The ability of surface complexation models (SCMs) to fit sets of titration data as a function of changes in model parameters was evaluated using FITEQL and acid-base titration data of a-FeOOH, a-AlzO3, and TiO2. Three SCMs were evaluated: the triple-layer model (TLM), the constant capacitance model (CCM), and the diffuse-layer model (DLM). For all models evaluated, increasing the model input value for the total number of surface sites caused a decrease in the best-fit Log K values of the surface protolysis constants. In the case of the CCM, the best-fit surface protolysis constants were relatively insensitive to changes in the value of the capacitance fitting parameter, G, particularly for values of C1 greater than 1.2 F/m 2. Similarly, the best-fit values of TLM surface electrolyte binding constants were less influenced by changes in the value of C~ when C~ was greater than 1.2 F/m 2. For a given C1 value, the best-fit TLM values of the electrolyte binding constants were sensitive to changes in ApK, up to ApKa values of 3. For ApKa values above 3, no changes in the best-fit electrolyte binding constants were observed. Effects of the quality and extent of titration data on the best-fit values for surface constants are discussed for each model. A method is suggested for choosing a unique set of parameter values for each of the models.
Recent revision of the arsenic in drinking water standard will cause many utilities to implement removal technologies. Most of the affected utilities are expected to use adsorption onto solid media for arsenic removal. The arsenic-bearing solid residuals (ABSR) from adsorption processes are to be disposed of in nonhazardous landfills. The Toxicity Characteristic Leaching Procedure (TCLP) tests whether a waste is hazardous or nonhazardous; most solid residuals pass the TCLP. However, the TCLP poorly simulates the alkaline pH, low redox potential, biological activity, long retention time, and organic composition of mature landfills. These same conditions are likely to favor mobilization of arsenic from metal oxide sorbents. This study quantifies leaching of arsenic from Activated Alumina (AA) and Granular Ferric Hydroxide (GFH), two sorbents expected to be widely used for arsenic removal. The sorbents were subjected to the TCLP, the Waste Extraction Test (WET), an actual landfill leachate, and two synthetic leachate solutions. Up to tenfold greater arsenic concentration is extracted by an actual landfill leachate than by the TCLP. Equilibrium leachate concentrations are not achieved within 18 h (the TCLP duration) and an N2 headspace and end-over-end tumbling increase the rate of arsenic mobilization. However, tests with actual landfill leachate indicate the WET may also underestimate arsenic mobilization in landfills.
The competitive adsorption of arsenate and arsenite with silicic acid at the ferrihydrite-water interface was investigated over a wide pH range using batch sorption experiments, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, extended X-ray absorption fine structure (EXAFS) spectroscopy, and density functional theory (DFT) modeling. Batch sorption results indicate that the adsorption of arsenate and arsenite on the 6-L ferrihydrite surface exhibits a strong pH-dependence, and the effect of pH on arsenic sorption differs between arsenate and arsenite. Arsenate adsorption decreases consistently with increasing pH; whereas arsenite adsorption initially increases with pH to a sorption maximum at pH 7–9, where after sorption decreases with further increases in pH. Results indicate that competitive adsorption between silicic acid and arsenate is negligible under the experimental conditions; whereas strong competitive adsorption was observed between silicic acid and arsenite, particularly at low and high pH. In-situ, flow-through ATR-FTIR data reveal that in the absence of silicic acid, arsenate forms inner-sphere, binuclear bidentate, complexes at the ferrihydrite surface across the entire pH range. Silicic acid also forms inner-sphere complexes at ferrihydrite surfaces throughout the entire pH range probed by this study (pH 2.8 – 9.0). The ATR-FTIR data also reveal that silicic acid undergoes polymerization at the ferrihydrite surface under the environmentally-relevant concentrations studied (e.g., 1.0 mM). According to ATR-FTIR data, arsenate complexation mode was not affected by the presence of silicic acid. EXAFS analyses and DFT modeling confirmed that arsenate tetrahedra were bonded to Fe metal centers via binuclear bidentate complexation with average As(V)-Fe bond distance of 3.27 Å. The EXAFS data indicate that arsenite forms both mononuclear bidentate and binuclear bidentate complexes with 6-L ferrihydrite as indicated by two As(III)-Fe bond distances of ~2.92–2.94 and 3.41–3.44 Å, respectively. The As-Fe bond distances in both arsenate and arsenite EXAFS spectra remained unchanged in the presence of Si, suggesting that whereas Si diminishes arsenite adsorption preferentially, it has a negligible effect on As-Fe bonding mechanisms.
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