High-resolution large-eddy simulation of indoor turbulence and its effect on airborne transmission of respiratory pathogens; model validation and infection probability analysis

TL;DR

This study uses high-resolution large-eddy simulation to analyze indoor air turbulence and aerosol dispersion, validating the model with experiments, and assessing risk reduction strategies like air purifiers and partitioning for airborne disease transmission.

Contribution

It introduces a validated LES-based approach to evaluate indoor aerosol dispersion and infection risk, improving upon classical models like Wells-Riley.

Findings

Air purifiers significantly reduce infection risk more than classical models predict.

Partitioning alone can increase transmission risk unless combined with air purifiers.

LES provides more accurate infection probability estimates compared to traditional models.

Abstract

High-resolution large-eddy simulation (LES) is exploited to study indoor air turbulence and its effect on the dispersion of respiratory virus-laden aerosols and subsequent transmission risks. The methodology is applied to assess two dissimilar approaches to reduce transmission risks: a strategy to augment the indoor ventilation capacity with portable air purifiers and a strategy to utilize partitioning by exploiting portable space dividers. To substantiate the physical relevance of the LES model, a set of experimental aerosol concentration measurements are carried out, and their results are used for validating the LES model results. The obtained LES dispersion results are subjected to pathogen exposure and infection probability analysis. Wells-Riley probability model is extended to rely on realistic time- and space-dependent concentration fields to yield time- and space-dependent infection probability fields. The use of air purifiers leads to greater reduction in absolute risks compared to the analytical Wells-Riley model, which fails to predict the original risk level. However, the two models do agree on the relative risk reduction. The spatial partitioning strategy is demonstrated to have an undesirable effect when employed without other measures. The partitioning approach may yield positive results when employed together with targeted air purifier units. The LES-based results are examined in juxtaposition with the classical Wells-Riley model, which is shown to significantly underestimate the infection probability, highlighting the importance of employing accurate indoor turbulence modeling when evaluating different risk-reduction strategies.