Modelling aerosol transport and virus exposure with numerical simulations in relation to SARS-CoV-2 transmission by inhalation indoors

Abstract

We provide research findings on the physics of aerosol and droplet dispersion relevant to the hypothesized aerosol transmission of SARS-CoV-2 during the current pandemic. We utilize physics-based modeling at different levels of complexity, along with previous literature on coronaviruses, to investigate the possibility of airborne transmission. The previous literature, our 0D-3D simulations by various physics-based models, and theoretical calculations, indicate that the typical size range of speech and cough originated droplets ( ) allows lingering in the air for ) so that they could be inhaled. Consistent with the previous literature, numerical evidence on the rapid drying process of even large droplets, up to sizes , into droplet nuclei/aerosols is provided. Based on the literature and the public media sources, we provide evidence that the individuals, who have been tested positive on COVID-19, could have been exposed to aerosols/droplet nuclei by inhaling them in significant numbers e.g. . By 3D scale-resolving computational fluid dynamics (CFD) simulations, we give various examples on the transport and dilution of aerosols ( ) over distances in generic environments. We study susceptible and infected individuals in generic public places by Monte-Carlo modelling. The developed model takes into account the locally varying aerosol concentration levels which the susceptible accumulate via inhalation. The introduced concept, ’exposure time’ to virus containing aerosols is proposed to complement the traditional ’safety distance’ thinking. We show that the exposure time to inhale aerosols could range from to or even to depending on the situation. The Monte-Carlo simulations, along with the theory, provide clear quantitative insight to the exposure time in different public indoor environments.

Predicting airborne coronavirus inactivation by far-UVC in populated rooms using a high-fidelity coupled radiation-CFD model

“…Fully resolved spatially distributed far-UVC intensities enable more accurate predictions of virus removal over simplified 1/r 2 strategies 19 , diffusion radiation models 20 , and, potentially, empirical data taken from physical measurements [21][22][23] . The use of LES models 24 provide more detailed descriptions of viral transport over other modelling methods, such as Reynolds Averaged Navier-Stokes 21,23 or analytical zone-mixing methods 23,25 , and despite their increased computational requirement, and hence limited use, their importance is now being recognised in the field of atmospheric viral transport predictions 24 .…”

Assessing the effectiveness of using various face coverings to mitigate the transport of airborne particles produced by coughing indoors

“…First, the current findings were obtained under a specific indoor condition. Many recent studies have pointed out that poor exhaust ventilation may contribute to the transmission of the virus (Buonanno et al 2020;Correia et al 2020;Vuorinen et al 2020). The fate of respiratory droplets in the indoor environment can be affected by a variety of factors such as temperature, relative humidity, and air exchange rate (Morawska 2006;Xie et al 2007).…”

Airflow Characteristics in Aeromedical Aircraft: Considerations During COVID-19

“…The characteristics of the smoke generated during testing are important, as a direct comparison with the characteristics of COVID-19 movement and transmission is difficult (23). The use and type of smoke as a medium for testing has limitations (24-26), but has been used to simulate airflow around oxygen masks (27), air escape in hospital isolation rooms (28), and to estimate the pattern of movement of aerosolised particles (26).…”