A multilevel window state model based on outdoor environmental conditions that captures behavioural variation at room and apartment levels

• Published in: Energy and buildings Vol. 277; p. 112562
• Main Authors: Wang, Yan, Cooper, Elizabeth, Tahmasebi, Farhang, Chalabi, Zaid, Stamp, Samuel, Burman, Esfandiar, Mumovic, Dejan
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.12.2022
• Subjects: Behavioural diversity; Environmental factors; Multilevel modelling; Residential buildings; Window open state; Environmental factors; Behavioural diversity; Residential buildings; Window open state; Multilevel modelling
• ISSN: 0378-7788
• DOI: 10.1016/j.enbuild.2022.112562

•Between-room variation in the effect of outdoor conditions on window openings was significant.•Between-flat variation in the effect of outdoor conditions on window openings was not significant.•The room type did not significantly affect occupants’ window opening behaviour.•The developed model accounted for hierarchical data structure in occupant behaviour. Occupants’ use of windows can influence the building energy demand, thermal conditions and indoor air quality. Researchers have made substantial efforts to develop probabilistic models to predict the window open/closed state. However, the hierarchical data structure and the heterogeneity in occupant behaviour have been generally neglected in previous modelling efforts. Multilevel modelling can provide an appropriate framework to handle this type of data structure and variability, but this method has rarely been used in the field. This study investigated room- and apartment-level variations in the effects of outdoor environmental variables on the window open state in low-energy apartment buildings in the UK using a multilevel modelling approach. The results showed that the room-level, rather than apartment-level, variation was statistically significant. Meanwhile, the room type (i.e., living room or bedroom) did not significantly affect the relationship between outdoor environmental variables and the window open state. The strength of this study is that the modelling accounted for the hierarchical structure of the data by simultaneously considering room-and apartment- level behavioural variations. By quantifying the significant diversity of occupant behaviour in the natural ventilation of residences, future research can more accurately estimate the variation in building energy and indoor air quality impacts.