Objective and subjective indoor air quality and thermal comfort indices: characterization of Mediterranean climate archetypal schools after the COVID‐19 pandemic

Research Article Objective and Subjective Indoor Air Quality and Thermal Comfort Indices: Characterization of Mediterranean Climate Archetypal Schools After the COVID-19 Pandemic Jesús Llanos-Jiménez , Rafael Suárez , Alicia Alonso , and Juan José Sendra Instituto Universitario de Arquitectura y Ciencias de la Construcción, Escuela Técnica Superior de Arquitectura, Universidad de Sevilla, Av. Reina Mercedes, 2, 41012 Seville, Spain Correspondence should be addressed to Jesús Llanos-Jiménez; [email protected] Received 1 April 2024; Revised 11 September 2024; Accepted 13 September 2024 Academic Editor: Geun Young Yun Copyright © 2024 Jesús Llanos-Jiménez 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. The COVID-19 pandemic has prompted renewed interest in indoor air quality (IAQ). Poor ventilation habits, energy obsolescence, and the lack of cooling equipment in schools, combined with increasing temperatures due to climate change, are leading to situations of thermal stress in classrooms. Changes in school operation, following the COVID pandemic, have made it necessary to establish an accurate understanding of the current situation. This research work presents an assessment of winter and summer IAQ and thermal comfort (TC) for a sample of 7 archetypal secondary schools in 5 Mediterranean climate variants in southern Spain in a postpandemic situation. IAQ was assessed through CO 2 , PM2.5, PM10, and CH 2 O, while static and adaptive models were used in the case of TC. Surveys were also used to assess both of these. The main novelty is the use of IAPI (indoor air pollution index) and IDI (indoor dissatisfaction index) objective global dimensionless indices to optimize the joint assessment of both variables. Poor objective IAQ results, especially for CO 2 and PM2.5, were obtained for both seasons and all climate variants. Global IAPI is between 6.2 and 8.1, with an index of 10 considered unacceptable, while time percentages exceeding established limits are more variable in winter, ranging from 7% to 31.9%, than in summer, ranging from 14.3% to 20.9%. TC objective results varied, and the summer percentage of hours outside the comfort bands reached 40%–47% due to excess heat in the hottest regions. This discomfort was reported by 58.3% of users. Keywords: indoor air quality; Mediterranean climate; natural ventilation; objective index; school building stock; subjective index; thermal comfort Summary •The use of global indices facilitates the single and joint assessment of IAQ and TC. •Summer and winter IAQ are poor in all climate zones, mainly due to CO 2 and PM2.5. •Perceived IAQ worsens with higher temperatures and lower humidity, unaffected by CO 2 . •TC is poor in the warm season in the hottest climate variants. •Schools need HVAC systems upgraded to ensure health and comfort. 1. Introduction Since the onset of COVID-19, discussions concerning health conditions in indoor spaces —including hospitals and health care facilities [1, 2], transport [3], work [4], leisure, restaurants [5], and educational spaces [6, 7]—have been democratized. Educational spaces are particularly critical due to children’s physiological vulnerability to diseases [8, 9] and the significant amount of time they spend in densely occupied and often poorly ventilated classrooms [10, 11], when no mechanical ventilation systems are in operation. One Wiley Indoor Air Volume 2024, Article ID 2456666, 20 pages https://doi.org/10.1155/2024/2456666 year after the COVID-19 virus emerged, airborne transmission via aerosols was confirmed as the primary spread route [12], making ventilation a key strategy for reducing transmission, as had been seen in past pandemics [13]. Many leading organizations, institutions, and bodies in the field proposed different measures to improve ventilation, based both on previous scientific literature and studies specifically conducted for the purpose of validating and verifying their effectiveness. In Mediterranean climates, various ventilation strategies have been analysed to reduce the risk of infection: permanent natural cross-ventilation and intermittent spot ventilation during class changes and breaks [14, 15]; ventilation with mechanical supply and extraction or mechanical supply and natural extraction [16], showing major reductions in risk; and portable air purifiers, face masks, methacrylate screens, or reduction in occupancy rates [6]. However, once the periods of greatest risk were considered to be over, most of these measures have been forgotten. Nevertheless, there is still a need for ventilation since the repercussions of poor indoor air quality (IAQ) have attracted society’s attention [17]. In fact, in 2004, Sundell pointed [18] out the impact of increasing indoor pollution on worldwide allergy rates. IAQ, along with temperature and humidity conditions in indoor environments, can greatly influence occupants’psychophysical capabilities, including agility and cognitive performance [19, 20]. Supporting Information 1: Table S1 summarizes publications on the environmental characterization of classrooms considering different educational levels, study samples and sizes, monitoring duration, and climate zones. The environmental variables (IAQ, thermal comfort (TC), or both) are shown, as is the level of detail of the analysis: It is stated whether several pollutants or only CO 2 have been analysed and whether—in the case of TC—static or adaptive models have been used. Finally, the approach selected is also discussed, specifying whether it was an objective approach based on monitoring, a