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ToxSci Advance Access published online on February 17, 2009
Toxicological Sciences, doi:10.1093/toxsci/kfp036
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© The Author 2009. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org

Probabilistic Exposure Analysis for Chemical Risk Characterization

Kenneth T. Bogen1,*, Alison C. Cullen2, H. Christopher Frey3 and Paul S. Price4

1 Exponent Health Sciences, Oakland CA 2 Evans School of Public Affairs, University of Washington 3 Department of Civil, Construction, and Environmental Engineering, North Carolina State University 4 Formerly with The LifeLine Group

* To whom inquiries should be sent: Dr. K.T. Bogen, Exponent Health Sciences, 500 12th Street, Oakland, CA 94607; kbogen{at}exponent.com

Received August 20, 2008; revision received January 21, 2009; accepted February 8, 2009


  Abstract

This paper summarizes the state of the science of probabilistic exposure assessment (PEA) as applied to chemical risk characterization. Current probabilistic risk analysis (PRA) methods applied to PEA are reviewed. PEA within the context of risk-based decision making is discussed, including probabilistic treatment of related uncertainty, inter-individual heterogeneity, and other sources of variability. Key examples of recent experience gained in assessing human exposures to chemicals in the environment, and other applications to chemical risk characterization and assessment, are presented. It is concluded that, while improvements continue to be made, existing methods suffice for effective application of PEA to support quantitative analyses of the risk of chemically induced toxicity that play an increasing role in key decision-making objectives involving health protection, triage, civil justice, and criminal justice. Different types of information required to apply PEA to these different decision contexts are identified, and specific PEA methods are highlighted that are best suited to exposure assessment in these separate contexts.

Key Words: Applied probability analysis; assessment methods; environmental chemicals; modeling; Monte Carlo; toxicity risk characterization.


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