Window opening behavior of occupants in residential buildings in Beijing

• Published in: Building and environment Vol. 124; pp. 441 - 449
• Main Authors: Yao, Mingyao, Zhao, Bin
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.11.2017; Elsevier BV
• Subjects: Air quality; Air temperature; Building energy; Buildings; Carbon dioxide; Energy consumption; Environmental monitoring; Habits; Indoor air; Indoor air pollution; Indoor air quality; Indoor environments; Influential factors; Particulate matter; Prediction models; Regression analysis; Relative humidity; Residences; Residential areas; Residential buildings; Residential energy; Schedules; Stochastic model; Temperature; Temperature effects; Thermal comfort; Time of use; Wind direction; Wind speed; Windows (intervals); Beijing China; China; Stochastic model; Influential factors; Building energy; Indoor air; Residences
• ISSN: 0360-1323; 1873-684X
• DOI: 10.1016/j.buildenv.2017.08.035

Window opening behavior has a vital influence on indoor air quality, thermal comfort, and energy consumption. In residential buildings, the window opening behavior of occupants may vary considerably owing to different indoor and outdoor environmental parameters and personal habits. In this study, we investigated the factors influencing the window opening behavior of occupants in 19 residences in Beijing by monitoring the open/closed status of windows, and eight environmental parameters, including temperature and relative humidity of indoor and outdoor air, indoor CO2 concentration, outdoor PM2.5 concentration, and outdoor wind speed and direction. The influence of the season and time of day was also analyzed, and typical window operation schedules were determined. Predictive models of the occupants' window opening behavior were established based on multivariate linear logistic regression. The results indicated that outdoor air temperature was the most influential factor, followed by indoor CO2 concentration, indoor air temperature, outdoor and indoor relative humidity, ambient PM2.5 concentrations, and outdoor wind direction and wind speed. •Window states were monitored in 19 residences in Beijing over 4 seasons.•Typical daily window opening and closing schedules were fitted.•The schedules provide key parameters for energy consumption and IAQ assessment.•Stochastic models of occupants' window opening behavior were established.