Open access peer-reviewed chapter
Abstract
Adverse thermal conditions alter the indoor habitability and, consequently, the occupants’ health, performance, mood, and comfort. Although there are local regulations that provide thermal indicators for the indoor architectural design, these are usually unrelated to the climate, type of construction project, and psychophysiological adaptation of people. In this way, this chapter shows the thermal comfort ranges estimated from the thermal environment’s physical variables, using the adaptive approach, for Ensenada City, Mexico (temperate-dry bioclimate). Surveys were applied to collect the subjective perception simultaneously with the measurement of black globe temperature, air temperature, relative humidity, and wind speed. Study sample was made up from students of a public university whose activity level is sedentary (1.2 met) and clothing is light (0.7 clo). The survey was designed based on the ISO 10551 and ANSI/ASHRAE 55 standards, while the physical measurement instruments were selected based on ISO 7726, managing to generate a class I database. The study was correlational and statistically analyzed with 3750 surveys from the average by thermal sensation intervals method. 16 comfort ranges were quantitatively and graphically estimated from the four physical variables analyzed in each of the four representative thermal periods of the city. These indicators offer objective knowledge for proper decision-making during the architectural design process and therefore for the thermal-energy efficiency of buildings.
Keywords
- adaptive approach
- adaptive thermal comfort
- field study
- indoor thermal comfort
- measurement of environmental variables
- psychophysiological adaptation
- surveys
1. Introduction
The adverse conditions of the thermal environment can cause a direct affectation on the well-being, efficiency, and comfort of people. Studying this phenomenon from the adaptive approach allows obtaining quantitative estimates that respond to the thermal adaptation that people present to the local climate. The particular study of this phenomenon is caused by the need to have local thermal indicators that derive directly from the specific conditions of the climate, type of construction project, and psychophysiological adaptation of the inhabitants, since the architectural design is regularly based on local regulations that present a partial or total disconnection of the thermal parameters that promote the effective habitability of the spaces. However, there are national [1] and international [2, 3, 4, 5, 6] standards that establish the technical and methodological bases to estimate these thermal indicators based on the local particularities of each case. At the same time, different authors [7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34] have developed universal thermal comfort models [7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24] of graphic, mathematical, computer, or algorithmic type, which offer an approach to local thermal comfort [25, 26, 27, 28, 29, 30, 31, 32, 33, 34] from outdoor weather and some endogenous factors of people (activity level and clothing).
So, the literature that documents this physical phenomenon [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34] indicates that the mean radiant temperature, air temperature, relative humidity, and wind speed are the thermal environment’s physical variables that present the greatest impact on the subjective perception that people manifest of the immediate environment, in addition to clothing and activity level.
However, the people’s adaptation to the thermal environment also represents a contribution to the effective estimation of thermal comfort. Thermal adaptation is “the gradual decrease in the organism’s response to repeated exposures to stimuli received from a specific environment” [35]. Therefore, the people’s thermal perception depends on the physical and psychological sensations generated by the thermal environment, activity level, clothing, experience (thermal history), expectation, mean outdoor temperature, and time spent in the space [36].
Therefore, this chapter presents the adaptive thermal comfort estimated from the thermal environment’s physical variables for the four representative thermal periods of Ensenada City, Mexico: cold period (December–March), thermal transition from the cold period to the warm period (April–June), warm period (July–September), and thermal transition from the warm period to the cold period (October–November). Additionally, it presents the adaptation actions taken by the people to get thermal comfort during these periods.
2. Methodology
The methodology is made up of the following sections: (1) Case study and target population, (2) Study periods, (3) Population sample, (4) Qualitative measurement instrument, (5) Environmental variables and physical measurement equipment, (6) Application of surveys, and (7) Data analysis.
2.1 Case study and target population
The study was carried out in Ensenada City, Mexico, geographically located at 31° 52′ latitude, −116° 40′ longitude, and 18 masl altitude [37] (Figure 1). The climate is extreme dry (BS0 ks(e)) [38], and bioclimate is temperate-dry [39]; the air temperature (AT) is 17.3°C, relative humidity (RH) is 75.8%, total rainfall (RF) is 217.3 mm, and the wind speed (WS) is 2.5 m/s, during a normalized year [40, 41].
Figure 1.
