Individual-based insight into occupants' interaction with windows in apartments in Beijing

Window opening plays a decisive role in indoor environments in residential buildings. To date great efforts have been conducted to explore the driving characteristics of window opening behavior based on a group of samples. In this context, at the level of one individual residential unit, more understanding of occupant interactions with windows is still required. Based on one-year field measurements of indoor and outdoor environmental parameters and window status of three apartments in Beijing and semi-structured interviews with occupants, this study provides an engineering and sociological analysis of the realistic characteristics of window opening behavior during the heating, transition, and cooling seasons for each apartment. These single apartment-based findings show that window opening is a complex occupant behavior under the combined influence of numerous environmental and non-environmental factors, which cannot be exhaustively listed. Moreover, the environmental and non-environmental factors interact with each other on their impacts on window opening behavior, and the interaction between the two kinds of factors is difficult to quantify. It is thus difficult to generalize the driving characteristics of window opening even based on window state transitions. Also due to this, window opening exhibited significant individual differences among these apartments. Nevertheless, it is more important to note that the indoor environment of these apartments, regulated only by opening the window, is statistically the same during the transition season. Based on thermal adaptive approach, these environmental outcomes illustrate that the indoor environment regulated by window airing alone can represent the environments acceptable to occupants under natural ventilation. Accordingly, comprehensively accurate investigation of the driving characteristics of window opening behavior would not be practical. In this context, this study suggests that a probabilistic model of window states is necessary to describe window opening behavior when focusing on window states and their effects on indoor environment. As long as the simulated indoor environment is guaranteed to be acceptable to occupants, the inferred model based on window state can be considered to be appropriate. More importantly, based on these new insights, this study presents a new research perspective compared to existing studies on occupants’ interaction with windows. It will contribute to more comprehensive understanding about the environments acceptable to occupants under natural ventilation, and more accurate predictions of indoor environments and energy consumptions in the real buildings, and thereby enhancing the application values of the study about occupants' interaction with windows.