An Inverse Model-based Approach to Estimate Air Infiltration in Commercial Buildings using Occupant-generated CO2 and Humidity

Monitoring air infiltration continuously is of great importance to detect building envelope degradation over time. However, environmental factors often make the accurate measurement of air infiltration challenging. Further, fan pressurization and tracer gas tests possess certain drawbacks limiting their applicability in commercial buildings. Thus, this research proposes a low-cost inverse model-based approach for estimating infiltration rates by using existing carbon dioxide (CO2) and humidity data. The laboratory tracer gas tests were carried out to explore the effectiveness of replacing sulphur hexafluoride (SF6) with CO2. A field study was conducted using both CO2 and water vapour. The historical CO2 and humidity data were also used to train the model. At last, air handling unit (AHU) return air CO2 concentration data were utilized to demonstrate this novel approach. The results indicated that the proposed method could conveniently lend itself to estimate air infiltration rates at a reasonable accuracy using existing sensor data.