subjective survey-based one, or a combination of both. Romero et al. [21] have been a reference for this work as they provide a detailed review of 223 publications on these issues, particularly emphasizing pre- and post-COVID studies on TC. Prior to COVID-19, research on IAQ and TC in schools, even in a Mediterranean climate (Csa according to the Köppen-Geiger climate classification [22]) was already available, although often lacking detail (in TC or IAQ) or dual method approaches (objective or subjective). Dias Pereira et al. [23] assessed Portuguese schools (Csa and Csb, Mediterranean-Oceanic climate) with natural ventilation using mainly subjective indices such as thermal sensation vote (TSV) and percentage of dissatisfied (PD) with IAQ, and were satisfied despite noncompliance with CO 2 , preferring somewhat higher temperatures than those obtained following static models. Tahsildoost and Zomorodian [24] conducted a similar survey study in university classrooms in Tehran (Csa), finding no clear correlation between IAQ and CO 2 levels. It is observed that results can be influenced by age or maturity, gender, date, and location of the experiment, as factors relating to climate and culture. Almeida and De Freitas [25] monitored objective IAQ and TC in northern Portuguese (Csb) naturally ventilated schools, concluding that winter IAQ values often exceeded the limits for maintaining acceptable TC. Research in Spain (Csa and Cfb, oceanic climate in the north of Spain), during the post-COVID reopening of schools [15, 26, 27], found that while natural ventilation significantly reduced CO 2 levels, it also led to notable drops in classroom temperatures during winter. IAQ and TC are inextricably linked, at least when working with naturally ventilated schools, common in Mediterranean climates. However, IAQ analysis is often simplified and reduced to the assessment of CO₂due to its ease of measurement and interpretation, while static TC model analyses are predominant [28]. Aparicio-Ruiz [29] and Almeida, Ramos, and De Freitas[30] assessed naturally ventilated classrooms in Csa during the summer season through static and adaptive TC models, as well as surveys, finding higher student tolerance to high temperatures, even in the adaptive comfort bands. Romero et al. [31] conducted a summer TC survey campaign in Csa combined with adaptive comfort model and CO₂analysis, finding similar conclusions to those above. Miao, Gangolells, andTejedor[32] evaluate different ventilation strategies through CO 2 levels and static TC model, finding notable improvement of the IAQ, especially in summer and midseason, with cross-ventilation strategies. Apart from CO 2 , IAQ includes many other pollutant substances with a potentially more significant impact on health. In 2006, the Building Assessment Survey and Evaluation (BASE) division of the US Environmental Protection Agency (EPA) drew up a list of 9 parameters that can provide a balanced and objective overview of IAQ: bacteria, carbon monoxide, carbon dioxide (CO 2 ), formaldehyde (CH 2 O), fungi, PM2.5, PM10, radon, and TVOC. Each of these pollutants has long been discussed in scientific literature. Madureira et al. [33] extensively analysed these pollutants in naturally ventilated Portuguese schools (Csb) during winter, finding several exceeded reference values (WHO for PM and ASHRAE 62-2001 for CO 2 ), in contrast to Becerra et al. [34], who found acceptable IAQ during Csa spring. These studies often overlook TC comparison or only consider basic temperature and relative humidity ranges, as it is difficult to manage a large number of pollutants and the different local and international IAQ regulations in place. Moschandreas and Sofuoglu [35] propose the use of the indoor air pollution index (IAPI), an objective indicator that numerically evaluates air quality by weighting observed values and regulatory limits, simplifying the rigorous assessment of IAQ as well as TC comparison. Cabovská et al. [36] successfully applied these indices in Swedish classrooms (Dfb, hemiboreal climate), finding poorer IAQ in naturally ventilated spaces than in mechanically ventilated ones. Following this analysis of the state of the art, mostly examining joint assessments of IAQ and TC in schools, the following considerations are made: - IAQ analysis tends to focus exclusively on CO 2 levels, while fewer studies conduct detailed pollutant 2 Indoor Air ina, 2024, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/2024/2456666 by Readcube (Labtiva Inc.), Wiley Online Library on [12/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License assessments together with TC. Furthermore, an objective approach tends to be used when analysing IAQ. - Static models dominate TC analysis [28, 37]. Although the subjective analysis of TC is widely used, it is less common to find comparisons of objective and subjective approaches. - Studies are sometimes limited by short monitoring periods where the representativeness of climate conditions cannot be assessed or there are unrepresentative samples. The main objective of this research is to characterize classroom environmental quality in archetypal schools in southern Spain’s Mediterranean climate under post-COVID-19 pandemic conditions. The study’s main novelty lies in the comprehensive joint assessment of IAQ and TC using global evaluation indices (IAPI G and IDI G ), which, combined with their comparison through a subjective approach, enhance the potential for lasting impact of the publication. Additionally, a further novelty compared to similar publications is the inclusion of detailed analysis of both environmental variables. For IAQ analysis, several pollutants apart from CO 2 were included, while adaptive models were incorporated into the TC analysis. 