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PREDICTING POPULATION EXPOSURES TO PM: THE IMPORTANCE OF MICROENVIRONMENTAL CONCENTRATIONS AND HUMAN ACTIVITIES
Citation:
Burke, J M., M J. Zufall, A H. Ozkaynak, J. Xue, AND J. Zidek. PREDICTING POPULATION EXPOSURES TO PM: THE IMPORTANCE OF MICROENVIRONMENTAL CONCENTRATIONS AND HUMAN ACTIVITIES. Presented at PM 2000 AWMA Conference, Charleston, SC, January 24-28, 2000.
Impact/Purpose:
The primary objective of this research is to improve current PM population exposure models to more accurately predict exposures for the general population and susceptible sub-populations. Through model improvements, a better understanding of the major factors controlling exposure to PM will be achieved. Specific objectives of this research are to:
- predict total personal exposure to PM10 and PM2.5 for the general and for susceptible sub-populations residing in different urban environments
- estimate the contribution of ambient PM to predicted total PM exposures
- determine what factors are of primary importance in determining PM exposures, including an analysis of the effects of time spent in various microenvironments and the importance of spatial variability in ambient PM concentrations
- determine what factors contribute the greatest uncertainty to model predictions and make recommendations for measurement and modeling studies to reduce these uncertainties
- predict daily and annual average exposures using single or multi-day time-activity diaries
- incorporate state-of-the-art dosimetric models of the lung into PM population exposure and dose models
- evaluate models against measured data from PM panel and other exposure measurement studies
- develop exposure and dose metrics applicable to acute and chronic environmental epidemiology studies
Description:
The Stochastic Human Exposure and Dose Simulation (SHEDS) models being developed by the US EPA/NERL use a probabilistic approach to predict population exposures to pollutants. The SHEDS model for particulate matter (SHEDS-PM) estimates the population distribution of PM exposure by sampling from distributions of ambient PM concentrations and from distributions of emission strengths for indoor sources of PM, such as cigarette smoking and cooking. A steady-state mass-balance equation is used to calculate PM concentrations for the home microenvironment. The physical factors data used in the equation (e.g., air exchange rate, penetration rate, deposition rate) are also sampled from distributions. Non-residential microenvironmental concentrations are calculated based on penetration of outdoor PM and indoor sources. Additional model inputs include demographic data for the population being modeled and human activity pattern data from the National Human Activity Pattern Survey (NHAPS). Output from the SHEDS-PM model includes distributions of PM exposures in various microenvironments (indoors at home, in vehicles, outdoors, etc.) and the relative contributions of these various microenvironments to the total exposure. SHEDS-PM has been applied to the population of Vancouver, Canada using spatially interpolated ambient PM measurements. The resulting distributions of PM exposures showed significant differences within population cohorts that was influenced by variability in human activities and in the contributions from indoor sources, such as smoking or cooking. The relative contributions of the different microenvironments to the total exposures indicate that the physical factors data used to calculate microenviromental concentrations need to be improved. Additional model developments underway include modifications to the input parameters required for modeling PM2.5 exposures, and application of SHEDS-PM to an urban. population in the United States.
This abstract has been reviewed in accordance with the U.S. Environmental Protection Agency's peer and administrative review policies and approved for presentation and publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.