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砷污染环境中铁氧化还原转化的含水层尺度观测以预测未来污染

Aquifer-Scale Observations of Iron Redox Transformations in Arsenic-Impacted Environments to Predict Future Contamination.

作者信息

Nghiem Athena A, Shen Yating, Stahl Mason, Sun Jing, Haque Ezazul, DeYoung Beck, Nguyen Khue N, Mai Tran Thi, Trang Pham Thi Kim, Pham Hung Viet, Mailloux Brian, Harvey Charles F, van Geen Alexander, Bostick Benjamin C

机构信息

Department of Earth and Environmental Sciences and Lamont-Doherty Earth Observatory, Columbia University, New York, New York 10027, United States.

Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York 10964, United States; National Research Center of Geoanalysis, Chinese Academy of Geological Sciences, Beijing, China.

出版信息

Environ Sci Technol Lett. 2020 Dec 8;7(12):916-922. doi: 10.1021/acs.estlett.0c00672. Epub 2020 Sep 30.

Abstract

Iron oxides control the mobility of a host of contaminants in aquifer systems, and the microbial reduction of iron oxides in the subsurface is linked to high levels of arsenic in groundwater that affects greater than 150 million people globally. Paired observations of groundwater and solid-phase aquifer composition are critical to understand spatial and temporal trends in contamination and effectively manage changing water resources, yet field-representative mineralogical data are sparse across redox gradients relevant to arsenic contamination. We characterize iron mineralogy using X-ray absorption spectroscopy across a natural gradient of groundwater arsenic contamination in Vietnam. Hierarchical cluster analysis classifies sediments into meaningful groups delineating weathering and redox changes, diagnostic of depositional history, in this first direct characterization of redox transformations in the field. Notably, these groupings reveal a signature of iron minerals undergoing active reduction before the onset of arsenic contamination in groundwater. Pleistocene sediments undergoing postdepositional reduction may be more extensive than previously recognized due to previous misclassification. By upscaling to similar environments in South and Southeast Asia via multinomial logistic regression modeling, we show that active iron reduction, and therefore susceptibility to future arsenic contamination, is more widely distributed in presumably pristine aquifers than anticipated.

摘要

氧化铁控制着含水层系统中大量污染物的迁移,而地下氧化铁的微生物还原与地下水中的高砷含量有关,全球超过1.5亿人受到影响。对地下水和固相含水层成分进行配对观测对于了解污染的时空趋势以及有效管理不断变化的水资源至关重要,然而,在与砷污染相关的氧化还原梯度上,具有现场代表性的矿物学数据却很稀少。我们利用X射线吸收光谱法对越南地下水砷污染的自然梯度上的铁矿物学进行了表征。层次聚类分析将沉积物分类为有意义的组,描绘了风化和氧化还原变化,这是对该领域氧化还原转变的首次直接表征,可诊断沉积历史。值得注意的是,这些分组揭示了在地下水砷污染开始之前,铁矿物正在经历主动还原的特征。由于之前的错误分类,经历沉积后还原的更新世沉积物可能比之前认为的更为广泛。通过多项式逻辑回归模型将其扩展到南亚和东南亚的类似环境,我们表明,活性铁还原以及因此对未来砷污染的敏感性,在可能原本未受污染的含水层中的分布比预期更为广泛。

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