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Sulfate reduction accelerates groundwater arsenic contamination even in aquifers with abundant iron oxides

Nature Water volume 1, pages 151–165 (2023)Cite this article

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Abstract

Groundwater contamination by geogenic arsenic is a global problem affecting nearly 200 million people. In South and Southeast Asia, a cost-effective mitigation strategy is to use oxidized low-arsenic aquifers rather than reduced high-arsenic aquifers. Aquifers with abundant oxidized iron minerals are presumably safeguarded against immediate arsenic contamination, due to strong sorption of arsenic onto iron minerals. However, preferential pumping of low-arsenic aquifers can destabilize the boundaries between these aquifers, pulling high-arsenic water into low-arsenic aquifers. We investigate this scenario in a hybrid field-column experiment in Bangladesh where naturally high-arsenic groundwater is pumped through sediment cores from a low-arsenic aquifer, and detailed aqueous and solid-phase measurements are used to constrain reactive transport modelling. Here we show that elevated groundwater arsenic concentrations are induced by sulfate reduction and the predicted formation of highly mobile, poorly sorbing thioarsenic species. This process suggests that contamination of currently pristine aquifers with arsenic can occur up to over 1.5 times faster than previously thought, leading to a deterioration of urgently needed water resources.

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Fig. 1: Time series of measured effluent groundwater composition (that is, from the column outlet, represented by circles) compared with model fits including all biogeochemical reactions (‘full model’), without thioarsenic species (‘no thioAs’) and IRB only (‘IRB only’).
Fig. 2: Observations of solid-phase Fe and solid-phase As, as measured by XAS and represented as fractions of the total Fe or As, compared with full model results.
Fig. 3: Biogeochemical reaction network of major processes related to Fe, As and sulfur cycling included in the full model and corresponding numerical implementation.
Fig. 4: In space (normalized column length on y axis) and time (PV, on x axis), decrease in sulfate concentrations leads to production of sulfide and the heterogeneous formation of thioarsenic species.
Fig. 5: The end of our experiment coincides with the points of reported higher concentrations of monothioarsenate measured from groundwater in an aquifer setting in the field.

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Data availability

The column transport parameters and geochemical solute data for the influent groundwater and all column effluent used for modelling have been previously published and can be found in Mozumder et al.29. The solid-phase data for the unaltered sediment can also be found in Mozumder et al.29. The mineralogy data at the end of the experiment for the Pleistocene columns are in Supplementary Tables 1 and 2. The normalized XAS spectra and standards used for both Fe EXAFS and As XANES are also available in in the additional Supplementary Information files. The data compilation of groundwater in Bangladesh is a subset of data publicly available at https://doi.org/10.7916/d8-zenj-yx36.

Code availability

ORTi3D was used for the initial model construction and manual model development and calibration phase (https://orti3d.ensegid.fr/). ORTi3D is an open source software that is a graphical user interface for the public domain codes MODFLOW78, MT3DMS81 and PHT3D79. MODFLOW is available from the United States Geological Survey (USGS) at https://www.usgs.gov/software/software-modflow, and PHT3D is available from www.phtd.org. PEST++ for model calibration is also publicly available (https://github.com/usgs/pestpp). Finally, the input data files for the reactive transport model are publicly available at https://doi.org/10.7916/945c-9w77.

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Acknowledgements

The experimental study was supported by the US National Institute of Environmental Health Sciences (NIEHS) grants ES0101349, ES009089 (B.C.B and A.v.G.) and P42ES033719 (B.C.B. and H.P.), US National Science Foundation (NSF) grant 1521356 (B.C.B. and A.v.G.) and US Department of Energy (DOE) grant EE0009596 (B.C.B. and H.P.). The computational modelling work was supported by an NSF Graduate Research Opportunities Worldwide (GROW) grant awarded to A.A.N. to conduct research in Western Australia. A.A.N. was also funded by an NSF Graduate Research Fellowship (NSF grant 1644869). Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, is supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences under contract no. DE-AC02-76SF00515. Computing resources, including high-performance computing, were provided by CSIRO Australia. The data for part of this work were compiled as a part of the Characterizing Global Variability in Groundwater Arsenic Working Group supported by the John Wesley Powell Center for Analysis and Synthesis, funded by the US Geological Survey. We also thank M. Selim, M. Atikul Islam, E. Shoenfelt Troein, T. Ellis, B. Mailloux and I. Choudhury for their contributions to the original experimental work. We also thank M. Stahl and D. Postma for their useful discussions.

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Author notes

  1. Athena A. Nghiem

    Present address: Institute of Biogeochemistry and Pollutant Dynamics, Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland

  2. Athena A. Nghiem

    Present address: Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland

Authors and Affiliations

  1. Department of Earth and Environmental Sciences, Columbia University, New York, NY, USA

    Athena A. Nghiem & M. Rajib H. Mozumder

  2. Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA

    Athena A. Nghiem, M. Rajib H. Mozumder, Alexander van Geen & Benjamin C. Bostick

  3. CSIRO Environment, Wembley, Western Australia, Australia

    Henning Prommer, Adam Siade & James Jamieson

  4. School of Earth Sciences, University of Western Australia, Perth, Western Australia, Australia

    Henning Prommer, Adam Siade & James Jamieson

  5. Ramboll Environment & Health, Westford, MA, USA

    M. Rajib H. Mozumder

  6. Department of Geology, University of Dhaka, Dhaka, Bangladesh

    Kazi Matin Ahmed

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Contributions

A.A.N., H.P. and B.C.B. conceived the reactive transport modelling work based off the column experiment work conceived by M.R.H.M., A.v.G. and B.C.B. The field work and column experiment work were performed by M.R.H.M., B.C.B. and K.M.A.; M.R.H.M. measured and provided data from the column experiment work. A.A.N. and H.P. performed the flow and reactive transport modelling. A.A.N., H.P., J.J. and B.C.B. contributed to the conceptual models underlying the numerical models. A.A.N. performed data curation, data visualization, analysis and model calibration of the reactive transport modelling results. H.P., A.S. and J.J. also contributed to the methodology, software/computing resources, model calibration and validation of the reactive transport modelling. A.S. also performed model sensitivity analysis. A.A.N. provided funding acquisition for the reactive transport modelling work; B.C.B. and A.v.G. provided funding acquisition for the column experiment and field work. A.A.N., H.P. and B.C.B. wrote and prepared the original manuscript, and all authors contributed to the review and editing of the manuscript.

Corresponding authors

Correspondence to Athena A. Nghiem or Benjamin C. Bostick.

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Nature Water thanks Rasmus Jakobsen, Britta Planer-Friedrich and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Information

Supplementary text, Figs. 1–15, Tables 1–9 and references.

Reporting Summary

Supplementary Data 1

Directory containing normalized Fe EXAFS and As XANES spectra.

Supplementary Data 2

Excel file containing root mean squared error for all models.

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Nghiem, A.A., Prommer, H., Mozumder, M.R.H. et al. Sulfate reduction accelerates groundwater arsenic contamination even in aquifers with abundant iron oxides. Nat Water 1, 151–165 (2023). https://doi.org/10.1038/s44221-022-00022-z

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