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Global Maps of Groundwater Quality

Global analysis and prediction of arsenic in groundwater

Podgorski, J.; Berg, M. (2020) Global threat of arsenic in groundwater, Science, 368(6493), 845-850, doi:10.1126/science.aba1510, Institutional Repository

Global analysis and prediction of fluoride in groundwater

Podgorski, J.; Berg, M. (2022) Global analysis and prediction of fluoride in groundwater, Nature Communications, 13(1), 4232 (9 pp.), doi:10.1038/s41467-022-31940-x, Institutional Repository

Explore more global maps

Amini, M.; Abbaspour, K. C.; Berg, M.; Winkel, L.; Hug, S. J.; Hoehn, E.; Yang, H.; Johnson, C. A. (2008) Statistical modeling of global geogenic arsenic contamination in groundwater, Environmental Science and Technology, 42(10), 3669-3675, doi:10.1021/es702859e, Institutional Repository

Amini, M.; Mueller, K.; Abbaspour, K. C.; Rosenberg, T.; Afyuni, M.; Møller, K. N.; Sarr, M.; Johnson, C. A. (2008) Statistical modeling of global geogenic fluoride contamination in groundwaters, Environmental Science and Technology, 42(10), 3662-3668, doi:10.1021/es071958y, Institutional Repository

National Maps of Groundwater Quality

Fluoride contamination of groundwater resources in Ghana: Country-wide hazard modeling and estimated population at risk

Araya, D.; Podgorski, J.; Kumi, M.; Mainoo, P. A.; Berg, M. (2022) Fluoride contamination of groundwater resources in Ghana: country-wide hazard modeling and estimated population at risk, Water Research, 212, 118083 (10 pp.), doi:10.1016/j.watres.2022.118083, Institutional Repository

Groundwater Arsenic Distribution in India by Machine Learning Geospatial Modeling

Podgorski, J.; Wu, R.; Chakravorty, B.; Polya, D. A. (2020) Groundwater arsenic distribution in India by machine learning geospatial modeling, International Journal of Environmental Research and Public Health, 17(19), 7119 (17 pp.), doi:10.3390/ijerph17197119, Institutional Repository

Groundwater arsenic contamination throughout China

Rodríguez-Lado, L.; Sun, G.; Berg, M.; Zhang, Q.; Xue, H.; Zheng, Q.; Johnson, C. A. (2013) Groundwater arsenic contamination throughout China, Science, 341(6148), 866-868, doi:10.1126/science.1237484, Institutional Repository

Monitoring and prediction of high fluoride concentrations in groundwater in Pakistan

Ling, Y.; Podgorski, J.; Sadiq, M.; Rasheed, H.; Eqani, S. A. M. A. S.; Berg, M. (2022) Monitoring and prediction of high fluoride concentrations in groundwater in Pakistan, Science of the Total Environment, 839, 156058 (9 pp.), doi:10.1016/j.scitotenv.2022.156058, Institutional Repository

Groundwater arsenic contamination in Burkina Faso, West Africa: predicting and verifying regions at risk

Bretzler, A.; Lalanne, F.; Nikiema, J.; Podgorski, J.; Pfenninger, N.; Berg, M.; Schirmer, M. (2017) Groundwater arsenic contamination in Burkina Faso, West Africa: predicting and verifying regions at risk, Science of the Total Environment, 584, 958-970, doi:10.1016/j.scitotenv.2017.01.147, Institutional Repository

Local Maps of Groundwater Quality

Geogenic manganese and iron in groundwater of Southeast Asia and Bangladesh – Machine learning spatial prediction modeling and comparison with arsenic

Podgorski, J.; Araya, D.; Berg, M. (2022) Geogenic manganese and iron in groundwater of Southeast Asia and Bangladesh - machine learning spatial prediction modeling and comparison with arsenic, Science of the Total Environment, 833, 155131 (11 pp.), doi:10.1016/j.scitotenv.2022.155131, Institutional Repository

Predicting groundwater arsenic contamination in Southeast Asia from surface parameters

Winkel, L.; Berg, M.; Amini, M.; Hug, S. J.; Johnson, C. A. (2008) Predicting groundwater arsenic contamination in Southeast Asia from surface parameters, Nature Geoscience, 1, 536-542, doi:10.1038/ngeo254, Institutional Repository

Extensive arsenic contamination in high-pH unconfined aquifers in the Indus Valley

Podgorski, J. E.; Eqani, S. A. M. A. S.; Khanam, T.; Ullah, R.; Shen, H.; Berg, M. (2017) Extensive arsenic contamination in high-pH unconfined aquifers in the Indus Valley, Science Advances, 3(8), e1700935 (10 pp.), doi:10.1126/sciadv.1700935, Institutional Repository

 

 

 

 

Keywords

contamination, groundwater contamination, exposure, groundwater contaminants, predict groundwater contamination, geogenic, geogenic contamination, groundwater, mitigation, human health, exposure groundwater, affect human health, health risk, natural, models, predictions, communities, worlds population, pollutants, advances mitigation