1. Introduction

2. Literature Review

3. Materials and Methods

3.4. Thermal comfort analysis

An evaluation for thermal comfort analysis included on-site measurements of indoor thermal conditions and a survey of the building users [26]. Nine conditioned rooms were selected for analysis (two classrooms and seven office rooms), as shown in Figure 4. The rooms were selected based on availability, according to the building manager. Both measurements and surveys occurred between November 13 and December 14, 2018, during the transition seasons between spring and summer in Campinas.

3.4.1. On-site measurements

The environmental parameters obtained during the monitoring period were the relative humidity, air and globe thermometer temperatures, and air velocity, with measurements using a microclimate data logger Testo brand digital thermo-hygrometer, model 175-H1; Testo brand digital thermometer, model 175-T2; Testo brand digital anemometer, model 405V. The equipment used was fixed on a tripod with a height of 1.10 cm above the ground to simulate the sitting position of the users and far away from the external walls but near where the user’s seat was. The instruments were shielded from direct solar radiation, cleaned, and calibrated.

The environmental and personal information collected in the buildings was input to evaluate through the Predict Mean Vote (PMV) and Percentage of Dissatisfaction (PPD) calculated by the computer program Comfort 2.03 [41], with the version updated in 2018.

3.4.2. Questionnaires

Table 3. Characteristics of the selected rooms.

Table 3. Characteristics of the selected rooms.

Room	Area (m²)	Floor level	Orientation	Window-to-wall ratio (%)	HVAC	People density (no.)	Number of surveys
CL1	54.4	1st	NW-SE	22.73	S	52	52
CL2	37.1	2nd	SE	22.73	S	45	45
OF1	43.3	1st	SE	22.73	W	3	10
OF2	12.1	1st	SW	77.5	W	4	16
OF3	39.8	1st	SW	77.75	W	5	21
OF4	39.6	1st	NE	77.75	W	3	12
OF5	18.4	1st	NE	77.75	W	3	12
OF6	54.3	1st	SE	17.2	W	4	16
OF7	15.4	2nd	NW	17.2	W	4	16

Note: S refers to split air conditioner equipment, and W refers to window equipment.

3.4.3. Survey study

The survey included a field study involving a set of five buildings that, inside, featured nine selected representative rooms for the thermal comfort study.

These buildings were from the University in Campinas—UNICAMP. The selected rooms used for research were teaching and administrative offices. The research occurred during the transition seasons between spring and summer, a warm time in the city. In Brazil, mechanically heated buildings with access to windows for natural ventilation are typical. Brager and Baker [42] refer to this combination of natural ventilation, window operation, and mechanical systems to provide cooling and obtain thermal comfort as a “Mixed mode.” Therefore, the buildings surveyed function in this way.

During the collection of environmental data, the application of the questionnaire surveys, simultaneously at pre-established times and through observation, aimed to describe the leading construction technologies (windows and doors) and equipment (air-conditioning). The research objective at the University was to describe the real (as built) way of using environments and air conditioning technologies.

The questionnaire encompasses three steps:

Step one: general building information (local, room, time, kind of users, or other).

Step two: the students’ information, such as age, gender, height, and the insulation based on (ASHRAE 55, 2017) [43] clothing vestment (clo) and activity (met).

Step three: evaluate the thermal environment, including the following questions:

Questions about Thermal Preference Vote (PPD) and Thermal Sensations Vote (PMV) in the representative rooms.

Questions:

Q1: What is your thermal sensation at this moment? This references the temperature from -3 cold to +3 hot. It is symmetrical by zero, which is considered neutral, where a person feels comfortable.

Q2: How would you prefer the temperature to be in this environment right now? The reference intensity would be from no change to much warmer or much cooler, as shown in Figure 5.

Questionnaires were applied to users in representative environments, following the criteria of the Performance Standard (ASHRAE 55, 2017 [43], page 16), or where they spend their time. In addition to data collection for qualitative analysis of environments, observation and notes of information related to using constructive technologies (windows and doors) and air conditioning were also used.

