Simplified Integration of Bioavailability Data into Food Chain Modeling to Estimate Biota Sediment Accumulation Factors

摘要

Overview. Proper estimation of potential uptake for sediments to fish is critical at manysediment sites where calculated risk to human or wildlife fish consumers is the driver forremediation. The key factor that estimates fish tissue concentrations-the biota sedimentaccumulation factor (BSAF)-is often derived based on default factors without considerationof actual bioavailability or metabolic factors. A simplified approach to incorporatingbioavailability into BSAF estimates is presented that relies on a published EPA foodweb model and commonly available site data. This approach is particularly useful in loweringpredicted risk associated with compounds that are tightly adsorbed or undergo metabolismin fish.Background/Objectives. It has become routine to measure or estimate porewater concentrationsin sediment as a measure of bioavailability, and these data are widelyaccepted in assessing risk to benthic life. However, at most sites estimates of dietary fishtissue concentrations rely on literature values or simplistic mathematical estimates ofBSAFs that do not use the available porewater data. The purpose of evaluation presentedhere was to develop a simplified approach to integrate the porewater results into BSAFestimation.Approach/Activities. Predicted BSAFs were estimated for several PAH compounds usingthe U.S.EPA KABAM version 1.0 model (free) and a limited number of site-specificvariables (porewater concentrations, bulk sediment concentrations, total organic carbonand estimated flow of the receiving surface water body) and published estimates of fishmetabolic factors. BSAFs decreased by fish trophic level and reflected accumulation atlevels several orders of magnitude below sediment. Conversely, BSAFs estimated usingsimplified equations based on equilibrium partitioning and lipophilicity predict unrealisticallyhigh accumulation in fish. These discrepancies are particularly notable for PAHs,which tend to be metabolized.Results/Lessons Learned. Data collected for bioavailability assessment of benthos canbe used to make better predictions of impacts to humans and higher-level wildlife, possiblyaltering risk management decisions at sites impacted by MGP, creosote, and otherPAH sources. Various modeled BSAFs are presented and compared with values reportedin the literature and predicted using equations. A key uncertainty is the water columnconcentration, which is typically below detection capability and must be estimated.Should this model be put into wider use for food chain effects at sites, a growing body ofresults will assist the user in identifying and modifying key variables to optimize themodel’s predictive value.