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Environmentally relevant chemical mixtures of concern in waters of United States tributaries to the Great Lakes

Overview of attention for article published in Integrated Environmental Assessment & Management, April 2018
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

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7 tweeters

Citations

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2 Dimensions

Readers on

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15 Mendeley
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Title
Environmentally relevant chemical mixtures of concern in waters of United States tributaries to the Great Lakes
Published in
Integrated Environmental Assessment & Management, April 2018
DOI 10.1002/ieam.4041
Pubmed ID
Authors

Sarah M Elliott, Mark E Brigham, Richard L Kiesling, Heiko L Schoenfuss, Zachary G Jorgenson

Abstract

The North American Great Lakes are a vital natural resource that provide fish and wildlife habitat, as well as drinking water and waste assimilation services for millions of people. Tributaries to the Great Lakes receive chemical inputs from various point and nonpoint sources, and thus are expected to have complex mixtures of chemicals. However, our understanding of the co-occurrence of specific chemicals in complex mixtures is limited. To better understand the occurrence of specific chemical mixtures in the US Great Lakes Basin, surface water from 24 US tributaries to the Laurentian Great Lakes was collected and analyzed for diverse suites of organic chemicals, primarily focused on chemicals of concern (e.g., pharmaceuticals, personal care products, fragrances). A total of 181 samples and 21 chemical classes were assessed for mixture compositions. Basin wide, 1664 mixtures occurred in at least 25% of sites. The most complex mixtures identified comprised 9 chemical classes and occurred in 58% of sampled tributaries. Pharmaceuticals typically occurred in complex mixtures, reflecting pharmaceutical-use patterns and wastewater facility outfall influences. Fewer mixtures were identified at lake or lake-influenced sites than at riverine sites. As mixture complexity increased, the probability of a specific mixture occurring more often than by chance greatly increased, highlighting the importance of understanding source contributions to the environment. This empirically based analysis of mixture composition and occurrence may be used to focus future sampling efforts or mixture toxicity assessments. Integr Environ Assess Manag 2018;00:000-000. © 2018 SETAC.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 4 27%
Student > Master 4 27%
Student > Doctoral Student 2 13%
Researcher 2 13%
Student > Ph. D. Student 1 7%
Other 2 13%
Readers by discipline Count As %
Unspecified 7 47%
Environmental Science 3 20%
Agricultural and Biological Sciences 2 13%
Engineering 2 13%
Social Sciences 1 7%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 28 July 2018.
All research outputs
#3,267,290
of 12,486,089 outputs
Outputs from Integrated Environmental Assessment & Management
#72
of 532 outputs
Outputs of similar age
#91,004
of 273,405 outputs
Outputs of similar age from Integrated Environmental Assessment & Management
#5
of 25 outputs
Altmetric has tracked 12,486,089 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 532 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done well, scoring higher than 86% 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 273,405 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.