Energy implications of meeting indoor air quality and thermal comfort standards in Mediterranean schools using natural and mechanical ventilation strategies

Energy implications of meeting indoor air quality and thermal comfort standards in Mediterranean schools using natural and mechanical ventilation strategies M. Maiques * , J. Tarragona , M. Gangolells , M. Casals Universitat Polit` ecnica de Catalunya, Group of Construction Research and Innovation (GRIC), C/ Colom, 11, Ed. TR5, 08222 Terrassa (Barcelona), Spain ARTICLE INFO Keywords: Indoor air quality Thermal comfort Natural ventilation Mechanical ventilation Educational buildings Energy efficiency HVAC ABSTRACT Educational buildings often face significant challenges with indoor air quality and thermal comfort, mainly due to a lack of mechanical ventilation and air conditioning systems. Research has demonstrated that these issues negatively affect students’learning. The main objective of this paper was to assess compliance with indoor air quality and thermal comfort standards in educational buildings, by quantifying HVAC energy implications under natural and mechanical ventilation strategies. For this purpose, an educational building model that has 4 classrooms occupied by students from different age groups was simulated in 11 Mediterranean climate zones, for 4 ventilation strategies, and with 2 building orientations. The results reveal that natural ventilation is effective only in mild Mediterranean climates, with air quality non-compliance ranging from 0 % to 2 % and thermal comfort non-compliance between 2 % and 5 %. As expected, mechanical ventilation always ensures acceptable indoor air quality and thermal comfort. It achieves average HVAC energy savings of 80 % compared to natural ventilation. When considering that students’CO 2 generation rates vary depending on the age, systems with CO 2 sensors further reduce HVAC demand (8 %), while maintaining comfort levels. Building orientation was found to have a significant impact for naturally ventilated buildings. South-facing orientations can reduce HVAC energy demand by up to 42 % (1,989 kWh/m 2 ⋅year), whereas mechanically ventilated buildings show minimal sensitivity to orientation (up to 36 kWh/m 2 ⋅year). This research will help public authorities of the educational community and architecture and engineering sectors when they are planning, designing and retrofitting educational buildings. Educational building managers will also benefit from this research by being able to optimise building ventilation through the effective management of existing resources. 1. Introduction As recently highlighted by the new Energy Performance of Buildings Directive 2024/1275 [1], improved living standards and increased concerns for human health and well-being have underscored the importance of ensuring indoor comfort in buildings, with a particular emphasis on indoor air quality and thermal comfort. The COVID-19 pandemic further highlighted the importance of maintaining adequate indoor air quality, given that the main mode of virus transmission occurs via airborne infectious particles [2,3,4], with transmission risks heightened in densely occupied indoor spaces with prolonged exposure [5]. Simultaneously, climate change has underscored the need to ensure proper thermal comfort, as it has led to substantial modifications in global weather patterns, including an increased frequency of prolonged heatwaves and extreme temperature events in the Mediterranean area [6]. In schools, poor indoor air quality and thermal discomfort have been demonstrated to adversely impact student performance, contributing to reduced concentration, negative health effects, and higher rates of illness among students [7,8,9]. Indoor air quality is achieved through the ventilation of indoor spaces, which aims to dilute airborne pollutant concentration to acceptable levels. Indoor air quality is commonly quantified by Abbreviations: BMR, Basal metabolic rate; CO 2 , Carbon dioxide; DMV, Direct mechanical ventilation; HVAC, Heating, ventilation and air conditioning; IAQ, Indoor air quality; IMV, Indirect mechanical ventilation; NV100, Full opening of windows and doors natural ventilation strategy; NV50, Half opening of windows and doors natural ventilation strategy; PVGIS, Photovoltaic geographical information system; RITE, Spanish Regulation of Thermal Installations in Buildings; TBC, Technical Building Code; TC, Thermal comfort. * Corresponding author. E-mail address: [email protected] (M. Maiques). Contents lists available at ScienceDirect Energy &Buildings journal homepage: www.elsevier.com/locate/enb https://doi.org/10.1016/j.enbuild.2024.115076 