Journal Article: EPA's National Dioxin Air Monitoring Network ...

EPA Pesticide Factsheets

The U.S. Environmental Protection Agency (U.S. EPA) established the National Dioxin Air Monitoring Network (NDAMN) in June of 1998, and operated it until November of 2004. The objective of NDAMN was to determine background air concentrations of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (dl-PCBs). NDAMN started with 10 sampling sites, adding more over time until the final count of 34 sites was reached by the beginning of 2003. Samples were taken quarterly, and the final sample count was 685. All samples were measured for 17 PCDD/PCDF congeners, 8 PCDD/PCDF homologue groups, and 7 dl-PCBs (note: 5 additional dl-PCBs were added for samples starting in the summer of 2002; 317 samples had measurements of 12 dl-PCBs). The overall average total toxic equivalent (TEQ) concentration in the United States was 11.2 fg TEQ m−3 with dl-PCBs contributing 0.8 fg TEQ m−3 (7%) to this total. The archetype dioxin and furan background air congener profile was seen in the survey averages and in most individual samples. This archetype profile is characterized by low and similar concentrations for tetra – through hexa PCDD/PCDF congeners, with elevations in four congeners – a hepta dioxin and furan congener, and both octa congeners. Sites were generally categorized as urban (4 sites), rural (23 sites), or remote (7 sites). The average TEQ concentrations over all sites and samples within these cat

Identifying influencers from sampled social networks

NASA Astrophysics Data System (ADS)

Tsugawa, Sho; Kimura, Kazuma

2018-10-01

Identifying influencers who can spread information to many other individuals from a social network is a fundamental research task in the network science research field. Several measures for identifying influencers have been proposed, and the effectiveness of these influence measures has been evaluated for the case where the complete social network structure is known. However, it is difficult in practice to obtain the complete structure of a social network because of missing data, false data, or node/link sampling from the social network. In this paper, we investigate the effects of node sampling from a social network on the effectiveness of influence measures at identifying influencers. Our experimental results show that the negative effect of biased sampling, such as sample edge count, on the identification of influencers is generally small. For social media networks, we can identify influencers whose influence is comparable with that of those identified from the complete social networks by sampling only 10%-30% of the networks. Moreover, our results also suggest the possible benefit of network sampling in the identification of influencers. Our results show that, for some networks, nodes with higher influence can be discovered from sampled social networks than from complete social networks.

40 CFR 61.34 - Air sampling.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 8 2011-07-01 2011-07-01 false Air sampling. 61.34 Section 61.34... sampling. (a) Stationary sources subject to § 61.32(b) shall locate air sampling sites in accordance with a... concentrations calculated within 30 days after filters are collected. Records of concentrations at all sampling...

Global thermal analysis of air-air cooled motor based on thermal network

NASA Astrophysics Data System (ADS)

Hu, Tian; Leng, Xue; Shen, Li; Liu, Haidong

2018-02-01

The air-air cooled motors with high efficiency, large starting torque, strong overload capacity, low noise, small vibration and other characteristics, are widely used in different department of national industry, but its cooling structure is complex, it requires the motor thermal management technology should be high. The thermal network method is a common method to calculate the temperature field of the motor, it has the advantages of small computation time and short time consuming, it can save a lot of time in the initial design phase of the motor. The domain analysis of air-air cooled motor and its cooler was based on thermal network method, the combined thermal network model was based, the main components of motor internal and external cooler temperature were calculated and analyzed, and the temperature rise test results were compared to verify the correctness of the combined thermal network model, the calculation method can satisfy the need of engineering design, and provide a reference for the initial and optimum design of the motor.

Air sampling with solid phase microextraction

NASA Astrophysics Data System (ADS)

Martos, Perry Anthony

There is an increasing need for simple yet accurate air sampling methods. The acceptance of new air sampling methods requires compatibility with conventional chromatographic equipment, and the new methods have to be environmentally friendly, simple to use, yet with equal, or better, detection limits, accuracy and precision than standard methods. Solid phase microextraction (SPME) satisfies the conditions for new air sampling methods. Analyte detection limits, accuracy and precision of analysis with SPME are typically better than with any conventional air sampling methods. Yet, air sampling with SPME requires no pumps, solvents, is re-usable, extremely simple to use, is completely compatible with current chromatographic equipment, and requires a small capital investment. The first SPME fiber coating used in this study was poly(dimethylsiloxane) (PDMS), a hydrophobic liquid film, to sample a large range of airborne hydrocarbons such as benzene and octane. Quantification without an external calibration procedure is possible with this coating. Well understood are the physical and chemical properties of this coating, which are quite similar to those of the siloxane stationary phase used in capillary columns. The log of analyte distribution coefficients for PDMS are linearly related to chromatographic retention indices and to the inverse of temperature. Therefore, the actual chromatogram from the analysis of the PDMS air sampler will yield the calibration parameters which are used to quantify unknown airborne analyte concentrations (ppb v to ppm v range). The second fiber coating used in this study was PDMS/divinyl benzene (PDMS/DVB) onto which o-(2,3,4,5,6- pentafluorobenzyl) hydroxylamine (PFBHA) was adsorbed for the on-fiber derivatization of gaseous formaldehyde (ppb v range), with and without external calibration. The oxime formed from the reaction can be detected with conventional gas chromatographic detectors. Typical grab sampling times were as small as 5 seconds

US EPA's National Dioxin Air Monitoring Network: Analytical ...

EPA Pesticide Factsheets

The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric chlorinated dibenzo-p-dioxins (CDDs), furans (CDFs), and coplanar polychlorinated biphenyls (PCBs) at rural and non-impacted locations throughout the United States. Currently operating at 32 sampling stations, NDAMN has three primary purposes: (1) to determine the atmospheric levels and occurrences of dioxin-like compounds in rural and agricultural areas where livestock, poultry, and animal feed crops are grown; (2) to provide measurements of atmospheric levels in different geographic regions of the U.S.; and (3) to provide information regarding the long-range transport of dioxin-like compounds in air over the U.S. Designed in 1997, NDAMN has been implemented in phases, with the first phase consisting of 9 monitoring stations and is achieving congener-specific detection lmits of 0.1 fg/m3 for 2,3,7,8-TCDD and 10 fg/m3 for OCDD. With respect to coplanar PCBs, the detection limits are generally higher due to the presence of background levels in the air during the preparation and processing of the samples. Achieving these extremely low levels of detection present a host of analytical issues. Among these issues are the methods used to establish ultra-trace detection limits, measures to ensure against and monitor for breakthrough of native analytes when sampling large volumes of air, and procedures for handling and e

Inertial impaction air sampling device

DOEpatents

Dewhurst, Katharine H.

1990-01-01

An inertial impactor to be used in an air sampling device for collection of respirable size particles in ambient air which may include a graphite furnace as the impaction substrate in a small-size, portable, direct analysis structure that gives immediate results and is totally self-contained allowing for remote and/or personal sampling. The graphite furnace collects suspended particles transported through the housing by means of the air flow system, and these particles may be analyzed for elements, quantitatively and qualitatively, by atomic absorption spectrophotometry.

Inertial impaction air sampling device

DOEpatents

Dewhurst, K.H.

1990-05-22

An inertial impactor is designed which is to be used in an air sampling device for collection of respirable size particles in ambient air. The device may include a graphite furnace as the impaction substrate in a small-size, portable, direct analysis structure that gives immediate results and is totally self-contained allowing for remote and/or personal sampling. The graphite furnace collects suspended particles transported through the housing by means of the air flow system, and these particles may be analyzed for elements, quantitatively and qualitatively, by atomic absorption spectrophotometry. 3 figs.

Inertial impaction air sampling device

DOEpatents

Dewhurst, K.H.

1987-12-10

An inertial impactor to be used in an air sampling device for collection of respirable size particles in ambient air which may include a graphite furnace as the impaction substrate in a small-size, portable, direct analysis structure that gives immediate results and is totally self-contained allowing for remote and/or personal sampling. The graphite furnace collects suspended particles transported through the housing by means of the air flow system, and these particles may be analyzed for elements, quantitatively and qualitatively, by atomic absorption spectrophotometry. 3 figs.

Air Sampling Filter

NASA Technical Reports Server (NTRS)

1980-01-01

General Metal Works' Accu-Vol is a high-volume air sampling system used by many government agencies to monitor air quality for pollution control purposes. Procedure prevents possible test-invalidating contamination from materials other than particulate pollutants, caused by manual handling or penetration of windblown matter during transit, a cassette was developed in which the filter is sealed within a metal frame and protected in transit by a snap-on aluminum cover, thus handled only under clean conditions in the laboratory.

Atmospheric CO2 Records from Sites in the Umweltbundesamt (UBA) Air Sampling Network (1972 - 1997)

DOE Data Explorer

Fricke, W. [Umweltbundesamt, Offenbach/Main, Germany; Wallasch, M. [Umweltbundesamt, Offenbach/Main, Germany; Uhse, Karin [Umweltbundesamt, Offenbach/Main, Germany; Schmidt, Martina [University of Heidelberg, Heidelberg, Germany; Levin, Ingeborg [University of Heidelberg, Heidelberg, Germany

1998-01-01

Air samples for the purpose of monitoring atmospheric CO2 were collected from five sites in the UBA air sampling network. Annual atmospheric CO2 concentrations at Brotjacklriegel rose from 331.63 parts per million by volume (ppmv) in 1972 to 353.12 ppmv in 1988. Because of the site's forest location, the monthly atmospheric CO2 record from Brotjacklriegel exhibits very large seasonal amplitude. This amplitude reached almost 40 ppmv in 1985. Minimum mixing ratios are recorded at Brotjacklriegel during July-September; maximum values, during November-March. CO2 concentrations at Deuselbach rose from 340.82 parts per million by volume (ppmv) in 1972 to 363.76 ppmv in 1989. The monthly atmospheric CO2 record from Deuselbach is influenced by local agricultural activities and photosynthetic depletion but does not exhibit the large seasonal amplitude observed at other UBA monitoring sites. Minimum monthly atmospheric CO2 mixing ratios at Deuselbach are typically observed in August but may appear as early as June. Maximum values are seen in the record for November-March. Atmospheric CO2 concentrations at Schauinsland rose from ~328 parts per million by volume (ppmv) in 1972 to ~365 ppmv in 1997. This represents a growth rate of approximately 1.5 ppmv per year. The Schauinsland site is considered the least contaminated of the UBA sites. CO2 concentrations at Waldhof rose from 346.82 parts per million by volume (ppmv) in 1972 to 372.09 ppmv in 1993. The Waldhof site is subject to pollution sources; consequently, the monthly atmospheric CO2 record exhibits a large seasonal amplitude. Atmospheric CO2 concentrations at Westerland rose from ~329 parts per million by volume (ppmv) in 1973 to ~364 ppmv in 1997. The atmospheric CO2 record from Westerland shows a seasonal pattern similar to other UBA sites; minimum values are recorded during July-September; maximum mixing ratios during November-March.

Diagnosing AIRS Sampling with CloudSat Cloud Classes

NASA Technical Reports Server (NTRS)

Fetzer, Eric; Yue, Qing; Guillaume, Alexandre; Kahn, Brian

2011-01-01

AIRS yield and sampling vary with cloud state. Careful utilization of collocated multiple satellite sensors is necessary. Profile differences between AIRS and ECMWF model analyses indicate that AIRS has high sampling and excellent accuracy for certain meteorological conditions. Cloud-dependent sampling biases may have large impact on AIRS L2 and L3 data in climate research. MBL clouds / lower tropospheric stability relationship is one example. AIRS and CloudSat reveal a reasonable climatology in the MBL cloud regime despite limited sampling in stratocumulus. Thermodynamic parameters such as EIS derived from AIRS data map these cloud conditions successfully. We are working on characterizing AIRS scenes with mixed cloud types.

Air sampling workshop: October 24-25, 1978

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

Not Available

1979-06-01

A two-day workshop was held in October 1978 on air sampling strategies for the occupational environment. Strategies comprise the elements of implementing an air sampling program including deciding on the extent of sampling, selecting appropriate types of measurement, placing sampling instruments properly, and interpreting sample results correctly. All of these elements are vital in the reliable assessment of occupational exposures yet their coverage in the industrial hygiene literature is meager. Although keyed to a few introductory topics, the agenda was sufficiently informal to accommodate extemporaneous discussion on any subject related to sampling strategies. Questions raised during the workshop mirror themore » status of air sampling strategy as much as the factual information that was presented. It may be concluded from the discussion and questions that air sampling strategy is an elementary state and urgently needs concerted attention from the industrial hygiene profession.« less

Wireless Sensor Network Applications for the Combat Air Forces

DTIC Science & Technology

2006-06-13

WIRELESS SENSOR NETWORK APPLICATIONS FOR THE COMBAT AIR FORCES GRADUATE RESEARCH PROJECT...Government. AFIT/IC4/ENG/06-05 WIRELESS SENSOR NETWORK APPLICATIONS FOR THE COMBAT AIR FORCES GRADUATE RESEARCH PROJECT Presented to the...Major, USAF June 2006 APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED AFIT/IC4/ENG/06-05 WIRELESS SENSOR NETWORK APPLICATIONS

40 CFR 61.34 - Air sampling.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 9 2012-07-01 2012-07-01 false Air sampling. 61.34 Section 61.34 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS National Emission Standard for Beryllium § 61.34 Air...

40 CFR 61.34 - Air sampling.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 9 2013-07-01 2013-07-01 false Air sampling. 61.34 Section 61.34 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS National Emission Standard for Beryllium § 61.34 Air...

Journal Article: the National Dioxin Air Monitoring Network ...

EPA Pesticide Factsheets

In June, 1998, the U.S. EPA established the National Dioxin Air Monitoring Network (NDAMN). The primary goal of NDAMN is determine the temporal and geographical variability of atmospheric CDDs, CDFs, and coplanar PCBs at rural and nonimpacted locations throughout the United States. Currently operating at 32 sampling stations, NDAMN has three primary purposes: (1) to determine the atmospheric levels and occurrences of dioxin-like compounds in rural and agricultural areas where livestock, poultry and animal feed crops are grown; (2) to provide measurements of atmospheric levels of dioxin-like compounds in different geographic regions of the U.S.; and (3) to provide information regarding the long-range transport of dioxin-like compounds in air over the U.S. At Dioxin 2000, we reported on the preliminary results of monitoring at 9 rural locations from June 1998 through June 1999. By the end of 1999, NDAMN had expanded to 21 sampling stations. Then, at Dioxin 2001, we reported the results of the first 18 months of operation of NDAMN at 15 rural and 6 National Park stations in the United States. The following is intended to be an update to this national monitoring effort. We are reporting the air monitoring results of 17 rural and 8 National Park NDAMN stations operational over 4 sampling moments during calendar year 2000. Two stations located in suburban Washington DC and San Francisco, CA are more urban in character and serve as an indicator of CDD/F and cop

Network Sampling and Classification:An Investigation of Network Model Representations

PubMed Central

Airoldi, Edoardo M.; Bai, Xue; Carley, Kathleen M.

2011-01-01

Methods for generating a random sample of networks with desired properties are important tools for the analysis of social, biological, and information networks. Algorithm-based approaches to sampling networks have received a great deal of attention in recent literature. Most of these algorithms are based on simple intuitions that associate the full features of connectivity patterns with specific values of only one or two network metrics. Substantive conclusions are crucially dependent on this association holding true. However, the extent to which this simple intuition holds true is not yet known. In this paper, we examine the association between the connectivity patterns that a network sampling algorithm aims to generate and the connectivity patterns of the generated networks, measured by an existing set of popular network metrics. We find that different network sampling algorithms can yield networks with similar connectivity patterns. We also find that the alternative algorithms for the same connectivity pattern can yield networks with different connectivity patterns. We argue that conclusions based on simulated network studies must focus on the full features of the connectivity patterns of a network instead of on the limited set of network metrics for a specific network type. This fact has important implications for network data analysis: for instance, implications related to the way significance is currently assessed. PMID:21666773

Journal Article: the National Dioxin Air Monitoring Network ...

EPA Pesticide Factsheets

The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric CDDs, CDFs and coplanar PCBs at rural and nonimpacted locations throughout the United States. Currently operating at 32 sampling stations, NDAMN has three primary purposes: (1) to determine the atmospheric levels and occurrences of dioxin-like compounds in rural and agricultural areas where livestock, poultry and animal feed crops are grown; (2) to provide measurements of atmospheric levels of dioxin-like compounds in different geographic regions of the U.S.; and (3) to provide information regarding the long-range transport of dioxin-like compounds in air over the U.S. Designed in 1997, NDAMN has been implemented in phases, with the first phase consisting of 9 monitoring stations. Previously EPA has reported on the preliminary results of monitoring at 9 rural locations from June1998 through June 19991. The one-year measurement at the 9 stations indicated an annual mean TEQDF–WHO98 air concentration of 12 fg m-3. Since this reporting, NDAMN has been extended to include additional stations. The following is intended to be an update to this national monitoring effort. We are reporting the air monitoring results of 22 NDAMN stations operational over 9 sampling moments from June 1998 to December 1999. Fifteen stations are in rural areas, and 6 are located in National Parks. One station is located in suburban Wa

Sampling of temporal networks: Methods and biases

NASA Astrophysics Data System (ADS)

Rocha, Luis E. C.; Masuda, Naoki; Holme, Petter

2017-11-01

Temporal networks have been increasingly used to model a diversity of systems that evolve in time; for example, human contact structures over which dynamic processes such as epidemics take place. A fundamental aspect of real-life networks is that they are sampled within temporal and spatial frames. Furthermore, one might wish to subsample networks to reduce their size for better visualization or to perform computationally intensive simulations. The sampling method may affect the network structure and thus caution is necessary to generalize results based on samples. In this paper, we study four sampling strategies applied to a variety of real-life temporal networks. We quantify the biases generated by each sampling strategy on a number of relevant statistics such as link activity, temporal paths and epidemic spread. We find that some biases are common in a variety of networks and statistics, but one strategy, uniform sampling of nodes, shows improved performance in most scenarios. Given the particularities of temporal network data and the variety of network structures, we recommend that the choice of sampling methods be problem oriented to minimize the potential biases for the specific research questions on hand. Our results help researchers to better design network data collection protocols and to understand the limitations of sampled temporal network data.

Atmospheric Hydrogen (H2) Concentrations from the CSIRO GASLAB Flask Sampling Network (1992 - 2001)

DOE Data Explorer

Steele, L. P. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Atmospheric Research, Aspendale, Victoria, Australia; Krummel, P. B. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Atmospheric Research, Aspendale, Victoria, Australia; Langenfelds, R. L. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Atmospheric Research, Aspendale, Victoria, Australia

2003-01-01

Air samples from nine sites were collected from the CSIRO GASLAB Flask Sampling Network for the purpose of monitoring the atmospheric hydrogen (H2) concentrations. The listed data were obtained from flask air samples returned to the CSIRO GASLAB for analysis. Typical sample storage times ranged from days to weeks for some sites (e.g., Cape Grim) to as much as one year for Macquarie Island and the Antarctic sites. Experiments carried out to test for any change in sample H22 mixing ratio during storage have shown no consistent and systematic drift in these flask types over test periods of several months to years (Cooper et al., 1999). An annual cycle of H2 is evident, reflecting the seasonal nature of some of the major sources and sinks (Novelli et al., 1999).

High-Density, High-Resolution, Low-Cost Air Quality Sensor Networks for Urban Air Monitoring

NASA Astrophysics Data System (ADS)

Mead, M. I.; Popoola, O. A.; Stewart, G.; Bright, V.; Kaye, P.; Saffell, J.

2012-12-01

Monitoring air quality in highly granular environments such as urban areas which are spatially heterogeneous with variable emission sources, measurements need to be made at appropriate spatial and temporal scales. Current routine air quality monitoring networks generally are either composed of sparse expensive installations (incorporating e.g. chemiluminescence instruments) or higher density low time resolution systems (e.g. NO2 diffusion tubes). Either approach may not accurately capture important effects such as pollutant "hot spots" or adequately capture spatial (or temporal) variability. As a result, analysis based on data from traditional low spatial resolution networks, such as personal exposure, may be inaccurate. In this paper we present details of a sophisticated, low-cost, multi species (gas phase, speciated PM, meteorology) air quality measurement network methodology incorporating GPS and GPRS which has been developed for high resolution air quality measurements in urban areas. Sensor networks developed in the Centre for Atmospheric Science (University of Cambridge) incorporated electrochemical gas sensors configured for use in urban air quality studies operating at parts-per-billion (ppb) levels. It has been demonstrated that these sensors can be used to measure key air quality gases such as CO, NO and NO2 at the low ppb mixing ratios present in the urban environment (estimated detection limits <4ppb for CO and NO and <1ppb for NO2. Mead et al (submitted Aug., 2012)). Based on this work, a state of the art multi species instrument package for deployment in scalable sensor networks has been developed which has general applicability. This is currently being employed as part of a major 3 year UK program at London Heathrow airport (the Sensor Networks for Air Quality (SNAQ) Heathrow project). The main project outcome is the creation of a calibrated, high spatial and temporal resolution data set for O3, NO, NO2, SO2, CO, CO2, VOCstotal, size-speciated PM

Adaptive Sampling for Urban Air Quality through Participatory Sensing

PubMed Central

Zeng, Yuanyuan; Xiang, Kai

2017-01-01

Air pollution is one of the major problems of the modern world. The popularization and powerful functions of smartphone applications enable people to participate in urban sensing to better know about the air problems surrounding them. Data sampling is one of the most important problems that affect the sensing performance. In this paper, we propose an Adaptive Sampling Scheme for Urban Air Quality (AS-air) through participatory sensing. Firstly, we propose to find the pattern rules of air quality according to the historical data contributed by participants based on Apriori algorithm. Based on it, we predict the on-line air quality and use it to accelerate the learning process to choose and adapt the sampling parameter based on Q-learning. The evaluation results show that AS-air provides an energy-efficient sampling strategy, which is adaptive toward the varied outside air environment with good sampling efficiency. PMID:29099766

DESIGN OF LARGE-SCALE AIR MONITORING NETWORKS

EPA Science Inventory

The potential effects of air pollution on human health have received much attention in recent years. In the U.S. and other countries, there are extensive large-scale monitoring networks designed to collect data to inform the public of exposure risks to air pollution. A major crit...

Evaluation of Urban Air Quality By Passive Sampling Technique

NASA Astrophysics Data System (ADS)

Nunes, T. V.; Miranda, A. I.; Duarte, S.; Lima, M. J.

Aveiro is a flat small city in the centre of Portugal, close to the Atlantic coast. In the last two decades an intensive development of demographic, traffic and industry growth in the region was observed which was reflected on the air quality degrada- tion. In order to evaluate the urban air quality in Aveiro, a field-monitoring network by passive sampling with high space resolution was implemented. Twenty-four field places were distributed in a area of 3x3 Km2 and ozone and NO2 concentrations were measured. The site distribution density was higher in the centre, 250x250 m2 than in periphery where a 500x500 m2 grid was used. The selection of field places took into consideration the choice criteria recommendation by United Kingdom environmental authorities, and three tubes and a blank tube for each pollutant were used at each site. The sampling system was mounted at 3m from the ground usually profiting the street lampposts. Concerning NO2 acrylic tubes were used with 85 mm of length and an in- ternal diameter of 12mm, where in one of the extremities three steel grids impregnated with a solution of TEA were placed and fixed with a polyethylene end cup (Heal et al., 1999); PFA Teflon tube with 53 mm of length and 9 mm of internal diameter and three impregnated glass filters impregnated with DPE solution fixed by a teflon end cup was used for ozone sampling (Monn and Hargartner, 1990). The passive sampling method for ozone and nitrogen dioxide was compared with continuous measurements, but the amount of measurements wasnSt enough for an accurate calibration and validation of the method. Although this constraint the field observations (June to August 2001) for these two pollutants assign interesting information about the air quality in the urban area. A krigger method of interpolation (Surfer- Golden Software-2000) was applied to field data to obtain isolines distribution of NO2 and ozone concentration for the studied area. Even the used passive sampling method has many

Maximizing algebraic connectivity in air transportation networks

NASA Astrophysics Data System (ADS)

Wei, Peng

In air transportation networks the robustness of a network regarding node and link failures is a key factor for its design. An experiment based on the real air transportation network is performed to show that the algebraic connectivity is a good measure for network robustness. Three optimization problems of algebraic connectivity maximization are then formulated in order to find the most robust network design under different constraints. The algebraic connectivity maximization problem with flight routes addition or deletion is first formulated. Three methods to optimize and analyze the network algebraic connectivity are proposed. The Modified Greedy Perturbation Algorithm (MGP) provides a sub-optimal solution in a fast iterative manner. The Weighted Tabu Search (WTS) is designed to offer a near optimal solution with longer running time. The relaxed semi-definite programming (SDP) is used to set a performance upper bound and three rounding techniques are discussed to find the feasible solution. The simulation results present the trade-off among the three methods. The case study on two air transportation networks of Virgin America and Southwest Airlines show that the developed methods can be applied in real world large scale networks. The algebraic connectivity maximization problem is extended by adding the leg number constraint, which considers the traveler's tolerance for the total connecting stops. The Binary Semi-Definite Programming (BSDP) with cutting plane method provides the optimal solution. The tabu search and 2-opt search heuristics can find the optimal solution in small scale networks and the near optimal solution in large scale networks. The third algebraic connectivity maximization problem with operating cost constraint is formulated. When the total operating cost budget is given, the number of the edges to be added is not fixed. Each edge weight needs to be calculated instead of being pre-determined. It is illustrated that the edge addition and the

Sampling from complex networks using distributed learning automata

NASA Astrophysics Data System (ADS)

Rezvanian, Alireza; Rahmati, Mohammad; Meybodi, Mohammad Reza

2014-02-01

A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.

PRECISION OF ATMOSPHERIC DRY DEPOSITION DATA FROM THE CLEAN AIR STATUS AND TRENDS NETWORK (CASTNET)

EPA Science Inventory

A collocated, dry deposition sampling program was begun in January 1987 by the US Environmental Protection Agency to provide ongoing estimates of the overall precision of dry deposition and supporting data entering the Clean Air Status and Trends Network (CASTNet) archives Duplic...

Passive air sampling theory for semivolatile organic compounds.

PubMed

Bartkow, Michael E; Booij, Kees; Kennedy, Karen E; Müller, Jochen F; Hawker, Darryl W

2005-07-01

The mathematical modelling underlying passive air sampling theory can be based on mass transfer coefficients or rate constants. Generally, these models have not been inter-related. Starting with basic models, the exchange of chemicals between the gaseous phase and the sampler is developed using mass transfer coefficients and rate constants. Importantly, the inter-relationships between the approaches are demonstrated by relating uptake rate constants and loss rate constants to mass transfer coefficients when either sampler-side or air-side resistance is dominating chemical exchange. The influence of sampler area and sampler volume on chemical exchange is discussed in general terms and as they relate to frequently used parameters such as sampling rates and time to equilibrium. Where air-side or sampler-side resistance dominates, an increase in the surface area of the sampler will increase sampling rates. Sampling rates are not related to the sampler/air partition coefficient (K(SV)) when air-side resistance dominates and increase with K(SV) when sampler-side resistance dominates.

BOREAS AFM-5 Level-1 Upper Air Network Data

NASA Technical Reports Server (NTRS)

Barr, Alan; Hrynkiw, Charmaine; Newcomer, Jeffrey A. (Editor); Hall, Forrest G. (Editor); Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-5 team collected and processed data from the numerous radiosonde flights during the project. The goals of the AFM-05 team were to provide large-scale definition of the atmosphere by supplementing the existing Atmospheric Environment Service (AES) aerological network, both temporally and spatially. This data set includes basic upper-air parameters collected from the network of upper-air stations during the 1993, 1994, and 1996 field campaigns over the entire study region. The data are contained in tabular ASCII files. The level-1 upper-air network data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files also are available on a CD-ROM (see document number 20010000884).

A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems

PubMed Central

Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling

2015-01-01

The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems. PMID:26703598

A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems.

PubMed

Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling

2015-12-12

The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems.

Congestion transition in air traffic networks.

PubMed

Monechi, Bernardo; Servedio, Vito D P; Loreto, Vittorio

2015-01-01

Air Transportation represents a very interesting example of a complex techno-social system whose importance has considerably grown in time and whose management requires a careful understanding of the subtle interplay between technological infrastructure and human behavior. Despite the competition with other transportation systems, a growth of air traffic is still foreseen in Europe for the next years. The increase of traffic load could bring the current Air Traffic Network above its capacity limits so that safety standards and performances might not be guaranteed anymore. Lacking the possibility of a direct investigation of this scenario, we resort to computer simulations in order to quantify the disruptive potential of an increase in traffic load. To this end we model the Air Transportation system as a complex dynamical network of flights controlled by humans who have to solve potentially dangerous conflicts by redirecting aircraft trajectories. The model is driven and validated through historical data of flight schedules in a European national airspace. While correctly reproducing actual statistics of the Air Transportation system, e.g., the distribution of delays, the model allows for theoretical predictions. Upon an increase of the traffic load injected in the system, the model predicts a transition from a phase in which all conflicts can be successfully resolved, to a phase in which many conflicts cannot be resolved anymore. We highlight how the current flight density of the Air Transportation system is well below the transition, provided that controllers make use of a special re-routing procedure. While the congestion transition displays a universal scaling behavior, its threshold depends on the conflict solving strategy adopted. Finally, the generality of the modeling scheme introduced makes it a flexible general tool to simulate and control Air Transportation systems in realistic and synthetic scenarios.

An improved sampling method of complex network

NASA Astrophysics Data System (ADS)

Gao, Qi; Ding, Xintong; Pan, Feng; Li, Weixing

2014-12-01

Sampling subnet is an important topic of complex network research. Sampling methods influence the structure and characteristics of subnet. Random multiple snowball with Cohen (RMSC) process sampling which combines the advantages of random sampling and snowball sampling is proposed in this paper. It has the ability to explore global information and discover the local structure at the same time. The experiments indicate that this novel sampling method could keep the similarity between sampling subnet and original network on degree distribution, connectivity rate and average shortest path. This method is applicable to the situation where the prior knowledge about degree distribution of original network is not sufficient.

Double-layer Tedlar bags: a means to limit humidity evolution of air samples and to dry humid air samples.

PubMed

Cariou, Stephane; Guillot, Jean-Michel

2006-01-01

Tedlar bags, which are widely used to collect air samples, especially VOCs and odorous atmospheres, can allow humidity to diffuse when relative humidity levels differ between the inside and outside. Starting with dry air inside the bag and humid air outside, we monitored equilibrium times under several conditions showing the evolution and influence of collected volumes and exposed surfaces. A double-film Tedlar bag was made, to limit the impact of external humidity on a sample at low humidity level. With the addition of a drying agent between both films, the evolution of humidity of a sample can be stopped for several hours. When a VOC mixture was monitored in a humid atmosphere, humidity was decreased but no significant evolution of VOC concentrations was observed.

A Framework for Dimensioning VDL-2 Air-Ground Networks

NASA Technical Reports Server (NTRS)

Ribeiro, Leila Z.; Monticone, Leone C.; Snow, Richard E.; Box, Frank; Apaza, Rafel; Bretmersky, Steven

2014-01-01

This paper describes a framework developed at MITRE for dimensioning a Very High Frequency (VHF) Digital Link Mode 2 (VDL-2) Air-to-Ground network. This framework was developed to support the FAA's Data Communications (Data Comm) program by providing estimates of expected capacity required for the air-ground network services that will support Controller-Pilot-Data-Link Communications (CPDLC), as well as the spectrum needed to operate the system at required levels of performance. The Data Comm program is part of the FAA's NextGen initiative to implement advanced communication capabilities in the National Airspace System (NAS). The first component of the framework is the radio-frequency (RF) coverage design for the network ground stations. Then we proceed to describe the approach used to assess the aircraft geographical distribution and the data traffic demand expected in the network. The next step is the resource allocation utilizing optimization algorithms developed in MITRE's Spectrum ProspectorTM tool to propose frequency assignment solutions, and a NASA-developed VDL-2 tool to perform simulations and determine whether a proposed plan meets the desired performance requirements. The framework presented is capable of providing quantitative estimates of multiple variables related to the air-ground network, in order to satisfy established coverage, capacity and latency performance requirements. Outputs include: coverage provided at different altitudes; data capacity required in the network, aggregated or on a per ground station basis; spectrum (pool of frequencies) needed for the system to meet a target performance; optimized frequency plan for a given scenario; expected performance given spectrum available; and, estimates of throughput distributions for a given scenario. We conclude with a discussion aimed at providing insight into the tradeoffs and challenges identified with respect to radio resource management for VDL-2 air-ground networks.

Development and Application of a Next Generation Air Sensor Network for the Hong Kong Marathon 2015 Air Quality Monitoring.

PubMed

Sun, Li; Wong, Ka Chun; Wei, Peng; Ye, Sheng; Huang, Hao; Yang, Fenhuan; Westerdahl, Dane; Louie, Peter K K; Luk, Connie W Y; Ning, Zhi

2016-02-05

This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO2) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring.

Overview of the new National Near-Road Air Quality Monitoring Network

EPA Science Inventory

In 2010, EPA promulgated new National Ambient Air Quality Standards (NAAQS) for nitrogen dioxide (NO2). As part of this new NAAQS, EPA required the establishment of a national near-road air quality monitoring network. This network will consist of one NO2 near-road monitoring st...

Outlier Detection in Urban Air Quality Sensor Networks.

PubMed

van Zoest, V M; Stein, A; Hoek, G

2018-01-01

Low-cost urban air quality sensor networks are increasingly used to study the spatio-temporal variability in air pollutant concentrations. Recently installed low-cost urban sensors, however, are more prone to result in erroneous data than conventional monitors, e.g., leading to outliers. Commonly applied outlier detection methods are unsuitable for air pollutant measurements that have large spatial and temporal variations as occur in urban areas. We present a novel outlier detection method based upon a spatio-temporal classification, focusing on hourly NO 2 concentrations. We divide a full year's observations into 16 spatio-temporal classes, reflecting urban background vs. urban traffic stations, weekdays vs. weekends, and four periods per day. For each spatio-temporal class, we detect outliers using the mean and standard deviation of the normal distribution underlying the truncated normal distribution of the NO 2 observations. Applying this method to a low-cost air quality sensor network in the city of Eindhoven, the Netherlands, we found 0.1-0.5% of outliers. Outliers could reflect measurement errors or unusual high air pollution events. Additional evaluation using expert knowledge is needed to decide on treatment of the identified outliers. We conclude that our method is able to detect outliers while maintaining the spatio-temporal variability of air pollutant concentrations in urban areas.

Novel Method for Detection of Air Pollution using Cellular Communication Networks

NASA Astrophysics Data System (ADS)

David, N.; Gao, O. H.

2016-12-01

Air pollution can lead to a wide spectrum of severe and chronic health impacts. Conventional tools for monitoring the phenomenon do not provide a sufficient monitoring solution in a global scale since they are, for example, not representative of the larger space or due to limited deployment as a result of practical limitations, such as: acquisition, installation, and ongoing maintenance costs. Near ground temperature inversions are directly identified with air pollution events since they suppress vertical atmospheric movement and trap pollutants near the ground. Wireless telecommunication links that comprise the data transfer infrastructure in cellular communication networks operate at frequencies of tens of GHz and are affected by different atmospheric phenomena. These systems are deployed near ground level across the globe, including in developing countries such as India, countries in Africa, etc. Many cellular providers routinely store data regarding the received signal levels in the network for quality assurance needs. Temperature inversions cause atmospheric layering, and change the refractive index of the air when compared to standard conditions. As a result, the ducts that are formed can operate, in essence, as atmospheric wave guides, and cause interference (signal amplification / attenuation) in the microwaves measured by the wireless network. Thus, this network is in effect, an existing system of environmental sensors for monitoring temperature inversions and the episodes of air pollution identified with them. This work presents the novel idea, and demonstrates it, in operation, over several events of air pollution which were detected by a standard cellular communication network during routine operation. Reference: David, N. and Gao, H.O. Using cellular communication networks to detect air pollution, Environmental Science & Technology, 2016 (accepted).

Development and Application of a Next Generation Air Sensor Network for the Hong Kong Marathon 2015 Air Quality Monitoring

PubMed Central

Sun, Li; Wong, Ka Chun; Wei, Peng; Ye, Sheng; Huang, Hao; Yang, Fenhuan; Westerdahl, Dane; Louie, Peter K.K.; Luk, Connie W.Y.; Ning, Zhi

2016-01-01

This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO2) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring. PMID:26861336

Using neural networks for prediction of air pollution index in industrial city

NASA Astrophysics Data System (ADS)

Rahman, P. A.; Panchenko, A. A.; Safarov, A. M.

2017-10-01

This scientific paper is dedicated to the use of artificial neural networks for the ecological prediction of state of the atmospheric air of an industrial city for capability of the operative environmental decisions. In the paper, there is also the described development of two types of prediction models for determining of the air pollution index on the basis of neural networks: a temporal (short-term forecast of the pollutants content in the air for the nearest days) and a spatial (forecast of atmospheric pollution index in any point of city). The stages of development of the neural network models are briefly overviewed and description of their parameters is also given. The assessment of the adequacy of the prediction models, based on the calculation of the correlation coefficient between the output and reference data, is also provided. Moreover, due to the complexity of perception of the «neural network code» of the offered models by the ordinary users, the software implementations allowing practical usage of neural network models are also offered. It is established that the obtained neural network models provide sufficient reliable forecast, which means that they are an effective tool for analyzing and predicting the behavior of dynamics of the air pollution in an industrial city. Thus, this scientific work successfully develops the urgent matter of forecasting of the atmospheric air pollution index in industrial cities based on the use of neural network models.

Quantitative Assessment of Detection Frequency for the INL Ambient Air Monitoring Network

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

Sondrup, A. Jeffrey; Rood, Arthur S.

National Emission Standards for Hazardous Air Pollutants maximum exposed individual location (i.e., Frenchman’s Cabin) was no more than 0.1 mrem yr–1 (i.e., 1% of the 10 mrem yr–1 standard). Detection frequencies were calculated separately for the onsite and offsite monitoring network. As expected, detection frequencies were generally less for the offsite sampling network compared to the onsite network. Overall, the monitoring network is very effective at detecting the potential releases of Cs-137 or Sr-90 from all sources/facilities using either the ESER or BEA MDAs. The network was less effective at detecting releases of Pu-239. Maximum detection frequencies for Pu-239 using ESER MDAs ranged from 27.4 to 100% for onsite samplers and 3 to 80% for offsite samplers. Using BEA MDAs, the maximum detection frequencies for Pu-239 ranged from 2.1 to 100% for onsite samplers and 0 to 5.9% for offsite samplers. The only release that was not detected by any of the samplers under any conditions was a release of Pu-239 from the Idaho Nuclear Technology and Engineering Center main stack (CPP-708). The methodology described in this report could be used to improve sampler placement and detection frequency, provided clear performance objectives are defined.« less

Scale-Free Networks and Commercial Air Carrier Transportation in the United States

NASA Technical Reports Server (NTRS)

Conway, Sheila R.

2004-01-01

Network science, or the art of describing system structure, may be useful for the analysis and control of large, complex systems. For example, networks exhibiting scale-free structure have been found to be particularly well suited to deal with environmental uncertainty and large demand growth. The National Airspace System may be, at least in part, a scalable network. In fact, the hub-and-spoke structure of the commercial segment of the NAS is an often-cited example of an existing scale-free network After reviewing the nature and attributes of scale-free networks, this assertion is put to the test: is commercial air carrier transportation in the United States well explained by this model? If so, are the positive attributes of these networks, e.g. those of efficiency, flexibility and robustness, fully realized, or could we effect substantial improvement? This paper first outlines attributes of various network types, then looks more closely at the common carrier air transportation network from perspectives of the traveler, the airlines, and Air Traffic Control (ATC). Network models are applied within each paradigm, including discussion of implied strengths and weaknesses of each model. Finally, known limitations of scalable networks are discussed. With an eye towards NAS operations, utilizing the strengths and avoiding the weaknesses of scale-free networks are addressed.

3D Air Quality and the Clean Air Interstate Rule: Lagrangian Sampling of CMAQ Model Results to Aid Regional Accountability Metrics

NASA Technical Reports Server (NTRS)

Fairlie, T. D.; Szykman, Jim; Pierce, Robert B.; Gilliland, A. B.; Engel-Cox, Jill; Weber, Stephanie; Kittaka, Chieko; Al-Saadi, Jassim A.; Scheffe, Rich; Dimmick, Fred;

Presence of organophosphorus pesticide oxygen analogs in air samples

NASA Astrophysics Data System (ADS)

Armstrong, Jenna L.; Fenske, Richard A.; Yost, Michael G.; Galvin, Kit; Tchong-French, Maria; Yu, Jianbo

2013-02-01

A number of recent toxicity studies have highlighted the increased potency of oxygen analogs (oxons) of several organophosphorus (OP) pesticides. These findings were a major concern after environmental oxons were identified in environmental samples from air and surfaces following agricultural spray applications in California and Washington State. This paper reports on the validity of oxygen analog measurements in air samples for the OP pesticide, chlorpyrifos. Controlled environmental and laboratory experiments were used to examine artificial formation of chlorpyrifos-oxon using OSHA Versatile Sampling (OVS) tubes as recommended by NIOSH method 5600. Additionally, we compared expected chlorpyrifos-oxon attributable to artificial transformation to observed chlorpyrifos-oxon in field samples from a 2008 Washington State Department of Health air monitoring study using non-parametric statistical methods. The amount of artificially transformed oxon was then modeled to determine the amount of oxon present in the environment. Toxicity equivalency factors (TEFs) for chlorpyrifos-oxon were used to calculate chlorpyrifos-equivalent air concentrations. The results demonstrate that the NIOSH-recommended sampling matrix (OVS tubes with XAD-2 resin) was found to artificially transform up to 30% of chlorpyrifos to chlorpyrifos-oxon, with higher percentages at lower concentrations (<30 ng m-3) typical of ambient or residential levels. Overall, the 2008 study data had significantly greater oxon than expected by artificial transformation, but the exact amount of environmental oxon in air remains difficult to quantify with the current sampling method. Failure to conduct laboratory analysis for chlorpyrifos-oxon may result in underestimation of total pesticide concentration when using XAD-2 resin matrices for occupational or residential sampling. Alternative methods that can accurately measure both OP pesticides and their oxygen analogs should be used for air sampling, and a toxicity

Analysis of EPA and DOE WIPP Air Sampling Data

EPA Pesticide Factsheets

During the April 2014 EPA visit to WIPP, EPA co-located four ambient air samplers with existing Department of Energy (DOE) ambient air samplers to independently corroborate DOE's reported air sampling results.

Hyper-Spectral Networking Concept of Operations and Future Air Traffic Management Simulations

NASA Technical Reports Server (NTRS)

Davis, Paul; Boisvert, Benjamin

2017-01-01

The NASA sponsored Hyper-Spectral Communications and Networking for Air Traffic Management (ATM) (HSCNA) project is conducting research to improve the operational efficiency of the future National Airspace System (NAS) through diverse and secure multi-band, multi-mode, and millimeter-wave (mmWave) wireless links. Worldwide growth of air transportation and the coming of unmanned aircraft systems (UAS) will increase air traffic density and complexity. Safe coordination of aircraft will require more capable technologies for communications, navigation, and surveillance (CNS). The HSCNA project will provide a foundation for technology and operational concepts to accommodate a significantly greater number of networked aircraft. This paper describes two of the HSCNA projects technical challenges. The first technical challenge is to develop a multi-band networking concept of operations (ConOps) for use in multiple phases of flight and all communication link types. This ConOps will integrate the advanced technologies explored by the HSCNA project and future operational concepts into a harmonized vision of future NAS communications and networking. The second technical challenge discussed is to conduct simulations of future ATM operations using multi-bandmulti-mode networking and technologies. Large-scale simulations will assess the impact, compared to todays system, of the new and integrated networks and technologies under future air traffic demand.

[Microbial air monitoring in operating theatre: active and passive samplings].

PubMed

Pasquarella, C; Masia, M D; Nnanga, Nga; Sansebastiano, G E; Savino, A; Signorelli, C; Veronesi, L

2004-01-01

Microbial air contamination was evaluated in 11 operating theatres using active and passive samplings. SAS (Surface Air System) air sampling was used to evaluate cfu/m3 and settle plates were used to measure the index of microbial air contamination (IMA). Samplings were performed at the same time on three different days, at three different times (before, during and after the surgical activity). Two points were monitored (patient area and perimeter of the operating theatre). Moreover, the cfu/m3 were evaluated at the air inlet of the conditioner system. 74.7% of samplings performed at the air inlet and 66.7% of the samplings performed at the patient area before the beginning of the surgical activity (at rest) exceeded the 35 cfu/m3 used as threshold value. 100% of IMA values exceeded the threshold value of 5. Using both active and passive sampling, the microbial contamination was shown to increase significantly during activity. The cfu values were higher at the patient area than at the perimeter of the operating theatre. Mean values of the cfu/m3 during activity at the patient area ranged from a minimum of 61+/-41 cfu/m3 to a maximum of 242+/-136 cfu/m3; IMA values ranged from a minimum of 19+/-10 to a maximum of 129+/-60. 15.2% of samplings performed at the patient area using SAS and 75.8% of samplings performed using settle plates exceeded the threshold values of 180 cfu/m3 and 25 respectively, with a significant difference of the percentages. The highest values were found in the operating theatre with inadequate structural and managerial conditions. These findings confirm that the microbiological quality of air may be considered a mirror of the hygienic conditions of the operating theatre. Settle plates proved to be more sensitive in detecting the increase of microbial air contamination related to conditions that could compromise the quality of the air in operating theatres.

