A mathematical algorithm to identify toxicity and prioritize pollutants in field sediments.
In order to evaluate sediment toxicity, a mathematical algorithm was developed to compute the toxicity of multiple component mixtures acting in an additive manner. A statistical approach was devised to determine the presence of potential interactive effects among mixture components. The algorithm uses three kinds of data to obtain an integrative approach to sediment toxicity assessment: Microtox toxicity data (EC50 values), sediment pollutant concentration measurements, and sequential extraction (SEQ) data to investigate metal partitioning. To simplify the analysis of complex mixtures using a prioritization scheme based on intrinsic toxicity and relative abundance, a toxicity index (TI) was employed as an indicator of adverse ecological impact. In general, the ranking of contaminants using the TI approach was found to be most efficient in reducing computational time, and concentrations using bioavailability data from SEQ was found to be the best theoretical predictor of the experimental mixture toxicity value. Only a few pollutants that were present at the greatest abundance were needed to provide a good approximation of the calculated EC50 found when all components were included. Not only does this substantially reduce the computational time needed to determine the EC50, it could in some cases dramatically reduce the pollutant monitoring effort required to track toxicity effectively. This approach would have substantial implications for both risk assessment and for remediation strategies, making them more efficient by focusing on the priority pollutants identified.
D000465:Algorithms; D005544:Forecasting; D019015:Geologic Sediments / Q000737:chemistry*; D008145:Louisiana; D008954:Models, Biological; D014874:Water Pollutants, Chemical / Q000032:analysis / Q000633:toxicity*
D014874:Water Pollutants, Chemical