H.B.Gunay et al.Building and Environment 70 (2013)31-47 33 the observations and develops recommendations that will incor- parameters,despite their importance being qualitatively acknowl- porate the bias introduced by these factors. edged,have not been included in the reviewed literature.Haldi and Robinson [46]suggested building statistical models that incorpo- 2.1.Behaviors that adapt the indoor environment rate non-temperature physical variables as predictors as a future research effort.However,as window openings connect the ambient Occupants adapt their indoor environment with their alter- conditions to the indoor environment,the type of the window ations to operable windows and window shading devices,lights. opening can also play a significant role on the occupant's prefer- fans,carpets,and thermostats.Various research projects have ences.For example,bottom hung inside opening windows provide conducted observational studies where they investigated these weather protection[22.Thus,in this case,wind and rain may be adaptive behaviors using a variety of methods.This section pre- discarded from the monitored variables.But for the side hung or sents these methodologies and discusses the limitations and sliding windows,it may be more appropriate to include the associated challenges. weather variables to the monitored variables. Similarly,to predict a window shade deployment model,indoor 2.1.1.Physical variables variables,such as indoor temperature 29,32,47,49,indoor daylight Researchers have either used their prior knowledge on the 29,32,47,49,50],transmitted solar radiation [29,32,50,51]:and observed system or they carried out questionnaire surveys to nar- outdoor variables,such as outdoor temperature [39,47]and row down the variables that should be measured,such as tem- external solar radiation [49.50,52-54].have been monitored. perature,relative humidity(RH),noise,and workplane illuminance. Zhang and Barrett [47]observed that window shade deployment so that the adaptive occupant behaviors can be predicted with did not follow the outdoor temperature.Arguably.Lindsay and these monitored variables.For example,Inkarojrit [29]carried out a Littlefair [52]and Foster and Oreszczyn55]claimed that indoor survey to identify the main motivations for closing window blinds temperature and external solar radiation cannot be a predictor in private offices.In this study,it was reported that the majority of variable for the window shade deployment.Also,Reinhart [56 occupants who closed their blinds do so to protect their worksta- used only visual/optical variables that may lead to blind lowering. tions and screens from direct or reflected glare from sunlight,while A reasonable explanation for this controversy is that occupants use 27.4%of the participants claimed that they use their blinds to window shades to mitigate both visual and thermal discomfort reduce the heat from the sun and only 12.3%stated privacy and (excluding the non-physical factors such as view or privacy).which security as a reason for blind closure.Eilers et al.[30]surveyed can be caused by temperature,solar radiation,glare,et cetera. office occupants and confirmed that the majority of the subjects Clearly,it is crucial to monitor independent variables that can who closed their blinds do so to reduce the glare on their computer represent the window shade deployment.Reviewed literature screen.Similarly.Warren and Parkins [31]carried out a survey in suggests that these variables are:the depth of penetration of the which occupants stated that lAQ was the main reason for opening direct sunlight as a function of the solar altitude [47,51,57]and glare windows during the heating season and noise was the main reason 52,58,59].Inoue et al.[51]suggested that the depth of penetration for closing windows during the summer season.These surveys, of direct sunlight changes with the mean blind occlusion.This when used prior to the physical measurements,can give pre- observation was later confirmed by Reinhart and Voss [57]with a liminary insight into determining the variables that should be theoretical solar penetration depth measured from the top of the measured and the spatial distribution of sensors that will be placed window.Subsequently,Reinhart and Wienold 60]performed in the office during a study.Furthermore,it can be used to identify representative daylight design strategies that incorporate occu- the subtleties that are difficult to measure (e.g.rattling blinds pants'reaction against direct sunlight and glare. caused by wind passing over deployed venetian blinds)before starting the data collection 32]. 