A simple novel device for air sampling by electrokinetic capture.

PubMed

Gordon, Julian; Gandhi, Prasanthi; Shekhawat, Gajendra; Frazier, Angel; Hampton-Marcell, Jarrad; Gilbert, Jack A

2015-12-27

A variety of different sampling devices are currently available to acquire air samples for the study of the microbiome of the air. All have a degree of technical complexity that limits deployment. Here, we evaluate the use of a novel device, which has no technical complexity and is easily deployable. An air-cleaning device powered by electrokinetic propulsion has been adapted to provide a universal method for collecting samples of the aerobiome. Plasma-induced charge in aerosol particles causes propulsion to and capture on a counter-electrode. The flow of ions creates net bulk airflow, with no moving parts. A device and electrode assembly have been re-designed from air-cleaning technology to provide an average air flow of 120 lpm. This compares favorably with current air sampling devices based on physical air pumping. Capture efficiency was determined by comparison with a 0.4 μm polycarbonate reference filter, using fluorescent latex particles in a controlled environment chamber. Performance was compared with the same reference filter method in field studies in three different environments. For 23 common fungal species by quantitative polymerase chain reaction (qPCR), there was 100 % sensitivity and apparent specificity of 87 %, with the reference filter taken as "gold standard." Further, bacterial analysis of 16S RNA by amplicon sequencing showed equivalent community structure captured by the electrokinetic device and the reference filter. Unlike other current air sampling methods, capture of particles is determined by charge and so is not controlled by particle mass. We analyzed particle sizes captured from air, without regard to specific analyte by atomic force microscopy: particles at least as low as 100 nM could be captured from ambient air. This work introduces a very simple plug-and-play device that can sample air at a high-volume flow rate with no moving parts and collect particles down to the sub-micron range. The performance of the device is

Uncertainties in monitoring of SVOCs in air caused by within-sampler degradation during active and passive air sampling

NASA Astrophysics Data System (ADS)

Melymuk, Lisa; Bohlin-Nizzetto, Pernilla; Prokeš, Roman; Kukučka, Petr; Přibylová, Petra; Vojta, Šimon; Kohoutek, Jiří; Lammel, Gerhard; Klánová, Jana

2017-10-01

Degradation of semivolatile organic compounds (SVOCs) occurs naturally in ambient air due to reactions with reactive trace gases (e.g., ozone, NOx). During air sampling there is also the possibility for degradation of SVOCs within the air sampler, leading to underestimates of ambient air concentrations. We investigated the possibility of this sampling artifact in commonly used active and passive air samplers for seven classes of SVOCs, including persistent organic pollutants (POPs) typically covered by air monitoring programs, as well as SVOCs of emerging concern. Two active air samplers were used, one equipped with an ozone denuder and one without, to compare relative differences in mass of collected compounds. Two sets of passive samplers were also deployed to determine the influence of degradation during longer deployment times in passive sampling. In active air samplers, comparison of the two sampling configurations suggested degradation of particle-bound polycyclic aromatic hydrocarbons (PAHs), with concentrations up to 2× higher in the denuder-equipped sampler, while halogenated POPs did not have clear evidence of degradation. In contrast, more polar, reactive compounds (e.g., organophosphate esters and current use pesticides) had evidence of losses in the sampler with denuder. This may be caused by the denuder itself, suggesting sampling bias for these compounds can be created when typical air sampling apparatuses are adapted to limit degradation. Passive air samplers recorded up to 4× higher concentrations when deployed for shorter consecutive sampling periods, suggesting that within-sampler degradation may also be relevant in passive air monitoring programs.

30 CFR 90.205 - Approved sampling devices; operation; air flowrate.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approved sampling devices; operation; air... LABOR COAL MINE SAFETY AND HEALTH MANDATORY HEALTH STANDARDS-COAL MINERS WHO HAVE EVIDENCE OF THE DEVELOPMENT OF PNEUMOCONIOSIS Sampling Procedures § 90.205 Approved sampling devices; operation; air flowrate...

Atmospheric CO2 Records from Sites in the Scripps Institution of Oceanography (SIO) Air Sampling Network (1985 - 2007)

DOE Data Explorer

Keeling, R. F. [Scripps Institution of Oceanography (SIO) University of California, La Jolla, California (USA); Piper, S. C. [Scripps Institution of Oceanography (SIO) University of California, La Jolla, California (USA); Bollenbacher, A. F. [Scripps Institution of Oceanography (SIO) University of California, La Jolla, California (USA); Walker , J. S. [Scripps Institution of Oceanography (SIO) University of California, La Jolla, California (USA)

2008-05-01

At Alert weekly air samples are collected in 5-L evacuated glass flasks exposed in triplicate. Flasks are returned to the SIO for CO2 determinations, which are made using an Applied Physics Corporation nondispersive infrared gas analyzer. In May 1983, the CO2-in-N2 calibration gases were replaced with CO2-in-air calibration gases, which are currently used (Keeling et al. 2002). Data are in terms of the Scripps "03A" calibration scale. On the basis of flask samples collected at Alert and analyzed by SIO, the annual average of the fitted monthly concentrations CO2 rose from 348.48 ppmv in 1986 to 384.84 ppmv in 2007. This represents an average annual growth rate of 1.73 ppmv per year at Alert.

Convair F-106B Delta Dart with Air Sampling Equipment

NASA Image and Video Library

1974-04-21

The National Aeronautics and Space Administration (NASA) Lewis Research Center’s Convair F-106B Delta Dart equipped with air sampling equipment in the mid-1970s. NASA Lewis created and managed the Global Air Sampling Program (GASP) in 1972 in partnership with several airline companies. NASA researchers used the airliners’ Boeing 747 aircraft to gather air samples to determine the amount of pollution present in the stratosphere. Private companies developed the air sampling equipment for the GASP program, and Lewis created a particle collector. The collector was flight tested on NASA Lewis’ F-106B in the summer of 1973. The sampling equipment was automatically operated once the proper altitude was achieved. The sampling instruments collected dust particles in the air so their chemical composition could be analyzed. The equipment analyzed one second’s worth of data at a time. The researchers also monitored carbon monoxide, monozide, ozone, and water vapor. The 747 flights began in December 1974 and soon included four airlines flying routes all over the globe. The F-106B augmented the airline data with sampling of its own, seen here. It gathered samples throughout this period from locations such as New Mexico, Texas, Michigan, and Ohio. In July 1977 the F-106B flew eight GASP flights in nine days over Alaska to supplement the earlier data gathered by the airlines.

Monitoring air quality in mountains: Designing an effective network

USGS Publications Warehouse

Peterson, D.L.

2000-01-01

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.

Systematic Evaluation of Aggressive Air Sampling for Bacillus ...

EPA Pesticide Factsheets

Report The primary objectives of this project were to evaluate the Aggressive Air Sampling (AAS) method compared to currently used surface sampling methods and to determine if AAS is a viable option for sampling Bacillus anthracis spores.

A simple novel device for air sampling by electrokinetic capture

DOE PAGES

Gordon, Julian; Gandhi, Prasanthi; Shekhawat, Gajendra; ...

2015-12-27

A variety of different sampling devices are currently available to acquire air samples for the study of the microbiome of the air. All have a degree of technical complexity that limits deployment. Here, we evaluate the use of a novel device, which has no technical complexity and is easily deployable. An air-cleaning device powered by electrokinetic propulsion has been adapted to provide a universal method for collecting samples of the aerobiome. Plasma-induced charge in aerosol particles causes propulsion to and capture on a counter-electrode. The flow of ions creates net bulk airflow, with no moving parts. A device and electrodemore » assembly have been re-designed from air-cleaning technology to provide an average air flow of 120 lpm. This compares favorably with current air sampling devices based on physical air pumping. Capture efficiency was determined by comparison with a 0.4 μm polycarbonate reference filter, using fluorescent latex particles in a controlled environment chamber. Performance was compared with the same reference filter method in field studies in three different environments. For 23 common fungal species by quantitative polymerase chain reaction (qPCR), there was 100 % sensitivity and apparent specificity of 87%, with the reference filter taken as “gold standard.” Further, bacterial analysis of 16S RNA by amplicon sequencing showed equivalent community structure captured by the electrokinetic device and the reference filter. Unlike other current air sampling methods, capture of particles is determined by charge and so is not controlled by particle mass. We analyzed particle sizes captured from air, without regard to specific analyte by atomic force microscopy: particles at least as low as 100 nM could be captured from ambient air. This work introduces a very simple plug-and-play device that can sample air at a high-volume flow rate with no moving parts and collect particles down to the sub-micron range. In conclusion, the performance of

A simple novel device for air sampling by electrokinetic capture

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

Gordon, Julian; Gandhi, Prasanthi; Shekhawat, Gajendra

A variety of different sampling devices are currently available to acquire air samples for the study of the microbiome of the air. All have a degree of technical complexity that limits deployment. Here, we evaluate the use of a novel device, which has no technical complexity and is easily deployable. An air-cleaning device powered by electrokinetic propulsion has been adapted to provide a universal method for collecting samples of the aerobiome. Plasma-induced charge in aerosol particles causes propulsion to and capture on a counter-electrode. The flow of ions creates net bulk airflow, with no moving parts. A device and electrodemore » assembly have been re-designed from air-cleaning technology to provide an average air flow of 120 lpm. This compares favorably with current air sampling devices based on physical air pumping. Capture efficiency was determined by comparison with a 0.4 μm polycarbonate reference filter, using fluorescent latex particles in a controlled environment chamber. Performance was compared with the same reference filter method in field studies in three different environments. For 23 common fungal species by quantitative polymerase chain reaction (qPCR), there was 100 % sensitivity and apparent specificity of 87%, with the reference filter taken as “gold standard.” Further, bacterial analysis of 16S RNA by amplicon sequencing showed equivalent community structure captured by the electrokinetic device and the reference filter. Unlike other current air sampling methods, capture of particles is determined by charge and so is not controlled by particle mass. We analyzed particle sizes captured from air, without regard to specific analyte by atomic force microscopy: particles at least as low as 100 nM could be captured from ambient air. This work introduces a very simple plug-and-play device that can sample air at a high-volume flow rate with no moving parts and collect particles down to the sub-micron range. In conclusion, the performance of

Enhanced data validation strategy of air quality monitoring network.

PubMed

Harkat, Mohamed-Faouzi; Mansouri, Majdi; Nounou, Mohamed; Nounou, Hazem

2018-01-01

Quick validation and detection of faults in measured air quality data is a crucial step towards achieving the objectives of air quality networks. Therefore, the objectives of this paper are threefold: (i) to develop a modeling technique that can be used to predict the normal behavior of air quality variables and help provide accurate reference for monitoring purposes; (ii) to develop fault detection method that can effectively and quickly detect any anomalies in measured air quality data. For this purpose, a new fault detection method that is based on the combination of generalized likelihood ratio test (GLRT) and exponentially weighted moving average (EWMA) will be developed. GLRT is a well-known statistical fault detection method that relies on maximizing the detection probability for a given false alarm rate. In this paper, we propose to develop GLRT-based EWMA fault detection method that will be able to detect the changes in the values of certain air quality variables; (iii) to develop fault isolation and identification method that allows defining the fault source(s) in order to properly apply appropriate corrective actions. In this paper, reconstruction approach that is based on Midpoint-Radii Principal Component Analysis (MRPCA) model will be developed to handle the types of data and models associated with air quality monitoring networks. All air quality modeling, fault detection, fault isolation and reconstruction methods developed in this paper will be validated using real air quality data (such as particulate matter, ozone, nitrogen and carbon oxides measurement). Copyright © 2017 Elsevier Inc. All rights reserved.

An online air pollution forecasting system using neural networks.

PubMed

Kurt, Atakan; Gulbagci, Betul; Karaca, Ferhat; Alagha, Omar

2008-07-01

In this work, an online air pollution forecasting system for Greater Istanbul Area is developed. The system predicts three air pollution indicator (SO(2), PM(10) and CO) levels for the next three days (+1, +2, and +3 days) using neural networks. AirPolTool, a user-friendly website (http://airpol.fatih.edu.tr), publishes +1, +2, and +3 days predictions of air pollutants updated twice a day. Experiments presented in this paper show that quite accurate predictions of air pollutant indicator levels are possible with a simple neural network. It is shown that further optimizations of the model can be achieved using different input parameters and different experimental setups. Firstly, +1, +2, and +3 days' pollution levels are predicted independently using same training data, then +2 and +3 days are predicted cumulatively using previously days predicted values. Better prediction results are obtained in the cumulative method. Secondly, the size of training data base used in the model is optimized. The best modeling performance with minimum error rate is achieved using 3-15 past days in the training data set. Finally, the effect of the day of week as an input parameter is investigated. Better forecasts with higher accuracy are observed using the day of week as an input parameter.

Function approximation and documentation of sampling data using artificial neural networks.

PubMed

Zhang, Wenjun; Barrion, Albert

2006-11-01

Biodiversity studies in ecology often begin with the fitting and documentation of sampling data. This study is conducted to make function approximation on sampling data and to document the sampling information using artificial neural network algorithms, based on the invertebrate data sampled in the irrigated rice field. Three types of sampling data, i.e., the curve species richness vs. the sample size, the curve rarefaction, and the curve mean abundance of newly sampled species vs.the sample size, are fitted and documented using BP (Backpropagation) network and RBF (Radial Basis Function) network. As the comparisons, The Arrhenius model, and rarefaction model, and power function are tested for their ability to fit these data. The results show that the BP network and RBF network fit the data better than these models with smaller errors. BP network and RBF network can fit non-linear functions (sampling data) with specified accuracy and don't require mathematical assumptions. In addition to the interpolation, BP network is used to extrapolate the functions and the asymptote of the sampling data can be drawn. BP network cost a longer time to train the network and the results are always less stable compared to the RBF network. RBF network require more neurons to fit functions and generally it may not be used to extrapolate the functions. The mathematical function for sampling data can be exactly fitted using artificial neural network algorithms by adjusting the desired accuracy and maximum iterations. The total numbers of functional species of invertebrates in the tropical irrigated rice field are extrapolated as 140 to 149 using trained BP network, which are similar to the observed richness.

Can car air filters be useful as a sampling medium for air pollution monitoring purposes?

PubMed

Katsoyiannis, Athanasios; Birgul, Askin; Ratola, Nuno; Cincinelli, Alessandra; Sweetman, Andy J; Jones, Kevin C

2012-11-01

Urban air quality and real human exposure to chemical environmental stressors is an issue of high scientific and political interest. In an effort to find innovative and inexpensive means for air quality monitoring, the ability of car engine air filters (CAFs) to act as efficient samplers collecting street level air, to which people are exposed to, was tested. In particular, in the case of taxis, air filters are replaced after regular distances, the itineraries are almost exclusively urban, cruising mode is similar and, thus, knowledge of the air flow can provide with an integrated city air sample. The present pilot study focused on polycyclic aromatic hydrocarbons (PAHs), the most important category of organic pollutants associated with traffic emissions. Concentrations of ΣPAHs in CAFs ranged between 650 and 2900 μg CAF(-1), with benzo[b]fluoranthene, benzo[k]fluoranthene and indeno[123-cd]pyrene being the most abundant PAHs. Benzo[a]pyrene (BaP) ranged between 110 and 250 μg CAF(-1), accounting regularly for 5-15% of the total carcinogenic PAHs. The CAF PAH loads were used to derive road-level atmospheric PAH concentrations from a standard formula relating to the CAF air flow. Important parameters/assumptions for these estimates are the cruising speed and the exposure duration of each CAF. Based on information obtained from the garage experts, an average 'sampled air volume' of 48,750 m(3) per CAF was estimated, with uncertainty in this calculation estimated to be about a factor of 4 between the two extreme scenarios. Based on this air volume, ΣPAHs ranged between 13 and 56 ng m(-3) and BaP between 2.1 and 5.0 ng m(-3), suggesting that in-traffic BaP concentrations can be many times higher than the limit values set by the UK (0.25 ng m(-3)) and the European Union (1.0 ng m(-3)), or from active sampling stations normally cited on building roof tops or far from city centres. Notwithstanding the limitations of this approach, the very low cost, the continuous

Air Sample Conditioner Helps the Waste Treatment Plant Meet Emissions Standards

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

Glissmeyer, John A.; Flaherty, Julia E.; Pekour, Mikhail S.

2014-12-02

The air in three of the Hanford Site Waste Treatment and Immobilization Plant (WTP) melter off-gas discharge stacks will be hot and humid after passing through the train of emission abatement equipment. The off-gas temperature and humidity levels will be incompatible with the airborne emissions monitoring equipment required for this type of stack. To facilitate sampling from these facilities, an air sample conditioner system will be installed to introduce cool, dry air into the sample stream to reduce the temperature and dew point. This will avoid thermal damage to the instrumentation and problematic condensation. The complete sample transport system mustmore » also deliver at least 50% of the particles in the sample airstream to the sample collection and on-line analysis equipment. The primary components of the sample conditioning system were tested in a laboratory setting. The sample conditioner itself is based on a commercially-available porous tube filter design. It consists of a porous sintered metal tube inside a coaxial metal jacket. The hot gas sample stream passes axially through the porous tube, and the dry, cool air is injected into the jacket and through the porous wall of the inner tube, creating an effective sample diluter. The dilution and sample air mix along the entire length of the porous tube, thereby simultaneously reducing the dew point and temperature of the mixed sample stream. Furthermore, because the dilution air enters through the porous tube wall, the sample stream does not come in contact with the porous wall and particle deposition is reduced in this part of the sampling system. Tests were performed with an environmental chamber to supply air with the temperature and humidity needed to simulate the off-gas conditions. Air from the chamber was passed through the conditioning system to test its ability to reduce the temperature and dew point of the sample stream. To measure particle deposition, oil droplets in the range of 9 to 11

AEROCAN, the Canadian sub-network of AERONET: Aerosol monitoring and air quality applications

NASA Astrophysics Data System (ADS)

Sioris, Christopher E.; Abboud, Ihab; Fioletov, Vitali E.; McLinden, Chris A.

2017-10-01

Previous studies have demonstrated the utility of AERONET (Aerosol Robotic Network) aerosol optical depth (AOD) data for monitoring the spatial variability of particulate matter (PM) in relatively polluted regions of the globe. AEROCAN, a Canadian sub-network of AERONET, was established 20 years ago and currently consists of twenty sites across the country. In this study, we examine whether the AEROCAN sunphotometer data provide evidence of anthropogenic contributions to ambient particulate matter concentrations in relatively clean Canadian locations. The similar weekly cycle of AOD and PM2.5 over Toronto provides insight into the impact of local pollution on observed AODs. High temporal correlations (up to r = 0.78) between daily mean AOD (or its fine-mode component) and PM2.5 are found at southern Ontario AEROCAN sites during May-August, implying that the variability in the aerosol load resides primarily in the boundary layer and that sunphotometers capture day-to-day PM2.5 variations at moderately polluted sites. The sensitivity of AEROCAN AOD data to anthropogenic surface-level aerosol enhancements is demonstrated using boundary-layer wind information for sites near sources of aerosol or its precursors. An advantage of AEROCAN relative to the Canadian in-situ National Air Pollution Surveillance (NAPS) network is the ability to detect free tropospheric aerosol enhancements, which can be large in the case of lofted forest fire smoke or desert dust. These aerosol plumes eventually descend to the surface, sometimes in populated areas, exacerbating air quality. In cases of large AOD (≥0.4), AEROCAN data are also useful in characterizing the aerosol type. The AEROCAN network includes three sites in the high Arctic, a region not sampled by the NAPS PM2.5 monitoring network. These polar sites show the importance of long-range transport and meteorology in the Arctic haze phenomenon. Also, AEROCAN sunphotometers are, by design and due to regular maintenance, the most

A new device for dynamic sampling of radon in air

NASA Astrophysics Data System (ADS)

Lozano, J. C.; Escobar, V. Gómez; Tomé, F. Vera

2000-08-01

A new system is proposed for the active sampling of radon in air, based on the well-known property of activated charcoal to retain radon. Two identical carbon-activated cartridges arranged in series remove the radon from the air being sampled. The air passes first through a desiccant cell and then the carbon cartridges for short sampling times using a low-flow pump. The alpha activity for each cartridge is determined by a liquid scintillation counting system. The cartridge is placed in a holder into a vial that also contains the appropriate amount of scintillation cocktail, in a way that avoids direct contact between cocktail and charcoal. Once dynamic equilibrium between the phases has been reached, the vials can be counted. Optimum sampling conditions concerning flow rates and sampling times are determined. Using those conditions, the method was applied to environmental samples, straightforwardly providing good results for very different levels of activity.

Air bubbles and hemolysis of blood samples during transport by pneumatic tube systems.

PubMed

Mullins, Garrett R; Bruns, David E

2017-10-01

Transport of blood samples through pneumatic tube systems (PTSs) generates air bubbles in transported blood samples and, with increasing duration of transport, the appearance of hemolysis. We investigated the role of air-bubble formation in PTS-induced hemolysis. Air was introduced into blood samples for 0, 1, 3 or 5min to form air bubbles. Hemolysis in the blood was assessed by (H)-index, lactate dehydrogenase (LD) and potassium in plasma. In an effort to prevent PTS-induced hemolysis, blood sample tubes were completely filled, to prevent air bubble formation, and compared with partially filled samples after PTS transport. We also compared hemolysis in anticoagulated vs clotted blood subjected to PTS transport. As with transport through PTSs, the duration of air bubble formation in blood by a gentle stream of air predicted the extent of hemolysis as measured by H-index (p<0.01), LD (p<0.01), and potassium (p<0.02) in plasma. Removing air space in a blood sample prevented bubble formation and fully protected the blood from PTS-induced hemolysis (p<0.02 vs conventionally filled collection tube). Clotted blood developed less foaming during PTS transport and was partially protected from hemolysis vs anticoagulated blood as indicated by lower LD (p<0.03) in serum than in plasma after PTS sample transport. Prevention of air bubble formation in blood samples during PTS transport protects samples from hemolysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Network Theory: A Primer and Questions for Air Transportation Systems Applications

NASA Technical Reports Server (NTRS)

Holmes, Bruce J.

2004-01-01

A new understanding (with potential applications to air transportation systems) has emerged in the past five years in the scientific field of networks. This development emerges in large part because we now have a new laboratory for developing theories about complex networks: The Internet. The premise of this new understanding is that most complex networks of interest, both of nature and of human contrivance, exhibit a fundamentally different behavior than thought for over two hundred years under classical graph theory. Classical theory held that networks exhibited random behavior, characterized by normal, (e.g., Gaussian or Poisson) degree distributions of the connectivity between nodes by links. The new understanding turns this idea on its head: networks of interest exhibit scale-free (or small world) degree distributions of connectivity, characterized by power law distributions. The implications of scale-free behavior for air transportation systems include the potential that some behaviors of complex system architectures might be analyzed through relatively simple approximations of local elements of the system. For air transportation applications, this presentation proposes a framework for constructing topologies (architectures) that represent the relationships between mobility, flight operations, aircraft requirements, and airspace capacity, and the related externalities in airspace procedures and architectures. The proposed architectures or topologies may serve as a framework for posing comparative and combinative analyses of performance, cost, security, environmental, and related metrics.

Measurements of CO2 Mole Fractionand δ13C in Archived Air Samples from Cape Meares, Oregon (USA) 1977 - 1998

NASA Astrophysics Data System (ADS)

Clark, O.; Rice, A. L.

2017-12-01

Carbon dioxide (CO2) is the most abundant, anthropogenically forced greenhouse gas (GHG) in the global atmosphere. Emissions of CO2 account for approximately 75% of the world's total GHG emissions. Atmospheric concentrations of CO2 are higher now than they've been at any other time in the past 800,000 years. Currently, the global mean concentration exceeds 400 ppm. Today, global networks regularly monitor CO2 concentrations and isotopic composition (δ13C and δ18O). However, past data is sparse. Over 200 ambient air samples from Cape Meares, Oregon (45.5°N, 124.0°W), a coastal site in Western United States, were obtained by researchers at Oregon Institute of Science and Technology (OGI, now Oregon Health & Science University), between the years of 1977 and 1998 as part of a global monitoring program of six different sites in the polar, middle, and tropical latitudes of the Northern and Southern Hemispheres. Air liquefaction was used to compress approximately 1000L of air (STP) to 30bar, into 33L electropolished (SUMMA) stainless steel canisters. Select archived air samples from the original network are maintained at Portland State University (PSU) Department of Physics. These archived samples are a valuable look at changing atmospheric concentrations of CO2 and δ13C, which can contribute to a better understanding of changes in sources during this time. CO2 concentrations and δ13C of CO2 were measured at PSU, with a Picarro Cavity Ringdown Spectrometer, model G1101-i analytical system. This study presents the analytical methods used, calibration techniques, precision, and reproducibility. Measurements of select samples from the archive show rising CO2 concentrations and falling δ13C over the 1977 to 1998 period, compatible with previous observations and rising anthropogenic sources of CO2. The resulting data set was statistically analyzed in MATLAB. Results of preliminary seasonal and secular trends from the archive samples are presented.

Sample size and power considerations in network meta-analysis

PubMed Central

2012-01-01

Background Network meta-analysis is becoming increasingly popular for establishing comparative effectiveness among multiple interventions for the same disease. Network meta-analysis inherits all methodological challenges of standard pairwise meta-analysis, but with increased complexity due to the multitude of intervention comparisons. One issue that is now widely recognized in pairwise meta-analysis is the issue of sample size and statistical power. This issue, however, has so far only received little attention in network meta-analysis. To date, no approaches have been proposed for evaluating the adequacy of the sample size, and thus power, in a treatment network. Findings In this article, we develop easy-to-use flexible methods for estimating the ‘effective sample size’ in indirect comparison meta-analysis and network meta-analysis. The effective sample size for a particular treatment comparison can be interpreted as the number of patients in a pairwise meta-analysis that would provide the same degree and strength of evidence as that which is provided in the indirect comparison or network meta-analysis. We further develop methods for retrospectively estimating the statistical power for each comparison in a network meta-analysis. We illustrate the performance of the proposed methods for estimating effective sample size and statistical power using data from a network meta-analysis on interventions for smoking cessation including over 100 trials. Conclusion The proposed methods are easy to use and will be of high value to regulatory agencies and decision makers who must assess the strength of the evidence supporting comparative effectiveness estimates. PMID:22992327

Comparison of stationary and personal air sampling with an ...

EPA Pesticide Factsheets

Manganese (Mn) is ubiquitous in the environment and essential for normal growth and development, yet excessive exposure can lead to impairments in neurological function. This study modeled ambient Mn concentrations as an alternative to stationary and personal air sampling to assess exposure for children enrolled in the Communities Actively Researching Exposure Study in Marietta, OH. Ambient air Mn concentration values were modeled using US Environmental Protection Agency’s Air Dispersion Model AERMOD based on emissions from the ferromanganese refinery located in Marietta. Modeled Mn concentrations were compared with Mn concentrations from a nearby stationary air monitor. The Index of Agreement for modeled versus monitored data was 0.34 (48 h levels) and 0.79 (monthly levels). Fractional bias was 0.026 for 48 h levels and −0.019 for monthly levels. The ratio of modeled ambient air Mn to measured ambient air Mn at the annual time scale was 0.94. Modeled values were also time matched to personal air samples for 19 children. The modeled values explained a greater degree of variability in personal exposures compared with time-weighted distance from the emission source. Based on these results modeled Mn concentrations provided a suitable approach for assessing airborne Mn exposure in this cohort. The purpose of the study was to investigate the use of air-dispersion modeling as an approach to exposure assessment for ambient manganese.

EPA's National Dioxin Air Monitoring Network (NDAMN): Design, implementation, and final results

NASA Astrophysics Data System (ADS)

Lorber, Matthew; Ferrario, Joseph; Byrne, Christian

2013-10-01

The U.S. Environmental Protection Agency (U.S. EPA) established the National Dioxin Air Monitoring Network (NDAMN) in June of 1998, and operated it until November of 2004. The objective of NDAMN was to determine background air concentrations of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (dl-PCBs). NDAMN started with 10 sampling sites, adding more over time until the final count of 34 sites was reached by the beginning of 2003. Samples were taken quarterly, and the final sample count was 685. All samples were measured for 17 PCDD/PCDF congeners, 8 PCDD/PCDF homologue groups, and 7 dl-PCBs (note: 5 additional dl-PCBs were added for samples starting in the summer of 2002; 317 samples had measurements of 12 dl-PCBs). The overall average total toxic equivalent (TEQ) concentration in the United States was 11.2 fg TEQ m-3 with dl-PCBs contributing 0.8 fg TEQ m-3 (7%) to this total. The archetype dioxin and furan background air congener profile was seen in the survey averages and in most individual samples. This archetype profile is characterized by low and similar concentrations for tetra - through hexa PCDD/PCDF congeners, with elevations in four congeners - a hepta dioxin and furan congener, and both octa congeners. Sites were generally categorized as urban (4 sites), rural (23 sites), or remote (7 sites). The average TEQ concentrations over all sites and samples within these categories were: urban = 15.9 fg TEQ m-3, rural = 13.9 fg TEQ m-3, and remote = 1.2 fg TEQ m-3. Rural sites showed elevations during the fall or winter months when compared to the spring or summer months, and the same might be said for urban sites, but the remote sites appear to show little variation over time. The four highest individual moment measurements were 847, 292, 241, and 132 fg TEQ m-3. For the 847 and 292 fg TEQ m-3 samples, the concentrations of all congeners were elevated over their site averages, but for

APPLICATION OF SEMIPERMEABLE MEMBRANE DEVICES TO INDOOR AIR SAMPLING

EPA Science Inventory

Semipermeable membrane devices (SPMDs) are a relatively new passive sampling technique for nonpolar organic compounds that have been extensively used for surface water sampling. A small body of literature indicates that SPMDs are also useful for air sampling. Because SPMDs ha...

Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models.

PubMed

Adams, Matthew D; Kanaroglou, Pavlos S

2016-03-01

Air pollution poses health concerns at the global scale. The challenge of managing air pollution is significant because of the many air pollutants, insufficient funds for monitoring and abatement programs, and political and social challenges in defining policy to limit emissions. Some governments provide citizens with air pollution health risk information to allow them to limit their exposure. However, many regions still have insufficient air pollution monitoring networks to provide real-time mapping. Where available, these risk mapping systems either provide absolute concentration data or the concentrations are used to derive an Air Quality Index, which provides the air pollution risk for a mix of air pollutants with a single value. When risk information is presented as a single value for an entire region it does not inform on the spatial variation within the region. Without an understanding of the local variation residents can only make a partially informed decision when choosing daily activities. The single value is typically provided because of a limited number of active monitoring units in the area. In our work, we overcome this issue by leveraging mobile air pollution monitoring techniques, meteorological information and land use information to map real-time air pollution health risks. We propose an approach that can provide improved health risk information to the public by applying neural network models within a framework that is inspired by land use regression. Mobile air pollution monitoring campaigns were conducted across Hamilton from 2005 to 2013. These mobile air pollution data were modelled with a number of predictor variables that included information on the surrounding land use characteristics, the meteorological conditions, air pollution concentrations from fixed location monitors, and traffic information during the time of collection. Fine particulate matter and nitrogen dioxide were both modelled. During the model fitting process we reserved

Constructing a generalized network design model to study air distribution in ventilation networks in subway with a single-track tunnel

NASA Astrophysics Data System (ADS)

Lugin, IV

2018-03-01

In focus are the features of construction of the generalized design model for the network method to study air distribution in ventilation system in subway with the single-track tunnel. The generalizations, assumptions and simplifications included in the model are specified. The air distribution is calculated with regard to the influence of topology and air resistances of the ventilation network sections. The author studies two variants of the subway line: half-open and closed with dead end on the both sides. It is found that the total air exchange at a subway station depends on the station location within the line. The operating mode of fans remains unaltered in this case. The article shows that elimination of air leakage in the station ventilation room allows an increase in the air flow rate by 7–8% at the same energy consumption by fans. The influence of the stop of a train in the tunnel on the air distribution is illustrated.

Interferometrically stable, enclosed, spinning sample cell for spectroscopic experiments on air-sensitive samples

NASA Astrophysics Data System (ADS)

Baranov, Dmitry; Hill, Robert J.; Ryu, Jisu; Park, Samuel D.; Huerta-Viga, Adriana; Carollo, Alexa R.; Jonas, David M.

2017-01-01

In experiments with high photon flux, it is necessary to rapidly remove the sample from the beam and to delay re-excitation until the sample has returned to equilibrium. Rapid and complete sample exchange has been a challenge for air-sensitive samples and for vibration-sensitive experiments. Here, a compact spinning sample cell for air and moisture sensitive liquid and thin film samples is described. The principal parts of the cell are a copper gasket sealed enclosure, a 2.5 in. hard disk drive motor, and a reusable, chemically inert glass sandwich cell. The enclosure provides an oxygen and water free environment at the 1 ppm level, as demonstrated by multi-day tests with sodium benzophenone ketyl radical. Inside the enclosure, the glass sandwich cell spins at ≈70 Hz to generate tangential speeds of 7-12 m/s that enable complete sample exchange at 100 kHz repetition rates. The spinning cell is acoustically silent and compatible with a ±1 nm rms displacement stability interferometer. In order to enable the use of the spinning cell, we discuss centrifugation and how to prevent it, introduce the cycle-averaged resampling rate to characterize repetitive excitation, and develop a figure of merit for a long-lived photoproduct buildup.

Interferometrically stable, enclosed, spinning sample cell for spectroscopic experiments on air-sensitive samples.

PubMed

Baranov, Dmitry; Hill, Robert J; Ryu, Jisu; Park, Samuel D; Huerta-Viga, Adriana; Carollo, Alexa R; Jonas, David M

2017-01-01

In experiments with high photon flux, it is necessary to rapidly remove the sample from the beam and to delay re-excitation until the sample has returned to equilibrium. Rapid and complete sample exchange has been a challenge for air-sensitive samples and for vibration-sensitive experiments. Here, a compact spinning sample cell for air and moisture sensitive liquid and thin film samples is described. The principal parts of the cell are a copper gasket sealed enclosure, a 2.5 in. hard disk drive motor, and a reusable, chemically inert glass sandwich cell. The enclosure provides an oxygen and water free environment at the 1 ppm level, as demonstrated by multi-day tests with sodium benzophenone ketyl radical. Inside the enclosure, the glass sandwich cell spins at ≈70 Hz to generate tangential speeds of 7-12 m/s that enable complete sample exchange at 100 kHz repetition rates. The spinning cell is acoustically silent and compatible with a ±1 nm rms displacement stability interferometer. In order to enable the use of the spinning cell, we discuss centrifugation and how to prevent it, introduce the cycle-averaged resampling rate to characterize repetitive excitation, and develop a figure of merit for a long-lived photoproduct buildup.

Sampling networks with prescribed degree correlations

NASA Astrophysics Data System (ADS)

Del Genio, Charo; Bassler, Kevin; Erdos, Péter; Miklos, István; Toroczkai, Zoltán

2014-03-01

A feature of a network known to affect its structural and dynamical properties is the presence of correlations amongst the node degrees. Degree correlations are a measure of how much the connectivity of a node influences the connectivity of its neighbours, and they are fundamental in the study of processes such as the spreading of information or epidemics, the cascading failures of damaged systems and the evolution of social relations. We introduce a method, based on novel mathematical results, that allows the exact sampling of networks where the number of connections between nodes of any given connectivity is specified. Our algorithm provides a weight associated to each sample, thereby allowing network observables to be measured according to any desired distribution, and it is guaranteed to always terminate successfully in polynomial time. Thus, our new approach provides a preferred tool for scientists to model complex systems of current relevance, and enables researchers to precisely study correlated networks with broad societal importance. CIDG acknowledges support by the European Commission's FP7 through grant No. 288021. KEB acknowledges support from the NSF through grant DMR?1206839. KEB, PE, IM and ZT acknowledge support from AFSOR and DARPA through grant FA?9550-12-1-0405.

Based on Artificial Neural Network to Realize K-Parameter Analysis of Vehicle Air Spring System

NASA Astrophysics Data System (ADS)

Hung, San-Shan; Hsu, Chia-Ning; Hwang, Chang-Chou; Chen, Wen-Jan

2017-10-01

In recent years, because of the air-spring control technique is more mature, that air- spring suspension systems already can be used to replace the classical vehicle suspension system. Depend on internal pressure variation of the air-spring, thestiffnessand the damping factor can be adjusted. Because of air-spring has highly nonlinear characteristic, therefore it isn’t easy to construct the classical controller to control the air-spring effectively. The paper based on Artificial Neural Network to propose a feasible control strategy. By using offline way for the neural network design and learning to the air-spring in different initial pressures and different loads, offline method through, predict air-spring stiffness parameter to establish a model. Finally, through adjusting air-spring internal pressure to change the K-parameter of the air-spring, realize the well dynamic control performance of air-spring suspension.

SENSITIVITY ANALYSIS OF THE MULTI-LAYER MODEL USED IN THE CLEAN AIR STATUS AND TRENDS NETWORK (CASTNET)

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) established the Clean Air Status and Trends Network (CASTNET) and its predecessor, the National Dry Deposition Network (NDDN), as national air quality and meteorological monitoring networks. The purpose of CASTNET is to track the pr...

A soil sampling intercomparison exercise for the ALMERA network.

PubMed

Belli, Maria; de Zorzi, Paolo; Sansone, Umberto; Shakhashiro, Abduhlghani; Gondin da Fonseca, Adelaide; Trinkl, Alexander; Benesch, Thomas

2009-11-01

Soil sampling and analysis for radionuclides after an accidental or routine release is a key factor for the dose calculation to members of the public, and for the establishment of possible countermeasures. The IAEA organized for selected laboratories of the ALMERA (Analytical Laboratories for the Measurement of Environmental Radioactivity) network a Soil Sampling Intercomparison Exercise (IAEA/SIE/01) with the objective of comparing soil sampling procedures used by different laboratories. The ALMERA network is a world-wide network of analytical laboratories located in IAEA member states capable of providing reliable and timely analysis of environmental samples in the event of an accidental or intentional release of radioactivity. Ten ALMERA laboratories were selected to participate in the sampling exercise. The soil sampling intercomparison exercise took place in November 2005 in an agricultural area qualified as a "reference site", aimed at assessing the uncertainties associated with soil sampling in agricultural, semi-natural, urban and contaminated environments and suitable for performing sampling intercomparison. In this paper, the laboratories sampling performance were evaluated.

Community Air Sensor Network (CAIRSENSE) Project: Lower Cost, Continuous Ambient Monitoring Methods

EPA Science Inventory

Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of numerous sensors across a small geographic area would have potential benefits to supplement existing monitoring networks and ...

Network Structure and Biased Variance Estimation in Respondent Driven Sampling

PubMed Central

Verdery, Ashton M.; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J.

2015-01-01

This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network. PMID:26679927

Inside the Mechanics of Network Development: How Competition and Strategy Reorganize European Air Traffic

NASA Technical Reports Server (NTRS)

Huber, Hans

2006-01-01

Air transport forms complex networks that can be measured in order to understand its structural characteristics and functional properties. Recent models for network growth (i.e., preferential attachment, etc.) remain stochastic and do not seek to understand other network-specific mechanisms that may account for their development in a more microscopic way. Air traffic is made up of many constituent airlines that are either privately or publicly owned and that operate their own networks. They follow more or less similar business policies each. The way these airline networks organize among themselves into distinct traffic distributions reveals complex interaction among them, which in turn can be aggregated into larger (macro-) traffic distributions. Our approach allows for a more deterministic methodology that will assess the impact of airline strategies on the distinct distributions for air traffic, particularly inside Europe. One key question this paper is seeking to answer is whether there are distinct patterns of preferential attachment for given classes of airline networks to distinct types of European airports. Conclusions about the advancing degree of concentration in this industry and the airline operators that accelerate this process can be drawn.

Air sampling unit for breath analyzers

NASA Astrophysics Data System (ADS)

Szabra, Dariusz; Prokopiuk, Artur; Mikołajczyk, Janusz; Ligor, Tomasz; Buszewski, Bogusław; Bielecki, Zbigniew

2017-11-01

The paper presents a portable breath sampling unit (BSU) for human breath analyzers. The developed unit can be used to probe air from the upper airway and alveolar for clinical and science studies. The BSU is able to operate as a patient interface device for most types of breath analyzers. Its main task is to separate and to collect the selected phases of the exhaled air. To monitor the so-called I, II, or III phase and to identify the airflow from the upper and lower parts of the human respiratory system, the unit performs measurements of the exhaled CO2 (ECO2) in the concentration range of 0%-20% (0-150 mm Hg). It can work in both on-line and off-line modes according to American Thoracic Society/European Respiratory Society standards. A Tedlar bag with a volume of 5 dm3 is mounted as a BSU sample container. This volume allows us to collect ca. 1-25 selected breath phases. At the user panel, each step of the unit operation is visualized by LED indicators. This helps us to regulate the natural breathing cycle of the patient. There is also an operator's panel to ensure monitoring and configuration setup of the unit parameters. The operation of the breath sampling unit was preliminarily verified using the gas chromatography/mass spectrometry (GC/MS) laboratory setup. At this setup, volatile organic compounds were extracted by solid phase microextraction. The tests were performed by the comparison of GC/MS signals from both exhaled nitric oxide and isoprene analyses for three breath phases. The functionality of the unit was proven because there was an observed increase in the signal level in the case of the III phase (approximately 40%). The described work made it possible to construct a prototype of a very efficient breath sampling unit dedicated to breath sample analyzers.

Air and smear sample calculational tool for Fluor Hanford Radiological control

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

BAUMANN, B.L.

2003-07-11

A spreadsheet calculation tool was developed to automate the calculations performed for determining the concentration of airborne radioactivity and smear counting as outlined in HNF-13536, Section 5.2.7, ''Analyzing Air and Smear Samples''. This document reports on the design and testing of the calculation tool. Radiological Control Technicians (RCTs) will save time and reduce hand written and calculation errors by using an electronic form for documenting and calculating work place air samples. Current expectations are RCTs will perform an air sample and collect the filter or perform a smear for surface contamination. RCTs will then survey the filter for gross alphamore » and beta/gamma radioactivity and with the gross counts utilize either hand calculation method or a calculator to determine activity on the filter. The electronic form will allow the RCT with a few key strokes to document the individual's name, payroll, gross counts, instrument identifiers; produce an error free record. This productivity gain is realized by the enhanced ability to perform mathematical calculations electronically (reducing errors) and at the same time, documenting the air sample.« less

Atmospheric CO2 Concentrations--The Canadian Background Air Pollution Monitoring Network (1993) (NDP-034)

DOE Data Explorer

Trivett, N. B. A. [Environment Canada, Atmospheric Environment Service, Downsview, Ontario, Canada; Hudec, V. C. [Environment Canada, Atmospheric Environment Service, Downsview, Ontario, Canada; Wong, C. S. [Marine Carbon Research Centre, Institute of Ocean Sciences, Sidney, British Columbia, Canada

1993-01-01

Flask air samples collected at roughly weekly intervals at three Canadian sites [Alert, Northwest Territories (July 1975 through July 1992); Sable Island, Nova Scotia (March 1975 through July 1992); and Cape St. James, British Columbia (May 1979 through July 1992)] were analyzed for CO2 concentration with the measurements directly traceable to the WMO primary CO2 standards. Each record includes the date, atmospheric CO2 concentration, and flask classification code. They provide an accurate record of CO2 concentration levels in Canada during the past two decades. Because these data are directly traceable to WMO standards, this record may be compared with records from other Background Air Pollution Monitoring Network (BAPMoN) stations. The data are in three files (one for each of the monitoring stations) ranging in size from 9.4 to 20.1 kB.

Sorbent-based sampling methods for volatile and semi-volatile organic compounds in air Part 1: Sorbent-based air monitoring options.

PubMed

Woolfenden, Elizabeth

2010-04-16

Sorbent tubes/traps are widely used in combination with gas chromatographic (GC) analytical methods to monitor the vapour-phase fraction of organic compounds in air. Target compounds range in volatility from acetylene and freons to phthalates and PCBs and include apolar, polar and reactive species. Airborne vapour concentrations will vary depending on the nature of the location, nearby pollution sources, weather conditions, etc. Levels can range from low percent concentrations in stack and vent emissions to low part per trillion (ppt) levels in ultra-clean outdoor locations. Hundreds, even thousands of different compounds may be present in any given atmosphere. GC is commonly used in combination with mass spectrometry (MS) detection especially for environmental monitoring or for screening uncharacterised workplace atmospheres. Given the complexity and variability of organic vapours in air, no one sampling approach suits every monitoring scenario. A variety of different sampling strategies and sorbent media have been developed to address specific applications. Key sorbent-based examples include: active (pumped) sampling onto tubes packed with one or more sorbents held at ambient temperature; diffusive (passive) sampling onto sorbent tubes/cartridges; on-line sampling of air/gas streams into cooled sorbent traps; and transfer of air samples from containers (canisters, Tedlar) bags, etc.) into cooled sorbent focusing traps. Whichever sampling approach is selected, subsequent analysis almost always involves either solvent extraction or thermal desorption (TD) prior to GC(/MS) analysis. The overall performance of the air monitoring method will depend heavily on appropriate selection of key sampling and analytical parameters. This comprehensive review of air monitoring using sorbent tubes/traps is divided into 2 parts. (1) Sorbent-based air sampling option. (2) Sorbent selection and other aspects of optimizing sorbent-based air monitoring methods. The paper presents

Detection of the urban release of a bacillus anthracis simulant by air sampling.

