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Bill Adams - One of the best experts on this subject based on the ideXlab platform.
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Recommendations to improve wildlife Exposure Estimation for development of soil screening and cleanup values
Integrated environmental assessment and management, 2013Co-Authors: Bradley E Sample, Chris Schlekat, David J. Spurgeon, Charlie Menzie, Jon Rauscher, Bill AdamsAbstract:An integral component in the development of media-specific values for the ecological risk assessment of chemicals is the derivation of safe levels of Exposure for wildlife. Although the derivation and subsequent application of these values can be used for screening purposes, there is a need to identify the threshold for effects when making remedial decisions during site-specific assessments. Methods for evaluation of wildlife Exposure are included in the US Environmental Protection Agency (USEPA) ecological soil screening levels (Eco-SSLs), registration, evaluation, authorization, and restriction of chemicals (REACH), and other risk-based soil assessment approaches. The goal of these approaches is to ensure that soil-associated contaminants do not pose a risk to wildlife that directly ingest soil, or to species that may be exposed to contaminants that persist in the food chain. These approaches incorporate broad assumptions in the Exposure and effects assessments and in the risk characterization process. Consequently, thresholds for concluding risk are frequently very low with conclusions of risk possible when soil metal concentrations fall in the range of natural background. A workshop held in September, 2012 evaluated existing methods and explored recent science about factors to consider when establishing appropriate remedial goals for concentrations of metals in soils. A Foodweb Exposure Workgroup was organized to evaluate methods for quantifying Exposure of wildlife to soil-associated metals through soil and food consumption and to provide recommendations for the development of ecological soil cleanup values (Eco-SCVs) that are both practical and scientifically defensible. The specific goals of this article are to review the current practices for quantifying Exposure of wildlife to soil-associated contaminants via bioaccumulation and trophic transfer, to identify potential opportunities for refining and improving these Exposure estimates, and finally, to make recommendations for application of these improved models to the development of site-specific remedial goals protective of wildlife. Although the focus is on metals contamination, many of the methods and tools discussed are also applicable to organic contaminants. The conclusion of this workgroup was that existing Exposure Estimation models are generally appropriate when fully expanded and that methods are generally available to develop more robust site-specific Exposure estimates. Improved realism in site-specific wildlife Eco-SCVs could be achieved by obtaining more realistic estimates for diet composition, bioaccumulation, bioavailability and/or bioaccessibility, soil ingestion, spatial aspects of Exposure, and target organ Exposure. These components of wildlife Exposure Estimation should be developed on a site-, species-, and analyte-specific basis to the extent that the expense for their derivation is justified by the value they add to Eco-SCV development.
Lidia Morawska - One of the best experts on this subject based on the ideXlab platform.
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Spatial Variation of Particle Number Concentration in School Microscale Environments and Its Impact on Exposure Assessment
Environmental science & technology, 2013Co-Authors: Farhad Salimi, Mandana Mazaheri, Samuel Clifford, Leigh R. Crilley, Rusdin Laiman, Lidia MorawskaAbstract:It has not yet been established whether the spatial variation of particle number concentration (PNC) within a microscale environment can have an effect on Exposure Estimation results. In general, the degree of spatial variation within microscale environments remains unclear, since previous studies have only focused on spatial variation within macroscale environments. The aims of this study were to determine the spatial variation of PNC within microscale school environments, in order to assess the importance of the number of monitoring sites on Exposure Estimation. Furthermore, this paper aims to identify which parameters have the largest influence on spatial variation as well as the relationship between those parameters and spatial variation. Air quality measurements were conducted for two consecutive weeks at each of the 25 schools across Brisbane, Australia. PNC was measured at three sites within the grounds of each school, along with the measurement of meteorological and several other air quality param...
