Abstract

The study goal was to develop a sediment polychlorinated biphenyl (PCB) dose-response model based on benthic invertebrate effects to PCBs. The authors used an equilibrium partitioning (EqP) approach to generate predicted PCB sediment effect concentrations (largely Aroclor 1254) associated with a gradient of toxic effects in benthic organisms from effects observed in aquatic toxicity studies. The present study differs from all other EqP collective sediment investigations in that the authors examined a common dose-response gradient of effects for PCBs rather than a single, protective value. The authors reviewed the chronic aquatic toxicity literature to identify measured aqueous PCB concentrations and associated benthic invertebrate effects. The authors control-normalized the aquatic toxic effect data and expressed results from various studies as a common metric, percent injury. Then, they calculated organic carbon-normalized sediment PCB concentrations (mg/kg organic carbon) from the aqueous PCB toxicity data set using EqP theory based on the US Environmental Protection Agency's (EPIWEB 4.1) derivation of the water-organic carbon partition coefficient (KOC ). Lastly, the authors constructed a nonlinear dose-response numerical model for these synoptic sediment PCB concentrations and biological effects: Y = 100/1 + 10([logEC50-logX] × [Hill slope]) (EC50 = median effective concentration). These models were used to generate "look-up" tables reporting percent injury in benthic biota for a range of Aroclor-specific sediment concentrations. For example, the model using the EPIWEB KOC estimate predicts mean benthic injury of 23.3%, 46.0%, 70.6%, 87.1%, and 95% for hypothetical sediment concentrations of 1 mg/kg, 2 mg/kg, 4 mg/kg, 8 mg/kg, and 16 mg/kg dry weight of Aroclor 1254, respectively (at 1% organic carbon). The authors recommend the model presented for screening but suggest, when possible, determining a site-specific KOC that, along with the tables and equations, allows users to create their own protective dose-response sediment concentration. Environ Toxicol Chem 2017;36:1311-1329. © 2016 SETAC.

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