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Exploring the Potential of a Global Emerging Contaminant Early Warning Network through the Use of Retrospective Suspect Screening with High-Resolution Mass Spectrometry

Overview of attention for article published in Environmental Science & Technology, April 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

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3 news outlets
blogs
1 blog
twitter
25 X users
facebook
1 Facebook page

Citations

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101 Dimensions

Readers on

mendeley
153 Mendeley
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Title
Exploring the Potential of a Global Emerging Contaminant Early Warning Network through the Use of Retrospective Suspect Screening with High-Resolution Mass Spectrometry
Published in
Environmental Science & Technology, April 2018
DOI 10.1021/acs.est.8b00365
Pubmed ID
Authors

Nikiforos A. Alygizakis, Saer Samanipour, Juliane Hollender, María Ibáñez, Sarit Kaserzon, Varvara Kokkali, Jan A. van Leerdam, Jochen F. Mueller, Martijn Pijnappels, Malcolm J. Reid, Emma L. Schymanski, Jaroslav Slobodnik, Nikolaos S. Thomaidis, Kevin V. Thomas

Abstract

A key challenge in the environmental and exposure sciences is to establish experimental evidence of the role of chemical exposure in human and environmental systems. High resolution and accurate tandem mass spectrometry (HRMS) is increasingly being used for the analysis of environmental samples. One lauded benefit of HRMS is the possibility to retrospectively process data for (previously omitted) compounds that has led to the archiving of HRMS data. Archived HRMS data affords the possibility of exploiting historical data to rapidly and effectively establish the temporal and spatial occurrence of newly identified contaminants through retrospective suspect screening. We propose to establish a global emerging contaminant early warning network to rapidly assess the spatial and temporal distribution of contaminants of emerging concern in environmental samples through performing retrospective analysis on HRMS data. The effectiveness of such a network is demonstrated through a pilot study, where eight reference laboratories with available archived HRMS data retrospectively screened data acquired from aqueous environmental samples collected in 14 countries on 3 different continents. The widespread spatial occurrence of several surfactants (e.g., polyethylene glycols ( PEGs ) and C12AEO-PEGs ), transformation products of selected drugs (e.g., gabapentin-lactam, metoprolol-acid, carbamazepine-10-hydroxy, omeprazole-4-hydroxy-sulfide, and 2-benzothiazole-sulfonic-acid), and industrial chemicals (3-nitrobenzenesulfonate and bisphenol-S) was revealed. Obtaining identifications of increased reliability through retrospective suspect screening is challenging, and recommendations for dealing with issues such as broad chromatographic peaks, data acquisition, and sensitivity are provided.

X Demographics

X Demographics

The data shown below were collected from the profiles of 25 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 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 153 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 38 25%
Researcher 26 17%
Student > Master 23 15%
Student > Bachelor 10 7%
Professor 7 5%
Other 18 12%
Unknown 31 20%
Readers by discipline Count As %
Environmental Science 40 26%
Chemistry 33 22%
Engineering 8 5%
Agricultural and Biological Sciences 6 4%
Pharmacology, Toxicology and Pharmaceutical Science 3 2%
Other 14 9%
Unknown 49 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 45. 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 02 May 2022.
All research outputs
#929,962
of 25,411,814 outputs
Outputs from Environmental Science & Technology
#1,342
of 20,697 outputs
Outputs of similar age
#20,832
of 342,934 outputs
Outputs of similar age from Environmental Science & Technology
#23
of 251 outputs
Altmetric has tracked 25,411,814 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 20,697 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 93% 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 342,934 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 93% of its contemporaries.
We're also able to compare this research output to 251 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 90% of its contemporaries.