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Microbial risk assessment of drinking water based on hydrodynamic modelling of pathogen concentrations in source water

Overview of attention for article published in Science of the Total Environment, April 2015
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

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Title
Microbial risk assessment of drinking water based on hydrodynamic modelling of pathogen concentrations in source water
Published in
Science of the Total Environment, April 2015
DOI 10.1016/j.scitotenv.2015.04.040
Pubmed ID
Authors

Ekaterina Sokolova, Susan R. Petterson, Olaf Dienus, Fredrik Nyström, Per-Eric Lindgren, Thomas J.R. Pettersson

Abstract

Norovirus contamination of drinking water sources is an important cause of waterborne disease outbreaks. Knowledge on pathogen concentrations in source water is needed to assess the ability of a drinking water treatment plant (DWTP) to provide safe drinking water. However, pathogen enumeration in source water samples is often not sufficient to describe the source water quality. In this study, the norovirus concentrations were characterised at the contamination source, i.e. in sewage discharges. Then, the transport of norovirus within the water source (the river Göta älv in Sweden) under different loading conditions was simulated using a hydrodynamic model. Based on the estimated concentrations in source water, the required reduction of norovirus at the DWTP was calculated using quantitative microbial risk assessment (QMRA). The required reduction was compared with the estimated treatment performance at the DWTP. The average estimated concentration in source water varied between 4.8×10(2) and 7.5×10(3) genome equivalents L(-1); and the average required reduction by treatment was between 7.6 and 8.8 Log10. The treatment performance at the DWTP was estimated to be adequate to deal with all tested loading conditions, but was heavily dependent on chlorine disinfection, with the risk of poor reduction by conventional treatment and slow sand filtration. To our knowledge, this is the first article to employ discharge-based QMRA, combined with hydrodynamic modelling, in the context of drinking water.

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The data shown below were collected from the profiles of 2 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 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 <1%
United States 1 <1%
Unknown 112 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 30%
Student > Master 18 16%
Researcher 14 12%
Professor 7 6%
Student > Doctoral Student 5 4%
Other 15 13%
Unknown 21 18%
Readers by discipline Count As %
Engineering 28 25%
Environmental Science 16 14%
Agricultural and Biological Sciences 14 12%
Immunology and Microbiology 4 4%
Medicine and Dentistry 4 4%
Other 15 13%
Unknown 33 29%
Attention Score in Context

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 01 January 2016.
All research outputs
#7,975,082
of 25,411,814 outputs
Outputs from Science of the Total Environment
#10,400
of 29,716 outputs
Outputs of similar age
#88,916
of 279,343 outputs
Outputs of similar age from Science of the Total Environment
#55
of 171 outputs
Altmetric has tracked 25,411,814 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 29,716 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 gotten more attention than average, scoring higher than 64% 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 279,343 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 67% of its contemporaries.
We're also able to compare this research output to 171 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 66% of its contemporaries.