Transient zonal modeling of SARS-CoV-2 airborne infection risk for incomplete mixing air distribution methods
17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022
; 2022.
Article
Dans Anglais
| Scopus | ID: covidwho-2321198
ABSTRACT
A widely used analytical model to quantitatively assess airborne infection risk is the Wells-Riley model based on the assumption of complete air mixing in a single zone. This study aimed to extend the Wells-Riley model so that the infection risk can be calculated in spaces where complete mixing is not present. This is done by evaluating the time-dependent distribution of infectious quanta in each zone and by solving the coupled system of differential equations based on the zonal quanta concentrations. In conclusion, this study shows that using the Wells-Riley model based on the assumption of completely mixing air may overestimate the long-range airborne infection risk compared to some high-efficiency ventilation systems such as displacement ventilation, but also underestimate the infection risk in a room heated with warm air supplied from the ceiling. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
Air distribution method; Infection risk; SARS-CoV-2; Virus airborne transmission; Zonal modeling; Air quality; Climate models; Differential equations; Indoor air pollution; Mixing; Risk assessment; Risk perception; Transmissions; Ventilation; Air distribution; Air mixing; Airborne infection; Airborne transmission; Incomplete mixing; Model-based OPC; Zonal model; Coronavirus
Collection:
Bases de données des oragnisations internationales
Base de données:
Scopus
Type d'étude:
Études expérimentales
/
Étude pronostique
langue:
Anglais
Revue:
17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022
Année:
2022
Type de document:
Article
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