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Air Pollution Exposure Model for Individuals (EMI) in Health Studies: Evaluation for Ambient PM2.5
Citation:
Breen, M., T. Long, B. Schultz, R. Williams, AND J. Richmond-Bryant. Air Pollution Exposure Model for Individuals (EMI) in Health Studies: Evaluation for Ambient PM2.5. Int'l Society of Indoor Air Quality (ISIAQ), Boulder, CO, July 19 - 22, 2015.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
Health studies of fine particulate matter (PM2.5) often use outdoor concentrations as exposure surrogates, which fail to account for indoor attenuation of ambient PM2.5 and time indoors. To address these limitations, we developed an air pollution exposure model for individuals (EMI) in health studies, which predicts five tiers of exposure metrics from questionnaires and outdoor concentrations. We linked an air exchange rate (AER) model to a mass-balance PM2.5 infiltration model to predict residential AER (Tier 1), infiltration factors (Tier 2), indoor concentrations (Tier 3), exposure factors (Tier 4), and exposures (Tier 5). Individual predictions were compared to 591 daily measurements across 31 homes in North Carolina. Relative differences were 39% (median; Tier 1), 18% (Tier 2), 20% (Tier 3), 18% (Tier 4), and 20% (Tier 5). Using outdoor concentrations as surrogates for exposures (Tier 5), differences of 86% (median) were substantially larger. Thus, EMI could improve exposures for health studies.