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.

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[1] Laboratory experiments, pore-scale simulations, and continuum (Darcy) -scale simulations were used to study mixing-induced precipitation in porous media. In the experimental investigation, solutions containing Na 2 CO 3 and CaCl 2 were each injected in different halves of a quasi two-dimensional flow cell filled with quartz sand. As a result of the in situ mixing between the two solutions, a narrow calcite precipitate layer (less than 5 mm wide) of more or less uniform width was formed between the individual solutions. Pore-scale simulations were conducted to help understand the mechanism of precipitation layer formation. The effect of the Peclet number, Pe, and the Damköhler number, Da, on mixing induced precipitation was also investigated. Pore-scale simulations revealed the presence of large pore-scale concentration gradients. This, and the presence of features, such as the precipitation layer, with characteristic lengths on the order of the average sand grain diameter, indicate the absence of a clear scale separation required for the strict derivation of Darcy-scale advection-dispersion equations. Nevertheless, we found that an adaptive high-resolution model based on advection-dispersion equations with grid sizes in the mixing zone smaller than the size of the sand grains can qualitatively reproduce the essential features of the experiment. As an alternative to computationally expensive high-resolution simulations, we proposed new forms for the homogeneous and heterogeneous reaction terms in Darcy-scale advection dispersion equations. These terms involve transport and mixing indices that account for highly nonuniform pore-scale concentration distributions and highly localized reactions. The proposed model accurately estimates the changes in solute concentrations due to homogenous and heterogeneous reactions during precipitation of minerals, observed in the pore-scale simulations, while conventional low-resolution advective-dispersion equations produced erroneous results.

Abstract-Strontium incorporation into calcite generated by bacterial ureolysis was investigated as part of an assessment of a proposed remediation approach for 90 Sr contamination in groundwater. Urea hydrolysis produces ammonium and carbonate and elevates pH, resulting in the promotion of calcium carbonate precipitation. Urea hydrolysis by the bacterium Bacillus pasteurii in a medium designed to mimic the chemistry of the Snake River Plain Aquifer in Idaho resulted in a pH rise from 7.5 to 9.1. Measured average distribution coefficients (D EX ) for Sr in the calcite produced by ureolysis (0.5) were up to an order of magnitude higher than values reported in the literature for natural and synthetic calcites (0.02-0.4). They were also higher than values for calcite produced abiotically by ammonium carbonate addition (0.3). The precipitation of calcite in these experiments was verified by X-ray diffraction. Time-of-flight secondary ion mass spectrometry (ToF SIMS) depth profiling (up to 350 nm) suggested that the Sr was not merely sorbed on the surface, but was present at depth within the particles. X-ray absorption near edge spectra showed that Sr was present in the calcite samples as a solid solution. The extent of Sr incorporation appeared to be driven primarily by the overall rate of calcite precipitation, where faster precipitation was associated with greater Sr uptake into the solid. The presence of bacterial surfaces as potential nucleation sites in the ammonium carbonate precipitation treatment did not enhance overall precipitation or the Sr distribution coefficient. Because bacterial ureolysis can generate high rates of calcite precipitation, the application of this approach is promising for remediation of 90 Sr contamination in environments where calcite is stable over the long term.

BackgroundA proposed strategy for immobilizing trace metals in the subsurface is to stimulate calcium carbonate precipitation and incorporate contaminants by co-precipitation. Such an approach will require injecting chemical amendments into the subsurface to generate supersaturated conditions that promote mineral precipitation. However, the formation of reactant mixing zones will create gradients in both the saturation state and ion activity ratios (i.e., aCO32MathClass-bin-MathClass-bin/aCa2MathClass-bin+). To better understand the effect of ion activity ratios on CaCO3 precipitation kinetics and Sr2+ co-precipitation, experiments were conducted under constant composition conditions where the supersaturation state (Ω) for calcite was held constant at 9.4, but the ion activity ratio (rMathClass-rel=aCO32MathClass-bin-MathClass-bin/aCa2MathClass-bin+) was varied between 0.0032 and 4.15.ResultsCalcite was the only phase observed, by XRD, at the end of the experiments. Precipitation rates increased from 41.3 ± 3.4 μmol m-2 min-1 at r = 0.0315 to a maximum rate of 74.5 ± 4.8 μmol m-2 min-1 at r = 0.306 followed by a decrease to 46.3 ± 9.6 μmol m-2 min-1 at r = 1.822. The trend was simulated using a simple mass transfer model for solute uptake at the calcite surface. However, precipitation rates at fixed saturation states also evolved with time. Precipitation rates accelerated for low r values but slowed for high r values. These trends may be related to changes in effective reactive surface area. The aCO32MathClass-bin-MathClass-bin/aCa2MathClass-bin+ ratios did not affect the distribution coefficient for Sr in calcite (DPSr2+), apart from the indirect effect associated with the established positive correlation between DPSr2+ and calcite precipitation rate.ConclusionAt a constant supersaturation state (Ω = 9.4), varying the ion activity ratio affects the calcite precipitation rate. This behavior is not predicted by affinity-based rate models. Furthermore, at the highest ion ratio tested, no precipitation was observed, while at the lowest ion ratio precipitation occurred immediately and valid rate measurements could not be made. The maximum measured precipitation rate was 2-fold greater than the minima, and occurred at a carbonate to calcium ion activity ratio of 0.306. These findings have implications for predicting the progress and cost of remediation operations involving enhanced calcite precipitation where mineral precipitation rates, and the spatial/temporal distribution of those rates, can have significant impacts on the mobility of contaminants.