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Development of a semi-quantitative risk assessment model for evaluating environmental threat posed by the three first EU watch-list pharmaceuticals to urban wastewater treatment plants: An Irish case…

Overview of attention for article published in Science of the Total Environment, June 2017
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Title
Development of a semi-quantitative risk assessment model for evaluating environmental threat posed by the three first EU watch-list pharmaceuticals to urban wastewater treatment plants: An Irish case study
Published in
Science of the Total Environment, June 2017
DOI 10.1016/j.scitotenv.2017.05.227
Pubmed ID
Authors

Alexandre Tahar, Erin Jo Tiedeken, Eoghan Clifford, Enda Cummins, Neil Rowan

Abstract

Contamination of receiving waters with pharmaceutical compounds is of pressing concern. This constitutes the first study to report on the development of a semi-quantitative risk assessment (RA) model for evaluating the environmental threat posed by three EU watch list pharmaceutical compounds namely, diclofenac, 17-beta-estradiol and 17-alpha-ethinylestradiol, to aquatic ecosystems using Irish data as a case study. This RA model adopts the Irish Environmental Protection Agency Source-Pathway-Receptor concept to define relevant parameters for calculating low, medium or high risk score for each agglomeration of wastewater treatment plant (WWTP), which include catchment, treatments, operational and management factors. This RA model may potentially be used on a national scale to (i) identify WWTPs that pose a particular risk as regards releasing disproportionally high levels of these pharmaceutical compounds, and (ii) help identify priority locations for introducing or upgrading control measures (e.g. tertiary treatment, source reduction). To assess risks for these substances of emerging concern, the model was applied to 16 urban WWTPs located in different regions in Ireland that were scored for the three different compounds and ranked as low, medium or high risk. As a validation proxy, this case study used limited monitoring data recorded at some these plants receiving waters. It is envisaged that this semi-quantitative RA approach may aid other EU countries investigate and screen for potential risks where limited measured or predicted environmental pollutant concentrations and/or hydrological data are available. This model is semi-quantitative, as other factors such as influence of climate change and drug usage or prescription data will need to be considered in a future point for estimating and predicting risks.

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The data shown below were collected from the profiles of 2 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 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 104 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 20%
Student > Ph. D. Student 19 18%
Student > Master 14 13%
Student > Bachelor 11 11%
Other 4 4%
Other 15 14%
Unknown 20 19%
Readers by discipline Count As %
Environmental Science 25 24%
Engineering 11 11%
Biochemistry, Genetics and Molecular Biology 8 8%
Social Sciences 5 5%
Pharmacology, Toxicology and Pharmaceutical Science 5 5%
Other 24 23%
Unknown 26 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 07 October 2017.
All research outputs
#16,725,651
of 25,382,440 outputs
Outputs from Science of the Total Environment
#18,284
of 29,635 outputs
Outputs of similar age
#199,475
of 328,359 outputs
Outputs of similar age from Science of the Total Environment
#242
of 420 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 29,635 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 35th percentile – i.e., 35% of its peers scored the same or lower than it.
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 328,359 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 420 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.