A Comprehensive Assessment of Indoor Air Quality and Thermal Comfort in Educational Buildings in the Mediterranean Climate

Miao, S.; Gangolells, M.; Tejedor, B.

doi:https://doi.org/10.1155/2023/6649829

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Abstract Introduction Implementation Results Conclusions Abbreviations Data Availability Conflicts of Interest Authors’ Contributions Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 6649829 | https://doi.org/10.1155/2023/6649829

A Comprehensive Assessment of Indoor Air Quality and Thermal Comfort in Educational Buildings in the Mediterranean Climate

S. Miao,¹M. Gangolells,¹and B. Tejedor¹

Academic Editor: Shah Fahad

Received30 Jul 2023

Revised10 Oct 2023

Accepted20 Oct 2023

Published17 Nov 2023

Abstract

Maintaining good indoor air quality and thermal comfort is a challenge for naturally ventilated educational buildings, as it can be difficult to achieve both aspects simultaneously. Nonetheless, most of the existing studies only focus on one aspect. To explore the potential of balancing indoor air quality and thermal comfort, both topics must be investigated concurrently. This study assessed indoor air quality and thermal comfort in 32 naturally ventilated classrooms of 16 primary and secondary schools in the Mediterranean climate, based on a large on-site measurement campaign lasting one year that gathered over 460 hours of data. The research investigated occupants’ adaptive behaviors, analyzed the actual thermal comfort of around 600 students, and characterized the representative scenarios leading to good and poor indoor air quality and thermal comfort by clustering analysis. The results showed that poor indoor air quality was mainly due to closing windows and doors in winter, while thermal discomfort mainly occurred in summer because of the high indoor temperature. The findings suggested that a proper ventilation protocol is the key to balancing indoor air quality and thermal comfort.

1. Introduction

Students spend around 70% of their time in the classroom on school days [1]. The environmental quality of the classroom is influenced by many factors, but indoor air quality (IAQ) and thermal comfort (TC) are the main factors affecting students’ health, well-being, and productivity [2]. The negative impacts of poor IAQ and thermal comfort have been widely reported, such as the loss of concentration, decline in cognitive ability, headache, fatigue, allergy, and, in particular, a high infection risk of airborne diseases [3–5].

Long-term occupancy and high occupant density often lead to great challenges in maintaining a safe, comfortable environment in the classrooms. More importantly, children are more vulnerable than adults, and their adaptation in the classroom is passive and limited. They usually do not complain when they are not really satisfied with the indoor environment [6]. For these reasons, the IAQ and thermal comfort of educational buildings have been a concern for relevant public authorities and researchers.

Ventilation is the most common way of maintaining good IAQ in schools, and most schools only rely on natural ventilation that changes from time to time [7]. A minimum air change rate per hour is required by relevant standards such as ASHRAE 62.1 [8] and EN 16798-1 [9]. The estimation of the air change rate of the classroom is predominantly achieved by measuring occupant-released CO₂ as a tracer gas. Thus, the indoor CO₂ concentration is a commonly adopted surrogate indicator for the assessment of IAQ for educational buildings [3, 10, 11].

Maintaining good IAQ in schools is challenging. Díaz et al. [12] conducted a study in 8 primary schools in Chile. They found that the indoor CO₂ concentration exceeded the maximum threshold for around 70% of school hours in winter. In a large-scale survey of 100 primary and secondary school classrooms in Switzerland, Vassella et al. [13] demonstrated that approximately two-thirds of the classrooms failed to meet the limit set by the national standard. Cai et al. [14] carried out a study in 21 public schools in China and found that mechanically ventilated classrooms exceeded the CO₂ limit during 40% of the measurement time, compared to 61% in naturally ventilated classrooms. Monge-Barrio et al. [15] performed a measurement campaign in 9 secondary schools in Spain. They discovered that CO₂ concentration values did not meet the national regulation, as the exceedance was 2 times higher due to the lack of a proper ventilation protocol. From these studies, it can be extrapolated that the variability of IAQ of classrooms can be attributed to many factors, including seasons [12], occupancy [15], ventilation system [14], and ventilation strategy [13].

Unlike IAQ, both objective and subjective factors influence students’ thermal comfort. Objective factors involve a range of thermal parameters such as temperature, relative humidity, and air velocity. In contrast, subjective parameters derive from the occupants’ physical and psychological adaptation [2].

Achieving students’ thermal comfort is also a challenge for schools. Firstly, the thermal sensation of children and teenagers is quite different from that of adults [16]. Notably, the models established by ASHRAE 55 [17] and ISO 7730 [18] were developed for adults in offices. This means that students may not necessarily be comfortable even if the temperature in educational centers is set following the thermal requirements specified by the regulations. Korsavi et al. [6] evaluated 8 primary schools in the UK, where 15% and 14% of the children were overheated during nonheating seasons and heating seasons, respectively. Aparicio-Ruiz et al. [19] investigated 3 classrooms in a primary school in Southern Spain during the summer. They found that only half of the students felt comfortable, even though the mean indoor air temperature of classrooms was within the operating range of the national regulation. Secondly, students’ thermal comfort varies due to many factors. Zomorodian et al. [5] indicated that students in various climates had different comfort temperatures. Yang et al. [20] assessed a primary school in Sweden and reported that students’ thermal neutrality varied from season to season. Al-Khatri et al. [21] investigated 5 girls’ secondary schools and 3 boys’ secondary schools in Saudi Arabia. The results indicated that the comfort temperature difference between females and males was nearly 2°C. Jiang et al. [22] analyzed 4 schools in northwest China during winter. In nonheated classrooms, students were more accepting of lower indoor temperatures. Shrestha et al. [23] carried out a survey of 8 schools in Nepal. In this case, the heavier clothing of students also led to a low comfort temperature. Considering the aforementioned aspects, students’ thermal comfort can be affected by a wide range of factors such as climate [5], season [20], heating systems [22], gender [21], and level of clothing insulation [23].

