Mechanical ventilation is an effective measure to control indoor long-range airborne transmission of COVID-19, but it often leads to substantial energy expenditure. This study introduces a novel exposure-based smart ventilation and occupancy control strategy to reduce infection risk and save energy in school environments that are typically characterized by fixed occupants and long exposure time. This exposure-based approach allows the quanta concentration to vary over time rather than keeping it constantly below certain thresholds. This enables us to: (1) adjust ventilation and occupant schedule to facilitate passive cooling/heating potential in response to outdoor weather conditions; (2) consider the interaction between ventilation and occupant schedule to maximize their benefits in reducing infection risk and energy consumption. Taking a typical classroom as a base case, ventilation and occupant schedule are optimized individually and jointly through Genetic Algorithm, to control infection risk, minimize energy consumption, maintain thermal comfort, and promise sufficient schooling time. Our results show that the most energy-efficient strategy is the concurrent optimization of both occupant schedule and ventilation, achieving an energy reduction of up to ~60% compared to traditional constant ventilation methods. Solely optimizing occupant schedule is the least energy-efficient strategy, yielding an energy reduction ratio (over base case) of only half of the most efficient strategy. Our study reveals the possibility of optimizing occupant schedule and ventilation to balance building energy consumption and transmission control. The viability of these control strategies has been proven across various climate zones and seasons in China, highlighting their broad applicability.

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 (Q_PFR), by using computational fluid dynamics (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.

There exist various vertical temperature gradients in different-type buildings. A holistic understanding of the impact of different temperature-stratified indoor environments on infection risk is necessary. In this work, the airborne transmission risk of SARS-CoV-2 in different thermally stratified indoor environments is assessed using our previously developed airborne infection risk model. Results show that the vertical temperature gradients in office building, hospital, classroom, etc. are within the range of −0.34 to 3.26 ℃/m. In large space such as coach station, airport terminal, and sport hall, the average temperature gradient ranges within 0.13–2.38 ℃/m in occupied zone (0–3 m); in ice rink with special requirements of indoor environment, the temperature gradient is higher than those in the above indoor spaces. The existence of temperature gradients causes multi-peaks of the transmission risk of SARS-CoV-2 with distancing, and our results show that in office, hospital ward and classroom, the second peak of the transmission risk is higher than 10⁻³ in most contact scenarios, while most being lower than 10⁻⁶ in large spaces like coach station and airport. The work is expected to provide some guidance on specific intervention policies in relation to the types of indoor environments.