ArticleJournal of exposure science & environmental epidemiology2024
Airborne respiratory aerosol transport and deposition in a two-person office using a novel diffusion-based numerical model.
Article in Journal of exposure science & environmental epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed, 8 citations in OpenAlex.
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7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe COVID-19 pandemic was caused by the SARS-CoV-2 coronaviruses transmitted mainly through exposure to airborne respiratory droplets and aerosols carrying the virus.
objectiveTo assess the transport and dispersion of respiratory aerosols containing the SARS-CoV-2 virus and other viruses in a small office space using a diffusion-based computational modeling approach.
methodsA 3-D computational model was used to simulate the airflow inside the 70.2 m
resultsAn increase in the hourly air change rate (ACH) from 2.0 to 5.6 decreased the 1 μm droplet concentration inside the office by a factor of 2.8 and in the breathing zone of the receptor occupant by a factor of 3.2. The concentration at the receptor breathing zone is estimated by the area-weighted average of a 1 m diameter circular disk, with its centroid at the center of the receptor mannequin mouth. While all aerosols were dispersed by airflow turbulence, the gravitational sedimentation significantly influenced the transport of larger aerosols in the room. The 1 and 10 μm aerosols remained suspended in the air and dispersed throughout the room. In contrast, the larger 20 and 50 μm aerosols deposited on the floor quickly due to the gravitational sedimentation. Increasing the partition between cubicles by 0.254 m (10") has little effect on the smaller aerosols and overall exposure. IMPACT: This paper provides an efficient computational model for analyzing the concentration of different respiratory droplets and aerosols in an indoor environment. Thus, the approach could be used for assessing the influence of the spatial concentration variations on exposure for which the fully mixed model cannot be used.
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