Evidence map›Paper›PMID 33051848›Full record

ArticleEnvironmental science and pollution research international2021

Quantitative microbial risk assessment of bioaerosols in a wastewater treatment plant by using two aeration modes.

Cheng Yan, Zi-Cheng Gui, Jun-Ting Wu

Abstract read
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Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Cheng YanSchool of Environmental Studies, China University of Geosciences, 388 Lumo Road, Wuhan, 430074, People's Republic of China. cheng_yan@cug.edu.cn.
Zi-Cheng GuiSchool of Environmental Studies, China University of Geosciences, 388 Lumo Road, Wuhan, 430074, People's Republic of China.
Jun-Ting WuSchool of Environmental Studies, China University of Geosciences, 388 Lumo Road, Wuhan, 430074, People's Republic of China.

Funding

Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) CUGL170409, CUG170103, CUGGC07National Natural Science Foundation of China (CN) 5160849Program of Geological Processes Resources and Environment in the Yangtze Basin CUGCJ1702the Major Science and Technology Program for Water Pollution Control and Treatment 2018ZX07110004the Special Fund from the State Key Joint Laboratory of Environment Simulation and Pollution Control (Research Center for Eco-environmental Sciences, Chinese Academy of Sciences) 18K03ESPCR
6 · The paper itself

Abstract

Nonnegligible emission of bioaerosols usually occurs during aeration of wastewater in aerator tanks in wastewater treatment plants (WWTPs). Literature had shown that the respiratory and intestinal diseases of workers at WWTPs are related to bioaerosols. Thus, quantitative microbial risk assessment (QMRA) based on Monte Carlo simulation was utilized in this research to assess the health risks of Gram-negative bacteria bioaerosol (GNBB) and Staphylococcus aureus bioaerosol (SAB) among academic visitors and staffs. Results showed that the concentrations of GNBB and SAB in the inverted umbrella aeration mode were consistently higher than those in the microporous aeration mode under all six size distribution ranges of the Anderson six-stage impactor. Thus, GNBB and SAB can be highly threatening to the weasand and first bronchus (or alveoli and third bronchus) for the exposure populations. The health risks (annual probability of infection (P

Indexed as

Air MicrobiologyWater PurificationAerosolsHumansRisk AssessmentWastewaterAerosolsWastewaterAnnual probability of infectionBioaerosolDisease burdenMonte Carlo simulationQuantitative microbial risk assessmentWastewater treatment plant

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.