[en] U(VI) adsorption by two aquifer sediment samples was studied under oxic conditions as a function of pH, U(VI), Ca, and dissolved carbonate concentration. Background-A (BKG-A) sediment was collected upstream of a former uranium mill-tailings site at Rifle, Colorado, and Little Rusty Composite (LRC) was collected on site but with low U contamination. Batch adsorption experiments were performed using artificial groundwater solutions prepared to simulate the field groundwater composition in equilibrium with specific partial pressures of carbon dioxide. To encompass the geochemical conditions of the alluvial aquifer at the site, the experimental conditions ranged from 6.8 x 10^-8 to 10^-5 M in [U(VI)]tot, 7.2 to 8.0 in pH, 3.0 x 10^-3 to 6.0 x 10^-3 M in [Ca²⁺], and 0.05 to 2.6% in partial pressure of carbon dioxide. The sediment was extracted with a dilute bicarbonate/carbonate solution to determine the background labile U(VI) already present in the sediment. A semi-empirical surface complexation model was developed to describe U(VI) adsorption using FITEQL4. The non-electrostatic, generalized composite surface complexation model successfully simulated U(VI) adsorption over the range of groundwater conditions at the Old Rifle site, using a two-site, two-reaction fitting scheme. The sensitivity of model parameters to background U(VI) concentration on the two samples was evaluated. U(VI) adsorption experiments were also performed using a sand fraction of BKG-A separated through repeated sonication and wet-sieving. Surface area normalized Kd for the bulk and sand fraction indicated similar reactivity for both. The surface complexation model developed in this work is expected to contribute to the prediction of fate and transport of U(VI) in the alluvial aquifer at the Old Rifle site, and to assist in the simulation of biostimulation field experiments performed at the site.

[en] CrunchClay reactive transport code was used to interpret through-diffusion data with a set of parameters, including the effective diffusion coefficient, clay porosity, and the radionuclide adsorption distribution coefficient (De - ε - K_D). We demonstrate that our modeling approach can accurately include and characterize the influence of unavoidable experimental biases on the estimation of diffusion parameters in the quantitative interpretation of diffusion experiment results. These biases include the effects of filters holding the solid sample in place, the variations in the constant concentration gradient across the diffusion cell due to sampling events, the impact of tubing/dead volumes on the estimation of diffusive fluxes and sample porosity, and the effects of O-ring-filter setups on the delivery of solutions to the clay packing. A freely available graphical user interface, CrunchEase, was created for the reactive transport code CrunchClay. CrunchEase supports the user by automating the creation of input files, the running of simulations, and the extraction and comparison of data and simulation results. Furthermore, the CrunchEase/CrunchClay package allows the user to simulate raw through-diffusion data, i.e. (radio)tracer concentrations and volumes in reservoirs directly without the need to convert experimental concentration data into diffusive flux values. This direct modeling of raw data is more accurate if tubing volumes and the time of reservoir sampling events are specifically included. CrunchEase makes it also possible to transition more easily from a De - ε - K_D modeling approach to a process-based understanding modeling approach. This is achieved by using the full capabilities of CrunchClay, which include surface complexation modeling and a multi-porosity description of the clay packing with charged diffuse layers. Overall, we believe that the development of the CrunchEase user interface will further facilitate the dialog between experimentalists and modelers on the most recent concepts applied to diffusion problems in clayey materials. This may ultimately lead to an improved decision-making process by radioactive waste agencies