IAQ and thermal comfort are associated because the outdoor air introduced into the classroom can lead to significant changes in indoor thermal conditions [2]. Heracleous and Michael [24] evaluated a secondary school in Cyprus and found that both indoor air and outdoor temperatures can affect occupants’ behavior of opening windows to ventilate the air in the space. Ma et al. [25] demonstrated that maintaining a comfortable thermal environment could reduce the ventilation rate, and consequently, a low level of IAQ could be detected in classrooms. Mohamed et al. [1] found that most of the classrooms experienced overheating for more than 40% of the day. At the same time, the classrooms failed to meet the IAQ requirement of the UK national standard for more than 60% of school hours.

Concerning the Mediterranean area, only a few studies address both topics (IAQ and thermal comfort of schools), as listed in the following: one elementary school study in Greece during spring [26], one secondary school study in Portugal during spring [27], one secondary school study in Cyprus during winter [24] and one preschool study in Spain during winter [28]. The above studies limited the scope to a single climate zone, season, and education level, which may be the shortcomings. In addition, none of the existing studies investigated the representative scenarios that often lead to good and poor IAQ and thermal comfort in classrooms. Hence, a comprehensive investigation is needed of IAQ and thermal comfort of primary and secondary schools in the Mediterranean climate.

For this reason, this paper is aimed at conducting a comprehensive characterization of both IAQ and thermal comfort in educational buildings, based on a large on-site measurement campaign in primary and secondary schools in several regions with specific climate conditions in the Mediterranean climate.

Following this introduction, Section 2 defines the methodology of this study, Section 3 describes the implementation of methodology and measurement campaigns, and Section 4 discusses the analyzed results. The conclusions and recommendations are summarized in Section 5.

2. Methodology

The research methodology of this study consists of four steps (Figure 1).

2.1. Identification and Description of Educational Buildings

Educational buildings must be selected considering representativeness and avoiding potential biases caused by the building and occupants. In this context, a range of factors that may affect IAQ and thermal comfort should be taken into account, such as climate zones, geographic location, construction year, ventilation type, and cooling and heating modes.

Educational centers are mainly used by children and teenagers. Their participation in the research must be based on the consent of all involved parties, such as government authorities, school management boards, teachers, and parents (who may ultimately restrict the availability of expected samples).

2.2. Characterization of Indoor Air Quality and Thermal Comfort

For IAQ, EN 16798-1 [9] specifies 4 categories with corresponding CO₂ concentration limits. The IAQ requirement for the classrooms corresponds to category I, which requires the indoor CO₂ concentration to be within 550 ppm above the outdoor concentration.

For thermal comfort, ISO 7730 [18] specifies the range of operative temperature and relative humidity (RH) for the classrooms with sedentary activity, given a typical clothing insulation value () of 0.5 for summer and 1.0 for winter. In summer, the recommended operative temperature is between 23 and 26°C, and relative humidity is 60%. In winter, the operative temperature is 20 to 24°C, while the relative humidity is 40%.

According to Kumar et al. [29], the operative temperature ( (°C)) can be calculated by where denotes the air temperature, is the air velocity, and is the mean radiant temperature given by the measurement instrument.

Table 1 summarizes the typical clothing insulation value indicated by ISO 7730 [18] and ASHRAE 55 [17].

Moreover, ISO 7730 [18] stipulates that the actual thermal comfort of occupants needs to be assessed using a thermal sensation vote (TSV) on a 7-point scale, which should be gathered 30 minutes after they have remained in a steady state in a stable thermal condition.

It should be noted that apart from these international standards, relevant national standards and guides should also be considered. The one with stricter criteria should be followed to meet the requirements at both national and international levels.

2.3. Development of the Protocol for the On-Site Measurement Campaign

To conduct the measurement campaign for data collection, a protocol needs to be developed and confirmed with the schools, which describes the measurement process, sensor deployment, and data collection methods. The measurement should follow the premise of avoiding interference in teaching activities in any case. Hence, background information about classrooms, students, and class schedules should be obtained in advance.

The number of sensors depends on the size of the classroom. Mahyuddin and Awbi [31] concluded that one sensor is needed for a space with a floor area below 100 m² and three or more sensors for rooms of over 200 m² in area. For minimum accuracy of sensors, ASTM D6245-18 [32] and ASHRAE 55 [17] require a ±5% of the measurement range for CO₂ concentration, ±0.2°C for air temperature, ±1°C for mean radiant temperature, and ±5% for relative humidity. The calibration and pretest are recommended to prevent malfunction and reading drift.

