Using Geological Facies to Estimate Chromate Sorption to Soils

摘要

Quantifying the extent to which contaminant metals bind to subsurface soils is important for risk assessment, the tendency for a contaminant to migrate, and developing environmental remediation strategies. Unfortunately, subsurface soils vary widely in their composition, which in turn affect their tendency to bind metals. The hypothesis of this study was predicated on how a better understanding of geological facies would reduce uncertainty associated with predicting contaminant metal sorption. Facies are layers of sediment deposited in the subsurface due to similar depositional conditions, including energy of an overlying waterway. As such, facies are expected to have similar assemblages of minerals, particle size distributions, origins of organic matter, and similar microbial population structures. These are all important factors affecting contaminant metal sorption. The approach of this study was to collect 42 composite soil samples from a 5 m by 1.5 m grid outcrop in Graniteville, South Carolina and five end-member facies samples. The fraction of each of the five facies comprising the 42 composite soil samples were estimated. Particle size distribution (gravel, sand, silt, and clay fractions), pH, organic matter (OM), iron coating content, and microbial colony forming units were determined for each composite soil and the five end-member facies soils. Because hexavalent chromium (Cr) is the most common contaminant metal in the U.S. to exceed drinking water limits, this highly toxic and soluble metal was used as a model contaminant to provide a measure of contaminant sorption. Chromium distribution coefficients (Kd = Crsoil/Crwater) were measured. Significant correlations were identified between several soil chemical and microbial properties. A significant correlation (r = 0.423; p ≤ 0.05, d.f. = 47) was also determined between measured Kd values and Kd values calculated based on knowledge of facies Kd values. Importantly, the calculated values were characterized by large amount of inherent error. Additional work is needed to determine the applicability of this approach for remediation of contaminated sites and how best to identify appropriate facies for this novel application.