title: Metal speciation in natural waters with emphasis on reduced sulfur groups as strong metal binding sites.
abstract: The proper application of biotic ligand models to predict metal toxicity depends on accurate prediction of metal binding to sites on natural organic matter (NOM) which compete with the 'biotic' ligand for available metal. A hard and soft metal classification along with associated ligand groups (carboxyl, phenolic, amino, sulfidic) are used as a basis to predict metal speciation in the presence of aqueous organic matter. Compilation of conditional metal formation constants (log K') are made for each ligand type using model ligands. Model ligands were chosen to reflect those found in NOM and bio-organic media. Total ligand concentration (L(T)) estimates for different natural settings and log K' values are then used to generate a L(T)-log K' distributions for a specific metal. A plot for Cu(II) gives a similar trend as a compilation of measured data for natural environments. A log K'-L(T) plot for Ag(I) shows a much more discrete binding pattern than for Cu(II). Estimation of speciation of a specific metal in a specific environmental setting and to design speciation and toxicological experiments requires accurate knowledge of the functional groups in NOM.
mesh_terms: D000818:Animals; D001665:Binding Sites / Q000502:physiology; D006801:Humans; D008670:Metals / Q000378:metabolism*; D013457:Sulfur Compounds / Q000378:metabolism*; D014867:Water / Q000032:analysis*
chemical_list: D008670:Metals; D013457:Sulfur Compounds; D014867:Water