2. Methods Figure 1 shows a summary of the methodology. Following the initial selection of case studies through (1) the definition of school archetypes in the region, based on previous multiparameter statistical analysis, experimental campaigns are implemented to (2) monitor environmental parameters relating to IAQ and TC, as well as surveys. After (3) data processing, the (4) results are analysed using a two-fold approach: objective and subjective. Finally, (5) global assessment indices obtained from both approaches allow the main objective of this work to be achieved, as well as a potential comparison with analogous research on the school building stock. The objective analysis completed in this investigation is carried out by monitoring 7 case studies, corresponding to archetypal centres of the most representative climate variables of the Mediterranean climate, based on a selection drawn up from previous work conducted by Llanos- Jiménez et al. [38]. In summary, after a multiparametric statistical analysis of a large database with information on 200 public schools in Andalusia, the archetypes were classified according to date of construction, orientation, types of façade and roof, types of windows and sun protection, and types of heating ventilation and air conditioning (HVAC) systems. More detailed information on the multiparametric analysis and the conclusions drawn in the definition of archetypes can be found in Supporting Information 2. The abundance of climate variants found in Andalusia, a large region with a varied orography, is a good choice for this type of research. According to the technical building code (CTE) [39], the climate zoning is configured according to a winter climate severity (A–E, from mildest to harshest) and a summer climate severity (1–4, applying identical criteria). The most representative climate zones were identified by comparing the locations of all the public schools in Andalusia, and a sample obtained was then used to create the database mentioned above. The result was a characterization table of archetypes in the most representative Csa climate zones according to the Köppen–Geiger climate classification. However, as indicated by Gómez-Zotano et al. [40], as well as by the Spanish Meteorological Agency (AEMET) [41], each of the zones chosen has its own unique properties: A3 has a temperate dry/subhumid Mediterranean climate; B4 and B3, a semioceanic dry/subhumid Mediterranean climate; C4 has a semicontinental dry/subhumid Mediterranean climate, while C3 has an oceanic Mediterranean climate. 2.1. Case Study Definition. As mentioned above, the study sample is archetypal and representative of a sample of up to 200 public secondary schools chosen, also representatively, among the climate variants with the largest number of schools. The sample is therefore optimized, with 7 case studies and an equivalent 14 classrooms (two with opposite orientations in each school). As these are secondary schools, the age range of students is between 12 and 16 years old, although one of the schools also offers professional training degrees, where the age range is usually between 18 and 25 years old. Table 1 shows the specific characteristics for each school. It is worth noting that three of these schools were built before 1979, the year when general energy demand specifications were first imposed for buildings in Spain, with the basic building regulation on thermal conditions of 1979 (NBE CT-79) [42]. The remaining four schools were built between 1979 and 2006, when these regulations were already in place. This also means that all the school buildings studied were built prior to the publication of the CTE in 2006, which unified the previous regulations on thermal-energy issues for buildings. All of these case studies follow a morphological structure of classroom + corridor + classroom. Most of the classrooms are located on intermediate floors and rely solely on natural ventilation, as mechanical ventilation first became mandatory in educational centres in Spain in 2007. For the heating installation, a combustion boiler acts as the thermal generator and radiators as heat emitters. According to the administrators of the different schools, in order to keep down costs, the general heating activation protocol is reserved for the coldest days; a comparison of the evolution curves of indoor and outdoor temperatures shows that this protocol is activated when the outdoor temperature is below 12.5 ° C–10 ° C and only during the first 3 h of the school day. The percentage of centres with cooling equipment other than the ceiling or wall fans in the classrooms is low, with use kept to a minimum for financial reasons. The classrooms in archetypal schools typically have a rectangular floor plan, with a façade length of 6.6–9.2m, a width of 5.9–6.5 m, and floor-to-ceiling heights of between 2.75 and 3.15 m. Floor surface areas are 41.–57.7m 2 and occupancy densities are in the range of 1.6–2m 2 /person. 3Indoor Air ina, 2024, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/2024/2456666 by Readcube (Labtiva Inc.), Wiley Online Library on [12/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License In general, the envelope solutions do not meet current energy efficiency standards. The façades are usually double-leaf brick with a 2–3cm unventilated air cavity or EPS insulation layer, with exposed brick or plaster. Ceilings are typically plastered under the slab or, occasionally resolved with false ceilings, while floors are often terrazzo or stone. The original joinery features aluminium frames with single glazing, replaced in some cases by PVC joinery. Additionally, when blinds are used as solar protection, their boxes are often quite permeable to outdoor air entry. A3 is the only climate zone where school centres without radiators are found, jeopardizing compliance with the Thermal Quality Requirement of the Building Thermal Installations Regulations (RITE). 