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 many sediment sites where calculated risk to human or wildlife fish consumers is the driver for remediation. The key factor that estimates fish tissue concentrations-the biota sediment accumulation factor (BSAF)-is often derived based on default factors without consideration of actual bioavailability or metabolic factors. A simplified approach to incorporating bioavailability into BSAF estimates is presented that relies on a published EPA food web model and commonly available site data. This approach is particularly useful in lowering predicted risk associated with compounds that are tightly adsorbed or undergo metabolism in fish. Background/Objectives. It has become routine to measure or estimate porewater concentrations in sediment as a measure of bioavailability, and these data are widely accepted in assessing risk to benthic life. However, at most sites estimates of dietary fish tissue concentrations rely on literature values or simplistic mathematical estimates of BSAFs that do not use the available porewater data. The purpose of evaluation presented here was to develop a simplified approach to integrate the porewater results into BSAF estimation. Approach/Activities. Predicted BSAFs were estimated for several PAH compounds using the U.S.EPA KABAM version 1.0 model (free) and a limited number of site-specific variables (porewater concentrations, bulk sediment concentrations, total organic carbon and estimated flow of the receiving surface water body) and published estimates of fish metabolic factors. BSAFs decreased by fish trophic level and reflected accumulation at levels several orders of magnitude below sediment. Conversely, BSAFs estimated using simplified equations based on equilibrium partitioning and lipophilicity predict unrealistically high 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 can be used to make better predictions of impacts to humans and higher-level wildlife, possibly altering risk management decisions at sites impacted by MGP, creosote, and other PAH sources. Various modeled BSAFs are presented and compared with values reported in the literature and predicted using equations. A key uncertainty is the water column concentration, 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 of results will assist the user in identifying and modifying key variables to optimize the model’s predictive value.