned taste aversion, and reduced MA-induced hypothermia across models. Genotype-phenotype correlations range from 0.68 to 0.96. This Taar1 polymorphism exists in DBA/2J mice sourced directly from The Jackson Laboratory, but not DBA/2 mice sourced from Charles River (DBA/2NCrl), Envigo (formerly Harlan Sprague Dawley; DBA/2NHsd) or Taconic (DBA/2NTac). By genotyping archived samples from The Jackson Laboratory, we have determined that this mutation arose in 2001–2003. Our data strengthen the conclusion that the mutant Taar1m1J allele, which codes for a non-functional receptor protein, increases risk for multiple MA-related traits, including MA intake, in homozygous Taar1m1J individuals. PMID:29403379

Estimation of decay rates for fecal indicator bacteria and bacterial pathogens in agricultural field-applied manure

EPA Science Inventory

Field-applied manure is an important source of pathogenic exposure in surface water bodies for humans and ecological receptors. We analyzed the persistence and decay of fecal indicator bacteria and bacterial pathogens from three sources (cattle, poultry, swine) for agricultural f...

Characteristics of Fine Particulate Carbonaceous Aerosol at Two Remote Sites in Central Asia

EPA Science Inventory

Central Asia is a relatively understudied region of the world in terms of characterizing ambient particulate matter (PM) and quantifying source impacts of PM at receptor locations, although it is speculated to have an important role as a source region for long-range transport of ...

[Energy saving and LED lamp lighting and human health].

PubMed

Deĭnego, V N; Kaptsov, V A

2013-01-01

The appearance of new sources of high-intensity with large proportion of blue light in the spectrum revealed new risks of their influence on the function of the eye and human health, especially for children and teenagers. There is an urgent need to reconsider the research methods of vision hygiene in conditions of energy-saving and LED bulbs lighting. On the basis of a systematic approach and knowledge of the newly discovered photosensitive receptors there was built hierarchical model of the interaction of "light environment - the eye - the system of formation of visual images - the hormonal system of the person - his psycho-physiological state." This approach allowed us to develop a range of risk for the negative impact of spectrum on the functions of the eye and human health, as well as to formulate the hygiene requirements for energy-efficient high-intensity light sources.

Modeling avian exposures to perfluoroalkyl substances in aquatic habitats impacted by historical aqueous film forming foam releases.

PubMed

Larson, Emily S; Conder, Jason M; Arblaster, Jennifer A

2018-06-01

Releases of Perfluoroalkyl and Polyfluoroalkyl Substances (PFASs) associated with Aqueous Film Forming Foams (AFFFs) have the potential to impact on-site and downgradient aquatic habitats. Dietary exposures of aquatic-dependent birds were modeled for seven PFASs (PFHxA, PFOA, PFNA, PFDA, PFHxS, PFOS, and PFDS) using five different scenarios based on measurements of PFASs obtained from five investigations of sites historically-impacted by AFFF. Exposure modeling was conducted for four avian receptors representing various avian feeding guilds: lesser scaup (Aythya affinis), spotted sandpiper (Actitis macularia), great blue heron (Ardea herodias), and osprey (Pandion haliaetus). For the receptor predicted to receive the highest PFAS exposure (spotted sandpiper), model-predicted exposure to PFOS exceeded a laboratory-based, No Observed Adverse Effect Level exposure benchmark in three of the five model scenarios, confirming that risks to aquatic-dependent avian wildlife should be considered for investigations of historic AFFF releases. Perfluoroalkyl sulfonic acids (PFHxS, PFOS, and PFDS) represented 94% (on average) of total PFAS exposures due to their prevalence in historical AFFF formulations, and increased bioaccumulation in aquatic prey items and partitioning to aquatic sediment relative to perfluoroalkyl carboxylic acids. Sediment-associated PFASs (rather than water-associated PFASs) were the source of the highest predicted PFAS exposures, and are likely to be very important for understanding and managing AFFF site-specific ecological risks. Additional considerations for research needs and site-specific ecological risk assessments are discussed with the goal of optimizing ecological risk-based decision making at AFFF sites and prioritizing research needs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Estrogen Receptor Mutants/Variants in Human Breast Cancer.