The deployment of the sensor should follow the criteria established by ASTM D6245-18, ASHRAE 55 [17], and ISO 7726 [33]. ASHRAE 55 [17] specified that the sensor should be located at least 1 m inward of the center of each room’s walls, while ASTM D6245-18 [32] recommended locating sensors preferably 2 m away from the following: (i) CO₂ sources (e.g., people in space), (ii) ventilated air with low CO₂ concentration (e.g., windows and doors), and (iii) heat sources (e.g., radiators and heaters).

No recommendation was made by ASTM D6245-18 [32] regarding the height that the sensor should be placed. However, the experimental study by Mahyuddin et al. [34] indicated that the CO₂ sensor should be placed within the occupant’s breathing zone, in a range of 0.75-1.80 m above ground, while 1.00-1.20 m is preferred. For the measurement of thermal parameters, ISO 7726 [33] specifies the heights of 0.60 or 1.10 m, which correspond to the occupant’s abdominal level when sitting and standing, respectively. To clarify open issues such as sensor location, height, and recording interval, a specific review of sensor deployment based on relevant case studies was conducted and is summarized in Table 2.

For the collection of TSV, relevant research pointed out that children may have difficulties understanding the concept of thermal comfort and expressing their thermal sensations; thus, the TSV graph should be designed in the most understandable way possible for them [42, 43].

2.4. Analysis of the Measurement Results

Firstly, IAQ and thermal comfort should be characterized, respectively, referring to the requirements of relevant standards. Statistical analysis needs to be performed to examine the correlation between relevant influential factors and IAQ/thermal comfort, such as season, climate, education level, geographic location of the building, year of construction, occupancy, ventilation strategy, and heating/cooling mode of the classroom. The measurement data usually has a hierarchical structure, as several classrooms or schools are measured in the same educational level, climate zone, and seasons. Hence, the hierarchical linear model should be applied for the statistical analysis. This model classifies the measurement from the same schools, educational level, climate zone, and/or seasons into identical groups and analyzes the statistical differences within and between groups. Relevant influential factors should be defined as independent variables, while indoor CO₂ concentration, operative temperature, and relative humidity are dependent variables.

Then, a simultaneous analysis of IAQ and thermal comfort must be conducted. Both aspects should be analyzed concurrently following the specified requirements. In addition, the representative scenarios that often lead to good/poor IAQ and thermal comfort need to be characterized based on the identified influential factors. Clustering analysis can extract key information from massive data by assigning the samples that share similarities into the same clusters, and highlighting their main features [44], which was applied to identify representative scenarios. Notably, to improve the readability and interpretability of the clustering results, numerical variables should be converted to categorical variables. K-mode clustering was applied in this study, since it is a widely used technique to cluster categorical data. It can identify K-representative clusters with the main features represented by the centroids [45], while the number of clusters k can be identified by the Elbow method [46].

3. Implementation

This section elaborates on the implementation of this study in detail, following the proposed methodology (Section 2). The research characterized and assessed IAQ and thermal comfort in primary and secondary schools in Catalonia, Spain.

3.1. Identification and Description of Educational Buildings

The sample schools were identified and contacted with the help of the Catalan government (Generalitat de Catalunya), but the participation of schools and students in this research completely depended on their willingness. Catalonia is primarily in a Mediterranean climate but has 3 specific climatic zones: Coastal Mediterranean, Continental Mediterranean, and Mountain. The coastal area has typical characteristics of a Mediterranean climate, with warm summers, moderately cold winters, and little rain. The continental region has cold winters and hot weather in summers. In mountainous areas, summers have mild temperatures, but there are high rainfall and snow in winters [47]. In the Coastal Mediterranean climate, Barcelona Metropolitan Area has a temperate climate (Csa in the Köppen climate classification), while Tarragona has a humid subtropical climate with hot summers (Cfa) [48].

In this study, a total of 9 primary and 7 secondary schools were selected, which are located in the aforementioned 4 climate zones and 3 geographic locations (city center, suburb, and rural area). These schools were built between 1953 and 2016, while 5 of them were built before 1979 when the first national standard NBE-CT-79 [49] regulating building thermal conditions was developed. Another 5 schools were constructed between 1979 and 2006, complying with the NBE-CT-79 standard but completely relying on natural ventilation. The remaining 6 schools were built after the establishment of the Spanish Technical Building Code in 2006. Table 3 summarizes the -values of construction elements of sample schools. These schools are designed with mechanical systems, but it was found that they did not work during the measurement campaign. To distinguish them from the naturally ventilated schools, their ventilation type is labeled as “free-running.” In addition, all schools are equipped with radiators but without any cooling system.

To avoid bias in sample selection, 2 classrooms were selected in each school, corresponding to different age groups. In primary schools, classrooms with 5- and 9-year-old students were selected, while in secondary schools, 12- and 16-year-old students’ classrooms were selected. One primary school only agreed to measure two classes that both have 9-year-old students. The volume of these classrooms ranges from 114.3 to 249.3 m³, with an average of 157.7 m³. The total area of windows and doors varies greatly, from 0.3 to 9.4 m² and 1.4 to 3.9 m², with an average of 4.5 and 2.1 m², respectively. Table 4 summarizes the characteristics of selected schools and classrooms.

