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. 2017 Nov 7;51(21):12443-12454.
doi: 10.1021/acs.est.7b02881. Epub 2017 Oct 18.

Estimating the High-Arsenic Domestic-Well Population in the Conterminous United States

Joseph D Ayotte  1 , Laura Medalie  2 , Sharon L Qi  3 , Lorraine C Backer  4 , Bernard T Nolan  5
Affiliations

Estimating the High-Arsenic Domestic-Well Population in the Conterminous United States

Joseph D Ayotte et al. Environ Sci Technol. .

Abstract

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.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1.
Figure 1.
Locations of domestic wells and As concentration ranges for data used to develop the logistic regression model.
Figure 2.
Figure 2.
Probabilities of (a) arsenic >10 μg/L (b) 95-percent confidence lower bound for arsenic >10 μg/L; and (c) 95-percent confidence upper bound for arsenic >10 μg/L.
Figure 3.
Figure 3.
County-level (a) domestic well population and (b) domestic well population with As > 10 μg/L based on probability estimates.
Figure 4.
Figure 4.
State populations and percent of state populations with arsenic >10 μg/L based on the probability modeling.
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