The target population was made up of students from the Autonomous University of Baja California (UABC, acronym in Spanish), who present the following characteristics: age between 18 and 23 years, minimum time of residence in Ensenada City of 1 year, sedentary activity (1.2 met) [5], and moderate clothing (1.0 clo) [2].
2.2 Study periods
The study was carried out in the four representative thermal periods of the city’s climate: cold period (December to March), thermal transition from the cold period to the warm period (April to June), warm period (July to September), and thermal transition from the warm period to the cold period (October and November) (Figure 2). Hereinafter, the thermal transition periods will be referred to as thermal transition cold-warm and thermal transition warm-cold, respectively.
Figure 2.
Monthly thermal dynamics in a normalized year for Ensenada City.
In this sense, the average climatic conditions that characterize each study period are presented in Table 1 [40, 41].
| Study period | Descriptors | AT (°C) | RH (%) | WS (m/s) | Rainfall (mm) |
|---|---|---|---|---|---|
| Cold | Average max | 19.2 | 89.5 | 3.5 | |
| Average min | 9.2 | 46.2 | 2.0 | ||
| Thermal transition cold-warm | Average max | 20.1 | 90.9 | 3.7 | |
| Average min | 13.7 | 63.0 | 2.0 | ||
| Warm | Average max | 24.6 | 94.2 | 3.3 | |
| Average min | 18.4 | 69.3 | 1.3 | ||
| Thermal transition warm-cold | Average max | 21.3 | 86.0 | 3.3 | |
| Average min | 11.4 | 44.8 | 1.8 |
Table 1.
2.3 Population sample
The population sample was designed with 95% confidence level and 5% confidence interval. Thus, the sample was estimated at 383 subjects for each study period; however, during the field work, it was possible to collect a sample greater than that required (Table 2). In total, 4153 observations were collected with the four study periods, of which 3750 observations had the certainty required to carry out the data analysis (1887 women and 1863 men).
| Study period | Sample collected | Sample analyzed | Women | Men |
|---|---|---|---|---|
| Cold | 983 | 915 | 458 | 457 |
| Thermal transition cold-warm | 987 | 870 | 476 | 394 |
| Warm | 1365 | 1214 | 572 | 642 |
| Thermal transition warm-cold | 818 | 751 | 381 | 370 |
Table 2.
Stratification of the population sample for each study period and gender.
2.4 Qualitative measurement instrument
The questionnaire was designed according to the one that was used by some referents specialized in the topic [30, 42, 43, 44] and what the national [1] and international [2, 3, 4, 5] standards suggest in this regard. The questions related to the environment’s hygrothermal sensation were based on the seven-point subjective scale shown in the ANSI/ASHRAE 55 [2] and ISO 10551 [3] standards, which was adapted as indicated in Table 3. The questionnaire’s full version can be consulted in Appendix I.
2.5 Environmental variables and physical measurement equipment
Thermal environment’s physical variables measured during the survey were: black-globe temperature (BGT), AT, RH, and WS as well as the clothing and activity level of the subjects. The measurement equipment used was a thermal environment monitor with three sensor arrays (3 M, model QUESTemp 36-3) (Figure 3). This equipment has a resolution of 0.1°C (BGT/AT), 0.1% (RH), and 0.1 m/s (WS); also, it has an accuracy of ±0.5°C (BGT/AT), ± 3.0% (RH), and ± 0.1 m/s (WS) [45]. The selection, distribution, and use of the instruments were carried out based on the ISO 7726 [6] and ANSI/ASHRAE 55 [2] standards, which allowed the creation of a class I database [46].
Figure 3.
Measuring equipment and heights used to measure the physical variables during the surveys.
The evaluation indoor spaces were classrooms, computer rooms, and drawing workshops (Figure 4). When people were seated, the measurement sensors were set at 0.1, 0.6, and 1.1 m from the floor [2, 6]; but when people were semi-seated, the sensor heights were adapted to 0.1, 0.85, and 1.4 m, since it was not possible to consider them as sitting or standing (Figure 3).
Figure 4.
Application of surveys in the evaluation indoor spaces.
2.6 Application of surveys
The surveys were applied in three-story buildings, built with concrete blocks and naturally ventilated (in isolated cases, natural ventilation was supplemented with air circulator fans). With this, the systematic procedure followed in the application of surveys is represented in Figure 5.
