Citation:

OZKAYNAK, H. A. EXPERIENCES WITH USING PROBABILISTIC EXPOSURE ANALYSIS METHODS IN THE U.S. EPA. Presented at Society for Risk Analysis 2007 Annual Conference, San Antonio, TX, December 09 - 12, 2007.

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:

Over the past decade various Offices and Programs within the U.S. EPA have either initiated or increased the development and application of probabilistic exposure analysis models. These models have been applied to a broad range of research or regulatory problems in EPA, such as evaluation of human exposures to air toxics or criteria air pollutants (e.g., Particulate Matter and Ozone) or assessing the impacts from exposures to multimedia pollutants, such as pesticides and toxic metals in the environment or in the diet. Predominantly, probabilistic exposure models have been developed by EPA's Office of Research and Development (ORD), as well as, by the various Program offices of EPA, such as the Office of Air (OAR), Office of Pesticides Programs (OPP), and Office of Solid Waste and Emergency Response (OSWER). Most of the probabilistic analysis techniques used in modeling personal or population exposures combine human time activity or food consumption survey data with distributional information, on: pollution or contaminant concentrations in the relevant media and microenvironments; release or application rates, and; exposure factors data (e.g., inhalation or contact rates, uptake rates). These models were often applied to quantify the magnitude and the drivers of exposures and risks at various upper percentiles of regulatory concern. This presentation provides an overview of the different probabilistic exposure modeling methodologies considered by the different Programs/Offices in EPA, along with some illustrative examples. The impetus for using probabilistic modeling tools in Agency research or policy evaluations will be addressed. Finally, this presentation will also discuss the principal reasons for successful use of probabilistic exposure methods by the EPA, as well as some of the key challenges facing for its broader use in the future.

Record Details: