Estimating the high-arsenic domestic-well population in the conterminous United States

Environmental Science & Technology
By: , and 



Arsenic concentrations from 20 450 domestic wells in the U.S. were used to develop a logistic regression model of the probability of having arsenic >10 μg/L (“high arsenic”), which is presented at the county, state, and national scales. Variables representing geologic sources, geochemical, hydrologic, and physical features were among the significant predictors of high arsenic. For U.S. Census blocks, the mean probability of arsenic >10 μg/L was multiplied by the population using domestic wells to estimate the potential high-arsenic domestic-well population. Approximately 44.1 M people in the U.S. use water from domestic wells. The population in the conterminous U.S. using water from domestic wells with predicted arsenic concentration >10 μg/L is 2.1 M people (95% CI is 1.5 to 2.9 M). Although areas of the U.S. were underrepresented with arsenic data, predictive variables available in national data sets were used to estimate high arsenic in unsampled areas. Additionally, by predicting to all of the conterminous U.S., we identify areas of high and low potential exposure in areas of limited arsenic data. These areas may be viewed as potential areas to investigate further or to compare to more detailed local information. Linking predictive modeling to private well use information nationally, despite the uncertainty, is beneficial for broad screening of the population at risk from elevated arsenic in drinking water from private wells.

Study Area

Publication type Article
Publication Subtype Journal Article
Title Estimating the high-arsenic domestic-well population in the conterminous United States
Series title Environmental Science & Technology
DOI 10.1021/acs.est.7b02881
Volume 51
Issue 21
Year Published 2017
Language English
Publisher American Chemical Society
Contributing office(s) New England Water Science Center
Description 12 p.
First page 12443
Last page 12454
Country United States
Google Analytic Metrics Metrics page
Additional publication details