TY - JOUR
T1 - Dispersion of virus-laden droplets in ventilated rooms
T2 - Effect of homemade facemasks
AU - Aliyu, Aliyu
AU - Singh, Dharminder
AU - Uzoka, Chino
AU - Mishra, Rakesh
N1 - Funding Information:
The authors acknowledge the funding provided by the University of Huddersfield via the UK's Higher Education Innovation Fund (HEIF) .
Publisher Copyright:
© 2021 Elsevier Ltd
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/12/1
Y1 - 2021/12/1
N2 - In December 2019, the SARS-CoV-2 virus emerged and rapidly spread throughout the world. It causes the respiratory disease COVID-19 via the transmission of microbial pathogens within bio-aerosols during speaking, sneezing, and coughing. Therefore, understanding bioaerosol dynamics is important for developing mitigation strategies against droplet-induced infections. Computer modelling, using Computational Fluid Dynamics, has become a useful tool in studying and visualising the spread of atomised bio-droplets but the effect of using cloth facemasks has not been fully quantified. In this study, simulations were carried out to quantify the extent of respiratory droplet transfer with and without facemasks between a pair of ventilated rooms by a mathematical model for the first time. A 600-μm pore facemask was used, representing the porosity of a typical cloth facemask. Using the discrete phase model, the transport of ejected droplets was tracked. The results show that in the facemask cases, more than 96% of all the ejected droplets in all scenarios were trapped in the recommended 2 m social distancing radius around the human source. Correspondingly, only a maximum of 80% of droplets were deposited within the social distancing radius in the no facemask scenarios, with >20% airborne and transported to the second room. One-dimensional empirical correlations were developed for droplet concentration as a function of distance from the bioaerosol source. The models show that droplet concentration decays exponentially from the source especially in the facemask cases. The study therefore reinforces the importance of face coverings in lessening the transmission of possibly infected respiratory droplets that transmit highly infectious diseases such as COVID-19.
AB - In December 2019, the SARS-CoV-2 virus emerged and rapidly spread throughout the world. It causes the respiratory disease COVID-19 via the transmission of microbial pathogens within bio-aerosols during speaking, sneezing, and coughing. Therefore, understanding bioaerosol dynamics is important for developing mitigation strategies against droplet-induced infections. Computer modelling, using Computational Fluid Dynamics, has become a useful tool in studying and visualising the spread of atomised bio-droplets but the effect of using cloth facemasks has not been fully quantified. In this study, simulations were carried out to quantify the extent of respiratory droplet transfer with and without facemasks between a pair of ventilated rooms by a mathematical model for the first time. A 600-μm pore facemask was used, representing the porosity of a typical cloth facemask. Using the discrete phase model, the transport of ejected droplets was tracked. The results show that in the facemask cases, more than 96% of all the ejected droplets in all scenarios were trapped in the recommended 2 m social distancing radius around the human source. Correspondingly, only a maximum of 80% of droplets were deposited within the social distancing radius in the no facemask scenarios, with >20% airborne and transported to the second room. One-dimensional empirical correlations were developed for droplet concentration as a function of distance from the bioaerosol source. The models show that droplet concentration decays exponentially from the source especially in the facemask cases. The study therefore reinforces the importance of face coverings in lessening the transmission of possibly infected respiratory droplets that transmit highly infectious diseases such as COVID-19.
KW - Bio-aerosols
KW - Computational Fluid Dynamics
KW - Covid-19
KW - Facemask
KW - Ventilation
KW - Isolation rooms
KW - Respiratory droplets
KW - COVID-19
KW - Computational fluid dynamics
UR - http://www.scopus.com/inward/record.url?scp=85120507573&partnerID=8YFLogxK
U2 - 10.1016/j.jobe.2021.102933
DO - 10.1016/j.jobe.2021.102933
M3 - Article
VL - 44
JO - Journal of Building Engineering
JF - Journal of Building Engineering
SN - 2352-7102
M1 - 102933
ER -