2.1.2.Non-physical parameters Early studies on the window opening behavior started by Physical variables (i.e.thermal,visual,acoustic,indoor air monitoring the outdoor variables [31.33-36]with the following environment)influence the chance that an office occupant will reasoning:(1)once these observations are integrated to BPS as experience discomfort.However,it is his/her social,economic,and occupant models the indoor variables become outputs of the BPS, psychological influences,which are driven by non-physical (i.e. therefore,the indoor variables cannot be more reliable than out- latent)variables that lead to these adaptive actions [61.These non- door variables [37.38];and (2)indoor temperature can be defined physical (latent)variables are parameters that are not measurable as a spatial distribution rather than a single scalar [38]which re- with typical sensors such as view and connection to the outside. quires time consuming and expensive instrumentation of the privacy or daylight-health perception. sensors and data loggers.Subsequently,it was suggested that oc- It is evident that one of the main design purposes of windows is cupants only have an indirect perception of outdoor physical vari- to provide a clear view and physical connection to the outside 60. ables [38].consequently indoor variables (at least the indoor Green building rating systems (e.g.LEED)define a view as "a thermal variables)have been incorporated amongst monitored straight visual connection from an interior point to a point outside variables in many of the recent studies [10,38-41.In particular, through a facade opening located within a certain height range within using a reasonable balance between the indoor and outdoor vari- a facade"[62].Inoue et al.[51]reported that most occupants ables to describe the window opening behavior can be suggested as preferred to have seats close to the windows,however these seats follows:(1)window opening behavior can be described with the were known to be the most susceptible locations to glare and solar indoor variables (e.g.indoor temperature);and (2)window closing radiation.Based on the surveys to study the stimulating factors for behavior can be explained with both indoor and outdoor variables window opening,it was reported that some of the window opening (e.g.indoor and outdoor temperature)[39,42].This would take into behaviors,despite allowing some ambient noise,may be explained account the transmitted effects of the outdoors once the window is to maintain a direct connection to outdoors [63,64].These findings open,while ignoring them once it is closed.Non-temperature can be interpreted as occupants prefer to tolerate some discomfort physical variables that can affect the window opening/closing in order to have a better quality of view and connection to the behavior have been listed as the indoor air quality [31,43-45.the outdoors. outdoor noise level 22.31,46,47],RH39].wind speed and direction Window shading devices may obstruct the view to the outside [22.34,47].and rain [41,47,48].These non-temperature physical Haldi and Robinson[65]carried out a study on window controlthe observations and develops recommendations that will incor￾porate the bias introduced by these factors. 2.1. Behaviors that adapt the indoor environment Occupants adapt their indoor environment with their alter￾ations to operable windows and window shading devices, lights, fans, carpets, and thermostats. Various research projects have conducted observational studies where they investigated these adaptive behaviors using a variety of methods. This section pre￾sents these methodologies and discusses the limitations and associated challenges. 2.1.1. Physical variables Researchers have either used their prior knowledge on the observed system or they carried out questionnaire surveys to nar￾row down the variables that should be measured, such as tem￾perature, relative humidity (RH), noise, and workplane illuminance, so that the adaptive occupant behaviors can be predicted with these monitored variables. For example, Inkarojrit [29] carried out a survey to identify the main motivations for closing window blinds in private offices. In this study, it was reported that the majority of occupants who closed their blinds do so to protect their worksta￾tions and screens from direct or reflected glare from sunlight, while 27.4% of the participants claimed that they use their blinds to reduce the heat from the sun and only 12.3% stated privacy and security as a reason for blind closure. Eilers et al. [30] surveyed office occupants and confirmed that the majority of the subjects who closed their blinds do so to reduce the glare on their computer screen. Similarly, Warren and Parkins [31] carried out a survey in which occupants stated that IAQ was the main reason for opening windows during the heating season and noise was the main reason for closing windows during the summer season. These surveys, when used prior to the physical measurements, can give pre￾liminary insight into determining the variables that should be measured and the spatial distribution of sensors that will be placed in the office during a study. Furthermore, it can be used to identify the subtleties that are difficult to measure (e.g. rattling blinds caused by wind passing over deployed venetian blinds) before starting the data collection [32]. Early studies on the window opening behavior started by monitoring the outdoor variables [31,33e36] with the following reasoning: (1) once these observations are integrated to BPS as occupant models the indoor variables become outputs of the BPS, therefore, the indoor variables cannot be more reliable than out￾door variables [37,38]; and (2) indoor temperature can be defined as a spatial distribution rather than a single scalar [38] which