Impact of Indoor Air Quality, Including Thermal Conditions, in Educational Buildings on Health, Wellbeing, and Performance: A Scoping Review

Abstract

Educational buildings, including schools, nurseries and universities, face stricter regulation and design control on indoor air quality (IAQ) and thermal conditions than other built environments, as these may affect children’s health and wellbeing. In this scoping review, wide-ranging health, performance, and absenteeism consequences of poor—and benefits of good—IAQ and thermal conditions are evaluated, focusing on source control, ventilation and air purification interventions. Economic impacts of interventions in educational buildings have been evaluated to enable the assessment of tangible building-related costs and savings, alongside less easily quantifiable improvements in educational attainment and reduced healthcare. Key recommendations are provided to assist decision makers in pathways to provide clean air, at an optimal temperature for students’ learning and health outcomes. Although the role of educational buildings can be challenging to isolate from other socio-economic confounders, secondary short- and long-term impacts on attainment and absenteeism have been demonstrated from the health effects associated with various pollutants. Sometimes overlooked, source control and repairing existing damage can be important cost-effective methods in minimising generation and preventing ingress of pollutants. Existing ventilation standards are often not met, even when mechanical and hybrid ventilation systems are already in place, but can often be achieved with a fraction of a typical school budget through operational and maintenance improvements, and small-scale air-cleaning and ventilation technologies, where necessary.

1. Introduction

Young people in high-income countries spend a substantial amount of time in educational buildings such as nurseries, schools, colleges, and universities. Approximately 180 days of the year and roughly 30% of a child’s waking hours are spent at school [1,2,3], where they are exposed to indoor air quality (IAQ), thermal, acoustic, and lighting aspects of indoor environmental quality (IEQ) outside of their control.

Throughout the last two decades, IEQ in educational buildings has been framed in a multitude of ways in literature. Holistic evaluations of IEQ have attempted to incorporate a range of environmental factors, including air pollutants generated outdoors in the vicinity of the building [4,5] and with respect to often conflicting IEQ components of acoustic, lighting, and thermal quality [6,7]. Other studies have focused on impacts from singular aspects of IEQ on occupants’ health and wellbeing [4,7,8], absenteeism [8], attainment [9] or a combination of the above [10]. Within IEQ, acoustic, lighting and visual aspects constitute important and substantial fields of study, even on their own, and can influence ventilation practices [11,12]. To focus on ventilation and air cleaning interventions, this scoping review will consider only aspects of IEQ which quantify the impact of exposure to poor indoor air quality (IAQ), thermal conditions and ventilation in educational buildings on health, wellbeing and attainment of students. Thermal conditions encompass measured indoor temperatures (objective) and perceived thermal comfort (subjective), both of which can impact learning capability and health outcomes. Since the focus is on educational buildings of all varieties, the term “students” in this context includes children, adolescents and adults, as colleges also cater to adult/mature students, but excludes other building occupants such as teaching and facilities staff. Steps taken to improve IAQ and thermal comfort can include control of indoor pollution sources [13], measures to reduce heat fluctuations through improved insulation, airtightness or energy performance [14], and/or installation and appropriate maintenance of heating, cooling and ventilation systems [15,16]. All of these may result in increased capital or operating costs, but could be offset by associated net socio-economic benefits [17].

Growing research evidence demonstrating reduced building energy consumption alongside maintaining good IAQ and thermal conditions [18,19] will continue to be of importance as the world moves towards reaching national and international Net Zero greenhouse gas (GHG) emission targets [20], due to the alterations made to the airtightness and insulating properties of buildings. Despite the increasing focus on the potential health and educational outcomes associated with improving IAQ and thermal conditions in educational buildings [21,22], there seems to be a disconnect between the scientific evidence and weighing up the economic costs of implementing the interventions in practice. Bridging this gap could aid decision-makers in developing their own methods to conclude whether investing in interventions to improve aspects of IEQ could be worth the short- and long-term benefits to the students. This scoping review aims to reduce this gap in decision-making capability by detailing the latest evidence of IAQ and thermal conditions’ impacts on health in educational buildings, and how they translate into impacts on absenteeism and performance. Furthermore, we review the latest literature outlining the factors that need to be accounted for within a cost-benefit analysis of interventions to improve IAQ and thermal comfort.

