Determining Building Natural Ventilation Potential via IoT-Based Air Quality Sensors

Abstract

Natural ventilation (NV) represents the most energy-efficient way to operate buildings and, in an attempt to reduce the built environment's global carbon footprint, represents a resource, the usage of which has to be maximized. This study demonstrated how a combination of an IoT environmental sensing network implemented locally outdoors and indoors can help to determine the NV potential and actual utilization throughout the year with the consideration of outdoor climate variance, air pollution levels, and window open/closed status. An NV potential index was developed by analyzing indoor and outdoor PM2.5, and outdoor air temperature and air speed throughout the year at different spatial (from room scale to building level and local weather stations) and temporal (instantaneous, season, and annual) scales. The index was applied on a case building located in Berkeley, California, during the period of August 2018 to the end of 2019. Compared to the potential NV availability, the actual window opening time in typical rooms was less than 35%. These results point out that the actual window usage behavior was the key limiting factor in NV potential utilization. Even during periods when climate- and pollution-wise outdoor conditions allowed use of the NV, many occupants kept their windows closed. Keeping windows open or closed was significantly affected by outdoor climate condition and air pollution levels, especially during the wild-fire period.