PubMed

Garza, Alexander G; Van Cuyk, Sheila M; Brown, Michael J; Omberg, Kristin M

2014-01-01

In 2005 and 2009, the Pentagon Force Protection Agency (PFPA) staged deliberate releases of a commercially available organic pesticide containing Bacillus amyloliquefaciens to evaluate PFPA's biothreat response protocols. In concert with, but independent of, these releases, the Department of Homeland Security sponsored experiments to evaluate the efficacy of commonly employed air and surface sampling techniques for detection of an aerosolized biological agent. High-volume air samplers were placed in the expected downwind plume, and samples were collected before, during, and after the releases. Environmental surface and personal air samples were collected in the vicinity of the high-volume air samplers hours after the plume had dispersed. The results indicate it is feasible to detect the release of a biological agent in an urban area both during and after the release of a biological agent using high-volume air and environmental sampling techniques.

On the feasibility of measuring urban air pollution by wireless distributed sensor networks.

PubMed

Moltchanov, Sharon; Levy, Ilan; Etzion, Yael; Lerner, Uri; Broday, David M; Fishbain, Barak

2015-01-01

Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability to capture spatiotemporal concentration variations at an exceptional fine resolution but highlight the need for a frequent in-situ calibration to maintain the consistency of some sensors. Accordingly, a procedure for a field calibration is proposed and shown to improve the system's performance. Overall, our results support the compatibility of wireless distributed sensor networks for measuring urban air pollution at a sub-neighborhood spatial resolution, which suits the requirement for highly spatiotemporal resolved measurements at the breathing-height when assessing exposure to urban air pollution. Copyright © 2014 Elsevier B.V. All rights reserved.

Near-Road Air Quality Monitoring: Factors Affecting Network Design and Interpretation of Data

EPA Science Inventory

The growing number of health studies identifying adverse health effects for populations spending significant amounts of time near large roadways has increased the interest in monitoring air quality in this microenvironment. Designing near-road air monitoring networks or interpret...

Commander De Winne poses for a photo during Air Sampling

NASA Image and Video Library

2009-11-11

ISS021-E-024700 (11 Nov. 2009) --- European Space Agency astronaut Frank De Winne, Expedition 21 commander, uses the Microbial Air Sampler kit (floating freely near De Winne) to obtain microbiology (bacterial & fungal) air samples in the Kibo laboratory of the International Space Station.

Detection of Mycoplasma hyopneumoniae by Air Sampling with a Nested PCR Assay

PubMed Central

Stärk, Katharina D. C.; Nicolet, Jacques; Frey, Joachim

1998-01-01

This article describes the first successful detection of airborne Mycoplasma hyopneumoniae under experimental and field conditions with a new nested PCR assay. Air was sampled with polyethersulfone membranes (pore size, 0.2 μm) mounted in filter holders. Filters were processed by dissolution and direct extraction of DNA for PCR analysis. For the PCR, two nested pairs of oligonucleotide primers were designed by using an M. hyopneumoniae-specific DNA sequence of a repeated gene segment. A nested PCR assay was developed and used to analyze samples collected in eight pig houses where respiratory problems had been common. Air was also sampled from a mycoplasma-free herd. The nested PCR was highly specific and 104 times as sensitive as a one-step PCR. Under field conditions, the sampling system was able to detect airborne M. hyopneumoniae on 80% of farms where acute respiratory disease was present. No airborne M. hyopneumoniae was detected on infected farms without acute cases. The chance of successful detection was increased if air was sampled at several locations within a room and at a lower air humidity. PMID:9464391

Monitoring airborne fungal spores in an experimental indoor environment to evaluate sampling methods and the effects of human activity on air sampling.

PubMed Central

Buttner, M P; Stetzenbach, L D

1993-01-01

Aerobiological monitoring was conducted in an experimental room to aid in the development of standardized sampling protocols for airborne microorganisms in the indoor environment. The objectives of this research were to evaluate the relative efficiencies of selected sampling methods for the retrieval of airborne fungal spores and to determine the effect of human activity on air sampling. Dry aerosols containing known concentrations of Penicillium chrysogenum spores were generated, and air samples were taken by using Andersen six-stage, Surface Air System, Burkard, and depositional samplers. The Andersen and Burkard samplers retrieved the highest numbers of spores compared with the measurement standard, an aerodynamic particle sizer located inside the room. Data from paired samplers demonstrated that the Andersen sampler had the highest levels of sensitivity and repeatability. With a carpet as the source of P. chrysogenum spores, the effects of human activity (walking or vacuuming near the sampling site) on air sampling were also examined. Air samples were taken under undisturbed conditions and after human activity in the room. Human activity resulted in retrieval of significantly higher concentrations of airborne spores. Surface sampling of the carpet revealed moderate to heavy contamination despite relatively low airborne counts. Therefore, in certain situations, air sampling without concomitant surface sampling may not adequately reflect the level of microbial contamination in indoor environments. PMID:8439150

Twenty years of measurement of polycyclic aromatic hydrocarbons (PAHs) in UK ambient air by nationwide air quality networks.

PubMed

Brown, Andrew S; Brown, Richard J C; Coleman, Peter J; Conolly, Christopher; Sweetman, Andrew J; Jones, Kevin C; Butterfield, David M; Sarantaridis, Dimitris; Donovan, Brian J; Roberts, Ian

2013-06-01

The impact of human activities on the health of the population and of the wider environment has prompted action to monitor the presence of toxic compounds in the atmosphere. Toxic organic micropollutants (TOMPs) are some of the most insidious and persistent of these pollutants. Since 1991 the United Kingdom has operated nationwide air quality networks to assess the presence of TOMPs, including polycyclic aromatic hydrocarbons (PAHs), in ambient air. The data produced in 2010 marked 20 years of nationwide PAH monitoring. This paper marks this milestone by providing a novel and critical review of the data produced since nationwide monitoring began up to the end of 2011 (the latest year for which published data is available), discussing how the networks performing this monitoring has evolved, and elucidating trends in the concentrations of the PAHs measured. The current challenges in the area and a forward look to the future of air quality monitoring for PAHs are also discussed briefly.

Prediction of air pollutant concentration based on sparse response back-propagation training feedforward neural networks.

PubMed

Ding, Weifu; Zhang, Jiangshe; Leung, Yee

2016-10-01

In this paper, we predict air pollutant concentration using a feedforward artificial neural network inspired by the mechanism of the human brain as a useful alternative to traditional statistical modeling techniques. The neural network is trained based on sparse response back-propagation in which only a small number of neurons respond to the specified stimulus simultaneously and provide a high convergence rate for the trained network, in addition to low energy consumption and greater generalization. Our method is evaluated on Hong Kong air monitoring station data and corresponding meteorological variables for which five air quality parameters were gathered at four monitoring stations in Hong Kong over 4 years (2012-2015). Our results show that our training method has more advantages in terms of the precision of the prediction, effectiveness, and generalization of traditional linear regression algorithms when compared with a feedforward artificial neural network trained using traditional back-propagation.

The Roland Maze Project school-based extensive air shower network

NASA Astrophysics Data System (ADS)

Feder, J.; Jȩdrzejczak, K.; Karczmarczyk, J.; Lewandowski, R.; Swarzyński, J.; Szabelska, B.; Szabelski, J.; Wibig, T.

2006-01-01

We plan to construct the large area network of extensive air shower detectors placed on the roofs of high school buildings in the city of Łódź. Detection points will be connected by INTERNET to the central server and their work will be synchronized by GPS. The main scientific goal of the project are studies of ultra high energy cosmic rays. Using existing town infrastructure (INTERNET, power supply, etc.) will significantly reduce the cost of the experiment. Engaging high school students in the research program should significantly increase their knowledge of science and modern technologies, and can be a very efficient way of science popularisation. We performed simulations of the projected network capabilities of registering Extensive Air Showers and reconstructing energies of primary particles. Results of the simulations and the current status of project realisation will be presented.

From trees to forest: relational complexity network and workload of air traffic controllers.

PubMed

Zhang, Jingyu; Yang, Jiazhong; Wu, Changxu

2015-01-01

In this paper, we propose a relational complexity (RC) network framework based on RC metric and network theory to model controllers' workload in conflict detection and resolution. We suggest that, at the sector level, air traffic showing a centralised network pattern can provide cognitive benefits in visual search and resolution decision which will in turn result in lower workload. We found that the network centralisation index can account for more variance in predicting perceived workload and task completion time in both a static conflict detection task (Study 1) and a dynamic one (Study 2) in addition to other aircraft-level and pair-level factors. This finding suggests that linear combination of aircraft-level or dyad-level information may not be adequate and the global-pattern-based index is necessary. Theoretical and practical implications of using this framework to improve future workload modelling and management are discussed. We propose a RC network framework to model the workload of air traffic controllers. The effect of network centralisation was examined in both a static conflict detection task and a dynamic one. Network centralisation was predictive of perceived workload and task completion time over and above other control variables.

Contemporary-use pesticides in personal air samples during pregnancy and blood samples at delivery among urban minority mothers and newborns.

PubMed Central

Whyatt, Robin M; Barr, Dana B; Camann, David E; Kinney, Patrick L; Barr, John R; Andrews, Howard F; Hoepner, Lori A; Garfinkel, Robin; Hazi, Yair; Reyes, Andria; Ramirez, Judyth; Cosme, Yesenia; Perera, Frederica P

2003-01-01

We have measured 29 pesticides in plasma samples collected at birth between 1998 and 2001 from 230 mother and newborn pairs enrolled in the Columbia Center for Children's Environmental Health prospective cohort study. Our prior research has shown widespread pesticide use during pregnancy among this urban minority cohort from New York City. We also measured eight pesticides in 48-hr personal air samples collected from the mothers during pregnancy. The following seven pesticides were detected in 48-83% of plasma samples (range, 1-270 pg/g): the organophosphates chlorpyrifos and diazinon, the carbamates bendiocarb and 2-isopropoxyphenol (metabolite of propoxur), and the fungicides dicloran, phthalimide (metabolite of folpet and captan), and tetrahydrophthalimide (metabolite of captan and captafol). Maternal and cord plasma levels were similar and, except for phthalimide, were highly correlated (p < 0.001). Chlorpyrifos, diazinon, and propoxur were detected in 100% of personal air samples (range, 0.7-6,010 ng/m(3)). Diazinon and propoxur levels were significantly higher in the personal air of women reporting use of an exterminator, can sprays, and/or pest bombs during pregnancy compared with women reporting no pesticide use or use of lower toxicity methods only. A significant correlation was seen between personal air level of chlorpyrifos, diazinon, and propoxur and levels of these insecticides or their metabolites in plasma samples (maternal and/or cord, p < 0.05). The fungicide ortho-phenylphenol was also detected in 100% of air samples but was not measured in plasma. The remaining 22 pesticides were detected in 0-45% of air or plasma samples. Chlorpyrifos, diazinon, propoxur, and bendiocarb levels in air and/or plasma decreased significantly between 1998 and 2001. Findings indicate that pesticide exposures are frequent but decreasing and that the pesticides are readily transferred to the developing fetus during pregnancy. PMID:12727605

Air quality measurements and monitoring network in the Republic of Latvia

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

Grinman, A.; Lyulko, J.; Dubrovskaja, R.

1996-12-31

The territory of Latvia is covered with a wide environmental monitoring network, that falls under 2 main categories: (1) regional network featuring the region and involved in international monitoring programs, including EMEP, GAW, IM; (2) state network providing for local pollution monitoring of the atmosphere (19 posts), precipitation (5 station) and radioactivity (46 station). In 1994, measurements were made at 20 stationary posts located in Daugavpils (2), Jekabpils (2), Jurmala, (2), Liepaja (2), Nigrande (1), Olaine (1), Rezekne (1), Riga (5), Valn-dera (2), Ventspils (2). This atmospheric air observation network covers mostly towns densely populated with industrial objects and othermore » pollutant emitting sources. Thus, the observation programs encompass measurements of pollutants that have higher concentrations in the ambient air. Results indicate that the annual pollution dynamics are closely connected with concentration fluctuations in the seasons. The sulfur dioxide and nitrogen dioxide concentrations increased during the heating season in Jekabpils, Jurmala and Valmiera, i.e., in the town that have many small heating installations. The data obtained allow to trace a dependence of measurement values upon the location of the observational posts vis-a-vis the pollutant emitting sources.« less

Profiling quinones in ambient air samples collected from the Athabasca region (Canada).

PubMed

Wnorowski, Andrzej; Charland, Jean-Pierre

2017-12-01

This paper presents new findings on polycyclic aromatic hydrocarbon oxidation products-quinones that were collected in ambient air samples in the proximity of oil sands exploration. Quinones were characterized for their diurnal concentration variability, phase partitioning, and molecular size distribution. Gas-phase (GP) and particle-phase (PM) ambient air samples were collected separately in the summer; a lower quinone content was observed in the PM samples from continuous 24-h sampling than from combined 12-h sampling (day and night). The daytime/nocturnal samples demonstrated that nighttime conditions led to lower concentrations and some quinones not being detected. The highest quinone levels were associated with wind directions originating from oil sands exploration sites. The statistical correlation with primary pollutants directly emitted from oil sands industrial activities indicated that the bulk of the detected quinones did not originate directly from primary emission sources and that quinone formation paralleled a reduction in primary source NO x levels. This suggests a secondary chemical transformation of primary pollutants as the origin of the determined quinones. Measurements of 19 quinones included five that have not previously been reported in ambient air or in Standard Reference Material 1649a/1649b and seven that have not been previously measured in ambient air in the underivatized form. This is the first paper to report on quinone characterization in secondary organic aerosols originating from oil sands activities, to distinguish chrysenequinone and anthraquinone positional isomers in ambient air, and to report the requirement of daylight conditions for benzo[a]pyrenequinone and naphthacenequinone to be present in ambient air. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

An Open-Access Modeled Passenger Flow Matrix for the Global Air Network in 2010

PubMed Central

Huang, Zhuojie; Wu, Xiao; Garcia, Andres J.; Fik, Timothy J.; Tatem, Andrew J.

2013-01-01

The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data. PMID:23691194

An open-access modeled passenger flow matrix for the global air network in 2010.

PubMed

Huang, Zhuojie; Wu, Xiao; Garcia, Andres J; Fik, Timothy J; Tatem, Andrew J

2013-01-01

The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data.

U.S. EPA's National Dioxin Air Monitoring Network: Analytical Issues

EPA Science Inventory

The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric chlorinated dibenzo-p-dioxins (CDDs), furans (CDFs), and coplanar polychlorinated biphenyls (PCBs) at rural and non-impacted locatio...

Landscape Characterization and Representativeness Analysis for Understanding Sampling Network Coverage

DOE Data Explorer

Maddalena, Damian; Hoffman, Forrest; Kumar, Jitendra; Hargrove, William

2014-08-01

Sampling networks rarely conform to spatial and temporal ideals, often comprised of network sampling points which are unevenly distributed and located in less than ideal locations due to access constraints, budget limitations, or political conflict. Quantifying the global, regional, and temporal representativeness of these networks by quantifying the coverage of network infrastructure highlights the capabilities and limitations of the data collected, facilitates upscaling and downscaling for modeling purposes, and improves the planning efforts for future infrastructure investment under current conditions and future modeled scenarios. The work presented here utilizes multivariate spatiotemporal clustering analysis and representativeness analysis for quantitative landscape characterization and assessment of the Fluxnet, RAINFOR, and ForestGEO networks. Results include ecoregions that highlight patterns of bioclimatic, topographic, and edaphic variables and quantitative representativeness maps of individual and combined networks.

Evaluation of Legionella Air Contamination in Healthcare Facilities by Different Sampling Methods: An Italian Multicenter Study.

PubMed

Montagna, Maria Teresa; De Giglio, Osvalda; Cristina, Maria Luisa; Napoli, Christian; Pacifico, Claudia; Agodi, Antonella; Baldovin, Tatjana; Casini, Beatrice; Coniglio, Maria Anna; D'Errico, Marcello Mario; Delia, Santi Antonino; Deriu, Maria Grazia; Guida, Marco; Laganà, Pasqualina; Liguori, Giorgio; Moro, Matteo; Mura, Ida; Pennino, Francesca; Privitera, Gaetano; Romano Spica, Vincenzo; Sembeni, Silvia; Spagnolo, Anna Maria; Tardivo, Stefano; Torre, Ida; Valeriani, Federica; Albertini, Roberto; Pasquarella, Cesira

2017-06-22

Healthcare facilities (HF) represent an at-risk environment for legionellosis transmission occurring after inhalation of contaminated aerosols. In general, the control of water is preferred to that of air because, to date, there are no standardized sampling protocols. Legionella air contamination was investigated in the bathrooms of 11 HF by active sampling (Surface Air System and Coriolis ® μ) and passive sampling using settling plates. During the 8-hour sampling, hot tap water was sampled three times. All air samples were evaluated using culture-based methods, whereas liquid samples collected using the Coriolis ® μ were also analyzed by real-time PCR. Legionella presence in the air and water was then compared by sequence-based typing (SBT) methods. Air contamination was found in four HF (36.4%) by at least one of the culturable methods. The culturable investigation by Coriolis ® μ did not yield Legionella in any enrolled HF. However, molecular investigation using Coriolis ® μ resulted in eight HF testing positive for Legionella in the air. Comparison of Legionella air and water contamination indicated that Legionella water concentration could be predictive of its presence in the air. Furthermore, a molecular study of 12 L. pneumophila strains confirmed a match between the Legionella strains from air and water samples by SBT for three out of four HF that tested positive for Legionella by at least one of the culturable methods. Overall, our study shows that Legionella air detection cannot replace water sampling because the absence of microorganisms from the air does not necessarily represent their absence from water; nevertheless, air sampling may provide useful information for risk assessment. The liquid impingement technique appears to have the greatest capacity for collecting airborne Legionella if combined with molecular investigations.

Evaluation of Legionella Air Contamination in Healthcare Facilities by Different Sampling Methods: An Italian Multicenter Study

PubMed Central

Montagna, Maria Teresa; De Giglio, Osvalda; Cristina, Maria Luisa; Napoli, Christian; Pacifico, Claudia; Agodi, Antonella; Baldovin, Tatjana; Casini, Beatrice; Coniglio, Maria Anna; D’Errico, Marcello Mario; Delia, Santi Antonino; Deriu, Maria Grazia; Guida, Marco; Laganà, Pasqualina; Liguori, Giorgio; Moro, Matteo; Mura, Ida; Pennino, Francesca; Privitera, Gaetano; Romano Spica, Vincenzo; Sembeni, Silvia; Spagnolo, Anna Maria; Tardivo, Stefano; Torre, Ida; Valeriani, Federica; Albertini, Roberto; Pasquarella, Cesira

2017-01-01

Healthcare facilities (HF) represent an at-risk environment for legionellosis transmission occurring after inhalation of contaminated aerosols. In general, the control of water is preferred to that of air because, to date, there are no standardized sampling protocols. Legionella air contamination was investigated in the bathrooms of 11 HF by active sampling (Surface Air System and Coriolis®μ) and passive sampling using settling plates. During the 8-hour sampling, hot tap water was sampled three times. All air samples were evaluated using culture-based methods, whereas liquid samples collected using the Coriolis®μ were also analyzed by real-time PCR. Legionella presence in the air and water was then compared by sequence-based typing (SBT) methods. Air contamination was found in four HF (36.4%) by at least one of the culturable methods. The culturable investigation by Coriolis®μ did not yield Legionella in any enrolled HF. However, molecular investigation using Coriolis®μ resulted in eight HF testing positive for Legionella in the air. Comparison of Legionella air and water contamination indicated that Legionella water concentration could be predictive of its presence in the air. Furthermore, a molecular study of 12 L. pneumophila strains confirmed a match between the Legionella strains from air and water samples by SBT for three out of four HF that tested positive for Legionella by at least one of the culturable methods. Overall, our study shows that Legionella air detection cannot replace water sampling because the absence of microorganisms from the air does not necessarily represent their absence from water; nevertheless, air sampling may provide useful information for risk assessment. The liquid impingement technique appears to have the greatest capacity for collecting airborne Legionella if combined with molecular investigations. PMID:28640202

Composition Alteration of Stratospheric Air Due to Sampling through a Flow Tube.

DTIC Science & Technology

1984-02-03

C. C. , Forsberg, C. A. , and Pieri , H. V. (19)83) Stratospheric N 20 CF2 Cl and CFCI3 composition studies utilizing in situ cryogenic whole air...Gas-Surface Interactions in Cryogenic Whole Air Sampling, AFGL-TR-81-0162, AD A108255. 19. Gallagher, C. C., Forsberg, C. A., and Pieri , R. V. (1983...Gallagher, C. C., Forsberg, C. A., Pieri , R. V., and Faucher, G. A. (1983a) Oxides of Nitrogen Content of Whole Air Samples Obtained at Altitudes From 12

A Novel Biobjective Risk-Based Model for Stochastic Air Traffic Network Flow Optimization Problem.

PubMed

Cai, Kaiquan; Jia, Yaoguang; Zhu, Yanbo; Xiao, Mingming

2015-01-01

Network-wide air traffic flow management (ATFM) is an effective way to alleviate demand-capacity imbalances globally and thereafter reduce airspace congestion and flight delays. The conventional ATFM models assume the capacities of airports or airspace sectors are all predetermined. However, the capacity uncertainties due to the dynamics of convective weather may make the deterministic ATFM measures impractical. This paper investigates the stochastic air traffic network flow optimization (SATNFO) problem, which is formulated as a weighted biobjective 0-1 integer programming model. In order to evaluate the effect of capacity uncertainties on ATFM, the operational risk is modeled via probabilistic risk assessment and introduced as an extra objective in SATNFO problem. Computation experiments using real-world air traffic network data associated with simulated weather data show that presented model has far less constraints compared to stochastic model with nonanticipative constraints, which means our proposed model reduces the computation complexity.

Carter Carburetor Weekly Air Monitoring & Sampling Report - March 7, 2013 - March 13, 2016

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Final Environmental Assessment for Wide Area Coverage Construct Land Mobile Network Communications Infrastructure Malmstrom Air Force Base, Montana

DTIC Science & Technology

2008-02-01

FINAL ENVIRONMENTAL ASSESSMENT February 2008 Malmstrom ® AFB WIDE AREA COVERAGE CONSTRUCT LAND MOBILE NETWORK COMMUNICATIONS INFRASTRUCTURE...Wide Area Coverage Construct Land Mobile Network Communications Infrastructure Malmstrom Air Force Base, Montana 5a. CONTRACT NUMBER 5b. GRANT...SIGNIFICANT IMPACT WIDE AREA COVERAGE CONSTRUCT LAND MOBILE NETWORK COMMUNICATIONS INFRASTRUCTURE MALMSTROM AIR FORCE BASE, MONTANA The

Architecture for an integrated real-time air combat and sensor network simulation

NASA Astrophysics Data System (ADS)

Criswell, Evans A.; Rushing, John; Lin, Hong; Graves, Sara

2007-04-01

An architecture for an integrated air combat and sensor network simulation is presented. The architecture integrates two components: a parallel real-time sensor fusion and target tracking simulation, and an air combat simulation. By integrating these two simulations, it becomes possible to experiment with scenarios in which one or both sides in a battle have very large numbers of primitive passive sensors, and to assess the likely effects of those sensors on the outcome of the battle. Modern Air Power is a real-time theater-level air combat simulation that is currently being used as a part of the USAF Air and Space Basic Course (ASBC). The simulation includes a variety of scenarios from the Vietnam war to the present day, and also includes several hypothetical future scenarios. Modern Air Power includes a scenario editor, an order of battle editor, and full AI customization features that make it possible to quickly construct scenarios for any conflict of interest. The scenario editor makes it possible to place a wide variety of sensors including both high fidelity sensors such as radars, and primitive passive sensors that provide only very limited information. The parallel real-time sensor network simulation is capable of handling very large numbers of sensors on a computing cluster of modest size. It can fuse information provided by disparate sensors to detect and track targets, and produce target tracks.

Efficient sampling of complex network with modified random walk strategies

NASA Astrophysics Data System (ADS)

Xie, Yunya; Chang, Shuhua; Zhang, Zhipeng; Zhang, Mi; Yang, Lei

2018-02-01

We present two novel random walk strategies, choosing seed node (CSN) random walk and no-retracing (NR) random walk. Different from the classical random walk sampling, the CSN and NR strategies focus on the influences of the seed node choice and path overlap, respectively. Three random walk samplings are applied in the Erdös-Rényi (ER), Barabási-Albert (BA), Watts-Strogatz (WS), and the weighted USAir networks, respectively. Then, the major properties of sampled subnets, such as sampling efficiency, degree distributions, average degree and average clustering coefficient, are studied. The similar conclusions can be reached with these three random walk strategies. Firstly, the networks with small scales and simple structures are conducive to the sampling. Secondly, the average degree and the average clustering coefficient of the sampled subnet tend to the corresponding values of original networks with limited steps. And thirdly, all the degree distributions of the subnets are slightly biased to the high degree side. However, the NR strategy performs better for the average clustering coefficient of the subnet. In the real weighted USAir networks, some obvious characters like the larger clustering coefficient and the fluctuation of degree distribution are reproduced well by these random walk strategies.

The Imperial County Community Air Monitoring Network: A Model for Community-based Environmental Monitoring for Public Health Action

PubMed Central

Olmedo, Luis; Bejarano, Ester; Lugo, Humberto; Murillo, Eduardo; Seto, Edmund; Wong, Michelle; King, Galatea; Wilkie, Alexa; Meltzer, Dan; Carvlin, Graeme; Jerrett, Michael; Northcross, Amanda

2017-01-01

Summary: The Imperial County Community Air Monitoring Network (the Network) is a collaborative group of community, academic, nongovernmental, and government partners designed to fill the need for more detailed data on particulate matter in an area that often exceeds air quality standards. The Network employs a community-based environmental monitoring process in which the community and researchers have specific, well-defined roles as part of an equitable partnership that also includes shared decision-making to determine study direction, plan research protocols, and conduct project activities. The Network is currently producing real-time particulate matter data from 40 low-cost sensors throughout Imperial County, one of the largest community-based air networks in the United States. Establishment of a community-led air network involves engaging community members to be citizen-scientists in the monitoring, siting, and data collection process. Attention to technical issues regarding instrument calibration and validation and electronic transfer and storage of data is also essential. Finally, continued community health improvements will be predicated on facilitating community ownership and sustainability of the network after research funds have been expended. https://doi.org/10.1289/EHP1772 PMID:28886604

Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States

NASA Astrophysics Data System (ADS)

Jiao, Wan; Hagler, Gayle; Williams, Ronald; Sharpe, Robert; Brown, Ryan; Garver, Daniel; Judge, Robert; Caudill, Motria; Rickard, Joshua; Davis, Michael; Weinstock, Lewis; Zimmer-Dauphinee, Susan; Buckley, Ken

2016-11-01

Advances in air pollution sensor technology have enabled the development of small and low-cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low-cost, continuous, and commercially available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ˜ 2 km area in the southeastern United States. Collocation of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as the degree to which multiple identical sensors produced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, and -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r < 0.5) with a reference monitor and erroneously high concentration values. A wide variety of particulate matter (PM) sensors were tested with variable results - some sensors had very high agreement (e.g., r = 0.99) between identical sensors but moderate agreement with a reference PM2.5 monitor (e.g., r = 0.65). For select sensors that had moderate to strong correlation with reference monitors (r > 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in number of sampling days could be used in a correction algorithm to improve the agreement. Maximum improvement in agreement with a reference

Novel sample preparation technique with needle-type micro-extraction device for volatile organic compounds in indoor air samples.

PubMed

Ueta, Ikuo; Mizuguchi, Ayako; Fujimura, Koji; Kawakubo, Susumu; Saito, Yoshihiro

2012-10-09

A novel needle-type sample preparation device was developed for the effective preconcentration of volatile organic compounds (VOCs) in indoor air before gas chromatography-mass spectrometry (GC-MS) analysis. To develop a device for extracting a wide range of VOCs typically found in indoor air, several types of particulate sorbents were tested as the extraction medium in the needle-type extraction device. To determine the content of these VOCs, air samples were collected for 30min with the packed sorbent(s) in the extraction needle, and the extracted VOCs were thermally desorbed in a GC injection port by the direct insertion of the needle. A double-bed sorbent consisting of a needle packed with divinylbenzene and activated carbon particles exhibited excellent extraction and desorption performance and adequate extraction capacity for all the investigated VOCs. The results also clearly demonstrated that the proposed sample preparation method is a more rapid, simpler extraction/desorption technique than traditional sample preparation methods. Copyright © 2012 Elsevier B.V. All rights reserved.

Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

PubMed

Maguire, Jack B; Boyken, Scott E; Baker, David; Kuhlman, Brian

2018-05-08

Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

Sampling for Air Chemical Emissions from the Life Sciences Laboratory II

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

Ballinger, Marcel Y.; Lindberg, Michael J.

Sampling for air chemical emissions from the Life Science Laboratory II (LSL-II) ventilation stack was performed in an effort to determine potential exposure of maintenance staff to laboratory exhaust on the building roof. The concern about worker exposure was raised in December 2015 and several activities were performed to assist in estimating exposure concentrations. Data quality objectives were developed to determine the need for and scope and parameters of a sampling campaign to measure chemical emissions from research and development activities to the outside air. The activities provided data on temporal variation of air chemical concentrations and a basis formore » evaluating calculated emissions. Sampling for air chemical emissions was performed in the LSL-II ventilation stack over the 6-week period from July 26 to September 1, 2016. A total of 12 sampling events were carried out using 16 sample media. Resulting analysis provided concentration data on 49 analytes. All results were below occupational exposure limits and most results were below detection limits. When compared to calculated emissions, only 5 of the 49 chemicals had measured concentrations greater than predicted. This sampling effort will inform other study components to develop a more complete picture of a worker’s potential exposure from LSL-II rooftop activities. Mixing studies were conducted to inform spatial variation in concentrations at other rooftop locations and can be used in conjunction with these results to provide temporal variations in concentrations for estimating the potential exposure to workers working in and around the LSL-II stack.« less

Network Model-Assisted Inference from Respondent-Driven Sampling Data.

PubMed

Gile, Krista J; Handcock, Mark S

2015-06-01

Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights for traditional design-based inference, and likelihood inference requires modeling the complex sampling process. As an alternative, we introduce a model-assisted approach, resulting in a design-based estimator leveraging a working network model. We derive a new class of estimators for population means and a corresponding bootstrap standard error estimator. We demonstrate improved performance compared to existing estimators, including adjustment for an initial convenience sample. We also apply the method and an extension to the estimation of HIV prevalence in a high-risk population.

Group Centric Networking: Large Scale Over the Air Testing of Group Centric Networking

DTIC Science & Technology

2016-11-01

protocol designed to support groups of devices in a local region [4]. It attempts to use the wireless medium to broadcast minimal control information...1) Group Discovery: The goal of the group discovery algo- rithm is to find group nodes without globally flooding control messages. To facilitate this...Large Scale Over-the-Air Testing of Group Centric Networking Logan Mercer, Greg Kuperman, Andrew Hunter, Brian Proulx MIT Lincoln Laboratory

BOREAS AFM-5 Level-2 Upper Air Network Standard Pressure Level Data

NASA Technical Reports Server (NTRS)

Barr, Alan; Hrynkiw, Charmaine; Hall, Forrest G. (Editor); Newcomer, Jeffrey A. (Editor); Smith, David E. (Technical Monitor)

2000-01-01

The BOREAS AFM-5 team collected and processed data from the numerous radiosonde flights during the project. The goals of the AFM-05 team were to provide large-scale definition of the atmosphere by supplementing the existing AES aerological network, both temporally and spatially. This data set includes basic upper-air parameters interpolated at 0.5 kiloPascal increments of atmospheric pressure from data collected from the network of upper-air stations during the 1993, 1994, and 1996 field campaigns over the entire study region. The data are contained in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Combining Community Engagement and Scientific Approaches in Next-Generation Monitor Siting: The Case of the Imperial County Community Air Network.

PubMed

Wong, Michelle; Bejarano, Esther; Carvlin, Graeme; Fellows, Katie; King, Galatea; Lugo, Humberto; Jerrett, Michael; Meltzer, Dan; Northcross, Amanda; Olmedo, Luis; Seto, Edmund; Wilkie, Alexa; English, Paul

2018-03-15

Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach.

Combining Community Engagement and Scientific Approaches in Next-Generation Monitor Siting: The Case of the Imperial County Community Air Network

PubMed Central

Wong, Michelle; Bejarano, Esther; Carvlin, Graeme; King, Galatea; Lugo, Humberto; Jerrett, Michael; Northcross, Amanda; Olmedo, Luis; Seto, Edmund; Wilkie, Alexa; English, Paul

2018-01-01

Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach. PMID:29543726

Network Model-Assisted Inference from Respondent-Driven Sampling Data

PubMed Central

Gile, Krista J.; Handcock, Mark S.

2015-01-01

Summary Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights for traditional design-based inference, and likelihood inference requires modeling the complex sampling process. As an alternative, we introduce a model-assisted approach, resulting in a design-based estimator leveraging a working network model. We derive a new class of estimators for population means and a corresponding bootstrap standard error estimator. We demonstrate improved performance compared to existing estimators, including adjustment for an initial convenience sample. We also apply the method and an extension to the estimation of HIV prevalence in a high-risk population. PMID:26640328

Classifying Sources Influencing Indoor Air Quality (IAQ) Using Artificial Neural Network (ANN)

PubMed Central

Mad Saad, Shaharil; Melvin Andrew, Allan; Md Shakaff, Ali Yeon; Mohd Saad, Abdul Rahman; Muhamad Yusof @ Kamarudin, Azman; Zakaria, Ammar

2015-01-01

Monitoring indoor air quality (IAQ) is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN—a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC), base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room’s conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity. PMID:26007724

Respondent-driven sampling and the recruitment of people with small injecting networks.

PubMed

Paquette, Dana; Bryant, Joanne; de Wit, John

2012-05-01

Respondent-driven sampling (RDS) is a form of chain-referral sampling, similar to snowball sampling, which was developed to reach hidden populations such as people who inject drugs (PWID). RDS is said to reach members of a hidden population that may not be accessible through other sampling methods. However, less attention has been paid as to whether there are segments of the population that are more likely to be missed by RDS. This study examined the ability of RDS to capture people with small injecting networks. A study of PWID, using RDS, was conducted in 2009 in Sydney, Australia. The size of participants' injecting networks was examined by recruitment chain and wave. Participants' injecting network characteristics were compared to those of participants from a separate pharmacy-based study. A logistic regression analysis was conducted to examine the characteristics independently associated with having small injecting networks, using the combined RDS and pharmacy-based samples. In comparison with the pharmacy-recruited participants, RDS participants were almost 80% less likely to have small injecting networks, after adjusting for other variables. RDS participants were also more likely to have their injecting networks form a larger proportion of those in their social networks, and to have acquaintances as part of their injecting networks. Compared to those with larger injecting networks, individuals with small injecting networks were equally likely to engage in receptive sharing of injecting equipment, but less likely to have had contact with prevention services. These findings suggest that those with small injecting networks are an important group to recruit, and that RDS is less likely to capture these individuals.

Local synchronization of chaotic neural networks with sampled-data and saturating actuators.

PubMed

Wu, Zheng-Guang; Shi, Peng; Su, Hongye; Chu, Jian

2014-12-01

This paper investigates the problem of local synchronization of chaotic neural networks with sampled-data and actuator saturation. A new time-dependent Lyapunov functional is proposed for the synchronization error systems. The advantage of the constructed Lyapunov functional lies in the fact that it is positive definite at sampling times but not necessarily between sampling times, and makes full use of the available information about the actual sampling pattern. A local stability condition of the synchronization error systems is derived, based on which a sampled-data controller with respect to the actuator saturation is designed to ensure that the master neural networks and slave neural networks are locally asymptotically synchronous. Two optimization problems are provided to compute the desired sampled-data controller with the aim of enlarging the set of admissible initial conditions or the admissible sampling upper bound ensuring the local synchronization of the considered chaotic neural networks. A numerical example is used to demonstrate the effectiveness of the proposed design technique.

Journal Article: EPA's National Dioxin Air Monitoring Network (Ndamn): Design, Implementation, and Final Results

EPA Science Inventory

The U.S. Environmental Protection Agency (U.S. EPA) established the National Dioxin Air Monitoring Network (NDAMN) in June of 1998, and operated it until November of 2004. The objective of NDAMN was to determine background air concentrations of polychlorinated dibenzo-p-dioxins (...

Solubility testing of actinides on breathing-zone and area air samples

NASA Astrophysics Data System (ADS)

Metzger, Robert Lawrence

The solubility of inhaled radionuclides in the human lung is an important characteristic of the compounds needed to perform internal dosimetry assessments for exposed workers. A solubility testing method for uranium and several common actinides has been developed with sufficient sensitivity to allow profiles to be determined from routine breathing zone and area air samples in the workplace. Air samples are covered with a clean filter to form a filter-sample-filter sandwich which is immersed in an extracellular lung serum simulant solution. The sample is moved to a fresh beaker of the lung fluid simulant each day for one week, and then weekly until the end of the 28 day test period. The soak solutions are wet ashed with nitric acid and hydrogen peroxide to destroy the organic components of the lung simulant solution prior to extraction of the nuclides of interest directly into an extractive scintillator for subsequent counting on a Photon-Electron Rejecting Alpha Liquid Scintillation (PERALSsp°ler ) spectrometer. Solvent extraction methods utilizing the extractive scintillators have been developed for the isotopes of uranium, plutonium, and curium. The procedures normally produce an isotopic recovery greater than 95% and have been used to develop solubility profiles from air samples with 40 pCi or less of Usb3Osb8. This makes it possible to characterize solubility profiles in every section of operating facilities where airborne nuclides are found using common breathing zone air samples. The new method was evaluated by analyzing uranium compounds from two uranium mills whose product had been previously analyzed by in vitro solubility testing in the laboratory and in vivo solubility testing in rodents. The new technique compared well with the in vivo rodent solubility profiles. The method was then used to evaluate the solubility profiles in all process sections of an operating in situ uranium plant using breathing zone and area air samples collected during routine

Flexible sampling large-scale social networks by self-adjustable random walk

NASA Astrophysics Data System (ADS)

Xu, Xiao-Ke; Zhu, Jonathan J. H.

2016-12-01

Online social networks (OSNs) have become an increasingly attractive gold mine for academic and commercial researchers. However, research on OSNs faces a number of difficult challenges. One bottleneck lies in the massive quantity and often unavailability of OSN population data. Sampling perhaps becomes the only feasible solution to the problems. How to draw samples that can represent the underlying OSNs has remained a formidable task because of a number of conceptual and methodological reasons. Especially, most of the empirically-driven studies on network sampling are confined to simulated data or sub-graph data, which are fundamentally different from real and complete-graph OSNs. In the current study, we propose a flexible sampling method, called Self-Adjustable Random Walk (SARW), and test it against with the population data of a real large-scale OSN. We evaluate the strengths of the sampling method in comparison with four prevailing methods, including uniform, breadth-first search (BFS), random walk (RW), and revised RW (i.e., MHRW) sampling. We try to mix both induced-edge and external-edge information of sampled nodes together in the same sampling process. Our results show that the SARW sampling method has been able to generate unbiased samples of OSNs with maximal precision and minimal cost. The study is helpful for the practice of OSN research by providing a highly needed sampling tools, for the methodological development of large-scale network sampling by comparative evaluations of existing sampling methods, and for the theoretical understanding of human networks by highlighting discrepancies and contradictions between existing knowledge/assumptions of large-scale real OSN data.

Quantitative evaluation of an air-monitoring network using atmospheric transport modeling and frequency of detection methods

DOE PAGES

Rood, Arthur S.; Sondrup, A. Jeffrey; Ritter, Paul D.

2016-04-01

A methodology to quantify the performance of an air monitoring network in terms of frequency of detection has been developed. The methodology utilizes an atmospheric transport model to predict air concentrations of radionuclides at the samplers for a given release time and duration. Frequency of detection is defined as the fraction of “events” that result in a detection at either a single sampler or network of samplers. An “event” is defined as a release of finite duration that begins on a given day and hour of the year from a facility with the potential to emit airborne radionuclides. Another metricmore » of interest is the network intensity, which is defined as the fraction of samplers in the network that have a positive detection for a given event. The frequency of detection methodology allows for evaluation of short-term releases that include effects of short-term variability in meteorological conditions. The methodology was tested using the U.S. Department of Energy Idaho National Laboratory (INL) Site ambient air monitoring network consisting of 37 low-volume air samplers in 31 different locations covering a 17,630 km 2 region. Releases from six major INL facilities distributed over an area of 1,435 km 2 were modeled and included three stack sources and eight ground-level sources. A Lagrangian Puff air dispersion model (CALPUFF) was used to model atmospheric transport. The model was validated using historical 125Sb releases and measurements. Relevant one-week release quantities from each emission source were calculated based on a dose of 1.9 × 10 –4 mSv at a public receptor (0.01 mSv assuming release persists over a year). Important radionuclides considered include 241Am, 137Cs, 238Pu, 239Pu, 90Sr, and tritium. Results show the detection frequency is over 97.5% for the entire network considering all sources and radionuclides. Network intensities ranged from 3.75% to 62.7%. Evaluation of individual samplers indicated some samplers were poorly

Quantitative evaluation of an air-monitoring network using atmospheric transport modeling and frequency of detection methods

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

Rood, Arthur S.; Sondrup, A. Jeffrey; Ritter, Paul D.

A methodology to quantify the performance of an air monitoring network in terms of frequency of detection has been developed. The methodology utilizes an atmospheric transport model to predict air concentrations of radionuclides at the samplers for a given release time and duration. Frequency of detection is defined as the fraction of “events” that result in a detection at either a single sampler or network of samplers. An “event” is defined as a release of finite duration that begins on a given day and hour of the year from a facility with the potential to emit airborne radionuclides. Another metricmore » of interest is the network intensity, which is defined as the fraction of samplers in the network that have a positive detection for a given event. The frequency of detection methodology allows for evaluation of short-term releases that include effects of short-term variability in meteorological conditions. The methodology was tested using the U.S. Department of Energy Idaho National Laboratory (INL) Site ambient air monitoring network consisting of 37 low-volume air samplers in 31 different locations covering a 17,630 km 2 region. Releases from six major INL facilities distributed over an area of 1,435 km 2 were modeled and included three stack sources and eight ground-level sources. A Lagrangian Puff air dispersion model (CALPUFF) was used to model atmospheric transport. The model was validated using historical 125Sb releases and measurements. Relevant one-week release quantities from each emission source were calculated based on a dose of 1.9 × 10 –4 mSv at a public receptor (0.01 mSv assuming release persists over a year). Important radionuclides considered include 241Am, 137Cs, 238Pu, 239Pu, 90Sr, and tritium. Results show the detection frequency is over 97.5% for the entire network considering all sources and radionuclides. Network intensities ranged from 3.75% to 62.7%. Evaluation of individual samplers indicated some samplers were poorly

ASSESSING THE COMPARABILITY OF AMMONIUM, NITRATE AND SULFATE CONCENTRATIONS MEASURED BY THREE AIR QUALITY MONITORING NETWORKS

EPA Science Inventory

Airborne fine particulate matter across the United States is monitored by different networks, the three prevalent ones presently being the Clean Air Status and Trend Network (CASTNet), the Interagency Monitoring of PROtected Visual Environment Network (IMPROVE) and the Speciati...

A smart indoor air quality sensor network

NASA Astrophysics Data System (ADS)

Wen, Jin

2006-03-01

The indoor air quality (IAQ) has an important impact on public health. Currently, the indoor air pollution, caused by gas, particle, and bio-aerosol pollutants, is considered as the top five environmental risks to public health and has an estimated cost of $2 billion/year due to medical cost and lost productivity. Furthermore, current buildings are especially vulnerable for chemical and biological warfare (CBW) agent contamination because the central air conditioning and ventilation system serve as a nature carrier to spread the released agent from one location to the whole indoor environment within a short time period. To assure the IAQ and safety for either new or existing buildings, real time comprehensive IAQ and CBW measurements are needed. With the development of new sensing technologies, economic and reliable comprehensive IAQ and CBW sensors become promising. However, few studies exist that examine the design and evaluation issues related to IAQ and CBW sensor network. In this paper, relevant research areas including IAQ and CBW sensor development, demand control ventilation, indoor CBW sensor system design, and sensor system design for other areas such as water system protection, fault detection and diagnosis, are reviewed and summarized. Potential research opportunities for IAQ and CBW sensor system design and evaluation are discussed.

High-throughput liquid-absorption air-sampling apparatus and methods

DOEpatents

Zaromb, Solomon

2000-01-01

A portable high-throughput liquid-absorption air sampler [PHTLAAS] has an asymmetric air inlet through which air is drawn upward by a small and light-weight centrifugal fan driven by a direct current motor that can be powered by a battery. The air inlet is so configured as to impart both rotational and downward components of motion to the sampled air near said inlet. The PHTLAAS comprises a glass tube of relatively small size through which air passes at a high rate in a swirling, highly turbulent motion, which facilitates rapid transfer of vapors and particulates to a liquid film covering the inner walls of the tube. The pressure drop through the glass tube is <10 cm of water, usually <5 cm of water. The sampler's collection efficiency is usually >20% for vapors or airborne particulates in the 2-3.mu. range and >50% for particles larger than 4.mu.. In conjunction with various analyzers, the PHTLAAS can serve to monitor a variety of hazardous or illicit airborne substances, such as lead-containing particulates, tritiated water vapor, biological aerosols, or traces of concealed drugs or explosives.

