Skip to main content
ARS Home » Research » Publications at this Location » Publication #204409
Title: Predicting Selenite Adsorption by Soils Using Soil Chemical Parameters in the Constant Capacitance Model

Author
item Goldberg, Sabine
item LESCH, SCOTT - UC RIVERSIDE, CA
item Suarez, Donald

Submitted to: Geochimica et Cosmochimica Acta
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/24/2007
Publication Date: 9/5/2007
Citation: Goldberg, S.R., Lesch, S.M., Suarez, D.L. 2007. Predicting Selenite Adsorption by Soils Using Soil Chemical Parameters in the Constant Capacitance Model. Geochimica et Cosmochimica Acta. 71:5750-5762.

Interpretive Summary: Selenite is a specifically adsorbing anion that is toxic to animals at elevated concentrations. Toxic concentrations can occur in agricultural soils and irrigation waters. A better understanding of the adsorption behavior of this ion is necessary. Adsorption of selenite by 36 soil samples was investigated under changing conditions of solution pH. The adsorption behavior was evaluated and predicted using a chemical model and easily measured soil chemical characteristics. Our results will benefit scientists who are developing models of selenite movement in arid zone soils. The results can be used to improve predictions of selenite behavior in soils and thus aid action and regulatory agencies in the management of soils and waters which contain elevated concentrations of selenite.

Technical 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 three soils. Incorporation of these prediction equations into chemical speciation-transport models will allow simulation of soil solution Se(IV) concentrations under diverse noncalcareous agricultural and environmental conditions without the requirement of soil specific adsorption data and subsequent parameter optimization.