Air exchange rates and advection–diffusion of CO ₂ and aerosols in a route bus for evaluation of infection risk

Abstract

As COVID‐19 continues to spread, infection risk on public transport is concerning. Air exchange rates (ACH) and advection–diffusion of CO2 and particles were determined in a route bus to evaluate the infection risk. ACH increased with bus speed whether windows were open or closed, and ACH were greater when more windows were open. With two open windows, ACH was greater when a front and rear window were open than when two rear windows were open. With both front and rear ventilation fans set to exhaust, ACH was more than double that when both were set to supply. With air conditioning (AC) off, CO2 and particles spread proportionally at the same rate from a source, whereas with the AC on, the spread rate of particles was about half that of CO2, because particles might be trapped by a prefilter on the AC unit. Infection risk can be reduced by equipping AC unit with an appropriate filter. Calculations with a modified Wells–Riley equation showed that average infection risk was reduced by 92% in the moving bus with windows open comparing to with windows closed. When the bus was moving with windows closed, exhaust fan operation reduced the average risk by 35%.

A COVID‐19 cluster analysis in an office: Assessing the long‐range aerosol and fomite transmissions with infection control measures

“…The risk of long‐range aerosol transmission was calculated using a dose–response function with the parameter k L in comparing the multiple pathways. Meanwhile, the risk of long‐range aerosol transmission is usually calculated by quantum emission q (Azuma, Yanagi, et al., 2020; Bazant & Bush, 2021; Buonanno, Stabile, et al., 2020; Buonanno, Morawska, et al., 2020; Dai & Zhao, 2020; Riley et al., 1978; Shinohara et al., 2022). In the relationship between k L and q , the q is 204 h −1 (range; 23–916 h −1 ) and 151 h −1 (range; 18–679 h −1 ) in the LF and SLF scenarios, respectively, higher than the value 14–48 h −1 estimated for the wild‐type strain (Dai & Zhao, 2020).…”

Role of Fluid Dynamics in Infectious Disease Transmission: Insights from COVID-19 and Other Pathogens

“…The simulation results were used to analyse how the ventilation rate affects the distribution of temperature and aerosol concentration [270]. These results can enhance our understanding of how inhaled airborne SARS-CoV-2 aerosols are transmitted between individuals in close proximity [271].…”

Wind Velocity and Dispersion/Advection-diffusion of Artificial Droplets and Droplet Nuclei in a Domed All- weather Multi-purpose Stadium

“…The former model has been applied to estimate risk in health care centers 20,21 , o ces 22 , stadiums 23 , subways 24 , and buses 25 . The latter model has been used to assess infection risks in classrooms 26 , hospitals 27 , various other types of facilities 28 , and buses 29 . However, most previous assessments have used results from laboratory tests or estimates from simulation models; few have evaluated aerosol behavior in real environments based on actual measurements 25 .…”