Figure 5.
Systematic procedure with which the field surveys were applied.
2.7 Data analysis
The collected data was analyzed by the averages for thermal sensation intervals (ATSI) method [47, 48]. This method groups the comfort votes by thermal sensation (TS) category to obtain the arithmetic mean of the physical variable registered in each of them and adds and subtracts ±2 standard deviation (SD) to each case in order to estimate the comfort range. Subsequently, it allows graphing the data pairs and plotting the simple linear regression: The neutral temperature (Nt) and comfort range (Cr) result from crossing them and the TS category number four.
Figure 6 exemplifies the statistical analysis by ATSI method to estimate thermal comfort by thermal environment’s physical variable (neutral value and comfort range limits). Therefore, this data analysis had to be carried out 16 consecutive times: four physical variables (BGT, AT, RH, and WS) analyzed in each of the four study periods (cold, warm, and two thermal transition periods).
Figure 6.
Data analysis by ATSI method. This example only represents the analysis of BGT-TS, for the cold period.
3. Results
The influence exerted by each thermal environment’s physical variable on the TS was determined by the coefficient of determination (r2). This allowed us to identify that BGT is the physical variable with the greatest influence on the TS, followed by AT, RH, and WS, respectively; thus, the results obtained are presented in this order. For this, Table 4 shows the neutral value and comfort range of each thermal environment’s physical variable to achieve and maintain the indoor thermal comfort in Ensenada City, México, throughout the year.
| Study period | Values description | Neutral value and comfort range | |||
|---|---|---|---|---|---|
| BGT (°C) | AT (°C) | RH (%) | WS (m/s) | ||
| Cold | Upper limit | 24.0 | 23.8 | 95.4 | 0.09 |
| Lower limit | 17.2 | 16.8 | 27.5 | 0.00 | |
| Thermal transition cold-warm | Upper limit | 24.5 | 22.7 | 83.7 | 0.22 |
| Lower limit | 18.6 | 17.7 | 57.6 | 0.00 | |
| Warm | Upper limit | 26.6 | 25.3 | 87.9 | 0.36 |
| Lower limit | 22.4 | 20.9 | 60.2 | 0.00 | |
| Thermal transition warm-cold | Upper limit | 25.9 | 25.7 | 80.0 | 0.11 |
| Lower limit | 20.1 | 19.7 | 38.1 | 0.00 | |
Table 4.
Thermal comfort from thermal environment’s physical variable for each study period.
3.1 Thermal comfort from black globe temperature
According to Figure 7, thermal comfort from BGT is defined by a Nt of 20.6°C and a Cr of 17.2–24.0°C (thermal amplitude [Ta] of 6.8°C) for the cold period, a Nt of 21.5°C and a Cr of 18.6–24.5°C (Ta of 5.9°C) for the thermal transition cold-warm, a Nt of 24.5°C and a Cr of 22.4–26.6°C (Ta of 4.2°C) for the warm period, and a Nt of 23.0°C and a Cr of 20.1–25.9°C (Ta of 5.8°C) for the thermal transition warm-cold. In all cases, the upper and lower limits of the comfort range were equidistant from the Nt, which allows us to notice the same level of adaptation and tolerance at temperatures both above and below the Nt, establishing a thermal symmetry in each study period.
Figure 7.
Thermal comfort from BGT for each study period, contrasted with the thermal conditions of Ensenada City.
Additionally, the thermal dynamics that the comfort ranges present throughout the year suggests the psychophysiological adaptation by the subjects to achieve and maintain thermal comfort in view of the outdoor thermal conditions that occur in each study period (given the close relationship between naturally ventilated indoor and outdoor weather [36, 49, 50]). Therefore, due to outdoor thermal conditions of the cold and warm periods, the comfort ranges for these periods resulted with the extreme values of the annual thermal dynamics, presenting the greatest thermal amplitude in the cold period (6.8°C) and the lowest thermal amplitude in the warm period (4.2°C); in contrast, the comfort ranges of the thermal transition periods presented thermal amplitudes equivalent to each other (5.9°C) and intermediate to the thermal amplitudes of the aforementioned periods. It is noteworthy in this last case that, although both periods are of thermal transition, each one presents specific magnitudes due to the direct and differentiated influence that the previous and subsequent thermal periods exert on each one of them (cold > warm; warm > cold), which would be equivalent to the thermal history and thermal expectation, respectively [36, 49, 50].