3.2. Characterization of Indoor Air Quality and Thermal Comfort

Following the defined methodology (Section 2.2), the Spanish standards and guides were reviewed and considered.

For IAQ, compared with the international standard EN 16798-1 [9], the RITE standard [52] specified a lower CO₂ concentration threshold for the classrooms. The Ventilation Guide for Indoor Spaces recently proposed by the Spanish Institute of Environmental Assessment and Water Research [53] even indicated a stricter limit to prevent massive exposure to the SARS-CoV-2 virus in the schools. Table 5 summarizes the IAQ levels with the corresponding CO₂ concentrations applied in this study, assuming an outdoor CO₂ concentration of 420 ppm as recommended by IDAEA [53]. The IDA2 level is the minimum IAQ requirement for the classrooms stipulated by the RITE standard [52], and the safe level represents the optimum requirement by IDAEA [53].

For thermal comfort, Royal Decree 486/2004 [54] established the minimum acceptable requirements for typical sedentary workplaces, where the operative temperature must be between 17 and 27°C and relative humidity must be within 30 to 70%. The RITE standard [52] proposed the optimum thermal requirement with stricter comfort zones given the same assumptions made by ISO 7730 [18]. As both standards do not specify the requirements for the mild season (i.e., spring), it is assumed that the lower and upper limits of operative temperature and relative humidity for summer and winter establish the comfort zone for spring.

The minimum and optimum IAQ and thermal requirements applied in this study are summarized in Table 6.

3.3. Implementation of the Measurement Protocol in the On-Site Measurement Campaign

The measurement campaign was conducted from April 2022 to January 2023 (Figure 2), following the protocol defined in Section 2.3.

The technical specifications of the measurement instrument are summarized in Figure 3. The sensor was calibrated by the manufacturer and pretested by researchers in advance. All readings were recorded in a 1-minute interval.

The measurement lasted all day long during school hours, generally from 9:00 to 15:00 in spring and winter, while the school usually began and ended one hour earlier in summer. The measurement instrument was deployed in the classroom for 10 minutes before the beginning of the first class and was always preferentially placed in the center of the classroom at a 1.1 m height (whenever feasible). In classrooms with high occupancy where the desks and seats could not be moved, the sensor was located at the closest point to the center. A distance of 2 m was ensured from any disturbance (students, windows, doors, walls, and radiators). The location of the equipment was confirmed with the teachers before the class to avoid affecting teaching activities and the movement of students.

To protect the privacy of students during the measurement campaign, the Catalan government prohibited the researchers to conduct written surveys and to take photos and video records. In this context, researchers collected information about students’ gender and clothing and recorded the change in occupancy (students and teachers) and the behavior of opening windows and doors in the classroom through observation and notes during the entire survey.

In each measurement day, the TSV was collected by the teachers one time in each classroom, usually at the end of the class to ensure that the students had been in a sedentary state for 30 minutes. Teachers explained the concept of thermal sensation and showed TSV graphs (Figure 4) in advance, to ensure that all students understood correctly. The TSV graphs are specifically designed for this study based on the opinions of native Spanish speakers and teachers.

3.4. Analysis of the Measurement Results

Following the methodology defined in Section 2.4, IAQ and thermal comfort were assessed, respectively, following the thresholds of CO₂ concentration, operative temperature, and relative humidity indicated in Tables 5 and 6. Relevant influential factors of IAQ and thermal comfort were analyzed statistically. The collected measurement data has a 4-level hierarchical structure, season, climate, educational level, and school, which was defined in the model.

Then, the simultaneous analysis of IAQ and thermal comfort was performed. Depending on the satisfaction of the minimum and optimum requirements (Table 6), IAQ and thermal comfort were classified into 3 categories: (1) good (the optimum requirement is achieved), (2) acceptable (the minimum requirement is accomplished), and (3) bad (both requirements are not satisfied). IAQ and thermal comfort of the classrooms were characterized concurrently according to these 3 categories given the measured time.

The representative scenarios within each category were identified with K-mode clustering analysis. The occupancy ratio of the classroom and opening area of windows and doors were categorized to improve the readability and interpretability of the clustering results, as shown in Table 7. The categorization was based on the characteristics of the measured data (i.e., the range of occupancy ratio and opening areas), due to the lack of reference values.

The analysis was performed on the Google Colab platform using Python 3.7.3 [55]. Python packages of NumPy [56], Pandas [57], and Statsmodels [58] were adopted for data processing and statistical analysis. Kmodes [59] and Kneed [60] packages were used for clustering analysis and elbow point detection, and Matplotlib [61] and Seaborn [62] were used for data visualization.

4. Results

This section presents the assessment of results regarding IAQ, thermal comfort, and simultaneous analysis of both aspects.

