  In this paper 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 air flow 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 parameter: 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.
