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Modeling Competitive Arsenate‐Phosphate Retention and Transport in Soils: A Multi‐Component Multi‐Reaction Approach
Author(s) -
Zhang Hua,
Selim H. M.
Publication year - 2007
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj2006.0422
Subject(s) - soil water , sorption , chemistry , arsenate , kinetics , phosphate , soil science , environmental chemistry , adsorption , environmental science , physics , arsenic , organic chemistry , quantum mechanics
This study was conducted to investigate the kinetics of arsenate [As(V)]‐phosphate [P] competitive retention during transport in soils. Time‐dependent batch experiments were performed to describe competitive As(V)‐P sorption kinetics in Olivier (fine‐silty, mixed, active, thermic Aquic Fraglossudalfs) and Windsor (mixed, mesic Typic Udipsamments) soils. Miscible‐displacement experiments were also performed to quantify As(V)‐P competition when anion pulses were introduced simultaneously or consecutively into water‐saturated soil columns. The results demonstrated that the rates and amounts of As(V) sorption are significantly reduced by increasing addition of P. Due to competitive sorption, the presence of P resulted in increased mobility of As(V) in the soil columns. Flow interruptions indicated the dominance of time‐dependent sorption during As(V) and P transport in soils. We extended the equilibrium‐kinetic multireaction model (MRM) to simulate competitive retention kinetics of multiple chemical species in soils. Competitive coefficients from Sheindorf–Rebhun–Sheintuch (SRS) equation were adopted to describe the extent of As(V)‐P competition. A multi‐component multireaction model (MCMRM) was coupled with the advection‐dispersion equation (ADE) to describe breakthrough curves (BTCs) of As(V) and P simultaneously. Model predictions of measured BTCs for competitive As(V)‐P transport were achieved using rate coefficients based on inverse modeling.

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