Carter Carburetor Weekly Air Monitoring & Sampling Report - November 30, 2015 – December 6, 2015

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Carter Carburetor Weekly Air Monitoring & Sampling Report - October 26, 2015 – November 1, 2015

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Carter Carburetor Weekly Air Monitoring & Sampling Report - February 15, 2016 – February 21, 2016

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Carter Carburetor Weekly Air Monitoring & Sampling Report - October 12, 2015 – October 18, 2015

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Carter Carburetor Weekly Air Monitoring & Sampling Report - November 23, 2015 – November 29, 2015

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Carter Carburetor Weekly Air Monitoring & Sampling Report - October 5, 2015 – October 11, 2015

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Carter Carburetor Weekly Air Monitoring & Sampling Report - February 1, 2016 – February 7, 2016

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Carter Carburetor Weekly Air Monitoring & Sampling Report - September 28, 2015 – October 4, 2015

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Carter Carburetor Weekly Air Monitoring & Sampling Report - November 16, 2015 – November 22, 2015

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Carter Carburetor Weekly Air Monitoring & Sampling Report - November 9, 2015 – November 15, 2015

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Carter Carburetor Weekly Air Monitoring & Sampling Report - October 19, 2015 – October 25, 2015

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Carter Carburetor Weekly Air Monitoring & Sampling Report - November 2, 2015 – November 8, 2015

EPA Pesticide Factsheets

Carter Carburetor Daily Weather Conditions, Dairly Work Activities, Daily Air Monitoring and Samplying Results, Air Monitoring/Samplying Results –Station 2 Linc 126, Air Monitoring/Sampling Results- Sation 3 Linc 123, Air Monitoring/Samplying Results-Stati

Development of wireless sensor network for monitoring indoor air pollutant

NASA Astrophysics Data System (ADS)

Saad, Shaharil Mad; Shakaff, Ali Yeon Md; Saad, Abdul Rahman Mohd; Yusof @ Kamarudin, Azman Muhamad

2015-05-01

The air that we breathe with everyday contains variety of contaminants and particles. Some of these contaminants and particles are hazardous to human health. Most of the people don't realize that the content of air they being exposed to whether it was a good or bad air quality. The air quality whether in indoor or outdoor environment can be influenced by physical factors like dust particles, gaseous pollutants (including carbon dioxide, carbon monoxide and volatile organic compounds) and biological like molds and bacteria growth which largely depend on temperature and humidity condition of a room. These kinds of pollutants can affect human health, physical reaction, comfort or work performance. In this study, a wireless sensor network (WSN) monitoring system for monitor air pollutant in indoor environment was developed. The system was divided into three parts: web-based interface program, sensing module and a base station. The measured data was displayed on the web which is can be accessed by the user. The result shows that the overall measured parameters were meet the acceptable limit, requirement and criteria of indoor air pollution inside the building. The research can be used to improve the indoor air quality level in order to create a comfortable working and healthy environment for the occupants inside the building.

Probabilistic inference using linear Gaussian importance sampling for hybrid Bayesian networks

NASA Astrophysics Data System (ADS)

Sun, Wei; Chang, K. C.

2005-05-01

Probabilistic inference for Bayesian networks is in general NP-hard using either exact algorithms or approximate methods. However, for very complex networks, only the approximate methods such as stochastic sampling could be used to provide a solution given any time constraint. There are several simulation methods currently available. They include logic sampling (the first proposed stochastic method for Bayesian networks, the likelihood weighting algorithm) the most commonly used simulation method because of its simplicity and efficiency, the Markov blanket scoring method, and the importance sampling algorithm. In this paper, we first briefly review and compare these available simulation methods, then we propose an improved importance sampling algorithm called linear Gaussian importance sampling algorithm for general hybrid model (LGIS). LGIS is aimed for hybrid Bayesian networks consisting of both discrete and continuous random variables with arbitrary distributions. It uses linear function and Gaussian additive noise to approximate the true conditional probability distribution for continuous variable given both its parents and evidence in a Bayesian network. One of the most important features of the newly developed method is that it can adaptively learn the optimal important function from the previous samples. We test the inference performance of LGIS using a 16-node linear Gaussian model and a 6-node general hybrid model. The performance comparison with other well-known methods such as Junction tree (JT) and likelihood weighting (LW) shows that LGIS-GHM is very promising.

Air Sampling Logbook of Region 4 Yellow Bluff Air Study Wilcox County, Alabama SESD Project Identification Number:11-0068

EPA Pesticide Factsheets

Contains the Air Sampling Logbook between 1-24-2011 thru 1-28-2011 from the Region 4 Yellow Bluff Air Study Wilcox County, Alabama SESD Project Identification Number:11-0068 November 2010-December 2010

Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial, California, USA.

PubMed

Carvlin, Graeme N; Lugo, Humberto; Olmedo, Luis; Bejarano, Ester; Wilkie, Alexa; Meltzer, Dan; Wong, Michelle; King, Galatea; Northcross, Amanda; Jerrett, Michael; English, Paul B; Hammond, Donald; Seto, Edmund

2017-12-01

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM 2.5 and PM 10 (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R 2 for converted hourly averaged Dylos mass measurements versus a PM 2.5 BAM was 0.79 and that versus a PM 10 BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM 2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R 2 = 0.35-0.81). The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on

Simulating and explaining passive air sampling rates for semi-volatile compounds on polyurethane foam passive samplers

PubMed Central

Petrich, Nicholas T.; Spak, Scott N.; Carmichael, Gregory R.; Hu, Dingfei; Martinez, Andres; Hornbuckle, Keri C.

2013-01-01

Passive air samplers (PAS) including polyurethane foam (PUF) are widely deployed as an inexpensive and practical way to sample semi-volatile pollutants. However, concentration estimates from PAS rely on constant empirical mass transfer rates, which add unquantified uncertainties to concentrations. Here we present a method for modeling hourly sampling rates for semi-volatile compounds from hourly meteorology using first-principle chemistry, physics, and fluid dynamics, calibrated from depuration experiments. This approach quantifies and explains observed effects of meteorology on variability in compound-specific sampling rates and analyte concentrations; simulates nonlinear PUF uptake; and recovers synthetic hourly concentrations at a reference temperature. Sampling rates are evaluated for polychlorinated biphenyl congeners at a network of Harner model samplers in Chicago, Illinois during 2008, finding simulated average sampling rates within analytical uncertainty of those determined from loss of depuration compounds, and confirming quasi-linear uptake. Results indicate hourly, daily and interannual variability in sampling rates, sensitivity to temporal resolution in meteorology, and predictable volatility-based relationships between congeners. We quantify importance of each simulated process to sampling rates and mass transfer and assess uncertainty contributed by advection, molecular diffusion, volatilization, and flow regime within the PAS, finding PAS chamber temperature contributes the greatest variability to total process uncertainty (7.3%). PMID:23837599

Forecasting daily source air quality using multivariate statistical analysis and radial basis function networks.

PubMed

Sun, Gang; Hoff, Steven J; Zelle, Brian C; Nelson, Minda A

2008-12-01

It is vital to forecast gas and particle matter concentrations and emission rates (GPCER) from livestock production facilities to assess the impact of airborne pollutants on human health, ecological environment, and global warming. Modeling source air quality is a complex process because of abundant nonlinear interactions between GPCER and other factors. The objective of this study was to introduce statistical methods and radial basis function (RBF) neural network to predict daily source air quality in Iowa swine deep-pit finishing buildings. The results show that four variables (outdoor and indoor temperature, animal units, and ventilation rates) were identified as relative important model inputs using statistical methods. It can be further demonstrated that only two factors, the environment factor and the animal factor, were capable of explaining more than 94% of the total variability after performing principal component analysis. The introduction of fewer uncorrelated variables to the neural network would result in the reduction of the model structure complexity, minimize computation cost, and eliminate model overfitting problems. The obtained results of RBF network prediction were in good agreement with the actual measurements, with values of the correlation coefficient between 0.741 and 0.995 and very low values of systemic performance indexes for all the models. The good results indicated the RBF network could be trained to model these highly nonlinear relationships. Thus, the RBF neural network technology combined with multivariate statistical methods is a promising tool for air pollutant emissions modeling.

Chemical reactivities of ambient air samples in three Southern California communities

PubMed Central

Eiguren-Fernandez, Arantza; Di Stefano, Emma; Schmitz, Debra A.; Guarieiro, Aline Lefol Nani; Salinas, Erika M.; Nasser, Elina; Froines, John R.; Cho, Arthur K.

2015-01-01

The potential adverse health effects of PM2.5 and vapor samples from three communities that neighbor railyards, Commerce (CM), Long Beach (LB), and San Bernardino (SB), were assessed by determination of chemical reactivities attributed to the induction of oxidative stress by air pollutants. The assays used were dithiothreitol (DTT) and dihydrobenzoic acid (DHBA) based procedures for prooxidant content and a glyceraldehyde-3-phosphate dehydrogenase (GAPDH) assay for electrophiles. Prooxidants and electrophiles have been proposed as the reactive chemical species responsible for the induction of oxidative stress by air pollution mixtures. The PM2.5 samples from CM and LB sites showed seasonal differences in reactivities with higher levels in the winter whereas the SB sample differences were reversed. The reactivities in the vapor samples were all very similar, except for the summer SB samples, which contained higher levels of both prooxidants and electrophiles. The results suggest the observed reactivities reflect general geographical differences rather than direct effects of the railyards. Distributional differences in reactivities were also observed with PM2.5 fractions containing most of the prooxidants (74–81%) and the vapor phase most of the electrophiles (82–96%). The high levels of the vapor phase electrophiles and their potential for adverse biological effects point out the importance of the vapor phase in assessing the potential health effects of ambient air. PMID:25947123

Influence of Applying Additional Forcing Fans for the Air Distribution in Ventilation Network

NASA Astrophysics Data System (ADS)

Szlązak, Nikodem; Obracaj, Dariusz; Korzec, Marek

2016-09-01

Mining progress in underground mines cause the ongoing movement of working areas. Consequently, it becomes necessary to adapt the ventilation network of a mine to direct airflow into newly-opened districts. For economic reasons, opening new fields is often achieved via underground workings. Length of primary intake and return routes increases and also increases the total resistance of a complex ventilation network. The development of a subsurface structure can make it necessary to change the air distribution in a ventilation network. Increasing airflow into newly-opened districts is necessary. In mines where extraction does not entail gas-related hazards, there is possibility of implementing a push-pull ventilation system in order to supplement airflows to newly developed mining fields. This is achieved by installing subsurface fan stations with forcing fans at the bottom of downcast shaft. In push-pull systems with multiple main fans, it is vital to select forcing fans with characteristic curves matching those of the existing exhaust fans to prevent undesirable mutual interaction. In complex ventilation networks it is necessary to calculate distribution of airflow (especially in networks with a large number of installed fans). In the article the influence of applying additional forcing fans for the air distribution in ventilation network for underground mine were considered. There are also analysed the extent of overpressure caused by the additional forcing fan in branches of the ventilation network (the operating range of additional forcing fan). Possibilities of increasing airflow rate in working areas were conducted.

The LAAS network observation for studying time correlations in extensive air showers

NASA Astrophysics Data System (ADS)

Ochi, Nobuaki; Iyono, A.; Kimura, Hitoomi; Konishi, Takeharu; Nakamura, Toru; Nakatsuka, Takao; Ohara, Soji; Ohmori, Nobuharu; Saito, Katsuhiko; Takahashi, Nobusuke; Tsuji, Shuhei; Wada, Tomonori; Yamamoto, Isao; Yamashita, Yoshihiko; Yanagimoto, Yukio

2003-02-01

The Large Area Air Shower (LAAS) group has been performing a network observation of extensive air showers (EAS) since 1996 in Japan. Ten compact EAS arrays are operating simultaneously at distant stations (up to ≍1000 km) and detecting EAS with mean energy of ≍1015 eV. Each station has 4--12 scintillation counters and a Global Positioning System (GPS), which provides time stamps of EAS triggers with an accuracy of 1μs. As a consequence of the comparable time stamps, uniformly-adjusted detectors and a standardized data format among all stations, we can treat the independent observations as a gigantic EAS detector system as a whole. The primary purpose of the network observation is to study large-scale correlations in ultra-high-energy cosmic rays. On the other hand, three nearby stations within 1~km distance at Okayama area have a possibility to detect extremely-high-energy EAS (≍1019 eV) as coincident triggers of the three stations. The present status of the network and some results from computer simulations are reported here.

Curve fitting air sample filter decay curves to estimate transuranic content.

PubMed

Hayes, Robert B; Chiou, Hung Cheng

2004-01-01

By testing industry standard techniques for radon progeny evaluation on air sample filters, a new technique is developed to evaluate transuranic activity on air filters by curve fitting the decay curves. The industry method modified here is simply the use of filter activity measurements at different times to estimate the air concentrations of radon progeny. The primary modification was to not look for specific radon progeny values but rather transuranic activity. By using a method that will provide reasonably conservative estimates of the transuranic activity present on a filter, some credit for the decay curve shape can then be taken. By carrying out rigorous statistical analysis of the curve fits to over 65 samples having no transuranic activity taken over a 10-mo period, an optimization of the fitting function and quality tests for this purpose was attained.

Air-sampling inlet contamination by aircraft emissions on the NASA CV-990 aircraft

NASA Technical Reports Server (NTRS)

Condon, E. P.; Vedder, J. F.

1984-01-01

Results of an experimental investigation of the contamination of air sampling inlets by aircraft emissions from the NASA CV-990 research aircraft are presented. This four-engine jet aircraft is a NASA facility used for many different atmospheric and meteorological experiments, as well as for developing spacecraft instrumentation for remote measurements. Our investigations were performed to provide information on which to base the selection of sampling locations for a series of multi-instrument missions for measuring tropospheric trace gases. The major source of contamination is the exhaust from the jet engines, which generate many of the same gases that are of interest in atmospheric chemistry, as well as other gases that may interfere with sampling measurements. The engine exhaust contains these gases in mixing ratios many orders of magnitude greater than those that occur in the clean atmosphere which the missions seek to quantify. Pressurized samples of air were collected simultaneously from a scoop located forward of the engines to represent clean air and from other multiport scoops at various aft positions on the aircraft. The air samples were analyzed in the laboratory by gas chromatography for carbon monoxide, an abundant combustion by-product. Data are presented for various scoop locations under various flight conditions.

A new technique for preliminary estimates of TRU activity on air sample filters and radiological smears.

PubMed

Hayes, Robert

2004-10-01

In most nuclear facilities, fixed air samplers and sometimes portable air samplers are used where some probability of a release exists but is not expected, and so the added expense and effort of using a continuous air monitor is not deemed justified. When a release is suspected, naturally occurring radioactive material buildup on the filter typically prevents any quantitative measurements within the first day or so. Likewise, outdoor air measurements suffer from the same limitations (such as those taken during the Los Alamos fires) and so any rapid quantifiable measurements of fixed air sampler/portable air sampler filters which are technically defendable (even though conservative) are of use. The technique presented here is only intended for use in routine health physics survey applications and does not presently appear to be appropriate for sub pico Curie activity determinations. This study evaluates the utility of using a portable continuous air monitor as an alpha spectrometer to make transuranic activity determinations of samples using both the built in algorithm for air monitoring and a simple region of interest analysis. All samples evaluated were from air sample filters taken using a portable air sampler. Samples were taken over many months to quantify effects from natural variation in radon progeny activity distributions.

Evaluation of membrane filter field monitors for microbiological air sampling

NASA Technical Reports Server (NTRS)

Fields, N. D.; Oxborrow, G. S.; Puleo, J. R.; Herring, C. M.

1974-01-01

Due to area constraints encountered in assembly and testing areas of spacecraft, the membrane filter field monitor (MF) and the National Aeronautics and Space Administration-accepted Reyniers slit air sampler were compared for recovery of airborne microbial contamination. The intramural air in a microbiological laboratory area and a clean room environment used for the assembly and testing of the Apollo spacecraft was studied. A significantly higher number of microorganisms was recovered by the Reyniers sampler. A high degree of consistency between the two sampling methods was shown by a regression analysis, with a correlation coefficient of 0.93. The MF samplers detected 79% of the concentration measured by the Reyniers slit samplers. The types of microorganisms identified from both sampling methods were similar.

The NYC native air sampling pilot project: using HVAC filter data for urban biological incident characterization.

PubMed

Ackelsberg, Joel; Leykam, Frederic M; Hazi, Yair; Madsen, Larry C; West, Todd H; Faltesek, Anthony; Henderson, Gavin D; Henderson, Christopher L; Leighton, Terrance

2011-09-01

Native air sampling (NAS) is distinguished from dedicated air sampling (DAS) devices (eg, BioWatch) that are deployed to detect aerosol disseminations of biological threat agents. NAS uses filter samples from heating, ventilation, and air conditioning (HVAC) systems in commercial properties for environmental sampling after DAS detection of biological threat agent incidents. It represents an untapped, scientifically sound, efficient, widely distributed, and comparably inexpensive resource for postevent environmental sampling. Calculations predict that postevent NAS would be more efficient than environmental surface sampling by orders of magnitude. HVAC filter samples could be collected from pre-identified surrounding NAS facilities to corroborate the DAS alarm and delineate the path taken by the bioaerosol plume. The New York City (NYC) Native Air Sampling Pilot Project explored whether native air sampling would be acceptable to private sector stakeholders and could be implemented successfully in NYC. Building trade associations facilitated outreach to and discussions with property owners and managers, who expedited contact with building managers of candidate NAS properties that they managed or owned. Nominal NAS building requirements were determined; procedures to identify and evaluate candidate NAS facilities were developed; data collection tools and other resources were designed and used to expedite candidate NAS building selection and evaluation in Manhattan; and exemplar environmental sampling playbooks for emergency responders were completed. In this sample, modern buildings with single or few corporate tenants were the best NAS candidate facilities. The Pilot Project successfully demonstrated that in one urban setting a native air sampling strategy could be implemented with effective public-private collaboration.

Random sampling of elementary flux modes in large-scale metabolic networks.

PubMed

Machado, Daniel; Soons, Zita; Patil, Kiran Raosaheb; Ferreira, Eugénio C; Rocha, Isabel

2012-09-15

The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set. Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks. Source code for a cross-platform implementation in Python is freely available at http://code.google.com/p/emsampler. dmachado@deb.uminho.pt Supplementary data are available at Bioinformatics online.

Determination of beryllium concentrations in UK ambient air

NASA Astrophysics Data System (ADS)

Goddard, Sharon L.; Brown, Richard J. C.; Ghatora, Baljit K.

2016-12-01

Air quality monitoring of ambient air is essential to minimise the exposure of the general population to toxic substances such as heavy metals, and thus the health risks associated with them. In the UK, ambient air is already monitored under the UK Heavy Metals Monitoring Network for a number of heavy metals, including nickel (Ni), arsenic (As), cadmium (Cd) and lead (Pb) to ensure compliance with legislative limits. However, the UK Expert Panel on Air Quality Standards (EPAQS) has highlighted a need to limit concentrations of beryllium (Be) in air, which is not currently monitored, because of its toxicity. The aim of this work was to analyse airborne particulate matter (PM) sampled onto filter papers from the UK Heavy Metals Monitoring Network for quantitative, trace level beryllium determination and compare the results to the guideline concentration specified by EPAQS. Samples were prepared by microwave acid digestion in a matrix of 2% sulphuric acid and 14% nitric acid, verified by the use of Certified Reference Materials (CRMs). The digested samples were then analysed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The filters from the UK Heavy Metals Monitoring Network were tested using this procedure and the average beryllium concentration across the network for the duration of the study period was 7.87 pg m-3. The highest site average concentration was 32.0 pg m-3 at Scunthorpe Low Santon, which is significantly lower than levels that are thought to cause harm. However the highest levels were observed at sites monitoring industrial point sources, indicating that beryllium is being used and emitted, albeit at very low levels, from these point sources. Comparison with other metals concentrations and data from the UK National Atmospheric Emissions Inventory suggests that current emissions of beryllium may be significantly overestimated.

Comparison of indoor air sampling and dust collection methods for fungal exposure assessment using quantitative PCR.

PubMed

Cox, Jennie; Indugula, Reshmi; Vesper, Stephen; Zhu, Zheng; Jandarov, Roman; Reponen, Tiina

2017-10-18

Evaluating fungal contamination indoors is complicated because of the many different sampling methods utilized. In this study, fungal contamination was evaluated using five sampling methods and four matrices for results. The five sampling methods were a 48 hour indoor air sample collected with a Button™ inhalable aerosol sampler and four types of dust samples: a vacuumed floor dust sample, newly settled dust collected for four weeks onto two types of electrostatic dust cloths (EDCs) in trays, and a wipe sample of dust from above floor surfaces. The samples were obtained in the bedrooms of asthmatic children (n = 14). Quantitative polymerase chain reaction (qPCR) was used to analyze the dust and air samples for the 36 fungal species that make up the Environmental Relative Moldiness Index (ERMI). The results from the samples were compared by four matrices: total concentration of fungal cells, concentration of fungal species associated with indoor environments, concentration of fungal species associated with outdoor environments, and ERMI values (or ERMI-like values for air samples). The ERMI values for the dust samples and the ERMI-like values for the 48 hour air samples were not significantly different. The total cell concentrations of the 36 species obtained with the four dust collection methods correlated significantly (r = 0.64-0.79, p < 0.05), with the exception of the vacuumed floor dust and newly settled dust. In addition, fungal cell concentrations of indoor associated species correlated well between all four dust sampling methods (r = 0.68-0.86, p < 0.01). No correlation was found between the fungal concentrations in the air and dust samples primarily because of differences in concentrations of Cladosporium cladosporioides Type 1 and Epicoccum nigrum. A representative type of dust sample and a 48 hour air sample might both provide useful information about fungal exposures.

Applicability of canisters for sample storage in the determination of hazardous air pollutants

NASA Astrophysics Data System (ADS)

Kelly, Thomas J.; Holdren, Michael W.

This paper evaluates the applicability of canisters for storage of air samples containing volatile organic compounds listed among the 189 hazardous air pollutants (HAPs) in the 1990 U.S. Clean Air Act Amendments. Nearly 100 HAPs have sufficient vapor pressure to be considered volatile compounds. Of those volatile organic HAPs, 52 have been tested previously for stability during storage in canisters. The published HAP stability studies are reviewed, illustrating that for most of the 52 HAPs tested, canisters are an effective sample storage approach. However, the published stability studies used a variety of canister types and test procedures, and generally considered only a few compounds in a very small set of canisters. A comparison of chemical and physical properties of the HAPs has also been conducted, to evaluate the applicability of canister sampling for other HAPs, for which canister stability testing has never been conducted. Of 45 volatile HAPs never tested in canisters, this comparison identifies nine for which canisters should be effective, and 17 for which canisters are not likely to be effective. For the other 19 HAPs, no clear decision can be reached on the likely applicability of air sample storage in canisters.

Volatile organic compounds: sampling methods and their worldwide profile in ambient air.

PubMed

Kumar, Anuj; Víden, Ivan

2007-08-01

The atmosphere is a particularly difficult analytical system because of the very low levels of substances to be analysed, sharp variations in pollutant levels with time and location, differences in wind, temperature and humidity. This makes the selection of an efficient sampling technique for air analysis a key step to reliable results. Generally, methods for volatile organic compounds sampling include collection of the whole air or preconcentration of samples on adsorbents. All the methods vary from each other according to the sampling technique, type of sorbent, method of extraction and identification technique. In this review paper we discuss various important aspects for sampling of volatile organic compounds by the widely used and advanced sampling methods. Characteristics of various adsorbents used for VOCs sampling are also described. Furthermore, this paper makes an effort to comprehensively review the concentration levels of volatile organic compounds along with the methodology used for analysis, in major cities of the world.

A Low Cost High Density Sensor Network for Air Quality at London Heathrow Airport

NASA Astrophysics Data System (ADS)

Bright, V.; Mead, M. I.; Popoola, O. A.; Baron, R. P.; Saffell, J.; Stewart, G.; Kaye, P.; Jones, R.

2012-12-01

Atmospheric composition within urban areas has a direct effect on the air quality of an environment in which a large majority of people live and work. Atmospheric pollutants including ozone (O3), nitrogen dioxide (NO2), volatile organic compounds (VOCs) and particulate matter (PM) can have a significant effect on human health. As such it is important to determine the potential exposure of individuals to these atmospheric constituents and investigate the processes that lead to the degradation of air quality within the urban environment. Whilst modelled pollutant levels on the local scale often suggest high degrees of spatial and temporal variability, the relatively sparse fixed site automated urban networks only provide low spatial resolution data that do not appear adequate in detecting such small scale variability. In this paper we demonstrate that measurements can now be made using networks of low-cost sensors that utilise a variety of techniques, including electrochemical and optical, to measure concentrations of atmospheric species. Once equipped with GPS and GPRS to determine position and transmit data respectively, these networks have the potential to provide valuable insights into pollutant variability inherent on the local or micro-scale. The methodology has been demonstrated successfully in field campaigns carried out in cities including London and Valencia, and is now being deployed as part of the Sensor Networks for Air Quality currently deployed at London Heathrow airport (SNAQ-Heathrow) which is outlined in the partner paper presented by Mead et al. (this conference). The SNAQ-Heathrow network of 50 sensor nodes will provide an unprecedented data set that includes measurements of O3, NO, NO2, CO, CO2, SO2, total VOCs, size-speciated PM as well as meteorological variables that include temperature, relative humidity, wind speed and direction. This network will provide high temporal (20 second intervals) and spatial (50 sites within the airport area

Polyurethane foam (PUF) disks passive air samplers: wind effect on sampling rates.

PubMed

Tuduri, Ludovic; Harner, Tom; Hung, Hayley

2006-11-01

Different passive sampler housings were evaluated for their wind dampening ability and how this might translate to variability in sampler uptake rates. Polyurethane foam (PUF) disk samplers were used as the sampling medium and were exposed to a PCB-contaminated atmosphere in a wind tunnel. The effect of outside wind speed on PUF disk sampling rates was evaluated by exposing polyurethane foam (PUF) disks to a PCB-contaminated air stream in a wind tunnel over air velocities in the range 0 to 1.75 m s-1. PUF disk sampling rates increased gradually over the range 0-0.9 m s-1 at approximately 4.5-14.6 m3 d-1 and then increased sharply to approximately 42 m3 d-1 at approximately 1.75 m s-1 (sum of PCBs). The results indicate that for most field deployments the conventional 'flying saucer' housing adequately dampens the wind effect and will yield approximately time-weighted air concentrations.

Sample EP Flow Analysis of Severely Damaged Networks

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

Werley, Kenneth Alan; McCown, Andrew William

These are slides for a presentation at the working group meeting of the WESC SREMP Software Product Integration Team on sample EP flow analysis of severely damaged networks. The following topics are covered: ERCOT EP Transmission Model; Zoomed in to Houston and Overlaying StreetAtlas; EMPACT Solve/Dispatch/Shedding Options; QACS BaseCase Power Flow Solution; 3 Substation Contingency; Gen. & Load/100 Optimal Dispatch; Dispatch Results; Shed Load for Low V; Network Damage Summary; Estimated Service Areas (Potential); Estimated Outage Areas (potential).

Performance evaluation of an importance sampling technique in a Jackson network

NASA Astrophysics Data System (ADS)

brahim Mahdipour, E.; Masoud Rahmani, Amir; Setayeshi, Saeed

2014-03-01

Importance sampling is a technique that is commonly used to speed up Monte Carlo simulation of rare events. However, little is known regarding the design of efficient importance sampling algorithms in the context of queueing networks. The standard approach, which simulates the system using an a priori fixed change of measure suggested by large deviation analysis, has been shown to fail in even the simplest network settings. Estimating probabilities associated with rare events has been a topic of great importance in queueing theory, and in applied probability at large. In this article, we analyse the performance of an importance sampling estimator for a rare event probability in a Jackson network. This article carries out strict deadlines to a two-node Jackson network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We have estimated the probability of network blocking for various sets of parameters, and also the probability of missing the deadline of customers for different loads and deadlines. We have finally shown that the probability of total population overflow may be affected by various deadline values, service rates and arrival rates.

Permeability of gypsum samples dehydrated in air

NASA Astrophysics Data System (ADS)

Milsch, Harald; Priegnitz, Mike; Blöcher, Guido

2011-09-01

We report on changes in rock permeability induced by devolatilization reactions using gypsum as a reference analog material. Cylindrical samples of natural alabaster were dehydrated in air (dry) for up to 800 h at ambient pressure and temperatures between 378 and 423 K. Subsequently, the reaction kinetics, so induced changes in porosity, and the concurrent evolution of sample permeability were constrained. Weighing the heated samples in predefined time intervals yielded the reaction progress where the stoichiometric mass balance indicated an ultimate and complete dehydration to anhydrite regardless of temperature. Porosity showed to continuously increase with reaction progress from approximately 2% to 30%, whilst the initial bulk volume remained unchanged. Within these limits permeability significantly increased with porosity by almost three orders of magnitude from approximately 7 × 10-19 m2 to 3 × 10-16 m2. We show that - when mechanical and hydraulic feedbacks can be excluded - permeability, reaction progress, and porosity are related unequivocally.

Influences of sampling effort on detected patterns and structuring processes of a Neotropical plant-hummingbird network.

PubMed

Vizentin-Bugoni, Jeferson; Maruyama, Pietro K; Debastiani, Vanderlei J; Duarte, L da S; Dalsgaard, Bo; Sazima, Marlies

2016-01-01

Virtually all empirical ecological interaction networks to some extent suffer from undersampling. However, how limitations imposed by sampling incompleteness affect our understanding of ecological networks is still poorly explored, which may hinder further advances in the field. Here, we use a plant-hummingbird network with unprecedented sampling effort (2716 h of focal observations) from the Atlantic Rainforest in Brazil, to investigate how sampling effort affects the description of network structure (i.e. widely used network metrics) and the relative importance of distinct processes (i.e. species abundances vs. traits) in determining the frequency of pairwise interactions. By dividing the network into time slices representing a gradient of sampling effort, we show that quantitative metrics, such as interaction evenness, specialization (H2 '), weighted nestedness (wNODF) and modularity (Q; QuanBiMo algorithm) were less biased by sampling incompleteness than binary metrics. Furthermore, the significance of some network metrics changed along the sampling effort gradient. Nevertheless, the higher importance of traits in structuring the network was apparent even with small sampling effort. Our results (i) warn against using very poorly sampled networks as this may bias our understanding of networks, both their patterns and structuring processes, (ii) encourage the use of quantitative metrics little influenced by sampling when performing spatio-temporal comparisons and (iii) indicate that in networks strongly constrained by species traits, such as plant-hummingbird networks, even small sampling is sufficient to detect their relative importance for the frequencies of interactions. Finally, we argue that similar effects of sampling are expected for other highly specialized subnetworks. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

An Architectural Concept for Intrusion Tolerance in Air Traffic Networks

NASA Technical Reports Server (NTRS)

Maddalon, Jeffrey M.; Miner, Paul S.

2003-01-01

The goal of an intrusion tolerant network is to continue to provide predictable and reliable communication in the presence of a limited num ber of compromised network components. The behavior of a compromised network component ranges from a node that no longer responds to a nod e that is under the control of a malicious entity that is actively tr ying to cause other nodes to fail. Most current data communication ne tworks do not include support for tolerating unconstrained misbehavio r of components in the network. However, the fault tolerance communit y has developed protocols that provide both predictable and reliable communication in the presence of the worst possible behavior of a limited number of nodes in the system. One may view a malicious entity in a communication network as a node that has failed and is behaving in an arbitrary manner. NASA/Langley Research Center has developed one such fault-tolerant computing platform called SPIDER (Scalable Proces sor-Independent Design for Electromagnetic Resilience). The protocols and interconnection mechanisms of SPIDER may be adapted to large-sca le, distributed communication networks such as would be required for future Air Traffic Management systems. The predictability and reliabi lity guarantees provided by the SPIDER protocols have been formally v erified. This analysis can be readily adapted to similar network stru ctures.

Optimal redistribution of an urban air quality monitoring network using atmospheric dispersion model and genetic algorithm

NASA Astrophysics Data System (ADS)

Hao, Yufang; Xie, Shaodong

2018-03-01

Air quality monitoring networks play a significant role in identifying the spatiotemporal patterns of air pollution, and they need to be deployed efficiently, with a minimum number of sites. The revision and optimal adjustment of existing monitoring networks is crucial for cities that have undergone rapid urban expansion and experience temporal variations in pollution patterns. The approach based on the Weather Research and Forecasting-California PUFF (WRF-CALPUFF) model and genetic algorithm (GA) was developed to design an optimal monitoring network. The maximization of coverage with minimum overlap and the ability to detect violations of standards were developed as the design objectives for redistributed networks. The non-dominated sorting genetic algorithm was applied to optimize the network size and site locations simultaneously for Shijiazhuang city, one of the most polluted cities in China. The assessment on the current network identified the insufficient spatial coverage of SO2 and NO2 monitoring for the expanding city. The optimization results showed that significant improvements were achieved in multiple objectives by redistributing the original network. Efficient coverage of the resulting designs improved to 60.99% and 76.06% of the urban area for SO2 and NO2, respectively. The redistributing design for multi-pollutant including 8 sites was also proposed, with the spatial representation covered 52.30% of the urban area and the overlapped areas decreased by 85.87% compared with the original network. The abilities to detect violations of standards were not improved as much as the other two objectives due to the conflicting nature between the multiple objectives. Additionally, the results demonstrated that the algorithm was slightly sensitive to the parameter settings, with the number of generations presented the most significant effect. Overall, our study presents an effective and feasible procedure for air quality network optimization at a city scale.

Use of randomized sampling for analysis of metabolic networks.

PubMed

Schellenberger, Jan; Palsson, Bernhard Ø

2009-02-27

Genome-scale metabolic network reconstructions in microorganisms have been formulated and studied for about 8 years. The constraint-based approach has shown great promise in analyzing the systemic properties of these network reconstructions. Notably, constraint-based models have been used successfully to predict the phenotypic effects of knock-outs and for metabolic engineering. The inherent uncertainty in both parameters and variables of large-scale models is significant and is well suited to study by Monte Carlo sampling of the solution space. These techniques have been applied extensively to the reaction rate (flux) space of networks, with more recent work focusing on dynamic/kinetic properties. Monte Carlo sampling as an analysis tool has many advantages, including the ability to work with missing data, the ability to apply post-processing techniques, and the ability to quantify uncertainty and to optimize experiments to reduce uncertainty. We present an overview of this emerging area of research in systems biology.

Development of a unique multi-contaminant air sampling device for a childhood asthma cohort in an agricultural environment.

PubMed

Armstrong, Jenna L; Fitzpatrick, Cole F; Loftus, Christine T; Yost, Michael G; Tchong-French, Maria; Karr, Catherine J

2013-09-01

This research describes the design, deployment, performance, and acceptability of a novel outdoor active air sampler to provide simultaneous measurements of multiple contaminants at timed intervals for the Aggravating Factors of Asthma in Rural Environment (AFARE) study-a longitudinal cohort of 50 children in Yakima Valley, Washington. The sampler was constructed of multiple sampling media connected to individual critical orifices and a rotary vane vacuum pump. It was connected to a timed control valve system to collect 24 hours samples every six days over 18 months. We describe a spatially representative approach with both quantitative and qualitative location criteria to deploy a network of 14 devices at participant residences in a rural region (20 × 60 km). Overall the sampler performed well, as the concurrent mean sample flow rates were within or above the ranges of recommended sampling rates for each exposure metric of interest. Acceptability was high among the study population of Hispanic farmworker participant households. The sampler design may prove useful for future urban and rural community-based studies with aims at collecting multiple contaminant data during specific time periods.

An Autosampler and Field Sample Carrier for Maximizing Throughput Using an Open-Air, Surface Sampling Ion Source for MS

EPA Science Inventory

A recently developed, commercially available, open-air, surface sampling ion source for mass spectrometers provides individual analyses in several seconds. To realize its full throughput potential, an autosampler and field sample carrier were designed and built. The autosampler ...

Assessing polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans in air across Latin American countries using polyurethane foam disk passive air samplers.

PubMed

Schuster, Jasmin K; Harner, Tom; Fillmann, Gilberto; Ahrens, Lutz; Altamirano, Jorgelina C; Aristizábal, Beatriz; Bastos, Wanderley; Castillo, Luisa Eugenia; Cortés, Johana; Fentanes, Oscar; Gusev, Alexey; Hernandez, Maricruz; Ibarra, Martín Villa; Lana, Nerina B; Lee, Sum Chi; Martínez, Ana Patricia; Miglioranza, Karina S B; Puerta, Andrea Padilla; Segovia, Federico; Siu, May; Tominaga, Maria Yumiko

2015-03-17

A passive air sampling network has been established to investigate polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) at Global Atmospheric Passive Sampling (GAPS) sites and six additional sites in the Group of Latin American and Caribbean Countries (GRULAC) region. The air sampling network covers background, agricultural, rural, and urban sites. Samples have been collected over four consecutive periods of 6 months, which started in January 2011 [period 1 (January to June 2011), period 2 (July to December 2011), period 3 (January to June 2012), and period 4 (July 2012 to January 2013)]. Results show that (i) the GAPS passive samplers (PUF disk type) and analytical methodology are adequate for measuring PCDD/F burdens in air and (ii) PCDD/F concentrations in air across the GRULAC region are widely variable by almost 2 orders of magnitude. The highest concentrations in air of Σ4-8PCDD/Fs were found at the urban site São Luis (Brazil, UR) (i.e., 2560 fg/m3) followed by the sites in São Paulo (Brazil, UR), Mendoza (Argentina, RU), and Sonora (Mexico, AG) with values of 1690, 1660, and 1610 fg/m3, respectively. Very low concentrations of PCDD/Fs in air were observed at the background site Tapanti (Costa Rica, BA), 10.8 fg/m3. This variability is attributed to differences in site characteristics and potential local/regional sources as well as meteorological influences. The measurements of PCDD/Fs in air agree well with model-predicted concentrations performed using the Global EMEP Multimedia Modeling System (GLEMOS) and emission scenario constructed on the basis of the UNEP Stockholm Convention inventory of dioxin and furan emissions.

[The Competence Network for HIV/AIDS. Data, Samples, Facts].

PubMed

Michalik, Claudia; Skaletz-Rorowski, Adriane; Brockmeyer, Norbert H

2016-04-01

With funding for the Competence Networks in Medicine from the Federal Ministry of Education and Research, the Competence Network for HIV/AIDS (KompNet HIV/AIDS) was established as an interdisciplinary research association. Essential working groups were incorporated all over Germany, which are active in clinical and basic HIV/AIDS research. After successful establishment, providing research infrastructure for national and international cooperation in the field of HIV/AIDS was the focus of the network. By bringing together research activities, preconditions are created for improving HIV infection treatment and increasing life expectancy of HIV-infected patients. The members of KompNet HIV/AIDS are HIV experts from university clinics, HIV physicians, patient representatives, as well as national reference centers. As a scientific research basis, the network established an HIV patient cohort. Clinical and sociodemographic data of HIV patients were documented biannually and complemented by serum and DNA-samples collected twice per year. Furthermore, a child cohort was set up. Within the KompNet HIV/AIDS, a research infrastructure for HIV was established for internal, external as well international scientists. Within the HIV cohort a total of 16,500 patients are documented. The associated biobank comprises ~ 56,000 serum samples and ~ 16,000 DNA samples. The child cohort consists of 647 HIV-exposed and 230 infected children. The KompNet HIV/AIDS cohorts became an important partner in several international collaborations. Nevertheless, the maintenance of such infrastructures without public funding is a challenge.

Determination of methyl bromide in air samples by headspace gas chromatography

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

Woodrow, J.E.; McChesney, M.M.; Seiber, J.N.

1988-03-01

Methyl bromide is extensively used in agriculture (4 x 10/sup 6/ kg for 1985 in California alone as a fumigant to control nematodes, weeds, and fungi in soil and insect pests in harvested grains and nuts. Given its low boiling point (3.8/sup 0/C) and high vapor pressure (approx. 1400 Torr at 20/sup 0/C), methyl bromide will readily diffuse if not rigorously contained. Methods for determining methyl bromide and other halocarbons in air vary widely. A common practice is to trap the material from air on an adsorbent, such as polymeric resins, followed by thermal desorption either directly into the analyticalmore » instrumentation or after intermediary cryofocusing. While in some cases analytical detection limits were reasonable (parts per million range), many of the published methods were labor intensive and required special handling techniques that precluded high sample throughput. They describe here a method for the sampling and analysis of airborne methyl bromide that was designed to handle large numbers of samples through automating some critical steps of the analysis. The result was a method that allowed around-the-clock operation with a minimum of operator attention. Furthermore, the method was not specific to methyl bromide and could be used to determine other halocarbons in air.« less

Comparison of mold concentrations quantified by MSQPCR in indoor and outdoor air sampled simultaneously

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

Meklin, Teija; Reponen, Tina; McKinstry, Craig A.

Mold specific quantitative PCR (MSQPCR) was used to measure the concentrations of 36 mold species in dust and in indoor and in outdoor air samples that were taken simultaneously in 17 homes in Cincinnati with no-known water damage. The total spore concentrations in the indoor (I) and outdoor (O) air samples were statistically significantly different and the concentrations in the three sample types of many of the individual species were significantly different (p < 0.05 based on the Wilcoxon Signed Rank Test). The I/O ratios of the averages or geometric means of the individual species were generally less than 1;more » but these I/O ratios were quite variable ranging from 0.03 for A. sydowii to 1.2 for Acremonium strictum. There were no significant correlations for the 36 specific mold concentrations between the dust samples and the indoor or outdoor air samples (based on the Spearman’s Rho test). The indoor and outdoor air concentrations of 32 of the species were not correlated. Only Aspergillus penicillioides, C. cladosporioides types 1 and 2 and C. herbarum had sufficient data to estimate a correlation at rho > 0.5 with signicance (p < 0.05) In six of these homes, a previous dust sample had been collected and analyzed 2 years earlier. The ERMI© values for the dust samples taken in the same home two years apart were not significantly different (p=0.22) based on Wilcoxon Signed Rank Test.« less

Assessment of an air pollution monitoring network to generate urban air pollution maps using Shannon information index, fuzzy overlay, and Dempster-Shafer theory, A case study: Tehran, Iran

NASA Astrophysics Data System (ADS)

Pahlavani, Parham; Sheikhian, Hossein; Bigdeli, Behnaz

2017-10-01

Air pollution assessment is an imperative part of megacities planning and control. Hence, a new comprehensive approach for air pollution monitoring and assessment was introduced in this research. It comprises of three main sections: optimizing the existing air pollutant monitoring network, locating new stations to complete the coverage of the existing network, and finally, generating an air pollution map. In the first section, Shannon information index was used to find less informative stations to be candidate for removal. Then, a methodology was proposed to determine the areas which are not sufficiently covered by the current network. These areas are candidates for establishing new monitoring stations. The current air pollution monitoring network of Tehran was used as a case study, where the air pollution issue has been worsened due to the huge population, considerable commuters' absorption and topographic barriers. In this regard, O3, NO, NO2, NOx, CO, PM10, and PM2.5 were considered as the main pollutants of Tehran. Optimization step concluded that all the 16 active monitoring stations should be preserved. Analysis showed that about 35% of the Tehran's area is not properly covered by monitoring stations and about 30% of the area needs additional stations. The winter period in Tehran always faces the most severe air pollution in the year. Hence, to produce the air pollution map of Tehran, three-month of winter measurements of the mentioned pollutants, repeated for five years in the same period, were selected and extended to the entire area using the kriging method. Experts specified the contribution of each pollutant in overall air pollution. Experts' rankings aggregated by a fuzzy-overlay process. Resulted maps characterized the study area with crucial air pollution situation. According to the maps, more than 45% of the city area faced high pollution in the study period, while only less than 10% of the area showed low pollution. This situation confirms the need

Air exposure and sample storage time influence on hydrogen release from tungsten

NASA Astrophysics Data System (ADS)

Moshkunov, K. A.; Schmid, K.; Mayer, M.; Kurnaev, V. A.; Gasparyan, Yu. M.

2010-09-01

In investigations of hydrogen retention in first wall components the influence of the conditions of the implanted target storage prior to analysis and the storage time is often neglected. Therefore we have performed a dedicated set of experiments. The release of hydrogen from samples exposed to ambient air after irradiation was compared to samples kept in vacuum. For air exposed samples significant amounts of HDO and D 2O are detected during TDS. Additional experiments have shown that heavy water is formed by recombination of releasing D and H atoms with O on the W surface. This water formation can alter hydrogen retention results significantly, in particular - for low retention cases. In addition to the influence of ambient air exposure also the influence of storage time in vacuum was investigated. After implantation at 300 K the samples were stored in vacuum for up to 1 week during which the retained amount decreased significantly. The subsequently measured TDS spectra showed that D was lost from both the high and low energy peaks during storage at ambient temperature of ˜300 K. An attempt to simulate this release from both peaks during room temperature storage by TMAP 7 calculations showed that this effect cannot be explained by conventional diffusion/trapping models.

