Phototoxicity occurs when exposure to ultraviolet radiation increases the toxicity of certain contaminants, including polycyclic aromatic hydrocarbons (PAHs). This study aimed to (1) develop a quantitative model to predict the risk of PAH phototoxicity to fish, (2) assess the predictive value of the model, and (3) estimate the risk of PAH phototoxicity to larval and young of year Pacific herring (Clupea pallasi) following the Exxon Valdez oil spill (EVOS) in Prince William Sound, Alaska. The model, in which median lethal times (LT50 values) are estimated from whole-body phototoxic PAH concentrations and ultraviolet A (UVA) exposure, was constructed from previously reported PAH phototoxicity data. The predictive value of this model was confirmed by the overlap of model-predicted and experimentally derived LT50 values. The model, along with UVA characterization data, was used to generate estimates for depths of de minimiz risk for PAH phototoxicity in young herring in 2003/2004 and immediately following the 1989 EVOS, assuming average and worst case conditions. Depths of de minimiz risk were estimated to be between 0 and 2 m deep when worst case UVA and PAH conditions were considered. A post hoc assessment determined that <1% of the young herring population would have been present at depths associated with significant risk of PAH phototoxicity in 2003/2004 and 1989.

We evaluated the use of biokinetic models to predict selenium (Se) bioaccumulation into model food chains after shortterm pulses of selenate or selenite into water. Both periphyton-and phytoplankton-based food chains were modeled, with Se trophically transferred to invertebrates and then to fish. Whole-body fish Se concentrations were predicted based on 1) the background waterborne Se concentration, 2) the magnitude of the Se pulse, and 3) the duration of the Se pulse. The models were used to evaluate whether the US Environmental Protection Agency's (USEPA's) existing acute Se criteria and their recently proposed intermittent Se criteria would be protective of a whole-body fish Se tissue-based criterion of 8.1 mg g -1 dry wt. Based on a background waterborne Se concentration of 1 mg L -1 and pulse durations of 1 d and 4 d, the Se pulse concentrations predicted to result in a whole-body fish Se concentration of 8.1 mg g -1 dry wt in the most conservative model food chains were 144 and 35 mg L -1 , respectively, for selenate and 57 and 16 mg L -1 , respectively, for selenite. These concentrations fall within the range of various acute Se criteria recommended by the USEPA based on direct waterborne toxicity, suggesting that these criteria may not always be protective against bioaccumulation-based toxicity that could occur after short-term pulses. Regarding the USEPA's draft intermittent Se criteria, the biokinetic modeling indicates that they may be overly protective for selenate pulses but potentially underprotective for selenite pulses. Predictions of whole-body fish Se concentrations were highly dependent on whether the food chain was periphyton-or phytoplankton-based, because the latter had much greater Se uptake rate constants. Overall, biokinetic modeling provides an approach for developing acute Se criteria that are protective against bioaccumulation-based toxicity after trophic transfer, and it is also a useful tool for evaluating averaging periods for chronic Se criteria. Integr Environ Assess Manag 2016;12:230-246. © 2015 SETAC

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Acceptance of the biotic ligand model (BLM) to derive aquatic life criteria, for metals in general and copper (Cu) in particular, is growing among regulatory agencies worldwide. Thus, it is important to ensure that water quality data are used appropriately and consistently in deriving such criteria. Here we present a suggested BLM implementation framework (hereafter referred to as "the Framework") to help guide the decision-making process when designing sampling and analysis programs for use of the BLM to derive water quality criteria applied on a site-specific basis. Such a framework will help inform stakeholders on the requirements needed to derive BLM-based criteria, and thus ensure that the appropriate types and amount of data are being collected and interpreted. The Framework was developed for calculating BLM-based criteria when data are available from multiple sampling locations on a stream. The Framework aspires to promote consistency when applying the BLM across data sets of disparate water quality, data quantity, and spatial and temporal representativeness and is meant to be flexible to maximize applicability over a wide range of scenarios. Therefore, the Framework allows for a certain level of interpretation and adjustment to address the issues unique to each data set. Integr Environ Assess Manag 2018;14:736-749. © 2018 SETAC.