2. Background

2.1. IAQ, Ventilation and Thermal Conditions

Air pollutants in educational microenvironments, such as daycare centres, classrooms and university lecture theatres, include particulate matter (PM) of all sizes (including black or elemental carbon), inorganic pollutants (e.g., nitrogen dioxide (NO₂), ozone (O₃), and sulphur dioxide (SO₂)), organic pollutants (e.g., formaldehyde, benzene, and other volatile organic compounds (VOCs), as well as biological contaminants (mould, fungi etc.)). A comprehensive list of priority pollutants for health impact assessments has previously been provided by the World Health Organisation (WHO) [23]. Some of these pollutants are generated indoors, while traffic-related air pollutants (TRAP) such as NO₂ (from combustion engine ignition), PM_2.5 (from brake wear) or pollution from industrial activities in the vicinity of the building can infiltrate indoors and significantly contribute to IAQ [2,4,21,24].

Indoor air pollution is closely linked to outdoor sources. PM_2.5, NO_2, black carbon (BC), ultrafine particles (UFP), metals, polycyclic aromatic hydrocarbons (PAHs) and certain VOCs are associated with industrial activity [2,21,24]. Finer particulates (e.g., PM_2.5, PM₁ and UFP) often come from outside, while higher PM₁₀ concentrations are linked with occupants’ activities indoors [24]. Median concentrations of PM₁₀ indoors have been reported at three times the outdoor concentrations, while PM_2.5 concentrations were comparable [25].

Ozone (O₃) forms in sunlight and reacts with VOCs from construction or cleaning materials and teaching activities, generating other indoor pollutants [25]. Without additional air filtration, naturally ventilated buildings are susceptible to the uncontrolled ingress of outdoor pollutants through cracks and gaps, with indoor/outdoor ratios of certain species often reported to be close to unity [10]. While NO₂ can also be generated indoors from combustion appliances such as boilers or catering facilities, studies of Dutch [24], French [26] and Turkish schools [25] showed that indoor NO₂ concentrations correlated with vehicle traffic, indicating infiltration and exposure to outdoor NO₂ and that even airtight buildings were not protective against outdoor NO₂.

Higher PM concentrations in classrooms observed in Asian and European studies compared to those in the United States and Northern Europe [25] indicate a need to investigate building location as a potential driver of such differences. Differences have also been reported between countries with similar climates and locations [22], with average indoor PM₁₀ concentrations found at minimal levels in Sweden (33 μg/m³) and Norway (54 μg/m³), compared to, e.g., 169 μg/m³ in Denmark, where ventilation standards and air cleaning practices vary [27]. This demonstrates the ability of interventions such as mechanical ventilation and air cleaning, which vary from country to country [27], to influence indoor concentrations and hence exposures.

Adequate ventilation provision is an integral element of maintaining good IAQ in educational buildings. In the UK, Building Bulletin 101 (BB101) guidance sets out standards for individual pollutant levels, ventilation design and rates and thermal comfort, which has been summarised in Table S1 in the Supplementary Materials. Minimum ventilation standards vary across different countries, based on carbon dioxide (CO₂) concentrations or airflow per occupant [28]. The Scientific Technical Committee 34 (STC34) of the International Society of Indoor Air Quality and Climate (ISIAQ) compiled a database with air quality guidelines and standards, including CO₂ [29,30]. Table S2 shows the guidelines for different countries which are relevant to educational buildings. In terms of the effectiveness of ventilation, high CO₂ concentrations are used as an indication of inadequate ventilation [10]. BB101 sets out maximum CO₂ concentrations during occupied hours for both naturally and mechanically ventilated UK school buildings of 1500 ppm and 1000 ppm, respectively [31]. Since 1000 ppm or above generally corresponds to a ventilation rate < 7 litres per second per person (L/s/person), the minimum ventilation rate in classrooms is defined as approximately 7 L/s/person in US standards. In Europe, the equivalent standards are deemed to be 8 L/s/person (moderate IAQ) and 12.5 L/s/person (good IAQ) [17]. During the COVID-19 pandemic, UK Health and Safety Executive (HSE) guidance on Welfare Regulations upgraded minimum fresh air supply rates from 5–8 L/s/person to 10 L/s/person [17,32] to address infection control concerns.