re￾quires time consuming and expensive instrumentation of the sensors and data loggers. Subsequently, it was suggested that oc￾cupants only have an indirect perception of outdoor physical vari￾ables [38], consequently indoor variables (at least the indoor thermal variables) have been incorporated amongst monitored variables in many of the recent studies [10,38e41]. In particular, using a reasonable balance between the indoor and outdoor vari￾ables to describe the window opening behavior can be suggested as follows: (1) window opening behavior can be described with the indoor variables (e.g. indoor temperature); and (2) window closing behavior can be explained with both indoor and outdoor variables (e.g. indoor and outdoor temperature) [39,42]. This would take into account the transmitted effects of the outdoors once the window is open, while ignoring them once it is closed. Non-temperature physical variables that can affect the window opening/closing behavior have been listed as the indoor air quality [31,43e45], the outdoor noise level [22,31,46,47], RH [39], wind speed and direction [22,34,47], and rain [41,47,48]. These non-temperature physical parameters, despite their importance being qualitatively acknowl￾edged, have not been included in the reviewed literature. Haldi and Robinson [46] suggested building statistical models that incorpo￾rate non-temperature physical variables as predictors as a future research effort. However, as window openings connect the ambient conditions to the indoor environment, the type of the window opening can also play a significant role on the occupant’s prefer￾ences. For example, bottom hung inside opening windows provide weather protection [22]. Thus, in this case, wind and rain may be discarded from the monitored variables. But for the side hung or sliding windows, it may be more appropriate to include the weather variables to the monitored variables. Similarly, to predict a window shade deployment model, indoor variables, such as indoor temperature [29,32,47,49], indoor daylight [29,32,47,49,50], transmitted solar radiation [29,32,50,51]; and outdoor variables, such as outdoor temperature [39,47] and external solar radiation [49,50,52e54], have been monitored. Zhang and Barrett [47] observed that window shade deployment did not follow the outdoor temperature. Arguably, Lindsay and Littlefair [52] and Foster and Oreszczyn [55] claimed that indoor temperature and external solar radiation cannot be a predictor variable for the window shade deployment. Also, Reinhart [56] used only visual/optical variables that may lead to blind lowering. A reasonable explanation for this controversy is that occupants use window shades to mitigate both visual and thermal discomfort (excluding the non-physical factors such as view or privacy), which can be caused by temperature, solar radiation, glare, et cetera. Clearly, it is crucial to monitor independent variables that can represent the window shade deployment. Reviewed literature suggests that these variables are: the depth of penetration of the direct sunlight as a function of the solar altitude [47,51,57] and glare [52,58,59]. Inoue et al. [51] suggested that the depth of penetration of direct sunlight changes with the mean blind occlusion. This observation was later confirmed by Reinhart and Voss [57] with a theoretical solar penetration depth measured from the top of the window. Subsequently, Reinhart and Wienold [60] performed representative daylight design strategies that incorporate occu￾pants’ reaction against direct sunlight and glare. 2.1.2. Non-physical parameters Physical variables (i.e. thermal, visual, acoustic, indoor air environment) influence the chance that an office occupant will experience discomfort. However, it is his/her social, economic, and psychological influences, which are driven by non-physical (i.e. latent) variables that lead to these adaptive actions [61]. These non￾physical (latent) variables are parameters that are not measurable with typical sensors such as view and connection to the outside, privacy or daylight-health perception. It is evident that one of the main design purposes of windows is to provide a clear view and physical connection to the outside [60]. Green building rating systems (e.g. LEED) define a view as “a straight visual connection from an interior point to a point outside through a facade opening located within a certain height range within a facade” [62]. Inoue et al. [51] reported that most occupants preferred to have seats close to the windows, however these seats were known to be the most susceptible locations to glare and solar radiation. Based on the surveys to study the stimulating factors for window opening, it was reported that some of the window opening behaviors, despite allowing some ambient noise, may be explained to maintain a direct connection to outdoors [63,64]. These findings can be interpreted as occupants prefer to tolerate some discomfort in order to have a better quality of view and connection to the outdoors. Window shading devices may obstruct the view to the outside. Haldi and Robinson [65] carried out a study on window control H.B. Gunay et al. / Building and Environment 70 (2013) 31e47 33