To understand the relationship between the environmental and personal variables, a descriptive analysis of the collected data and a statistical inference method were carried out, seeking relationships between thermal performance and the types of use of the environments.

The statistical sample was defined using Cochran’s equation (1997) based on the work of Luca e Silva [44] according to expression (2):

$$n=\frac{N.p.q.{\left(Z_{\propto /2}\right)}^2}{\left(N-1\right).d^2+p.q.{\left(Z_{\propto /2}\right)}^2}$$

(2)

where

N is the total size of the population;

n is the number of individuals in the sample (minimum sample size);

$Z_{\propto /2}$ is the critical value that corresponds to the desired degree of confidence;

p is the expected frequency (when this value is not known, 0.50 is adopted);

q is equal to 1- p;

σ is the population standard deviation of the studied variable (in this example, users);

d is the acceptable error (d = 5.55%, for a significance level of 5%);

For a confidence level equal to 95%, the value of Z α/2 is 1.96.

Table 4. Sample sizes for different rooms.

Table 4. Sample sizes for different rooms.

Building	Room	Data collection period	Period of the day	Minimum sample size (n)	Selected sample size (N)
FEM	Classrooms
	CL1	Nov. 13,14 2018	morning	32.4	36
			afternoon	15.3	16
	CL2	Nov. 13,14 2018	morning	24.9	27
			afternoon	17.1	18
	Offices
	Of.3, 4	Nov. 13,14 2018	morning	19.7	21
			afternoon	12.5	13
	Of. 6, 7	Nov. 13, 14 2018	morning	9.7	10
			afternoon	13.4	14
	Of. 1, 5, 2	Dec. 13, 14 2018	morning	9.7	10
			afternoon	13.4	14

4. Results

4.2. Thermal comfort

The climate environmental conditions are shown in Figure 6, which describes the inside and outside temperatures where the questionnaires were applied, as well as the relative humidity.

Simultaneously with measuring environmental data, questionnaires were applied to users of the environments. A total of 199 questionaries were applied inside the buildings, 97 in a classroom, and 102 in office rooms.

There were four sessions of questionnaires for two days, applied at 9:00 am, 11:45 am, 2:00 pm, and 4:30 pm.

The questionnaires covered two classrooms, one on the intermediate floor and another on the last floor. Most of the selected office rooms were on the first floor. Some environments’ locations are shown in Figure 7.a (classrooms) and Figure 7.b (office rooms).

Monitoring and data collection occurred during a warm period in Campinas (13 November–14 December) in 2018. The images of some environments are shown in Figures 8.a.b.c.d.

The images of two classes are shown in Figure 8 (a,b). The CL1 classroom had two façades of windows, but users removed one to fix a blackboard. Thus, the ventilation is not the same as the original layout. Another is classroom CL2, located on the last floor. c and d feature office rooms.

4.2.1. Classroom’s survey results

Researchers advised users to maintain the same use of the rooms during the collection phase. Therefore, all data were collected with the air conditioning always on.

In classroom environments, 52 users responded to the questionnaires in room CL1, and in room CL2, there were 45 users, with a total of 97 people interviewed. The percentage of women using this environment was 34%, and 66% were men (Table 3). The details of the two classroom environments investigated in the university are in Table 3.

Figure 9 shows the relationship between the sensation and thermal preference of users in classrooms and the age group of users. The thermal sensation of the users indicates a feeling of cold, while they prefer slightly higher temperatures—that is, a slightly warmer environment. This preference for slightly higher temperatures may be an eventual loophole for energy savings in classrooms since they use air-conditioning equipment at the minimum temperature. According to Parra [45], studies by the Brazilian Association of Refrigeration, Air Conditioning and Ventilation (ABRAVA) prove that raising the air conditioning temperature by two degrees can reduce energy consumption by 7%.

