Importance of inhomogeneous mixing in governing exposure to indoor airborne contaminants
ORAL
Abstract
Airborne contaminant concentration and transport in closed indoor spaces play a crucial role in exposure of occupants to respiratory pathogen transmission and public health outcomes in time of pandemics. One key assumption often invoked in indoor transmission risk modelling is that of homogeneous air mixing. Yet indoor spaces, including both mixing or displacement ventilation, are seldom homogeneously mixed. Yet there are little to no direct quantification and prediction of heterogeneity for such spaces.
In this joint experimental and modelling study, detailed and systematic multimodal measurements of heterogeneity of clearance of aerosol contaminants were performed in an indoor, slanted auditorium-type space with displacement ventilation design under a range of ventilation and environmental conditions. The results show that systematic and pronounced mixing heterogeneity emerge, depending on seating location in the indoor space. Such spatial inhomogeneity is associated with different contaminant exposure, and thus, risk levels of infection.
We discuss the results in the context of mitigation and risk management of exposure to the infectious dose of a respiratory pathogen.
In this joint experimental and modelling study, detailed and systematic multimodal measurements of heterogeneity of clearance of aerosol contaminants were performed in an indoor, slanted auditorium-type space with displacement ventilation design under a range of ventilation and environmental conditions. The results show that systematic and pronounced mixing heterogeneity emerge, depending on seating location in the indoor space. Such spatial inhomogeneity is associated with different contaminant exposure, and thus, risk levels of infection.
We discuss the results in the context of mitigation and risk management of exposure to the infectious dose of a respiratory pathogen.
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Presenters
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Markus J Schmidt
Massachusetts Institute of Technology MIT
Authors
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Markus J Schmidt
Massachusetts Institute of Technology MIT
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Xiaoyi Hu
Massachusetts Institute of Technology MIT
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Reid Kovacs
Massachusetts Institute of Technology MIT
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Abbas Ghasemi
MIT
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James Lynch
MIT
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Naijian Shen
Massachusetts Institute of Technology (MIT)
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Jonathan Jilesen
Dassault Système , United States
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Thomas Heldt
MIT
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Lydia Bourouiba
Massachusetts Institute of Technology MIT