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Arsenic and other geogenic contaminants in global groundwater
Mukherjee, A., Coomar, P., Sarkar, S., Johannesson, K. H., Fryar, A. E., Schreiber, M. E., … Vengosh, A. (2024). Arsenic and other geogenic contaminants in global groundwater. Nature Reviews Earth & Environment. https://doi.org/10.1038/s43017-024-00519-z
Groundwater salinity in the Horn of Africa: spatial prediction modeling and estimated people at risk
Araya, D., Podgorski, J., & Berg, M. (2023). Groundwater salinity in the Horn of Africa: spatial prediction modeling and estimated people at risk. Environment International, 176, 107925 (12 pp.). https://doi.org/10.1016/j.envint.2023.107925
A global perspective on assessing groundwater quality
Misstear, B., Vargas, C. R., Lapworth, D., Ouedraogo, I., & Podgorski, J. (2023). A global perspective on assessing groundwater quality. Hydrogeology Journal, 31(1), 11-14. https://doi.org/10.1007/s10040-022-02461-0
Second-generation global risk map of groundwater arsenic contamination
Podgorski, J., & Berg, M. (2023). Second-generation global risk map of groundwater arsenic contamination. In A. van der Wal, A. Ahmad, B. Petrusevski, J. Weijma, D. Savic, P. van der Wens, … R. Naidu (Eds.), Arsenic in the environment. Proceedings. Proceedings of the 8th international congress and exhibition on arsenic in the environment (As2021) (pp. 3-4). https://doi.org/10.1201/9781003317395-1
Gaseous and soil OCPs and PCBs along the Indus River, Pakistan: spatial patterns and air-soil gradients
Sohail, M., Eqani, S. A. M. A. S., Ilyas, S., Bokhari, H., Ali, N., Podgorski, J. E., … Lohmann, R. (2023). Gaseous and soil OCPs and PCBs along the Indus River, Pakistan: spatial patterns and air-soil gradients. Environmental Science: Processes and Impacts, 25(3), 531-541. https://doi.org/10.1039/d2em00363e
Pseudo contour maps from logistic regression modelling: case study of groundwater arsenic distribution in Gujarat state, India
Wu, R., Podgorski, J., Berg, M., & Polya, D. A. (2023). Pseudo contour maps from logistic regression modelling: case study of groundwater arsenic distribution in Gujarat state, India. In A. van der Wal, A. Ahmad, B. Petrusevski, J. Weijma, D. Savic, P. van der Wens, … R. Naidu (Eds.), Arsenic in the environment. Proceedings. Proceedings of the 8th international congress and exhibition on arsenic in the environment (As2021) (pp. 95-96). https://doi.org/10.1201/9781003317395-40
Chromium contamination in paddy soil-rice systems and associated human health risks in Pakistan
Ali, W., Zhang, H., Mao, K., Shafeeque, M., Aslam, M. W., Yang, X., … Podgorski, J. (2022). Chromium contamination in paddy soil-rice systems and associated human health risks in Pakistan. Science of the Total Environment, 826, 153910 (12 pp.). https://doi.org/10.1016/j.scitotenv.2022.153910
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.). https://doi.org/10.1016/j.watres.2022.118083
How widespread is fluoride contamination of Ghana's groundwater?
Araya, D., Podgorski, J., & Berg, M. (2022). How widespread is fluoride contamination of Ghana's groundwater? Water Science Policy (4 pp.). https://doi.org/10.53014/OGJS9699
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.). https://doi.org/10.1016/j.scitotenv.2022.156058
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.). https://doi.org/10.1016/j.scitotenv.2022.155131
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.). https://doi.org/10.1038/s41467-022-31940-x
Freely dissolved organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) along the Indus River Pakistan: spatial pattern and risk assessment
Sohail, M., Ali Musstjab Akber Shah Eqani, S., Bokhari, H., Zaffar Hashmi, M., Ali, N., Alamdar, A., … Lohmann, R. (2022). Freely dissolved organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) along the Indus River Pakistan: spatial pattern and risk assessment. Environmental Science and Pollution Research, 29(43), 65670-65683. https://doi.org/10.1007/s11356-022-20418-4
A critical review on the occurrence and distribution of the uranium- and thorium-decay nuclides and their effect on the quality of groundwater
Vengosh, A., Coyte, R. M., Podgorski, J., & Johnson, T. M. (2022). A critical review on the occurrence and distribution of the uranium- and thorium-decay nuclides and their effect on the quality of groundwater. Science of the Total Environment, 808, 151914 (23 pp.). https://doi.org/10.1016/j.scitotenv.2021.151914
Human arsenic exposure risk via crop consumption and global trade from groundwater-irrigated areas
Alam, M. F., Villholth, K. G., & Podgorski, J. (2021). Human arsenic exposure risk via crop consumption and global trade from groundwater-irrigated areas. Environmental Research Letters, 16(12), 124013 (18 pp.). https://doi.org/10.1088/1748-9326/ac34bb
Characterization, geostatistical modeling and health risk assessment of potentially toxic elements in groundwater resources of northeastern Iran
Joodavi, A., Aghlmand, R., Podgorski, J., Dehbandi, R., & Abbasi, A. (2021). Characterization, geostatistical modeling and health risk assessment of potentially toxic elements in groundwater resources of northeastern Iran. Journal of Hydrology: Regional Studies, 37, 100885 (15 pp.). https://doi.org/10.1016/j.ejrh.2021.100885
Geostatistical model of the spatial distribution of arsenic in groundwaters in Gujarat State, India
Wu, R., Podgorski, J., Berg, M., & Polya, D. A. (2021). Geostatistical model of the spatial distribution of arsenic in groundwaters in Gujarat State, India. Environmental Geochemistry and Health, 43, 2649-2664. https://doi.org/10.1007/s10653-020-00655-7
A global-scale dataset of direct natural groundwater recharge rates: a review of variables, processes and relationships
Moeck, C., Grech-Cumbo, N., Podgorski, J., Bretzler, A., Gurdak, J. J., Berg, M., & Schirmer, M. (2020). A global-scale dataset of direct natural groundwater recharge rates: a review of variables, processes and relationships. Science of the Total Environment, 717, 137042 (19 pp.). https://doi.org/10.1016/j.scitotenv.2020.137042
Global threat of arsenic in groundwater
Podgorski, J., & Berg, M. (2020). Global threat of arsenic in groundwater. Science, 368(6493), 845-850. https://doi.org/10.1126/science.aba1510
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.). https://doi.org/10.3390/ijerph17197119