Abstract

Occupants’ interactions with windows influence both building energy consumption and exposure to airborne pollutants indoors. Occupants’ window opening behavior varies from region to region due to physical environmental factors and social reasons. China is now confronting severe atmospheric pollution, which may affect occupants’ window opening behaviors. A field study was conducted in 8 naturally ventilated residential apartments in Beijing and Nanjing, China. This involved periodically monitoring window states of eight residential apartments within each season from October 2013 to December 2014 by magnetic induction devices (TJHY, CKJM-1). Relationships between the probability of window opening (p) and explanatory variables, including outdoor air temperature (t o), outdoor relative humidity (RH), outdoor wind speed (V s), and ambient PM2.5 (particles with aerodynamic diameter less than 2.5 microns) concentrations (C p), were analyzed. Stochastic models of occupants’ interactions with windows in monitored residences were established via univariate and multivariate linear logistic regression for both cities. According to the results, t o is the most important explanatory variable affecting occupants’ interactions with windows in monitored residences. The best multivariate linear logistic model result from the “backward selection” procedure based on “Akaike Information Criterion” (AIC) includes t o, RH, V s and C p as explanatory variables, which implied that outdoor air quality, represented by C p, has become a concern affecting Chinese residents’ interactions with windows.

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