DTIC Science & Technology

1996-12-01

average 1 hour per response, including the time for reviewing instructions, searching existing data sources,gathering and maintaining the data needed...Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188...we identified, for the first time , the expression of exon deleted progesterone receptor (PR) mRNAs in both normal and neoplastic human breast tissues

Delta-opioid receptors as targets for migraine therapy.

PubMed

Charles, Andrew; Pradhan, Amynah A

2016-06-01

The purpose of this review is to contrast the properties of the δ-opioid receptor with those of the μ-opioid receptor, which is the primary target of most currently available opioid analgesics. We also discuss preclinical evidence that indicates the potential efficacy of δ-opioid receptor agonists as migraine therapy. The use of currently available opioid analgesics is highly problematic for patients with migraine. Delta-opioid receptors have key differences from μ receptors; these differences make the δ receptor an attractive therapeutic target for migraine. Delta-opioid receptors are expressed in both the peripheral and central nervous system in anatomical regions and cell types that are believed to play a role in migraine. Delta-receptor agonists have also shown promising effects in multiple migraine models, including nitroglycerin evoked hyperalgesia and conditioned place aversion, and cortical spreading depression. Evidence from animal models indicates that activation of δ receptors is less likely to cause tolerance and dependence, and less likely to cause hyperalgesia. In addition, δ receptors may have antidepressant and anxiolytic properties that are distinct from those of μ receptors. In human studies investigating other conditions, δ-receptor agonists have been generally safe and well tolerated. Delta-opioid receptor agonists have promising potential as acute and/or preventive migraine therapies, without the problems associated with currently used opioid analgesics.

[The potential of group II metabotropic glutamate receptor antagonists as a novel antidepressant].

PubMed

Chaki, Shigeyuki

2012-08-01

Recently, abnormalities of glutamatergic transmission have been implicated in the pathophysiology of depression. Moreover, both ketamine, an NMDA receptor antagonist, and riluzole, a modulator of glutamatergic, transmission have been reported to be effective for the treatment of patients with treatment-refractory depression. Based on these findings, extensive studies to develop agents acting on glutamatergic transmission have been conducted. Glutamate receptors are divided into two main subtypes, ionotropic glutamate receptors and metabotropic glutamate (mGlu) receptors, both of which have subtypes. Of these, much attention has been paid to mGlu2/3 receptors. mGlu2/3 receptor antagonists such as MGS0039 and LY341495 have been reported to exert antidepressant effects in animal models of depression including the forced swim test, tail suspension test, learned helplessness paradigm, olfactory bulmectomy model and isolation rearing model, and to enhance serotonin release in the prefrontal cortex and dopamine release in the nucleus accumbens. Moreover, activation of AMPA receptor and mTOR signaling have been suggested to be involved in the antidepressant effects of mGlu2/3 receptor antagonists, as demonstrated in the actions of ketamine. Thus, mGlu2/3 receptor antagonists may share some neural networks with ketamine in exerting their antidepressant effects. In addition, the potential of other agents targeting glutamatergic transmission for novel antidepressants is being investigated.

Designing peptide inhibitor of insulin receptor to induce diabetes mellitus type 2 in animal model Mus musculus.

PubMed

Permatasari, Galuh W; Utomo, Didik H; Widodo

2016-10-01

A designing peptide as agent for inducing diabetes mellitus type 2 (T2DM) in an animal model is challenging. The computational approach provides a sophisticated tool to design a functional peptide that may block the insulin receptor activity. The peptide that able to inhibit the binding between insulin and insulin receptor is a warrant for inducing T2DM. Therefore, we designed a potential peptide inhibitor of insulin receptor as an agent to generate T2DM animal model by bioinformatics approach. The peptide has been developed based on the structure of insulin receptor binding site of insulin and then modified it to obtain the best properties of half life, hydrophobicity, antigenicity, and stability binding into insulin receptor. The results showed that the modified peptide has characteristics 100h half-life, high-affinity -95.1±20, and high stability 28.17 in complex with the insulin receptor. Moreover, the modified peptide has molecular weight 4420.8g/Mol and has no antigenic regions. Based on the molecular dynamic simulation, the complex of modified peptide-insulin receptor is more stable than the commercial insulin receptor blocker. This study suggested that the modified peptide has the promising performance to block the insulin receptor activity that potentially induce diabetes mellitus type 2 in mice. Copyright © 2016 Elsevier Ltd. All rights reserved.