The above is attributed to the set of actions that people actively carry out to eventually achieve thermal comfort (opening and closing doors and windows, having drinks, using accessories or ventilation devices, etc.) as well as the level of clothing and the expectation generated in view of the approach of the next thermal period, achieving an efficient performance of their activities and favorable thermal conditions for their well-being.
Finally, the contextualization of these comfort ranges in the normalized conditions of the city (Table 1) allows us to identify the constant heating requirement throughout the year to achieve thermal comfort for people since only during the afternoons of each day, conditions that contribute to achieving thermal comfort occur naturally; however, during the rest of day (night, early morning, and morning), cold conditions occur (Figure 7).
3.2 Thermal comfort from air temperature
Thermal comfort from AT shown in Figure 8 is defined by a Nt of 20.3°C and a Cr of 16.8–23.8°C (Ta of 7.0°C) for the cold period, a Nt of 20.2°C and a Cr of 17.7–22.7°C (Ta of 5.0°C) for the thermal transition cold-warm, a Nt of 23.1°C and a Cr of 20.9–25.3°C (Ta of 4.4°C) for the warm period, and a Nt of 22.6°C and a Cr of 19.7–25.7°C (Ta of 6.0°C) for the thermal transition warm-cold. As with the thermal comfort by BGT, in practically all cases, the upper and lower limits of the comfort range were equidistant from the Nt, which shows the same adaptation and tolerance at temperatures both above and below the Nt.
Figure 8.
Thermal comfort from AT for each study period, contrasted with the thermal conditions of Ensenada City.
In this case, the thermal dynamics presented by the comfort ranges throughout the year is similar to that presented by the BGT comfort ranges, making visible the psychophysiological adaptation to achieve and maintain thermal comfort in view of the outdoor thermal conditions.
Therefore, again, the comfort ranges estimated for the cold and warm periods are the extremes of the annual thermal dynamics, presenting the highest thermal amplitude in the cold period (7.0°C) and the lowest thermal amplitude in the period warm (4.4°C); on the other hand, the thermal amplitude in the thermal transition periods remained intermediate to the aforementioned thermal amplitudes, evidencing a greater thermal amplitude in the thermal transition warm-cold (6.0°C) than in the thermal transition cold-warm (5.0°C). The analysis of this physical variable (AT) allows us to again identify the particularity of the thermal requirements for each thermal transition period, due to the influence exerted on them by the previous and subsequent thermal periods (cold>warm; warm>cold).
However, these comfort ranges contextualized in normalized climate of the city (Table 1) allow us to identify the constant heating requirement throughout the year to achieve thermal comfort since practically nights, early mornings, and mornings are cold (Figure 8), which could be solved with the architectural envelope of the buildings (shape, orientation, construction materials, thermal insulation, dimensions, heights, window-wall ratio, etc.) and voluntary/involuntary actions that contribute to the adaptation of the subjects to the immediate environment. It should be noted that the combination of the BGT/AT with the RH and the WS accentuates the thermal sensation of the subjects throughout the year: in the warm period, the RH influences so that the weather is perceived as warmer and muggier, while in the cold period, the WS influences so that the weather is perceived as colder.
In summary, the annual thermal dynamics obtained with the thermal comfort from BGT is practically the same as that presented with the estimation of thermal comfort from AT, although with slightly higher values due to radiant temperature identified in the first case.
3.3 Thermal comfort from relative humidity
Thermal comfort from RH is defined by a neutral relative humidity (Nrh) of 60.8% and a Cr of 27.5–95.4% (hygric amplitude [Ha] of 67.9%) for the cold period, a Nrh of 70.4% and a Cr of 57.6–83.7% (Ha of 26.1%) for the thermal transition cold-warm, a Nrh of 74.1% and a Cr of 60.2–87.9% (Ha of 27.7%) for the warm period, and a Nrh of 57.7% and a Cr of 38.1–80.0% (Ha of 41.9%) for the thermal transition warm-cold (Figure 9). In none of the cases were the upper and lower limits of the comfort range equidistant from the Nrh, which means an asymmetric adaptation and tolerance by the subjects to humidity both above and below the Nrh. The Ha of the cold period is the largest of the annual hygric dynamics, in correspondence with the rainy season in the city, while the warm period presents the second-lowest Ha (but with values higher than 60.2%), due to the thermal damping required to minimize the thermal oscillation. It is noteworthy how the similarity with which the hygric values of the thermal transition cold-warm resulted with respect to those of the warm period.
