Abstract

The ability to predict the distribution of metals in geologic systems requires a modeling approach that can describe the competition among adsorbing surfaces for the metal of interest. In this study, we test if a component additivity (CA) surface complexation approach can account for the distribution of Cd(II) in mixtures of kaolinite, Bacillus subtilis bacterial cells, iron oxyhydroxide, and a dissolved organic ligand, acetate. We use existing surface complexation models to define the stoichiometries, acidity constants, and site concentrations for the important surface species on each of the sorbents, and we conduct Cd adsorption experiments with each sorbent individually to determine the stability constants for the important Cd–surface complexes on each sorbent. We test the CA approach by comparing CA predictions to measured extents of Cd adsorption in two-, three-, and four-component mixtures of the sorbents at various ratios. Our results indicate that for systems containing B. subtilis, iron oxyhydroxide, and kaolinite, the CA approach is a reasonable predictor of metal distribution, with the accuracy limited by the accuracy of the stability constants of the important surface complexes. However, in systems including acetate, the CA predictions significantly underestimate the extent of adsorption above pH 5, likely due to the formation of ternary Cd–acetate surface complexes on each surface. Metal-organic-surface ternary complexation and site blockage of one sorbent by another are two possible limitations of the applicability of CA surface complexation models to realistic geologic systems.

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