Redox processes in Earth’s subsurface interact in complex ways that are greatly affected by hydrological, mineralogical and biogeochemical factors. Our research explores the scales of environmental variability in redox processes from the lab to the field; we are especially interested in data-driven and statistical approaches to better understand and especially quantify these factors. Currently, we study how these factors interact in the subsurface to drive the naturally-occurring release of toxic arsenic and other trace elements into groundwater. Next, we are interested in investigating currently-used mitigation strategies that re-distribute contaminants in the environment.
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DeltAs Project
We are happy to be part of a Swiss National Science Foundation funded project with collaborators in Switzerland (ETH Zurich, University of Zurich, University of Neuchatel) and in Vietnam entitled “Evaluating delta-wide changes in geogenic arsenic (As) contamination under anthropogenic pressures: An integrated approach to assess groundwater vulnerability in Vietnam (DeltAs)”. For more information, visit the DeltAs project main website.
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Reactive Transport Modeling
With Prof. Henning Prommer at Commonwealth Scientific and Industrial Research Organisation (CSIRO) & University of Western Australia, we developed a biogeochemical reaction network and reactive transport model to simulate the infiltration of arsenic-contaminated water into uncontaminated aquifers. We found that uncontaminated and presumably safe-guarded aquifers, which contain abundant oxidized Fe minerals, may be contaminated with arsenic more quickly than expected due to sulfur processes and the formation of highly mobile thiolated arsenic species (Nghiem et al. 2023, Nature Water). Our work was covered by a News and Views article (Planer-Friedrich 2023, Nature Water).
Iron Mineralogy
Contamination of groundwater by toxic arsenic is pervasive across South and Southeast Asia, yet the iron mineralogy associated with and often responsible for the release of arsenic remains poorly investigated. We used statistical methods such as hierarchical cluster analysis on an extensive data set of X-ray absorption spectroscopy measurements to reveal signatures of iron mineral reduction that could lead to future arsenic release. We also showed that the extent of previously pristine aquifers that have been contaminated may have been misclassified and thus underrepresented (Nghiem et al. 2020, Environmental Science & Technology Letters).
Groundwater Recharge
From a regional survey in the Red River Delta, Vietnam, we used an ensemble approach to an end-member mixing model and quantified fraction of different recharge sources into an aquifer based on stable water isotopes. These fraction of recharge sources can then be statistically compared to geochemical parameters, showing that aquifers with high riverine recharge have high dissolved arsenic concentrations without high dissolved organic carbon (Nghiem et al. 2019, Water Resources Research).
