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Soil Physics

Modeling the Transport and Retention of Arsenic (V) in Soils

Sturgis Hall, Dep. of Agronomy and Environmental Management, Louisiana State Univ. Agric. Center, Baton Rouge, LA 70803-2110

^* Corresponding author (mselim{at}agctr.lsu.edu)

Adsorption and transport of reactive solutes when nonequilibrium conditions are dominant may impact significantly their mobility in heterogeneous systems. In this study, arsenate [As(V)] sorption and transport in three soils having different properties were investigated. Kinetic batch experiments were performed to characterize arsenate [As(V)] adsorption over a wide range of concentrations. Adsorption of arsenate by all soils was strongly nonlinear and kinetic, where the rate of As(V) retention was rapid initially and was followed by gradual or somewhat slow retention behavior with increasing reaction time. Arsenic mobility in soils was investigated using the miscible displacement technique where uniformly packed soil columns under steady and water-saturated flow were used. The column transport experiments indicated strong As(V) retardation followed by slow release or extensive tailing of the breakthrough curves (BTCs). Sharp decrease in As(V) concentration during flow interruption (no flow) further verified the extensive non-equilibrium condition, which was likely due to the dominance of kinetic retention (sorption-release) processes. We evaluated several formulations of a nonlinear equilibrium-kinetic multireaction transport model (MRM) for its prediction capability of As(V) retention as well as transport in all soils. The asymmetrical and retarded BTCs for As(V) from our column experiments were well described using the MRM model. Nonlinear reversible along with a consecutive or concurrent irreversible reactions were the dominant mechanisms in the MRM model. The use of batch rate coefficients as model parameters for the predictions of As(V) BTCs underestimated the extent of retention and overestimated the extent of As(V) mobility for all soils. When utilized in an inverse mode, the MRM model provided good predictions of As(V) BTCs.

Abbreviations: BTC, breakthrough curve • MRM, multireaction transport model • MSMA, monosodium methanearsonate • RMSE, root mean square error

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