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Predicting sediment metal toxicity using a sediment biotic ligand model: methodology and initial application
Authors:Di Toro Dominic M  McGrath Joy A  Hansen David J  Berry Walter J  Paquin Paul R  Mathew Rooni  Wu Kuen Benjamin  Santore Robert C
Affiliation:Department of Civil and Environmental Engineering, University of Delaware, Newark, Delaware 19716, USA. dditoro@ce.udel.edu
Abstract:An extension of the simultaneously extracted metals/acid-volatile sulfide (SEM/AVS) procedure is presented that predicts the acute and chronic sediment metals effects concentrations. A biotic ligand model (BLM) and a pore water-sediment partitioning model are used to predict the sediment concentration that is in equilibrium with the biotic ligand effects concentration. This initial application considers only partitioning to sediment particulate organic carbon. This procedure bypasses the need to compute the details of the pore-water chemistry. Remarkably, the median lethal concentration on a sediment organic carbon (OC)-normalized basis, SEM*(x,OC), is essentially unchanged over a wide range of concentrations of pore-water hardness, salinity, dissolved organic carbon, and any other complexing or competing ligands. Only the pore-water pH is important. Both acute and chronic exposures in fresh- and saltwater sediments are compared to predictions for cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) based on the Daphnia magna BLM. The SEM*(x,OC) concentrations are similar for all the metals except cadmium. For pH = 8, the approximate values (micromol/gOC) are Cd-SEM*(xOC) approximately equal to 100, Cu-SEM*(x,OC) approximately equal to 900, Ni-SEMoc approximately equal to 1,100, Zn-SEM*(x,OC) approximately equal to 1,400, and Pb-SEM*(x,OC) approximately equal to 2,700. This similarity is the explanation for an empirically observed dose-response relationship between SEM and acute and chronic effects concentrations that had been observed previously. This initial application clearly demonstrates that BLMs can be used to predict toxic sediment concentrations without modeling the pore-water chemistry.
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