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In this paper the risk of infection from SARS-CoV-2 Delta variant ofpassengers sharing a car cabin with an infected subject for a 30-min journey isestimated through an integrated approach combining a recently developedpredictive emission-to-risk approach and a validated CFD numerical modelnumerically solved using the open-source OpenFOAM software. Different scenarioswere investigated to evaluate the effect of the infected subject positionwithin the car cabin, the air flow rate of the HVAC system, the HVACventilation mode, and the expiratory activity (breathing vs. speaking). Thenumerical simulations here performed reveal that the risk of infection isstrongly influenced by several key parameter: as an example, under the sameventilation mode and emitting scenario, the risk of infection ranges from zeroto roughly 50% as a function of the HVAC flow rate. The results obtained alsodemonstrate that: (i) simplified zero-dimensional approaches limit properevaluation of the risk in such confined spaces, conversely, (ii) CFD approachesare needed to investigate the complex fluid-dynamics in similar indoorenvironments, and, thus, (iii) the risk of infection in indoor environmentscharacterized by fixed seats can be in principle controlled by properlydesigning the flow patterns of the environment.

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