Abstract

In indoor environments, ventilation is essential for diluting or removing contaminants, pathogens, excess heat, and moisture, thereby ensuring a healthy and comfortable space. The COVID-19 pandemic underscored the critical role of ventilation in controlling airborne respiratory infections indoors. During this period, inadequate ventilation systems and improper operations in densely populated public spaces were frequently linked to outbreaks and superspreading events, heightening concerns over indoor exposure risks for occupants. As COVID-19 restrictions begin to relax globally, the focus is transitioning to long-term management strategies for the virus. This transition necessitates a comprehensive understanding of the specific ventilation requirements for various indoor spaces. It is imperative to swiftly and accurately assess ventilation conditions and consistently ensure an adequate supply of clean air. This study focuses on mitigation strategies to reduce indoor exposure risks and prepare for the post-pandemic era. The multizone CONTAM modeling of aerosol transport under different mechanical mitigation strategies was investigated in five DOE prototype buildings. To utilize field evidence for improving indoor air quality, a novel approach integrating Bayesian inference and stochastic CO2 grey-box models was applied. This approach was used to evaluate the ventilation conditions within two primary school classrooms in Montreal. The Equivalent Clean Airflow Rate (ECAi) was calculated following ASHRAE 241, revealing an insufficient clean air supply in both classrooms. To achieve a sufficient ECAi, an additional 0.38 m3/s of clean air delivery rate (CADR) from air-cleaning devices is recommended. Finally, steady-state CO2 thresholds (Climit, Ctarget, and Cideal) were established to indicate when ECAi requirements could be achieved under various mitigation strategies.