Vouriot, C.V.M. orcid.org/0000-0003-1846-4586, van Reeuwijk, M. and Burridge, H.C. orcid.org/0000-0002-0719-355X (2024) Uncertainties in exposure predictions arising from point measurements of carbon dioxide in classroom environments. Journal of The Royal Society Interface, 21 (219). 20240270. ISSN 1742-5689
Abstract
Predictions of airborne infection risk can be made based on the fraction of rebreathed air inferred from point measurements of carbon dioxide (CO2). We investigate the extent to which environmental factors, particularly spatial variations due to the ventilation provision, affect the uncertainty in these predictions. Spatial variations are expected to be especially problematic in naturally ventilated spaces, which include the majority of classrooms in the UK. An idealized classroom, broadly representative of the physics of (buoyancy-driven) displacement ventilation, is examined using computational fluid dynamics, with different ventilation configurations. Passive tracers are used to model both the CO2 generated by all 32 occupants and the breath of a single infectious individual (located in nine different regions). The distribution of infected breath is shown to depend strongly on the distance from the release location but is also affected by the pattern of the ventilating flow, including the presence of stagnating regions. However, far-field exposure predictions based on single point measurements of CO2 within the breathing zone are shown to rarely differ from the actual exposure to infected breath by more than a factor of two—we argue this uncertainty is small compared with other uncertainties inherent in modelling airborne infection risk.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Author(s). Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
Keywords: | airborne infection; carbon dioxide; computational fluid dynamics; risk modelling; ventilation; Carbon Dioxide; Humans; Ventilation; Air Pollution, Indoor; Schools; Uncertainty; COVID-19; Environmental Exposure |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > School of Mechanical, Aerospace and Civil Engineering |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 28 Oct 2024 15:47 |
Last Modified: | 28 Oct 2024 15:47 |
Status: | Published |
Publisher: | The Royal Society |
Refereed: | Yes |
Identification Number: | 10.1098/rsif.2024.0270 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:218927 |