Sampling and Analyzing Air Pollution: An Apparatus Suitable for Use in Schools.

ERIC Educational Resources Information Center

Rockwell, Dean M.; Hansen, Tony

1994-01-01

Describes two variations of an air sampler and analyzer that are inexpensive to construct, easy to operate, and designed to be used in an educational program. Variations use vacuum cleaners and aquarium pumps, and white facial tissues serve as filters. Samples of air pollution obtained by this method may be used from early grade school to advanced…

Artificial neural networks as a useful tool to predict the risk level of Betula pollen in the air

NASA Astrophysics Data System (ADS)

Castellano-Méndez, M.; Aira, M. J.; Iglesias, I.; Jato, V.; González-Manteiga, W.

2005-05-01

An increasing percentage of the European population suffers from allergies to pollen. The study of the evolution of air pollen concentration supplies prior knowledge of the levels of pollen in the air, which can be useful for the prevention and treatment of allergic symptoms, and the management of medical resources. The symptoms of Betula pollinosis can be associated with certain levels of pollen in the air. The aim of this study was to predict the risk of the concentration of pollen exceeding a given level, using previous pollen and meteorological information, by applying neural network techniques. Neural networks are a widespread statistical tool useful for the study of problems associated with complex or poorly understood phenomena. The binary response variable associated with each level requires a careful selection of the neural network and the error function associated with the learning algorithm used during the training phase. The performance of the neural network with the validation set showed that the risk of the pollen level exceeding a certain threshold can be successfully forecasted using artificial neural networks. This prediction tool may be implemented to create an automatic system that forecasts the risk of suffering allergic symptoms.

Networking Multiple Autonomous Air and Ocean Vehicles for Oceanographic Research and Monitoring

NASA Astrophysics Data System (ADS)

McGillivary, P. A.; Borges de Sousa, J.; Rajan, K.

2013-12-01

Autonomous underwater and surface vessels (AUVs and ASVs) are coming into wider use as components of oceanographic research, including ocean observing systems. Unmanned airborne vehicles (UAVs) are now available at modest cost, allowing multiple UAVs to be deployed with multiple AUVs and ASVs. For optimal use good communication and coordination among vehicles is essential. We report on the use of multiple AUVs networked in communication with multiple UAVs. The UAVs are augmented by inferential reasoning software developed at MBARI that allows UAVs to recognize oceanographic fronts and change their navigation and control. This in turn allows UAVs to automatically to map frontal features, as well as to direct AUVs and ASVs to proceed to such features and conduct sampling via onboard sensors to provide validation for airborne mapping. ASVs can also act as data nodes for communication between UAVs and AUVs, as well as collecting data from onboard sensors, while AUVs can sample the water column vertically. This allows more accurate estimation of phytoplankton biomass and productivity, and can be used in conjunction with UAV sampling to determine air-sea flux of gases (e.g. CO2, CH4, DMS) affecting carbon budgets and atmospheric composition. In particular we describe tests in July 2013 conducted off Sesimbra, Portugal in conjunction with the Portuguese Navy by the University of Porto and MBARI with the goal of tracking large fish in the upper water column with coordinated air/surface/underwater measurements. A thermal gradient was observed in the infrared by a low flying UAV, which was used to dispatch an AUV to obtain ground truth to demonstrate the event-response capabilities using such autonomous platforms. Additional field studies in the future will facilitate integration of multiple unmanned systems into research vessel operations. The strength of hardware and software tools described in this study is to permit fundamental oceanographic measurements of both ocean

Analyzing the evolutionary mechanisms of the Air Transportation System-of-Systems using network theory and machine learning algorithms

NASA Astrophysics Data System (ADS)

Kotegawa, Tatsuya

Complexity in the Air Transportation System (ATS) arises from the intermingling of many independent physical resources, operational paradigms, and stakeholder interests, as well as the dynamic variation of these interactions over time. Currently, trade-offs and cost benefit analyses of new ATS concepts are carried out on system-wide evaluation simulations driven by air traffic forecasts that assume fixed airline routes. However, this does not well reflect reality as airlines regularly add and remove routes. A airline service route network evolution model that projects route addition and removal was created and combined with state-of-the-art air traffic forecast methods to better reflect the dynamic properties of the ATS in system-wide simulations. Guided by a system-of-systems framework, network theory metrics and machine learning algorithms were applied to develop the route network evolution models based on patterns extracted from historical data. Constructing the route addition section of the model posed the greatest challenge due to the large pool of new link candidates compared to the actual number of routes historically added to the network. Of the models explored, algorithms based on logistic regression, random forests, and support vector machines showed best route addition and removal forecast accuracies at approximately 20% and 40%, respectively, when validated with historical data. The combination of network evolution models and a system-wide evaluation tool quantified the impact of airline route network evolution on air traffic delay. The expected delay minutes when considering network evolution increased approximately 5% for a forecasted schedule on 3/19/2020. Performance trade-off studies between several airline route network topologies from the perspectives of passenger travel efficiency, fuel burn, and robustness were also conducted to provide bounds that could serve as targets for ATS transformation efforts. The series of analysis revealed that high

Variations in collagen fibrils network structure and surface dehydration of acid demineralized intertubular dentin: effect of dentin depth and air-exposure time.

PubMed

Fawzy, Amr S

2010-01-01

The aim was to characterize the variations in the structure and surface dehydration of acid demineralized intertubular dentin collagen network with the variations in dentin depth and time of air-exposure (3, 6, 9 and 12 min). In addition, to study the effect of these variations on the tensile bond strength (TBS) to dentin. Phosphoric acid demineralized superficial and deep dentin specimens were prepared. The structure of the dentin collagen network was characterized by AFM. The surface dehydration was characterized by probing the nano-scale adhesion force (F(ad)) between AFM tip and intertubular dentin surface as a new experimental approach. The TBS to dentin was evaluated using an alcohol-based dentin self-priming adhesive. AFM images revealed a demineralized open collagen network structure in both of superficial and deep dentin at 3 and 6 min of air-exposure. However, at 9 min, superficial dentin showed more collapsed network structure compared to deep dentin that partially preserved the open network structure. Total collapsed structure was found at 12 min for both of superficial and deep dentin. The value of the F(ad) is decreased with increasing the time of air-exposure and is increased with dentin depth at the same time of air-exposure. The TBS was higher for superficial dentin at 3 and 6 min, however, no difference was found at 9 and 12 min. The ability of the demineralized dentin collagen network to resist air-dehydration and to preserve the integrity of open network structure with the increase in air-exposure time is increased with dentin depth. Although superficial dentin achieves higher bond strength values, the difference in the bond strength is decreased by increasing the time of air-exposure. The AFM probed F(ad) showed to be sensitive approach to characterize surface dehydration, however, further researches are recommended regarding the validity of such approach.

Passive air sampling of organochlorine pesticides in Mexico.

PubMed

Wong, Fiona; Alegria, Henry A; Bidleman, Terry F; Alvarado, Víctor; Angeles, Felipe; Galarza, Alfredo Avila; Bandala, Erick R; Hinojosa, Idolina de la Cerda; Estrada, Ignacio Galindo; Reyes, Guillermo Galindo; Gold-Bouchot, Gerardo; Zamora, Jose Vinicio Macías; Murguía-González, Joaquín; Espinoza, Elias Ramirez

2009-02-01

The spatial and temporal variation of organochlorine pesticides (OCs) in air across Mexico was investigated by deploying passive samplers at eleven stations across the country during 2005-2006. Integrated samples were taken over three-month periods and quantified for DDT compounds, endosulfans, toxaphenes, components of technical chlordane, hexachlorocyclohexanes (HCHs), and dieldrin. Enantiomers of chiral chlordanes and o,p'-DDT were determined on chiral stationary phase columns as an indicator of source and age. Results are discussed in combination with pumped air samples taken at four other stations in southern Mexico during 2002-2004. DDT and its metabolites, endosulfan and toxaphene were the most abundant OCs detected in all sampling sites. Atmospheric concentrations of SigmaDDT (p,p'-DDT + o,p'-DDT + p,p'-DDE + o,p'-DDE + p,p'-DDD + o,p'-DDD) ranged from 15 to 2360 pg m(-3) with the highest concentrations found in southern Mexico and the lowest found in northern and central Mexico. A fresher DDT residue was observed at sites with greater DDT use and in the southern part of the country, as shown from the higher FDDTe = p,p'-DDT/(p,p'-DDT + p,p'-DDE) and nearly racemic o,p'-DDT. This agrees with the former heavy use of DDT in the endemic malarious area of the country. A local hotspot of endosulfan was identified at an agricultural area in Mazatlan, Sinaloa, with a annual mean concentration of SigmaENDO (endosulfans I + II + endosulfan sulfate) = 26,800 pg m(-3). At this site, higher concentrations of SigmaENDO were recorded during the winter (November to February) and spring (February to May) periods. From back trajectory analysis, this coincides with a shift in the air mass coming from the Pacific Ocean (May to November) to the inland agricultural area (November to May). The elevated SigmaENDO observed is likely due to the local agricultural usage. HCHs, chlordanes, transnonachlors, and dieldrin were more evenly distributed across the country likely due to

Modeling the potential of different countries for pandemic spread over the global air network

NASA Astrophysics Data System (ADS)

Sun, Zhe; Lv, Baolei; Xu, Bing

2017-04-01

Air network plays an important role in the spread of global epidemics due to its superior speed and range. Understanding the disease transmission pattern via network is the foundation for the prevention and control of future pandemics. In this study, we measured the potential of different countries for the pandemic spread by using a disease transmission model which integrated inter-country air traffic flow and geographic distance. The model was verified on the spread pattern of 2003 SARS, 2009 H1N1 influenza and 2014 Ebola by setting starting point at China, Mexico and Guinea respectively. Results showed that the model well reproduced the spread direction during the early stage as the time course were in good agreement with the reported arrival dates. Then the model was used to simulate the potential risk of each country in spreading the disease as the origin country. We observed that countries in North America, Europe and East Asia had the highest risk of transmission considering their high degree in the air network. We also found that for most starting countries, United States, United Kingdom, Germany and France would become the most-important spreading cores. Compared with empirical Susceptible-Infectious-Recover model, this model could respond much faster to the disease spread with no need for empirical disease transmission parameters.

Microbial Air and Surface Monitoring Results from International Space Station Samples

NASA Technical Reports Server (NTRS)

Ott, C. Mark; Bruce, Rebekah J.; Castro, Victoria A.; Novikova, Natalia D.; Pierson, D. L.

2005-01-01

Over the course of long-duration spaceflight, spacecraft develop a microbial ecology that directly interacts with the crew of the vehicle. While most microorganisms are harmless or beneficial to the inhabitants of the vehicle, the presence of medically significant organisms appearing in this semi-closed environment could adversely affect crew health and performance. The risk of exposure of the crew to medically significant organisms during a mission is estimated using information gathered during nominal and contingency environmental monitoring. Analysis of the air and surface microbiota in the habitable compartments of the International Space Station (ISS) over the last four years indicate a high presence of Staphylococcus species reflecting the human inhabitants of the vehicle. Generally, air and surface microbial concentrations are below system design specifications, suggesting a lower risk of contact infection or biodegradation. An evaluation of sample frequency indicates a decrease in the identification of new species, suggesting a lower potential for unknown microorganisms to be identified. However, the opportunistic pathogen, Staphylococcus aureus, has been identified in 3 of the last 5 air samples and 5 of the last 9 surface samples. In addition, 47% of the coagulase negative Staphylococcus species that were isolated from the crew, ISS, and its hardware were found to be methicillin resistance. In combination, these observations suggest the potential of methicillin resistant infectious agents over time.

Air Sampling Data for BP Spill/Deepwater Horizon

EPA Pesticide Factsheets

The Deepwater Horizon oil spill (also referred to as the BP oil spill) began on 20 April 2010 in the Gulf of Mexico on the BP-operated Macondo Prospect. Following the explosion and sinking of the Deepwater Horizon oil rig, a sea-floor oil gusher flowed for 87 days, until it was capped on 15 July 2010.In response to the BP oil spill, EPA sampled air, water, sediment, and waste generated by the cleanup operations.

Trace gas measurements from whole air samples collected over the Antarctic continent

NASA Technical Reports Server (NTRS)

Heidt, L. E.; Vedder, J. F.; Pollock, Walter H.; Henry, Bruce E.; Lueb, Richard A.

1988-01-01

Whole air samples collected aboard the NASA DC-8 and ER-2 aircraft as part of the Airborne Antarctic Ozone Experiment (AAOE) were analyzed in a field laboratory set up at Punta Arenas, Chile, in August and September, 1987. Mixing ratios obtained from gas chromatographic analyses of these samples are presented for N2O, CFCl3, CFCl2, C2F3Cl3, CH3CCl3, CH4, and CO. Variations in the mixing ratios of these gases along the individual flight paths of the aircraft are used as tracers to indicate the history of air masses over and near the Antarctic continent.

A STRINGENT COMPARISON OF SAMPLING AND ANALYSIS METHODS FOR VOCS IN AMBIENT AIR

EPA Science Inventory

A carefully designed study was conducted during the summer of 1998 to simultaneously collect samples of ambient air by canisters and compare the analysis results to direct sorbent preconcentration results taken at the time of sample collection. A total of 32 1-h sample sets we...

Characterizing Intra-Urban Air Quality Gradients with a Spatially-Distributed Network

NASA Astrophysics Data System (ADS)

Zimmerman, N.; Ellis, A.; Schurman, M. I.; Gu, P.; Li, H.; Snell, L.; Gu, J.; Subramanian, R.; Robinson, A. L.; Apte, J.; Presto, A. A.

2016-12-01

City-wide air pollution measurements have typically relied on regulatory or research monitoring sites with low spatial density to assess population-scale exposure. However, air pollutant concentrations exhibit significant spatial variability depending on local sources and features of the built environment, which may not be well captured by the existing monitoring regime. To better understand urban spatial and temporal pollution gradients at 1 km resolution, a network of 12 real-time air quality monitoring stations was deployed beginning July 2016 in Pittsburgh, PA. The stations were deployed at sites along an urban-rural transect and in urban locations with a range of traffic, restaurant, and tall building densities to examine the impact of various modifiable factors. Measurements from the stationary monitoring stations were further supported by mobile monitoring, which provided higher spatial resolution pollutant measurements on nearby roadways and enabled routine calibration checks. The stationary monitoring measurements comprise ultrafine particle number (Aerosol Dynamics "MAGIC" CPC), PM2.5 (Met One Neighborhood PM Monitor), black carbon (Met One BC 1050), and a new low-cost air quality monitor, the Real-time Affordable Multi-Pollutant (RAMP) sensor package for measuring CO, NO2, SO2, O3, CO2, temperature and relative humidity. High time-resolution (sub-minute) measurements across the distributed monitoring network enable insight into dynamic pollutant behaviour. Our preliminary findings show that our instruments are sensitive to PM2.5 gradients exceeding 2 micro-grams per cubic meter and ultrafine particle gradients exceeding 1000 particles per cubic centimeter. Additionally, we have developed rigorous calibration protocols to characterize the RAMP sensor response and drift, as well as multiple linear regression models to convert sensor response into pollutant concentrations that are comparable to reference instrumentation.

Transboundary Air Pollution over the Central Himalayas: Monitoring network and Preliminary Results

NASA Astrophysics Data System (ADS)

Zhang, Qianggong; Kang, Shichang

2016-04-01

The Himalayas, stretching over 3000 kms along west-east, separates South Asia continent and the Tibetan Plateau with its extreme high altitudes. The South Asia is being increasingly recognized to be among the hotspots of air pollution, posing multi-effects on regional climate and environment. Recent monitoring and projection have indicated an accelerated decrease of glacier and increasing glacier runoff in the Himalayas, and a remarkable phenomenon has been recognized in the Himalayas that long-range transport atmospheric pollutants (e.g., black carbon and dust) deposited on glacier surface can promote glacier melt, and in turns, may liberate historical contaminant legacy in glaciers into downward ecosystems. To understand the air pollution variation and how they can infiltrate the Himalayas and beyond, we started to operate a coordinated atmospheric pollution monitoring network composing 11 sites with 5 in Nepal and 6 in Tibet since April 2013. Atmospheric total suspended particles ( TSP < 100 μm) are collected for 24h at an interval of 3-6 days at all sites. Black carbon, typical persistent organic pollutants (PAHs) and heavy metals (particulate-bounded mercury) are measured to reveal their spatial and temporal distributions. Results revealed a consistent gradient decrease in almost all analyzed parameters along south-north gradient across the Himalayas, with a clear seasonal variation of higher values in pre-monsoon seasons. Analysis of geochemical signatures of carbonaceous aerosols indicated dominant sources from biomass burning and vehicle exhaust. PAHs concentrations and signatures from soils and aerosols indicated that low-ring PAHs can readily transport across the Himalayas. Integrated analysis of satellite images and air mass trajectories suggested that the transboundary air pollution over the Himalayas is episodic and is likely concentrated in pre-monsoon seasons. Our results emphasis the potential transport and impact of air pollution from South Asia

Note: Design and development of wireless controlled aerosol sampling network for large scale aerosol dispersion experiments.

PubMed

Gopalakrishnan, V; Subramanian, V; Baskaran, R; Venkatraman, B

2015-07-01

Wireless based custom built aerosol sampling network is designed, developed, and implemented for environmental aerosol sampling. These aerosol sampling systems are used in field measurement campaign, in which sodium aerosol dispersion experiments have been conducted as a part of environmental impact studies related to sodium cooled fast reactor. The sampling network contains 40 aerosol sampling units and each contains custom built sampling head and the wireless control networking designed with Programmable System on Chip (PSoC™) and Xbee Pro RF modules. The base station control is designed using graphical programming language LabView. The sampling network is programmed to operate in a preset time and the running status of the samplers in the network is visualized from the base station. The system is developed in such a way that it can be used for any other environment sampling system deployed in wide area and uneven terrain where manual operation is difficult due to the requirement of simultaneous operation and status logging.

Note: Design and development of wireless controlled aerosol sampling network for large scale aerosol dispersion experiments

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

Gopalakrishnan, V.; Subramanian, V.; Baskaran, R.

2015-07-15

Wireless based custom built aerosol sampling network is designed, developed, and implemented for environmental aerosol sampling. These aerosol sampling systems are used in field measurement campaign, in which sodium aerosol dispersion experiments have been conducted as a part of environmental impact studies related to sodium cooled fast reactor. The sampling network contains 40 aerosol sampling units and each contains custom built sampling head and the wireless control networking designed with Programmable System on Chip (PSoC™) and Xbee Pro RF modules. The base station control is designed using graphical programming language LabView. The sampling network is programmed to operate in amore » preset time and the running status of the samplers in the network is visualized from the base station. The system is developed in such a way that it can be used for any other environment sampling system deployed in wide area and uneven terrain where manual operation is difficult due to the requirement of simultaneous operation and status logging.« less

Indoor-air microbiome in an urban subway network: diversity and dynamics.

PubMed

Leung, Marcus H Y; Wilkins, David; Li, Ellen K T; Kong, Fred K F; Lee, Patrick K H

2014-11-01

Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on α- and β-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Indoor-Air Microbiome in an Urban Subway Network: Diversity and Dynamics

PubMed Central

Leung, Marcus H. Y.; Wilkins, David; Li, Ellen K. T.; Kong, Fred K. F.

2014-01-01

Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on α- and β-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe. PMID:25172855

Seluge++: A Secure Over-the-Air Programming Scheme in Wireless Sensor Networks

PubMed Central

Doroodgar, Farzan; Razzaque, Mohammad Abdur; Isnin, Ismail Fauzi

2014-01-01

Over-the-air dissemination of code updates in wireless sensor networks have been researchers' point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge. PMID:24618781

Seluge++: a secure over-the-air programming scheme in wireless sensor networks.

PubMed

Doroodgar, Farzan; Abdur Razzaque, Mohammad; Isnin, Ismail Fauzi

2014-03-11

Over-the-air dissemination of code updates in wireless sensor networks have been researchers' point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge.

Inter-laboratory comparison study on measuring semi-volatile organic chemicals in standards and air samples.

PubMed

Su, Yushan; Hung, Hayley

2010-11-01

Measurements of semi-volatile organic chemicals (SVOCs) were compared among 21 laboratories from 7 countries through the analysis of standards, a blind sample, an air extract, and an atmospheric dust sample. Measurement accuracy strongly depended on analytes, laboratories, and types of standards and samples. Intra-laboratory precision was generally good with relative standard deviations (RSDs) of triplicate injections <10% and with median differences of duplicate samples between 2.1 and 22%. Inter-laboratory variability, measured by RSDs of all measurements, was in the range of 2.8-58% in analyzing standards, and 6.9-190% in analyzing blind sample and air extract. Inter-laboratory precision was poorer when samples were subject to cleanup processes, or when SVOCs were quantified at low concentrations. In general, inter-laboratory differences up to a factor of 2 can be expected to analyze atmospheric SVOCs. When comparing air measurements from different laboratories, caution should be exercised if the data variability is less than the inter-laboratory differences. 2010. Published by Elsevier Ltd. All rights reserved.

Adaptive enhanced sampling by force-biasing using neural networks

NASA Astrophysics Data System (ADS)

Guo, Ashley Z.; Sevgen, Emre; Sidky, Hythem; Whitmer, Jonathan K.; Hubbell, Jeffrey A.; de Pablo, Juan J.

2018-04-01

A machine learning assisted method is presented for molecular simulation of systems with rugged free energy landscapes. The method is general and can be combined with other advanced sampling techniques. In the particular implementation proposed here, it is illustrated in the context of an adaptive biasing force approach where, rather than relying on discrete force estimates, one can resort to a self-regularizing artificial neural network to generate continuous, estimated generalized forces. By doing so, the proposed approach addresses several shortcomings common to adaptive biasing force and other algorithms. Specifically, the neural network enables (1) smooth estimates of generalized forces in sparsely sampled regions, (2) force estimates in previously unexplored regions, and (3) continuous force estimates with which to bias the simulation, as opposed to biases generated at specific points of a discrete grid. The usefulness of the method is illustrated with three different examples, chosen to highlight the wide range of applicability of the underlying concepts. In all three cases, the new method is found to enhance considerably the underlying traditional adaptive biasing force approach. The method is also found to provide improvements over previous implementations of neural network assisted algorithms.

Journal Article: the National Dioxin Air Monitoring Network (Ndamn): Measurements of CDDs, CDFs and Coplanar PCBs at 15 Rural and 6 National Park Areas of the U.S.: June 1998-December 1999.

EPA Science Inventory

The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric CDDs, CDFs and coplanar PCBs at rural and nonimpacted locations throughout the United States. Currently operating at 32 sampling st...

Sampling for Global Epidemic Models and the Topology of an International Airport Network

PubMed Central

Bobashev, Georgiy; Morris, Robert J.; Goedecke, D. Michael

2008-01-01

Mathematical models that describe the global spread of infectious diseases such as influenza, severe acute respiratory syndrome (SARS), and tuberculosis (TB) often consider a sample of international airports as a network supporting disease spread. However, there is no consensus on how many cities should be selected or on how to select those cities. Using airport flight data that commercial airlines reported to the Official Airline Guide (OAG) in 2000, we have examined the network characteristics of network samples obtained under different selection rules. In addition, we have examined different size samples based on largest flight volume and largest metropolitan populations. We have shown that although the bias in network characteristics increases with the reduction of the sample size, a relatively small number of areas that includes the largest airports, the largest cities, the most-connected cities, and the most central cities is enough to describe the dynamics of the global spread of influenza. The analysis suggests that a relatively small number of cities (around 200 or 300 out of almost 3000) can capture enough network information to adequately describe the global spread of a disease such as influenza. Weak traffic flows between small airports can contribute to noise and mask other means of spread such as the ground transportation. PMID:18776932

Artificial Neural Network with Regular Graph for Maximum Air Temperature Forecasting:. the Effect of Decrease in Nodes Degree on Learning

NASA Astrophysics Data System (ADS)

Ghaderi, A. H.; Darooneh, A. H.

The behavior of nonlinear systems can be analyzed by artificial neural networks. Air temperature change is one example of the nonlinear systems. In this work, a new neural network method is proposed for forecasting maximum air temperature in two cities. In this method, the regular graph concept is used to construct some partially connected neural networks that have regular structures. The learning results of fully connected ANN and networks with proposed method are compared. In some case, the proposed method has the better result than conventional ANN. After specifying the best network, the effect of input pattern numbers on the prediction is studied and the results show that the increase of input patterns has a direct effect on the prediction accuracy.

Comparison of precipitation chemistry measurements obtained by the Canadian Air and Precipitation Monitoring Network and National Atmospheric Deposition Program for the period 1995-2004

USGS Publications Warehouse

Wetherbee, Gregory A.; Shaw, Michael J.; Latysh, Natalie E.; Lehmann, Christopher M.B.; Rothert, Jane E.

2010-01-01

Precipitation chemistry and depth measurements obtained by the Canadian Air and Precipitation Monitoring Network (CAPMoN) and the US National Atmospheric Deposition Program/National Trends Network (NADP/NTN) were compared for the 10-year period 1995–2004. Colocated sets of CAPMoN and NADP instrumentation, consisting of precipitation collectors and rain gages, were operated simultaneously per standard protocols for each network at Sutton, Ontario and Frelighsburg, Ontario, Canada and at State College, PA, USA. CAPMoN samples were collected daily, and NADP samples were collected weekly, and samples were analyzed exclusively by each network’s laboratory for pH, H + , Ca2+  , Mg2+  , Na + , K + , NH+4 , Cl − , NO−3 , and SO2−4 . Weekly and annual precipitation-weighted mean concentrations for each network were compared. This study is a follow-up to an earlier internetwork comparison for the period 1986–1993, published by Alain Sirois, Robert Vet, and Dennis Lamb in 2000. Median weekly internetwork differences for 1995–2004 data were the same to slightly lower than for data for the previous study period (1986–1993) for all analytes except NO−3 , SO2−4 , and sample depth. A 1994 NADP sampling protocol change and a 1998 change in the types of filters used to process NADP samples reversed the previously identified negative bias in NADP data for hydrogen-ion and sodium concentrations. Statistically significant biases (α = 0.10) for sodium and hydrogen-ion concentrations observed in the 1986–1993 data were not significant for 1995–2004. Weekly CAPMoN measurements generally are higher than weekly NADP measurements due to differences in sample filtration and field instrumentation, not sample evaporation, contamination, or analytical laboratory differences.

2018 Annual Terrestrial Sampling Plan for Sandia National Laboratories/New Mexico on Kirtland Air Force Base.

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

Griffith, Stacy R.

The 2018 Annual Terrestrial Sampling Plan for Sandia National Laboratories/New Mexico on Kirtland Air Force Base has been prepared in accordance with the “Letter of Agreement Between Department of Energy, National Nuclear Security Administration, Sandia Field Office (DOE/NNSA/SFO) and 377th Air Base Wing (ABW), Kirtland Air Force Base (KAFB) for Terrestrial Sampling” (signed January 2017), Sandia National Laboratories, New Mexico (SNL/NM). The Letter of Agreement requires submittal of an annual terrestrial sampling plan.

2017 Annual Terrestrial Sampling Plan for Sandia National Laboratories/New Mexico on Kirtland Air Force Base

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

Griffith, Stacy R.

The 2017 Annual Terrestrial Sampling Plan for Sandia National Laboratories/New Mexico on Kirtland Air Force Base has been prepared in accordance with the “Letter of Agreement Between Department of Energy, National Nuclear Security Administration, Sandia Field Office (DOE/NNSA/SFO) and 377th Air Base Wing (ABW), Kirtland Air Force Base (KAFB) for Terrestrial Sampling” (signed January 2017), Sandia National Laboratories, New Mexico (SNL/NM). The Letter of Agreement requires submittal of an annual terrestrial sampling plan.

Development and deployment of a low-cost, mobile-ready, air quality sensor system: progress toward distributed networks and autonomous aerial sampling

NASA Astrophysics Data System (ADS)

Hersey, S. P.; DiVerdi, R.; Gadtaula, P.; Sheneman, T.; Flores, K.; Chen, Y. H.; Jayne, J. T.; Cross, E. S.

2017-12-01

Throughout the 2016-2017 academic year, a new partnership between Olin College of Engineering and Aerodyne Research, Inc. developed an affordable, self-contained air quality monitoring instrument called Modulair. The Modulair instrument is based on the same operating principles as Aerodyne's newly-developed ARISense integrated sensor system, employing electrochemical sensors for gas-phase measurements of CO, NO, NO2, and O3 and an off-the-shelf optical particle counter for particle concentration, number, and size distribution information (0.4 < dp < 17 microns). High Dimensional Model Representation (HDMR) has been used to model the interference derived from relative humidity and temperature as well as the cross-sensitivity of the electrochemical sensors to non-target gas-phase species. The aim of the modeling effort is to provide transparent and robust calibration of electrical signals to pollutant concentrations from a set of electrochemical sensors. Modulair was designed from the ground-up, with custom electronics - including a more powerful microcontroller, a fully re-designed housing and a device-specific backend with a mobile, cloud-based data management system for real-time data posting and analysis. Open source tools and software were utilized in the development of the instrument. All initial work was completed by a team of undergraduate students as part of the Senior Capstone Program in Engineering (SCOPE) at Olin College. Deployment strategies for Modulair include distributed, mobile measurements and drone-based aerial sampling. Design goals for the drone integration include maximizing airborne sampling time and laying the foundation for software integration with the drone's autopilot system to allow for autonomous plume sampling across concentration gradients. Modulair and its flexible deployments enable real-time mapping of air quality data at exposure-relevant spatial scales, as well as regular, autonomous characterization of sources and dispersion of

Identifying a Probabilistic Boolean Threshold Network From Samples.

PubMed

Melkman, Avraham A; Cheng, Xiaoqing; Ching, Wai-Ki; Akutsu, Tatsuya

2018-04-01

This paper studies the problem of exactly identifying the structure of a probabilistic Boolean network (PBN) from a given set of samples, where PBNs are probabilistic extensions of Boolean networks. Cheng et al. studied the problem while focusing on PBNs consisting of pairs of AND/OR functions. This paper considers PBNs consisting of Boolean threshold functions while focusing on those threshold functions that have unit coefficients. The treatment of Boolean threshold functions, and triplets and -tuplets of such functions, necessitates a deepening of the theoretical analyses. It is shown that wide classes of PBNs with such threshold functions can be exactly identified from samples under reasonable constraints, which include: 1) PBNs in which any number of threshold functions can be assigned provided that all have the same number of input variables and 2) PBNs consisting of pairs of threshold functions with different numbers of input variables. It is also shown that the problem of deciding the equivalence of two Boolean threshold functions is solvable in pseudopolynomial time but remains co-NP complete.

Early Detection of Foot-And-Mouth Disease Virus from Infected Cattle Using A Dry Filter Air Sampling System.

PubMed

Pacheco, J M; Brito, B; Hartwig, E; Smoliga, G R; Perez, A; Arzt, J; Rodriguez, L L

2017-04-01

Foot-and-mouth disease (FMD) is a highly contagious livestock disease of high economic impact. Early detection of FMD virus (FMDV) is fundamental for rapid outbreak control. Air sampling collection has been demonstrated as a useful technique for detection of FMDV RNA in infected animals, related to the aerogenous nature of the virus. In the current study, air from rooms housing individual (n = 17) or two groups (n = 4) of cattle experimentally infected with FDMV A24 Cruzeiro of different virulence levels was sampled to assess the feasibility of applying air sampling as a non-invasive, screening tool to identify sources of FMDV infection. Detection of FMDV RNA in air was compared with first detection of clinical signs and FMDV RNA levels in serum and oral fluid. FMDV RNA was detected in room air samples 1-3 days prior (seven animals) or on the same day (four animals) as the appearance of clinical signs in 11 of 12 individually housed cattle. Only in one case clinical signs preceded detection in air samples by one day. Overall, viral RNA in oral fluid or serum preceded detection in air samples by 1-2 days. Six individually housed animals inoculated with attenuated strains did not show clinical signs, but virus was detected in air in one of these cases 3 days prior to first detection in oral fluid. In groups of four cattle housed together, air detection always preceded appearance of clinical signs by 1-2 days and coincided more often with viral shedding in oral fluid than virus in blood. These data confirm that air sampling is an effective non-invasive screening method for detecting FMDV infection in confined to enclosed spaces (e.g. auction barns, milking parlours). This technology could be a useful tool as part of a surveillance strategy during FMD prevention, control or eradication efforts. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Spatiotemporal Patterns, Monitoring Network Design, and Environmental Justice of Air Pollution in the Phoenix Metropolitan Region: A Landscape Approach

NASA Astrophysics Data System (ADS)

Pope, Ronald L.

Air pollution is a serious problem in most urban areas around the world, which has a number of negative ecological and human health impacts. As a result, it's vitally important to detect and characterize air pollutants to protect the health of the urban environment and our citizens. An important early step in this process is ensuring that the air pollution monitoring network is properly designed to capture the patterns of pollution and that all social demographics in the urban population are represented. An important aspect in characterizing air pollution patterns is scale in space and time which, along with pattern and process relationships, is a key subject in the field of landscape ecology. Thus, using multiple landscape ecological methods, this dissertation research begins by characterizing and quantifying the multi-scalar patterns of ozone (O3) and particulate matter (PM10) in the Phoenix, Arizona, metropolitan region. Results showed that pollution patterns are scale-dependent, O3 is a regionally-scaled pollutant at longer temporal scales, and PM10 is a locally-scaled pollutant with patterns sensitive to season. Next, this dissertation examines the monitoring network within Maricopa County. Using a novel multiscale indicator-based approach, the adequacy of the network was quantified by integrating inputs from various academic and government stakeholders. Furthermore, deficiencies were spatially defined and recommendations were made on how to strengthen the design of the network. A sustainability ranking system also provided new insight into the strengths and weaknesses of the network. Lastly, the study addresses the question of whether distinct social groups were experiencing inequitable exposure to pollutants - a key issue of distributive environmental injustice. A novel interdisciplinary method using multi-scalar ambient pollution data and hierarchical multiple regression models revealed environmental inequities between air pollutants and race, ethnicity

Assessing NIR & MIR Spectral Analysis as a Method for Soil C Estimation Across a Network of Sampling Sites

NASA Astrophysics Data System (ADS)

Spencer, S.; Ogle, S.; Borch, T.; Rock, B.

2008-12-01

Monitoring soil C stocks is critical to assess the impact of future climate and land use change on carbon sinks and sources in agricultural lands. A benchmark network for soil carbon monitoring of stock changes is being designed for US agricultural lands with 3000-5000 sites anticipated and re-sampling on a 5- to10-year basis. Approximately 1000 sites would be sampled per year producing around 15,000 soil samples to be processed for total, organic, and inorganic carbon, as well as bulk density and nitrogen. Laboratory processing of soil samples is cost and time intensive, therefore we are testing the efficacy of using near-infrared (NIR) and mid-infrared (MIR) spectral methods for estimating soil carbon. As part of an initial implementation of national soil carbon monitoring, we collected over 1800 soil samples from 45 cropland sites in the mid-continental region of the U.S. Samples were processed using standard laboratory methods to determine the variables above. Carbon and nitrogen were determined by dry combustion and inorganic carbon was estimated with an acid-pressure test. 600 samples are being scanned using a bench- top NIR reflectance spectrometer (30 g of 2 mm oven-dried soil and 30 g of 8 mm air-dried soil) and 500 samples using a MIR Fourier-Transform Infrared Spectrometer (FTIR) with a DRIFT reflectance accessory (0.2 g oven-dried ground soil). Lab-measured carbon will be compared to spectrally-estimated carbon contents using Partial Least Squares (PLS) multivariate statistical approach. PLS attempts to develop a soil C predictive model that can then be used to estimate C in soil samples not lab-processed. The spectral analysis of soil samples either whole or partially processed can potentially save both funding resources and time to process samples. This is particularly relevant for the implementation of a national monitoring network for soil carbon. This poster will discuss our methods, initial results and potential for using NIR and MIR spectral

Bioassay vs. Air Sampling: Practical Guidance and Experience at Hanford

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

Carbaugh, Eugene H.; Carlson, Eric W.; Hill, Robin L.

2004-02-08

The Hanford Site has implemented a policy to guide in determining whether air sampling data or special fecal bioassay data are more appropriate for determining doses of record for low-level plutonium exposures. The basis for the policy and four years of experience in comparing DAC-hours exposure with bioassay-based dosimetry is discussed.

Air sampling results in relation to extent of fungal colonization of building materials in some water-damaged buildings.

PubMed

Miller, J D; Haisley, P D; Reinhardt, J H

2000-09-01

We studied the extent and nature of fungal colonization of building materials in 58 naturally ventilated apartments that had suffered various kinds of water damage in relation to air sampling done before the physical inspections. The results of air samples from each apartment were compared by rank order of species with pooled data from outdoor air. Approximately 90% of the apartments that had significant amounts of fungi in wall cavities were identified by air sampling. There was no difference in the average fungal colony forming unit values per m3 between the 15 apartments with the most fungal contamination and the 15 with the least. In contrast, the prevalence of samples with fungal species significantly different than the pooled outdoor air between the more contaminated versus the less contaminated apartments was approximately 10-fold. We provide information on methods to document fungal contamination in buildings.

Application of Frequency of Detection Methods in Design and Optimization of the INL Site Ambient Air Monitoring Network

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

Rood, Arthur S.; Sondrup, A. Jeffrey

This report presents an evaluation of a hypothetical INL Site monitoring network and the existing INL air monitoring network using frequency of detection methods. The hypothetical network was designed to address the requirement in 40 CFR Part 61, Subpart H (2006) that “emissions of radionuclides to ambient air from U.S. DOE facilities shall not exceed those amounts that would cause any member of the public to receive in any year an effective dose equivalent exceeding 10 mrem/year.” To meet the requirement for monitoring only, “radionuclide releases that would result in an effective dose of 10% of the standard shall bemore » readily detectable and distinguishable from background.” Thus, the hypothetical network consists of air samplers placed at residence locations that surround INL and at other locations where onsite livestock grazing takes place. Two exposure scenarios were used in this evaluation: a resident scenario and a shepherd/rancher scenario. The resident was assumed to be continuously present at their residence while the shepherd/rancher was assumed to be present 24-hours at a fixed location on the grazing allotment. Important radionuclides were identified from annual INL radionuclide National Emission Standards for Hazardous Pollutants reports. Important radionuclides were defined as those that potentially contribute 1% or greater to the annual total dose at the radionuclide National Emission Standards for Hazardous Pollutants maximally exposed individual location and include H-3, Am-241, Pu-238, Pu 239, Cs-137, Sr-90, and I-131. For this evaluation, the network performance objective was set at achieving a frequency of detection greater than or equal to 95%. Results indicated that the hypothetical network for the resident scenario met all performance objectives for H-3 and I-131 and most performance objectives for Cs-137 and Sr-90. However, all actinides failed to meet the performance objectives for most sources. The shepherd/rancher scenario

Network visualization of conformational sampling during molecular dynamics simulation.

PubMed

Ahlstrom, Logan S; Baker, Joseph Lee; Ehrlich, Kent; Campbell, Zachary T; Patel, Sunita; Vorontsov, Ivan I; Tama, Florence; Miyashita, Osamu

2013-11-01

Effective data reduction methods are necessary for uncovering the inherent conformational relationships present in large molecular dynamics (MD) trajectories. Clustering algorithms provide a means to interpret the conformational sampling of molecules during simulation by grouping trajectory snapshots into a few subgroups, or clusters, but the relationships between the individual clusters may not be readily understood. Here we show that network analysis can be used to visualize the dominant conformational states explored during simulation as well as the connectivity between them, providing a more coherent description of conformational space than traditional clustering techniques alone. We compare the results of network visualization against 11 clustering algorithms and principal component conformer plots. Several MD simulations of proteins undergoing different conformational changes demonstrate the effectiveness of networks in reaching functional conclusions. Copyright © 2013 Elsevier Inc. All rights reserved.

Air sampling procedures to evaluate microbial contamination: a comparison between active and passive methods in operating theatres.

PubMed

Napoli, Christian; Marcotrigiano, Vincenzo; Montagna, Maria Teresa

2012-08-02

Since air can play a central role as a reservoir for microorganisms, in controlled environments such as operating theatres regular microbial monitoring is useful to measure air quality and identify critical situations. The aim of this study is to assess microbial contamination levels in operating theatres using both an active and a passive sampling method and then to assess if there is a correlation between the results of the two different sampling methods. The study was performed in 32 turbulent air flow operating theatres of a University Hospital in Southern Italy. Active sampling was carried out using the Surface Air System and passive sampling with settle plates, in accordance with ISO 14698. The Total Viable Count (TVC) was evaluated at rest (in the morning before the beginning of surgical activity) and in operational (during surgery). The mean TVC at rest was 12.4 CFU/m3 and 722.5 CFU/m2/h for active and passive samplings respectively. The mean in operational TVC was 93.8 CFU/m3 (SD = 52.69; range = 22-256) and 10496.5 CFU/m2/h (SD = 7460.5; range = 1415.5-25479.7) for active and passive samplings respectively. Statistical analysis confirmed that the two methods correlate in a comparable way with the quality of air. It is possible to conclude that both methods can be used for general monitoring of air contamination, such as routine surveillance programs. However, the choice must be made between one or the other to obtain specific information.

Salmonella recovery following air chilling for matched neck-skin and whole carcass sampling methodologies

USDA-ARS?s Scientific Manuscript database

The prevalence and serogroups of Salmonella recovered following air chilling were determined for both enriched neck skin and matching enriched whole carcass samples. Commercially processed and eviscerated carcasses were air chilled to 4C before removing the neck skin (8.3 g) and stomaching in 83 mL...

On the Effect of Preferential Sampling in Spatial Prediction

EPA Science Inventory

The choice of the sampling locations in a spatial network is often guided by practical demands. In particular, typically, locations are preferentially chosen to capture high values of a response, for example, air pollution levels in environmental monitoring. Then, model estimatio...

Potential assessment of a neural network model with PCA/RBF approach for forecasting pollutant trends in Mong Kok urban air, Hong Kong.

PubMed

Lu, Wei-Zhen; Wang, Wen-Jian; Wang, Xie-Kang; Yan, Sui-Hang; Lam, Joseph C

2004-09-01

The forecasting of air pollutant trends has received much attention in recent years. It is an important and popular topic in environmental science, as concerns have been raised about the health impacts caused by unacceptable ambient air pollutant levels. Of greatest concern are metropolitan cities like Hong Kong. In Hong Kong, respirable suspended particulates (RSP), nitrogen oxides (NOx), and nitrogen dioxide (NO2) are major air pollutants due to the dominant usage of diesel fuel by commercial vehicles and buses. Hence, the study of the influence and the trends relating to these pollutants is extremely significant to the public health and the image of the city. The use of neural network techniques to predict trends relating to air pollutants is regarded as a reliable and cost-effective method for the task of prediction. The works reported here involve developing an improved neural network model that combines both the principal component analysis technique and the radial basis function network and forecasts pollutant tendencies based on a recorded database. Compared with general neural network models, the proposed model features a more simple network architecture, a faster training speed, and a more satisfactory prediction performance. The improved model was evaluated with hourly time series of RSP, NOx and NO2 concentrations monitored at the Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000 and proved to be effective. The model developed is a potential tool for forecasting air quality parameters and is superior to traditional neural network methods.

Sorbent-based sampling methods for volatile and semi-volatile organic compounds in air. Part 2. Sorbent selection and other aspects of optimizing air monitoring methods.

PubMed

Woolfenden, Elizabeth

2010-04-16

Sorbent tubes/traps are widely used in combination with gas chromatographic (GC) analytical methods to monitor the vapour-phase fraction of organic compounds in air. Applications range from atmospheric research and ambient air monitoring (indoor and outdoor) to occupational hygiene (personal exposure assessment) and measuring chemical emission levels. Part 1 of this paper reviewed the main sorbent-based air sampling strategies including active (pumped) tube monitoring, diffusive (passive) sampling onto sorbent tubes/cartridges plus sorbent trapping/focusing of whole air samples that are either collected in containers (such as canisters or bags) or monitored online. Options for subsequent extraction and transfer to GC(MS) analysis were also summarised and the trend to thermal desorption (TD)-based methods and away from solvent extraction was explained. As a result of this trend, demand for TD-compatible sorbents (alternatives to traditional charcoal) is growing. Part 2 of this paper therefore continues with a summary of TD-compatible sorbents, their respective advantages and limitations and considerations for sorbent selection. Other analytical considerations for optimizing sorbent-based air monitoring methods are also discussed together with recent technical developments and sampling accessories which have extended the application range of sorbent trapping technology generally. Copyright 2010 Elsevier B.V. All rights reserved.

Measuring the Operational Readiness of an Air Force Network Warfare Squadron

DTIC Science & Technology

2008-06-01

Abstract As part of its unit activation, the 315th Network Warfare Squadron (NWS) needed to measure and report its progression of unit readiness...NWS unit readiness should be measured and reported by SORTS Category Levels (C-Level) to support wartime missions, not by IOC and FOC milestones...This paper reviews SORTS computations and provides a case study of a notional Air Force NWS to propose that any new cyber squadron should report

Airborne detection and quantification of swine influenza a virus in air samples collected inside, outside and downwind from swine barns.

