Characterizing global variability in groundwater arsenic
Groundwater contaminated with naturally occurring arsenic is a widespread problem affecting many alluvial and deltaic aquifer systems throughout the world. The human health toll from consuming groundwater with high levels of arsenic is staggering in its proportions. Furthermore, the use of arsenic contaminated groundwater for irrigation is observed to result in diminished crop yields and thus poses a threat to food security in arsenic affected regions. Decades of research at individual field sites have resulted in the collection of many geochemical and geologic datasets. A key feature of alluvial and deltaic aquifer systems is the large degree of spatial variability in groundwater arsenic concentrations from local to regional scales. While research has identified many processes that affect arsenic concentrations at individual sites, we are presently unable to explain how these processes interact to create the observed local to regional to global variability. To take understanding and prediction of current and future arsenic concentrations to the next level, a more holistic set of hypotheses must be developed, and this can only be achieved by integrating the large number of individual datasets and evaluating them together. Regional statistical analyses have been conducted to predict regional vulnerability, but these have been based on small geochemical datasets and therefore cannot be used to infer large-scale processes to explain variability. We propose to compile, for the first time, the many existing geochemical, hydrologic and geologic datasets for aquifer systems throughout the world into a single database with a consistent format. Geochemical, hydrological, geostatistical and geospatial analysis of this dataset will be used to generate testable hypotheses that explain the current distribution of groundwater arsenic concentrations and enable more comprehensive prediction of future evolution in deltaic and alluvial aquifers throughout the world.
Publications:
Athena A. Nghiem, Yating Shen, Mason Stahl, Jing Sun, Ezazul Haque, Beck DeYoung, Khue N. Nguyen, Tran Thi Mai, Pham Thi Kim Trang, Hung Viet Pham, Brian Mailloux, Charles F. Harvey, Alexander van Geen, and Benjamin C. Bostick. Environmental Science & Technology Letters 2020 7 (12), 916-922. DOI: 10.1021/acs.estlett.0c00672
Catherine M. Bulka, Molly Scannell Bryan, Melissa A. Lombard, Scott M. Bartell, Daniel K. Jones, Paul M. Bradley, Veronica M. Vieira, Debra T. Silverman, Michael Focazio, Patricia L. Toccalino, Johnni Daniel, Lorraine C. Backer, Joseph D. Ayotte, Matthew O. Gribble, Maria Argos, Arsenic in private well water and birth outcomes in the United States,
Environment International, Volume 163, 2022, 107176, ISSN 0160-4120, https://doi.org/10.1016/j.envint.2022.107176. (https://www.sciencedirect.com/science/article/pii/S0160412022001027)
Erickson, M.L., Hill, E.R., and Wilson, J.T., 2020, Arsenic, manganese, and pH groundwater quality data, selected well construction characteristics, and aquifer assignments for wells in the conterminous U.S.: U.S. Geological Survey data release, https://doi.org/10.5066/P9JMUAPY.
Stahl, Mason O., Jaclyn Gehring, and Yusuf Jameel. “Isotopic Variation in Groundwater across the Conterminous US – Insight into Hydrologic Processes.” Hydrological Processes n/a, no. n/a. Accessed June 4, 2020. https://doi.org/10.1002/hyp.13832.
