Derivation of an ambient water quality criterion for mercury: taking account of site-specific conditions.

Mercury is considered to be a serious risk to wildlife. As a result, the Great Lakes Water Quality Initiative and others have developed ambient water quality criteria (AWQC) for the protection of wildlife. These AWQC have been controversial, however, because the AWQC were single values that did not account for site-specific conditions, derivation of the AWQC relied on a single no-observed-adverse-effect level, and the AWQC had an unknown level of conservatism because of reliance on both average and conservative assumptions and uncertainty factors. Rather than develop a single-value AWQC for total mercury, we derived an AWQC model that explicitly incorporates factors controlling bioavailability, methylation rates, and bioaccumulation in the aquatic environment (e.g., pH, dissolved organic carbon). To derive our AWQC model, field data were collected from 31 lakes in Ontario and an additional 10 lakes in Nova Scotia (North America). In the field study, levels of total and methylmercury in water and fish as well as levels of key water quality variables were determined. We conducted multiple-regression analysis to derive a model that estimates mercury levels in prey of mink. Mink are very sensitive to mercury exposure. An independent dataset consisting of 51 water bodies in the United States was then used to confirm the validity and robustness of the AWQC model. Next, we combined the results of chronic-feeding studies with similar protocols and endpoints in a meta-analysis to derive a dose-response curve for mink exposed to mercury in the diet. In the final step, we used a probabilistic risk model to estimate the concentrations of methylmercury in water that would lead to levels in fish sufficient for a 10% probability of exceeding the lethal dose affecting 5% of the mink population. The result is an AWQC equation for mercury for the protection of wildlife that can be used with a variety of site-specific conditions.