PubMed

Corzo, Cesar A; Culhane, Marie; Dee, Scott; Morrison, Robert B; Torremorell, Montserrat

2013-01-01

Airborne transmission of influenza A virus (IAV) in swine is speculated to be an important route of virus dissemination, but data are scarce. This study attempted to detect and quantify airborne IAV by virus isolation and RRT-PCR in air samples collected under field conditions. This was accomplished by collecting air samples from four acutely infected pig farms and locating air samplers inside the barns, at the external exhaust fans and downwind from the farms at distances up to 2.1 km. IAV was detected in air samples collected in 3 out of 4 farms included in the study. Isolation of IAV was possible from air samples collected inside the barn at two of the farms and in one farm from the exhausted air. Between 13% and 100% of samples collected inside the barns tested RRT-PCR positive with an average viral load of 3.20E+05 IAV RNA copies/m³ of air. Percentage of exhaust positive air samples also ranged between 13% and 100% with an average viral load of 1.79E+04 RNA copies/m³ of air. Influenza virus RNA was detected in air samples collected between 1.5 and 2.1 Km away from the farms with viral levels significantly lower at 4.65E+03 RNA copies/m³. H1N1, H1N2 and H3N2 subtypes were detected in the air samples and the hemagglutinin gene sequences identified in the swine samples matched those in aerosols providing evidence that the viruses detected in the aerosols originated from the pigs in the farms under study. Overall our results indicate that pigs can be a source of IAV infectious aerosols and that these aerosols can be exhausted from pig barns and be transported downwind. The results from this study provide evidence of the risk of aerosol transmission in pigs under field conditions.

Airborne Detection and Quantification of Swine Influenza A Virus in Air Samples Collected Inside, Outside and Downwind from Swine Barns

PubMed Central

Corzo, Cesar A.; Culhane, Marie; Dee, Scott; Morrison, Robert B.; Torremorell, Montserrat

2013-01-01

Airborne transmission of influenza A virus (IAV) in swine is speculated to be an important route of virus dissemination, but data are scarce. This study attempted to detect and quantify airborne IAV by virus isolation and RRT-PCR in air samples collected under field conditions. This was accomplished by collecting air samples from four acutely infected pig farms and locating air samplers inside the barns, at the external exhaust fans and downwind from the farms at distances up to 2.1 km. IAV was detected in air samples collected in 3 out of 4 farms included in the study. Isolation of IAV was possible from air samples collected inside the barn at two of the farms and in one farm from the exhausted air. Between 13% and 100% of samples collected inside the barns tested RRT-PCR positive with an average viral load of 3.20E+05 IAV RNA copies/m3 of air. Percentage of exhaust positive air samples also ranged between 13% and 100% with an average viral load of 1.79E+04 RNA copies/m3 of air. Influenza virus RNA was detected in air samples collected between 1.5 and 2.1 Km away from the farms with viral levels significantly lower at 4.65E+03 RNA copies/m3. H1N1, H1N2 and H3N2 subtypes were detected in the air samples and the hemagglutinin gene sequences identified in the swine samples matched those in aerosols providing evidence that the viruses detected in the aerosols originated from the pigs in the farms under study. Overall our results indicate that pigs can be a source of IAV infectious aerosols and that these aerosols can be exhausted from pig barns and be transported downwind. The results from this study provide evidence of the risk of aerosol transmission in pigs under field conditions. PMID:23951164

PM2.5 Monitors in New England | Air Quality Planning Unit ...

EPA Pesticide Factsheets

2017-04-10

The New England states are currently operating a network of 58 ambient PM2.5 air quality monitors that meet EPA's Federal Reference Method (FRM) for PM2.5, which is necessary in order for the resultant data to be used for attainment/non-attainment purposes. These monitors collect particles in the ambient air smaller than 2.5 microns in size on a filter, which is weighed prior and post sampling to produce a 24-hour sample concentration.

Coupling Network Computing Applications in Air-cooled Turbine Blades Optimization

NASA Astrophysics Data System (ADS)

Shi, Liang; Yan, Peigang; Xie, Ming; Han, Wanjin

2018-05-01

Through establishing control parameters from blade outside to inside, the parametric design of air-cooled turbine blade based on airfoil has been implemented. On the basis of fast updating structure features and generating solid model, a complex cooling system has been created. Different flow units are modeled into a complex network topology with parallel and serial connection. Applying one-dimensional flow theory, programs have been composed to get pipeline network physical quantities along flow path, including flow rate, pressure, temperature and other parameters. These inner units parameters set as inner boundary conditions for external flow field calculation program HIT-3D by interpolation, thus to achieve full field thermal coupling simulation. Referring the studies in literatures to verify the effectiveness of pipeline network program and coupling algorithm. After that, on the basis of a modified design, and with the help of iSIGHT-FD, an optimization platform had been established. Through MIGA mechanism, the target of enhancing cooling efficiency has been reached, and the thermal stress has been effectively reduced. Research work in this paper has significance for rapid deploying the cooling structure design.

Air-Sense: indoor environment monitoring evaluation system based on ZigBee network

NASA Astrophysics Data System (ADS)

Huang, Yang; Hu, Liang; Yang, Disheng; Liu, Hengchang

2017-08-01

In the modern life, people spend most of their time indoors. However, indoor environmental quality problems have always been affecting people’s social activities. In general, indoor environmental quality is also related to our indoor activities. Since most of the organic irritants and volatile gases are colorless, odorless and too tiny to be seen, because we have been unconsciously overlooked indoor environment quality. Consequently, our body suffer a great health problem. In this work, we propose Air-Sense system which utilizes the platform of ZigBee Network to collect and detect the real-time indoor environment quality. What’s more, Air-Sense system can also provide data analysis, and visualizing the results of the indoor environment to the user.

Cyber-Threat Assessment for the Air Traffic Management System: A Network Controls Approach

NASA Technical Reports Server (NTRS)

Roy, Sandip; Sridhar, Banavar

2016-01-01

Air transportation networks are being disrupted with increasing frequency by failures in their cyber- (computing, communication, control) systems. Whether these cyber- failures arise due to deliberate attacks or incidental errors, they can have far-reaching impact on the performance of the air traffic control and management systems. For instance, a computer failure in the Washington DC Air Route Traffic Control Center (ZDC) on August 15, 2015, caused nearly complete closure of the Centers airspace for several hours. This closure had a propagative impact across the United States National Airspace System, causing changed congestion patterns and requiring placement of a suite of traffic management initiatives to address the capacity reduction and congestion. A snapshot of traffic on that day clearly shows the closure of the ZDC airspace and the resulting congestion at its boundary, which required augmented traffic management at multiple locations. Cyber- events also have important ramifications for private stakeholders, particularly the airlines. During the last few months, computer-system issues have caused several airlines fleets to be grounded for significant periods of time: these include United Airlines (twice), LOT Polish Airlines, and American Airlines. Delays and regional stoppages due to cyber- events are even more common, and may have myriad causes (e.g., failure of the Department of Homeland Security systems needed for security check of passengers, see [3]). The growing frequency of cyber- disruptions in the air transportation system reflects a much broader trend in the modern society: cyber- failures and threats are becoming increasingly pervasive, varied, and impactful. In consequence, an intense effort is underway to develop secure and resilient cyber- systems that can protect against, detect, and remove threats, see e.g. and its many citations. The outcomes of this wide effort on cyber- security are applicable to the air transportation infrastructure

Air sampling procedures to evaluate microbial contamination: a comparison between active and passive methods in operating theatres

PubMed Central

2012-01-01

Background Since air can play a central role as a reservoir for microorganisms, in controlled environments such as operating theatres regular microbial monitoring is useful to measure air quality and identify critical situations. The aim of this study is to assess microbial contamination levels in operating theatres using both an active and a passive sampling method and then to assess if there is a correlation between the results of the two different sampling methods. Methods The study was performed in 32 turbulent air flow operating theatres of a University Hospital in Southern Italy. Active sampling was carried out using the Surface Air System and passive sampling with settle plates, in accordance with ISO 14698. The Total Viable Count (TVC) was evaluated at rest (in the morning before the beginning of surgical activity) and in operational (during surgery). Results The mean TVC at rest was 12.4 CFU/m3 and 722.5 CFU/m2/h for active and passive samplings respectively. The mean in operational TVC was 93.8 CFU/m3 (SD = 52.69; range = 22-256) and 10496.5 CFU/m2/h (SD = 7460.5; range = 1415.5-25479.7) for active and passive samplings respectively. Statistical analysis confirmed that the two methods correlate in a comparable way with the quality of air. Conclusion It is possible to conclude that both methods can be used for general monitoring of air contamination, such as routine surveillance programs. However, the choice must be made between one or the other to obtain specific information. PMID:22853006

Breakthrough of 1,3-dichloropropene and chloropicrin from 600 mg XAD-4 air sampling tubes

USDA-ARS?s Scientific Manuscript database

Accurately measuring air concentrations of agricultural fumigants is important for the regulation of air quality. Understanding the conditions under which sorbent tubes can effectively retain such fumigants during sampling is critical in mitigating chemical breakthrough from the tubes and facilitati...

Sample selection via angular distance in the space of the arguments of an artificial neural network

NASA Astrophysics Data System (ADS)

Fernández Jaramillo, J. M.; Mayerle, R.

2018-05-01

In the construction of an artificial neural network (ANN) a proper data splitting of the available samples plays a major role in the training process. This selection of subsets for training, testing and validation affects the generalization ability of the neural network. Also the number of samples has an impact in the time required for the design of the ANN and the training. This paper introduces an efficient and simple method for reducing the set of samples used for training a neural network. The method reduces the required time to calculate the network coefficients, while keeping the diversity and avoiding overtraining the ANN due the presence of similar samples. The proposed method is based on the calculation of the angle between two vectors, each one representing one input of the neural network. When the angle formed among samples is smaller than a defined threshold only one input is accepted for the training. The accepted inputs are scattered throughout the sample space. Tidal records are used to demonstrate the proposed method. The results of a cross-validation show that with few inputs the quality of the outputs is not accurate and depends on the selection of the first sample, but as the number of inputs increases the accuracy is improved and differences among the scenarios with a different starting sample have and important reduction. A comparison with the K-means clustering algorithm shows that for this application the proposed method with a smaller number of samples is producing a more accurate network.

optGpSampler: an improved tool for uniformly sampling the solution-space of genome-scale metabolic networks.

PubMed

Megchelenbrink, Wout; Huynen, Martijn; Marchiori, Elena

2014-01-01

Constraint-based models of metabolic networks are typically underdetermined, because they contain more reactions than metabolites. Therefore the solutions to this system do not consist of unique flux rates for each reaction, but rather a space of possible flux rates. By uniformly sampling this space, an estimated probability distribution for each reaction's flux in the network can be obtained. However, sampling a high dimensional network is time-consuming. Furthermore, the constraints imposed on the network give rise to an irregularly shaped solution space. Therefore more tailored, efficient sampling methods are needed. We propose an efficient sampling algorithm (called optGpSampler), which implements the Artificial Centering Hit-and-Run algorithm in a different manner than the sampling algorithm implemented in the COBRA Toolbox for metabolic network analysis, here called gpSampler. Results of extensive experiments on different genome-scale metabolic networks show that optGpSampler is up to 40 times faster than gpSampler. Application of existing convergence diagnostics on small network reconstructions indicate that optGpSampler converges roughly ten times faster than gpSampler towards similar sampling distributions. For networks of higher dimension (i.e. containing more than 500 reactions), we observed significantly better convergence of optGpSampler and a large deviation between the samples generated by the two algorithms. optGpSampler for Matlab and Python is available for non-commercial use at: http://cs.ru.nl/~wmegchel/optGpSampler/.

Training augmentation device for the Air Force satellite Control Network

NASA Technical Reports Server (NTRS)

Shoates, Keith B.

1993-01-01

From the 1960's and into the early 1980's satellite operations and control were conducted by Air Force Systems Command (AFSC), now Air Force Materiel Command (AFMC), out of the Satellite Control Facility at Onizuka AFB, CA. AFSC was responsible for acquiring satellite command and control systems and conducting routine satellite operations. The daily operations, consisting of satellite health and status contacts and station keeping activities, were performed for AFSC by a Mission Control Team (MCT) staffed by civilian contractors who were responsible for providing their own technically 'qualified' personnel as satellite operators. An MCT consists of five positions: mission planner, ground controller, planner analyst, orbit analyst, and ranger controller. Most of the training consisted of On-the-Job-Training (OJT) with junior personnel apprenticed to senior personnel until they could demonstrate job proficiency. With most of the satellite operators having 15 to 25 years of experience, there was minimal risk to the mission. In the mid 1980's Air Force Space Command (AFSPACOM) assumed operational responsibility for a newly established control node at Falcon AFB (FAFB) in CO. The satellites and ground system program offices (SPO's) are organized under AFSC's Space and Missiles Systems Center (SMC) to function as a systems engineering and acquisition agency for AFSPACECOM. The collection of the satellite control nodes, ground tracking stations, computer processing equipment, and connecting communications links is referred to as the Air Force Satellite Control Network (AFSCN).

Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation.

PubMed

Li, Xiang; Peng, Ling; Yao, Xiaojing; Cui, Shaolong; Hu, Yuan; You, Chengzeng; Chi, Tianhe

2017-12-01

Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model long-term dependencies, and most neglect spatial correlations. In this paper, a novel long short-term memory neural network extended (LSTME) model that inherently considers spatiotemporal correlations is proposed for air pollutant concentration prediction. Long short-term memory (LSTM) layers were used to automatically extract inherent useful features from historical air pollutant data, and auxiliary data, including meteorological data and time stamp data, were merged into the proposed model to enhance the performance. Hourly PM 2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) concentration data collected at 12 air quality monitoring stations in Beijing City from Jan/01/2014 to May/28/2016 were used to validate the effectiveness of the proposed LSTME model. Experiments were performed using the spatiotemporal deep learning (STDL) model, the time delay neural network (TDNN) model, the autoregressive moving average (ARMA) model, the support vector regression (SVR) model, and the traditional LSTM NN model, and a comparison of the results demonstrated that the LSTME model is superior to the other statistics-based models. Additionally, the use of auxiliary data improved model performance. For the one-hour prediction tasks, the proposed model performed well and exhibited a mean absolute percentage error (MAPE) of 11.93%. In addition, we conducted multiscale predictions over different time spans and achieved satisfactory performance, even for 13-24 h prediction tasks (MAPE = 31.47%). Copyright © 2017 Elsevier Ltd. All rights reserved.

Social Network Status and Depression among Adolescents: An Examination of Social Network Influences and Depressive Symptoms in a Chinese Sample

PubMed Central

Okamoto, Janet; Johnson, C. Anderson; Leventhal, Adam; Milam, Joel; Pentz, Mary Ann; Schwartz, David; Valente, Thomas W.

2012-01-01

Despite the well established influence of peer experiences on adolescent attitudes, thoughts, and behaviors, surprisingly little research has examined the importance of peer context and the increased prevalence of depressive symptoms accompanying the transition into adolescence. Examination of social networks may provide some insight into the role of peers in the vulnerability of some adolescents to depression. To address this issue, we leveraged an existing sample of 5,563 Chinese 10th graders to incorporate social network data into a multilevel regression model of depressive symptoms. We found that, in this sample, being nominated as a friend was more important than being nominated as most liked. Social network centrality was significantly associated with depression; those adolescents who were less connected were more likely to suffer from depression. The risk of depression for those who were marginal members of classroom social networks was substantial. These findings suggest that a social network perspective could help to increase the effectiveness of programs aimed at preventing adolescent depression. PMID:23226988

Ozone measurement system for NASA global air sampling program

NASA Technical Reports Server (NTRS)

Tiefermann, M. W.

1979-01-01

The ozone measurement system used in the NASA Global Air Sampling Program is described. The system uses a commercially available ozone concentration monitor that was modified and repackaged so as to operate unattended in an aircraft environment. The modifications required for aircraft use are described along with the calibration techniques, the measurement of ozone loss in the sample lines, and the operating procedures that were developed for use in the program. Based on calibrations with JPL's 5-meter ultraviolet photometer, all previously published GASP ozone data are biased high by 9 percent. A system error analysis showed that the total system measurement random error is from 3 to 8 percent of reading (depending on the pump diaphragm material) or 3 ppbv, whichever are greater.

Variables Related to Pre-Service Cannabis Use in a Sample of Air Force Enlistees.

ERIC Educational Resources Information Center

Mullins, Cecil J.; And Others

This report is an attempt to add to the existing information about cannabis use, its correlates, and its effects. The sample population consisted of self-admitted abusers of various drugs, identified shortly after entering the Air Force. The subjects (N=4688) were located through the Drug Control Office at Lackland Air Force Base. Variables…

Modeling and Qualification of a Modified Emission Unit for Radioactive Air Emissions Stack Sampling Compliance.

PubMed

Barnett, J Matthew; Yu, Xiao-Ying; Recknagle, Kurtis P; Glissmeyer, John A

2016-11-01

A planned laboratory space and exhaust system modification to the Pacific Northwest National Laboratory Material Science and Technology Building indicated that a new evaluation of the mixing at the air sampling system location would be required for compliance to ANSI/HPS N13.1-2011. The modified exhaust system would add a third fan, thereby increasing the overall exhaust rate out the stack, thus voiding the previous mixing study. Prior to modifying the radioactive air emissions exhaust system, a three-dimensional computational fluid dynamics computer model was used to evaluate the mixing at the sampling system location. Modeling of the original three-fan system indicated that not all mixing criteria could be met. A second modeling effort was conducted with the addition of an air blender downstream of the confluence of the three fans, which then showed satisfactory mixing results. The final installation included an air blender, and the exhaust system underwent full-scale tests to verify velocity, cyclonic flow, gas, and particulate uniformity. The modeling results and those of the full-scale tests show agreement between each of the evaluated criteria. The use of a computational fluid dynamics code was an effective aid in the design process and allowed the sampling system to remain in its original location while still meeting the requirements for sampling at a well mixed location.

Digital Curation of Marine Physical Samples at Ocean Networks Canada

NASA Astrophysics Data System (ADS)

Jenkyns, R.; Tomlin, M. C.; Timmerman, R.

2015-12-01

Ocean Networks Canada (ONC) has collected hundreds of geological, biological and fluid samples from the water column and seafloor during its maintenance expeditions. These samples have been collected by Remotely Operated Vehicles (ROVs), divers, networked and autonomously deployed instruments, and rosettes. Subsequent measurements are used for scientific experiments, calibration of in-situ and remote sensors, monitoring of Marine Protected Areas, and environment characterization. Tracking the life cycles of these samples from collection to dissemination of results with all the pertinent documents (e.g., protocols, imagery, reports), metadata (e.g., location, identifiers, purpose, method) and data (e.g., measurements, taxonomic classification) is a challenge. The initial collection of samples is normally documented in SeaScribe (an ROV dive logging tool within ONC's Oceans 2.0 software) for which ONC has defined semantics and syntax. Next, samples are often sent to individual scientists and institutions (e.g., Royal BC Museum) for processing and storage, making acquisition of results and life cycle metadata difficult. Finally, this information needs to be retrieved and collated such that multiple user scenarios can be addressed. ONC aims to improve and extend its digital infrastructure for physical samples to support this complex array of samples, workflows and applications. However, in order to promote effective data discovery and exchange, interoperability and community standards must be an integral part of the design. Thus, integrating recommendations and outcomes of initiatives like the EarthCube iSamples working groups are essential. Use cases, existing tools, schemas and identifiers are reviewed, while remaining gaps and challenges are identified. The current status, selected approaches and possible future directions to enhance ONC's digital infrastructure for each sample type are presented.

Prediction of Indoor Air Exposure from Outdoor Air Quality Using an Artificial Neural Network Model for Inner City Commercial Buildings.

PubMed

Challoner, Avril; Pilla, Francesco; Gill, Laurence

2015-12-01

NO₂ and particulate matter are the air pollutants of most concern in Ireland, with possible links to the higher respiratory and cardiovascular mortality and morbidity rates found in the country compared to the rest of Europe. Currently, air quality limits in Europe only cover outdoor environments yet the quality of indoor air is an essential determinant of a person's well-being, especially since the average person spends more than 90% of their time indoors. The modelling conducted in this research aims to provide a framework for epidemiological studies by the use of publically available data from fixed outdoor monitoring stations to predict indoor air quality more accurately. Predictions are made using two modelling techniques, the Personal-exposure Activity Location Model (PALM), to predict outdoor air quality at a particular building, and Artificial Neural Networks, to model the indoor/outdoor relationship of the building. This joint approach has been used to predict indoor air concentrations for three inner city commercial buildings in Dublin, where parallel indoor and outdoor diurnal monitoring had been carried out on site. This modelling methodology has been shown to provide reasonable predictions of average NO₂ indoor air quality compared to the monitored data, but did not perform well in the prediction of indoor PM2.5 concentrations. Hence, this approach could be used to determine NO₂ exposures more rigorously of those who work and/or live in the city centre, which can then be linked to potential health impacts.

Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

PubMed

Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

AirCore-HR: a high-resolution column sampling to enhance the vertical description of CH4 and CO2

NASA Astrophysics Data System (ADS)

Membrive, Olivier; Crevoisier, Cyril; Sweeney, Colm; Danis, François; Hertzog, Albert; Engel, Andreas; Bönisch, Harald; Picon, Laurence

2017-06-01

An original and innovative sampling system called AirCore was presented by NOAA in 2010 Karion et al.(2010). It consists of a long ( > 100 m) and narrow ( < 1 cm) stainless steel tube that can retain a profile of atmospheric air. The captured air sample has then to be analyzed with a gas analyzer for trace mole fraction. In this study, we introduce a new AirCore aiming to improve resolution along the vertical with the objectives to (i) better capture the vertical distribution of CO2 and CH4, (ii) provide a tool to compare AirCores and validate the estimated vertical resolution achieved by AirCores. This (high-resolution) AirCore-HR consists of a 300 m tube, combining 200 m of 0.125 in. (3.175 mm) tube and a 100 m of 0.25 in. (6.35 mm) tube. This new configuration allows us to achieve a vertical resolution of 300 m up to 15 km and better than 500 m up to 22 km (if analysis of the retained sample is performed within 3 h). The AirCore-HR was flown for the first time during the annual StratoScience campaign from CNES in August 2014 from Timmins (Ontario, Canada). High-resolution vertical profiles of CO2 and CH4 up to 25 km were successfully retrieved. These profiles revealed well-defined transport structures in the troposphere (also seen in CAMS-ECMWF high-resolution forecasts of CO2 and CH4 profiles) and captured the decrease of CO2 and CH4 in the stratosphere. The multi-instrument gondola also carried two other low-resolution AirCore-GUF that allowed us to perform direct comparisons and study the underlying processing method used to convert the sample of air to greenhouse gases vertical profiles. In particular, degrading the AirCore-HR derived profiles to the low resolution of AirCore-GUF yields an excellent match between both sets of CH4 profiles and shows a good consistency in terms of vertical structures. This fully validates the theoretical vertical resolution achievable by AirCores. Concerning CO2 although a good agreement is found in terms of vertical structure

ESTIMATES OF THE ATMOSPHERIC DEPOSITION OF SULFUR AND NITROGEN SPECIES: CLEAN AIR STATUS AND TRENDS NETWORK. 1990 THROUGH 2000

EPA Science Inventory

The Clean Air Status and Trends Network (CASTNet) was established by EPA in response to the requirements of the 1990 Clean Air Act Amendments. To satisfy these requirements CASTNet was designed to assess and report on geographic patterns and long-term, temporal trends in ambient ...

Passive Samplers for Investigations of Air Quality: Method Description, Implementation, and Comparison to Alternative Sampling Methods

EPA Science Inventory

This Paper covers the basics of passive sampler design, compares passive samplers to conventional methods of air sampling, and discusses considerations when implementing a passive sampling program. The Paper also discusses field sampling and sample analysis considerations to ensu...

The Deployment of Carbon Monoxide Wireless Sensor Network (CO-WSN) for Ambient Air Monitoring

PubMed Central

Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C.; Khang, Soon-Jai

2014-01-01

Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011–2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1–1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring. PMID:24937527

The deployment of carbon monoxide wireless sensor network (CO-WSN) for ambient air monitoring.

PubMed

Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C; Khang, Soon-Jai

2014-06-16

Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011-2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1-1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring.

Use of respondent driven sampling (RDS) generates a very diverse sample of men who have sex with men (MSM) in Buenos Aires, Argentina.

PubMed

Carballo-Diéguez, Alex; Balan, Ivan; Marone, Rubén; Pando, María A; Dolezal, Curtis; Barreda, Victoria; Leu, Cheng-Shiun; Avila, María Mercedes

2011-01-01

Prior research focusing on men who have sex with men (MSM) conducted in Buenos Aires, Argentina, used convenience samples that included mainly gay identified men. To increase MSM sample representativeness, we used Respondent Driven Sampling (RDS) for the first time in Argentina. Using RDS, under certain specified conditions, the observed estimates for the percentage of the population with a specific trait are asymptotically unbiased. We describe, the diversity of the recruited sample, from the point of view of sexual orientation, and contrast the different subgroups in terms of their HIV sexual risk behavior. 500 MSM were recruited using RDS. Behavioral data were collected through face-to-face interviews and Web-based CASI. In contrast with prior studies, RDS generated a very diverse sample of MSM from a sexual identity perspective. Only 24.5% of participants identified as gay; 36.2% identified as bisexual, 21.9% as heterosexual, and 17.4% were grouped as "other." Gay and non-gay identified MSM differed significantly in their sexual behavior, the former having higher numbers of partners, more frequent sexual contacts and less frequency of condom use. One third of the men (gay, 3%; bisexual, 34%, heterosexual, 51%; other, 49%) reported having had sex with men, women and transvestites in the two months prior to the interview. This population requires further study and, potentially, HIV prevention strategies tailored to such diversity of partnerships. Our results highlight the potential effectiveness of using RDS to reach non-gay identified MSM. They also present lessons learned in the implementation of RDS to recruit MSM concerning both the importance and limitations of formative work, the need to tailor incentives to circumstances of the less affluent potential participants, the need to prevent masking, and the challenge of assessing network size.

Use of Respondent Driven Sampling (RDS) Generates a Very Diverse Sample of Men Who Have Sex with Men (MSM) in Buenos Aires, Argentina

PubMed Central

Carballo-Diéguez, Alex; Balan, Ivan; Marone, Rubén; Pando, María A.; Dolezal, Curtis; Barreda, Victoria; Leu, Cheng-Shiun; Ávila, María Mercedes

2011-01-01

Background Prior research focusing on men who have sex with men (MSM) conducted in Buenos Aires, Argentina, used convenience samples that included mainly gay identified men. To increase MSM sample representativeness, we used Respondent Driven Sampling (RDS) for the first time in Argentina. Using RDS, under certain specified conditions, the observed estimates for the percentage of the population with a specific trait are asymptotically unbiased. We describe, the diversity of the recruited sample, from the point of view of sexual orientation, and contrast the different subgroups in terms of their HIV sexual risk behavior. Methodology 500 MSM were recruited using RDS. Behavioral data were collected through face-to-face interviews and Web-based CASI. Conclusion In contrast with prior studies, RDS generated a very diverse sample of MSM from a sexual identity perspective. Only 24.5% of participants identified as gay; 36.2% identified as bisexual, 21.9% as heterosexual, and 17.4% were grouped as “other.” Gay and non-gay identified MSM differed significantly in their sexual behavior, the former having higher numbers of partners, more frequent sexual contacts and less frequency of condom use. One third of the men (gay, 3%; bisexual, 34%, heterosexual, 51%; other, 49%) reported having had sex with men, women and transvestites in the two months prior to the interview. This population requires further study and, potentially, HIV prevention strategies tailored to such diversity of partnerships. Our results highlight the potential effectiveness of using RDS to reach non-gay identified MSM. They also present lessons learned in the implementation of RDS to recruit MSM concerning both the importance and limitations of formative work, the need to tailor incentives to circumstances of the less affluent potential participants, the need to prevent masking, and the challenge of assessing network size. PMID:22102896

Airborne Network Optimization with Dynamic Network Update

DTIC Science & Technology

2015-03-26

Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force Institute of Technology Air University...Member Dr. Barry E. Mullins Member AFIT-ENG-MS-15-M-030 Abstract Modern networks employ congestion and routing management algorithms that can perform...airborne networks. Intelligent agents can make use of Kalman filter predictions to make informed decisions to manage communication in airborne networks. The

TECHNOLOGY EVALUATION REPORT CEREX ENVIRONMENTAL SERVICES UV HOUND POINT SAMPLE AIR MONITOR

EPA Science Inventory

The USEPA's National Homeland Security Research Center (NHSRC) Technology Testing and Evaluation Program (TTEP) is carrying out performance tests on homeland security technologies. Under TTEP, Battelle evaluated the performance of the Cerex UV Hound point sample air monitor in de...

Comparison of indoor air sampling and dust collection methods for fungal exposure assessment using quantitative PCR

EPA Science Inventory

Evaluating fungal contamination indoors is complicated because of the many different sampling methods utilized. In this study, fungal contamination was evaluated using five sampling methods and four matrices for results. The five sampling methods were a 48 hour indoor air sample ...

Scheduling whole-air samples above the Trade Wind Inversion from SUAS using real-time sensors

NASA Astrophysics Data System (ADS)

Freer, J. E.; Greatwood, C.; Thomas, R.; Richardson, T.; Brownlow, R.; Lowry, D.; MacKenzie, A. R.; Nisbet, E. G.

2015-12-01

Small Unmanned Air Systems (SUAS) are increasingly being used in science applications for a range of applications. Here we explore their use to schedule the sampling of air masses up to 2.5km above ground using computer controlled bespoked Octocopter platforms. Whole-air sampling is targeted above, within and below the Trade Wind Inversion (TWI). On-board sensors profiled the TWI characteristics in real time on ascent and, hence, guided the altitudes at which samples were taken on descent. The science driver for this research is investigation of the Southern Methane Anomaly and, more broadly, the hemispheric-scale transport of long-lived atmospheric tracers in the remote troposphere. Here we focus on the practical application of SUAS for this purpose. Highlighting the need for mission planning, computer control, onboard sensors and logistics in deploying such technologies for out of line-of-sight applications. We show how such a platform can be deployed successfully, resulting in some 60 sampling flights within a 10 day period. Challenges remain regarding the deployment of such platforms routinely and cost-effectively, particularly regarding training and support. We present some initial results from the methane sampling and its implication for exploring and understanding the Southern Methane Anomaly.

Estimating the Size of a Large Network and its Communities from a Random Sample

PubMed Central

Chen, Lin; Karbasi, Amin; Crawford, Forrest W.

2017-01-01

Most real-world networks are too large to be measured or studied directly and there is substantial interest in estimating global network properties from smaller sub-samples. One of the most important global properties is the number of vertices/nodes in the network. Estimating the number of vertices in a large network is a major challenge in computer science, epidemiology, demography, and intelligence analysis. In this paper we consider a population random graph G = (V, E) from the stochastic block model (SBM) with K communities/blocks. A sample is obtained by randomly choosing a subset W ⊆ V and letting G(W) be the induced subgraph in G of the vertices in W. In addition to G(W), we observe the total degree of each sampled vertex and its block membership. Given this partial information, we propose an efficient PopULation Size Estimation algorithm, called PULSE, that accurately estimates the size of the whole population as well as the size of each community. To support our theoretical analysis, we perform an exhaustive set of experiments to study the effects of sample size, K, and SBM model parameters on the accuracy of the estimates. The experimental results also demonstrate that PULSE significantly outperforms a widely-used method called the network scale-up estimator in a wide variety of scenarios. PMID:28867924

Estimating the Size of a Large Network and its Communities from a Random Sample.

PubMed

Chen, Lin; Karbasi, Amin; Crawford, Forrest W

2016-01-01

Most real-world networks are too large to be measured or studied directly and there is substantial interest in estimating global network properties from smaller sub-samples. One of the most important global properties is the number of vertices/nodes in the network. Estimating the number of vertices in a large network is a major challenge in computer science, epidemiology, demography, and intelligence analysis. In this paper we consider a population random graph G = ( V, E ) from the stochastic block model (SBM) with K communities/blocks. A sample is obtained by randomly choosing a subset W ⊆ V and letting G ( W ) be the induced subgraph in G of the vertices in W . In addition to G ( W ), we observe the total degree of each sampled vertex and its block membership. Given this partial information, we propose an efficient PopULation Size Estimation algorithm, called PULSE, that accurately estimates the size of the whole population as well as the size of each community. To support our theoretical analysis, we perform an exhaustive set of experiments to study the effects of sample size, K , and SBM model parameters on the accuracy of the estimates. The experimental results also demonstrate that PULSE significantly outperforms a widely-used method called the network scale-up estimator in a wide variety of scenarios.

Intraregional links between the trends in air pollutants observed at the EANET network sites for 2000-2014

NASA Astrophysics Data System (ADS)

Gromov, Sergey A.; Trifonova-Yakovleva, Alisa; Gromov, Sergey S.

2016-04-01

Recent changes in economic development tendencies and environmental protection policies in the East Asian countries raise hopes for improvement of regional air quality in this vast region populated by more than 3 billion people. To recognize anticipated changes in atmospheric pollutants levels, deposition rates and impact on the environment, the Acid Deposition Monitoring Network in East Asia (EANET, http://www.eanet.asia/) is regularly operating region-wide since 2000 in 13 countries. The network provides continuous monitoring data on the air quality and precipitation (including gas-phase and particulate chemistry) at 55 monitoring sites, including 20 remote and 14 rural sites. Observation of soil and inland water environments are performed at more than 30 monitoring sites [1]. In this study we focus on 1) the data quality assessment and preparation and 2) analysis of temporal trends of compositions observed at selected 26 non-urban EANET stations. Speciation includes gas-phase (SO2, HNO3, HCl, NH3) and particulate matter (SO42-, NO3-, Cl-, NH4+, Na+, K+, Mg2+, Ca2+) abundances analysed in samples collected using filterpack technique with sampling duration/frequency of one-two weeks. Data quality assessment (distribution test and manual inspection) allowed us to remove/repair random and operator errors. Wrong sample timing was found for 0.37% (severe) and 34% (mild inconsistency) of the total of 7630 samples regarded. Erroneous data flagging (e.g. missing or below the detection limit) was repaired for 9.3%, respectively. Some 1.8% of severely affected data were corrected (where possible) or removed. Thus refined 15-year dataset is made available for the scientific community. For convenience, we also provide data in netCDF format (per station or in an assembly). Based on this refined dataset, we performed trend analysis using several statistical approaches including quantile regression which provides robust results against outliers and better understanding of trend

DEVELOPMENT OF A SUB-SLAB AIR SAMPLING PROTOCOL TO SUPPORT ASSESSMENT OF VAPOR INTRUSION

EPA Science Inventory

The primary purpose of this research effort is to develop a methodology for sub-slab sampling to support the EPA guidance and vapor intrusion investigations after vapor intrusion has been established at a site. Methodologies for sub-slab air sampling are currently lacking in ref...

Avian influenza H9N2 virus isolated from air samples in LPMs in Jiangxi, China.

PubMed

Zeng, Xiaoxu; Liu, Mingbin; Zhang, Heng; Wu, Jingwen; Zhao, Xiang; Chen, Wenbing; Yang, Lei; He, Fenglan; Fan, Guoyin; Wang, Dayan; Chen, Haiying; Shu, Yuelong

2017-07-24

Recently, avian influenza virus has caused repeated worldwide outbreaks in humans. Live Poultry Markets (LPMs) play an important role in the circulation and reassortment of novel Avian Influenza Virus (AIVs). Aerosol transmission is one of the most important pathways for influenza virus to spread among poultry, from poultry to mammals, and among mammals. In this study, air samples were collected from LPMs in Nanchang city between April 2014 and March 2015 to investigate possible aerosol transmission of AIVs. Air samples were detected for Flu A by Real-Time Reverse Transcription-Polymerase Chain Reaction (RRT-PCR). If samples were positive for Flu A, they were inoculated into 9- to 10-day-old specific-pathogen-free embryonated eggs. If the result was positive, the whole genome of the virus was sequenced by MiSeq. Phylogenetic trees of all 8 segments were constructed using MEGA 6.05 software. To investigate the possible aerosol transmission of AIVs, 807 air samples were collected from LPMs in Nanchang city between April 2014 and March 2015. Based on RRT-PCR results, 275 samples (34.1%) were Flu A positive, and one virus was successfully isolated with embryonated eggs. The virus shared high nucleotide homology with H9N2 AIVs from South China. Our study provides further evidence that the air in LPMs can be contaminated by influenza viruses and their nucleic acids, and this should be considered when choosing and evaluating disinfection strategies in LPMs, such as regular air disinfection. Aerosolized viruses such as the H9N2 virus detected in this study can increase the risk of human infection when people are exposed in LPMs.

Comparison of stationary and personal air sampling with an air dispersion model for children’s ambient exposure to manganese

EPA Science Inventory

Manganese (Mn) is ubiquitous in the environment and essential for normal growth and development, yet excessive exposure can lead to impairments in neurological function. This study modeled ambient Mn concentrations as an alternative to stationary and personal air sampling to asse...

Use of alpha spectroscopy for conducting rapid surveys of transuranic activity on air sample filters and smears.

PubMed

Hayes, Robert B; Peña, Adan M; Goff, Thomas E

2005-08-01

This paper demonstrates the utility of a portable alpha Continuous Air Monitor (CAM) as a bench top scalar counter for multiple sample types. These include using the CAM to count fixed air sample filters and radiological smears. In counting radiological smears, the CAM is used very much like a gas flow proportional counter (GFPC), albeit with a lower efficiency. Due to the typically low background in this configuration, the minimum detectable activity for a 5-min count should be in the range of about 10 dpm which is acceptably below the 20 dpm limit for transuranic isotopes. When counting fixed air sample filters, the CAM algorithm along with other measurable characteristics can be used to identify and quantify the presence of transuranic isotopes in the samples. When the radiological control technician wants to take some credit from naturally occurring radioactive material contributions due to radon progeny producing higher energy peaks (as in the case with a fixed air sample filter), then more elaborate techniques are required. The techniques presented here will generate a decision level of about 43 dpm for such applications. The calibration for this application should alternatively be done using the default values of channels 92-126 for region of interest 1. This can be done within 10 to 15 min resulting in a method to rapidly evaluate air filters for transuranic activity. When compared to the 1-h count technique described by , the technique presented in the present work demonstrates a technique whereby more than two thirds of samples can be rapidly shown (within 10 to 15 min) to be within regulatory compliant limits. In both cases, however, spectral quality checks are required to insure sample self attenuation is not a significant bias in the activity estimates. This will allow the same level of confidence when using these techniques for activity quantification as is presently available for air monitoring activity quantification using CAMs.

Air-dropped sensor network for real-time high-fidelity volcano monitoring

USGS Publications Warehouse

Song, W.-Z.; Huang, R.; Xu, M.; Ma, A.; Shirazi, B.; LaHusen, R.

2009-01-01

This paper presents the design and deployment experience of an air-dropped wireless sensor network for volcano hazard monitoring. The deployment of five stations into the rugged crater of Mount St. Helens only took one hour with a helicopter. The stations communicate with each other through an amplified 802.15.4 radio and establish a self-forming and self-healing multi-hop wireless network. The distance between stations is up to 2 km. Each sensor station collects and delivers real-time continuous seismic, infrasonic, lightning, GPS raw data to a gateway. The main contribution of this paper is the design and evaluation of a robust sensor network to replace data loggers and provide real-time long-term volcano monitoring. The system supports UTC-time synchronized data acquisition with 1ms accuracy, and is online configurable. It has been tested in the lab environment, the outdoor campus and the volcano crater. Despite the heavy rain, snow, and ice as well as gusts exceeding 120 miles per hour, the sensor network has achieved a remarkable packet delivery ratio above 99% with an overall system uptime of about 93.8% over the 1.5 months evaluation period after deployment. Our initial deployment experiences with the system have alleviated the doubts of domain scientists and prove to them that a low-cost sensor network system can support real-time monitoring in extremely harsh environments. Copyright 2009 ACM.

Validation of Networks Derived from Snowball Sampling of Municipal Science Education Actors

ERIC Educational Resources Information Center

von der Fehr, Ane; Sølberg, Jan; Bruun, Jesper

2018-01-01

Social network analysis (SNA) has been used in many educational studies in the past decade, but what these studies have in common is that the populations in question in most cases are defined and known to the researchers studying the networks. Snowball sampling is an SNA methodology most often used to study hidden populations, for example, groups…

Spectral fingerprinting of polycyclic aromatic hydrocarbons in high-volume ambient air samples by constant energy synchronous luminescence spectroscopy

USGS Publications Warehouse

Kerkhoff, M.J.; Lee, T.M.; Allen, E.R.; Lundgren, D.A.; Winefordner, J.D.

1985-01-01

A high-volume sampler fitted with a glass-fiber filter and backed by polyurethane foam (PUF) was employed to collect airborne particulate and gas-phase polycylic aromatic hydrocarbons (PAHs) in ambient air. Samples were collected from four sources representing a range of environmental conditions: gasoline engine exhaust, diesel engine exhaust, air near a heavily traveled interstate site, and air from a moderately polluted urban site. Spectral fingerprints of the unseparated particulate and gas-phase samples were obtained by constant energy synchronous luminescence spectroscopy (CESLS). Five major PAHs in the gas-phase extracts were characterized and estimated. The compatibility of a high-volume sampling method using polyurethane foam coupled with CESLS detection is explored for use as a screening technique for PAHs in ambient air. ?? 1985 American Chemical Society.

Analysis of feature selection with Probabilistic Neural Network (PNN) to classify sources influencing indoor air quality

NASA Astrophysics Data System (ADS)

Saad, S. M.; Shakaff, A. Y. M.; Saad, A. R. M.; Yusof, A. M.; Andrew, A. M.; Zakaria, A.; Adom, A. H.

2017-03-01

There are various sources influencing indoor air quality (IAQ) which could emit dangerous gases such as carbon monoxide (CO), carbon dioxide (CO2), ozone (O3) and particulate matter. These gases are usually safe for us to breathe in if they are emitted in safe quantity but if the amount of these gases exceeded the safe level, they might be hazardous to human being especially children and people with asthmatic problem. Therefore, a smart indoor air quality monitoring system (IAQMS) is needed that able to tell the occupants about which sources that trigger the indoor air pollution. In this project, an IAQMS that able to classify sources influencing IAQ has been developed. This IAQMS applies a classification method based on Probabilistic Neural Network (PNN). It is used to classify the sources of indoor air pollution based on five conditions: ambient air, human activity, presence of chemical products, presence of food and beverage, and presence of fragrance. In order to get good and best classification accuracy, an analysis of several feature selection based on data pre-processing method is done to discriminate among the sources. The output from each data pre-processing method has been used as the input for the neural network. The result shows that PNN analysis with the data pre-processing method give good classification accuracy of 99.89% and able to classify the sources influencing IAQ high classification rate.

Occurrence and quantitative microbial risk assessment of Cryptosporidium and Giardia in soil and air samples.

PubMed

Balderrama-Carmona, Ana Paola; Gortáres-Moroyoqui, Pablo; Álvarez-Valencia, Luis Humberto; Castro-Espinoza, Luciano; Mondaca-Fernández, Iram; Balderas-Cortés, José de Jesús; Chaidez-Quiroz, Cristóbal; Meza-Montenegro, María Mercedes

2014-09-01

Cryptosporidium oocysts and Giardia cysts can be transmitted by the fecal-oral route and may cause gastrointestinal parasitic zoonoses. These zoonoses are common in rural zones due to the parasites being harbored in fecally contaminated soil. This study assessed the risk of illness (giardiasis and cryptosporidiosis) from inhaling and/or ingesting soil and/or airborne dust in Potam, Mexico. To assess the risk of infection, Quantitative Microbial Risk Assessment (QMRA) was employed, with the following steps: (1) hazard identification, (2) hazard exposure, (3) dose-response, and (4) risk characterization. Cryptosporidium oocysts and Giardia cysts were observed in 52% and 57%, respectively, of total soil samples (n=21), and in 60% and 80%, respectively, of air samples (n=12). The calculated annual risks were higher than 9.9 × 10(-1) for both parasites in both types of sample. Soil and air inhalation and/or ingestion are important vehicles for these parasites. To our knowledge, the results obtained in the present study represent the first QMRAs for cryptosporidiosis and giardiasis due to soil and air inhalation/ingestion in Mexico. In addition, this is the first evidence of the microbial air quality around these parasites in rural zones. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Event-triggered synchronization for reaction-diffusion complex networks via random sampling

NASA Astrophysics Data System (ADS)

Dong, Tao; Wang, Aijuan; Zhu, Huiyun; Liao, Xiaofeng

2018-04-01

In this paper, the synchronization problem of the reaction-diffusion complex networks (RDCNs) with Dirichlet boundary conditions is considered, where the data is sampled randomly. An event-triggered controller based on the sampled data is proposed, which can reduce the number of controller and the communication load. Under this strategy, the synchronization problem of the diffusion complex network is equivalently converted to the stability of a of reaction-diffusion complex dynamical systems with time delay. By using the matrix inequality technique and Lyapunov method, the synchronization conditions of the RDCNs are derived, which are dependent on the diffusion term. Moreover, it is found the proposed control strategy can get rid of the Zeno behavior naturally. Finally, a numerical example is given to verify the obtained results.

Artificial Neural Network for Total Laboratory Automation to Improve the Management of Sample Dilution.