2.2. Objective Approach. The objective approach to the analysis of the monitoring results uses the IAPI and IDI indices proposed by Moschandreas and Sofuoglu [35] but adapted in the terms described below to meet the objectives of this research. Both indices, defined in detail in the following subsections, are mathematical constructions in a tree diagram, as shown in Figure 2. 2.2.1. IAQ Analysis Group. IAQ is assessed based on CO 2 , PM2.5, PM10, and CH 2 O levels during periods of occupancy. In addition to assessing IAQ according to the ratio of maximum (90th percentile), minimum (10th percentile) and mean (median) values, and the percentage of overall hours outside the established regulatory limits (IAQ G ), the IAPI is assessed globally according to the Equation (1). IAPI = 1 I〠 I i=I 1 J〠 J j=1 1 K〠 K k=1 10 1 −Cmax i,j,k−Cobs i,j,k Cmax i,j,k−Cmin i,j,k ·Cdmc i,j,k−Cobs i,j,k Cdmc i,j,k 1 Additional conditions are as follows: 1. If Cmax < Cobs,thenCobs = Cmax in the location term and Cobs = Cdmc in the weight term 2. If Cdmc < Cobs ≤Cmax, then Cobs = Cdmc 3. If Cobs < Cmin, then Cobs = Cmin This equation is in fact a tree system of equations. It contemplates the aggregation of several sublevels (I= level 4,J= level 3,K= level 2) in which the arithmetical mean is obtained successively for each of the pollutants analysed. This specific calculation, placed after the summations, considers the position of the value monitored or observed for the calculation of the index (Cobs, which will be the median value) normalized with respect to the complete range of measurements, which matches the first factor of the multiplication. Cmax and Cmin are the maximum and minimum measured concentrations of the pollutant, respectively. The second multiplication factor is used to weigh the index with respect to the specific regional or international limits for each substance (using the Cdmc demarcation concentration). The result of the equation will be the IAPI G , a dimensionless index that can provide values of between 0 (lowest pollution level and best IAQ) and 10 (highest pollution level and worst IAQ), contemplates all the polluting substances analysed Results assessment Data processing Monitoring and surveys of the case studies Case study definition Statistical analysis of the database of a selection of schools Archetypal school in representative climate zones Objective approach Subjective approach IAQV TCV IAPI IDI VS +200 2 4 3 15 Figure 1: Methodological diagram. 4 Indoor Air ina, 2024, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/2024/2456666 by Readcube (Labtiva Inc.), Wiley Online Library on [12/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Table 1: Case study definition. ID Climate zone (location) Regulation (construction period) Classroom orientation Classroom dimensions (m; m 2 ;m 3 ) Windows: Surface max. aperture (m 2 )HVAC systems [1] Occupancy density (m 2 /pers.)Façade transmittance (W/m 2 K) Transmittance (W/m 2 K) Shading CS 1 A3 (Málaga) NBE CT-79 (1979–2006) SE-NW 61×9,h=3; 54.9; 164.7 10.2 (5.1) Radiators 1.85–5.5 1.3 vertical blades CS 2 A3 (Málaga) -(<1979) SE-NW 62×92,h=3; 57; 171.1 9.4 (4.7) None 25–5.5 1.5 Blinds CS 3 B4 (Sevilla) NBE CT-79 (1979–2006) SE-NW 58×79,h=275; 45.8; 126 13.3–9.8 (6.6–4.9) Radiators + fans 1.84.5–5 1.3 horizontal blades CS 4 B4 (Sevilla) -(<1979) SE-NW 63×66,h=315; 41.6; 131 7.3 (3.6) Radiators + splits 1.75–5.5 1.1 Blinds CS 5 B3 (Dos Hermanas) NBE CT-79 (1979–2006) E-W 59×8,h=3; 47.2; 141.6 6.4 (3.2) Radiators + splits 1.64.5–5 1.5 Vertical blades CS 6 C4 (Córdoba) -(<1979) E-W 6×87,h=3; 52.2; 156.6 8.2 (4.1) Radiators + fans 1.75–5.5 1.25 Blinds CS 7 C3 (Huelva) NBE CT-79 (1979–2006) S-N 65×89, h=3; 57.7; 173.2 8.4 (4.2) Radiators + fans 1.95–5.5 1.5 Horizontal blades Note: In [1], all case studies have only natural ventilation through the opening of windows (usually sliding) and doors, some of them with high windows onto the corridor. 5Indoor Air ina, 2024, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/2024/2456666 by Readcube (Labtiva Inc.), Wiley Online Library on [12/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License simultaneous and homogenously. The resulting index provides an overview of the deviation of the median values both from the full range of values and from the regulatory limits. These limit values are sometimes established by national institutions themselves, as is the case of CO 2 ,an essential parameter for IAQ assessment in Spain and regulated by RITE [43], based in turn on international standards such as EN 16798-1:2019 [44], which establishes a target CO₂for classrooms of 900 ppm, considering a level of 400ppm outdoors. For this, a ventilation flow rate of 12.5l/s per person is prescribed. Pettenkofer’s number, an international recommendation which establishes that 1000ppm is the limit at which IAQ is considered good, is also used. In contrast, the WHO standard is used for PM2.5 and PM10 limits [45], establishing concentration limits of 15 and 45 μg/m 3 , respectively, in a daily exposure period (although other international institutions, such as the EPA, establish different indicators). Finally, in the case of CH 2 O, the WHO [46] recommendation is adopted, with a limit concentration of 100μg/m 3 established for an exposure period of 30min. This provides a standardized framework that can facilitate the comparison of IAQ between different studies. 