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PREDICTING POPULATION EXPOSURES TO PM10 AND PM 2.5
Citation:
Ozkaynak, A H., M J. Zufall, J M. Burke, J. Xue, AND J. Zidek. PREDICTING POPULATION EXPOSURES TO PM10 AND PM 2.5. Presented at Third Colloquium on Particulate Air Pollution and Public Health, Durham, NC, June 6-8, 1999.
Description:
An improved model for human exposure to particulate matter (PM), specifically PM10 and PM2.5 is under development by the U.S. EPA/NERL. This model will incorporate data from new PM exposure measurement and exposure factors research. It is intended to be used to predict exposure of the general population and susceptible subpopulations to PM from both ambient and other sources. Two-stage Monte-Carlo simulation techniques will be used to characterize uncertainty and variability in the various model parameters and inputs. The initial version of this model was applied to Vancouver, Canada, following the statistical spatial interpolation of ambient PM10, data, to predict the distributions of PM10 exposures of both indoor and outdoor origin by cohort, age, activity type and microenvironment category. Exposures in homes were modeled using the information derived from the PTEAM study. The preliminary results showed wide ranges in the predicted personal exposures of various population cohorts due to influences from different human activities and contributions from indoor sources, such as smoking or cooking. Limitations of available data on PM measurements in schools, commuting environments, and different public places were identified as important sources of model uncertainties. Data from a recent review of PM concentrations in various nonresidential microenviromnents will be used to improve model estimates of indoor PM exposures in offices, schools, restaurants, public places and during commuting. Other planned model improvements include utilization of the results of recent research on: infiltration of ambient PM indoors, the effects of a personal cloud on PM exposure, and linkage with ambient. air quality and dosimetric models.
This is a proposed abstract and does not necessarily reflect USEPA policy.