4.1. Statistical Summary of Measured Indoor Environmental Parameters

Table 8 summarizes the statistical details of measured indoor environmental parameters in investigated classrooms by season. The mean indoor CO₂ concentration in summer was 593 ppm, which met the safe level requirement (700 ppm) by IDAEA [53]. In spring, the value was 774 ppm and achieved the minimum acceptable IAQ requirement-IDA2 level (920 ppm) specified by the national regulation RITE standard [52]. In contrast, the mean indoor CO₂ concentration in winter reached 1194 ppm, suggesting a potential of poor IAQ in classrooms. The mean air velocity in summer (0.064 m/s) was much higher than in spring (0.025 m/s) and winter (0.021 m/s). Due to the use of heating systems, the classrooms had similar mean operative temperatures in winter (21.24°C) and spring (22.53°C); both were within the comfort range specified by the RITE standard. However, the average operative temperature in summer reached 28.18°C, which was even higher than the maximum acceptable temperature limit (27°C) specified by Royal Decree 486 [54], indicating a high risk of thermal discomfort. The average indoor relative humidity ranged from 44.9% to 50.2%, which were all within the comfort range specified by the RITE standard.

4.2. Indoor Air Quality Analysis

Section 4.2.1 discusses the assessment results of measured classrooms, and Section 4.2.2 analyzes relevant influential factors.

4.2.1. Indoor Air Quality Assessment

Table 9 summarizes the statistical details of indoor CO₂ concentration in classrooms, and Figure 5(a) shows the IAQ assessment results of the measured classroom. In terms of the satisfaction of the minimum IAQ requirement (IDA2 level). On average, the IAQ of all investigated classrooms reached the IDA2 level nearly 71% of the time, whereas half of the classrooms were above the average level. Approximately 88% of the classrooms met the minimum requirement for up to 50% of the measured time.

(a) Indoor air quality of the investigated classrooms

(b) Thermal comfort of the investigated classrooms

For the achievement of the optimum IAQ requirement (safe level). In general, all the classrooms ensured a safe IAQ level 53% of the time, while 14 classrooms had a level above average. Over half of the classrooms met the optimum requirement for over 50% of the time in the measurement.

It is noteworthy that the initial CO₂ concentration of 81% of the measurements was below the threshold of safe level (700 ppm), but 8% exceeded the IDA2 level (920 ppm), which depends on whether the classroom was adequately ventilated at the end of the class in the previous day.

4.2.2. Influential Factor Analysis of Indoor Air Quality

Table 10 summarizes the statistical analysis results. For IAQ, correlated factors were found to be educational level, occupancy ratio, and opening area of windows and doors (ventilation strategy).

The most relevant factors are occupancy and ventilation, which determine the generation and removal of CO₂ in space. The results of statistical analysis indicated a positive correlation between the indoor CO₂ concentration and the occupancy ratio (person/m³) and a negative correlation with the opening of windows and doors in the classroom. Both correlations are statistically significant with values of less than 0.001. During the measurement campaign, classrooms were occupied by students for around 70% of the time. Figure 6 shows the IAQ level during unoccupied and occupied periods. As expected, the proportion of the safe level significantly decreased during the occupied period, which implies an increased infection risk due to the presence of the students.

Natural ventilation enables the renewal of indoor air but is manually controlled by opening windows and doors. During the measurement campaign, the researchers did not intervene in the opening of windows and doors in the classrooms. Hence, the occupants’ ventilation behavior in schools was observed. The outcomes showed that classrooms had cross ventilation up to 54% of the time. The ventilation was carried out only by opening doors 19% of the time, which is slightly higher than only by windows (15%), while for the rest of the time, the windows and doors were completely closed (no ventilation). Cross ventilation is the most effective strategy for improving indoor air quality in the classroom. As seen in Figure 7, cross ventilation maintained the IAQ above the IDA2 level in 90% of the observations and at a safe level in 70% of the observations. In comparison, ventilation by windows had better effects than doors, which is consistent with the findings of other studies [6, 63].

The statistical analysis results show that the CO₂ concentration in the classroom is statistically different in winter than in spring and summer. As seen in Figure 8, classrooms had better IAQ in spring and summer than in winter. In summer, the IAQ was above the IDA2 level more than 90% of the time, compared with less than 50% in winter. The average indoor CO₂ concentration in winter was 1194 ppm, which is significantly higher than that of spring (744 ppm) and summer (593 ppm). There is no significant difference in terms of occupancy for each season. Therefore, such a discrepancy was mainly due to different ventilation practices in schools. In summer and spring, the classrooms had cross ventilation for nearly 78% and 69% of the time, respectively, compared to less than 29% in winter. In winter, the windows and doors were completely closed for 23% of the time, and ventilation was carried out mainly by opening doors, which is consistent with the fact that the classroom occupants declined to open the window due to the low outdoor temperatures.

Moreover, there is a statistically significant difference in CO₂ concentration between educational levels (with values < 0.001), while the rest of the factors are not correlated. In general, primary schools had better IAQ than secondary schools (Figure 9). The average CO₂ concentration of primary schools was 744 ppm, while that of secondary schools was 1083 ppm. Such a discrepancy is believed caused by occupancy, generation ratio, and ventilation. The average occupancy ratio of primary classrooms was 20% lower than that of secondary classrooms, while primary students generate around 28% less CO₂ than secondary students [64]. Besides, primary classrooms had more cross ventilation than secondary classrooms by 10% on average.