2.2.2. TC Analysis Group. As detailed above, the evolution of indoor temperatures and relative humidity was analysed for the characterization of TC. The monitoring period corresponds to the full school year in most of the case studies, but data were selected according to the outdoor temperature conditions so that the review focuses on the most unfavourable periods. Both static comfort [43, 47] and adaptive models [44, 48] will be used to objectively analyse the situation of students’TC. In the case of the static model, both RITE 2021 [43] and ISO 7730:2005 [47] define comfort bands depending on the use of the space and the thermal environment category to be achieved. In the case of classrooms, these standards require at least a Category B, which implies a PPD < 10%, and delimits comfort bands of 24 5±15°Cin the summer season and 22 ± 2°Cin the winter season. For the application of the adaptive method ASHRAE 55:2020 [48], the Category I thermal environment is prescribed, which also implies reaching a minimum of 90% acceptability. Thus, if the prevailing mean outdoor temperature (PMOT), calculated using Equation (2), is known and a value of 0.6 applied to the constant α[49], the equations for defining the comfort band limits can be solved. RM T CO2 PM2.5 PM10 CH2O Level 1 Inorganic gases Total particulate matter Organic gases Level 2 Particles Gases Level 3 Level 4 Indoor dissatisfaction index Indoor air pollution index IAPIL2 IDI IAPIIAPIL3 Figure 2: Configuration structure of IAQ and TC objective indices analysis. PMOT = 1 −α·Text,d−1+αText,d−2+α2Text,d−3+α4Text,d−4+⋯ 0 31 × PMOT + 20 3°CUpper limit 0 31 × PMOT + 15 3°CLower limit tC=031 × PMOT + 17 8°COptimum comfort temperature 2 6 Indoor Air ina, 2024, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/2024/2456666 by Readcube (Labtiva Inc.), Wiley Online Library on [12/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License For the application of EN 16798-1:2019 [44], Category III, used for existing buildings, is prescribed. In this case, the running mean outdoor temperature (RMOT) is calculated according to Equation (3), and the upper and lower limits of the comfort band are obtained. In addition to these methods, which provide the percentage of hours outside the comfort bands, an analysis is carried out for IDI G [35], which uses Equation (4), where CA is the comfort agent, ucl/lcl is the upper/lower limit of the comfort band, opt is the optimal value, and obs corresponds to the measured value. As in the case of IAPI G , it works by aggregating several sublevels of hygrothermal parameters (temperature and relative humidity). Although the use of this index is usually limited to static comfort bands, in this case, adaptive bands have been applied. IDI = 1 L〠 L l=I 10 CAi,opt −CAi,obs CAi,ucl −CAi,lcl 4 2.2.3. Monitoring Equipment and Campaigns. Outdoor environmental parameters have been obtained through AEMET [50], which is in charge of the operation of weather stations close to the case study locations. The indoor environmental parameters have been measured in a 1-year monitoring campaign (school year 2022–2023), using a properly calibrated SW-20 Sensonet multisensor, whose characteristics are listed in Table 2, placed inside the classrooms (Figure 3). This datalogger records at 5-min intervals the parameters of globe temperature, air temperature, relative humidity, CO 2 ,CH 2 O, and particulate matter of 2.5 and 10μm. Since the sensors measure a wide variety of pollutants from different sources (occupancy, furniture, outdoor pollution, etc.), which are stratified in the classroom section and are often in motion, they have been placed at a height of approximately 1.5 m, close to the breathing zone and considering the constraints of a classroom environment. In addition, in order to avoid distortions in measurements and, in view of the more intense use of natural ventilation observed in recent times, the sensors have been arranged in the central area of the wall adjacent to the corridor, separate from windows and doors. The setup conforms to standard practice in numerous analogous investigations [51, 52], as well as to commercial and institutional recommendations [53]. In all cases, rigorous data processing and error analysis have been followed to assess consistency and coherence. According to ISO 25012 [54], to obtain high-quality data, five inherent characteristics must be examined: accuracy, completeness, consistency, credibility, and update. In relation to accuracy and update, these depend on the proper accuracy and calibration of the sensors used, as previously described. Regarding completeness, consistency, and credibility, the following criteria have been followed: First, data from occupied and unoccupied periods have been separated, thanks to the availability of schedules, which provides credibility and traceability to the analysis; second, dates have been chosen where both classes in each school had a complete volume of data without interruptions, or where interruptions represented less than 10%; finally, inconsistent data have been detected, meaning that removed illogical values were identified and replaced through interpolation with the nearest values. 2.3. Subjective Approach. This approach makes use of an extensive campaign of surveys supplied and fulfilled in Spanish by students of the different case studies. The surveys were administered by researchers over several sessions in different seasons. A process was carried out to discard contradictory and incomplete responses, thus ensuring consistency in the survey database that is essential to provide veracity and objectivity to the results of the analysis. The dissemination of these results has the informed consent of those responsible for the centres and guarantees the digital rights of the users surveyed in compliance with the guidelines of the Spanish Personal Data Protection Law. The analysis of these survey results focuses specifically on the thermal environment of the classroom, as manifested in a TC vote index (TCV), as well as 0n the answers given in relation to the IAQ, reflected in turn in an indoor air quality vote index (IAQV). 