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Effect-directed analysis supporting monitoring of aquatic environments — An in-depth overview

Overview of attention for article published in Science of the Total Environment, January 2016
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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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
4 X users

Citations

dimensions_citation
290 Dimensions

Readers on

mendeley
499 Mendeley
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Title
Effect-directed analysis supporting monitoring of aquatic environments — An in-depth overview
Published in
Science of the Total Environment, January 2016
DOI 10.1016/j.scitotenv.2015.11.102
Pubmed ID
Authors

Werner Brack, Selim Ait-Aissa, Robert M. Burgess, Wibke Busch, Nicolas Creusot, Carolina Di Paolo, Beate I. Escher, L. Mark Hewitt, Klara Hilscherova, Juliane Hollender, Henner Hollert, Willem Jonker, Jeroen Kool, Marja Lamoree, Matthias Muschket, Steffen Neumann, Pawel Rostkowski, Christoph Ruttkies, Jennifer Schollee, Emma L. Schymanski, Tobias Schulze, Thomas-Benjamin Seiler, Andrew J. Tindall, Gisela De Aragão Umbuzeiro, Branislav Vrana, Martin Krauss

Abstract

Aquatic environments are often contaminated with complex mixtures of chemicals that may pose a risk to ecosystems and human health. This contamination cannot be addressed with target analysis alone but tools are required to reduce this complexity and identify those chemicals that might cause adverse effects. Effect-directed analysis (EDA) is designed to meet this challenge and faces increasing interest in water and sediment quality monitoring. Thus, the present paper summarizes current experience with the EDA approach and the tools required, and provides practical advice on their application. The paper highlights the need for proper problem formulation and gives general advice for study design. As the EDA approach is directed by toxicity, basic principles for the selection of bioassays are given as well as a comprehensive compilation of appropriate assays, including their strengths and weaknesses. A specific focus is given to strategies for sampling, extraction and bioassay dosing since they strongly impact prioritization of toxicants in EDA. Reduction of sample complexity mainly relies on fractionation procedures, which are discussed in this paper, including quality assurance and quality control. Automated combinations of fractionation, biotesting and chemical analysis using so-called hyphenated tools can enhance the throughput and might reduce the risk of artifacts in laboratory work. The key to determining the chemical structures causing effects is analytical toxicant identification. The latest approaches, tools, software and databases for target-, suspect and non-target screening as well as unknown identification are discussed together with analytical and toxicological confirmation approaches. A better understanding of optimal use and combination of EDA tools will help to design efficient and successful toxicant identification studies in the context of quality monitoring in multiply stressed environments.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 499 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 <1%
Canada 2 <1%
Czechia 1 <1%
Indonesia 1 <1%
Iran, Islamic Republic of 1 <1%
Mexico 1 <1%
Unknown 491 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 106 21%
Researcher 90 18%
Student > Master 67 13%
Student > Doctoral Student 29 6%
Student > Bachelor 29 6%
Other 78 16%
Unknown 100 20%
Readers by discipline Count As %
Environmental Science 137 27%
Agricultural and Biological Sciences 51 10%
Chemistry 51 10%
Engineering 32 6%
Biochemistry, Genetics and Molecular Biology 14 3%
Other 68 14%
Unknown 146 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 08 November 2019.
All research outputs
#2,807,893
of 25,394,764 outputs
Outputs from Science of the Total Environment
#3,746
of 29,655 outputs
Outputs of similar age
#46,536
of 401,163 outputs
Outputs of similar age from Science of the Total Environment
#30
of 271 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 29,655 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 well, scoring higher than 87% 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 401,163 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 271 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.