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ASSESSING POPULATION EXPOSURES TO MULTIPLE AIR POLLUTANTS USING A MECHANISTIC SOURCE-TO-DOSE MODELING FRAMEWORK
Citation:
Georgopoulos, P. G., S. W. Wang, V. M. Vyas, Q. Sun, P. Shade, Y. C. Yang, J M. Burke, R. Vedantham, AND A H. Ozkaynak. ASSESSING POPULATION EXPOSURES TO MULTIPLE AIR POLLUTANTS USING A MECHANISTIC SOURCE-TO-DOSE MODELING FRAMEWORK. Presented at International Society of Exposure Analysis, Stresa, Italy, September 21-25, 2003.
Impact/Purpose:
The overall objective of this research is to develop, apply, and evaluate a human exposure model for predicting population exposures to the components of particulate matter (PM) identified as potential toxic agents contributing to adverse health effects.
Description:
The Modeling Environment for Total Risks studies (MENTOR) system, combined with an extension of the SHEDS (Stochastic Human Exposure and Dose Simulation) methodology, provide a mechanistically consistent framework for conducting source-to-dose exposure assessments of multiple pollutants, for either individuals or populations. Typical simulations employing the Population Based Modeling (PBM) option consist of the following steps: (1) Characterization of ambient pollution levels through a combination of environmental model predictions and field data; (2) Estimation of local outdoor levels of contaminants, which characterize the ambient air of an administrative unit (e.g. census tract); (2) Characterization of levels and temporal profiles of contaminants in various residential and occupational microenvironments; (3) Selection of a fixed-size sample population that statistically reproduces essential demographics (age, gender, race, occupation) of the population unit used (e.g. census tract) in the assessment; (4) Development of activity event sequences for each member of the sample population from diaries or by matching attributes to entries of USEPA's Consolidated Human Activity Database (CHAD); (5) Calculation of physiological intake rates for the members of the sample population, reflecting/combining physiological attributes and activities pursued; (6) Combination of intake rates with microenvironmental levels of contaminants to assess exposures; (7) Averaging of exposure estimates over appropriate time-intervals to produce appropriate exposure metrics; (8) Development of appropriate estimates of dose, reflecting physiological, biochemical, and activity factors; (9) "Extrapolation" of results to the population of concern. A series of case studies is presented, demonstrating simultaneous population exposures to multiple air pollutants such as PM2.5, O3, and air toxics.
Disclaimer: This work had been funded in part by the US Environmental Protection Agency under Cooperative Agreement # EPAR-827033 to Environmental and Occupation Health Sciences Institute. It has been subjected to Agency review and approved for publication.