High Sensitivity Crosslink Detection Coupled With Integrative Structure Modeling in the Mass Spec Studio *

PubMed Central

Sarpe, Vladimir; Rafiei, Atefeh; Hepburn, Morgan; Ostan, Nicholas; Schryvers, Anthony B.; Schriemer, David C.

2016-01-01

The Mass Spec Studio package was designed to support the extraction of hydrogen-deuterium exchange and covalent labeling data for a range of mass spectrometry (MS)-based workflows, to integrate with restraint-driven protein modeling activities. In this report, we present an extension of the underlying Studio framework and provide a plug-in for crosslink (XL) detection. To accommodate flexibility in XL methods and applications, while maintaining efficient data processing, the plug-in employs a peptide library reduction strategy via a presearch of the tandem-MS data. We demonstrate that prescoring linear unmodified peptide tags using a probabilistic approach substantially reduces search space by requiring both crosslinked peptides to generate sparse data attributable to their linear forms. The method demonstrates highly sensitive crosslink peptide identification with a low false positive rate. Integration with a Haddock plug-in provides a resource that can combine multiple sources of data for protein modeling activities. We generated a structural model of porcine transferrin bound to TbpB, a membrane-bound receptor essential for iron acquisition in Actinobacillus pleuropneumoniae. Using mutational data and crosslinking restraints, we confirm the mechanism by which TbpB recognizes the iron-loaded form of transferrin, and note the requirement for disparate sources of restraint data for accurate model construction. The software plugin is freely available at www.msstudio.ca. PMID:27412762

High Sensitivity Crosslink Detection Coupled With Integrative Structure Modeling in the Mass Spec Studio.

PubMed

Sarpe, Vladimir; Rafiei, Atefeh; Hepburn, Morgan; Ostan, Nicholas; Schryvers, Anthony B; Schriemer, David C

2016-09-01

The Mass Spec Studio package was designed to support the extraction of hydrogen-deuterium exchange and covalent labeling data for a range of mass spectrometry (MS)-based workflows, to integrate with restraint-driven protein modeling activities. In this report, we present an extension of the underlying Studio framework and provide a plug-in for crosslink (XL) detection. To accommodate flexibility in XL methods and applications, while maintaining efficient data processing, the plug-in employs a peptide library reduction strategy via a presearch of the tandem-MS data. We demonstrate that prescoring linear unmodified peptide tags using a probabilistic approach substantially reduces search space by requiring both crosslinked peptides to generate sparse data attributable to their linear forms. The method demonstrates highly sensitive crosslink peptide identification with a low false positive rate. Integration with a Haddock plug-in provides a resource that can combine multiple sources of data for protein modeling activities. We generated a structural model of porcine transferrin bound to TbpB, a membrane-bound receptor essential for iron acquisition in Actinobacillus pleuropneumoniae Using mutational data and crosslinking restraints, we confirm the mechanism by which TbpB recognizes the iron-loaded form of transferrin, and note the requirement for disparate sources of restraint data for accurate model construction. The software plugin is freely available at www.msstudio.ca. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Molecular characterization of the receptor binding structure-activity relationships of influenza B virus hemagglutinin.