2.3.1. Survey Model. The surveys, which can be found in the supporting information of the publication (Supporting Information 3), were prepared using the survey guidelines on TC and air quality of EN ISO 10551 [55], ASHRAE standard 55 [56], and the survey model used by Campano [57]. The first part of the survey contains the necessary questions to obtain essential information for data management (location, date, time and classroom, window opening pattern, and window position during the survey), in addition to some basic level segmentation parameters (biological sex, date of birth and position within the classroom, clothing insulation, metabolic activity, and whether RMOT = Text,d−1+08Text,d−2+06Text,d−3+05Text,d−4+04Text,d−5+03Text,d−6+02Text,d−7/3 8°C 0 33 × RMOT + 22 8°CUpper limit 0 33 × RMOT + 13 8°CLower limit tC=033 × RMOT + 18 8°COptimum comfort temperature 3 7Indoor Air ina, 2024, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/2024/2456666 by Readcube (Labtiva Inc.), Wiley Online Library on [12/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License they suffer from any chronic illness) and the daily time spent in outdoor spaces. Few next questions ask about the importance, individually and comparatively, of the four variables of indoor environmental comfort. Next, for the subjective evaluation of TC, the indications of Annex A: “Commonly used scales for assessing thermal environments”from the aforementioned UNE-EN ISO 10551 standard are followed. Several questions relating to environmental thermal assessment are used with 5- or 7- point scales in order to establish neutral perceptions and to verify the coherence of the answers given. One of these questions is the TCV, based on the TC question, the answers to which are based on a 5-point scale. In addition, the TSV, which indicates the thermal sensation of the students applying a 7-point scale and helps to verify the TCV, is used. Finally, thermal preference vote (TPV) and a few questions on thermal stratification and humidity, by means of the sweating level, are also asked. There is one last group of questions relating to the IAQ assessment, where olfactory perception and the reproduction of symptoms tied to air quality are checked, before finally moving on to the IAQV, a 5-point acceptability scale of the IAQ. 3. Results and Discussion 3.1. Objective Approach. This section will review the objective results obtained through monitoring in cold and warm seasons during the school year. It is divided into two subsections, one focusing on IAQ and the other on TC. 3.1.1. IAQ Assessment Through IAPI. As mentioned above, CO 2 , PM2.5, PM10, and CH₂O levels have been analysed for the characterization of air quality. In most of the case studies, the monitoring period corresponds to the full school year, although data were selected according to outdoor temperature conditions in order to focus the review on the most unfavourable periods throughout the academic year, that is, the coldest and hottest periods. Applying the monitored parameters for the different substances, Table 3 provides a general summary of the IAQ, in the different climate variants, with a comparison of these for the cold (◊) and warm (∗) seasons. The results are restricted to occupancy time. The first column of each substance shows the mean, median, and min–max value Cable alimentación Cable micro USB configuración desde PC Agujeros sensores Microtarjeta SD Sensor de temperatura de globo LED alimentación Figure 3: Sensor and location used for indoor monitoring of classrooms. Table 2: Measuring equipment characteristics (multisensor SW-20 by Sensonet). Scope Parameters Units Range Accuracy IAQ CO₂Carbon dioxide ppm 0–5000 ±10% CH₂O Formaldehyde mg/m 3 0–6.25 ±0.03 mg/m 3 PM 2.5 2.5 μm particulate matter μg/m 3 0–1000 ±15 μg/m3< 100 ± 15%> 100 PM 10 10 μm particulate matter μg/m 3 Hygrothermal Tg Globe temperature ° C−20 to +65 ±0.5% Ta Air temperature RH Relative humidity % 0–100 ±3% 8 Indoor Air ina, 2024, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/2024/2456666 by Readcube (Labtiva Inc.), Wiley Online Library on [12/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Table 3: Summary of IAQ results by climate zones and seasons, where ◊means cold season and ∗means the warm one. CZ Season CO 2 PM2.5 PM10 CH 2 O IAQ G IAPI G Average median %h>lim (900) Average median % days >lim (15) Average median % days >lim (45) Average median % 0.5 h >lim (0.1) % time >lim Min–max IAPI Min–max IAPI Min–max IAPI Min–max IAPI A3 ◊ 715.7 12.6% 12.7 12.5% 13.7 0.0% 0.035 3.0% 7.0% 6.8634.5 12.5 13.5 0.023 485–1044.7 7.8 10–15.5 9.1 11–16.5 5.9 0.013–0.052 4.2 ∗ 602.2 2.2% 15.4 51.2% 16.8 0.0% 0.04 3.7% 14.3% 6.5570.3 14.5 15.8 0.019 472.7–838.8 7.3 12.5–19.7 9.7 13.5–21.9 5.2 0.011–0.049 3.6 B4 ◊ 999.7 29.3% 16.7 64.9% 18.2 0.0% 0.042 5.7% 25.0% 8.1845.5 15.5 16.5 0.028 542–1669.1 9.6 12.5–22 10 14–24 5.2 0.016–0.072 7.6 ∗ 625.5 6.1% 15.2 49.0% 16.7 0.0% 0.05 7.5% 15.6% 6.2550.5 14.5 15.5 0.026 477.5–1033.8 6.3 12–19.5 9.8 13–22.5 5.2 0.014–0.091 3.7 B3 ◊ 583.9 6.2% 18.8 93.8% 20.1 0.0% 0.132 27.6% 31.9% 7.2515 17.1 18.5 0.062 430.1–999.7 6 14.5–24.5 10 15.5–26 5.8 0.028–0.231 6.8 ∗ 934.9 22.3% 15 38.5% 16.3 0.0% 0.11 13.7% 18.6% 7.4741.8 14.5 15.5 0.045 526.2–1867.9 8.5 11.5–18.4 9.8 13–20 5.8 0.019–0.144 5.6 C4 ◊ 1101.2 33.5% 13 41.4% 14.1 0.0% 0.025 