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

Overview of attention for article published in Environmental Science & Technology, October 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

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23 news outlets
blogs
3 blogs
twitter
38 X users
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6 Facebook pages

Citations

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179 Dimensions

Readers on

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197 Mendeley
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Title
Estimating the High-Arsenic Domestic-Well Population in the Conterminous United States
Published in
Environmental Science & Technology, October 2017
DOI 10.1021/acs.est.7b02881
Pubmed ID
Authors

Joseph D. Ayotte, Laura Medalie, Sharon L. Qi, Lorraine C. Backer, Bernard T. Nolan

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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X Demographics

The data shown below were collected from the profiles of 38 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 197 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 197 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 19%
Student > Master 27 14%
Researcher 24 12%
Student > Bachelor 18 9%
Student > Doctoral Student 13 7%
Other 30 15%
Unknown 48 24%
Readers by discipline Count As %
Environmental Science 37 19%
Engineering 25 13%
Earth and Planetary Sciences 17 9%
Agricultural and Biological Sciences 9 5%
Chemistry 8 4%
Other 38 19%
Unknown 63 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 216. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 October 2022.
All research outputs
#182,068
of 25,707,225 outputs
Outputs from Environmental Science & Technology
#275
of 21,019 outputs
Outputs of similar age
#3,726
of 337,553 outputs
Outputs of similar age from Environmental Science & Technology
#8
of 238 outputs
Altmetric has tracked 25,707,225 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 21,019 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.8. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 337,553 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 238 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.