4.3. Thermal Comfort Analysis

Section 4.3.1 discusses the assessment results of thermal comfort, Section 4.3.2 analyzes relevant influential factors, and Section 4.3.3 assesses the actual thermal comfort of students.

4.3.1. Thermal Comfort Assessment

Table 9 summarizes the statistical details of operative temperature and relative humidity in classrooms, and Figure 5(b) shows the assessment results of thermal comfort in the measured classrooms.

In general, the investigated classrooms met the minimum thermal requirement (Table 6) 74% of the time, while 14 classrooms were above average. More than 90% of the classrooms achieved the minimum requirement at least 50% of the measured time. In contrast, the optimum thermal requirement was met only 19% of the measured time, while 8 classrooms did not meet the optimum requirement in all the measurements.

Table 11 summarizes the accomplishment of minimum and optimum thermal requirements in terms of operative temperature and relative humidity. Regarding the satisfaction of the minimum thermal requirement, the relative humidity was within the required range for 97% of the measured time, but the operative temperature exceeded the upper limit for nearly 23% of the time. For the optimum thermal requirement, the relative humidity was within the required range 53% of the time, but the optimum temperature was achieved only 36% of the time.

Concerning the initial thermal conditions of the classrooms during the measurement campaign, only 17% of the measurements achieved the optimum requirement, while 62% met the minimum requirement. Notably, 21% of the measurements initially failed to meet the minimum thermal requirements due to a high indoor temperature of above 27°C in summer.

4.3.2. Influential Factor Analysis of Thermal Comfort

The statistical analysis results (Table 10) indicated that season, occupancy ratio, ventilation strategy, and heating mode of the classroom are influential factors of thermal comfort.

The results demonstrate that operative temperature is statistically correlated with the season with a value < 0.001, while relative humidity is independent of the season. In addition, both indoor operative temperature and relative humidity are not correlated with the climate and geographic location of the building, which is mainly attributed to the fact that the indoor thermal condition of the classrooms was regulated by the adaptive behavior of the occupants and the heating systems. The average operative temperature in spring was 22.53°C, slightly higher than that in winter (21.24°C); both were within the required range of optimum temperature. In spring and winter, the minimum temperature requirement was achieved more than 95% of the measured time, whereas the satisfaction of the optimum temperature requirement was 14% higher in spring than in winter (Figure 10). In comparison, the average operative temperature in summer was 28.18°C. The indoor operative temperature exceeded the upper limit of the minimum acceptable value (27°C) during 67% of the measured time and exceeded the optimum temperature limit (25°C) nearly 93% of the time. During the summer measurement campaign, teachers and students frequently complained to the researchers that it was too hot to withstand, particularly in the afternoon.

(a)

(b)

Both operative temperature and relative humidity are statistically correlated with the occupancy, ventilation state, and heating mode of the classroom (with values < 0.001). Temperature and relative humidity are positively correlated with the occupancy ratio, indicating that an increase in occupancy may lead to higher indoor operative temperature and relative humidity. Natural ventilation had a negative impact on the indoor thermal condition in general. As seen in Figure 11, ventilation brought in cool, dry air from outside in spring. On the contrary, it introduced a lot of heat from outdoor air into the classrooms in summer, leading to a significant reduction in the satisfaction of the optimum temperature requirement. Since heating systems were turned on in winter, ventilation had almost no impact on the indoor temperature, but it positively affects the indoor humidity as it removed the moisture from indoor air, which reduces the condensation risk that may lead to the growth of mold. During the winter measurement, radiators in 3 classrooms were completely turned off during the measurement day. The analysis found that the overall satisfaction of the optimum temperature increased owing to the heating, but an overheating problem was detected (i.e., the temperature was above the optimum limit 13.3% of the time). This can be attributed to the lack of a thermostat that controls the heating system in almost all the classrooms. In addition, although heating systems evaporated the moisture in the air, the satisfaction of the optimum humidity requirement slightly dropped in general.

(a)

(b)

Although the indoor thermal condition is not statistically correlated with the building construction year, the analysis of winter data found that the schools built after 2006 had a higher proportion above the optimum temperature limit of 23°C by nearly 10% of the time on average (Figure 12), which suggests an overheating problem and potential waste of energy for heating.

(a)

(b)

4.3.3. Thermal Comfort of Students

During the measurement campaign, students’ activity state, clothing, and actual thermal sensation were investigated. Measurement data revealed that students remained in a sedentary state for over 80% of the time in the classroom and performed light activities (such as having breakfast and doing craft projects) and medium activities (walking) for around 10% of the time, respectively.

The clothing insulation of students in each season is summarized in Table 12. It was observed that students wore fewer clothes than adults in general. The total students’ clothing insulation value was lower than the recommended value of ISO 7730 [18] in all seasons. In addition, gender was a relevant factor of divergence since the average clothing insulation value was greater in female students than in male students.