The results show an asymmetrical variation in the seven-point scale in classroom environments, indicating heat. However, this indication of heat is due to the room’s ambience on the third and last floors. This environment has a more significant impact on the thermal load on the roof of the building, according to the survey, set 2, seen in Table 2. It has a thermal transmittance on the roof equal to (U¹ = 2.06 W/m²K | α² = 0.52). As quoted by the researcher Holanda [37], parameters of design (orientation, facades, absorbance, transmittance, among others), combined with HVAC (air conditioning), can reduce energy consumption by 34%. Users can spend more energy on environmental comfort when some bioclimatic attributes and material performance are not considered during the design and construction phase of a building.

4.2.2. PMV/PPD of the classrooms

The results in Figure 10 show that the PMV ranged from -1.06, with 28% dissatisfied, to 1.33, reaching 41% dissatisfied in the CL1 classroom, which means results were asymmetric, with a concentration on the positive side that directs to heat. The conditions of Figure 10 occurred with the air conditioning on and according to the previous orientation of daily use of the environment as usual.

It is interesting to note that when analysing the same data related to the vote of sensation and thermal preference by the age group of users, this level of dissatisfaction due to the heat does not appear, replaced instead with a slight dissatisfaction directed at the cold in the classrooms, as shown in Figure 9.

In this sense, Faraji et al. [25] mentioned that it is also interesting to consider aspects such as age and some other parameters that are very important when evaluating thermal comfort that is not or were not considered in some models of comfort analysis. In this case, there is a contradiction in evaluating the data calculated by the Comfort 2.03 program and the real average data of sensation and thermal preference of the users. The user’s voted for slightly cool but preferred slightly warmer environments, as seen in Figure 9 and Figure 10.

The data in Figure 9 and Figure 10 included the two rooms (CL1 and CL2) as a whole. However, a separate assessment is also helpful since the rooms’ thermal characteristics and locations are distinct.

The result showed the influence of the different locations of the environments of the PMV on the last floor.

For the CL2 room, located on the intermediate floor by the PMV and PPD, there is a PMV value concentration between -1 and +1. However, a tendency toward discomfort due to heat occurred at a rate of approximately 30%, as shown in Figure 11a.

In the CL2 room, discomfort due to heat reached about 70%, confirming the expected result of more significant discomfort in proximity to the roof and raising the level of dissatisfaction with the environment. As noted, a return to activities without a previous circulation of internal air to remove the hot air and without mechanical air conditioning makes the environment very uncomfortable, as shown in Figure 11b.

Table 4 and Table 5 show results for the mean and standard deviation of the calculated variables (PMV and PPD). The coefficient of variation (CV) of the PMV variable is very high in both rooms compared to the other variables.

The coefficient of variation of the PPD variable of room CL2, as shown in Table 4, has a much higher value than that of room Cl1 in Table 3. Additionally, the average value of PPD is much higher than that of CL1.

Table 4 shows the results, described as statistical parameters for Room Cl1 (mean value, standard deviation, and coefficient of variation).

In addition, the values of dissatisfaction perceived by users in room CL2 show more dispersion compared to room CL1, which is demonstrated by the comparison of the coefficient of variation between the two rooms.

Table 5. Statistical parameters of the sample data for room CL2 (45 questionnaires).

Table 5. Statistical parameters of the sample data for room CL2 (45 questionnaires).

CL2	PMV	PPD	(Icl)
Average	0.09	28	0.50
Standard Deviation	0.80	23	0.12
Coefficient of Variation (%)	888%	82%	24%

The comparison between the coefficient of variation (CV) for PMV of room CL2 and CL1 shows that the variability of answers of CL2 is much higher than those of CL1. Part of this can be explained by the higher exposition to solar irradiance of JE3 since it is under the top of the building (Figure 2. b, block J). In addition to the solar irradiance exposition, the material construction of the roof of building 2 is concrete slab and fibre cement tile with high thermal transfer parameters. The CL1 is on the intermediary floor of the building, thus with low solar irradiance exposition, which results in less variability in the ’s perception of users.

In the comparison of the averages of the isolation variables (Icl-Clo) of users’ clothing in both rooms, it is noticed that the difference in the average is only 0.1 (clo) and 2% with regard to the coefficient of variation between the interviewees of the two environments, according to data shown in Table 3 and Table 4.

