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Quantification of human-associated fecal indicators reveal sewage from urban watersheds as a source of pollution to Lake Michigan

Overview of attention for article published in Water Research, September 2016
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  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

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2 tweeters

Citations

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39 Dimensions

Readers on

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94 Mendeley
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Title
Quantification of human-associated fecal indicators reveal sewage from urban watersheds as a source of pollution to Lake Michigan
Published in
Water Research, September 2016
DOI 10.1016/j.watres.2016.05.056
Pubmed ID
Authors

Hayley A. Templar, Deborah K. Dila, Melinda J. Bootsma, Steven R. Corsi, Sandra L. McLellan

Abstract

Sewage contamination of urban waterways from sewer overflows and failing infrastructure is a major environmental and public health concern. Fecal coliforms (FC) are commonly employed as fecal indicator bacteria, but do not distinguish between human and non-human sources of fecal contamination. Human Bacteroides and human Lachnospiraceae, two genetic markers for human-associated indicator bacteria, were used to identify sewage signals in two urban rivers and the estuary that drains to Lake Michigan. Grab samples were collected from the rivers throughout 2012 and 2013 and hourly samples were collected in the estuary across the hydrograph during summer 2013. Human Bacteroides and human Lachnospiraceae were highly correlated with each other in river samples (Pearson's r = 0.86), with average concentrations at most sites elevated during wet weather. These human indicators were found during baseflow, indicating that sewage contamination is chronic in these waterways. FC are used for determining total maximum daily loads (TMDLs) in management plans; however, FC concentrations alone failed to prioritize river reaches with potential health risks. While 84% of samples with >1000 CFU/100 ml FC had sewage contamination, 52% of samples with moderate (200-1000 CFU/100 ml) and 46% of samples with low (<200 CFU/100 ml) FC levels also had evidence of human sewage. Load calculations in the in the Milwaukee estuary revealed storm-driven sewage contamination varied greatly among events and was highest during an event with a short duration of intense rain. This work demonstrates urban areas have unrecognized sewage inputs that may not be adequately prioritized for remediation by the TMDL process. Further analysis using these approaches could determine relationships between land use, storm characteristics, and other factors that drive sewage contamination in urban waterways.

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 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
United States 1 1%
Sweden 1 1%
Unknown 91 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 23 24%
Student > Ph. D. Student 16 17%
Researcher 13 14%
Student > Bachelor 9 10%
Student > Doctoral Student 6 6%
Other 14 15%
Unknown 13 14%
Readers by discipline Count As %
Environmental Science 30 32%
Agricultural and Biological Sciences 16 17%
Engineering 11 12%
Earth and Planetary Sciences 4 4%
Immunology and Microbiology 4 4%
Other 9 10%
Unknown 20 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 May 2017.
All research outputs
#7,667,622
of 12,269,818 outputs
Outputs from Water Research
#3,677
of 5,590 outputs
Outputs of similar age
#150,211
of 275,995 outputs
Outputs of similar age from Water Research
#59
of 140 outputs
Altmetric has tracked 12,269,818 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,590 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 28th percentile – i.e., 28% 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 275,995 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 140 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.