Furthermore, students’ actual thermal sensation votes were collected and analyzed. The TSV frequency values were 596 in spring, 599 in summer, and 592 in winter. In terms of educational centers, 55% of the TSV corresponded to primary schools and 45% were from secondary schools. Regarding gender, 49% collected were from female students and 51% were from male students. Figure 13 shows the distribution of students’ TSV in each season. As shown, thermal neutrality reached the highest level in winter, while most of the students felt hot (from +1 to +3) in summer and felt between neutral (0) and a little bit hot (+1) in spring. The average values of students’ TSV in spring, summer, and winter were 0.76, 1.26, and -0.04, respectively. Male students felt hotter than female students. In spring, summer, and winter, the average TSV of female students were 0.61, 1.08, and -0.26, while those of male students were 0.91, 1.41, and 0.16, respectively.

Linear regressions were established between the mean thermal sensation vote (MTSV) of students and the operative temperature at the time of TSV (Figure 14). The neutral temperature of primary schools was found to be lower than that of secondary schools in spring and winter, but they were quite similar in summer. In comparison with secondary students, primary students have a higher metabolic rate per kg body weight, limited adaptive opportunities in classrooms, and more class schedules for outdoor activities. These factors result in a difference in their thermal perception and ultimately lead to a lower comfort temperature [5]. On average, the neutral temperatures in spring, summer, and winter were found to be 21.7°C, 25.3°C, and 21.0°C, respectively. These neutral temperatures are very close to the upper and lower limits of the optimum temperature range specified by the RITE standard [52]. The regressions had values of over 0.8 in summer, which indicates that over 80% of the variance in MTSV is attributed to changes in operative temperature. Both schools had lower values in spring and winter, which implies a greater influence of occupants’ adaptive behaviors such as opening windows and changing clothes [65].

4.4. Simultaneous Analysis of Indoor Air Quality and Thermal Comfort

Figure 15 categorizes IAQ and thermal comfort of the measured classrooms simultaneously, following the methodology defined in Section 3.4. The horizontal axis denotes the indoor air quality aspect, and the vertical axis represents the thermal comfort aspect. The size of the bubbles refers to the percentage of observations for each category in all measurements.

As seen, the optimum requirements of both IAQ and thermal comfort were achieved in 7.5% of the measured time. In contrast, only 0.3% of observations were labeled completely as bad, which means a failure to meet the minimum requirements of both aspects. For nearly 30% of the observations, one aspect reached a good level, while the other achieved an acceptable level. Then, for 9% of the observations, both aspects only reached the acceptable level. Overall, the investigated classrooms achieved acceptable and good levels of both IAQ and thermal comfort aspects for over 46% of the measured time.

Figures 16(a) and 16(b) summarize the identification results of representative scenarios under each IAQ and thermal comfort category with clustering analysis. The results showed that good IAQ and thermal comfort could hardly be achieved simultaneously in summer. According to the measurement results, only 7% of the observations in the good IAQ and good TC category were in summer, while the figure was 48% and 45% for spring and winter, respectively. For a good IAQ and acceptable TC category, the summer’s observation was also less than 29%. Besides, it was found that almost all observations in the good IAQ and bad TC category were from summer. In comparison, spring and winter create favorable conditions for ensuring good and acceptable IAQ and thermal comfort in the classrooms.

(a) The number of representative clusters k identified by the Elbow method

(b) The representative scenarios with each indoor air quality and thermal comfort category

For the categories involving bad IAQ, secondary schools accounted for a high proportion. The main reason is that, as previously mentioned, the occupancy ratio of secondary schools is usually higher than that of primary schools, while these students also generate more CO₂ than children. Therefore, it is necessary to limit the number of students in secondary school classrooms to guarantee a satisfactory IAQ level. Furthermore, the ventilation strategy is critical to maintaining a good IAQ. Most of the observations in categories with bad IAQ are related to a small opening area of windows and doors. Cross ventilation with a sufficient total opening area (>3 m²) can guarantee good or acceptable IAQ in most cases, which should be adopted by schools, as strongly recommended by IDAEA [53].

Temperature was the main factor leading to poor thermal comfort in schools. For categories involving bad TC, 87% of the observations exceeded the upper limit of minimum acceptable temperature. Only in a few cases in winter, the temperature was below the acceptable limit. In contrast, relative humidity usually caused a decline in thermal comfort level, particularly in winter. When ventilation and heating occurred at the same time, the relative humidity fell below the lower acceptable limit, leading to a bad TC (cluster 5 in good IAQ and bad TC category). When there was a lack of sufficient ventilation, the relative humidity was often higher than the optimum limit, which reduces the possibility of achieving good thermal comfort in the classrooms (clusters 2 and 5 in bad IAQ and acceptable TC category).

The results of representative scenarios suggest that clustering analysis is an effective and efficient way to analyze large measurement databases.