Ventilation systems can be defined as natural, mechanical or hybrid, accounting for, respectively, the supply of fresh air through passive means, the use of fans to drive extraction and supply, and ventilation methods combining the two. Mechanical ventilation systems can be further defined as exhaust-only, supply-only or balanced. Natural ventilation is dominant in educational buildings across the US, central and southern Europe, and Australia; conversely, Nordic countries have a similar percentage of natural vs. mechanical or hybrid ventilation systems, while Canada recently experienced intensive investment in Heating, Ventilation and Air Conditioning (HVAC) systems in response to the COVID-19 pandemic [21]. Older buildings tend to be more naturally ventilated than newer buildings since over 75% of educational buildings in Europe were built before 1980, when standards were generally lower on insulating and airtightness properties, which can result in higher energy use [33]. For instance, Danish buildings built prior to the inclusion of provisions for mechanical ventilation (1995 Building Code update) are likely to be naturally ventilated [34]. Improvement in the condition of older European buildings is hampered by a lack of budget and a regulatory framework for energy efficiency, which can conflict with the demand for better IAQ (e.g., by increasing airtightness) [25]. Flagship buildings, adhering to Leadership in Energy and Environmental Design (LEED) standards, benefit from compliance standards on the minimum supply of outdoor air and air cleaner provision where outdoor air pollution exceeds a concentration threshold [14]. The quality of outdoor air entering indoors is an important matter, given the elevated levels of air pollutants in urban areas, and the topic of air cleaning before supplying it into classrooms is a growing concern due to installation costs and implications for energy consumption [25]. Interventions such as air filtration and cleaning technologies, both associated with and independent of mechanical ventilation provision, are discussed in Section 4.5.

In addition to climate, seasonality and geographical location [17], cultural differences in pollutant sources and window-opening practices in naturally ventilated schools can influence the concentrations of pollutants such as PM, mould and allergens. Differences in allergen exposures in Swedish (combination of cat-, dog- and horse-allergens) and Korean schools (dominated by dog-and dust mite-allergens) have been recorded from dust samples [35]. In addition to sources, differences in exposure can be attributable to the presence of mechanical ventilation, linoleum/PVC flooring and professionally cleaned surfaces in Swedish schools [35].

Mould is a type of fungi that grows in moist environments. Mould can be particularly prevalent in floor dust [36], moisture-damaged buildings [37], wooden building types [10] and in damp/cooler climates [38,39]. Both viable mould and fungal DNA [40] have been commonly found in monitored European classrooms and are adversely related to respiratory health [22]. As well as a linear association between dampness and the presence of culturable bacteria, 63% of classrooms examined in three US public schools exhibited both dampness and mould [10]. Prevalence of moisture damage in European schools ranged from 20% to 49% [10]. The link between damaged schools and the very different cultures formed in damp conditions in timber frame schools in Finland than in warmer Netherlands and Spain, leading to more significant links to symptoms, has been explored [38,39]. Remediation efforts must couple elimination of sources with ventilation improvements [10,41] and effective maintenance [38] to significantly decrease airborne fungi and related symptoms by avoiding excessive relative humidities above the ideal range of 30–50% [22]. While concentrations of 14,800 CFU/m³ (Colony Forming Unit per cubic metre of dust) [42] and 18,000 CFU/m³ [43] appear in general agreement for concentrations found in a typical classroom, three-fold higher concentrations of mould in mechanical compared to exhaust-only ventilation systems were found [22,44].

