Contaminant removal and contaminant dispersion of air distribution for overall and local airborne infection risk controls.
Sci Total Environ
; 833: 155173, 2022 Aug 10.
Article
in English
| MEDLINE | ID: covidwho-1783747
ABSTRACT
Proper air distribution is crucial for airborne infection risk control of infectious respiratory diseases like COVID-19. Existing studies evaluate and compare the performances of different air distributions for airborne infection risk control, but the mechanisms of air distribution for airborne infection risk control remain unclear. This study investigates the mechanisms of air distribution for both overall and local airborne infection risk controls. The experimentally validated CFD models simulate the contaminant concentration fields in a hospital ward based on which the airborne infection risks of COVID-19 are evaluated with the dilution-based expansion of the Wells-Riley model. Different air distributions, i.e., stratum ventilation, displacement ventilation, and mixing ventilation, with various supply airflow rates are tested. The results show that the variations of the overall and local airborne infection risks under different air distributions and different supply airflow rates are complicated and non-linear. The contaminant removal and the contaminant dispersion are proposed as the mechanisms for the overall and local airborne infection risk controls, respectively, regardless of airflow distributions and supply airflow rates. A large contaminant removal ability benefits the overall airborne infection risk control, with the coefficient of determination of 0.96 between the contaminant removal index and the reciprocal of the overall airborne infection risk. A large contaminant dispersion ability benefits the local airborne infection risk control, with the coefficient of determination of 0.99 between the contaminant dispersion index and the local airborne infection risk.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Air Pollution, Indoor
/
COVID-19
Type of study:
Experimental Studies
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Sci Total Environ
Year:
2022
Document Type:
Article
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