Received 26 September 2024; Received in revised form 31 October 2024; Accepted 17 November 2024 Energy & Buildings 328 (2025) 115076 Available online 19 November 2024 0378-7788/© 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/bync-nd/4.0/ ). measuring the concentration level of carbon dioxide (CO 2 ), which is primarily increased by the respiratory activity of occupants. CO 2 is used as a tracer gas and serves as a surrogate indicator of indoor air quality, as it is typically well dispersed in occupied areas and is easy and reliable to measure [10,11,12]. Air renewal can be achieved through either natural or mechanical ventilation systems. Natural ventilation relies on passive design strategies that allow air to flow through building openings using natural forces such as wind and thermal buoyancy. Although natural ventilation has no operational costs, its efficiency is highly dependent on external conditions such as climate, building orientation and wind. Due to its direct connection with the outside environment, occupant thermal comfort might be significantly compromised [13]. In contrast, mechanical ventilation regulates air renewal to ensure indoor air quality through active energy equipment, using a duct system with fans. Due to the high investment and operational costs associated with mechanical ventilation systems, their adoption in educational buildings has been limited. As a result, most educational buildings in Europe lack mechanical ventilation systems [14,15]. Therefore, natural ventilation is the only available ventilation method. The effectiveness of this method relies on the occupants’subjective assessment of comfort. Ventilation results in energy losses due to the exchange of indoor and outdoor air, leading to compromised thermal comfort. Thermal comfort is ensured by using heating systems and air conditioning equipment to maintain comfortable indoor temperatures. Therefore, balancing indoor air quality and thermal comfort is essential [16]. Previous research involving on-site measurements in naturally ventilated educational buildings across Europe has demonstrated that relying exclusively on natural ventilation is insufficient to maintain acceptable indoor air quality during all occupied periods without affecting thermal comfort. Studies conducted in London [17], Spain [18,19], Italy [20,21], Portugal [22], Cyprus [23] and Turkey [24] consistently determined that CO 2 concentration limits are often exceeded. This highlights the need for improved ventilation strategies to ensure that indoor air quality and thermal comfort are effectively achieved. Along this line, Miao et al. [15] assessed indoor air quality and thermal comfort in 32 naturally ventilated schools in the Mediterranean climate based on an extensive monitoring campaign. Their results indicated that the minimum requirements for both aspects were only met 46 % of the time. Poor indoor air quality was mainly due to closing windows and doors in winter, whereas thermal discomfort mainly occurred in summer due to high indoor temperature. Other studies based on on-site measurements in schools equipped with mechanical ventilation systems have concluded that both CO 2 - based and constant airflow ventilation systems are effective in maintaining optimal CO 2 concentration levels [25]. In the context of the COVID-19 pandemic, research has demonstrated that mechanical ventilation has a positive impact on controlling infection [26,27,28,29]. Additionally, demand-controlled ventilation systems have been shown to maintain acceptable indoor air quality and offer more energy-efficient solutions [30]. Few studies have quantified the impact of natural and mechanical ventilation strategies on indoor air quality, thermal comfort and energy consumption in schools under a simulation-based approach. Bernardo et al. [31] conducted a year-long simulation of a school building in the city of Coimbra, Portugal, using mechanical ventilation strategies over a year. Their results showed that extending the operating hours of mechanical ventilation systems could improve air exchange rates without increasing energy consumption. However, the study did not quantify the impact of these changes on indoor air quality and thermal comfort. Pollozhani et al. [32] evaluated the functionality of natural and mechanical ventilation strategies within the COVID-19 pandemic context in a classroom of an Austrian university. Their research combined on-site measurements for natural ventilation strategies with simulations of various mechanical ventilation approaches using building performance simulation software. They concluded that a trade-off between acceptable indoor air quality, thermal