The interaction of air pollutants between indoors and outdoors of educational buildings requires a thorough understanding, not only of individual and holistic efforts to provide fresh air, but also of minimising uncontrolled ingress of outdoor pollution, and maximising the extraction of indoor-generated pollutants outdoors. To determine the effectiveness of interventions, the impact of pollutants on the performance of the school needs to be weighed against the costs.

2.2. Health Effects of IAQ and Thermal Comfort and Impact on Learning Outcomes

The impacts of indoor air pollution on human health vary across different ages [45]. Many epidemiological studies of pollution health impacts are based on adults [25,46], often in office settings [47,48]. Such studies may not be entirely transferable to children due to their generally higher and sex-specific metabolic base rate [49,50] and having less agency in the type of clothing worn at school. While this review also considers colleges and universities that cater to adult and mature students, most of the subjects considered in this work are children and adolescents.

Substantial evidence exists for associations between indoor air pollution and impacts on respiratory and nervous systems in children [23], but much of this knowledge is based on mixed indoor micro-environments (e.g., residences and public spaces [51]) or a combination of indoor and outdoor environments [5]. Knowledge and awareness of indoor air pollution and its detrimental health effects still lag that of outdoor pollution [52], especially for children and adolescents [25,51], although this gap is diminishing with the advent of recent reviews focusing on the impacts of IAQ on younger children’s health in educational settings (e.g., daycare centres and kindergartens) [33,53,54,55]. A systematic review of links between indoor pollution and children’s respiratory health identified that distinct age-specific symptoms can present in infants, pre-school and school-age children [45]; therefore, any discussion of health effects in educational settings should recognise these differences alongside the different educational settings relevant to the children’s age. Children are also subject to different exposures compared to adults, such as vermin-related (i.e., allergens from insects or small mammals), due to breathing air at lower heights [8].

Substantial evidence suggests that IAQ in classrooms influences student learning capabilities and educational attainment [4,56], though the mechanisms are not yet fully understood. An early study [57] demonstrates that the performance and attendance of schoolchildren are intrinsically linked to IAQ, particularly through health effects caused by indoor air pollutants, finding persuasive evidence for the negative effect of NO₂ on absenteeism and subsequent academic achievement. Since then, various studies have attempted to quantify the direct and indirect associations between IAQ, absenteeism and performance, with varying levels of agreement [58,59].

Several reviews have evaluated the emerging evidence to demonstrate that IAQ directly influences student learning capabilities and educational attainment through impairment of executive and cognitive function and development [4,9,60]. Table S3 summarises a number of key reviews on the impact of IAQ within educational buildings, along with their limitations; meanwhile, Table S4 presents differences in scope between previous reviews, highlighting the need for a review that holistically considers the whole spectrum of educational buildings, age-ranges, health or education outcomes and socio-economic impacts. Despite the increasing number of review articles in this area, as has been compiled in Table S3, there is a research gap for increasing the collective understanding of the impacts of improving IAQ and thermal comfort in educational settings as they pertain to making decisions on interventions. Nevertheless, valuable insights can be gained from these previous publications, though as Table S4 shows, few of them simultaneously focus on IAQ and thermal comfort alongside learning or health outcomes, and fewer still extend the analysis to monetary or socio-economic impacts arising from improving these specific aspects of IEQ.

Maintenance of public educational buildings and their facilities is often less adequately funded than for other buildings (e.g., private offices) and may lead to unfavourable environmental conditions for health and learning despite the existence of guidelines and standards for IAQ and ventilation [10]. The next question, then, is whether health-based guidelines based on epidemiological studies of adults can sufficiently protect children [25]. An evaluation of current research focusing on holistic interventions to improve the educational building condition, ventilation and energy use with the aim of improving IAQ, thermal comfort, and ventilation—and, as a corollary, the potential health and performance outcomes of the occupants—is therefore timely and necessary to inform decision-making about the temporal and financial investments required to achieve optimal conditions for learning.

