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Humic Ion-Binding Model VII: a revised parameterisation of cation-binding by humic substances

Humic Ion-Binding Model VII: a revised parameterisation of cation-binding by humic substances Environmental context Natural organic matter exerts a powerful control on chemical conditions in waters and soils, affecting pH and influencing the biological availability, transport and retention of metals. To quantify the reactions, we collated a wealth of laboratory data covering 40 metals and acid–base reactions, and used them to parameterise the latest in a series of Humic Ion-Binding Models. Model VII is now available to interpret field data, and contribute to the prediction of environmental chemistry. Abstract Humic Ion-Binding Model VII aims to predict the competitive reactions of protons and metals with natural organic matter in soils and waters, based on laboratory results with isolated humic and fulvic acids (HA and FA). Model VII is simpler in its postulated multidentate metal binding sites than the previous Model VI. Three model parameters were eliminated by using a formal relationship between monodentate binding to strong- and weak-acid oxygen-containing ligands, and removing factors that provide ranges of ligand binding strengths. Thus Model VII uses a single adjustable parameter, the equilibrium constant for monodentate binding to strong-acid (carboxylate) groups ( K MA ), for each metallic cation. Proton-binding parameters, and mean values of log K MA were derived by fitting 248 published datasets (28 for protons, 220 for cationic metals). Default values of log K MA for FA were obtained by combining the fitted values for FA, results for HA, and the relationship for different metals between log K MA and equilibrium constants for simple oxygen-containing ligands. The equivalent approach was used for HA. The parameterised model improves on Model VI by incorporating more metals (40), providing better descriptions of metal binding at higher pH, and through more internally consistent parameter values. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Environmental Chemistry CSIRO Publishing

Humic Ion-Binding Model VII: a revised parameterisation of cation-binding by humic substances

Tipping E.; Lofts S.; Sonke J. E.
Environmental Chemistry , Volume 8 (3) – Jun 22, 2011
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Publisher
CSIRO Publishing
Copyright
CSIRO
ISSN
1448-2517
eISSN
1449-8979
DOI
10.1071/EN11016
Publisher site
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Abstract

Environmental context Natural organic matter exerts a powerful control on chemical conditions in waters and soils, affecting pH and influencing the biological availability, transport and retention of metals. To quantify the reactions, we collated a wealth of laboratory data covering 40 metals and acid–base reactions, and used them to parameterise the latest in a series of Humic Ion-Binding Models. Model VII is now available to interpret field data, and contribute to the prediction of environmental chemistry. Abstract Humic Ion-Binding Model VII aims to predict the competitive reactions of protons and metals with natural organic matter in soils and waters, based on laboratory results with isolated humic and fulvic acids (HA and FA). Model VII is simpler in its postulated multidentate metal binding sites than the previous Model VI. Three model parameters were eliminated by using a formal relationship between monodentate binding to strong- and weak-acid oxygen-containing ligands, and removing factors that provide ranges of ligand binding strengths. Thus Model VII uses a single adjustable parameter, the equilibrium constant for monodentate binding to strong-acid (carboxylate) groups ( K MA ), for each metallic cation. Proton-binding parameters, and mean values of log K MA were derived by fitting 248 published datasets (28 for protons, 220 for cationic metals). Default values of log K MA for FA were obtained by combining the fitted values for FA, results for HA, and the relationship for different metals between log K MA and equilibrium constants for simple oxygen-containing ligands. The equivalent approach was used for HA. The parameterised model improves on Model VI by incorporating more metals (40), providing better descriptions of metal binding at higher pH, and through more internally consistent parameter values.

Journal

Environmental Chemistry – CSIRO Publishing

Published: Jun 22, 2011

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