Approaches to surface complexation modeling of Uranium(VI) adsorption on aquifer sediments
Dates
Year
2004
Citation
Davis, James A, Meece, David E, Kohler, Matthias, and Curtis, Gary P, 2004, Approaches to surface complexation modeling of Uranium(VI) adsorption on aquifer sediments: Geochimica et Cosmochimica Acta, v. 68, iss. 18, p. 3621-3641.
Summary
Uranium(VI) adsorption onto aquifer sediments was studied in batch experiments as a function of pH and U(VI) and dissolved carbonate concentrations in artificial groundwater solutions. The sediments were collected from an alluvial aquifer at a location upgradient of contamination from a former uranium mill operation at Naturita, Colorado (USA). The ranges of aqueous chemical conditions used in the U(VI) adsorption experiments (pH 6.9 to 7.9; U(VI) concentration 2.5 · 10−8 to 1 · 10−5 M; partial pressure of carbon dioxide gas 0.05 to 6.8%) were based on the spatial variation in chemical conditions observed in 1999–2000 in the Naturita alluvial aquifer. The major minerals in the sediments were quartz, feldspars, and calcite, with minor [...]
Summary
Uranium(VI) adsorption onto aquifer sediments was studied in batch experiments as a function of pH and U(VI) and dissolved carbonate concentrations in artificial groundwater solutions. The sediments were collected from an alluvial aquifer at a location upgradient of contamination from a former uranium mill operation at Naturita, Colorado (USA). The ranges of aqueous chemical conditions used in the U(VI) adsorption experiments (pH 6.9 to 7.9; U(VI) concentration 2.5 · 10−8 to 1 · 10−5 M; partial pressure of carbon dioxide gas 0.05 to 6.8%) were based on the spatial variation in chemical conditions observed in 1999–2000 in the Naturita alluvial aquifer. The major minerals in the sediments were quartz, feldspars, and calcite, with minor amounts of magnetite and clay minerals. Quartz grains commonly exhibited coatings that were greater than 10 nm in thickness and composed of an illite-smectite clay with occluded ferrihydrite and goethite nanoparticles. Chemical extractions of quartz grains removed from the sediments were used to estimate the masses of iron and aluminum present in the coatings. Various surface complexation modeling approaches were compared in terms of the ability to describe the U(VI) experimental data and the data requirements for model application to the sediments. Published models for U(VI) adsorption on reference minerals were applied to predict U(VI) adsorption based on assumptions about the sediment surface composition and physical properties (e.g., surface area and electrical double layer). Predictions from these models were highly variable, with results overpredicting or underpredicting the experimental data, depending on the assumptions used to apply the model. Although the models for reference minerals are supported by detailed experimental studies (and in ideal cases, surface spectroscopy), the results suggest that errors are caused in applying the models directly to the sediments by uncertain knowledge of: 1) the proportion and types of surface functional groups available for adsorption in the surface coatings; 2) the electric field at the mineral-water interface; and 3) surface reactions of major ions in the aqueous phase, such as Ca2+, Mg2+, HCO3−, SO42−, H4SiO4, and organic acids. In contrast, a semi-empirical surface complexation modeling approach can be used to describe the U(VI) experimental data more precisely as a function of aqueous chemical conditions. This approach is useful as a tool to describe the variation in U(VI) retardation as a function of chemical conditions in field-scale reactive transport simulations, and the approach can be used at other field sites. However, the semi-empirical approach is limited by the site-specific nature of the model parameters.
Added to ScienceBase on Fri Apr 19 11:15:14 MDT 2013 by processing file
<b>Multiphase Flow, Transport, Reaction, and Biodegradation.xml</b> in item
<a href="https://www.sciencebase.gov/catalog/item/51117dcfe4b03611765639d6">https://www.sciencebase.gov/catalog/item/51117dcfe4b03611765639d6</a>