Numerical Modeling of Arsenic Mobility during Reductive Iron-Mineral Transformations.

Environ Sci Technol

Earth System Science Department, Stanford University, Stanford, California 94305, United States.

Published: March 2016

Millions of individuals worldwide are chronically exposed to hazardous concentrations of arsenic from contaminated drinking water. Despite massive efforts toward understanding the extent and underlying geochemical processes of the problem, numerical modeling and reliable predictions of future arsenic behavior remain a significant challenge. One of the key knowledge gaps concerns a refined understanding of the mechanisms that underlie arsenic mobilization, particularly under the onset of anaerobic conditions, and the quantification of the factors that affect this process. In this study, we focus on the development and testing of appropriate conceptual and numerical model approaches to represent and quantify the reductive dissolution of iron oxides, the concomitant release of sorbed arsenic, and the role of iron-mineral transformations. The initial model development in this study was guided by data and hypothesized processes from a previously reported,1 well-controlled column experiment in which arsenic desorption from ferrihydrite coated sands by variable loads of organic carbon was investigated. Using the measured data as constraints, we provide a quantitative interpretation of the processes controlling arsenic mobility during the microbial reductive transformation of iron oxides. Our analysis suggests that the observed arsenic behavior is primarily controlled by a combination of reductive dissolution of ferrihydrite, arsenic incorporation into or co-precipitation with freshly transformed iron minerals, and partial arsenic redox transformations.

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http://dx.doi.org/10.1021/acs.est.5b05956DOI Listing

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