[Predicting Sediment Metal Toxicity Using a Sediment Biotic Ligand Model: Methodology and Initial Application; Environmental Toxicology and Chemistry], 2005; Vol. 24(10): 2410-2427
Newswise — Following eight years of study, researchers in the European Union have found that the Biotic Ligand Model (BLM) can now also predict sediment metal toxicity. By using a sediment BML (sBML), scientists can bypass time-consuming computations that were necessary in the past. This new study is published in the latest issue of Environmental Toxicology and Chemistry.
The Biotic Ligand Model is a method used to predict concentrations of metals on biological receptors. For the researchers, the application of BLM to sediment pore water was obvious. Before, a complete characterization of the concentrations of metal ligands present was required. These data normally are not available and are difficult to collect on a routine basis. With a sBML, these data are not necessary.
Instead, computations needed were based on assumptions that, in the study, proved to true. This demonstrates that a sBLM is possible and can avoid the complications of modeling the pore-water chemistry. The obtained results were remarkably consistent with observations in acute and chronic freshwater and marine sediment tests using sensitive organisms. The degree of agreement was within one order of magnitude.
This indicates that a sBLM can be developed in a way that can avoid the use of sediment quality guideline values based on whole sediment contaminant concentrations. Rather, guidelines can be site-specific and based on bioavailability considerations. This way, contaminated sediments can be realistically assessed, allowing resources to go where they are really needed.
To read the entire study about sediment BML, visit: http://www.allenpress.com/pdf/entc_24_1006_2410_2427.pdf.
Integrated Environmental Assessment and Management is the quarterly journal of the Society for Environmental Toxicology and Chemistry. For more information, please visit http://www.setac.org.
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