This scoping review aims to provide an updated summary of the latest research on the effects of IAQ, thermal comfort and ventilation in educational environments on students’ health, wellbeing, absenteeism and learning outcomes, highlighting any unintended consequences and co-benefits of maintaining indoor environments at a good standard. We consider other aspects of IEQ (such as noise) only in the context of ventilation systems (e.g., mechanical ventilation or air purifiers, or outdoor noise interfering with natural ventilation). The novelty of the present review lies in quantifying the potential links and cofounders between the above aspects of students’ educational experience, including demonstrating potential monetary and socio-economic benefits or shortcomings associated with improving the above aspects of IEQ to inform decision-making.

3. Methodology

The method proposed for synthesising evidence is a scoping review [61], incorporating a protocol with the following review question: “What are the unintended consequences/benefits of IEQ in educational school buildings, according to the research literature?”. Since the scope of the review question could include nurseries and colleges, at different ends of the age spectrum, it is important to emphasise that the different circumstances of these students will also lead to differences in exposure and hence other outcomes.

3.1. Eligibility Criteria

This scoping review was initiated through the Knowledge and Library Services (KLS) at the UK Health Security Agency (UKHSA), to identify peer-reviewed, preprint and grey literature since 1990 from high-income countries in Europe, North America, Japan, South Korea, Taiwan, Australia, and New Zealand. Eurovent provided additional articles at the initial stage. The inclusion and exclusion criteria were divided into six categories, as shown in

Table 1. Inclusion and exclusion criteria of rapid review.

	Included	Excluded
Type of building	Educational building, Classroom, Exam Hall, School, Nursery, University	Residential microenvironments (i.e., boarding schools, halls of residence), Sports/recreational facilities
Type of occupants	Students, Pupils, Toddlers, Children	Occupational exposure studies, Teaching staff, Non-teaching staff
Environmental conditions	Indoor environmental quality (IEQ), Indoor air quality (IAQ)/pollution, Thermal comfort, Ventilation, Heating, Cooling, Carbon dioxide (CO2), Particulate matter (PM), Nitrogen dioxide (NO2), Temperature, Relative humidity, Allergens, Volatile organic compounds (VOCs), Radon, Noise from ventilation system, External noise	Lighting and visual conditions, noise (not relating to ventilation)
Health impacts	Respiratory disease (Asthma, Allergies, Transmission of airborne disease, COVID-19, Influenza), Irritation, Neurological/ dizziness/fatigue	Cancer, low birthweight (pregnancy)
Attainment	Absences, Exams, Standardised scoring tests	University degree class
Impact of climate change policy on ventilation	Retrofit/retrofitting, Energy efficiency, Net zero

, and are included in Supplementary Materials S2 together with the search string used by KLS.

3.2. Search Strategy and Data Extraction

The initial search strategy was developed by UKHSA Knowledge and Library Services in early August 2024, which was then peer reviewed by a UKHSA KLS team member and refined, before clarifying the strategy with the authors and testing of results to ensure relevance. OVID Medline, OVID Embase, Scopus and The Cochrane Library databases were searched on August 15th and 16th, 2024, with 7650 unique records retrieved. Grey literature was provided by Eurovent and UKHSA stakeholders, which also allowed us to refine the search.

This literature review followed a recommended methodology [62] developed as an extension to PRISMA, but for scoping reviews. Figure 1 provides a summary of the records gathered through this process.

After screening on title and abstract with the help of the online screening platform Rayyan, 1035 records were identified and further screened on full text. A total of 114 relevant records were eventually identified and used within this literature review, including individual studies, review articles and grey literature. To test the screening process, Supplementary Materials Figures S1 and S2 show the most cited studies within the sample of papers and the studies which cite the most papers from within the sample, respectively. Figure 2 depicts the year trend of cited articles, showing the increasing research interest in this area.

