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United States Department of Agriculture

Agricultural Research Service

Research Project: SALINITY AND TRACE ELEMENTS ASSOCIATED WITH WATER REUSE IN IRRIGATED SYSTEMS: PROCESSES, SAMPLING PROTOCOLS, AND SITE-SPECIFIC MANAGEMENT Title: Predicting Selenite Adsorption by Soils Using Soil Chemical Parameters in the Constant Capacitance Model

Authors
item GOLDBERG, SABINE
item Lesch, Scott - UC RIVERSIDE
item SUAREZ, DONALD
item SUAREZ, DONALD

Submitted to: Soil Science Society of America Annual Meeting
Publication Type: Abstract Only
Publication Acceptance Date: September 1, 2007
Publication Date: November 8, 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. Soil Science Society of America Annual Meeting. Paper No. 91-9.

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 on 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.

Last Modified: 7/25/2014
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