Figure 9.
Thermal comfort from RH for each study period, contrasted with the hygric conditions of Ensenada City.
Based on the hygric dynamics presented by the comfort ranges, it is possible to observe the psychophysiological adaptation that the subjects adopt to achieve and maintain indoor thermal comfort, which is linked to outdoor weather through natural ventilation [36, 49, 50]. In addition, from hygric amplitude with which each comfort range was estimated, the specific humidity requirements in each period can be determined to achieve thermal comfort, regardless of the outdoor hygric conditions. In other words, the hygric dynamics presented by the estimated comfort ranges are not linked to the hygric dynamics of Ensenada City but rather to the necessary requirements to achieve and maintain thermal comfort.
In this sense, Figure 9 allows us to identify that the lower limit of the comfort ranges is less than the average minimum humidity that occurs outdoors in each period (Table 1), which indicates that the subjects would require a drier indoor environment to achieve thermal comfort during afternoons. Similarly, the upper limit of the comfort ranges in all periods, except in the cold period, is less than the average maximum humidity that occurs outdoors (Table 1), which again indicates the need for drier indoor environments during the mornings to achieve thermal comfort.
3.4 Thermal comfort from wind speed
Thermal comfort from WS is defined by a neutral wind speed (Nws) of 0.02 m/s and a Cr of 0.00–0.09 m/s (wind amplitude [Wa] of 0.09 m/s) for the cold period, a Nws of 0.11 m/s and a Cr of 0.00–0.22 m/s (Wa of 0.22 m/s) for the thermal transition cold-warm, a Nws of 0.17 m/s and a Cr of 0.00–0.36 m/s (Wa of 0.36 m/s) for the warm period, and a Nws of 0.01 m/s and a Cr of 0.00–0.11 m/s (Wa of 0.11 m/s) for the thermal transition warm-cold (Figure 10). Based on strictly statistical analysis, in all cases, the upper and lower limits of the comfort range were equidistant from the Nws; however, from the climatic point of view, the airflow does not present negative values in the same direction, so they were replaced by 0.00 m/s. Thus, the limits of the comfort range were not equidistant from the Nws, which allows us to notice, from a phenomenological interpretation, a variable adaptation and tolerance at wind speeds both above and below the Nws, thus establishing a wind asymmetry in each study periods.
Figure 10.
Thermal comfort from WS for each study period.
The wind dynamics presented by the comfort ranges derives from the wind requirements necessary to achieve thermal comfort, and not from the annual wind dynamics that occurs in Ensenada City. According to Table 1, the minimum WS in this case is 1.3 m/s, a speed above that required to achieve indoor thermal comfort. In this sense, and based on Figure 10, it is possible to appreciate that in the cold period, the lowest comfort range of the year (0.09 m/s) is required in order to preserve thermal comfort, avoid heat loss due to wind, and promote the cyclic air renewal; in contrast, the opposite occurs in the warm period; the highest comfort range (0.36 m/s) is required in order to achieve thermal comfort and promote heat loss during the afternoons. For its part, the comfort range estimated for thermal transitions resulted with an intermediate magnitude to those mentioned above, which, in addition, in each case, responds to the extreme thermal period to be transited (thermal expectation [36, 49, 50]); that is, the WS required for the thermal transition cold-warm (0.22 m/s) is greater than that required for the thermal transition warm-cold (0.11 m/s), corresponding to the approaching thermal period.
This requires strict control of natural ventilation in indoor spaces in order to reduce the risk of losing or gaining excessive heat and thus altering the thermal comfort achieved in each period.
The dynamics presented by the wind comfort ranges throughout the year also allows us to notice the psychophysiological adaptation that the subjects adopt to achieve thermal comfort in view of the direct influence of the outdoor weather (due to the close relationship between naturally ventilated indoor spaces and the outdoor weather [36, 49, 50]). The above supports the behavioral actions that subjects actively carry out to modify their immediate environment and clothing level to eventually achieve thermal comfort (opening/closing doors and windows, manual/mechanical ventilation, clothing, etc.), as well as the expectation that they generate in view of the approach of the next thermal period, getting an efficient performance and favorable thermal conditions for their well-being.
