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Title: Development of Surface Complexation Models of Cr(VI) Adsorption on Soils, Sediments and Model Mixtures of Kaolinite, Montmorillonite, γ-Alumina, Hydrous Manganese and Ferric Oxides and Goethite

Hexavalent chromium is a highly toxic contaminant that has been introduced into aquifers and shallow sediments and soils via many anthropogenic activities. Hexavalent chromium contamination is a problem or potential problem in the shallow subsurface at several DOE sites, including Hanford, Idaho National Laboratory, Los Alamos National Laboratory and the Oak Ridge Reservation (DOE, 2008). To accurately quantify the fate and transport of hexavalent chromium at DOE and other contaminated sites, robust geochemical models, capable of correctly predicting changes in chromium chemical form resulting from chemical reactions occurring in subsurface environments are needed. One important chemical reaction that may greatly impact the bioavailability and mobility of hexavalent chromium in the subsurface is chemical binding to the surfaces of particulates, termed adsorption or surface complexation. Quantitative thermodynamic surface complexation models have been derived that can correctly calculate hexavalent chromium adsorption on well-characterized materials over ranges in subsurface conditions, such pH and salinity. However, models have not yet been developed for hexavalent chromium adsorption on many important constituents of natural soils and sediments, such as clay minerals. Furthermore, most of the existing thermodynamic models have been developed for relatively simple, single solid systems and have rarely been tested for the complex mixturesmore » of solids present in real sediments and soils. In this study, the adsorption of hexavalent chromium was measured as a function of pH (3-10), salinity (0.001 to 0.1 M NaNO3), and partial pressure of carbon dioxide(0-5%) on a suite of naturally-occurring solids including goethite (FeOOH), hydrous manganese oxide (MnOOH), hydrous ferric oxide (Fe(OH)3), γ-alumina (Al2O3), kaolinite (Al2Si2O5(OH)4), and montmorillonite (Na3(Al, Mg)2Si4O10(OH)2-nH2O). The results show that all of these materials can bind substantial quantities of hexavalent chromium, especially at low pH. Unexpectedly, experiments with the clay minerals kaolinite and montmorillonite suggest that hexavalent chromium may interact with these solids over much longer periods of time than expected. Furthermore, hexavalent chromium may irreversibly bind to these solids, perhaps because of oxidation-reduction reactions occurring on the surfaces of the clay minerals. More work should be done to investigate and quantify these chemical reactions. Experiments conducted with mixtures of goethite, hydrous manganese oxide, hydrous ferric oxide, γ-alumina, montmorillonite and kaolinite demonstrate that it is possible to correctly predict hexavalent chromium binding in the presence of multiple minerals using thermodynamic models derived for the simpler systems. Further, these models suggest that of the six solid considered in this study, goethite is typically the solid to which most of the hexavalent chromium will bind. Experiments completed with organic-rich and organic-poor natural sediments demonstrate that in organic-rich substrates, organic matter is likely to control uptake of the hexavalent chromium. The models derived and tested in this study for hexavalent chromium binding to γ-alumina, hydrous manganese oxide, goethite, hydrous ferric oxide and clay minerals can be used to better predict changes in hexavalent chromium bioavailability and mobility in contaminated sediments and soils.« less
  1. Western Michigan University
Publication Date:
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Technical Report
Research Org:
Western Michigan University
Sponsoring Org:
USDOE SC Office of Biological and Environmental Research (SC-23)
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; 36 MATERIALS SCIENCE; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY Hexavalent chromium; surface complexation model; component additivity