Digital Twins in the Built Environment for Indoor Air Quality Management

Indoor air quality (IAQ) is a crucial aspect of the performance of the built environment that influences the health and wellbeing of occupants. A digital twin (DT) is an emerging technology that enables mirroring of real-world conditions to optimize building operations in anticipation of improvements of the occupant experience. However, existing studies and applications lack a holistic approach using digital twin technologies to quantitatively analyze the interactions between factors affecting indoor air quality. To fill this gap, two cases in a university building in Bristol were selected for in-depth study. IAQ was measured with sensors and simulated using computational fluid dynamics (CFD) in four scenarios. The results show that air temperature and humidity were not significantly affected across different scenarios, whereas CO₂ concentration varied distinctly under different conditions. In the four scenarios, the deviations of the CFD-simulated CO₂ outcomes from real-world measurements were 0.9%, 6.4%, 2.6%, and 2.8% respectively, demonstrating that the CFD simulation can predict and manage indoor air quality with high accuracy. This research reveals the extent to which IAQ factors (e.g., temperature, humidity, CO₂) are affected by window or door operation, room size and occupant distribution. Accordingly, measures for applying multi-functional sensors to monitor building conditions, simulating indoor air quality and optimizing building operations are proposed with the support of digital twin technologies.