2.2% 19.3% 6.8883 12.5 13 0.017 511.5–2034.2 9.8 8–19 8.7 8.5–20.5 5.6 0.011–0.043 3.1 ∗ 1168.2 40.0% 11.7 38.5% 12.7 0.0% 0.032 5.0% 20.9% 6.2988.8 10.5 11 0.016 544.7–2115.2 10 6.8–18 7.5 7.5–19.5 4.7 0.011–0.055 2.6 C3 ◊ 1079.6 39.5% 13.1 19.4% 14.5 0.0% 0.063 6.2% 16.3% 7.5973.5 12 14 0.032 487–1805.4 10 9–18 8.7 9–19 6.6 0.021–0.066 4.9 ∗ 772.4 16.9% 15.1 50.0% 16.4 0.0% 0.054 5.4% 18.1% 7689.5 15 16 0.025 489.2–1168.8 8.3 11.5–19 9.8 13–22 5.7 0.013–0.069 4.3 9Indoor Air ina, 2024, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/2024/2456666 by Readcube (Labtiva Inc.), Wiley Online Library on [12/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License neutral in both winter and summer, although in summer there was a percentage of votes on the index of preference for a slightly cooler environment. A detailed evaluation of the individual climate zones shows how, in the summer season, Zone B4 stands out with a shift in responses towards Indices 3 and 2, with 46.2% of respondents reporting notable thermal dissatisfaction due to excess heat. Zone A3 (the mildest winters) also stands out in winter, as the percentages are more evenly distributed between indices 1 and −3 (this fits with the indication made by users about the pattern of permanent opening of windows also in winter), as opposed to the rest of the zones, which are concentrated in Indices 0 to −1. The relative position in the classroom of the respondents shows a greater sensation of cold in the band next to the wall separating the classroom from the corridor, which seems logical as radiators are always placed under the windows in classrooms between 5.8 and 6.6m wide, which implies that their coverage is limited, as has been corroborated in previous studies in similar case studies and climate zones [67]. Figure 9(a) shows the relationship between TSV and TCV, finding a clear correlation between the thermal neutrality of TSV (0), and Indices 1 and 2 of TCV, which show thermal satisfaction. Figure 9(b) shows the winter and 0 % 10 % 20 % 30 % 40 % 50 % 60 % 70 % 3210–1 –2 –3 3 210–1 –2 –3 TSV summer TSV winter 17.8 % 19.4 % 21.1 % 38.1 % 0 % 100 % 11.1 % 54.2 % 21.5 % 8.9 % 0 % 100 % A3 B4 B3 C4 C3 3 2 1 0 –1 –2 –3 Figure 8: TSV results clustered by season and climate zone. 0 1 2 3 4 5 –4 –3 –2 –1 0 1 2 3 4 TCV TSV (a) 10 15 20 25 30 35 40 –3 –2 –1 0 1 2 3 T (°C) TSV (b) Figure 9: (a) Comparison of TCV and TSV. (b) Comparison of TSV with respect to indoor temperature. 16 Indoor Air ina, 2024, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/2024/2456666 by Readcube (Labtiva Inc.), Wiley Online Library on [12/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License summer total fit of TSV with respect to the indoor temperature of the classrooms for all climate zones and allows for a graphical analysis. It is worth noting that the significant slope of the temperature trend between TSV Indices −1 and 2. If specifically examining the medians of the ranges for Indices 1, 2, and 3, which indicate a warmer thermal sensation, these thermal sensation stages are obtained with temperatures of 24.5, 30, and 31.2 ° C, respectively. The range of indices indicating a cooler thermal sensation: −1, −2, and −3, occur with temperatures of 19.2 ° C, 18.1 ° C, and 18.2 ° C, respectively. Here, it is observed that responses to cold, predominantly influenced by winter surveys, occur within a narrow temperature range, whereas the response gradient to heat in summer is more differentiated and proportional relative to temperature. Average thermal neutrality (Index 0) for both winter and summer is obtained in the range of 18.4 ° C−25.1 ° C (according to the upper and lower quartiles shown in the graph), with a median value at 21.1 ° C, similar to those obtained in winter survey campaigns in other studies [62]. If only the summer surveys, which are most significant in the warm TSV zone, were isolated, a neutral temperature of 26.1 ° C would be obtained, very similar to the range of 24.6 ° C–26.2 ° C found in similar research studies [31]. The limitations of this work lie in the fact that the opening and closing of doors and windows were not recorded. Instead, the environmental conditions resulting from longterm monitoring under spontaneous use conditions were evaluated. Therefore, the results will primarily serve to provide a general diagnosis of the need for intervention and renovation of these buildings. This is not a research aimed at defining specific protocols or strategies for improving IAQ or TCs which, on the other hand, are difficult to implement effectively in an environment as challenging as a classroom, especially if active participation from the users is required. However, it would be advisable to conduct a more detailed study of the operation of doors and windows to detect general patterns that could be used to evaluate the building’s performance, not only in the present but also under projected future climate scenarios. 