Risk of SARS‐CoV‐2 in a car cabin assessed through 3D CFD simulations

In this study, the risk of infection from SARS‐CoV‐2 Delta variant of passengers sharing a car cabin with an infected subject for a 30‐min journey is estimated through an integrated approach combining a recently developed predictive emission‐to‐risk approach and a validated CFD numerical model numer...

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Vydané v:Indoor air Ročník 32; číslo 3; s. e13012 - n/a
Hlavní autori: Arpino, Fausto, Grossi, Giorgio, Cortellessa, Gino, Mikszewski, Alex, Morawska, Lidia, Buonanno, Giorgio, Stabile, Luca
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England John Wiley & Sons, Inc 01.03.2022
John Wiley and Sons Inc
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ISSN:0905-6947, 1600-0668, 1600-0668
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Abstract In this study, the risk of infection from SARS‐CoV‐2 Delta variant of passengers sharing a car cabin with an infected subject for a 30‐min journey is estimated through an integrated approach combining a recently developed predictive emission‐to‐risk approach and a validated CFD numerical model numerically solved using the open‐source OpenFOAM software. Different scenarios were investigated to evaluate the effect of the infected subject position within the car cabin, the airflow rate of the HVAC system, the HVAC ventilation mode, and the expiratory activity (breathing vs. speaking). The numerical simulations here performed reveal that the risk of infection is strongly influenced by several key parameters: As an example, under the same ventilation mode and emitting scenario, the risk of infection ranges from zero to roughly 50% as a function of the HVAC flow rate. The results obtained also demonstrate that (i) simplified zero‐dimensional approaches limit proper evaluation of the risk in such confined spaces, conversely, (ii) CFD approaches are needed to investigate the complex fluid dynamics in similar indoor environments, and, thus, (iii) the risk of infection in indoor environments characterized by fixed seats can be in principle controlled by properly designing the flow patterns of the environment.
AbstractList In this study, the risk of infection from SARS‐CoV‐2 Delta variant of passengers sharing a car cabin with an infected subject for a 30‐min journey is estimated through an integrated approach combining a recently developed predictive emission‐to‐risk approach and a validated CFD numerical model numerically solved using the open‐source OpenFOAM software. Different scenarios were investigated to evaluate the effect of the infected subject position within the car cabin, the airflow rate of the HVAC system, the HVAC ventilation mode, and the expiratory activity (breathing vs. speaking). The numerical simulations here performed reveal that the risk of infection is strongly influenced by several key parameters: As an example, under the same ventilation mode and emitting scenario, the risk of infection ranges from zero to roughly 50% as a function of the HVAC flow rate. The results obtained also demonstrate that (i) simplified zero‐dimensional approaches limit proper evaluation of the risk in such confined spaces, conversely, (ii) CFD approaches are needed to investigate the complex fluid dynamics in similar indoor environments, and, thus, (iii) the risk of infection in indoor environments characterized by fixed seats can be in principle controlled by properly designing the flow patterns of the environment.
In this study, the risk of infection from SARS-CoV-2 Delta variant of passengers sharing a car cabin with an infected subject for a 30-min journey is estimated through an integrated approach combining a recently developed predictive emission-to-risk approach and a validated CFD numerical model numerically solved using the open-source OpenFOAM software. Different scenarios were investigated to evaluate the effect of the infected subject position within the car cabin, the airflow rate of the HVAC system, the HVAC ventilation mode, and the expiratory activity (breathing vs. speaking). The numerical simulations here performed reveal that the risk of infection is strongly influenced by several key parameters: As an example, under the same ventilation mode and emitting scenario, the risk of infection ranges from zero to roughly 50% as a function of the HVAC flow rate. The results obtained also demonstrate that (i) simplified zero-dimensional approaches limit proper evaluation of the risk in such confined spaces, conversely, (ii) CFD approaches are needed to investigate the complex fluid dynamics in similar indoor environments, and, thus, (iii) the risk of infection in indoor environments characterized by fixed seats can be in principle controlled by properly designing the flow patterns of the environment.In this study, the risk of infection from SARS-CoV-2 Delta variant of passengers sharing a car cabin with an infected subject for a 30-min journey is estimated through an integrated approach combining a recently developed predictive emission-to-risk approach and a validated CFD numerical model numerically solved using the open-source OpenFOAM software. Different scenarios were investigated to evaluate the effect of the infected subject position within the car cabin, the airflow rate of the HVAC system, the HVAC ventilation mode, and the expiratory activity (breathing vs. speaking). The numerical simulations here performed reveal that the risk of infection is strongly influenced by several key parameters: As an example, under the same ventilation mode and emitting scenario, the risk of infection ranges from zero to roughly 50% as a function of the HVAC flow rate. The results obtained also demonstrate that (i) simplified zero-dimensional approaches limit proper evaluation of the risk in such confined spaces, conversely, (ii) CFD approaches are needed to investigate the complex fluid dynamics in similar indoor environments, and, thus, (iii) the risk of infection in indoor environments characterized by fixed seats can be in principle controlled by properly designing the flow patterns of the environment.
Author Morawska, Lidia
Arpino, Fausto
Cortellessa, Gino
Grossi, Giorgio
Buonanno, Giorgio
Stabile, Luca
Mikszewski, Alex
AuthorAffiliation 1 Department of Civil and Mechanical Engineering University of Cassino and Southern Lazio Cassino FR Italy
2 International Laboratory for Air Quality and Health Queensland University of Technology Brisbane Queensland Australia
AuthorAffiliation_xml – name: 2 International Laboratory for Air Quality and Health Queensland University of Technology Brisbane Queensland Australia
– name: 1 Department of Civil and Mechanical Engineering University of Cassino and Southern Lazio Cassino FR Italy
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  email: l.stabile@unicas.it
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Issue 3
Keywords risk of infection
SARS-CoV-2
CFD analysis
respiratory particles
car cabin
virus transmission
Language English
License 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.
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PublicationTitle Indoor air
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Snippet In this study, the risk of infection from SARS‐CoV‐2 Delta variant of passengers sharing a car cabin with an infected subject for a 30‐min journey is estimated...
In this study, the risk of infection from SARS-CoV-2 Delta variant of passengers sharing a car cabin with an infected subject for a 30-min journey is estimated...
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StartPage e13012
SubjectTerms Air flow
Automobiles
car cabin
CFD analysis
Computational fluid dynamics
Computer Simulation
Confined spaces
COVID-19 - etiology
Evaluation
Flow distribution
Flow pattern
Flow rates
Flow velocity
Fluid dynamics
Health risks
Humans
HVAC
HVAC equipment
Hydrodynamics
Indoor environments
Infections
Mathematical models
Numerical models
respiratory particles
Review
Risk
risk of infection
SARS-CoV-2
Seats
Severe acute respiratory syndrome
Severe acute respiratory syndrome coronavirus 2
Ventilation
virus transmission
Title Risk of SARS‐CoV‐2 in a car cabin assessed through 3D CFD simulations
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fina.13012
https://www.ncbi.nlm.nih.gov/pubmed/35347787
https://www.proquest.com/docview/2644245559
https://www.proquest.com/docview/2644944470
https://pubmed.ncbi.nlm.nih.gov/PMC9111293
Volume 32
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