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Cited by 908

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Groundwater Arsenic Contamination Throughout China

Open access
Rodríguez-Lado, Luis, Sun, Guifan, Berg, Michael, Zhang, Qiang, Xue, Hanbin, Zheng, Quanmei, Johnson, C. Annette·2013·Science

Abstract

Arsenic and Populace: The solubility of arsenic in groundwater aquifers is controlled by a number of hydrologic and geochemical factors. In rural communities that rely on groundwater for drinking water, the risk from exposure may pose a public health threat, especially when groundwater pumping can increase arsenic solubility. In an effort to provide a focused assessment of risk to arsenic exposure from groundwater, Rodríguez-Lado et al. (p. 866 ; see the Perspective by Michael ) constructed a geostatistical model that incorporates a number of factors that control arsenic solubility across China. Most of the risk centers in a few provinces—Xinjiang, Inner Mongolia, Henan, Shandong, and Jiangsu—but the total population exposed to arsenic levels above 10 micrograms per liter could be upwards of 19 million people.

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Crossref · 10.1126/science.1237484

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Metadata

Authors
Rodríguez-Lado, L., Sun, G., Berg, M., Zhang, Q., Xue, H., Zheng, Q., & Johnson, C. A.
Venue
Science
Published
2013-08-23
Volume
341
Issue
6148
Pages
866-868
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2070164699
Cited by
908
References
2
FWCI
42.12
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Groundwater Arsenic Contamination Throughout China. https://app.cochat.ai/papers/10.1126/science.1237484
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Rodríguez-Lado, L., Sun, G., Berg, M., Zhang, Q., Xue, H., Zheng, Q., & Johnson, C. A. (2013). Groundwater Arsenic Contamination Throughout China. Science. https://doi.org/10.1126/science.1237484

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.