A probabilistic risk assessment (PRA) using a range of sustainable usual fish consumption rates (SUFCRs) was performed to evaluate the potential health risks from consuming resident fish at two contaminated sediment sites. The analysis focused on the Portland Harbor Superfund Site, a large river in Oregon, and Koppers Pond, a small pond in New York. At both sites, the sediment cleanup remedy is driven by PCBs in resident fish. The PRA fit probability distributions to inputs used to develop a distribution of SUFCR, the long-term fish consumption rate sustainably supported by a fishery, and other exposure parameters to calculate the range and likelihood of cancer risks and noncancer hazards for adult anglers. At the 95th percentile, which is often considered a reasonable maximum exposure (RME), the SUFCRs calculated using site-specific inputs are six- to ten-fold lower than the point estimate fish consumption rates used in the deterministic baseline human health risk assessment conducted for each site. The combination of sustainable fish consumption rates and probabilistic methods results in a range of risks and thereby provides more information than the more commonly used deterministic approach. For over 99% of the resident fish-consuming population, the potential cancer risks and noncancer hazards calculated in the PRA are below the deterministic estimates for the RME adult consumer at each site. The combination of PRA with the estimation of SUFCRs is a novel application of these techniques at contaminated sediment sites that provides critical information for risk management decision-making. Integr Environ Assess Manag 2023;19:830–843. © 2022 AECOM Technical Services, Inc and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
CITATION STYLE
Ruffle, B., Pfeiffer, D., Morrison, E., Kirkwood, G., & Anderson, P. (2023). Probabilistic risk assessment of sustainable fish consumption at sediment sites. Integrated Environmental Assessment and Management, 19(3), 830–843. https://doi.org/10.1002/ieam.4724
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