Table 6 shows the results obtained through the measurements for the two rooms, CL1 and CL2. Based on the data, it is possible to verify that in the first measurement schedule at 9:00, the internal temperature is very close to the external one, being very close in both. CL2 was slightly lower. The air is turned on at the beginning of activities in both rooms.

Air conditioners are turned off at 11:30 am and switched on when users return at 2:00 pm. At that time, the temperature of the CL2 room again equalled the outside temperature. This situation might affect the roof since, in room CL1, there were no significant increases in temperature in the same range.

In room CL2, it is possible to notice that the internal temperature at 2 pm is close to the external temperature, with a difference of 1.4 °C, which may explain the dissatisfaction with the environment since the air conditioners were turned off during the lunch break activities restarting again at 2 pm in a scorching environment.

4.2.2. Office rooms

The offices were evaluated according to actual use; some environments were designed for individual use, while others were shared. The evaluation was also performed according to daily use and oriented to maintain use. Therefore, all data were collected with the air conditioning always on.

Questionaries

In the office room environments, users responded to 102 questionnaires. The percentage of women using the office room environment was 62%, and 38% of men (Table 3). The data details of the office room environments investigated in the university are shown in Table 7.

The average age of office users was 47 years, and when evaluating the group of women, the average age was 47.5 years and 49.2 years for men.

The relationship between the sensation and thermal preference of users in classrooms and the age group of users is shown in Figure 12. The lowest age found for users in FEM office environments was 24 years old, and the maximum was 65 years old. In these office environments, there were no users in the three age groups, 16 to 20, 26 to 30 years old, and 36 to 40 years old (Figure 12).

The age group with the highest representation in the offices was, in ascending order, the 31 to 35 age group and the 46 to 50 age group. The second largest group was between 51 and 55 years old, and the third was between 56 and 60. Notably, all users of the surveyed environments participated in the survey. They said, “They insisted on participating because they considered the environment uncomfortable.”

The thermal sensation vote ranged from 0.11 in the 31 to 35 age group, while in the 46 to 50 age group, it was 0.38; in the 51 to 55 age group, it was 1; and in the 61 to 65 age group, it was 1.28.

The average thermal preference vote in these same age groups was -0.44 in the 31 to 35 and 46 to 50 age groups. The average thermal preference vote in the 51-55 age group was -0.81. In the age group of those 56 to 60 years old, it was -0.59.

Environments remained wholly closed during the night. When arriving early, users turn on the air conditioning equipment and leave it on until lunchtime at noon. The equipment is turned off during the interval between leaving and returning from lunch. The devices are turned on again when people return to their work environment and are only turned off at the end of the day. Additionally, as observed in the study, a relatively common case at the university is opening the windows and “forgetting”, leaving them open for a long time, or even all day, with the air conditioning on.

4.2.3. PMV/PPD—office rooms

The predicted mean value of the thermal sensation votes of respondents inside office rooms of FEM ranged from neutral (-0.16) to very hot (+2.61), which is asymmetric, indicating a warmer environment.

In Figure 13, asymmetry in the PMV scale ranging from -0.16 to + 2.91 in office environments is shown. Such asymmetry indicates dissatisfaction due to heat on the part of users. There was a higher concentration between +0.13 and +1.32. The PPD varied between -0.16 at 5% and 2.91 at 95%, concentrated between 5% and 41%.

Table 8. Statistical parameters of the sample data for office rooms (102 questionnaires).

Table 8. Statistical parameters of the sample data for office rooms (102 questionnaires).

Office	PMV		PPD (%)	Iclo-clo
Average	0.52		14.59	0.48
Standard Deviation	0.49		15.28	0.12
Coefficient of Variation (%)	94.23		104.73	25
TBS	9:00 am	11:30 am	2:00 pm	4:30 pm
Average air temperature outside	27.7	30.65	31.5	30.9
Average TBS inside	25.81	25	25.75	26

5. Conclusions

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