comfort and energy efficiency can only be achieved through mechanical or hybrid ventilation methods. In a recent study, Rizzo et al. [33] explored the potential for enhancing indoor air quality and thermal comfort in a Maltese school through the simulation of an educational building with a demand-controlled ventilation system for a one-year period. The findings indicated that with this system, CO 2 levels are maintained below the recommended threshold for at least 76 % of the year, depending on classroom orientation. Finally, Zemitis et al. [34] simulated a classroom in Latvia with natural ventilation strategies. They concluded that they are not able to provide proper thermal comfort levels with these strategies. To the authors’knowledge, the abovementioned simulation-based research initiatives typically assumed a constant CO 2 generation rate, along the lines of most current standards (i.e. the Spanish Technical Building Code [35]. However, ASTM D6245-18 “Standard Guide for Using Indoor Carbon Dioxide Concentrations to Evaluate Indoor Air Quality and Ventilation”[36] and recent experimental findings by Tugores et al. [37] indicate that the CO 2 generation rate of individuals is influenced by factors such as age, gender, weight and level of physical activity. Moreover, existing research in the field typically simulates educational buildings in a specific location under particular climate conditions. In addition, studies have not explored the impact of building orientation in relation to each ventilation strategy. Therefore, to overcome the aforementioned gap, this paper quantifies, for the first time, the energy required to ensure indoor air quality and thermal comfort in schools under natural and mechanical ventilation strategies. It provides a comprehensive analysis that considers the influence of tailored CO 2 generation rates and the effect of building orientation in all Mediterranean climate types. The results of this research will provide valuable insights for the design and upgrading of educational buildings, with the ultimate purpose of optimising the allocation of often scarce economic resources, and thus providing tools to assist in decision-making for the installation of mechanical ventilation systems. This paper is structured in five sections. Section 2 outlines the methodological steps employed in this research. Section 3 introduces the specific case study implemented. Section 4 presents and discusses the results. Finally, Section 5 summarises the conclusions derived from this research. 2. Methodology Fig. 1 summarises the methodological steps taken to assess the energy implications of ensuring indoor air quality and thermal comfort in a building. This process involves the creation of a building model through the use of dynamic energy simulation software. The simulation of the model requires input data defining the building conditions, including space occupancy, boundary conditions such as weather data, outdoor CO 2 levels and building orientation, as well as control parameters for indoor air quality and thermal comfort based on relevant standards. Additionally, the ventilation strategies to be evaluated must be defined. Finally, the simulation of this data generates key performance indicators for indoor air quality, thermal comfort and energy consumption of HVAC systems. Each step is explained in more detail in the following sections. 2.1. Development of the building model and data input First, dynamic energy simulation software must be used to develop the building model. As shown in Fig. 1, the simulation of the building model requires input data (occupancy internal gains, boundary conditions and control parameters). Regarding occupancy internal gains, occupants are considered to be internal sources of CO 2 and heat gains. The influence of occupancy is assessed according to the guidelines specified in ASTM [36], which define the CO 2 generation rate of individuals. Additionally, ASTM [36] determines the basal metabolic rate (BMR), which represents M. Maiques et al. Energy & Buildings 328 (2025) 115076 2 individuals’heat generation. The CO 2 generation rate (VCO2) expressed in L/s⋅person depends on an individual’s body size and level of physical activity. This rate is determined by ASTM [36] using Equation (1). VCO2=RQ ⋅BMR⋅M⋅(T/P)⋅0.000211 (1) Where RQ indicates the respiratory quotient, a dimensionless parameter that represents the ratio of the volumetric rate of CO 2 production to the rate of oxygen consumption by an individual. This value depends on diet, with established literature on human nutrition suggesting an approximate value of 0.85 [38].BMR represents the basal metabolic rate of individuals