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A PROBABILISTIC MODELING FRAMEWORK FOR PREDICTING POPULATION EXPOSURES TO BENZENE
Citation:
Graham, S E., J M. Burke, AND A H. Ozkaynak. A PROBABILISTIC MODELING FRAMEWORK FOR PREDICTING POPULATION EXPOSURES TO BENZENE. Presented at International Society of Exposure Analysis 2002 Conference, Vancouver, Canada, August 11-15, 2002.
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:
The US Environmental Protection Agency (EPA) is modifying their probabilistic Stochastic Human Exposure Dose Simulation (SHEDS) model to assess aggregate exposures to air toxics. Air toxics include urban Hazardous Air Pollutants (HAPS) such as benzene from mobile sources, particulate organic matter and metals from industrial point sources, and formaldehyde from indoor sources. However, in addition to these and other air emission sources, many of these HAPS have exposure pathways other than through inhalation. Therefore, a model needs to be developed that allows for prediction of the population distribution of exposure to air toxics through both single or multiple exposure pathways.
As part of a preliminary case study, benzene was selected for investigation and initial model development. Data for exposure factors, ambient air concentrations, and other relevant concentrations were compiled from multiple sources, including EPA's Aerometric Information Retrieval System (AIRS) and Consolidated Human Activity Database (CHAD), as well as measurement data obtained in the literature. The selection of critical microenvironments, the use of mass balance equations or linear models in generating specific exposure concentrations such as in-vehicle or indoor air concentrations, and the development of other microenvironmental exposure concentration distributions were based on human activity patterns, data quality, and data availability. The results of this research serve as inputs to a newly constructed SHEDS-Air Toxics model to estimate population distributions of benzene exposure and absorbed dose.
This work has been subjected to United States Environmental Protection Agency review and approved for presentation and publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.