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(P247) An Approach to Identifying Contributors to Toxicity and Prioritizing Pollutants in Sediment Mixtures.
Mowat, F*,1, Bundy, K2, 1 Tetra Tech EM Inc., San Francisco, CA2 Tulane University, New Orleans, LA
ABSTRACT- A mathematical algorithm was developed to compute toxicity of multiple component sediment mixtures acting in an additive manner, after bioavailability and speciation effects are taken into account. A statistical approach was devised to determine the presence of potential synergistic/antagonistic effects among mixture components. The algorithm uses three kinds of data: Microtox® toxicity (EC50 values), sediment concentration measurements, and sequential extraction (SEQ) data to investigate metal partitioning. use of three differing types represents an integrative approach to sediment assessment since biological, toxicological, and chemical factors are accounted for. To simplify the analysis of complex mixtures, a prioritizing scheme using a parameter (based on intrinsic toxicity and relative abundance) known as the toxicity index (TI) was employed. Calculation of overall sediment toxicity based on TI ranking was most efficient in reducing computational time needed to obtain the mixture EC50. In general, the ranking chemicals using TI and SEQ concentration data was found to be the best theoretical predictor of the experimental mixture toxicity value measured at nine sites in two Louisiana bayous. Only a few of the organic and metallic pollutants present in greatest abundance were needed to asymptotically approach the calculated EC50. Both synergistic and antagonistic effects were observed. In most cases, between 5 and 10 chemicals were sufficient to determine the asymptotic EC50, indicating that 67 to 85 percent of chemicals were detected at each site and do not appreciably contribute to the computed toxicity. Besides the substantial implications for both risk assessment and for remediation strategies. It would make them more efficient by focusing on the primary pollutants identified and in some cases dramatically reducing the pollutant monitoring effort required to track toxicity effectively.
Key words: mathematical algorithm, pollutant ranking, sediment mixture effects , Microtox®
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