expressed in MJ/day (Table 1). Mrepresents the metabolic rate per unit of surface area, expressed in dimensionless units of metabolic equivalent (met). This parameter serves to quantify the rate of human energy use associated with specific physical activities. Trefers to the zone temperature (K) and Pto the zone pressure (kPa). The occupancy internal heat gains are also determined by the basal metabolic rate (Table 1). The boundary conditions of the building, such as the weather patterns, outdoor CO 2 concentration and building orientation, must be defined according to the specific location. A typical meteorological year’s weather file, which provides a comprehensive set of hourly weather data for an entire year based on historical weather data, is required for the simulation software. Regarding the control parameters for indoor air quality and thermal comfort, maximum indoor CO 2 concentration and temperature setpoints must be defined according to the corresponding standards. 2.2. Identification and characterisation of ventilation strategies This paper explores two ventilation strategies: (i) natural ventilation, achieved through the opening of windows and doors, which is a common strategy employed in many educational buildings that lack alternative ventilation systems, and (ii) mechanical ventilation, implemented in newer school facilities. 2.2.1. Natural ventilation Natural ventilation is commonly achieved through large openings such as windows or doors. In cases with inlet and outlet openings of similar size and minimal internal resistance, the volume airflow (qv), expressed in m 3 /s, can be determined by considering both wind and buoyancy effects. According to Schulze &Eicker [39], volume airflow can be calculated along the lines of Equation (2). qv=Cd⋅Aeff ⋅  Cp,1⋅u2 w,1−Cp,2⋅u2 w,2 2±(Tin −Tout)g⋅hs Tin  √(2) Where Cdrepresents the discharge coefficient, which is assumed to be 0.60. Aeff (m 2 ) denotates the effective opening surface. Cp,1and Cp,2are the wind pressure coefficients of the inlet and the outlet respectively, uw,1and uw,2(m/s) are the reference wind speeds at the centroid of the inlet and the outlet openings respectively. Tin and Tout (K) are the temperature of the indoor building and the outdoor ambient air respectively and gis the gravity acceleration (9.81 m/s 2 ). Finally, hs(m) represents the stack height, which is the difference between the midpoints of the input and output openings. 2.2.2. Mechanical ventilation Conventional mechanical ventilation systems operate through an air loop installed in each thermal zone of the building. The system equipment typically includes a mixing box that combines the recirculated air from the zone with fresh outdoor air, a fan that recirculates the mixed air back into the zone, and a network of ducts arranged in a loop (Fig. 2). This arrangement allows regulation of both the recirculated air flow rate and the proportion of outdoor air. 2.2.3. Infiltrations Regardless of the ventilation strategy, buildings naturally have cracks in their envelopes, which cause air renewal. The airflow (Q) Fig. 1. Methodology. Table 1 Equations for calculating the basal metabolic rate. Age (years) Basal metabolic rate (MJ/day) Males Females <30.249⋅m−0.127 0.244⋅m−0.130 3 to 10 0.095⋅m+2.110 0.085⋅m+2.033 10 to 18 0.074⋅m+2.754 0.056⋅m+2.898 18 to 30 0.063⋅m+2.896 0.062⋅m+2.036 30 to 60 0.048⋅m+3.653 0.034⋅m+3.538 ≥60 0.049⋅m+2.459 0.038⋅m+2.755 Source: adapted from [36] M. Maiques et al. Energy & Buildings 328 (2025) 115076 3 expressed in (kg/s) through an infiltration depends on the pressure difference across the crack and the measurement conditions, as described by Equation (3). Q=CF⋅CT⋅CQ⋅(ΔP)n(3) Where CFis the crack factor and corresponds to the percentage of crack aperture in relation to crack size, it is assumed to be 1. CQis the air mass flow coefficient (kg/s⋅Pa n at 1 Pa), ΔP is the pressure difference across the crack (Pa), and nrepresents the air flow exponent. CTis the reference condition temperature correction factor, estimated as indicated in Equation (4). CT=[ ρ o ρ ]n−1 ⋅[ υ o υ ]2n−1(4) Where ρ (kg/m 3 ) and υ (m 2 /s) denotate the air density and the air kinetic viscosity, respectively, in the specific air temperature and humidity ratio conditions. ρ o (kg/m 3 ) and υ o (m 2 /s) represent the air density and the kinetic viscosity, respectively, in the reference air conditions. 2.3. Key performance indicator analysis Key performance indicators are analysed within indoor air quality, thermal comfort, and heating, ventilation, and air conditioning (HVAC) energy performance domains. 