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Spatial variation of particle number concentration in school microscale environments and its impact on Exposure assessment
2013Co-Authors: Farhad Salimi, Mandana Mazaheri, Samuel Clifford, Leigh R. Crilley, Rusdin Laiman, Lidia MorawskaAbstract:It has not yet been established whether the spatial variation of particle number concentration (PNC) within a microscale environment can have an effect on Exposure Estimation results. In general, the degree of spatial variation within microscale environments remains unclear, since previous studies have only focused on spatial variation within macroscale environments. The aims of this study were to determine the spatial variation of PNC within microscale school environments, in order to assess the importance of the number of monitoring sites on Exposure Estimation. Furthermore, this paper aims to identify which parameters have the largest influence on spatial variation, as well as the relationship between those parameters and spatial variation. Air quality measurements were conducted for two consecutive weeks at each of the 25 schools across Brisbane, Australia. PNC was measured at three sites within the grounds of each school, along with the measurement of meteorological and several other air quality parameters. Traffic density was recorded for the busiest road adjacent to the school. Spatial variation at each school was quantified using coefficient of variation (CV). The portion of CV associated with instrument uncertainty was found to be 0.3 and therefore, CV was corrected so that only non-instrument uncertainty was analysed in the data. The median corrected CV (CVc) ranged from 0 to 0.35 across the schools, with 12 schools found to exhibit spatial variation. The study determined the number of required monitoring sites at schools with spatial variability and tested the deviation in Exposure Estimation arising from using only a single site. Nine schools required two measurement sites and three schools required three sites. Overall, the deviation in Exposure Estimation from using only one monitoring site was as much as one order of magnitude. The study also tested the association of spatial variation with wind speed/direction and traffic density, using partial correlation coefficients to identify sources of variation and non-parametric function Estimation to quantify the level of variability. Traffic density and road to school wind direction were found to have a positive effect on CVc, and therefore, also on spatial variation. Wind speed was found to have a decreasing effect on spatial variation when it exceeded a threshold of 1.5 (m/s), while it had no effect below this threshold. Traffic density had a positive effect on spatial variation and its effect increased until it reached a density of 70 vehicles per five minutes, at which point its effect plateaued and did not increase further as a result of increasing traffic density.
David M. Broday - One of the best experts on this subject based on the ideXlab platform.
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Exposure Estimation errors to nitrogen oxides on a population scale due to daytime activity away from home.
The Science of the total environment, 2016Co-Authors: Rakefet Shafran-nathan, Yuval, Ilan Levy, David M. BrodayAbstract:Abstract Accurate Estimation of Exposure to air pollution is necessary for assessing the impact of air pollution on the public health. Most environmental epidemiology studies assign the home address Exposure to the study subjects. Here, we quantify the Exposure Estimation error at the population scale due to assigning it solely at the residence place. A cohort of most schoolchildren in Israel (~ 950,000), age 6–18, and a representative cohort of Israeli adults (~ 380,000), age 24–65, were used. For each subject the home and the work or school addresses were geocoded. Together, these two microenvironments account for the locations at which people are present during most of the weekdays. For each subject, we estimated ambient nitrogen oxide concentrations at the home and work or school addresses using two air quality models: a stationary land use regression model and a dynamic dispersion-like model. On average, accounting for the subjects' work or school address as well as for the daily pollutant variation reduced the Estimation error of Exposure to ambient NOx/NO2 by 5–10 ppb, since daytime concentrations at work/school and at home can differ significantly. These results were consistent regardless which air quality model as used and even for subjects that work or study close to their home. Yet, due to their usually short commute, assigning schoolchildren Exposure solely at their residential place seems to be a reasonable Estimation. In contrast, since adults commute for longer distances, assigning Exposure of adults only at the residential place has a lower correlation with the daily weighted Exposure, resulting in larger Exposure Estimation errors. We show that Exposure misclassification can result from not accounting for the subjects' time-location trajectories through the spatiotemporally varying pollutant concentrations field.
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Enhancement of PM2.5 Exposure Estimation using PM10 observations.