It is worth mentioning that with the wind analysis, the comfort ranges were not contrasted with the wind characterization for Ensenada city (Figure 10), since the minimum wind speed that occurs in this one is 1.3 m/s (Table 1), a speed well above that required in indoor spaces [16]. This suggests once again that wind control through windows, doors, and any opening is crucial to preserve indoor thermal comfort.
4. Conclusion
Thermal comfort is the eventual condition of people in which their psychophysiological perception achieves a balance with the immediate thermal environment, promoting a prolonged stay in the space, the efficient performance of their activities, and favorable conditions for their well-being in the short and medium terms. In spaces with a direct relationship to the outdoor, this phenomenon is mainly influenced by the environment’s physical conditions; therefore, in order to preserve it, the active adaptation of subjects is decisive (e.g., conscious/unconscious attitudinal actions to partially and cyclically modify the immediate environment, their person, and their expectations).
In this sense, thermal comfort estimated from the adaptive approach for indoor spaces in Ensenada City, Mexico, is presented from the thermal environment’s physical variables in Table 4; from BGT, in Figure 7; from AT, in Figure 8; from RH, in Figure 9; and, from WS, in Figure 10. The previous order represents the hierarchy with which the thermal environment’s physical variables influenced the thermal sensation of subjects.
From the comfort ranges estimated for each study period, it was possible to appreciate the similarity of the annual thermal dynamics of the BGT with respect to the annual thermal dynamics of the AT. The slight variations presented are due to the factors that conceive each physical variable at each moment, which are less than 0.4°C in the thermal transition warm-cold and cold period and less than 1.8°C in the thermal transition cold-warm and warm period. In both cases, the estimated thermal comfort shows a constant heating requirement during the nights, early mornings, and mornings of the day, since the outdoor climatic of Ensenada city only cover this requirement during the afternoons; however, the thermal dynamics obtained with the BGT/AT comfort ranges have a strong relationship with the outdoor thermal dynamics by showing a similar behavior.
Subjects’ tolerance to both magnitudes above and below the neutral value in each physical variable (BGT, AT, RH, and WS) is symmetric, since, in general, it is equidistant to the Nt, Nrh, and Nws. This allows us to deduce that subjects present the same level of acceptance to both magnitudes higher than and lower than the neutrality value, as long as the limits of the comfort range are not exceeded in each case.
Thermal transition periods present comfort ranges that are different from each other for each physical variable analyzed. This is due to the dependence that each one shows with respect to the thermal period from which they leave and to which they are approaching so that, although both periods are of thermal transition, each one presents comfort ranges with independent requirements.
Comfort ranges estimated with this study allow us to appreciate the adjustment that the subjects’ thermal sensation adopts with the dynamics that the outdoor climate presents, motivating them to constantly search for psychophysiological adaptation that allows them to achieve local thermal comfort.
When the thermal environment presents continuous variability, the subjects carry out voluntary/involuntary actions that allow them to recover the thermal balance between the immediate environment and their organism. Common adaptation actions are: changing the clothing level, having drinks, changing position, mobility, shelter in a microclimate that promotes prompt acclimatization, use of natural conditioning devices (doors/windows), and eventual use of artificial conditioning mechanical devices.
Thus, thermal comfort estimated with this study derives from the group’s thermal perception of the analyzed sample, which makes it possible to guarantee the adequate correspondence between the estimated thermal ranges and each of the study periods. These comfort ranges by physical variable represent local design parameters that, if considered during the conceptualization of the city’s architectural projects, will directly impact the indoor habitability, the efficiency of the conditioning equipment, thermal comfort and the performance of the occupants, energy performance of buildings, passive architectural design, and sustainability, for example.
The results obtained with this study have a local scope and derive exclusively from the climate and population of Ensenada City, Mexico; however, they can be comparative references of other studies developed in similar physical conditions or a related area of knowledge.
Acknowledgments
Special thanks to Program for Teacher Professional Development (PRODEP, acronym in Spanish), Mexico, for funding the project “Indoor thermal comfort: A study in the temperate-dry bioclimate in Ensenada, Baja California”, code UABC-PTC-607, within the call for support for the incorporation of
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