2.3.1. Indoor air quality Indoor air quality is assessed by examining the indoor CO 2 concentration. In this case, the suggested indicator is hours of unmet indoor air quality (UHCO2). This indicator measures the number of hours in a period that surpass the CO 2 limit concentration set by the applicable standard (Equations (5) and (6)). UHCO2=∑ N i=1 f(CO2i−CO2limit)(5) f(x) = {1if x >0 0if x <0 UHCO2(%) = unmet CO2hours ∑N i=1i⋅100 (6) Where Nis the total number of hourly values,CO2i(ppm) represents the CO 2 concentration at hour iand CO2limit (ppm) the CO 2 limit concentration recommended by the applicable standard. 2.3.2. Thermal comfort Thermal comfort is evaluated through indoor temperature values. In this case, the suggested indicator is unmet thermal comfort hours (UHT). This indicator measures the overall hours in a period in which the indoor temperature is out of an acceptable temperature range set by the applicable standard (Equations (7) and (8)). UHT=∑ N j=1 g(Tj<Tmin or Tj>Tmax)(7) g(x) = {1if x =True 0if x =False UHT(%) = unmet T hours ∑N j=1j⋅100 (8) Where Nis the total number of hourly values, Tj(◦C) the temperature at hour j,Tmin (◦C) the minimum temperature recommended by the applicable standard, and Tmax (◦C) represents the maximum temperature allowed by the applicable standard. 2.3.3. HVAC energy performance For the evaluation of building energy performance, the monthly HVAC energy demand (Em) and the annual HVAC energy demand (Ey), expressed in kWh/m 2 , are calculated (Equations (9) and (10)). Em=∑Nm i=1Em,i A(9) Ey=∑ 12 i=1 Em(10) Where Em,irepresents the HVAC energy demand for hour iin month m (kWh) and Ais the total area (m 2 ). 3. Description of the case study A building model with various zones replicating the behaviour of school classrooms was created and simulated using EnergyPlus [40] V23.1.0 software. The model includes natural ventilation through operable external windows and internal doors, and an HVAC system for heating, air conditioning and mechanical ventilation. This model was simulated in different Mediterranean regions to evaluate the impact of climate on indoor air quality, thermal comfort and HVAC energy demand. Additionally, the influence of the occupants’age and the impact of classroom orientation was assessed. 3.1. Description of the building model and data input This section describes the building model created for the simulations and the data input. 3.1.1. Building model The building has a two-level rectangular layout with a total floor area of 297.2 m 2 and a flat roof (Fig. 3). The ground floor is divided into three zones, as shown in Fig. 4: (i) the Hall 0 zone, (ii) Classroom A0 oriented to the southwest (iii) and Classroom B0 orientated to the southeast. Hall 0 has a single north-facing window (3.0 m x 1.3 m), while the two classrooms are each equipped with a single south-facing window (4.0 m x 1.5 m). Additionally, two doors (1.0 m x 2.0 m), provide access between the hall area and the respective classrooms. The layout of the first floor mirrors that of the ground floor, which has an identical configuration. On the first floor, rooms are designated as Hall 1, Classroom A1 and Classroom B1. Additionally, there is a horizontal aperture communicating Hall 0 of the ground floor and Hall 1 of the first floor. In the base case, classrooms are oriented to the south (Fig. 4). Table 2 describes the properties of the building envelope construction materials from the outermost layer to the innermost layer. Regarding the HVAC system, the building is equipped with variable air volume equipment. This type of system controls the dry bulb Fig. 2. Diagram of a mechanical ventilation system operation. M. Maiques et al. Energy & Buildings 328 (2025) 115076 4 temperature by varying the volume of supply air. The heating, airconditioning and ventilation share the same duct system (Fig. 5). For thermal comfort, the circulating air is heated or cooled by the heating coil or cooling coil depending on the climate requirements. For ventilation, the proportion of outside air and recirculated air in the mixing box is varied to meet the air quality requirements. Each conditioned zone has one of these loops that is completely independent from the others, providing fully independent results for each zone. As the four classrooms share the same characteristics, the specifications of all the components are the same in each system. 3.1.2. Data input This section defines the occupancy internal gains of the building, the boundary conditions and the control parameters of the case study. 