Modeling Virus Infection Risks in Automobile Cabin

In the post Covid era, risk of infection in conditioned space is getting attention and has generated a lot of interest for the design of the new systems and strategies for the management and operations of the existing HVAC systems. Risk management plays a key role where the amounts of outside air and recirculated airs can be used to mitigate the propagation of the virus within the conditioned space. In other words, ventilation plays a huge role within the conditioned space along with strategies based on UV irradiation, ionization and use of highly efficient filters. Different air purification systems have been created by the researchers based on the titanium oxide-based UV photocatalysis system, filters with MERV ratings higher than 13 (ASHRAE Standard 52.2) and HEPA filters. Recent ASHRAE standard 243 (2023) on infectious diseases recommends using high ventilation rates within the conditioned space to reduce virus concentration, and hence, to reduce the risk of infection. Determining risk of infection is difficult as we cannot conduct tests by exposing the passengers to different viruses in vehicle. Instead, empirical models have been developed to predict probability of risk of infection based on a number of variables. This risk of infection is then multiplied by the total population to determine the people infected within the cabin. In this investigation the author has determined the risk of infection by using Wells-Riley and Gammaitoni-Nucci correlations to determine risk of infection for occupants when an infector is present in the vehicle cabin.