Figure 2
Locations and features of selected buildings participating in the qualitative survey
Figure 3
Adaptive behavior for heat discomfort and respondents’ illustrative comments
Figure 4
Adaptive behavior for cold discomfort and respondents’ illustrative comments
Figure 5
Reasons for opening windows, adjusting shade devices and using fans, AC, and heating in the qualitative survey
Figure 6
Monthly temperature (maximum, average, minimum), relative humidity, and monthly energy consumption (average, maximum, minimum) for 2019
Figure 7
Monthly energy consumption by residence in the qualitative survey sample
Figure 8
Comparison of education level (A) (B) and income (C) (D) between this study and IBGE data
Figure 9
Number of residents per home
Figure 10
Age distribution by number of residents per home
Figure 11
Distribution of apartments by number of bedrooms and floor level
Figure 12
Occupant perception of sunlight exposure and apartment ventilation
Figure 13
Thermal comfort perception for summer and winter
Figure 14
Occupancy patterns: average (A) average, and occupancy 1 (B), occupancy 2 (C), occupancy 3 (D), and occupancy 4 (E)
Figure 15
Adaptive behavior for heat (A) and cold thermal (B) discomfort
Figure 16
Window (A), blind (B), and shutter (C) operations
Figure 17
Reason for opening windows (A) and shutters (B) and for closing windows (c) and shutters (D)
Figure 18
Fan (A) and AC (B) and (C) use for cooling
Figure 19
Reason for using a fan (A) and AC (B) (C) for cooling
Figure 20
Use of heater (A) and AC (B) for heating
Figure 21
Reason for using heating (A) and AC (A) for heating
Figure 22
Months of air-conditioning use for cooling and heating, average monthly dry bulb temperature for 2019, and comfort zone
Figure 23
Cooling (A) and heating (B) setpoint ranges
Figure 24
Equipment ownership among respondents
Figure 25
Daytime use of artificial lighting in rooms (A), during the day (B) and the night (C)
Figure 26
Total energy consumption versus temperature
Figure 27
Average (A) and boxplot (B) of energy consumption per capita versus temperature
Figure 28
Correlation between observed and predicted annual energy consumption
Figure 29
Grouping dendrogram – Average
Figure 30
Typical behavior profiles
Figure 31
Annual energy consumption for typical profiles
Figure 16
Window (A), blind (B), and shutter (C) operations
Figure 17
Reason for opening windows (A) and shutters (B) and for closing windows (c) and shutters (D)
Figure 18
Fan (A) and AC (B) and (C) use for cooling
Figure 19
Reason for using a fan (A) and AC (B) (C) for cooling
Figure 20
Use of heater (A) and AC (B) for heating
Figure 21
Reason for using heating (A) and AC (A) for heating
Figure 22
Months of air-conditioning use for cooling and heating, average monthly dry bulb temperature for 2019, and comfort zone
Figure 23
Cooling (A) and heating (B) setpoint ranges
Figure 24
Equipment ownership among respondents
Figure 25
Daytime use of artificial lighting in rooms (A), during the day (B) and the night (C)
Figure 26
Total energy consumption versus temperature
Figure 27
Average (A) and boxplot (B) of energy consumption per capita versus temperature
Figure 28
Correlation between observed and predicted annual energy consumption
Figure 29
Grouping dendrogram – Average
Figure 30
Typical behavior profiles
Figure 31
Annual energy consumption for typical profiles
Table 1
Monthly mean, maximum, and minimum temperatures, and rainfall in Santa Maria, Brazil
Table 2
Comparison between adaptive behavior and contextual factors
Table 3
Comparison of equipment use patterns and contextual factors
Table 4
Number of months of air-conditioning use (cooling) and contextual factors
Table 5
Number of months of air-conditioning use (heating) and contextual factors
Table 6
Setpoint and contextual factors
Table 7
Detailed survey: Respondent characteristics
Table 8
Energy consumption and number of residents
Table 9
Linear regression model for energy consumption
Table 10
Typical profile behavior according to the studied groups