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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, December 2017
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Mentioned by

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2 tweeters

Citations

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18 Dimensions

Readers on

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74 Mendeley
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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, December 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.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 74 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 24%
Student > Ph. D. Student 15 20%
Student > Master 10 14%
Student > Bachelor 7 9%
Other 4 5%
Other 10 14%
Unknown 10 14%
Readers by discipline Count As %
Environmental Science 21 28%
Social Sciences 5 7%
Biochemistry, Genetics and Molecular Biology 5 7%
Engineering 5 7%
Psychology 4 5%
Other 20 27%
Unknown 14 19%

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
#9,529,079
of 15,557,767 outputs
Outputs from Science of the Total Environment
#8,775
of 14,355 outputs
Outputs of similar age
#151,927
of 280,275 outputs
Outputs of similar age from Science of the Total Environment
#77
of 151 outputs
Altmetric has tracked 15,557,767 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,355 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one is in the 36th percentile – i.e., 36% 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 280,275 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 151 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.