3.1.2.1. Occupancy internal gains. Occupancy internal loads contribute to CO 2 gains and thermal gains. To accurately simulate the behaviour of a school environment, each of the four classrooms are assumed to host the same number of occupants (Fig. 6), distinguishing between weekdays and weekends. Given that each classroom contains students of the same age group, but all classrooms host different grade students (Table 3), basal metabolic rate and CO 2 generation rate were computed using Equation (1) with a Monte Carlo approach. The application of the prescribed equation requires the determination of occupants’body mass, the gender of the occupants and the activity performed in each zone. Fig. 3. EnergyPlus building model developed. Fig. 4. Building layout of the ground floor (left figure) and the first floor (right figure). M. Maiques et al. Energy & Buildings 328 (2025) 115076 5 For the purpose of this research, body mass data were randomly selected from the distribution of child body mass data [41]. Mean values and standard deviations for each age and gender are detailed in Table 4. A gender distribution of 52 % males and 48 % females was considered, based on the average birth rate in Catalonia from 2000 to 2022 [42]. Regarding the metabolic rate, random values ranging from 1.2 to 1.6 MET were considered, corresponding to activities such as sitting quietly, reading, writing, typing and standing, in accordance with the ASTM [36] standard. Furthermore, an indoor temperature of 23 ◦C was assumed, according to the Spanish Regulation of Thermal Installations in Buildings (RITE) [43], along with an atmospheric pressure of 101 kPa. Table 5 summarises the results used as inputs for internal CO 2 gains in the building simulations. 3.1.2.2. Boundary conditions. In accordance with the Spanish Technical Table 2 Thermal properties of construction materials. Element Material Thickness (cm) Conductivity (W/m⋅K) Density (kg/m 3 ) Specific heat (J/kg⋅K) External walls Stucco 2.54 0.69 1858.14 836.80 Bricks 10.15 0.73 1922.22 836.80 Gypsum plasterboard 1.90 0.73 1601.85 836.60 Internal walls Gypsum plasterboard 1.90 0.73 1601.85 836.60 Insulation 20.33 0.57 1121.29 836.80 Gypsum plasterboard 1.90 0.73 1601.85 836.60 Ground floor slab Concrete 20.33 1.73 2242.59 836.80 First floor slab Concrete 17.30 1.73 2242.59 836.80 Ceiling Stone 1.23 1.44 881.02 1673.60 Felt and membrane 0.95 0.19 1121.29 1673.60 Dense insulation 2.54 0.04 91.31 836.80 Concrete 5.09 1.73 2242.59 836.80 Fig. 5. HVAC system diagram. Fig. 6. Occupancy profile of the classrooms. Table 3 Students’age. Classroom Age (years) A0 4 B0 10 A1 13 B1 16 Table 4 Body mass distribution depending on students’age. Age (years) Body mass (kg) Male Female Mean Standard deviation Mean Standard deviation 4 18.04 2.57 14.91 1.44 10 36.05 7.32 36.11 6.26 13 49.21 8.45 64.98 1.82 16 64.98 11.82 57.84 8.96 M. Maiques et al. Energy & Buildings 328 (2025) 115076 6 Building Code [35], the outdoor air CO 2 concentration was assumed to be 400 ppm for all locations. The Spanish Technical Building Code (TBC) describes different winter and summer climate zones depending on the location. The winter climate is represented with a letter ( α , A, B, C, D and E), where α is the warmest winter and E the coldest one. The summer climate is represented with a number from 1 to 4, where 1 represents the coldest summer and 4 the warmest. For the analysis of the Mediterranean zone, the building model was simulated in all the winter-summer climate combinations found in the Spanish Mediterranean regions. For each climate zone, a representative location was selected (Table 6 and Fig. 7). As shown in Table 6, all these climates were related to the K¨ oppen-Geiger climate classification systems, which is effective in categorising long-term patterns based on average temperature and precipitation and serves as a global reference for understanding climate types [44]. In this paper, the typical meteorological year files required for the dynamic energy simulation software for each location were obtained from the Photovoltaic Geographical Information System (PVGIS) webpage [45]. 3.1.2.3. Control parameters. Ventilation methods and related constraints were identified in accordance with the Spanish Regulation of Thermal Installations in Buildings (RITE) standard [43]. In this standard, the indoor air quality requirements are stated depending on the space’s end use (Table 7). In this case, considering that the building serves as a school, the maximum acceptable indoor CO 2 concentration is 900 ppm (IDA 2). According to the Spanish Regulation of Thermal Installations in Buildings [43], the temperature setpoint value for the heating period (from 1 January to 30 April and from 1 October to 31 December) must be 21 ◦C. For the cooling period (from 1 May to 30 September), it must be 25 ◦C. 3.2. Definition of ventilation