Predicting selenite adsorption by soils using soil chemical parameters in the constant capacitance model |
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| Authors: | Sabine Goldberg Scott M Lesch Donald L Suarez |
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| Institution: | USDA-ARS, U.S. Salinity Laboratory, 450 W. Big Springs Road, Riverside, CA 92507, USA |
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| Abstract: | The constant capacitance model, a chemical surface complexation model, was applied to selenite, Se(IV), adsorption on 36 soils selected for variation in soil chemical properties. The constant capacitance model was able to fit Se(IV) adsorption by optimizing one monodentate Se(IV) surface complexation constant and the surface protonation constant. A general regression model was developed for predicting these surface complexation constants for Se(IV) from easily measured soil chemical characteristics. These chemical properties were inorganic carbon content, organic carbon content, iron oxide content, aluminum oxide content, and surface area. The prediction equations were used to obtain values for the surface complexation constants for four additional soils, thereby providing a completely independent evaluation of the ability of the constant capacitance model to describe Se(IV) adsorption. The model’s ability to predict Se(IV) adsorption was quantitative on one soil and semi-quantitative on three soils. Incorporation of these prediction equations into chemical speciation-transport models will allow simulation of soil solution Se(IV) concentrations under diverse non-calcareous agricultural and environmental conditions without the requirement of soil specific adsorption data and subsequent parameter optimization. |
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