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Exposure-effect model for calculating copper effect concentrations in sediments with varying copper binding properties: a synthesis.

Abstract

An exposure-effects model is described for calculating copper effect concentrations for benthic organisms in sediments with varying copper-binding properties. It is based on a bioenergetic-based kinetic model that describes the rate of assimilation of copper by benthic organisms from dissolved and particulate phases. During acute exposures, the total copper assimilated by the organisms was used as a measure of the organisms' exposure to bioavailable copper, and toxicity occurs when the copper exposure exceeds a threshold value. Exposure-effects models were developed for nine benthic organisms and were used to predict the effect of sediment-water partitioning (Kd) and copper assimilation from ingested solids on toxic effects and how these factors will influence derived sediment quality guideline (SQG) concentrations. Species sensitivity distributions were used to calculate SQG concentrations for copper for sediments of varying copper binding properties. The modeling indicated that "single value" SQG concentrations would be ineffective for predicting the toxicity of metals in sediment. It is proposed that, for all contaminants (not just metals), a better approach would be to have SQG concentrations, or ranges, that are applied to different sediment types. SQGs should account for contaminant exposure from both water-filtration and particulate-ingestion exposure routes, as can be achieved by models of sediment-water contaminant partitioning (Kd) and the contaminant assimilation efficiency (AE) of ingested particles. The study indicates that improved mechanistic models of contaminant exposure, as influenced by both organism physiology and sediment properties, are needed to predict toxic effects in sediments.

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BibTeXRIS

Stuart L Simpson. 2005-09-15. Exposure-effect model for calculating copper effect concentrations in sediments with varying copper binding properties: a synthesis.. https://doi.org/10.1021/es050765c

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