strategies To compare ventilation methods in terms of indoor air quality, thermal comfort and HVAC energy demand, the model was simulated for the ventilation strategies detailed in Section 2. For the application of the ventilation strategies, two natural ventilation strategies using the building’s openings and two mechanical ventilation strategies specified by the Spanish Regulation of Thermal Installations in Buildings [43] were analysed. In approaches where natural ventilation is used, there is no control mechanism to ensure that air quality standards are met. 3.2.1. Natural ventilation strategies Previous studies [23,15,37] based on on-site measurements in the Mediterranean region have found cross-ventilation through windows and doors to be the most effective natural ventilation strategy. Additionally, Miao et al. [15] performed a large monitoring campaign in 32 naturally ventilated schools in the Mediterranean region, identifying an average window and door opening area of 6.6 m 2 . Furthermore, Heracleous &Michael [23] research demonstrated that optimal natural cross-ventilation in educational buildings is achieved when applied for 20 min every 2 h. Based on these findings, and consistent with typical school operations characterised by 1-hour lessons, the selected natural ventilation strategy is to open windows and internal doors for 10 min per hour. Two degrees of window opening were considered for this approach: - Full opening of windows and doors (NV100), corresponding to a total opening area of 8 m 2 . - Half opening of windows and doors (NV50), corresponding to a total opening area of 5 m 2 . In all cases, there is no mechanical ventilation. Therefore, all airflow within the HVAC air loop is recirculated from the respective zone. 3.2.2. Mechanical ventilation strategies According to the Spanish Thermal Building Regulation [43], two mechanical ventilation control strategies are defined: - Indirect mechanical ventilation (IMV): minimum airflow rates are established according to the IDA level (Table 7). In this case, an airflow rate of 12.5 L/s⋅person is required (Table 8). - Direct mechanical ventilation (DMV): minimum airflow rates are determined by the maximum admissible indoor CO 2 concentration, according to the IDA level (Table 7). In this case, the maximum allowable CO 2 concentration is 900 ppm (Table 8). 3.3. Key performance indicators analysis Indoor air quality, thermal comfort and HVAC energy performance key performance indicators are calculated according to the methodology described in Section 2.3. The values of occupancy internal gains, boundary conditions and control parameters of the case study are applied. The results obtained from these analyses are subsequently discussed in Section 4. 4. Results and discussion Section 4.1 analyses the impact of climate zones on the effectiveness of natural and mechanical ventilation strategies, through an assessment of indoor air quality, thermal comfort and HVAC energy demand in educational spaces. Section 4.2 discusses the effect of building orientation depending on the climate zone and the ventilation strategy. Section 4.3 evaluates the influence of occupants’age on indoor air quality and HVAC energy demand. Finally, Section 4.4 provides a global assessment of indoor air quality, thermal comfort and HVAC energy demand for all the ventilation strategies and building orientations. 4.1. Analysis of the impact of the climate zone on ventilation strategies In this section, the balance between indoor air quality and thermal comfort, along with HVAC energy demand, is analysed to assess the Table 5 CO 2 generation rate and thermal gains of occupants depending on their age. Age (years) CO 2 gains Thermal gains CO 2 generation (L/h) BMR (W) Mean Standard deviation Mean Standard deviation 4 41.34 3.83 9.51 1.21 10 63.02 6.70 13.66 1.66 13 73.04 8.43 16.19 2.36 16 88.02 9.87 18.11 3.11 Table 6 Representative Mediterranean climate zones. Climate zone (TBC) Geographical coordinates Region Altitude (m) K¨ oppenGeiger climate E1 42.448, 1.880 Girona 1367 Cfb D1 42.101, 1.845 Barcelona 692 Cfb D2 40.380, −0.141 Castell´ o 832 Csb D3 41.310, 0.988 Tarragona 947 Csb C2 42.073, 2.836 Girona 75 Csa C3 38.231, −1.700 Murcia 355 Bsk C4 36.799, −3.639 Granada 366 Csa B3 39.472, −0.386 Valencia 24 Bsh B4 38.354, −0.490 Alicante 68 Bsh A3 36.720, −4.433 M´ alaga 20 Csa A4 36.763, −2.612 Almería 11 Bsh M. Maiques et al. Energy & Buildings 328 (2025) 115076 7 impact of the climate zone for each ventilation strategy. 