PubMed

Carbone, V; Kim, H; Huang, J X; Baker, M A; Ong, C; Cooper, M A; Li, J; Rockman, S; Velkov, T

2013-01-01

Selectivity of α2,6-linked human-like receptors by B hemagglutinin (HA) is yet to be fully understood. This study integrates binding data with structure-recognition models to examine the impact of regional-specific sequence variations within the receptor-binding pocket on selectivity and structure activity relationships (SAR). The receptor-binding selectivity of influenza B HAs corresponding to either B/Victoria/2/1987 or the B/Yamagata/16/88 lineages was examined using surface plasmon resonance, solid-phase ELISA and gel-capture assays. Our SAR data showed that the presence of asialyl sugar units is the main determinant of receptor preference of α2,6 versus α2,3 receptor binding. Changes to the type of sialyl-glycan linkage present on receptors exhibit only a minor effect upon binding affinity. Homology-based structural models revealed that structural properties within the HA pocket, such as a glyco-conjugate at Asn194 on the 190-helix, sterically interfere with binding to avian receptor analogs by blocking the exit path of the asialyl sugars. Similarly, naturally occurring substitutions in the C-terminal region of the 190-helix and near the N-terminal end of the 140-loop narrows the horizontal borders of the binding pocket, which restricts access of the avian receptor analog LSTa. This study helps bridge the gap between ligand structure and receptor recognition for influenza B HA; and provides a consensus SAR model for the binding of human and avian receptor analogs to influenza B HA.

Investigating the Vertical Distribution and Source Attribution of Black Carbon over the Pacific Ocean

NASA Astrophysics Data System (ADS)

Zhang, J.; Liu, J.; Ban-Weiss, G. A.; Tao, S.

2014-12-01

Long-range transport of black carbon (BC) aerosols to the Pacific Ocean can potentially play a significant role in changing the marine climate through influences on temperature and cloud profiles and the top-of-atmosphere and surface energy balance. Therefore, quantitatively understanding sources of BC over the Pacific, particularly at different altitudes, is of great importance. In this study, we simulate the transport of thirteen continental BC tracers with a variety of e-folding aging times (few hours to 1 month) using the global chemical transport model MOZART-4. We then optimize BC aging rate according to different source regions by constraining the vertical profile of BC concentrations to the HAIPER Polo-to-Pole Observations (HIPPO). We find that for all HIPPO deployments, a shorter BC aging timescale (less than half day) for tropical and mid-latitude tracers and a longer aging timescale (2-10 days) for high-latitude tracers (except summer) in most cases significantly reduces model biases. By comparing the source-receptor relationship between the optimized BC tracers over the Pacific, we find that during 2009-2011, East Asia contributes most to the BC loading over the Northern Pacific in all seasons except summer, while South American, African and Australian tracers dominate the BC loadings over the Southern Pacific. In addition, unlike other tracers, African BC is a dominant contributor over a larger area in the free troposphere versus the boundary layer. Our findings indicate that the aging rate of BC strongly depends on source location and season, which may significantly influence the contribution of different source regions to BC forcing over the Pacific Ocean.

Source apportionment of trace metals in river sediments: A comparison of three methods.

PubMed

Chen, Haiyang; Teng, Yanguo; Li, Jiao; Wu, Jin; Wang, Jinsheng

2016-04-01

Increasing trace metal pollution in river sediment poses a significant threat to watershed ecosystem health. Identifying potential sources of sediment metals and apportioning their contributions are of key importance for proposing prevention and control strategies of river pollution. In this study, three advanced multivariate receptor models, factor analysis with nonnegative constraints (FA-NNC), positive matrix factorization (PMF), and multivariate curve resolution weighted-alternating least-squares (MCR-WALS), were comparatively employed for source apportionment of trace metals in river sediments and applied to the Le'an River, a main tributary of Poyang Lake which is the largest freshwater lake in China. The pollution assessment with contamination factor and geoaccumulation index suggested that the river sediments in Le'an River were contaminated severely by trace metals due to human activities. With the three apportionment tools, similar source profiles of trace metals in sediments were extracted. Especially, the MCR-WALS and PMF models produced essentially the same results. Comparatively speaking, the weighted schemes might give better solutions than the unweighted FA-NNC because the uncertainty information of environmental data was considered by PMF and MCR-WALS. Anthropogenic sources were apportioned as the most important pollution sources influencing the sediment metals in Le'an River with contributions of about 90%. Among them, copper tailings occupied the largest contribution (38.4-42.2%), followed by mining wastewater (29.0-33.5%), and agricultural activities (18.2-18.7%). To protect the ecosystem of Le'an River and Poyang Lake, special attention should be paid to the discharges of mining wastewater and the leachates of copper tailing ponds in that region. Copyright © 2015 Elsevier Ltd. All rights reserved.

