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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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
24 news outlets
blogs
3 blogs
twitter
38 tweeters
facebook
6 Facebook pages

Citations

dimensions_citation
91 Dimensions

Readers on

mendeley
122 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.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 122 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 24%
Student > Master 20 16%
Researcher 17 14%
Student > Bachelor 14 11%
Student > Doctoral Student 7 6%
Other 16 13%
Unknown 19 16%
Readers by discipline Count As %
Environmental Science 31 25%
Engineering 19 16%
Earth and Planetary Sciences 9 7%
Agricultural and Biological Sciences 6 5%
Chemistry 6 5%
Other 24 20%
Unknown 27 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 225. 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 04 June 2021.
All research outputs
#101,464
of 19,023,266 outputs
Outputs from Environmental Science & Technology
#138
of 17,857 outputs
Outputs of similar age
#3,284
of 334,761 outputs
Outputs of similar age from Environmental Science & Technology
#7
of 249 outputs
Altmetric has tracked 19,023,266 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 17,857 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.3. This one has done particularly well, scoring higher than 99% 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 334,761 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 99% of its contemporaries.
We're also able to compare this research output to 249 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 97% of its contemporaries.