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HUMAN EXPOSURE MODELING: CONCEPTS, METHODS, AND TOOLS
Citation:
Ozkaynak, A H., J M. Burke, AND S E. Graham. HUMAN EXPOSURE MODELING: CONCEPTS, METHODS, AND TOOLS. Presented at EPA Region 1 Meeting, Boston, MA, August 28, 2003.
Impact/Purpose:
The goal of this research to develop models and computational tools to improve understanding of the functional relationships underlying human exposure to air toxics, and to reduce uncertainty in estimates of exposure to individuals and populations of concern. This goal will be met by addressing a number of key objectives in this task and include:
Model Research and Development: develop a multiroute/pathway/media human exposure and dose model for air toxics.
Model Application: apply model to an urban area (Houston, TX) to estimate human population exposure and dose.
Model Performance Evaluation: compare and evaluate exposure and dose estimates with independent model estimates or personal exposure measurements
Description:
Understanding human exposure is critical when estimating the occurrence of deleterious effects that could follow contact with environmental contaminants. For many pollutants, the intensity, duration, frequency, route, and timing of exposure is highly variable, particularly when human activity patterns are considered simultaneously with variant chemical concentrations. Basic exposure concepts, exposure modeling methods, and available tools are discussed to answer questions surrounding the utility and application of exposure models in a variety of risk-based regulatory scenarios. The discussion includes multipathway exposure assessments and details the stochastic/probabilistic modeling approach utilized by the US EPA's National Exposure Research Laboratory (NERL).
NERL is developing the Stochastic Human Exposure and Dose Simulation (SHEDS) model for estimating exposure to pesticides, particulate matter, and air toxics. SHEDS is a physically-based probabilistic model intended for improving estimates of human exposure and dose to multimedia, multipathway pollutants. A two-dimensional Monte-Carlo simulation methodology is incorporated to characterize population distributions of exposure and dose by explicitly quantifying the variability and the uncertainty in model inputs, parameters, and outputs. A SHEDS model developed for air toxics applications (SHEDS-ATOX) currently estimates an individual's exposure to benzene in several specific microenvironments (e.g., indoors at home) using ambient air toxic concentrations and various exposure factors (e.g., residential air exchange rate). Algorithms specific to mobile source pollutants are also included, such as exposure to chemicals while refueling an automobile and infiltration of air inside a residence from an attached garage. In addition, SHEDS-ATOX estimates dermal exposure from multiple pathways and dietary exposure through ingestion of foodstuffs. In all SHEDS models, the time series of exposure is preserved and allows for the identification of critical exposure factors to assist in determining how to reduce human exposure to chemicals.
This work has been wholly funded by the United States Environmental Protection Agency. It has been subjected to Agency review and approved for publication.