title: Predicting the risk of arsenic contaminated groundwater in Shanxi Province, Northern China.
abstract: Shanxi Province is one of the regions in northern China where endemic arsenicosis occurs. In this study, stepwise logistic regression was applied to analyze the statistical relationships of a dataset of arsenic (As) concentrations in groundwaters with some environmental explanatory parameters. Finally, a 2D spatial model showing the potential As-affected areas in this province was created. We identified topography, gravity, hydrologic parameters and remote sensing information as explanatory variables with high potential to predict high As risk areas. The model identifies correctly the already known endemic areas of arsenism. We estimate that the area at risk exceeding 10 μg L(-1) As occupies approximately 8,100 km(2) in 30 counties in the province.
authors.affiliation: Department of Occupational and Environmental Health, College of Public Health, China Medical University, No. 92 Bei Er Road, Heping District, 110001 Shenyang, China.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Zhang
authors.forename: Luis
authors.initials: L
authors.lastname: Rodríguez-Lado
authors.forename: C Annette
authors.initials: CA
authors.lastname: Johnson
authors.forename: Hanbin
authors.initials: H
authors.lastname: Xue
authors.forename: Jianbo
authors.initials: J
authors.lastname: Shi
authors.forename: Quanmei
authors.initials: Q
authors.lastname: Zheng
authors.forename: Guifan
authors.initials: G
authors.lastname: Sun
mesh_terms: D002681:China; D004784:Environmental Monitoring; D060587:Groundwater / Q000737:chemistry*; D016015:Logistic Models; D008956:Models, Chemical; D018570:Risk Assessment; D014874:Water Pollutants, Chemical / Q000032:analysis*; D014877:Water Pollution, Chemical / Q000706:statistics & numerical data*
chemical_list: D014874:Water Pollutants, Chemical