4.5. Discussion of Results

Maintaining good IAQ in the classroom is not a simple and easy task. As observed in many studies, classrooms did not meet the IAQ requirement of relevant standards over 50% of the time [12, 14, 25]. This is often caused by a lack of adequate ventilation, particularly in winter, because occupants usually have less willingness to open windows and doors in cold weather to ensure thermal comfort needs. In this study, classrooms failed to achieve the acceptable IAQ level nearly 49% of the time in winter, mainly due to a substantial reduction in cross ventilation. These findings are consistent with previous studies, which suggest the need of a proper ventilation protocol in schools. Monge-Barrio et al. [15] found that after adopting a clear ventilation protocol, IAQ in classrooms was significantly improved and the average CO₂ concentration dropped by 1400 ppm. Miranda et al. [66] discovered that when a ventilation protocol was enforced, IAQ in classrooms fully met the requirement 100% of the time, with a CO₂ concentration maintained below 800 ppm. These studies all pointed out that students’ thermal comfort was inevitably compromised due to the enforced ventilation protocol in winter. Therefore, more attention should be given to the balance of IAQ and thermal comfort when developing ventilation protocols [67]. But till now, there is a lack of reference in relevant standards combining both aspects [68]. Accordingly, the representative scenarios of good and poor IAQ and thermal comfort identified in this study lay the foundation for the development of such a proper ventilation protocol.

Ensuring the thermal comfort of students is also a challenging issue. Due to the difference in thermal sensation, children usually have a lower comfort temperature than adults. In this study, students’ neutral temperatures were found to range from 21.0 to 25.3°C, which is close to the values observed in relevant studies under similar climatic conditions [5, 19, 27]. These values are generally lower than the university students’ comfortable temperatures summarized in existing research [16, 69]. In this context, indoor temperature values specified by existing building codes and standards may not properly fit the needs of primary and secondary students. Moreover, children’s adaption in classrooms is often passive and limited, while teachers have the initiative to control indoor thermal conditions. Kumar et al. [70] investigated the adaptive behaviors of university students and identified diverse adaptive opportunities such as turning on fans/air conditioners, operating windows and doors, changing clothing, changing postures, and walking indoors or outdoors. These options are usually not applicable to children because they have to ask for the teacher’s permission [5, 20]. Accordingly, these factors may ultimately lead to lower satisfaction with the indoor thermal environment in classrooms, as observed in this and other relevant studies [6, 19]. These issues deserve more in-depth explorations in further research to guarantee a comfortable indoor environment for students.

5. Conclusions and Recommendations

This research conducted a comprehensive assessment of IAQ and thermal comfort of educational buildings, based on an on-site measurement campaign involving around 600 students in 32 classrooms of primary and secondary schools in the Mediterranean climate.

For IAQ, the investigated classrooms met the minimum IAQ requirement for 71% of the time and maintained a safe level avoiding massive exposure to the COVID pandemic 53% of the time. Occupancy and ventilation were found to be the most significant influential factors that cause the discrepancy in indoor CO₂ concentration across the seasons. The classrooms had cross ventilation for more than half of the measured time in general, and occupants preferred ventilating the space by opening doors, especially in winter.

Concerning thermal comfort, the measured classrooms satisfied the minimum thermal requirement for 74% of the time, but the optimum requirement was achieved less than 19% of the time. Poor thermal comfort was given by a high indoor air temperature in summer. The analysis found that indoor thermal conditions can be affected by factors such as season, occupancy, ventilation, and the heating mode of the classroom. The average value of the clothing insulation of students was lower than that specified by ISO 7730 [18]. TSV analysis confirmed that female students are more sensitive to colder temperatures. In addition, students’ neutral temperature was found to be very close to the upper and lower limits defined by the RITE standard [52].

When IAQ and thermal comfort aspects were assessed simultaneously, the minimum requirements of both aspects were achieved 46% of the time, but the optimum requirements were satisfied only 7.5% of the time. It was found that good IAQ and thermal comfort can hardly be achieved simultaneously in summer, while spring and winter render favorable conditions. Inadequate ventilation in winter not only results in a bad IAQ in the classrooms but also leads to relatively high humidity, which reduces the potential of achieving good thermal comfort. Besides, secondary schools should limit the number of students in the classrooms, and cross ventilation should be performed with a sufficient total opening area (>3 m²).

Based on the findings of this research, it was concluded that good IAQ can be maintained by developing a proper ventilation protocol for schools, but the impact of ventilation on indoor thermal conditions must be taken into account. Future research steps could investigate the adaptive thermal comfort of students.

Abbreviations

IAQ:	Indoor air quality
TC:	Thermal comfort
TSV:	Thermal sensation vote
MTSV:	Mean thermal sensation vote
NV:	Natural ventilation
FR:	Free-running.

Data Availability

Data are available on request.

Conflicts of Interest

The authors declare that they have no conflict of interest.

Authors’ Contributions

Sen Miao was responsible for the conceptualization, methodology, investigation, data curation, formal analysis, and visualization; wrote the original draft; and wrote, reviewed, and edited the manuscript. Marta Gangolells was responsible for the conceptualization, methodology, resources, supervision, project administration, and funding acquisition and wrote, reviewed, and edited the manuscript. Blanca Tejedor was responsible for the conceptualization, methodology, resources, and supervision and wrote, reviewed, and edited the manuscript.

Acknowledgments

This research is part of the R&D project IAQ4EDU (reference no. PID2020-117366RB-I00), funded by the MCIN/AEI/10.13039/501100011033. This work was supported by the Catalan Agency AGAUR under their research group support program (2021 SGR 00341). The author Sen Miao is funded by the China Scholarship Council (CSC) as a full-time PhD student (reference no. 202208390065).

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Copyright © 2023 S. Miao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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