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THE CONTRIBUTION OF AMBIENT PM2.5 TO TOTAL PERSONAL EXPOSURES: RESULTS FROM A POPULATION EXPOSURE MODEL FOR PHILADELPHIA, PA
Citation:
Burke, J M., M J. Zufall, A H. Ozkaynak, AND J. Zidek. THE CONTRIBUTION OF AMBIENT PM2.5 TO TOTAL PERSONAL EXPOSURES: RESULTS FROM A POPULATION EXPOSURE MODEL FOR PHILADELPHIA, PA. Presented at ISEA 2000 Exposure Analysis in the 21st Century: Integrating Science, Policy and Quality of Life, Monterey Peninsula, CA, October 24-27, 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 US EPA National Exposure Research Laboratory (NERL) is currently developing an integrated human exposure source-to-dose modeling system (HES2D). This modeling system will incorporate population exposure modules that use a probabilistic approach to predict population exposures to environmental pollutants, including ambient particulate matter (PM). A first-generation population exposure model for PM, called the Stochastic Human Exposure and Dose Simulation (SHEDS-PM) model, has been developed and applied to the population living in Philadelphia, PA.
SHEDS-PM estimates the population distribution of PM exposures by randomly sampling from various input distributions, including both ambient PM concentrations and emission strengths for indoor sources of PM (e.g., cigarette smoking, cooking). A steady-state mass-balance equation is used to calculate indoor PM concentrations for the home microenvironment using ambient PM concentrations and distributions of available physical factor data (e.g., air exchange, penetration, deposition). PM concentrations in non-residential microenvironments are calculated based on distributions of the effective penetration of ambient PM, which were produced using regression analysis of available measurement data for vehicles, offices, restaurants/bars, schools and stores. Additional model inputs include demographic data for the population being modeled and human activity pattern data from NERL's Consolidated Human Activity Database (CHAD). Model outputs include distributions of PM exposures in various microenvironments (indoors, in vehicles, outdoors), and the percent contribution from PM of ambient origin to total personal PM exposures in these microenvironments.
SHEDS-PM has been applied to the population of Philadelphia using spatially-interpolated ambient PM2.5 measurements and 1990 Census data for each census tract in Philadelphia. The resulting distributions of predicted PM2.5 population exposures showed significant differences in PM2.5 exposures for the population of Philadelphia that were largely due to variability in human activities since spatial differences in ambient PM2.5 measurements were not substantial. PM2.5 of ambient origin contributed significantly to total personal exposures, especially for people who spend most of their day either outdoors or indoors at home with no indoor PM2.5 source.
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.