↓ Skip to main content

Optimization of sampling strategy to determine pathogen removal efficacy of activated sludge treatment plant

Overview of attention for article published in Environmental Science & Pollution Research, June 2017
Altmetric Badge

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
14 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Optimization of sampling strategy to determine pathogen removal efficacy of activated sludge treatment plant
Published in
Environmental Science & Pollution Research, June 2017
DOI 10.1007/s11356-017-9557-5
Pubmed ID
Authors

Sidhu, Jatinder P. S., Ahmed, Warish, Palmer, Andrew, Smith, Kylie, Hodgers, Leonie, Toze, Simon

Abstract

Large-scale wastewater schemes rely on multi-barrier approach for the production of safe and sustainable recycled water. In multi-barrier wastewater reclamation systems, conventional activated sludge process (ASP) often constitutes a major initial treatment step. The main aim of this research was to determine most appropriate sampling approach to establish pathogen removal efficacy of ASP. The results suggest that ASP is capable of reducing human adenovirus (HAdV) and polyomavirus (HPyV) by up to 3 log10. The virus removal data suggests that HAdV removal is comparable to somatic bacteriophage belonging to Microviridae family. Due to the high removal of Escherichia coli (>3 log10) and very poor correlation with the enteric virus, it is not recommended that E. coli be used as a surrogate for enteric virus removal. The results also demonstrated no statistically significant differences (t test, P > 0.05) in calculated log removal values (LRVs) for HAdV, HPyV, and Microviridae from samples collected on hydraulic retention time (HRT) or simultaneous paired samples collected for influent and effluent. This indicates that a more practical approach of simultaneous sampling for influent and effluent could be used to determine pathogen removal efficiency of ASP. The results also suggest that a minimum of 10, preferably 20 samples, are required to fully capture variability in the removal of virus. In order to cover for the potential seasonal prevalence of viruses such as norovirus and rotavirus, sampling should be spread across all seasons.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 43%
Unspecified 2 14%
Student > Master 2 14%
Other 1 7%
Student > Ph. D. Student 1 7%
Other 2 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 29%
Unspecified 4 29%
Environmental Science 3 21%
Biochemistry, Genetics and Molecular Biology 1 7%
Medicine and Dentistry 1 7%
Other 1 7%

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 29 June 2017.
All research outputs
#10,128,051
of 11,410,328 outputs
Outputs from Environmental Science & Pollution Research
#1,889
of 2,888 outputs
Outputs of similar age
#218,963
of 260,942 outputs
Outputs of similar age from Environmental Science & Pollution Research
#114
of 187 outputs
Altmetric has tracked 11,410,328 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,888 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 1st percentile – i.e., 1% 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 260,942 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 187 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.