Throughout the COVID-19 pandemic, you have probably heard about how aerosols transport virus particles. But how exactly do these aerosols travel through closed spaces, and how much virus is present in one location at one time? Some models used for risk assessment often give inaccurate answers to these questions. Zhang et al. developed a numerical methodology accurately predicting virus transport in a closed bus with air conditioning.

In an enclosed bus, the concentration of virus varies by location and time. The authors show the probability of contracting an airborne disease like COVID-19 depends not only on the duration a person spends on the bus but where they sit.

The authors found exhaled aerosols follow complicated patterns within indoor spaces with air circulation due to the turbulence in the air generated by HVAC systems and the buoyancy induced by the heat from passengers’ bodies and our breath.

“The standard tools for predicting risk in an enclosed space based on a well-mixed assumption generally predict the mean concentration well but fails to capture the variation about the mean, which is found to be significant owing to the complexity of the transport of the virus through the air,” author Kevin Maki said. “Existing well-mixed models fail to adequately assess risk.”

The team’s method used computational fluid dynamics, which can predict unsteady turbulent flow throughout an enclosed space and assess the amount of virus that a person inhales as a function of time and location.

The work can identify how safe it is to ride a bus, Maki said, though future work should extend their results to any enclosed space.

Source: “On the utility of a well-mixed model for predicting disease transmission on an urban bus,” by Zhihang Zhang, Jesse Capecelatro, and Kevin Maki, AIP Advances (2021). The article can be accessed at