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POPULATION-BASED EXPOSURE AND DOSE MODELING FOR AIR POLLUTANTS
Impact/Purpose:
The primary objectives for this task are:
to assess the contribution of outdoor sources to total personal exposures for high priority air toxics and components of particulate matter (PM),
to identify the important microenvironments and human activities contributing to high exposures for these pollutants, and
to evaluate and refine model algorithms and inputs by incorporating new approaches and data, and modularizing model algorithms for application to multiple air pollutants (particles/gases).
Description:
This task will address EPA's need to better understand the variability in personal exposure to air pollutants for the purpose of assessing what populations are at risk for adverse health outcomes due to air pollutant exposures. To improve our understanding of exposures to air pollutants, two primary research questions need to be addressed: (1) what proportion of the population of interest may be exposed to air pollutant levels where health risks are of concern, and (2) what are the important factors driving the variability in population exposures, and thus the resultant risk. Estimating the uncertainty associated with the findings for these questions is also a key objective. The research to be conducted under this task will address these research objectives for high priority air toxics and components of particulate matter (PM) by applying, evaluating, and refining population exposure models. Existing population exposures models (developed under previous research tasks) will be applied in case studies to assess the contribution of outdoor sources to total personal exposures for these pollutants, and to identify the important microenvironments and human activities contributing to high exposures. Model predictions and algorithms will be evaluated through the case study applications, as well as model intercomparisons. Model algorithms and inputs will be refined by incorporating new approaches and newly aquired data, and modularized for application to multiple air pollutant types (e.g., particles, vapors). The focus of the exposure modeling research for PM will be on the chemical components of PM that are linked to health effects. Certain PM components are expected to have greater spatial variability within urban areas compared to PM mass due to local source impacts. Applications and evaluations will be selected based on the availability of measurement study data and/or air quality model output that provides spatial data sufficient for evaluation of different source-type impacts for PM components. The case study applications and evaluations performed under this task will be critical for producing a refined model capable of estimating population exposures to PM components that can be applied using the results from NERL's Detroit Exposure and Aerosol Research Study (DEARS) planned for 2004-2007. For air toxics, model applications and evaluations will initially focus on VOC compounds emitted from mobile sources and aldehydes (e.g., formaldehyde that also has indoor sources). Future integrative model refinements will be initiated to address pollutants that exist in multiple phases (e.g., polycyclic aromatic hydrocarbons (PAH)) and will require the merging of PM algorithms with gas phase algorithms to produce a modularized model capable of estimating exposure to multiple types of air pollutants. The research conducted under this task will provide EPA with evaluated and refined population-based exposure models capable of producing reliable estimates of variability in personal exposure to air pollutants needed for assessing health risks from air pollutant exposures.