4.1.1. Indoor air quality and thermal comfort Fig. 8 summarises the indoor air quality and thermal comfort performance of the classrooms when the building is located in the considered climate zones under both natural and mechanical ventilation strategies in terms of percentage of unmet hours in a year (Equations (6) and (8)). As expected, both direct and indirect mechanical ventilation strategies always meet indoor air quality and thermal comfort requirements. The fully opening windows and doors natural ventilation strategy (NV100) largely ensures good indoor air quality (less than 1 % of unmet CO 2 hours) but compromises thermal comfort, particularly in cold climates (10 % of unmet temperature hours in climate zones D1 and 14 % in climate zone E1). When natural ventilation is employed with half the windows and doors open (NV50), indoor air quality deteriorates, especially in regions with warmer summers (approximately 3–5 % of unmet CO 2 hours for A4 and C4 climate zones). The percentage of temperature unmet hours slightly decreases compared to the NV100 strategy but remains high in cold climate zones (around 8–10 % in D1 and E1 climate zones, respectively). The influence of the climate zone demonstrates that employing natural ventilation strategies in more extreme hot and cold climates results in higher deterioration of indoor air quality and thermal comfort. 4.1.2. HVAC energy demand Ventilation strategies were compared in terms of HVAC energy demand in all Mediterranean climate zones (Fig. 9). Colour coding was employed to facilitate table interpretation. The darkest red cells indicate the highest HVAC demand, while the darkest green cells indicate the lowest demand. For natural ventilation, using half-open windows (NV50) results in an average energy saving of 50 % for heating and 43 % for cooling compared to fully open windows (NV100). For mechanical ventilation, a direct mechanical ventilation strategy (DMV) represents an average energy saving of 8 % in heating and 7 % in cooling. Overall, mechanical ventilation, compared to natural ventilation, results in an average HVAC energy demand reduction for all climate zones of 90 % in the heating period and 71 % in the cooling period. Furthermore, although the percentage of savings was found to be similar across all climate zones, the total savings in absolute terms were much more significant in colder zones during the heating period and in warmer zones during the cooling period. For example, when the direct mechanical ventilation (DMV) strategy was compared with the full opening natural ventilation (NV100) strategy during the heating period, the savings were found to amount to 1196 kWh/m 2 ⋅year in the A climate zone, whereas in the E climate zone, the savings were triplicated (3459 kWh/m 2 ⋅year). Similarly, during the cooling period, the DMV strategy compared to the NV100 strategy resulted in savings of 457 kWh/m 2 ⋅year in the 1 climate zone, while in the 4 climate zone, the savings rose slightly to 662 kWh/m 2 ⋅year. 4.2. Analysis of the impact of building orientation Fig. 10 summarises the results obtained when the influence of building orientation was evaluated in all Mediterranean climate zones using the defined ventilation strategies. Bubble size is proportional to Fig. 7. Representative Mediterranean locations. Table 7 Indoor air quality categories according to the use of buildings. Category Air quality level End uses Maximum indoor CO 2 concentration (ppm) IDA 1 Optimum Hospitals, clinics, laboratories, nursery schools 750 IDA 2 Good Offices, residences, reading rooms, museums, classrooms 900 IDA 3 Medium Commercial buildings, hotel rooms, restaurants, etc. 1200 IDA 4 Low −1600 Source: adapted from [43] Table 8 Mechanical ventilation constraints from the RITE regulation. Category Indirect mechanical ventilation (IMV) Direct mechanical ventilation (DMV) Airflow rate (L/s⋅person) Maximum indoor CO 2 concentration (ppm) IDA 1 20.0 750 IDA 2 12.5 900 IDA 3 8.0 1200 IDA 4 5.0 1600 Source: adapted from [43] M. Maiques et al. Energy & Buildings 328 (2025) 115076 8 Fig. 8. Indoor air quality and thermal comfort performance in the considered climate zones under both natural and mechanical ventilation strategies. Climate zones Heating and cooling demand (kWh/m 2 ·year) Natural ventilation strategies Mechanical ventilation strategies NV100 NV50 IMV DMV Heating demand (winter climate zone) A 1279.12 603.21 91.50 82.40 B 1579.62 770.28 116.76 107.67 C 2199.97 1079.43 139.95 131.18 D 2801.29 1346.81 177.86 164.35 E3670.14 1769.8 232.32 211.17 Cooling demand (summer climate zone) 1565.54 297.5 110.94 107.95 2 533.15 301.78 144.03 133.74 3 669.96 391.72 154.51 143.17 4 837.14 519.92 200.72 175.01 Fig. 9. Heating and cooling demand (kWh/m 2 ⋅year) for Mediterranean climate zones. M. Maiques et al. Energy & Buildings 328 (2025) 115076 9