Environmental science. Processes & impacts, 2014Co-Authors: Yuval, David M. BrodayAbstract:The adverse consequences of particulate matter (PM) inhalation on human health are well documented. Most of the epidemiological work assessing the health impacts of PM Exposure concentrates on PM2.5, however, many of the PM monitoring records available for retrospective studies are of coarser PM10 data. This study explores the possibility to simulate PM2.5 data using PM10 records and assesses the trade-off between introduction of the unavoidable simulation errors and the improved spatial coverage enabled by the simulated series. Several modelling approaches are studied, bearing in mind the range of Exposure time scales typical to environmental epidemiology studies. The modelling capability is evaluated by cross-testing between three stations observing both the PM2.5 and PM10 fractions. The trade-off between improved spatial coverage and simulation errors is assessed using leave-one-out cross-validation interpolations. Interpolations including both original and simulated data resulted in richer spatial patterns. Their cross-validated performance was comparable to or slightly better than that obtained using the original PM2.5 data only. The study provides methodologies and guidelines for scientists and practitioners on how to properly exploit their PM10 data to enhance their PM2.5 spatial coverage and minimise investment in new PM2.5 monitoring.
Bradley E Sample - One of the best experts on this subject based on the ideXlab platform.
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Recommendations to improve wildlife Exposure Estimation for development of soil screening and cleanup values
Integrated environmental assessment and management, 2013Co-Authors: Bradley E Sample, Chris Schlekat, David J. Spurgeon, Charlie Menzie, Jon Rauscher, Bill AdamsAbstract:An integral component in the development of media-specific values for the ecological risk assessment of chemicals is the derivation of safe levels of Exposure for wildlife. Although the derivation and subsequent application of these values can be used for screening purposes, there is a need to identify the threshold for effects when making remedial decisions during site-specific assessments. Methods for evaluation of wildlife Exposure are included in the US Environmental Protection Agency (USEPA) ecological soil screening levels (Eco-SSLs), registration, evaluation, authorization, and restriction of chemicals (REACH), and other risk-based soil assessment approaches. The goal of these approaches is to ensure that soil-associated contaminants do not pose a risk to wildlife that directly ingest soil, or to species that may be exposed to contaminants that persist in the food chain. These approaches incorporate broad assumptions in the Exposure and effects assessments and in the risk characterization process. Consequently, thresholds for concluding risk are frequently very low with conclusions of risk possible when soil metal concentrations fall in the range of natural background. A workshop held in September, 2012 evaluated existing methods and explored recent science about factors to consider when establishing appropriate remedial goals for concentrations of metals in soils. A Foodweb Exposure Workgroup was organized to evaluate methods for quantifying Exposure of wildlife to soil-associated metals through soil and food consumption and to provide recommendations for the development of ecological soil cleanup values (Eco-SCVs) that are both practical and scientifically defensible. The specific goals of this article are to review the current practices for quantifying Exposure of wildlife to soil-associated contaminants via bioaccumulation and trophic transfer, to identify potential opportunities for refining and improving these Exposure estimates, and finally, to make recommendations for application of these improved models to the development of site-specific remedial goals protective of wildlife. Although the focus is on metals contamination, many of the methods and tools discussed are also applicable to organic contaminants. The conclusion of this workgroup was that existing Exposure Estimation models are generally appropriate when fully expanded and that methods are generally available to develop more robust site-specific Exposure estimates. Improved realism in site-specific wildlife Eco-SCVs could be achieved by obtaining more realistic estimates for diet composition, bioaccumulation, bioavailability and/or bioaccessibility, soil ingestion, spatial aspects of Exposure, and target organ Exposure. These components of wildlife Exposure Estimation should be developed on a site-, species-, and analyte-specific basis to the extent that the expense for their derivation is justified by the value they add to Eco-SCV development.
Kirk R Smith - One of the best experts on this subject based on the ideXlab platform.
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Better radiation Exposure Estimation for the Japanese atomic-bomb survivors enables us to better protect people from radiation today.
Journal of exposure science & environmental epidemiology, 2010Co-Authors: Harry M. Cullings, Kirk R SmithAbstract:Better radiation Exposure Estimation for the Japanese atomic-bomb survivors enables us to better protect people from radiation today
