Coldrick, S, Kelsey, A, Ivings, MJ et al. (6 more authors) (2022) Modeling and experimental study of dispersion and deposition of respiratory emissions with implications for disease transmission. Indoor Air, 32 (2). e13000. ISSN 0905-6947
Abstract
The ability to model the dispersion of pathogens in exhaled breath is important for characterizing transmission of the SARS-CoV-2 virus and other respiratory pathogens. A Computational Fluid Dynamics (CFD) model of droplet and aerosol emission during exhalations has been developed and for the first time compared directly with experimental data for the dispersion of respiratory and oral bacteria from ten subjects coughing, speaking, and singing in a small unventilated room. The modeled exhalations consist of a warm, humid, gaseous carrier flow and droplets represented by a discrete Lagrangian particle phase which incorporates saliva composition. The simulations and experiments both showed greater deposition of bacteria within 1 m of the subject, and the potential for a substantial number of bacteria to remain airborne, with no clear difference in airborne concentration of small bioaerosols (<10 μm diameter) between 1 and 2 m. The agreement between the model and the experimental data for bacterial deposition directly in front of the subjects was encouraging given the uncertainties in model input parameters and the inherent variability within and between subjects. The ability to predict airborne microbial dispersion and deposition gives confidence in the ability to model the consequences of an exhalation and hence the airborne transmission of respiratory pathogens such as SARS-CoV-2.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 Crown copyright. Indoor Air published by John Wiley & Sons Ltd. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) |
Keywords: | computational fluid dynamics, exhalation, microorganism, respiratory, SARS-CoV- 2 |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) |
Funding Information: | Funder Grant number NIHR National Inst Health Research Not Known |
Depositing User: | Symplectic Publications |
Date Deposited: | 12 Apr 2022 11:07 |
Last Modified: | 12 Apr 2022 11:07 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1111/ina.13000 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:185629 |