PubMed

Ialongo, Cristiano; Pieri, Massimo; Bernardini, Sergio

2017-02-01

Diluting a sample to obtain a measure within the analytical range is a common task in clinical laboratories. However, for urgent samples, it can cause delays in test reporting, which can put patients' safety at risk. The aim of this work is to show a simple artificial neural network that can be used to make it unnecessary to predilute a sample using the information available through the laboratory information system. Particularly, the Multilayer Perceptron neural network built on a data set of 16,106 cardiac troponin I test records produced a correct inference rate of 100% for samples not requiring predilution and 86.2% for those requiring predilution. With respect to the inference reliability, the most relevant inputs were the presence of a cardiac event or surgery and the result of the previous assay. Therefore, such an artificial neural network can be easily implemented into a total automation framework to sensibly reduce the turnaround time of critical orders delayed by the operation required to retrieve, dilute, and retest the sample.

High-resolution real-time optical studies of radiological air sample filtration processes in an environmental continuous air monitor

NASA Astrophysics Data System (ADS)

Rodgers, John C.; Wasiolek, Piotr T.; Schery, Stephen D.; Alcantara, Raul E.

1999-01-01

The need for a continuous air monitor capable of quick and accurate measurements of airborne radioactivity in close proximity to the work environment during waste management, site restoration, and D&D operations led to the Los Alamos National Laboratory development of an environmental continuous air monitor (ECAM). Monitoring the hostile work environment of waste recovery, for example, presents unique challenges for detector design for detectors previously used for the clean room conditions of the typical plutonium laboratory. The environmental and atmospheric conditions (dust, high wind, etc.) influence aerosol particle penetration into the ECAM sampling head as well as the build-up of deposits on the ECAM filter.

Size selective isocyanate aerosols personal air sampling using porous plastic foams

NASA Astrophysics Data System (ADS)

Khanh Huynh, Cong; Duc, Trinh Vu

2009-02-01

As part of a European project (SMT4-CT96-2137), various European institutions specialized in occupational hygiene (BGIA, HSL, IOM, INRS, IST, Ambiente e Lavoro) have established a program of scientific collaboration to develop one or more prototypes of European personal samplers for the collection of simultaneous three dust fractions: inhalable, thoracic and respirable. These samplers based on existing sampling heads (IOM, GSP and cassettes) use Polyurethane Plastic Foam (PUF) according to their porosity to support sampling and separator size of the particles. In this study, the authors present an original application of size selective personal air sampling using chemical impregnated PUF to perform isocyanate aerosols capturing and derivatizing in industrial spray-painting shops.

Prediction of Indoor Air Exposure from Outdoor Air Quality Using an Artificial Neural Network Model for Inner City Commercial Buildings

PubMed Central

Challoner, Avril; Pilla, Francesco; Gill, Laurence

2015-01-01

NO2 and particulate matter are the air pollutants of most concern in Ireland, with possible links to the higher respiratory and cardiovascular mortality and morbidity rates found in the country compared to the rest of Europe. Currently, air quality limits in Europe only cover outdoor environments yet the quality of indoor air is an essential determinant of a person’s well-being, especially since the average person spends more than 90% of their time indoors. The modelling conducted in this research aims to provide a framework for epidemiological studies by the use of publically available data from fixed outdoor monitoring stations to predict indoor air quality more accurately. Predictions are made using two modelling techniques, the Personal-exposure Activity Location Model (PALM), to predict outdoor air quality at a particular building, and Artificial Neural Networks, to model the indoor/outdoor relationship of the building. This joint approach has been used to predict indoor air concentrations for three inner city commercial buildings in Dublin, where parallel indoor and outdoor diurnal monitoring had been carried out on site. This modelling methodology has been shown to provide reasonable predictions of average NO2 indoor air quality compared to the monitored data, but did not perform well in the prediction of indoor PM2.5 concentrations. Hence, this approach could be used to determine NO2 exposures more rigorously of those who work and/or live in the city centre, which can then be linked to potential health impacts. PMID:26633448

A multi-objective assessment of an air quality monitoring network using environmental, economic, and social indicators and GIS-based models.

PubMed

Pope, Ronald; Wu, Jianguo

2014-06-01

In the United States, air pollution is primarily measured by Air Quality Monitoring Networks (AQMN). These AQMNs have multiple objectives, including characterizing pollution patterns, protecting the public health, and determining compliance with air quality standards. In 2006, the U.S. Environmental Protection Agency issued a directive that air pollution agencies assess the performance of their AQMNs. Although various methods to design and assess AQMNs exist, here we demonstrate a geographic information system (GIS)-based approach that combines environmental, economic, and social indicators through the assessment of the ozone (O3) and particulate matter (PM10) networks in Maricopa County, Arizona. The assessment was conducted in three phases: (1) to evaluate the performance of the existing networks, (2) to identify areas that would benefit from the addition of new monitoring stations, and (3) to recommend changes to the AQMN. A comprehensive set of indicators was created for evaluating differing aspects of the AQMNs' objectives, and weights were applied to emphasize important indicators. Indicators were also classified according to their sustainable development goal. Our results showed that O3 was well represented in the county with some redundancy in terms of the urban monitors. The addition of weights to the indicators only had a minimal effect on the results. For O3, urban monitors had greater social scores, while rural monitors had greater environmental scores. The results did not suggest a need for adding more O3 monitoring sites. For PM10, clustered urban monitors were redundant, and weights also had a minimal effect on the results. The clustered urban monitors had overall low scores; sites near point sources had high environmental scores. Several areas were identified as needing additional PM10 monitors. This study demonstrates the usefulness of a multi-indicator approach to assess AQMNs. Network managers and planners may use this method to assess the

Stabilization for sampled-data neural-network-based control systems.

PubMed

Zhu, Xun-Lin; Wang, Youyi

2011-02-01

This paper studies the problem of stabilization for sampled-data neural-network-based control systems with an optimal guaranteed cost. Unlike previous works, the resulting closed-loop system with variable uncertain sampling cannot simply be regarded as an ordinary continuous-time system with a fast-varying delay in the state. By defining a novel piecewise Lyapunov functional and using a convex combination technique, the characteristic of sampled-data systems is captured. A new delay-dependent stabilization criterion is established in terms of linear matrix inequalities such that the maximal sampling interval and the minimal guaranteed cost control performance can be obtained. It is shown that the newly proposed approach can lead to less conservative and less complex results than the existing ones. Application examples are given to illustrate the effectiveness and the benefits of the proposed method.

Air quality measurements-From rubber bands to tapping the rainbow.

PubMed

Hidy, George M; Mueller, Peter K; Altshuler, Samuel L; Chow, Judith C; Watson, John G

2017-06-01

It is axiomatic that good measurements are integral to good public policy for environmental protection. The generalized term for "measurements" includes sampling and quantitation, data integrity, documentation, network design, sponsorship, operations, archiving, and accessing for applications. Each of these components has evolved and advanced over the last 200 years as knowledge of atmospheric chemistry and physics has matured. Air quality was first detected by what people could see and smell in contaminated air. Gaseous pollutants were found to react with certain materials or chemicals, changing the color of dissolved reagents such that their light absorption at selected wavelengths could be related to both the pollutant chemistry and its concentration. Airborne particles have challenged the development of a variety of sensory devices and laboratory assays for characterization of their enormous range of physical and chemical properties. Advanced electronics made possible the sampling, concentration, and detection of gases and particles, both in situ and in laboratory analysis of collected samples. Accurate and precise measurements by these methods have made possible advanced air quality management practices that led to decreasing concentrations over time. New technologies are leading to smaller and cheaper measurement systems that can further expand and enhance current air pollution monitoring networks. Ambient air quality measurement systems have a large influence on air quality management by determining compliance, tracking trends, elucidating pollutant transport and transformation, and relating concentrations to adverse effects. These systems consist of more than just instrumentation, and involve extensive support efforts for siting, maintenance, calibration, auditing, data validation, data management and access, and data interpretation. These requirements have largely been attained for criteria pollutants regulated by National Ambient Air Quality Standards

Optimization of sampling parameters for collection and preconcentration of alveolar air by needle traps.

PubMed

Filipiak, Wojciech; Filipiak, Anna; Ager, Clemens; Wiesenhofer, Helmut; Amann, Anton

2012-06-01

The approach for breath-VOCs' collection and preconcentration by applying needle traps was developed and optimized. The alveolar air was collected from only a few exhalations under visual control of expired CO(2) into a large gas-tight glass syringe and then warmed up to 45 °C for a short time to avoid condensation. Subsequently, a specially constructed sampling device equipped with Bronkhorst® electronic flow controllers was used for automated adsorption. This sampling device allows time-saving collection of expired/inspired air in parallel onto three different needle traps as well as improvement of sensitivity and reproducibility of NT-GC-MS analysis by collection of relatively large (up to 150 ml) volume of exhaled breath. It was shown that the collection of alveolar air derived from only a few exhalations into a large syringe followed by automated adsorption on needle traps yields better results than manual sorption by up/down cycles with a 1 ml syringe, mostly due to avoided condensation and electronically controlled stable sample flow rate. The optimal profile and composition of needle traps consists of 2 cm Carbopack X and 1 cm Carboxen 1000, allowing highly efficient VOCs' enrichment, while injection by a fast expansive flow technique requires no modifications in instrumentation and fully automated GC-MS analysis can be performed with a commercially available autosampler. This optimized analytical procedure considerably facilitates the collection and enrichment of alveolar air, and is therefore suitable for application at the bedside of critically ill patients in an intensive care unit. Due to its simplicity it can replace the time-consuming sampling of sufficient breath volume by numerous up/down cycles with a 1 ml syringe.

Monte Carlo simulation of air sampling methods for the measurement of radon decay products.

PubMed

Sima, Octavian; Luca, Aurelian; Sahagia, Maria

2017-08-01

A stochastic model of the processes involved in the measurement of the activity of the 222 Rn decay products was developed. The distributions of the relevant factors, including air sampling and radionuclide collection, are propagated using Monte Carlo simulation to the final distribution of the measurement results. The uncertainties of the 222 Rn decay products concentrations in the air are realistically evaluated. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial and temporal trends from an air quality sensor network near a heavily trafficked intersection

NASA Astrophysics Data System (ADS)

Orlando, P.; Vo, D.; Giossi, C.; George, L.

2017-12-01

With the world-wide increase in urbanization and the increasing usage of combustion vehicles in urban areas, traffic-related air pollution is a growing health hazard. However, there are limited studies that examine the spatial and temporal impacts of traffic-related pollutants within cities. In particular, there are few studies that look at traffic management and its potential for pollution mitigation. In a previous study we examined roadway pollution and traffic parameters with one roadway station instrumented with standard measurement instruments. With the advent of low-cost air pollution sensors, we have expanded our work by observing multiple sites within a neighborhood to understand spatial and temporal exposures. We have deployed a high-density sensor network around urban arterial corridors in SE Portland, Oregon. This network consisted of ten nodes measuring CO, NO, NO2 and O3, and ten nodes measuring CO, CO2, VOC and PM2.5. The co-location of standard measurement instruments provided insight towards the utility of our low-cost sensor network, as the different nodes varied in cost, and potentially in quality. We have identified near-real-time temporal trends and local-scale spatial patterns during the summer of 2017. Meteorological and traffic data were included to further characterize these patterns, exploring the potential for pollution mitigation.

Residues of 2, 4-D in air samples from Saskatchewan: 1966-1975.

PubMed

Grover, R; Kerr, L A; Wallace, K; Yoshida, K; Maybank, J

1976-01-01

Residues of 2,4-D (2,4-dichlorophenoxyacetic acid) in air samples from several sampling sites in central and southern Saskatchewan during the spraying seasons in the 1966-68 and 1970-75 periods were determined by gas-liquid chromatographic techniques. Initially, individual esters of 2,4-D were characterized by retention times and confirmed further by co-injection and dual column procedures. Since 1973, however, only total 2,4-D acid levels in air samples have been determined after esterification to the methyl ester and confirmed by gc/ms techniques whenever possible. Up to 50% of the daily samples collected during the spraying season at any of the locations and during any given year contained 2,4-D, with butyl esters being found most frequently. The daily 24-hr mean atmospheric concentrations of 2,4-D ranged from 0.01 to 1.22 mug/m3, 0.01 to 13.50 mug/m3, and 0.05 to 0.59 mug/m3 for the iso-propyl, mixed butyl and iso-octyl esters, respectively. Even when the samples were analysed for the total 2,4-D content, i.e. from 1973 onwards, the maximum level of the total acid reached only 23.14 mug/m3. In any given year and at any of the sampling sites, about 30% of the samples contained less than 0.01 mug/m3 of 2,4-D. In another 40% of the samples, the levels of 2,4-D ranged from 0.01 to 0.099 mug/m3. Only about 30% of the samples contained 2,4-D concentrations higher than 0.1 mug/m3, with only 10% or less exceeding 1 mug/m3. None of the samples, obtained with the high volume particulate sampler, showed any detectable levels of 2,4-D, indicating little or no transport of 2,4-D adsorbed on dust particles or as crystals of amine salts.

Air sampling to assess potential generation of aerosolized viable bacteria during flow cytometric analysis of unfixed bacterial suspensions

PubMed Central

Carson, Christine F; Inglis, Timothy JJ

2018-01-01

This study investigated aerosolized viable bacteria in a university research laboratory during operation of an acoustic-assisted flow cytometer for antimicrobial susceptibility testing by sampling room air before, during and after flow cytometer use. The aim was to assess the risk associated with use of an acoustic-assisted flow cytometer analyzing unfixed bacterial suspensions. Air sampling in a nearby clinical laboratory was conducted during the same period to provide context for the existing background of microorganisms that would be detected in the air. The three species of bacteria undergoing analysis by flow cytometer in the research laboratory were Klebsiella pneumoniae, Burkholderia thailandensis and Streptococcus pneumoniae. None of these was detected from multiple 1000 L air samples acquired in the research laboratory environment. The main cultured bacteria in both locations were skin commensal and environmental bacteria, presumed to have been disturbed or dispersed in laboratory air by personnel movements during routine laboratory activities. The concentrations of bacteria detected in research laboratory air samples were reduced after interventional cleaning measures were introduced and were lower than those in the diagnostic clinical microbiology laboratory. We conclude that our flow cytometric analyses of unfixed suspensions of K. pneumoniae, B. thailandensis and S. pneumoniae do not pose a risk to cytometer operators or other personnel in the laboratory but caution against extrapolation of our results to other bacteria and/or different flow cytometric experimental procedures. PMID:29608197

Day and night variation in chemical composition and toxicological responses of size segregated urban air PM samples in a high air pollution situation

NASA Astrophysics Data System (ADS)

Jalava, P. I.; Wang, Q.; Kuuspalo, K.; Ruusunen, J.; Hao, L.; Fang, D.; Väisänen, O.; Ruuskanen, A.; Sippula, O.; Happo, M. S.; Uski, O.; Kasurinen, S.; Torvela, T.; Koponen, H.; Lehtinen, K. E. J.; Komppula, M.; Gu, C.; Jokiniemi, J.; Hirvonen, M.-R.

2015-11-01

Urban air particulate pollution is a known cause for adverse human health effects worldwide. China has encountered air quality problems in recent years due to rapid industrialization. Toxicological effects induced by particulate air pollution vary with particle sizes and season. However, it is not known how distinctively different photochemical activity and different emission sources during the day and the night affect the chemical composition of the PM size ranges and subsequently how it is reflected to the toxicological properties of the PM exposures. The particulate matter (PM) samples were collected in four different size ranges (PM10-2.5; PM2.5-1; PM1-0.2 and PM0.2) with a high volume cascade impactor. The PM samples were extracted with methanol, dried and thereafter used in the chemical and toxicological analyses. RAW264.7 macrophages were exposed to the particulate samples in four different doses for 24 h. Cytotoxicity, inflammatory parameters, cell cycle and genotoxicity were measured after exposure of the cells to particulate samples. Particles were characterized for their chemical composition, including ions, element and PAH compounds, and transmission electron microscopy (TEM) was used to take images of the PM samples. Chemical composition and the induced toxicological responses of the size segregated PM samples showed considerable size dependent differences as well as day to night variation. The PM10-2.5 and the PM0.2 samples had the highest inflammatory potency among the size ranges. Instead, almost all the PM samples were equally cytotoxic and only minor differences were seen in genotoxicity and cell cycle effects. Overall, the PM0.2 samples had the highest toxic potential among the different size ranges in many parameters. PAH compounds in the samples and were generally more abundant during the night than the day, indicating possible photo-oxidation of the PAH compounds due to solar radiation. This was reflected to different toxicity in the PM

A recurrent neural network for classification of unevenly sampled variable stars

NASA Astrophysics Data System (ADS)

Naul, Brett; Bloom, Joshua S.; Pérez, Fernando; van der Walt, Stéfan

2018-02-01

Astronomical surveys of celestial sources produce streams of noisy time series measuring flux versus time (`light curves'). Unlike in many other physical domains, however, large (and source-specific) temporal gaps in data arise naturally due to intranight cadence choices as well as diurnal and seasonal constraints1-5. With nightly observations of millions of variable stars and transients from upcoming surveys4,6, efficient and accurate discovery and classification techniques on noisy, irregularly sampled data must be employed with minimal human-in-the-loop involvement. Machine learning for inference tasks on such data traditionally requires the laborious hand-coding of domain-specific numerical summaries of raw data (`features')7. Here, we present a novel unsupervised autoencoding recurrent neural network8 that makes explicit use of sampling times and known heteroskedastic noise properties. When trained on optical variable star catalogues, this network produces supervised classification models that rival other best-in-class approaches. We find that autoencoded features learned in one time-domain survey perform nearly as well when applied to another survey. These networks can continue to learn from new unlabelled observations and may be used in other unsupervised tasks, such as forecasting and anomaly detection.

A New Black Carbon Sensor for Dense Air Quality Monitoring Networks

PubMed Central

Caubel, Julien J.; Cados, Troy E.; Kirchstetter, Thomas W.

2018-01-01

Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)—a major component of particulate matter pollution associated with adverse human health risks—is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD’s sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval). PMID:29494528

A New Black Carbon Sensor for Dense Air Quality Monitoring Networks.

PubMed

Caubel, Julien J; Cados, Troy E; Kirchstetter, Thomas W

2018-03-01

Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)-a major component of particulate matter pollution associated with adverse human health risks-is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD's sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval).

Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons

PubMed Central

Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang

2011-01-01

The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic features of their firing activity and the experimentally observed trial-to-trial variability of neural systems in the brain. In principle there exists a powerful computational framework for stochastic computations, probabilistic inference by sampling, which can explain a large number of macroscopic experimental data in neuroscience and cognitive science. But it has turned out to be surprisingly difficult to create a link between these abstract models for stochastic computations and more detailed models of the dynamics of networks of spiking neurons. Here we create such a link and show that under some conditions the stochastic firing activity of networks of spiking neurons can be interpreted as probabilistic inference via Markov chain Monte Carlo (MCMC) sampling. Since common methods for MCMC sampling in distributed systems, such as Gibbs sampling, are inconsistent with the dynamics of spiking neurons, we introduce a different approach based on non-reversible Markov chains that is able to reflect inherent temporal processes of spiking neuronal activity through a suitable choice of random variables. We propose a neural network model and show by a rigorous theoretical analysis that its neural activity implements MCMC sampling of a given distribution, both for the case of discrete and continuous time. This provides a step towards closing the gap between abstract functional models of cortical computation and more detailed models of networks of spiking neurons. PMID:22096452

Marine Technician's Handbook, Instructions for Taking Air Samples on Board Ship: Carbon Dioxide Project.

ERIC Educational Resources Information Center

Keeling, Charles D.

This booklet is one of a series intended to provide explicit instructions for the collection of oceanographic data and samples at sea. The methods and procedures described have been used by the Scripps Institution of Oceanography and found reliable and up-to-date. Instructions are given for taking air samples on board ship to determine the…

Active AirCore Sampling: Constraining Point Sources of Methane and Other Gases with Fixed Wing Unmanned Aerial Systems

NASA Astrophysics Data System (ADS)

Bent, J. D.; Sweeney, C.; Tans, P. P.; Newberger, T.; Higgs, J. A.; Wolter, S.

2017-12-01

Accurate estimates of point source gas emissions are essential for reconciling top-down and bottom-up greenhouse gas measurements, but sampling such sources is challenging. Remote sensing methods are limited by resolution and cloud cover; aircraft methods are limited by air traffic control clearances, and the need to properly determine boundary layer height. A new sampling approach leverages the ability of unmanned aerial systems (UAS) to measure all the way to the surface near the source of emissions, improving sample resolution, and reducing the need to characterize a wide downstream swath, or measure to the full height of the planetary boundary layer (PBL). The "Active-AirCore" sampler, currently under development, will fly on a fixed wing UAS in Class G airspace, spiraling from the surface to 1200 ft AGL around point sources such as leaking oil wells to measure methane, carbon dioxide and carbon monoxide. The sampler collects a 100-meter long sample "core" of air in an 1/8" passivated stainless steel tube. This "core" is run on a high-precision instrument shortly after the UAS is recovered. Sample values are mapped to a specific geographic location by cross-referencing GPS and flow/pressure metadata, and fluxes are quantified by applying Gauss's theorem to the data, mapped onto the spatial "cylinder" circumscribed by the UAS. The AirCore-Active builds off the sampling ability and analytical approach of the related AirCore sampler, which profiles the atmosphere passively using a balloon launch platform, but will add an active pumping capability needed for near-surface horizontal sampling applications. Here, we show design elements, laboratory and field test results for methane, describe the overall goals of the mission, and discuss how the platform can be adapted, with minimal effort, to measure other gas species.

40 CFR 58.10 - Annual monitoring network plan and periodic network assessment.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Annual monitoring network plan and periodic network assessment. 58.10 Section 58.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.10 Annual...

40 CFR 58.10 - Annual monitoring network plan and periodic network assessment.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Annual monitoring network plan and periodic network assessment. 58.10 Section 58.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.10 Annual...

Modeling Air Traffic Management Technologies with a Queuing Network Model of the National Airspace System

NASA Technical Reports Server (NTRS)

Long, Dou; Lee, David; Johnson, Jesse; Gaier, Eric; Kostiuk, Peter

1999-01-01

This report describes an integrated model of air traffic management (ATM) tools under development in two National Aeronautics and Space Administration (NASA) programs -Terminal Area Productivity (TAP) and Advanced Air Transport Technologies (AATT). The model is made by adjusting parameters of LMINET, a queuing network model of the National Airspace System (NAS), which the Logistics Management Institute (LMI) developed for NASA. Operating LMINET with models of various combinations of TAP and AATT will give quantitative information about the effects of the tools on operations of the NAS. The costs of delays under different scenarios are calculated. An extension of Air Carrier Investment Model (ACIM) under ASAC developed by the Institute for NASA maps the technologies' impacts on NASA operations into cross-comparable benefits estimates for technologies and sets of technologies.

Irreversible sorption of trace concentrations of perfluorocarboxylic acids to fiber filters used for air sampling

NASA Astrophysics Data System (ADS)

Arp, Hans Peter H.; Goss, Kai-Uwe

Due to the apparent environmental omnipresence of perfluorocarboxylic acids (PFAs), an increasing number of researchers are investigating their ambient particle- and gas-phase concentrations. Typically this is done using a high-volume air sampler equipped with Quartz Fiber Filters (QFFs) or Glass Fiber Filters (GFFs) to sample the particle-bound PFAs and downstream sorbents to sample the gas-phase PFAs. This study reports that at trace, ambient concentrations gas-phase PFAs sorb to QFFs and GFFs irreversibly and hardly pass through these filters to the downstream sorbents. As a consequence, it is not possible to distinguish between particle- and gas-phase concentrations, or to distinguish concentrations on different particle size fractions, unless precautions are taken. Failure to take such precautions could have already caused reported data to be misinterpreted. Here it is also reported that deactivating QFFs and GFFs with a silylating agent renders them suitable for sampling PFAs. Based on the presented study, a series of recommendations for air-sampling PFAs are provided.

Comparison of Air Impaction and Electrostatic Dust Collector Sampling Methods to Assess Airborne Fungal Contamination in Public Buildings.

PubMed

Normand, Anne-Cécile; Ranque, Stéphane; Cassagne, Carole; Gaudart, Jean; Sallah, Kankoé; Charpin, Denis-André; Piarroux, Renaud

2016-03-01

Many ailments can be linked to exposure to indoor airborne fungus. However, obtaining a precise measurement of airborne fungal levels is complicated partly due to indoor air fluctuations and non-standardized techniques. Electrostatic dust collector (EDC) sampling devices have been used to measure a wide range of airborne analytes, including endotoxins, allergens, β-glucans, and microbial DNA in various indoor environments. In contrast, viable mold contamination has only been assessed in highly contaminated environments such as farms and archive buildings. This study aimed to assess the use of EDCs, compared with repeated air-impactor measurements, to assess airborne viable fungal flora in moderately contaminated indoor environments. Indoor airborne fungal flora was cultured from EDCs and daily air-impaction samples collected in an office building and a daycare center. The quantitative fungal measurements obtained using a single EDC significantly correlated with the cumulative measurement of nine daily air impactions. Both methods enabled the assessment of fungal exposure, although a few differences were observed between the detected fungal species and the relative quantity of each species. EDCs were also used over a 32-month period to monitor indoor airborne fungal flora in a hospital office building, which enabled us to assess the impact of outdoor events (e.g. ground excavations) on the fungal flora levels on the indoor environment. In conclusion, EDC-based measurements provided a relatively accurate profile of the viable airborne flora present during a sampling period. In particular, EDCs provided a more representative assessment of fungal levels compared with single air-impactor sampling. The EDC technique is also simpler than performing repetitive air-impaction measures over the course of several consecutive days. EDC is a versatile tool for collecting airborne samples and was efficient for measuring mold levels in indoor environments. © The Author 2015

Optimal Design of Air Quality Monitoring Network and its Application in an Oil Refinery Plant: An Approach to Keep Health Status of Workers.

PubMed

ZoroufchiBenis, Khaled; Fatehifar, Esmaeil; Ahmadi, Javad; Rouhi, Alireza

2015-01-01

Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availability of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. A multi-pollutant method (implemented as a MATLAB program) was explored for configur-ing an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids) according to their ability to represent the ambient concentration. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a sta-tion's dosage to the total dosage in the network. Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network efficiency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health.

Across North America tracer experiment (ANATEX): Sampling and analysis

NASA Astrophysics Data System (ADS)

Draxler, R. R.; Dietz, R.; Lagomarsino, R. J.; Start, G.

Between 5 January 1987 and 29 March 1987, there were 33 releases of different tracers from each of two sites: Glasgow, MT and St. Cloud, MN. The perfluorocarbon tracers were routinely released in a 3-h period every 2.5 days, alternating between daytime and night-time tracer releases. Ground-level air samples of 24-h duration were taken at 77 sites mostly located near rawinsonde stations east of 105°W and between 26°N and 55°N. Weekly air samples were taken at 12 remote sites between San Diego, CA and Pt. Barrow, AK and between Norway and the Canary Islands. Short-term 6-h samples were collected at ground level and 200 m AGL along an arc of five towers between Tulsa, OK and Green Bay, WI. Aircraft sampling within several hundred kilometers of both tracer release sites was used to establish the initial tracer path. Experimental design required improved sampler performance, new tracers with lower atmospheric backgrounds, and improvements in analytic precision. The advances to the perfluorocarbon tracer system are discussed in detail. Results from the tracer sampling showed that the average and peak concentrations measured over the daily ground-level sampling network were consistent with what would be calculated using mass conservative approaches. however, ground-level samples from individual tracer patterns showed considerable complexity due to vertical stability or the interaction of the tracer plumes with low pressure and frontal systems. These systems could pass right through the tracer plume without appreciable effect. Aircraft tracer measurements are used to confirm the initial tracer trajectory when the narrow plume may miss the coarser spaced ground-level sampling network. Tower tracer measurements showed a more complex temporal structure than evident from the longer duration ground-level sampling sites. Few above background plume measurements were evident in the more distant remote sampling network due to larger than expected uncertainties in the ambient

Comparison of Passive and Active Air Sampling (PAAS) Methods for PCBs – A Pilot Study in New York City Schools

EPA Science Inventory

PCBs were used extensively in school building materials (caulk and lighting fixture ballasts) during the approximate period of 1950-1978. Most of the schools built nationwide during this period have not had indoor air sampling conducted for PCBs. Passive air sampling holds promi...

Mathematical estimation of the level of microbial contamination on spacecraft surfaces by volumetric air sampling

NASA Technical Reports Server (NTRS)

Oxborrow, G. S.; Roark, A. L.; Fields, N. D.; Puleo, J. R.

1974-01-01

Microbiological sampling methods presently used for enumeration of microorganisms on spacecraft surfaces require contact with easily damaged components. Estimation of viable particles on surfaces using air sampling methods in conjunction with a mathematical model would be desirable. Parameters necessary for the mathematical model are the effect of angled surfaces on viable particle collection and the number of viable cells per viable particle. Deposition of viable particles on angled surfaces closely followed a cosine function, and the number of viable cells per viable particle was consistent with a Poisson distribution. Other parameters considered by the mathematical model included deposition rate and fractional removal per unit time. A close nonlinear correlation between volumetric air sampling and airborne fallout on surfaces was established with all fallout data points falling within the 95% confidence limits as determined by the mathematical model.

Potential contamination of shipboard air samples by diffusive emissions of PCBs and other organic pollutants: implications and solutions.

PubMed

Lohmann, Rainer; Jaward, Foday M; Durham, Louise; Barber, Jonathan L; Ockenden, Wendy; Jones, Kevin C; Bruhn, Regina; Lakaschus, Soenke; Dachs, Jordi; Booij, Kees

2004-07-15

Air samples were taken onboard the RRS Bransfield on an Atlantic cruise from the United Kingdom to Halley, Antarctica, from October to December 1998, with the aim of establishing PCB oceanic background air concentrations and assessing their latitudinal distribution. Great care was taken to minimize pre- and post-collection contamination of the samples, which was validated through stringent QA/QC procedures. However, there is evidence that onboard contamination of the air samples occurred,following insidious, diffusive emissions on the ship. Other data (for PCBs and other persistent organic pollutants (POPs)) and examples of shipboard contamination are presented. The implications of these findings for past and future studies of global POPs distribution are discussed. Recommendations are made to help critically appraise and minimize the problems of insidious/diffusive shipboard contamination.

Development of a wireless air pollution sensor package for aerial-sampling of emissions

EPA Science Inventory

A new sensor system for mobile and aerial emission sampling was developed for open area pollutant sources, such as prescribed forest burns. The sensor system, termed “Kolibri”, consists of multiple low-cost air quality sensors measuring CO2, CO, samplers for particulate matter wi...

Structural Effects of Network Sampling Coverage I: Nodes Missing at Random1.

PubMed

Smith, Jeffrey A; Moody, James

2013-10-01

Network measures assume a census of a well-bounded population. This level of coverage is rarely achieved in practice, however, and we have only limited information on the robustness of network measures to incomplete coverage. This paper examines the effect of node-level missingness on 4 classes of network measures: centrality, centralization, topology and homophily across a diverse sample of 12 empirical networks. We use a Monte Carlo simulation process to generate data with known levels of missingness and compare the resulting network scores to their known starting values. As with past studies (Borgatti et al 2006; Kossinets 2006), we find that measurement bias generally increases with more missing data. The exact rate and nature of this increase, however, varies systematically across network measures. For example, betweenness and Bonacich centralization are quite sensitive to missing data while closeness and in-degree are robust. Similarly, while the tau statistic and distance are difficult to capture with missing data, transitivity shows little bias even with very high levels of missingness. The results are also clearly dependent on the features of the network. Larger, more centralized networks are generally more robust to missing data, but this is especially true for centrality and centralization measures. More cohesive networks are robust to missing data when measuring topological features but not when measuring centralization. Overall, the results suggest that missing data may have quite large or quite small effects on network measurement, depending on the type of network and the question being posed.

Evaluation of solid sorbents for the determination of fenhexamid, metalaxyl-M, pyrimethanil, malathion and myclobutanil residues in air samples: application to monitoring malathion and fenhexamid dissipation in greenhouse air using C-18 or Supelpak-2 for sampling.

PubMed

Tsiropoulos, Nikolaos G; Bakeas, Evangelos B; Raptis, Vasilios; Batistatou, Stavroula S

2006-07-28

A methodology is described for greenhouse air analysis by sampling fenhexamid, pyrimethanil, malathion, metalaxyl-M and myclobutanil in solid sorbents. Pesticides were determined by gas chromatography with NP Detector. The trapping efficiency of XAD-2, XAD-4, Supelpak-2, Florisil and C-18 at different sampling conditions (rate, time and air humidity) and pesticides concentration levels has been evaluated. No breakthrough was observed in the range of concentration studied (0.10-75 microg of each pesticide). In almost all the cases good stability results were obtained. Personal pumps have been used with selected sorbents (Supelpak-2 and C-18) in order to sample malathion and fenhexamid in air of experimental greenhouse after their application in a tomato crop. The dissipation process of the analytes in various time periods after application has been studied. Malathion concentrations varied between 20.1 microg m(-3) just after application and 1.06 microg m(-3) 3 days later. Fenhexamid concentrations, determined by high performance liquid chromatography with UV detection, fall rapidly; after 12 h post-application being below 0.50 microg m(-3).

Concentration and characteristics of depleted uranium in water, air and biological samples collected in Serbia and Montenegro.

PubMed

Jia, Guogang; Belli, Maria; Sansone, Umberto; Rosamilia, Silvia; Gaudino, Stefania

2005-09-01

During the Balkan conflicts, in 1995 and 1999, depleted uranium (DU) rounds were employed and were left in the battlefield. Health concern is related to the risk arising from contamination of the environment with DU penetrators and dust. In order to evaluate the impact of DU on the environment and population in Serbia and Montenegro, radiological surveys of DU in water, air and biological samples were carried out over the period 27 October-5 November 2001. The uranium isotopic concentrations in biological samples collected in Serbia and Montenegro, mainly lichens and barks, were found to be in the range of 0.67-704 Bqkg(-1) for (238)U, 0.48-93.9 Bqkg(-1) for (234)U and 0.02-12.2 Bqkg(-1) for (235)U, showing uranium levels to be higher than in the samples collected at the control sites. Moreover, (236)U was detectable in some of the samples. The isotopic ratios of (234)U/(238)U showed DU to be detectable in many biological samples at all examined sites, especially in Montenegro, indicating widespread ground-surface DU contamination, albeit at very low level. The uranium isotopic concentrations in air obtained from the air filter samples collected in Serbia and Montenegro were found to be in the range of 1.99-42.1 microBqm(-3) for (238)U, 0.96-38.0 microBqm(-3) for (234)U, and 0.05-1.83 microBqm(-3) for (235)U, being in the typical range of natural uranium values. Thus said, most of the air samples are DU positive, this fact agreeing well with the widespread DU contamination detected in the biological samples. The uranium concentrations in water samples collected in Serbia and Montenegro were found to be in the range of 0.40-21.9 mBql(-1) for (238)U, 0.27-28.1 mBql(-1) for (234)U, and 0.01-0.88 mBql(-1) for (235)U, these values being much lower than those in mineral water found in central Italy and below the WHO guideline for drinking water. From a radiotoxicological point of view, at this moment there is no significant radiological risk related to these investigated

Vulnerability of network of networks

NASA Astrophysics Data System (ADS)

Havlin, S.; Kenett, D. Y.; Bashan, A.; Gao, J.; Stanley, H. E.

2014-10-01

Our dependence on networks - be they infrastructure, economic, social or others - leaves us prone to crises caused by the vulnerabilities of these networks. There is a great need to develop new methods to protect infrastructure networks and prevent cascade of failures (especially in cases of coupled networks). Terrorist attacks on transportation networks have traumatized modern societies. With a single blast, it has become possible to paralyze airline traffic, electric power supply, ground transportation or Internet communication. How, and at which cost can one restructure the network such that it will become more robust against malicious attacks? The gradual increase in attacks on the networks society depends on - Internet, mobile phone, transportation, air travel, banking, etc. - emphasize the need to develop new strategies to protect and defend these crucial networks of communication and infrastructure networks. One example is the threat of liquid explosives a few years ago, which completely shut down air travel for days, and has created extreme changes in regulations. Such threats and dangers warrant the need for new tools and strategies to defend critical infrastructure. In this paper we review recent advances in the theoretical understanding of the vulnerabilities of interdependent networks with and without spatial embedding, attack strategies and their affect on such networks of networks as well as recently developed strategies to optimize and repair failures caused by such attacks.

Data Quality Objectives for Regulatory Requirements for Hazardous and Radioactive Air Emissions Sampling and Analysis

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

MULKEY, C.H.

1999-07-06

This document describes the results of the data quality objective (DQO) process undertaken to define data needs for state and federal requirements associated with toxic, hazardous, and/or radiological air emissions under the jurisdiction of the River Protection Project (RPP). Hereafter, this document is referred to as the Air DQO. The primary drivers for characterization under this DQO are the regulatory requirements pursuant to Washington State regulations, that may require sampling and analysis. The federal regulations concerning air emissions are incorporated into the Washington State regulations. Data needs exist for nonradioactive and radioactive waste constituents and characteristics as identified through themore » DQO process described in this document. The purpose is to identify current data needs for complying with regulatory drivers for the measurement of air emissions from RPP facilities in support of air permitting. These drivers include best management practices; similar analyses may have more than one regulatory driver. This document should not be used for determining overall compliance with regulations because the regulations are in constant change, and this document may not reflect the latest regulatory requirements. Regulatory requirements are also expected to change as various permits are issued. Data needs require samples for both radionuclides and nonradionuclide analytes of air emissions from tanks and stored waste containers. The collection of data is to support environmental permitting and compliance, not for health and safety issues. This document does not address health or safety regulations or requirements (those of the Occupational Safety and Health Administration or the National Institute of Occupational Safety and Health) or continuous emission monitoring systems. This DQO is applicable to all equipment, facilities, and operations under the jurisdiction of RPP that emit or have the potential to emit regulated air pollutants.« less

Transportation Network Topologies

NASA Technical Reports Server (NTRS)

Holmes, Bruce J.; Scott, John M.

2004-01-01

A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21PstP thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within

Transportation Network Topologies

NASA Technical Reports Server (NTRS)

Holmes, Bruce J.; Scott, John

2004-01-01

A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21st thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within which

Air Quality and Road Emission Results for Fort Stewart, Georgia

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

Kirkham, Randy R.; Driver, Crystal J.; Chamness, Mickie A.

2004-02-02

The Directorate of Public Works Environmental & Natural Resources Division (Fort Stewart /Hunter Army Airfield) contracted with the Pacific Northwest National Laboratory (PNNL) to monitor particulate matter (PM) concentrations on Fort Stewart, Georgia. The purpose of this investigation was to establish a PM sampling network using monitoring equipment typically used in U.S. Environmental Protection Agency (EPA) ''saturation sampling'', to determine air quality on the installation. In this initial study, the emphasis was on training-generated PM, not receptor PM loading. The majority of PM samples were 24-hr filter-based samples with sampling frequency ranging from every other day, to once every sixmore » days synchronized with the EPA 6th day national sampling schedule. Eight measurement sites were established and used to determine spatial variability in PM concentrations and evaluate whether fluctuations in PM appear to result from training activities and forest management practices on the installation. Data collected to date indicate the average installation PM2.5 concentration is lower than that of nearby urban Savannah, Georgia. At three sites near the installation perimeter, analyses to segregate PM concentrations by direction of air flow across the installation boundary indicate that air (below 80 ft) leaving the installation contains less PM2.5 than that entering the installation. This is reinforced by the observation that air near the ground is cleaner on average than the air at the top of the canopy.« less

High pressure air compressor valve fault diagnosis using feedforward neural networks

NASA Astrophysics Data System (ADS)

James Li, C.; Yu, Xueli

1995-09-01

Feedforward neural networks (FNNs) are developed and implemented to classify a four-stage high pressure air compressor into one of the following conditions: baseline, suction or exhaust valve faults. These FNNs are used for the compressor's automatic condition monitoring and fault diagnosis. Measurements of 39 variables are obtained under different baseline conditions and third-stage suction and exhaust valve faults. These variables include pressures and temperatures at all stages, voltage between phase aand phase b, voltage between phase band phase c, total three-phase real power, cooling water flow rate, etc. To reduce the number of variables, the amount of their discriminatory information is quantified by scattering matrices to identify statistical significant ones. Measurements of the selected variables are then used by a fully automatic structural and weight learning algorithm to construct three-layer FNNs to classify the compressor's condition. This learning algorithm requires neither guesses of initial weight values nor number of neurons in the hidden layer of an FNN. It takes an incremental approach in which a hidden neuron is trained by exemplars and then augmented to the existing network. These exemplars are then made orthogonal to the newly identified hidden neuron. They are subsequently used for the training of the next hidden neuron. The betterment continues until a desired accuracy is reached. After the neural networks are established, novel measurements from various conditions that haven't been previously seen by the FNNs are then used to evaluate their ability in fault diagnosis. The trained neural networks provide very accurate diagnosis for suction and discharge valve defects.

CASTNet Air Toxics Monitoring Program (CATMP): VOC and carbonyl data for July, 1993 through March, 1994

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

Harlos, D.P.; Edgerton, E.S.

1994-12-31

The US EPA has, under the auspices of the CASTNet program (Clean Air Status and Trends Network), initiated the CASTNet Air Toxics Monitoring Program (CATMP). Volatile Organic Compounds (VOC) and carbonyls and metals are sampled for 24-hour periods on a 12-day schedule using TO-14 samplers (SUMMA canisters) and dinitrophenylhydrazine-coated (dmph) sorbent cartridges and high volume particle samplers. Sampling was begun at most sites in July of 1993. The sites are operated by state and local air pollution control programs and all analysis is performed by Environmental Science and Engineering (ESE) in Gainesville, Florida. The network currently supports 15 VOC sites,more » of which 7 also sample carbonyls. Three sites sample metals only in Pinellas County, Florida. The limits of detection of 0.05 ppb for VOCs allow routine tracking of a wide range of pollutants including several greenhouse gases, transportation pollutants and photochemically-derived compounds. The sites range from major urban areas (Chicago, St. Louis) to a rural village (Waterbury, Vermont). Results of the first three quarters of VOC and carbonyl data collection are summarized in this presentation.« less

Surface pressure affects B-hordein network formation at the air-water interface in relation to gastric digestibility.

PubMed

Yang, Jingqi; Huang, Jun; Zeng, Hongbo; Chen, Lingyun

2015-11-01

Protein interfacial network formation under mechanical pressure and its influence on degradation was investigated at molecular level using Langmuir-Blodgett B-hordein monolayer as a 2D model. Surface properties, such as surface pressure, dilatational and shear rheology and the surface pressure--area (π-A) isotherm, of B-hordein at air-water interface were analyzed by tensiometer, rheometer and a Langmuir-Blodgett trough respectively. B-Hordein conformation and orientation under different surface pressures were determined by polarization modulation-infrared reflection absorption spectroscopy (PM-IRRAS). The interfacial network morphology was observed by atomic force microscopy (AFM). B-Hordein could reduce the air-water surface tension rapidly to ∼ 45 mN/m and form a solid-like network with high rheological elasticity and compressibility at interface, which could be a result of interactions developed by intermolecular β-sheets. The results also revealed that B-hordein interfacial network switched from an expanded liquid phase to a solid-like film with increasing compression pressure. The orientation of B-hordein was parallel to the surface when in expended liquid phase, whereas upon compression, the hydrophobic repetitive region tilted away from water phase. When compressed to 30 mN/m, a strong elastic network was formed at the interface, and it was resistant to a harsh gastric-like environment of low pH and pepsin. This work generated fundamental knowledge, which suggested the potential to design B-hordein stabilized emulsions and encapsulations with controllable digestibility for small intestine targeted delivery of bioactive compounds. Copyright © 2015 Elsevier B.V. All rights reserved.

Whole air canister sampling coupled with preconcentration GC/MS analysis of part-per-trillion levels of trimethylsilanol in semiconductor cleanroom air.

PubMed

Herrington, Jason S

2013-08-20

The costly damage airborne trimethylsilanol (TMS) exacts on optics in the semiconductor industry has resulted in the demand for accurate and reliable methods for measuring TMS at trace levels (i.e., parts per trillion, volume per volume of air [ppt(v)] [~ng/m(3)]). In this study I developed a whole air canister-based approach for field sampling trimethylsilanol in air, as well as a preconcentration gas chromatography/mass spectrometry laboratory method for analysis. The results demonstrate clean canister blanks (0.06 ppt(v) [0.24 ng/m(3)], which is below the detection limit), excellent linearity (a calibration relative response factor relative standard deviation [RSD] of 9.8%) over a wide dynamic mass range (1-100 ppt(v)), recovery/accuracy of 93%, a low selected ion monitoring method detection limit of 0.12 ppt(v) (0.48 ng/m(3)), replicate precision of 6.8% RSD, and stability (84% recovery) out to four days of storage at room temperature. Samples collected at two silicon wafer fabrication facilities ranged from 10.0 to 9120 ppt(v) TMS and appear to be associated with the use of hexamethyldisilazane priming agent. This method will enable semiconductor cleanroom managers to monitor and control for trace levels of trimethylsilanol.

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

Characterization of a photoacoustic system through neural networks to determine multicomponent samples

NASA Astrophysics Data System (ADS)

Zajarevich, N. M.; Peuriot, A. L.; Slezak, V. B.