4. Conclusions This research focused mainly on TC and IAQ (often conflicting variables), by means of annual monitoring and survey campaigns in archetypal secondary schools in the most representative climate variants of the Mediterranean climate in southern Spain. The methodological approach proposes objective global indices IAPI and IDI along with percentage indicators of teaching time exceeding regulatory limits. This method efficiently evaluates IAQ multisubstance and multiple TC models simultaneously without losing information, being objective and rigorous. The method, although not widely used, is replicable, could simplify comparisons, and greater implementation could help refine the indices. The main conclusions of the environmental characterization are as follows: −In the case of IAQ, respondents report a good level of satisfaction with the IAQ, although this perception is worse in the warm season. IAQ objective results show very variable percentages of teaching time over the limits in the cold season, with values ranging from 7% to 31.9%, and narrower ranges in the warm season, with values of between 14.3% and 20.9%. However, IAPI G shows an improbable situation in all climate zones in both in winter and summer, with values of between 6.2 and 8.1, obtained on the basis of statistically representative values. In addition, the contribution of PM2.5 and CO₂to the index is identified as particularly problematic. −Regarding TC results, both approaches identify a more unfavourable situation in summer than in winter. According to the surveys, 54.2% of the users, in the general count of all climate zones, are in thermal neutrality in the cold season; while in the warm season, 58.3% of the respondents indicate the warmest categories TSV. From an objective standpoint, during the winter season, the comfort band limits are exceeded between 19% and 37% of the time; while in summer, this ranges from 8% to 47%, with IDI G in a range of 1.8–6.8. This illustrates the overheating problem in summer in the warmer climate variants. Now, more than ever, the dichotomy between IAQ and TC is palpable. Although these are often conflicting factors, in the right balance, they are indispensable to achieve quality and healthy environments, as well as being decisive in energy performance. However, uncertainty about environmental conditions in the context of climate change must be assessed. The number of schools built in southern Spain since the application of the 2006 CTE is still relatively low. Therefore, Spanish school stock is inefficient, if not obsolete, in terms of indoor environmental quality and energy use. Its progressive rehabilitation from 2030 to 2050 is one of the major challenges faced by public education in Spain, and the feasibility of this will be greatly dependent on European funding. The conclusions of this work reinforce the need to undertake the large-scale intervention projects expected in this school building stock. Nomenclature AEMET Spanish Meteorological Agency ASHRAE American Society of Heating, Refrigerating and Air-Conditioning Engineers CH₂O formaldehyde (mg/m 3 ) CO₂carbon dioxide (ppm) COV volatile organic compounds CSIC Spanish National Research Council CTE Spanish Technical Building Code EEA European Environment Agency EPA US Environmental Protection Agency HR relative humidity (%) HVAC heating, ventilation, and air conditioning IAPI G IAQ general objective index (−) 17Indoor Air ina, 2024, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/2024/2456666 by Readcube (Labtiva Inc.), Wiley Online Library on [12/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License IAQ G indoor air quality general (−) IAQV IAQ subjective index (−) IDI G TC general objective index (−) IEI IEQ objective index (−) IEQ indoor environmental quality (−) IEQV IEQ subjective index (−) INSST Spanish National Institute for Occupational Safety and Health ISO, UNE International Organization for Standardization, Spanish Association for Standardization NBE-CT Spanish Basic Building Standard in relation to Thermal Comfort (outdated) PM2.5-10 particulate matter (μg/m 3 ) PMOT prevailing mean outdoor temperature ( ° C) PMV, PPD predicted mean vote, predicted percentage of dissatisfied RITE Spanish Regulation on Thermal Installations in Buildings RM relative humidity RMOT running mean outdoor temperature ( ° C) SBS sick building syndrome T, Top air temperature, operative temperature ( ° C) TC thermal comfort (−) TCV TC subjective index (−) WHO World Health Organization Data Availability Statement Data supporting this study cannot be made available due to privacy restrictions of the monitored case studies, as well as for reasons of exploitation, as the data will be used in further research work. Conflicts of Interest The authors declare no conflicts of interest. Author Contributions Conceptualization: J.L., J.J.S., R.S., and A.A.; methodology: J.L., R.S., A.A., and J.J.S.; monitoring campaign and surveys: J.L.; data curation: J.L.; software and visualization: J.L.; formal analysis, J.L., R.S., J.J.S., and A.A.; investigation, J.L., A.A., J.J.S., and R.S.; writing original draft: J.L.; writing review and editing: J.L., J.J.S., R.S., and A.A.; supervision: J.J.S., R.S., and A.A.; funding acquisition: R.S., J.L. All authors have read and agreed to the published version of the manuscript. Funding The authors wish to acknowledge the financial support provided by Grant (PID2020-117722RB-I00) “Retrofit ventilation strategies for healthy and comfortable schools within a nearly zero-energy building horizon”funded by MCIN/ AEI/10.13039/501100011033. In addition, the author J.L. gratefully acknowledges the funding received by the Ministry of Universities through the University Teacher Training Contract Grant Programme (FPU20/04393). Acknowledgments The authors wish to acknowledge the financial support provided by Grant (PID2020-117722RB-I00) “Retrofit ventilation strategies for healthy and comfortable schools within a nearly zero-energy building horizon”funded by MCIN/ AEI/10.13039/501100011033). In addition, the author J.L. gratefully acknowledges the funding received by the Ministry of Universities through the University Teacher Training Contract Grant Programme (FPU20/04393). Supporting Information Additional supporting information can be found online in the Supporting Information section. Supporting Information 1. Table S1 provides a literature review to support the introduction section. 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