Quantitative Analysis of Uncertainty and Variability in Environmental Policy Making

i ACKNOWLEDGMENTS I spent the summer of 1992 working as an American Association for the Advancement of Science (AAAS) and U.S. Environmental Protection Agency (EPA) Environmental Science and Engineering Fellow. This fellowship program is administered by AAAS under EPA sponsorship. My assignment was in the Exposure Assessment Group (EAG) of the Office of Health and Environmental Assessment, which is part of the Office of Research and Development (ORD) of EPA in Washington, DC. While in EAG, I worked closely with Paul White and enjoyed many long and thorough discussions with him of key concepts in uncertainty analysis. I benefited from interactions with many other individuals at EPA headquarters in ORD, the Office of Policy, Planning, and Evaluation, the Office of Air and Radiation, and the Office of Solid Waste. Thanks also to Max Henrion of Lumina Decision Systems for his helpful comments. I would like to thank the staff at AAAS for facilitating my stay at EPA and for providing a stimulating orientation and seminar program. In particular, thanks to Chris McPhaul, Claudia Sturges, and Patricia Curlin of AAAS, and to Karen Morehouse of EPA. Finally, while I am grateful for the input of many people at EPA and elsewhere, all of the text that follows is my sole responsibility. Environmental Science and Engineering Fellowship Program during the summer of 1992. The views expressed herein are entirely the author's and do not represent official policy of either the EPA or AAAS. The report is subject to further review and revision. Mention of trade names or commercial products does not constitute endorsement or recommendation. iii ABSTRACT Nearly all analyses of environmental problems are confronted with uncertainty. The implications of these uncertainties are particularly critical in the assessment and selection of regulatory options. Current practices within the regulatory community do not adequately deal with uncertainty. These practices, as embodied in EPA guideline documents, often place more emphasis on post-hoc qualitative approaches to caveating uncertainties. In contrast, a quantitative approach to uncertainty analysis is proposed as the most appropriate way to deal with uncertainties. The benefits of such an approach include more proper and explicit characterization of the state-of-knowledge about science and technology without the burden of simplifying, policy-motivated assumptions, concise communication of such information to decision-makers, and a capability to quantitatively identify modeling directions, data requirements, and research needs. General methodological issues of uncertainty analysis are discussed. These issues are illustrated based …