Humic acid protonation, metal ion binding and metal complex dissociation kinetics

Abstract

Two humic acids have been studied in terms of: (i) their ability to bind H⁺, Cd²⁺ and Cu²⁺, and; (ii) the rates of dissociation of their Cu²⁺ complexes.

For both Summit Hill and Waimari Peat humic acids, the protonation reactions of the carboxylic acid functional groups were sensitive to changes in solution ionic strength, such that COOH groups dissociated more readily at higher ionic strength. This behaviour was shown to be consistent with that expected for flexible, macro-ionic molecules with acidic functional group heterogeneity. For Summit Hill humic acid, both the acid strength, and abundance, of COOH groups increased with decreasing molecular size.

The observed complexation of Cd²⁺ and Cu²⁺ with sodium or calcium humates of the humic acids was found to be very heterogeneous with respect to binding af finity. Both metal ions bound significantly to humates in the presence of excess concentrations of Na⁺ or Ca²⁺, and displaced H⁺ from humates at neutral pH, suggesting inner-sphere complexation. The observed enhanced binding of Cd²⁺ and Cu²⁺ to humates, as temperature increased, was found to be more consistent with a very slow component in the complex formation reaction than with thermodynamic effects.

The kinetics of competing-ligand induced Cu²⁺-humate dissociation reactions were also found to be very heterogeneous with respect to first-order rate constants. A new model for metal-humate dissociation kinetics, based on a lognormal distribution of first-order dissociation rate constants, was developed and shown to give a good description of kinetic data. Dissociation reaction rates were found to increase with increasing Cu²⁺:humate ratio, salt concentration or temperature; a decrease in reaction rate was found when pH or pre-dissociation Cu²⁺-humate reaction time was increased.

Modelling of humic acid protonation, metal complexation, and Cu²⁺-humate complex dissociation kinetics data was found to be useful, using suitable models, for predictive or comparative purposes. All equations used for modelling were considered to give strictly empirical descriptions of data.