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Predicting Geogenic Arsenic Contamination in Shallow Groundwater of South Louisiana, United States
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/bf01704667openalex-snapshot
Naturally occurring arsenic in groundwaters of the midwestern United States
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Spatial relationship of groundwater arsenic distribution with regional topography and water-table fluctuations in the shallow aquifers in Bangladesh
inferredcites →https://doi.org/10.1007/s10040-003-0314-0openalex-snapshot
Arsenic in groundwater of the Bengal Basin, Bangladesh: Distribution, field relations, and hydrogeological setting
inferredcites →https://doi.org/10.1016/j.apgeochem.2003.09.006openalex-snapshot
Arsenic enrichment in groundwater of the alluvial aquifers in Bangladesh: an overview
inferredcites →https://doi.org/10.1016/j.apgeochem.2004.02.001openalex-snapshot
Natural organic matter in sedimentary basins and its relation to arsenic in anoxic ground water: the example of West Bengal and its worldwide implications
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inferredcites →https://doi.org/10.1016/j.gca.2004.04.020openalex-snapshot
Mobility of arsenic in a Bangladesh aquifer: Inferences from geochemical profiles, leaching data, and mineralogical characterization
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Quaternary stratigraphy, sediment characteristics and geochemistry of arsenic-contaminated alluvial aquifers in the Ganges–Brahmaputra floodplain in central Bangladesh
inferredcites →https://doi.org/10.1016/j.jhydrol.2007.11.027openalex-snapshot
Inverse geochemical modeling of groundwater evolution with emphasis on arsenic in the Mississippi River Valley alluvial aquifer, Arkansas (USA)
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Is organic matter a source or redox driver or both for arsenic release in groundwater?
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A review of the source, behaviour and distribution of arsenic in natural waters
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Mechanism of arsenic release to groundwater, Bangladesh and West Bengal
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Modeling the Probability of Arsenic in Groundwater in New England as a Tool for Exposure Assessment
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Statistical Modeling of Global Geogenic Arsenic Contamination in Groundwater
inferredcites →https://doi.org/10.1029/2001wr000968openalex-snapshot
Geochemical study of arsenic release mechanisms in the Bengal Basin groundwater
inferredcites →https://doi.org/10.1029/2007wr006000openalex-snapshot
Impact of local recharge on arsenic concentrations in shallow aquifers inferred from the electromagnetic conductivity of soils in Araihazar, Bangladesh
inferredcites →https://doi.org/10.1029/2007wr006552openalex-snapshot
How paleosols influence groundwater flow and arsenic pollution: A model from the Bengal Basin and its worldwide implication
inferredcites →https://doi.org/10.1038/ngeo129openalex-snapshot
Mississippi Delta subsidence primarily caused by compaction of Holocene strata
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Predicting groundwater arsenic contamination in Southeast Asia from surface parameters
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Arsenic pollution of groundwater in Vietnam exacerbated by deep aquifer exploitation for more than a century
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Validating Regression Procedures With New Data
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Arsenic Exposure and Risk of Spontaneous Abortion, Stillbirth, and Infant Mortality
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Arsenic Epidemiology and Drinking Water Standards
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Microbial Mineral Weathering for Nutrient Acquisition Releases Arsenic
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Contributions of floodplain stratigraphy and evolution to the spatial patterns of groundwater arsenic in Araihazar, Bangladesh
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Arsenic Exposure and Motor Function among Children in Bangladesh
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Water Arsenic Exposure and Children’s Intellectual Function in Araihazar, Bangladesh
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Water Manganese Exposure and Children’s Intellectual Function in Araihazar, Bangladesh
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A Retrospective Analysis on the Occurrence of Arsenic in Ground-Water Resources of the United States and Limitations in Drinking-Water-Supply Characterizations
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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inferred← citeshttps://doi.org/10.1016/j.apgeochem.2016.09.005openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.apgeochem.2018.10.014openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.ejrh.2015.11.023openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.envc.2024.100898openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.gca.2018.11.008openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.gca.2019.07.032openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jclepro.2025.146605openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jhydrol.2018.03.007openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jhydrol.2021.125995openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jhydrol.2021.126214openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.scitotenv.2021.150496openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.scitotenv.2021.151461openalex-snapshot
Anthropogenic dominance on geogenic arsenic problem of the groundwater in the Ganga-Brahmaputra floodplain: A paradox of origin and mobilization
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2023.167202openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.scitotenv.2024.175896openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.watres.2016.01.023openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.watres.2019.04.054openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.watres.2021.117666openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/acs.est.0c03617openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/acs.est.1c08682openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/acs.est.4c01327openalex-snapshot
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inferred← citeshttps://doi.org/10.1029/2018wr023106openalex-snapshot
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inferred← citeshttps://doi.org/10.1029/2020wr029282openalex-snapshot
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inferred← citeshttps://doi.org/10.1038/s41598-020-72514-5openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/10106049.2022.2035830openalex-snapshot
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