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R7 PM Uncertainty Analysis in Risk Assessment: Influences on Decision-making
(BRI-1117-724889) Managing Uncertainty to Make Risk-Informed Decisions About Contaminated Sediments.
Bridges, T1, von Stackelberg, K2, Vorhees, D2, Butler, C2, Cura, J2, Greges, M3, Reiss, M4, 1 United States Army Engineer Research and Development Center, Vicksburg, MS, USA2 Menzie-Cura & Associates, Inc., Winchester, MA, USA3 US Army Corps of Engineers, NY District, New York, NY, USA4 US EPA, Region 2, New York, NY, USA
ABSTRACT- This paper will describe how the regulatory community, concerned with placing sediments at the Historic Area Remediation Site (HARS) on the NY Bight, are incorporating site-specific information and uncertainty into their decision-making approach. Limited and uncertain data often challenge regulators in reaching credible conclusions about the extent, magnitude and management of risks. One response to this challenge has been to invest in additional data collection and research. This investment provides additional insights into the processes relevant to understanding risk, but still leaves unresolved uncertainties. Managing and addressing this residual uncertainty represent significant challenges to decision-making. At the HARS, past regulatory evaluations for sediment placement were a comparison of bioaccumulation test results to deterministically derived tissue based guidelines. More recently, regulators have considered risks to fish and humans from contaminant bioaccumulation and trophic transfer. Regulators, recognizing important uncertainties in these evaluations, commissioned two site-specific studies: a fish tagging study to learn more about how fish behavior may affect their exposures; and, a creel survey to refine fish ingestion rates for the angler population fishing near the HARS. Refined and updated estimates of these and other inputs to the evaluation were used to develop a remodeled approach for evaluating sediments based on estimating risks from cumulative contaminant effects. This approach factors uncertainty and variability in input parameters into bioaccumulation and risk modeling using two-dimensional Monte Carlo analysis. Model outputs are included in a decision-support tool that allows decision-makers to explore and factor uncertainty into their conclusions about risks and their decisions as to how to manage those risks.
Key words: uncertainty, creel survey, probabilistic, fish tagging
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