Transmission characteristics of respiratory droplets aerosol in indoor environment: an experimental study

Impacts of human movement and ventilation mode on the indoor environment, droplet evaporation, and aerosol transmission risk at airport terminals

The dispersion of the coronavirus pandemic has caused immense damage worldwide, and people have begun to ruminate epidemic prevention strategies for public places. Airport terminals with a high number of occupied passengers have become potentially high-risk regions for aerosol transmission of coronavirus disease 2019 (COVID-19). In this study, the Eulerian-Lagrangian approach and realizable k-ε turbulence model were used to numerically simulate airflow organization and aerosol transmission when passengers are moving slowly in a line. During the aerosol transmission period, evaporation was considered a key factor influencing the particle size distribution at the beginning of aerosol transmission from humans. Moreover, passenger movement at the airport terminal was attained by employing dynamic mesh algorithms. Based on the relative direction of passengers and air vents when queuing in the terminal building, we studied three conditions: windward walking, leeward walking, and crosswind walking. The results of this study showed that the walking has an important influence on droplet distribution. Droplet distribution indicates that individuals standing behind patients during queuing movements have a higher risk of infection than those standing in front of them. A significant aerosol accumulation was discovered at 0.5 m behind the patient when passengers moved simultaneously. An aerosol transmission distance of 15 s aligned with the passenger's walking direction could reach up to 9.32 m. Furthermore, although the evaporation time of the large droplets was longer than that of the small droplets, both large and small droplets evaporated rapidly after exhalation. The crosswind influence caused the droplets to travel farther away in a direction perpendicular to human movement, which increased the distance by approximately 1.26 m compared to the absence of the crosswind influence.

Airborne transmission of COVID-19 virus in enclosed spaces: An overview of research methods

Since the outbreak of COVID-19 in December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) has spread worldwide. This study summarized the transmission mechanisms of COVID-19 and their main influencing factors, such as airflow patterns, air temperature, relative humidity, and social distancing. The transmission characteristics in existing cases are providing more and more evidence that SARS CoV-2 can be transmitted through the air. This investigation reviewed probabilistic and deterministic research methods, such as the Wells-Riley equation, the dose-response model, the Monte-Carlo model, computational fluid dynamics (CFD) with the Eulerian method, CFD with the Lagrangian method, and the experimental approach, that have been used for studying the airborne transmission mechanism. The Wells-Riley equation and dose-response model are typically used for the assessment of the average infection risk. Only in combination with the Eulerian method or the Lagrangian method can these two methods obtain the spatial distribution of airborne particles' concentration and infection risk. In contrast with the Eulerian and Lagrangian methods, the Monte-Carlo model is suitable for studying the infection risk when the behavior of individuals is highly random. Although researchers tend to use numerical methods to study the airborne transmission mechanism of COVID-19, an experimental approach could often provide stronger evidence to prove the possibility of airborne transmission than a simple numerical model. All in all, the reviewed methods are helpful in the study of the airborne transmission mechanism of COVID-19 and epidemic prevention and control.

What is suitable social distancing for people wearing face masks during the COVID-19 pandemic?

COVID-19 has caused the global pandemic and had a serious impact on people's daily lives. The respiratory droplets produced from coughing and talking of an infected patient were possible transmission routes of coronavirus between people. To avoid the infection, the US Centers for Disease Control and Prevention (CDC) advised to wear face masks while maintaining a social distancing of 2 m. Can the social distancing be reduced if people wear masks? To answer this question, we measured the mass of inhaled droplets by a susceptible manikin wearing a mask with different social distances, which was produced by coughing and talking of an index "patient" (human subject) also wearing a mask. We also used the computational fluid dynamics (CFD) technology with a porous media model and particle dispersion model to simulate the transmission of droplets from the patient to the susceptible person with surgical and N95 masks. We compared the CFD results with the measured velocity in the environmental chamber and found that the social distancing could be reduced to 0.5 m when people wearing face masks. In this case, the mass concentration of inhaled particles was less than two people without wearing masks and with a social distancing of 2 m. Hence, when the social distancing was difficult, wearing masks could protect people. We also found that the leakage between the face mask and the human face played an important role in the exhaled airflow pattern and particle dispersion. The verified numerical model can be used for more scenarios with different indoor environments and HVAC systems. The results of this study would make business profitable with reduced social distancing in transportation, education, and entertainment industries, which was beneficial for the reopening of the economy.