Analyses of Static and Dynamic Airflow and Contaminant Dispersion in Elevator Environments

This study investigates airflow patterns and contaminant concentration in elevator-related areas, highlighting their critical role in indoor air quality and infection control. Despite widespread reliance on elevators, limited research addresses airflow patterns and contaminant behavior in these confined, high-density spaces. Using a full-scale elevator mockup connected to a lobby, this study conducted static and dynamic experiments to measure air velocity, temperature, and contaminant concentration. Static tests analyzed closed cabins with mixed ventilation, while dynamic tests examined the impact of passenger movement on airflow and contaminant dispersion.

Experimental data validated a Computational Fluid Dynamics (CFD) model, which revealed relatively uniform air conditions during elevator transit and notable wake effects associated with passenger movement. The CFD model simulated scenarios involving an index patient engaging in various respiratory activities, such as talking and coughing. Results showed that while the infection risk during short elevator rides is generally low, proximity to an infected individual during activities like talking increases transmission risk.

The findings underscore CFD’s value in studying both static and dynamic indoor airflow, though complexities in dynamic cases necessitate refined models and experimental methods. Additionally, the study enhances traditional displacement ventilation systems with induction panels and emphasizes the importance of integrated design for elevators and adjacent spaces to optimize ventilation performance and reduce infection risks during airborne crises, such as pandemics. This research advances understanding of indoor air quality in confined environments, providing insights for safer and more effective ventilation design.