Crosslinking Constraints and Computational Models as Complementary Tools in Modeling the Extracellular Domain of the Glycine Receptor

PubMed Central

Liu, Zhenyu; Szarecka, Agnieszka; Yonkunas, Michael; Speranskiy, Kirill; Kurnikova, Maria; Cascio, Michael

2014-01-01

The glycine receptor (GlyR), a member of the pentameric ligand-gated ion channel superfamily, is the major inhibitory neurotransmitter-gated receptor in the spinal cord and brainstem. In these receptors, the extracellular domain binds agonists, antagonists and various other modulatory ligands that act allosterically to modulate receptor function. The structures of homologous receptors and binding proteins provide templates for modeling of the ligand-binding domain of GlyR, but limitations in sequence homology and structure resolution impact on modeling studies. The determination of distance constraints via chemical crosslinking studies coupled with mass spectrometry can provide additional structural information to aid in model refinement, however it is critical to be able to distinguish between intra- and inter-subunit constraints. In this report we model the structure of GlyBP, a structural and functional homolog of the extracellular domain of human homomeric α1 GlyR. We then show that intra- and intersubunit Lys-Lys crosslinks in trypsinized samples of purified monomeric and oligomeric protein bands from SDS-polyacrylamide gels may be identified and differentiated by MALDI-TOF MS studies of limited resolution. Thus, broadly available MS platforms are capable of providing distance constraints that may be utilized in characterizing large complexes that may be less amenable to NMR and crystallographic studies. Systematic studies of state-dependent chemical crosslinking and mass spectrometric identification of crosslinked sites has the potential to complement computational modeling efforts by providing constraints that can validate and refine allosteric models. PMID:25025226

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

Homology modeling, active site prediction, and targeting the anti hypertension activity through molecular docking on endothelin – B receptor domain

PubMed Central

Rayalu, Daddam Jayasimha; Selvaraj, Chandrabose; Singh, Sanjeev Kumar; Ganeshan, Ramakrishan; Kumar, Nagapatla Udaya; Seshapani, Panthangi

2012-01-01

In cardiovascular system, activation of Endothelin receptors causes vasoconstriction which leads to Pulmonary Arterial Hypertension (PAH). Endothelin receptor antagonism has emerged as an important therapeutic strategy in pulmonary arterial hypertension. Bosentan is intended to affect vasoconstriction, hypertrophic and fibrotic effects by blocking the actions of receptors ETA and ETB. In this study we identified the action of Bosentan on endothelin B receptor using docking studies with homology modeled endothelin B receptor. Through the modeled protein, the flexible Docking study was performed with Bosentan and its derivatives with theoretically predicted active sites. The results indicated that amino acid ARG82, ARG84 and HIS197 present in endothelin B receptor are core important for binding activities and these residues are having strong hydrogen bond interactions with Bosentan. We have investigated the Bosentan and its derivatives interactions and scoring parameters using gold docking package. Among the docked compounds, one of the Bosentan derivatives BD6 shows better interaction than Bosentan with endothelin B receptor. Our results may be helpful for further investigations in both in vivo and in vitro conditions. PMID:22359440

Refinement of the conformation of a critical region of charge-charge interaction between cholecystokinin and its receptor.

