Project Summary (2012-2017)

Arsenic groundwater concentrations are determined in part by their sediment concentration but also by sediment mineralogy and the transformations that affect them. The first goal of the research led by Benjamin Bostick, Ph.D., and Brian Mailloux, Ph.D., is to examine the spatial distribution of aqueous As (and other analytes) within the comprehensive sampling efforts undertaken by other projects and Cores to link groundwater As levels to tangible aqueous and sediment properties (e.g., mineralogy, measured using state-of-the-art spectroscopic methods including Fe, As, and S X-ray spectroscopy) and the biological communities that transform them (with 16 rDNA community libraries and functional gene analysis). As part of this comprehensive effort, Bostick and Mailloux are characterizing the Fe, As and S phases that regulate dissolved As concentrations, identifying active redox processes in the aquifer that affect these phases and the bacteria that facilitate these processes, and determining which active carbon pools drive microbial respiration. The second overarching goal of this project is to examine the role of transformations in sediment mineralogy and aquifer geochemistry on arsenic levels. Within the simulated pond-village in Araihazar, and the Vineland Superfund Site, the researchers are studying the relationship between sediment mineralogy, redox status, microbial populations and arsenic levels, but are also monitoring how those and other parameters change over time in controlled laboratory experiments. These batch and column studies use natural sediments and probe the effect of perturbations of geochemical conditions on sediment biogeochemical processes, Fe, S and As mineralogies, and As geochemistry. These manipulations address the question of the effect of human activity on As contamination, and allow the researchers to examine the rates of relevant and fundamental environmental processes for the first time. The resulting data will then be used to develop and calibrate reactive transport models that more accurately capture the processes that affect As partitioning. These data also will be used to engineer improved remediation solutions at the Vineland Superfund site.