Principal Investigators:
Mason Stahl (Union College)
Benjamin C Bostick (Lamont-Doherty Earth Observatory)
Melinda Erickson (USGS - Upper Midwest Water Science Center)
Holly Michael (University of Delaware)
Participants:
Kirk Nordstrom (USGS)
Andrea Foster (USGS)
Laura Erban (US EPA Office of Research and Development)
Charles Harvey (Massachusetts Institute of Technology)
Alexander van Geen (Columbia University)
Athena Anh-Thu Nghiem (Columbia University)
Yusuf Jameel (Massachusetts Institute of Technology)
Scott Fendorf (Stanford University)
Henning Prommer (University of Western Australia)
Lenny Winkel (ETH Zürich)
Clifford I Voss (USGS - Branch of Regional Research, Western Region)
- Source: USGS Sciencebase (id: 5b16fe3ae4b092d9651fcc5e)
Groundwater contaminated with naturally occurring arsenic is a widespread problem affecting many alluvial and deltaic aquifer systems throughout the world. The human health toll from consuming groundwater with high levels of arsenic is staggering in its proportions. Furthermore, the use of arsenic contaminated groundwater for irrigation is observed to result in diminished crop yields and thus poses a threat to food security in arsenic affected regions. Decades of research at individual field sites have resulted in the collection of many geochemical and geologic datasets. A key feature of alluvial and deltaic aquifer systems is the large degree of spatial variability in groundwater arsenic concentrations from local to regional scales. While research has identified many processes that affect arsenic concentrations at individual sites, we are presently unable to explain how these processes interact to create the observed local to regional to global variability. To take understanding and prediction of current and future arsenic concentrations to the next level, a more holistic set of hypotheses must be developed, and this can only be achieved by integrating the large number of individual datasets and evaluating them together. Regional statistical analyses have been conducted to predict regional vulnerability, but these have been based on small geochemical datasets and therefore cannot be used to infer large-scale processes to explain variability. We propose to compile, for the first time, the many existing geochemical, hydrologic and geologic datasets for aquifer systems throughout the world into a single database with a consistent format. Geochemical, hydrological, geostatistical and geospatial analysis of this dataset will be used to generate testable hypotheses that explain the current distribution of groundwater arsenic concentrations and enable more comprehensive prediction of future evolution in deltaic and alluvial aquifers throughout the world.
Publications:
Athena A. Nghiem, Yating Shen, Mason Stahl, Jing Sun, Ezazul Haque, Beck DeYoung, Khue N. Nguyen, Tran Thi Mai, Pham Thi Kim Trang, Hung Viet Pham, Brian Mailloux, Charles F. Harvey, Alexander van Geen, and Benjamin C. Bostick. Environmental Science & Technology Letters 2020 7 (12), 916-922. DOI: 10.1021/acs.estlett.0c00672
Catherine M. Bulka, Molly Scannell Bryan, Melissa A. Lombard, Scott M. Bartell, Daniel K. Jones, Paul M. Bradley, Veronica M. Vieira, Debra T. Silverman, Michael Focazio, Patricia L. Toccalino, Johnni Daniel, Lorraine C. Backer, Joseph D. Ayotte, Matthew O. Gribble, Maria Argos, Arsenic in private well water and birth outcomes in the United States,
Environment International, Volume 163, 2022, 107176, ISSN 0160-4120, https://doi.org/10.1016/j.envint.2022.107176. (https://www.sciencedirect.com/science/article/pii/S0160412022001027)
Erickson, M.L., Hill, E.R., and Wilson, J.T., 2020, Arsenic, manganese, and pH groundwater quality data, selected well construction characteristics, and aquifer assignments for wells in the conterminous U.S.: U.S. Geological Survey data release, https://doi.org/10.5066/P9JMUAPY.
Stahl, Mason O., Jaclyn Gehring, and Yusuf Jameel. “Isotopic Variation in Groundwater across the Conterminous US – Insight into Hydrologic Processes.” Hydrological Processes n/a, no. n/a. Accessed June 4, 2020. https://doi.org/10.1002/hyp.13832.
Principal Investigators:
Mason Stahl (Union College)
Benjamin C Bostick (Lamont-Doherty Earth Observatory)
Melinda Erickson (USGS - Upper Midwest Water Science Center)
Holly Michael (University of Delaware)
Participants:
Kirk Nordstrom (USGS)
Andrea Foster (USGS)
Laura Erban (US EPA Office of Research and Development)
Charles Harvey (Massachusetts Institute of Technology)
Alexander van Geen (Columbia University)
Athena Anh-Thu Nghiem (Columbia University)
Yusuf Jameel (Massachusetts Institute of Technology)
Scott Fendorf (Stanford University)
Henning Prommer (University of Western Australia)
Lenny Winkel (ETH Zürich)
Clifford I Voss (USGS - Branch of Regional Research, Western Region)
- Source: USGS Sciencebase (id: 5b16fe3ae4b092d9651fcc5e)