2016-07-01

Photoacoustic spectroscopy for trace gases detection, based on a CO2 laser, can be used in a wide range of applications. The tunability of this laser in the mid-infrared (9.4-10.6 μm) allows the quantitative determination of different substances in multicomponent samples. In general, at traces level, the total photoacoustic amplitude at a certain wavelength may be approximated by a linear superposition of the amplitudes given by each of the species absorbing at that wavelength. However, in some cases, the sum of the individual signals is no longer valid. In particular, it is known the presence of CO2 delays the acoustic signal in relation to the laser excitation due to the exchange of vibrational energy between CO2 and N2. This phenomenon generates a slow V-T energy relaxation from a metastable N2 vibrational level and the sum of individual contributions may no longer be valid. Moreover, the resolution of a linear equation system has limitations, so the possibility to determine concentrations in photoacoustics based on neural network is proposed in this work. This procedure is tried in a particular case of a volatile organic compound, such as C2H4, and CO2 in air. The results are compared with the ones obtained with a model based on rate equations.

Optimal Design of Air Quality Monitoring Network and its Application in an Oil Refinery Plant: An Approach to Keep Health Status of Workers

PubMed Central

ZoroufchiBenis, Khaled; Fatehifar, Esmaeil; Ahmadi, Javad; Rouhi, Alireza

2015-01-01

Background: Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availability of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. Methods: A multi-pollutant method (implemented as a MATLAB program) was explored for configur­ing an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids) according to their ability to represent the ambient concentration. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a sta­tion’s dosage to the total dosage in the network. Results: Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network efficiency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. Conclusion: The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health. PMID:26933646

Estimating Sampling Biases and Measurement Uncertainties of AIRS-AMSU-A Temperature and Water Vapor Observations Using MERRA Reanalysis

NASA Technical Reports Server (NTRS)

Hearty, Thomas J.; Savtchenko, Andrey K.; Tian, Baijun; Fetzer, Eric; Yung, Yuk L.; Theobald, Michael; Vollmer, Bruce; Fishbein, Evan; Won, Young-In

2014-01-01

We use MERRA (Modern Era Retrospective-Analysis for Research Applications) temperature and water vapor data to estimate the sampling biases of climatologies derived from the AIRS/AMSU-A (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A) suite of instruments. We separate the total sampling bias into temporal and instrumental components. The temporal component is caused by the AIRS/AMSU-A orbit and swath that are not able to sample all of time and space. The instrumental component is caused by scenes that prevent successful retrievals. The temporal sampling biases are generally smaller than the instrumental sampling biases except in regions with large diurnal variations, such as the boundary layer, where the temporal sampling biases of temperature can be +/- 2 K and water vapor can be 10% wet. The instrumental sampling biases are the main contributor to the total sampling biases and are mainly caused by clouds. They are up to 2 K cold and greater than 30% dry over mid-latitude storm tracks and tropical deep convective cloudy regions and up to 20% wet over stratus regions. However, other factors such as surface emissivity and temperature can also influence the instrumental sampling bias over deserts where the biases can be up to 1 K cold and 10% wet. Some instrumental sampling biases can vary seasonally and/or diurnally. We also estimate the combined measurement uncertainties of temperature and water vapor from AIRS/AMSU-A and MERRA by comparing similarly sampled climatologies from both data sets. The measurement differences are often larger than the sampling biases and have longitudinal variations.

CTEPP STANDARD OPERATING PROCEDURE FOR COLLECTION OF FIXED SITE INDOOR AND OUTDOOR AIR SAMPLES FOR PERSISTENT ORGANIC POLLUTANTS (SOP-2.12)

EPA Science Inventory

This SOP describes the procedures to set up, calibrate, initiate and terminate air sampling for persistent organic pollutants. This method is used to sample air, indoors and outdoors, at homes and at day care centers over a 48-hr period.

Community Air Sensor Network CAIRSENSE Project: Lower ...

EPA Pesticide Factsheets

Presentation slides on the CAIRSENSE project, Atlanta field study testing low cost air sensors against FEM instruments. To be presented at the Air and Waste Management Association conference. Presentation slides on the CAIRSENSE project, Atlanta field study testing low cost air sensors against FEM instruments. To be presented at the Air and Waste Management Association conference.

Soyuz 22 Return Samples: Assessment of Air Quality Aboard the International Space Station

NASA Technical Reports Server (NTRS)

Jams, John T.

2010-01-01

Three mini-grab sample containers (m-GSCs) were returned aboard Soyuz 22 because of concerns that new air pollutants were present in the air and these were getting into the water recovery system. The Total Organic Carbon Analyzer had been giving increasing readings of total organic carbon (TOC) in the potable water, and it was postulated that an increased load into the system was responsible. The toxicological assessment of 3 m-GSCs from the ISS is shown in Table 1. The recoveries of the 3 standards (as listed above) from the GSCs averaged 103, 95 and 76%, respectively. Recovery from formaldehyde control badges were 90 and 91%.

Quality-control design for surface-water sampling in the National Water-Quality Network

USGS Publications Warehouse

Riskin, Melissa L.; Reutter, David C.; Martin, Jeffrey D.; Mueller, David K.

2018-04-10

The data-quality objectives for samples collected at surface-water sites in the National Water-Quality Network include estimating the extent to which contamination, matrix effects, and measurement variability affect interpretation of environmental conditions. Quality-control samples provide insight into how well the samples collected at surface-water sites represent the true environmental conditions. Quality-control samples used in this program include field blanks, replicates, and field matrix spikes. This report describes the design for collection of these quality-control samples and the data management needed to properly identify these samples in the U.S. Geological Survey’s national database.

An analytical method for trifluoroacetic Acid in water and air samples using headspace gas chromatographic determination of the methyl ester.

PubMed

Zehavi, D; Seiber, J N

1996-10-01

An analytical method has been developed for the determination of trace levels of trifluoroacetic acid (TFA), an atmospheric breakdown product of several of the hydrofluorocarbon (HFC) and hydrochlorofluorocarbon (HCFC) replacements for the chlorofluorocarbon (CFC) refrigerants, in water and air. TFA is derivatized to the volatile methyl trifluoroacetate (MTFA) and determined by automated headspace gas chromatography (HSGC) with electron-capture detection or manual HSGC using GC/MS in the selected ion monitoring (SIM) mode. The method is based on the reaction of an aqueous sample containing TFA with dimethyl sulfate (DMS) in concentrated sulfuric acid in a sealed headspace vial under conditions favoring distribution of MTFA to the vapor phase. Water samples are prepared by evaporative concentration, during which TFA is retained as the anion, followed by extraction with diethyl ether of the acidified sample and then back-extraction of TFA (as the anion) in aqueous bicarbonate solution. The extraction step is required for samples with a relatively high background of other salts and organic materials. Air samples are collected in sodium bicarbonate-glycerin-coated glass denuder tubes and prepared by rinsing the denuder contents with water to form an aqueous sample for derivatization and analysis. Recoveries of TFA from spiked water, with and without evaporative concentration, and from spiked air were quantitative, with estimated detection limits of 10 ng/mL (unconcentrated) and 25 pg/mL (concentrated 250 mL:1 mL) for water and 1 ng/m(3) (72 h at 5 L/min) for air. Several environmental air, fogwater, rainwater, and surface water samples were successfully analyzed; many showed the presence of TFA.

Glyphosate–rich air samples induce IL–33, TSLP and generate IL–13 dependent airway inflammation

PubMed Central

Kumar, Sudhir; Khodoun, Marat; Kettleson, Eric M.; McKnight, Christopher; Reponen, Tiina; Grinshpun, Sergey A.; Adhikari, Atin

2014-01-01

Several low weight molecules have often been implicated in the induction of occupational asthma. Glyphosate, a small molecule herbicide, is widely used in the world. There is a controversy regarding a role of glyphosate in developing asthma and rhinitis among farmers, the mechanism of which is unexplored. The aim of this study was to explore the mechanisms of glyphosate induced pulmonary pathology by utilizing murine models and real environmental samples. C57BL/6, TLR4−/−, and IL-13−/− mice inhaled extracts of glyphosate-rich air samples collected on farms during spraying of herbicides or inhaled different doses of glyphosate and ovalbumin. The cellular response, humoral response, and lung function of exposed mice were evaluated. Exposure to glyphosate-rich air samples as well as glyphosate alone to the lungs increased: eosinophil and neutrophil counts, mast cell degranulation, and production of IL-33, TSLP, IL-13, and IL-5. In contrast, in vivo systemic IL-4 production was not increased. Co-administration of ovalbumin with glyphosate did not substantially change the inflammatory immune response. However, IL-13-deficiency resulted in diminished inflammatory response but did not have a significant effect on airway resistance upon methacholine challenge after 7 or 21 days of glyphosate exposure. Glyphosate-rich farm air samples as well as glyphosate alone were found to induce pulmonary IL-13-dependent inflammation and promote Th2 type cytokines, but not IL-4 for glyphosate alone. This study, for the first time, provides evidence for the mechanism of glyphosate-induced occupational lung disease. PMID:25172162

Can Particulate Air Sampling Predict Microbial Load in Operating Theatres for Arthroplasty?

PubMed Central

Cristina, Maria Luisa; Spagnolo, Anna Maria; Sartini, Marina; Panatto, Donatella; Gasparini, Roberto; Orlando, Paolo; Ottria, Gianluca; Perdelli, Fernanda

2012-01-01

Several studies have proposed that the microbiological quality of the air in operating theatres be indirectly evaluated by means of particle counting, a technique derived from industrial clean-room technology standards, using airborne particle concentration as an index of microbial contamination. However, the relationship between particle counting and microbiological sampling has rarely been evaluated and demonstrated in operating theatres. The aim of the present study was to determine whether particle counting could predict microbiological contamination of the air in an operating theatre during 95 surgical arthroplasty procedures. This investigation was carried out over a period of three months in 2010 in an orthopedic operating theatre devoted exclusively to prosthetic surgery. During each procedure, the bacterial contamination of the air was determined by means of active sampling; at the same time, airborne particulate contamination was assessed throughout the entire procedure. On considering the total number of surgical operations, the mean value of the total bacterial load in the center of the operating theatre proved to be 35 CFU/m3; the mean particle count was 4,194,569 no./m3 for particles of diameter ≥0.5 µm and 13,519 no./m3 for particles of diameter ≥5 µm. No significant differences emerged between the median values of the airborne microbial load recorded during the two types of procedure monitored. Particulates with a diameter of ≥0.5 µm were detected in statistically higher concentrations (p<0.001) during knee-replacement procedures. By contrast, particulates with a diameter of ≥5 µm displayed a statistically higher concentration during hip-replacement procedures (p<0.05). The results did not reveal any statistically significant correlation between microbial loads and particle counts for either of the particle diameters considered (≥0.5 µm and ≥5 µm). Consequently, microbiological monitoring remains the most suitable method of

Can particulate air sampling predict microbial load in operating theatres for arthroplasty?

PubMed

Cristina, Maria Luisa; Spagnolo, Anna Maria; Sartini, Marina; Panatto, Donatella; Gasparini, Roberto; Orlando, Paolo; Ottria, Gianluca; Perdelli, Fernanda

2012-01-01

Several studies have proposed that the microbiological quality of the air in operating theatres be indirectly evaluated by means of particle counting, a technique derived from industrial clean-room technology standards, using airborne particle concentration as an index of microbial contamination. However, the relationship between particle counting and microbiological sampling has rarely been evaluated and demonstrated in operating theatres. The aim of the present study was to determine whether particle counting could predict microbiological contamination of the air in an operating theatre during 95 surgical arthroplasty procedures. This investigation was carried out over a period of three months in 2010 in an orthopedic operating theatre devoted exclusively to prosthetic surgery. During each procedure, the bacterial contamination of the air was determined by means of active sampling; at the same time, airborne particulate contamination was assessed throughout the entire procedure. On considering the total number of surgical operations, the mean value of the total bacterial load in the center of the operating theatre proved to be 35 CFU/m(3); the mean particle count was 4,194,569 no./m(3) for particles of diameter ≥0.5 µm and 13,519 no./m(3) for particles of diameter ≥5 µm. No significant differences emerged between the median values of the airborne microbial load recorded during the two types of procedure monitored. Particulates with a diameter of ≥0.5 µm were detected in statistically higher concentrations (p<0.001) during knee-replacement procedures. By contrast, particulates with a diameter of ≥5 µm displayed a statistically higher concentration during hip-replacement procedures (p<0.05). The results did not reveal any statistically significant correlation between microbial loads and particle counts for either of the particle diameters considered (≥0.5 µm and ≥5 µm). Consequently, microbiological monitoring remains the most suitable method of

Role of air sampling in investigation of an outbreak of legionnaires' disease associated with exposure to aerosols from an evaporative condenser.

PubMed

Breiman, R F; Cozen, W; Fields, B S; Mastro, T D; Carr, S J; Spika, J S; Mascola, L

1990-06-01

Epidemiologic studies have suggested that legionnaires' disease can be transmitted to susceptible hosts by contaminated aerosolized water from cooling towers and evaporative condensers; however, epidemic strains of Legionella have not been isolated by air sampling at such sites during epidemiologic investigations. An outbreak of legionnaires' disease occurred at a retirement hotel; Legionella pneumophila serogroup 1 was isolated from an evaporative condenser and from potable water. A case-control study showed that the only significant exposure risk was in area A. L. pneumophila serogroup 1 was isolated during air sampling near the evaporative condenser exhaust site, the air conditioning intake vent, and an air vent in area A, but not in shower stalls. Monoclonal antibody subtype patterns of L. pneumophila serogroup 1 isolates from patients matched those from the evaporative condenser but not from shower water. Air sampling and monoclonal antibody subtyping results support epidemiologic evidence that the evaporative condenser was the source of this outbreak.

Determination of air-loop volume and radon partition coefficient for measuring radon in water sample.

PubMed

Lee, Kil Yong; Burnett, William C

A simple method for the direct determination of the air-loop volume in a RAD7 system as well as the radon partition coefficient was developed allowing for an accurate measurement of the radon activity in any type of water. The air-loop volume may be measured directly using an external radon source and an empty bottle with a precisely measured volume. The partition coefficient and activity of radon in the water sample may then be determined via the RAD7 using the determined air-loop volume. Activity ratios instead of absolute activities were used to measure the air-loop volume and the radon partition coefficient. In order to verify this approach, we measured the radon partition coefficient in deionized water in the temperature range of 10-30 °C and compared the values to those calculated from the well-known Weigel equation. The results were within 5 % variance throughout the temperature range. We also applied the approach for measurement of the radon partition coefficient in synthetic saline water (0-75 ppt salinity) as well as tap water. The radon activity of the tap water sample was determined by this method as well as the standard RAD-H 2 O and BigBottle RAD-H 2 O. The results have shown good agreement between this method and the standard methods.

GCOS reference upper air network (GRUAN): Steps towards assuring future climate records

NASA Astrophysics Data System (ADS)

Thorne, P. W.; Vömel, H.; Bodeker, G.; Sommer, M.; Apituley, A.; Berger, F.; Bojinski, S.; Braathen, G.; Calpini, B.; Demoz, B.; Diamond, H. J.; Dykema, J.; Fassò, A.; Fujiwara, M.; Gardiner, T.; Hurst, D.; Leblanc, T.; Madonna, F.; Merlone, A.; Mikalsen, A.; Miller, C. D.; Reale, T.; Rannat, K.; Richter, C.; Seidel, D. J.; Shiotani, M.; Sisterson, D.; Tan, D. G. H.; Vose, R. S.; Voyles, J.; Wang, J.; Whiteman, D. N.; Williams, S.

2013-09-01

The observational climate record is a cornerstone of our scientific understanding of climate changes and their potential causes. Existing observing networks have been designed largely in support of operational weather forecasting and continue to be run in this mode. Coverage and timeliness are often higher priorities than absolute traceability and accuracy. Changes in instrumentation used in the observing system, as well as in operating procedures, are frequent, rarely adequately documented and their impacts poorly quantified. For monitoring changes in upper-air climate, which is achieved through in-situ soundings and more recently satellites and ground-based remote sensing, the net result has been trend uncertainties as large as, or larger than, the expected emergent signals of climate change. This is more than simply academic with the tropospheric temperature trends issue having been the subject of intense debate, two international assessment reports and several US congressional hearings. For more than a decade the international climate science community has been calling for the instigation of a network of reference quality measurements to reduce uncertainty in our climate monitoring capabilities. This paper provides a brief history of GRUAN developments to date and outlines future plans. Such reference networks can only be achieved and maintained with strong continuing input from the global metrological community.

Background Mole Fractions of Hydrocarbons in North America Determined from NOAA Global Reference Network Data

NASA Astrophysics Data System (ADS)

Mielke-Maday, I.

2015-12-01

The National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Division (GMD) maintains a global reference network for over 50 trace gas species and analyzes discrete air samples collected by this network throughout the world at the Earth System Research Laboratory in Boulder, Colorado. In particular, flask samples are analyzed for a number of hydrocarbons with policy and health relevance such as ozone precursors, greenhouse gases, and hazardous air pollutants. Because this global network's sites are remote and therefore minimally influenced by local anthropogenic emissions, these data yield information about background ambient mole fractions and can provide a context for observations collected in intensive field campaigns, such as the Front Range Air Pollution and Photochemistry Experiment (FRAPPE), the Southeast Nexus (SENEX) study, and the DISCOVER-AQ deployments. Information about background mole fractions during field campaigns is critical for calculating hydrocarbon enhancements in the region of study and for assessing the extent to which a particular region's local emissions sources contribute to these enhancements. Understanding the geographic variability of the background and its contribution to regional ambient mole fractions is also crucial for the development of realistic regulations. We present background hydrocarbon mole fractions and their ratios in North America using data from air samples collected in the planetary boundary layer at tall towers and aboard aircraft from 2008 to 2014. We discuss the spatial and seasonal variability in these data. We present trends over the time period of measurements and propose possible explanations for these trends.

Soyuz 23 Return Samples: Assessment of Air Quality Aboard the International Space Station

NASA Technical Reports Server (NTRS)

James, John T.

2011-01-01

Six mini-grab sample containers (m-GSCs) were returned aboard Soyuz 23 because of concerns that new air pollutants had been present in the air and these were getting into the water recovery system. The Total Organic Carbon Analyzer had been giving increasing readings of total organic carbon (TOC) in the potable water, and it was postulated that an increased load into the system was responsible. The TOC began to decline in late October, 2010. The toxicological assessment of 6 m-GSCs from the ISS is shown in Table 1. The recoveries of 13C-acetone, fluorobenzene, and chlorobenzene from the GSCs averaged 73, 82, and 59%, respectively. We are working to understand the sub-optimal recovery of chlorobenzene.

A new analysis system for whole air sampling: description and results from 2013 SENEX

NASA Astrophysics Data System (ADS)

Lerner, B. M.; Gilman, J.; Dumas, M.; Hughes, D.; Jaksich, A.; Hatch, C. D.; Graus, M.; Warneke, C.; Apel, E. C.; Hornbrook, R. S.; Holloway, J. S.; De Gouw, J. A.

2014-12-01

Accurate measurement of volatile organic compounds (VOCs) in the troposphere is critical for the understanding of emissions and physical and chemical processes that can impact both air quality and climate. Airborne VOC measurements have proven especially challenging due to the requirement of both high sensitivity (pptv) and short sample collection times (≤15 s) to maximize spatial resolution and sampling frequency for targeted plume analysis. The use of stainless steel canisters to collect whole air samples (WAS) for post-flight analysis has been pioneered by the groups of D. Blake and E. Atlas [Blake et al., 1992; Atlas et al., 1993]. For the 2013 Southeast Nexus Study (SENEX), the NOAA ESRL CSD laboratory undertook WAS measurements for the first time. This required the construction of three new, highly-automated, and field-portable instruments designed to sample, analyze, and clean the canisters for re-use. Analysis was performed with a new custom-built gas chromatograph-mass spectrometer system. The instrument pre-concentrates analyte cryostatically into two parallel traps by means of a Stirling engine, a novel technique which obviates the need for liquid nitrogen to reach trapping temperatures of -175C. Here we present an evaluation of the retrieval of target VOC species from WAS canisters. We discuss the effects of humidity and sample age on the analyte, particularly upon C8+ alkane and aromatic species and biogenic species. Finally, we present results from several research flights during SENEX that targeted emissions from oil/natural gas production.

A spatially distributed isotope sampling network in a snow-dominated catchment for the quantification of snow meltwater

NASA Astrophysics Data System (ADS)

Rücker, Andrea; Boss, Stefan; Von Freyberg, Jana; Zappa, Massimiliano; Kirchner, James

2017-04-01

In mountainous catchments with seasonal snowpacks, river discharge in downstream valleys is largely sustained by snowmelt in spring and summer. Future climate warming will likely reduce snow volumes and lead to earlier and faster snowmelt in such catchments. This, in turn, may increase the risk of summer low flows and hydrological droughts. Improved runoff predictions are thus required in order to adapt water management to future climatic conditions and to assure the availability of fresh water throughout the year. However, a detailed understanding of the hydrological processes is crucial to obtain robust predictions of river streamflow. This in turn requires fingerprinting source areas of streamflow, tracing water flow pathways, and measuring timescales of catchment storage, using tracers such as stable water isotopes (18O, 2H). For this reason, we have established an isotope sampling network in the Alptal, a snowmelt-dominated catchment (46.4 km2) in Central-Switzerland, as part of the SREP-Drought project (Snow Resources and the Early Prediction of hydrological DROUGHT in mountainous streams). Precipitation and snow cores are analyzed for their isotopic signature at daily or weekly intervals. Three-week bulk samples of precipitation are also collected on a transect along the Alptal valley bottom, and along an elevational transect perpendicular to the Alptal valley axis. Streamwater samples are taken at the catchment outlet as well as in two small nested sub-catchments (< 2 km2). In order to catch the isotopic signature of naturally-occurring snowmelt, a fully automatic snow lysimeter system was developed, which also facilitates real-time monitoring of snowmelt events, system status and environmental conditions (air and soil temperature). Three lysimeter systems were installed within the catchment, in one forested site and two open field sites at different elevations, and have been operational since November 2016. We will present the isotope time series from our

Identification of driving network of cellular differentiation from single sample time course gene expression data

NASA Astrophysics Data System (ADS)

Chen, Ye; Wolanyk, Nathaniel; Ilker, Tunc; Gao, Shouguo; Wang, Xujing

Methods developed based on bifurcation theory have demonstrated their potential in driving network identification for complex human diseases, including the work by Chen, et al. Recently bifurcation theory has been successfully applied to model cellular differentiation. However, there one often faces a technical challenge in driving network prediction: time course cellular differentiation study often only contains one sample at each time point, while driving network prediction typically require multiple samples at each time point to infer the variation and interaction structures of candidate genes for the driving network. In this study, we investigate several methods to identify both the critical time point and the driving network through examination of how each time point affects the autocorrelation and phase locking. We apply these methods to a high-throughput sequencing (RNA-Seq) dataset of 42 subsets of thymocytes and mature peripheral T cells at multiple time points during their differentiation (GSE48138 from GEO). We compare the predicted driving genes with known transcription regulators of cellular differentiation. We will discuss the advantages and limitations of our proposed methods, as well as potential further improvements of our methods.

Solid sorbent air sampling and analytical procedure for methyl-, dimethyl-, ethyl-, and diethylamine

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

Elskamp, C.J.; Schultz, G.R.

1986-01-01

A sampling and analytical procedure for methyl-, dimethyl-, ethyl-, and diethylamine was developed in order to avoid problems typically encountered in the sampling and analysis of low molecular weight aliphatic amines. Samples are collected with adsorbent tubes containing Amberlite XAD-7 resin coated with the derivatizing reagent, NBD chloride (7-chloro-4-nitrobenzo-2-oxa-1,3-diazole). Analysis is performed by high performance liquid chromatography with the use of a fluorescence and/or UV/visible detector. All four amines can be monitored simultaneously, and neither collection nor storage is affected by humidity. Samples are stable at room temperature for at least two weeks. The methodology has been tested for eachmore » of the four amines at sample loadings equivalent to air concentration ranges of 0.5 to 30 ppm for a sample volume of 10 liters. The method shows promise for determining other airborne primary and secondary low molecular weight aliphatic amines.« less

Estimating the Size of the Methamphetamine-Using Population in New York City Using Network Sampling Techniques.

PubMed

Dombrowski, Kirk; Khan, Bilal; Wendel, Travis; McLean, Katherine; Misshula, Evan; Curtis, Ric

2012-12-01

As part of a recent study of the dynamics of the retail market for methamphetamine use in New York City, we used network sampling methods to estimate the size of the total networked population. This process involved sampling from respondents' list of co-use contacts, which in turn became the basis for capture-recapture estimation. Recapture sampling was based on links to other respondents derived from demographic and "telefunken" matching procedures-the latter being an anonymized version of telephone number matching. This paper describes the matching process used to discover the links between the solicited contacts and project respondents, the capture-recapture calculation, the estimation of "false matches", and the development of confidence intervals for the final population estimates. A final population of 12,229 was estimated, with a range of 8235 - 23,750. The techniques described here have the special virtue of deriving an estimate for a hidden population while retaining respondent anonymity and the anonymity of network alters, but likely require larger sample size than the 132 persons interviewed to attain acceptable confidence levels for the estimate.

Low-cost, high-density sensor network for urban emission monitoring: BEACO2N

NASA Astrophysics Data System (ADS)

Kim, J.; Shusterman, A.; Lieschke, K.; Newman, C.; Cohen, R. C.

2017-12-01

In urban environments, air quality is spatially and temporally heterogeneous as diverse emission sources create a high degree of variability even at the neighborhood scale. Conventional air quality monitoring relies on continuous measurements with limited spatial resolution or passive sampling with high-density and low temporal resolution. Either approach averages the air quality information over space or time and hinders our attempts to understand emissions, chemistry, and human exposure in the near-field of emission sources. To better capture the true spatio-temporal heterogeneity of urban conditions, we have deployed a low-cost, high-density air quality monitoring network in San Francisco Bay Area distributed at 2km horizontal spacing. The BErkeley Atmospheric CO2 Observation Network (BEACO2N) consists of approximately 50 sensor nodes, measuring CO2, CO, NO, NO2, O­3, and aerosol. Here we describe field-based calibration approaches that are consistent with the low-cost strategy of the monitoring network. Observations that allow inference of emission factors and identification of specific local emission sources will also be presented.

Breakthrough during air sampling with polyurethane foam: What do PUF 2/PUF 1 ratios mean?

PubMed

Bidleman, Terry F; Tysklind, Mats

2018-02-01

Frontal chromatography theory is applied to describe movement of gaseous semivolatile organic compounds (SVOCs) through a column of polyurethane foam (PUF). Collected mass fractions (F C ) are predicted for sample volume/breakthrough volume ratios (τ = V S /V B ) up to 6.0 and PUF bed theoretical plate numbers (N) from 2 to 16. The predictions assume constant air concentrations and temperatures. Extension of the calculations is done to relate the collection efficiency of a 2-PUF train (F C1+2 ) to the PUF 2/PUF 1 ratio. F C1+2 exceeds 0.9 for PUF 2/PUF 1 ≤ 0.5 and lengths of PUF commonly used in air samplers. As the PUF 2/PUF 1 ratio approaches unity, confidence in these predictions is limited by the analytical ability to distinguish residues on the two PUFs. Field data should not be arbitrarily discarded because some analytes broke through to the backup PUF trap. The fractional collection efficiencies can be used to estimate air concentrations from quantities retained on the PUF trap when sampling is not quantitative. Copyright © 2017 Elsevier Ltd. All rights reserved.

Methane mole fraction and δ13C above and below the trade wind inversion at Ascension Island in air sampled by aerial robotics

NASA Astrophysics Data System (ADS)

Brownlow, R.; Lowry, D.; Thomas, R. M.; Fisher, R. E.; France, J. L.; Cain, M.; Richardson, T. S.; Greatwood, C.; Freer, J.; Pyle, J. A.; MacKenzie, A. R.; Nisbet, E. G.

2016-11-01

Ascension Island is a remote South Atlantic equatorial site, ideal for monitoring tropical background CH4. In September 2014 and July 2015, octocopters were used to collect air samples in Tedlar bags from different heights above and below the well-defined Trade Wind Inversion (TWI), sampling a maximum altitude of 2700 m above mean sea level. Sampling captured both remote air in the marine boundary layer below the TWI and also air masses above the TWI that had been lofted by convective systems in the African tropics. Air above the TWI was characterized by higher CH4, but no distinct shift in δ13C was observed compared to the air below. Back trajectories indicate that lofted CH4 emissions from Southern Hemisphere Africa have bulk δ13CCH4 signatures similar to background, suggesting mixed emissions from wetlands, agriculture, and biomass burning. The campaigns illustrate the usefulness of unmanned aerial system sampling and Ascension's value for atmospheric measurement in an understudied region.

Air and Surface Sampling Method for Assessing Exposures to Quaternary Ammonium Compounds Using Liquid Chromatography Tandem Mass Spectrometry.

PubMed

LeBouf, Ryan F; Virji, Mohammed Abbas; Ranpara, Anand; Stefaniak, Aleksandr B

2017-07-01

This method was designed for sampling select quaternary ammonium (quat) compounds in air or on surfaces followed by analysis using ultraperformance liquid chromatography tandem mass spectrometry. Target quats were benzethonium chloride, didecyldimethylammonium bromide, benzyldimethyldodecylammonium chloride, benzyldimethyltetradecylammonium chloride, and benzyldimethylhexadecylammonium chloride. For air sampling, polytetrafluoroethylene (PTFE) filters are recommended for 15-min to 24-hour sampling. For surface sampling, Pro-wipe® 880 (PW) media was chosen. Samples were extracted in 60:40 acetonitrile:0.1% formic acid for 1 hour on an orbital shaker. Method detection limits range from 0.3 to 2 ng/ml depending on media and analyte. Matrix effects of media are minimized through the use of multiple reaction monitoring versus selected ion recording. Upper confidence limits on accuracy meet the National Institute for Occupational Safety and Health 25% criterion for PTFE and PW media for all analytes. Using PTFE and PW analyzed with multiple reaction monitoring, the method quantifies levels among the different quats compounds with high precision (<10% relative standard deviation) and low bias (<11%). The method is sensitive enough with very low method detection limits to capture quats on air sampling filters with only a 15-min sample duration with a maximum assessed storage time of 103 days before sample extraction. This method will support future exposure assessment and quantitative epidemiologic studies to explore exposure-response relationships and establish levels of quats exposures associated with adverse health effects. © The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

PubMed Central

Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang

2011-01-01

An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows (“explaining away”) and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons. PMID:22219717

Atmospheric CO2 Concentrations from the Commonwealth Scientific and Industrial Research Organization (CSIRO) GASLAB Flask Sampling Network (March 1991 - December 2006)

DOE Data Explorer

Steele, L. P. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, Victoria, Australia; Krummel, P. B. [Commonwealth Scientific and Industrial Research Organization (CSIRO),; Langenfelds, R. L. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, Victoria, Australia

2008-01-01

Individual measurements have been obtained from flask air samples returned to the CSIRO GASLAB. Typical sample storage times range from days to weeks for some sites (e.g. Cape Grim, Aircraft over Tasmania and Bass Strait) to as much as one year for Macquarie Island and the Antarctic sites. Experiments carried out to test for changes in sample CO2 mixing ratio during storage have shown significant drifts in some flask types over test periods of several months to years (Cooper et al., 1999). Corrections derived from the test results are applied to network data according to flask type. These measurements indicate a rise in annual average atmospheric CO2 concentration from 357.72 parts per million by volume (ppmv) in 1992 to 383.05 ppmv in 2006, or an increase in annual average of about 1.81 ppmv/year. These flask data may be compared with other flask measurements from the Scripps Institution of Oceanography, available through 2004 in TRENDS; both indicate an annual average increase of 1.72 ppmv/year throuth 2004. Differences may be attributed to different sampling times or days, different numbers of samples, and different curve-fitting techniques used to obtain monthly and annual average numbers from flask data. Measurement error in flask data is believed to be small (Masarie et al., 2001).

Crossett Hydrogen Sulfide Air Sampling Report

EPA Pesticide Factsheets

This report summarizes the results of the EPA’s hydrogen sulfide air monitoring conducted along Georgia Pacific’s wastewater treatment system and in surrounding Crossett, AR, neighborhoods in 2017.

A Study of Voluntary Turnover of Air Force Officers in Critically-Manned Career Fields

DTIC Science & Technology

2003-03-01

sampling and the USAF Academy Association of Graduates (AOG). For network sampling, fellow students in the Air Force Institute of Technology (AFIT) were...the voluntary leavers, five independent judges who are graduate students in AFIT will review five random questionnaires and independently...significantly higher levels of emotional exhaustion that did Administrative Assistants and had significantly higher levels of depersonalization than all

Cast Stone Oxidation Front Evaluation: Preliminary Results For Samples Exposed To Moist Air

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

Langton, C. A.; Almond, P. M.

The rate of oxidation is important to the long-term performance of reducing salt waste forms because the solubility of some contaminants, e.g., technetium, is a function of oxidation state. TcO{sub 4}{sup -} in the salt solution is reduced to Tc(IV) and has been shown to react with ingredients in the waste form to precipitate low solubility sulfide and/or oxide phases. Upon exposure to oxygen, the compounds containing Tc(IV) oxidize to the pertechnetate ion, Tc(VII)O{sub 4}{sup -}, which is very soluble. Consequently the rate of technetium oxidation front advancement into a monolith and the technetium leaching profile as a function ofmore » depth from an exposed surface are important to waste form performance and ground water concentration predictions. An approach for measuring contaminant oxidation rate (effective contaminant specific oxidation rate) based on leaching of select contaminants of concern is described in this report. In addition, the relationship between reduction capacity and contaminant oxidation is addressed. Chromate (Cr(VI) was used as a non-radioactive surrogate for pertechnetate, Tc(VII), in Cast Stone samples prepared with 5 M Simulant. Cast Stone spiked with pertechnetate was also prepared and tested. Depth discrete subsamples spiked with Cr were cut from Cast Stone exposed to Savannah River Site (SRS) outdoor ambient temperature fluctuations and moist air. Depth discrete subsamples spiked with Tc-99 were cut from Cast Stone exposed to laboratory ambient temperature fluctuations and moist air. Similar conditions are expected to be encountered in the Cast Stone curing container. The leachability of Cr and Tc-99 and the reduction capacities, measured by the Angus-Glasser method, were determined for each subsample as a function of depth from the exposed surface. The results obtained to date were focused on continued method development and are preliminary and apply to the sample composition and curing / exposure conditions described in this

Air, hand wipe, and surface wipe sampling for Bisphenol A (BPA) among workers in industries that manufacture and use BPA in the United States.

PubMed

Hines, Cynthia J; Jackson, Matthew V; Christianson, Annette L; Clark, John C; Arnold, James E; Pretty, Jack R; Deddens, James A

2017-11-01

For decades, bisphenol A (BPA) has been used in making polycarbonate, epoxy, and phenolic resins and certain investment casting waxes, yet published exposure data are lacking for U.S. manufacturing workers. In 2013-2014, BPA air and hand exposures were quantified for 78 workers at six U.S. companies making BPA or BPA-based products. Exposure measures included an inhalable-fraction personal air sample on each of two consecutive work days (n = 146), pre- and end-shift hand wipe samples on the second day (n = 74 each), and surface wipe samples (n = 88). Potential determinants of BPA air and end-shift hand exposures (after natural log transformation) were assessed in univariate and multiple regression mixed models. The geometric mean (GM) BPA air concentration was 4.0 µg/m 3 (maximum 920 µg/m 3 ). The end-shift GM BPA hand level (26 µg/sample) was 10-times higher than the pre-shift level (2.6 µg/sample). BPA air and hand exposures differed significantly by industry and job. BPA air concentrations and end-shift hand levels were highest in the BPA-filled wax manufacturing/reclaim industry (GM Air = 48 µg/m 3 , GM Hand-End = 130 µg/sample) and in the job of working with molten BPA-filled wax (GM Air = 43 µg/m 3 , GM Hand-End = 180 µg/sample), and lowest in the phenolic resins industry (GM Air = 0.85 µg/m 3 , GM Hand-End = 0.43 µg/sample) and in the job of flaking phenolic resins (GM AIR = 0.62 µg/m 3 , GM Hand-End = 0.38 µg/sample). Determinants of increased BPA air concentration were industry, handling BPA containers, spilling BPA, and spending ≥50% of the shift in production areas; increasing age was associated with lower air concentrations. BPA hand exposure determinants were influenced by high values for two workers; for all other workers, tasks involving contact with BPA-containing materials and spending ≥50% of the shift in production areas were associated with increased BPA hand levels. Surface wipe BPA levels were significantly lower in

[Application of simulated annealing method and neural network on optimizing soil sampling schemes based on road distribution].

PubMed

Han, Zong-wei; Huang, Wei; Luo, Yun; Zhang, Chun-di; Qi, Da-cheng

2015-03-01

Taking the soil organic matter in eastern Zhongxiang County, Hubei Province, as a research object, thirteen sample sets from different regions were arranged surrounding the road network, the spatial configuration of which was optimized by the simulated annealing approach. The topographic factors of these thirteen sample sets, including slope, plane curvature, profile curvature, topographic wetness index, stream power index and sediment transport index, were extracted by the terrain analysis. Based on the results of optimization, a multiple linear regression model with topographic factors as independent variables was built. At the same time, a multilayer perception model on the basis of neural network approach was implemented. The comparison between these two models was carried out then. The results revealed that the proposed approach was practicable in optimizing soil sampling scheme. The optimal configuration was capable of gaining soil-landscape knowledge exactly, and the accuracy of optimal configuration was better than that of original samples. This study designed a sampling configuration to study the soil attribute distribution by referring to the spatial layout of road network, historical samples, and digital elevation data, which provided an effective means as well as a theoretical basis for determining the sampling configuration and displaying spatial distribution of soil organic matter with low cost and high efficiency.

Risk management in air protection in the Republic of Croatia.

PubMed

Peternel, Renata; Toth, Ivan; Hercog, Predrag

2014-03-01

In the Republic of Croatia, according to the Air Protection Act, air pollution assessment is obligatory on the whole State territory. For individual regions and populated areas in the State a network has been established for permanent air quality monitoring. The State network consists of stations for measuring background pollution, regional and cross-border remote transfer and measurements as part of international government liabilities, then stations for measuring air quality in areas of cultural and natural heritage, and stations for measuring air pollution in towns and industrial zones. The exceeding of alert and information threshold levels of air pollutants are related to emissions from industrial plants, and accidents. Each excess represents a threat to human health in case of short-time exposure. Monitoring of alert and information threshold levels is carried out at stations from the state and local networks for permanent air quality monitoring according to the Air Quality Measurement Program in the State network for permanent monitoring of air quality and air quality measurement programs in local networks for permanent air quality monitoring. The State network for permanent air quality monitoring has a developed automatic system for reporting on alert and information threshold levels, whereas many local networks under the competence of regional and local self-governments still lack any fully installed systems of this type. In case of accidents, prompt action at all responsibility levels is necessary in order to prevent crisis and this requires developed and coordinated competent units of State Administration as well as self-government units. It is also necessary to be continuously active in improving the implementation of legislative regulations in the field of crises related to critical and alert levels of air pollutants, especially at local levels.

Characterization and validation of sampling and analytical methods for mycotoxins in workplace air.

PubMed

Jargot, Danièle; Melin, Sandrine

2013-03-01

Mycotoxins are produced by certain plant or foodstuff moulds under growing, transport or storage conditions. They are toxic for humans and animals, some are carcinogenic. Methods to monitor occupational exposure to seven of the most frequently occurring airborne mycotoxins have been characterized and validated. Experimental aerosols have been generated from naturally contaminated particles for sampler evaluation. Air samples were collected on foam pads, using the CIP 10 personal aerosol sampler with its inhalable health-related aerosol fraction selector. The samples were subsequently solvent extracted from the sampling media, cleaned using immunoaffinity (IA) columns and analyzed by liquid chromatography with fluorescence detection. Ochratoxin A (OTA) or fumonisin and aflatoxin derivatives were detected and quantified. The quantification limits were 0.015 ng m(-3) OTA, 1 ng m(-3) fumonisins or 0.5 pg m(-3) aflatoxins, with a minimum dust concentration level of 1 mg m(-3) and a 4800 L air volume sampling. The methods were successfully applied to field measurements, which confirmed that workers could be exposed when handling contaminated materials. It was observed that airborne particles may be more contaminated than the bulk material itself. The validated methods have measuring ranges fully adapted to the concentrations found in the workplace. Their performance meets the general requirements laid down for chemical agent measurement procedures, with an expanded uncertainty less than 50% for most mycotoxins. The analytical uncertainty, comprised between 14 and 24%, was quite satisfactory given the low mycotoxin amounts, when compared to the food benchmarks. The methods are now user-friendly enough to be adopted for personal workplace sampling. They will later allow for mycotoxin occupational risk assessment, as only very few quantitative data have been available till now.

Ultimate detectability of volatile organic compounds: how much further can we reduce their ambient air sample volumes for analysis?

PubMed

Kim, Yong-Hyun; Kim, Ki-Hyun

2012-10-02

To understand the ultimately lowest detection range of volatile organic compounds (VOCs) in air, application of a high sensitivity analytical system was investigated by coupling thermal desorption (TD) technique with gas chromatography (GC) and time-of-flight (TOF) mass spectrometry (MS). The performance of the TD-GC/TOF MS system was evaluated using liquid standards of 19 target VOCs prepared in the range of 35 pg to 2.79 ng per μL. Studies were carried out using both total ion chromatogram (TIC) and extracted ion chromatogram (EIC) mode. EIC mode was used for calibration to reduce background and to improve signal-to-noise. The detectability of 19 target VOCs, if assessed in terms of method detection limit (MDL, per US EPA definition) and limit of detection (LOD), averaged 5.90 pg and 0.122 pg, respectively, with the mean coefficient of correlation (R(2)) of 0.9975. The minimum quantifiable mass of target analytes, when determined using real air samples by the TD-GC/TOF MS, is highly comparable to the detection limits determined experimentally by standard. In fact, volumes for the actual detection of the major aromatic VOCs like benzene, toluene, and xylene (BTX) in ambient air samples were as low as 1.0 mL in the 0.11-2.25 ppb range. It was thus possible to demonstrate that most target compounds including those in low abundance could be reliably quantified at concentrations down to 0.1 ppb at sample volumes of less than 10 mL. The unique sensitivity of this advanced analytical system can ultimately lead to a shift in field sampling strategy with smaller air sample volumes facilitating faster, simpler air sampling (e.g., use of gas syringes rather than the relative complexity of pumps or bags/canisters), with greatly reduced risk of analyte breakthrough and minimal interference, e.g., from atmospheric humidity. The improved detection limits offered by this system can also enhance accuracy and measurement precision.

Ram-air sample collection device for a chemical warfare agent sensor

DOEpatents

Megerle, Clifford A.; Adkins, Douglas R.; Frye-Mason, Gregory C.

2002-01-01

In a surface acoustic wave sensor mounted within a body, the sensor having a surface acoustic wave array detector and a micro-fabricated sample preconcentrator exposed on a surface of the body, an apparatus for collecting air for the sensor, comprising a housing operatively arranged to mount atop the body, the housing including a multi-stage channel having an inlet and an outlet, the channel having a first stage having a first height and width proximate the inlet, a second stage having a second lower height and width proximate the micro-fabricated sample preconcentrator, a third stage having a still lower third height and width proximate the surface acoustic wave array detector, and a fourth stage having a fourth height and width proximate the outlet, where the fourth height and width are substantially the same as the first height and width.

Design and application of air-conditioning suit based on eddy current cooling principle for distribution network working with power uninterrupted

NASA Astrophysics Data System (ADS)

Xu, Li; Liu, Lanlan; Niu, Jie; Tang, Li; Li, Jinliang; Zhou, Zhanfan; Long, Chenhai; Yang, Qi; Yi, Ziqi; Guo, Hao; Long, Yang; Fu, Yanyi

2017-05-01

As social requirement of power supply reliability keeps rising, distribution network working with power uninterrupted has been widely carried out, while the high - temperature operating environment in summer can easily lead to physical discomfort for the operators, and then lead to safety incidents. Aiming at above problem, air-conditioning suit for distribution network working with power uninterrupted has been putted forward in this paper, and the structure composition and cooling principle of which has been explained, and it has been ultimately put to on-site application. The results showed that, cooling effect of air-conditioning suits was remarkable, and improved the working environment for the operators effectively, which is of great significance to improve Chinese level of working with power uninterrupted, reduce the probability of accidents and enhance the reliability of power supply.

Assessment of Air Quality in the Shuttle and International Space Station (ISS) Based on Samples Returned by STS-104 at the Conclusion of 7A

NASA Technical Reports Server (NTRS)

James, John T.

2001-01-01

The toxicological assessment of air samples returned at the end of the STS-l04 (7 A) flight to the ISS is reported. ISS air samples were taken in June and July 2001 from the Service Module, FGB, and U.S. Laboratory using grab sample canisters (GSCs) and/or formaldehyde badges. Preflight and end-of-mission samples were obtained from Atlantis using GSCs. Solid sorbent air sampler (SSAS) samples were obtained from the ISS in April, June, and July. Analytical methods have not changed from earlier reports, and all quality control measures were met.

24-HOUR DIFFUSIVE SAMPLING OF TOXIC VOCS IN AIR ONTO CARBOPACK X SOLID ADSORBENT FOLLOWED BY THERMAL DESORPTION/GC/MS ANALYSIS - LABORATORY STUDIES

EPA Science Inventory