↓ Skip to main content

Arsenic contamination of drinking water in Ireland: A spatial analysis of occurrence and potential risk

Overview of attention for article published in Science of the Total Environment, December 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
2 news outlets
twitter
3 X users

Citations

dimensions_citation
56 Dimensions

Readers on

mendeley
125 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Arsenic contamination of drinking water in Ireland: A spatial analysis of occurrence and potential risk
Published in
Science of the Total Environment, December 2016
DOI 10.1016/j.scitotenv.2016.11.171
Pubmed ID
Authors

Ellen R. McGrory, Colin Brown, Norma Bargary, Natalya Hunter Williams, Anthony Mannix, Chaosheng Zhang, Tiernan Henry, Eve Daly, Sarah Nicholas, Barbara M. Petrunic, Monica Lee, Liam Morrison

Abstract

The presence of arsenic in groundwater has become a global concern due to the health risks from drinking water with elevated concentrations. The Water Framework Directive (WFD) of the European Union calls for drinking water risk assessment for member states. The present study amalgamates readily available national and sub-national scale datasets on arsenic in groundwater in the Republic of Ireland. However, due to the presence of high levels of left censoring (i.e. arsenic values below an analytical detection limit) and changes in detection limits over time, the application of conventional statistical methods would inhibit the generation of meaningful results. In order to handle these issues several arsenic databases were integrated and the data modelled using statistical methods appropriate for non-detect data. In addition, geostatistical methods were used to assess principal risk components of elevated arsenic related to lithology, aquifer type and groundwater vulnerability. Geographic statistical methods were used to overcome some of the geographical limitations of the Irish Environmental Protection Agency (EPA) sample database. Nearest-neighbour inverse distance weighting (IDW) and local indicator of spatial association (LISA) methods were used to estimate risk in non-sampled areas. Significant differences were also noted between different aquifer lithologies, indicating that Rhyolite, Sandstone and Shale (Greywackes), and Impure Limestone potentially presented a greater risk of elevated arsenic in groundwaters. Significant differences also occurred among aquifer types with poorly productive aquifers, locally important fractured bedrock aquifers and regionally important fissured bedrock aquifers presenting the highest potential risk of elevated arsenic. No significant differences were detected among different groundwater vulnerability groups as defined by the Geological Survey of Ireland. This research will assist management and future policy directions of groundwater resources at EU level and guide future research focused on understanding arsenic mobilisation processes to facilitate in guiding future development, testing and treatment requirements of groundwater resources.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Argentina 1 <1%
Unknown 124 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 20%
Researcher 16 13%
Student > Master 16 13%
Student > Doctoral Student 9 7%
Other 8 6%
Other 19 15%
Unknown 32 26%
Readers by discipline Count As %
Environmental Science 23 18%
Engineering 14 11%
Agricultural and Biological Sciences 13 10%
Chemistry 12 10%
Earth and Planetary Sciences 5 4%
Other 13 10%
Unknown 45 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 14 June 2017.
All research outputs
#1,754,717
of 25,373,627 outputs
Outputs from Science of the Total Environment
#2,338
of 29,625 outputs
Outputs of similar age
#34,337
of 420,272 outputs
Outputs of similar age from Science of the Total Environment
#35
of 309 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 29,625 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done particularly well, scoring higher than 92% 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 420,272 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 91% of its contemporaries.
We're also able to compare this research output to 309 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.