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Using Monte Carlo analysis to characterize the uncertainty in final acute values derived from aquatic toxicity data

Many ambient water quality criteria established to protect aquatic life from acute toxicity are calculated using a procedure described in the US Environmental Protection Agency's “1985 Guidelines” (USEPA 1985 ). The procedure yields a final acute value (FAV) from acceptable median lethal or effective concentrations (LC50 or EC50, respectively) that is a single‐point, deterministic estimate of the concentration of a chemical substance that will protect 95% of aquatic species from >50% mortality or other acute toxic effects. However, because of variation and uncertainty associated with toxicity test results, uncertainty in the estimated FAV exists that is not accounted for by the 1985 Guidelines procedure. Here, Monte Carlo analysis is used to characterize this uncertainty. The analysis uses Cu EC50 values adjusted for differences in test water chemistry obtained from USEPA's final freshwater Cu criteria guidance published in 2007. Additional Monte Carlo simulations illustrate Cu FAV distributions obtained using a subset of tested species and assuming fewer replicate tests. The deterministic procedure yields an FAV of 4.68 µg/L for the complete data set. By comparison, 3 replicate Monte Carlo simulations yielded mean FAVs of 4.66 µg/L. The 5th and 95th percentiles of the distribution of calculated FAVs were 4.14 µg/L and 5.20 µg/L, respectively. Reducing the number of tested genera from 27 to 8 (the minimum recommended by the 1985 Guidelines) and setting the number of tests per species equal to 3 yielded 5th and 95th percentiles of 1.22 µg/L and 6.18 µg/L, respectively, compared to a deterministic estimate of 2.80 µg/L. Results of this study indicate that Monte Carlo analysis can be used to improve the understanding and communication of uncertainty associated with water quality criteria derived from acute toxicity data using the 1985 Guidelines. This may benefit the development, revision, and application of these criteria in the future. Integr Environ Assess Manag 2011;7:269–279. © 2010 SETAC