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Possible high COVID-19 airborne infection risk in deep and poorly ventilated 2D street canyons

Lavor, V. ORCID: https://orcid.org/0000-0002-0078-4525, Coceal, O. ORCID: https://orcid.org/0000-0003-0705-6755, Grimmond, S. ORCID: https://orcid.org/0000-0002-3166-9415, Hang, J. and Luo, Z. ORCID: https://orcid.org/0000-0002-2082-3958 (2023) Possible high COVID-19 airborne infection risk in deep and poorly ventilated 2D street canyons. Building Simulation, 16 (9). pp. 1617-1628. ISSN 1996-8744

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To link to this item DOI: 10.1007/s12273-023-1037-x

Abstract/Summary

Despite the widespread assumption that outdoor environments provide sufficient ventilation and dilution capacity to mitigate the risk of COVID-19 infection, there is little understanding of airborne infection risk in outdoor urban areas with poor ventilation. To address this gap, we propose a modified Wells-Riley model based on the purging flow rate (QPFR), by using computational fluid dynamic (CFD) simulations. The model quantifies the outdoor risk in 2D street canyons with different approaching wind speeds, urban heating patterns and aspect ratios (building height to street width). We show that urban morphology plays a critical role in controlling airborne infectious disease transmission in outdoor environments, especially under calm winds; with deep street canyons (aspect ratio > 3) having a similar infection risk as typical indoor environments. While ground and leeward wall heating could reduce the risk, windward heating (e.g., windward wall ~10 K warmer than the ambient air) can increase the infection risk by up to 75%. Our research highlights the importance of considering outdoor infection risk and the critical role of urban morphology in mitigating airborne infection risk. By identifying and addressing these risks, we can inform measures that may enhance public health and safety, particularly in densely populated urban environments.

Item Type:Article
Refereed:Yes
Divisions:Science > School of the Built Environment > Construction Management and Engineering
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:111860
Publisher:Springer

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