Modelling aerosol transport and virus exposure with numerical simulations in relation to SARS-CoV-2 transmission by inhalation indoorsAtmospheric Dispersion Modelling, Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland; Molecular and Integrative Biosciences Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Finland.
Atmospheric Dispersion Modelling, Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland.
Department of Neuroscience and Biomedical Engineering, Aalto University, AALTO, Finland.
Department of Civil Engineering, Aalto University, AALTO, Finland.
Department of Information and Service Management, Aalto University, AALTO, Finland.
Department of Bioproducts and Biosystems, Aalto University, AALTO, Finland.
Department of Neuroscience and Biomedical Engineering, Aalto University, AALTO, Finland.
Atmospheric Dispersion Modelling, Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland.
Department of Civil Engineering, Aalto University, AALTO, Finland.
Department of Mechanical Engineering, Aalto University, AALTO, Finland.
VTT Technical Research Centre of Finland Ltd, Finland.
VTT Technical Research Centre of Finland Ltd, Finland.
Department of Applied Physics, Aalto University, AALTO, Finland.
Department of Mechanical Engineering, Aalto University, AALTO, Finland.
Emergency Department, Mikkeli Central Hospital, The South Savo Social and Health Care Authority, Finland.
Department of Mechanical Engineering, Aalto University, AALTO, Finland.
Department of Mechanical Engineering, Aalto University, AALTO, Finland.
Department of Neuroscience and Biomedical Engineering, Aalto University, AALTO, Finland.
Department of Mechanical Engineering, Aalto University, AALTO, Finland.
Department of Chemical and Metallurgical Engineering, Aalto University, AALTO, Finland.
Department of Applied Physics, Aalto University, AALTO, Finland.
CSC-IT Center for Science Ltd, Finland.
Department of Applied Physics, Aalto University, AALTO, Finland.
Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland.
Department of Bioproducts and Biosystems, Aalto University, AALTO, Finland.
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2020 (English)In: Safety Science, Vol. 130, article id 104866Article in journal (Refereed) Published
Abstract [en]
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 (d⩽20μm) allows lingering in the air for O(1h) 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 O(100μm), 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. O(100). By 3D scale-resolving computational fluid dynamics (CFD) simulations, we give various examples on the transport and dilution of aerosols (d⩽20μm) over distances O(10m) 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 O(100) aerosols could range from O(1s) to O(1min) or even to O(1h) 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.
Place, publisher, year, edition, pages
2020. Vol. 130, article id 104866
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:miun:diva-40681DOI: 10.1016/j.ssci.2020.104866ISI: 000560700900023Scopus ID: 2-s2.0-85086590250OAI: oai:DiVA.org:miun-40681DiVA, id: diva2:1507322
Note
Cited By :11; Export Date: 7 December 2020; Article
2020-12-072020-12-072021-05-03Bibliographically approved