## 2 Methods  
This work is part of an ongoing effort to perform electronic surveys in order to populate a database on common occupant behaviors related to their indoor home environments [13]. The electronic data collection method followed an easy to implement and repeat process with a low time-cost burden. It was based on an online electronic survey with 10 questions (Figure 10), which was circulated and completed by one occupant in each dwelling located around the country. This way, it was possible to generate a database that could be easily enriched over time and capture trends and occupant responses on popular energy conservation measures, typical trends for operating conditions and other variables. The information on the occupant behavior could then be used to derive empirical adaptation factors for bridging the gap between the calculated and actual energy use by making more realistic estimates for building stock modeling. Figure 4 illustrates the overall process of the method, and the main steps are elaborated next. The selection of the sample was not targeted in any prescriptive manner, since participation in the occupant surveys was open and voluntary. The effort prioritized data analysis from dwellings with available actual energy use data (e.g., utilities and other energy use records). The relevant data were solicited from energy auditors who were active in energy audits, participants in postgraduate educational seminars and relevant courses that included practical projects and other professional networks. The electronic occupant questionnaire was completed once for every household. The focus of the work reported here was on how occupants actually operated the heating systems in single-family houses (SFHs) and multi-family houses (MFHs). The surveys (Figure 10) collected information about the energy conservation measures that were implemented or other energy-related actions that may have been adopted by the occupants for reducing the operational energy of their dwellings. Additional information included the occupant's common practices in terms of regulating the operation of their dwellings' heating systems (in terms of time and temperature setpoints), the usable heated spaces and an overall assessment of their home indoor thermal comfort conditions. The empirical adaptation factors were calculated as the ratio of the actual to the corresponding normative value used in the calculations (i.e., _f(Actual/Calculated)_). Specifically, the work considered the most relevant parameters that impact space heating, which remains the most significant energy end use in dwellings, including the following:  
* Operating hours, depending on how long the occupants operated the central or local heating systems in their dwellings, while the normative calculations typically considered almost continuous operation outside of sleeping hours (i.e., more than 16 h);
* Heated floor area, depending on the spaces (rooms) that the occupants made use of and heated, while the normative calculations typically considered the entire livable floor area of a dwelling to be covered by the space heating system (i.e., no isolated spaces (rooms));
* Indoor temperature setpoint, depending on the day and night temperature that occupants adjusted the space thermostat of a central heating system to or the control of a local unit, while the normative calculations typically considered a constant temperature of 20 \({}^{\circ}\)C;
* Thermal comfort, depending on the prevailing indoor conditions and other personal perceptions. This was an overall assessment of the seasonal indoor thermal conditions as perceived by the occupants (e.g., comfortable, cool or cold). For example, considering the heated floor area of a dwelling, occupants may isolate 20% of their livable space that is not typically heated. Compared with the normative calculations that considered the total useable floor area of a dwelling as being heated, the adaptation factor would be 0.8 or 80%.