PubMed

Ding, Xi-Qin; Pinon, Delia I; Furse, Kristina E; Lybrand, Terry P; Miller, Laurence J

2002-05-01

Insight into the molecular basis of cholecystokinin (CCK) binding to its receptor has come from receptor mutagenesis and photoaffinity labeling studies, with both contributing to the current hypothesis that the acidic Tyr-sulfate-27 residue within the peptide is situated adjacent to basic Arg(197) in the second loop of the receptor. Here, we refine our understanding of this region of interaction by examining a structure-activity series of these positions within both ligand and receptor and by performing three-dimensional molecular modeling of key pairs of modified ligand and receptor constructs. The important roles of Arg(197) and Tyr-sulfate-27 were supported by the marked negative impact on binding and biological response with their natural partner molecule when the receptor residue was replaced by acidic Asp or Glu and when the peptide residue was replaced by basic Arg, Lys, p-amino-Phe, p-guanidino-Phe, or p-methylamino-Phe. Complementary ligand-receptor charge-exchange experiments were unable to regain the lost function. This was supported by the molecular modeling, which demonstrated that the charge-reversed double mutants could not form a good interaction without extensive rearrangement of receptor conformation. The models further predicted that R197D and R197E mutations would lead to conformational changes in the extracellular domain, and this was experimentally supported by data showing that these mutations decreased peptide agonist and antagonist binding and increased nonpeptidyl antagonist binding. These receptor constructs also had increased susceptibility to trypsin degradation relative to the wild-type receptor. In contrast, the relatively conservative R197K mutation had modest negative impact on peptide agonist binding, again consistent with the modeling demonstration of loss of a series of stabilizing inter- and intramolecular bonds. The strong correlation between predicted and experimental results support the reported refinement in the three-dimensional structure of the CCK-occupied receptor.

PM10 source apportionment applying PMF and chemical tracer analysis to ship-borne measurements in the Western Mediterranean

NASA Astrophysics Data System (ADS)

Bove, M. C.; Brotto, P.; Calzolai, G.; Cassola, F.; Cavalli, F.; Fermo, P.; Hjorth, J.; Massabò, D.; Nava, S.; Piazzalunga, A.; Schembari, C.; Prati, P.

2016-01-01

A PM10 sampling campaign was carried out on board the cruise ship Costa Concordia during three weeks in summer 2011. The ship route was Civitavecchia-Savona-Barcelona-Palma de Mallorca-Malta (Valletta)-Palermo-Civitavecchia. The PM10 composition was measured and utilized to identify and characterize the main PM10 sources along the ship route through receptor modelling, making use of the Positive Matrix Factorization (PMF) algorithm. A particular attention was given to the emissions related to heavy fuel oil combustion by ships, which is known to be also an important source of secondary sulphate aerosol. Five aerosol sources were resolved by the PMF analysis. The primary contribution of ship emissions to PM10 turned out to be (12 ± 4)%, while secondary ammonium sulphate contributed by (35 ± 5)%. Approximately, 60% of the total sulphate was identified as secondary aerosol while about 20% was attributed to heavy oil combustion in ship engines. The measured concentrations of methanesulphonic acid (MSA) indicated a relevant contribution to the observed sulphate loading by biogenic sulphate, formed by the atmospheric oxidation of dimethyl sulphide (DMS) emitted by marine phytoplankton.

Elimination of a ligand gating site generates a supersensitive olfactory receptor.

PubMed

Sharma, Kanika; Ahuja, Gaurav; Hussain, Ashiq; Balfanz, Sabine; Baumann, Arnd; Korsching, Sigrun I

2016-06-21

Olfaction poses one of the most complex ligand-receptor matching problems in biology due to the unparalleled multitude of odor molecules facing a large number of cognate olfactory receptors. We have recently deorphanized an olfactory receptor, TAAR13c, as a specific receptor for the death-associated odor cadaverine. Here we have modeled the cadaverine/TAAR13c interaction, exchanged predicted binding residues by site-directed mutagenesis, and measured the activity of the mutant receptors. Unexpectedly we observed a binding site for cadaverine at the external surface of the receptor, in addition to an internal binding site, whose mutation resulted in complete loss of activity. In stark contrast, elimination of the external binding site generated supersensitive receptors. Modeling suggests this site to act as a gate, limiting access of the ligand to the internal binding site and thereby downregulating the affinity of the native receptor. This constitutes a novel mechanism to fine-tune physiological sensitivity to socially relevant odors.