Assessing the application of an additive model to estimate toxicity of a complex effluent

A number of industries monitor levels of chemicals in their effluent, but few have undertaken prolonged biological monitoring of this wastewater. The focus of the present study was to determine whether past chemical data for effluent from a lead smelter could be used to estimate its past toxicity. Since the interactive effects of metals in effluents are often assumed to be additive, it was hypothesized that an additive model, 100/[sigma(metal concentration in effluent/EC50 for individual metal)], could be used to generate an EC50 from chemical data (where EC50 is the concentration of test material that affects 50% of the test organisms). To test the approach, a larval development toxicity test with the marine polychaete, Galeolaria caespitosa, was used to test 26 separate samples of effluent from a lead smelter, generating empirical EC50 values. EC50 values for each individual metal in the effluent were also generated using the larval development toxicity test. The concentrations of trace metals in each effluent sample were determined and, using the additive model, EC50 values were calculated. For the majority of effluent samples tested, the additive model underestimated toxicity, suggesting the presence of additional unidentified contaminants in the effluent samples. Additionally, a nonlinear rather than linear regression curve was found to best describe the relationship between the model and empirically derived EC50 values. This relationship was then used to estimate past trends in toxicity of the smelter effluent. Forty-eight percent of the variability in measured toxicity was explained by the model, with the model underestimating toxicity in the majority of samples.