4. Analysis of Literature

4.1. Health Effects and IAQ

A recent review outlined current evidence for health effects in children associated with exposure to specific indoor air pollutants in school environments [23]. The vast majority (80%) of relevant published evidence relates to respiratory effects, including wheeze, rhinitis, atopic asthma, pneumonia, and other respiratory infections associated with children’s exposure to indoor air pollution [45]. Non-respiratory effects include low birthweight and pre-term birth, skin and eye irritations such as eczema, atopic dermatitis or conjunctivitis. In a school environment, evidence of poor IAQ has been linked to poor health primarily through inadequate ventilation rates [17] and moisture damage [39,45]. Knowledge gaps have previously been identified in understanding the health impacts of individual pollutants within the school environment on children across different ages [25]. Importantly, at school age, indoor air pollution has been associated with reduced cognitive performance and difficulty sleeping. To evaluate the effectiveness of various intervention measures of improving IAQ across different educational buildings, such as increasing ventilation or using electrostatic air cleaners [47], we need to better understand pollutant sources, exposure mechanisms and how health effects are triggered.

In

Table 2. Individual studies of pollutant exposure of pupils and measured health outcomes (OR = odds ratio, CI = confidence level (95% by default), T = temperature, RH = relative humidity).

Study	Description of Schools	Measurement Type and Period	Key Findings	Limitations/Other Details
Meyer et al. 2004 [36]	Denmark 1832 teachers and pupils, 8 water-damaged, 7 non-damaged primaries	Airborne and floor dust and associated T, RH, CO2 sampled in winter 1999–2000 for 3 separate weeks	Mould levels significantly associated with five self-reported building related symptoms: eye irritation, throat irritation, headache, concentration problems, and dizziness	Symptoms from questionnaire
Simoni et al. 2010 [40]	European HESE project 46 classrooms, 21 schools Siena, Udine (ITA), Reims (FRA), Oslo (NOR), Uppsala (SWE), Arhus (DEN)	VR, T, RH, lighting, NO2, CO2, O3, HCOO, dust, allergens, mould, PM. 1 week (heating season, 2004–2005) in each location	All disorders more prevalent in children from poorly ventilated classrooms. CO2 exposure > 1000 ppm increased risk of dry cough (OR 2.99, 95% CI 1.65–5.44), rhinitis (OR 2.07, 95% CI 1.14–3.73). By two-level (child, classroom) hierarchical analyses, CO2 was significantly associated with dry cough (OR 1.06, 95% CI 1.00–1.13 per 100 ppm increment) and rhinitis (OR 1.06, 95% CI 1.00–1.11). Nasal patency significantly lower in children exposed to PM10 500 μg/m3	Wide-ranging study, involving multiple pollutants, multiple countries
Prokopciuk et al. 2024 [63]	Vilnius (Lithuania) 11 primaries	PM (compositional analysis), respiratory infection incidence over each year (2016–2020)	Vanadium concentration (12.7 to 52.1 ppm) correlates significantly to the number of episodes of acute upper respiratory infections per school per year. Lowest correlation, r = 0.67 (p = 0.024), highest was r = 0.82 (p = 0.002). No significant correlations between other trace elements found.	Clinical records by school not individual Low heavy metal concentrations.
Branco et al. 2020 [64]	Northern Portugal 69 nursery/primary	Exposure to CO2, CO, HCHO, NO2, O3, TVOC, PM over 24 h to 9 consecutive days	Between each Interquartile range of NO2 and O3 exposure there is an OR increase of FEV1/FVC in pre- and primary school children even though pollutants never exceeded reference threshold (200 μg/m3). NO2 > median (4.6 μg/m3), significantly increased odds of wheezing. Formaldehyde exposure > median (22.5 μg/m3) significantly increased odds of reduced FEV1/FVC, although not when children were exposed to formaldehyde levels higher than the threshold.	Difficult to separate school exposures from others
Cavaleiro et al. 2020 [65]	Porto (Portugal) 20 primaries	T, RH, CO2, O3, NO2, PMs, VOCs for 1–5 days (2010–2012, 2014–2015)	PM2.5 linked to high pupil constriction velocity. Bacteria concentration inversely proportionate to reversibility of asthma. No significant IAQ-> asthma prevalence, but low VR-> allergy sensitivity	Abstract only
Juskiene et al. 2022 [66]	Vilnius (Lithuania) 11 primaries	Particle Number and Mass Concentrations (PNC, PMC) (autumn 2017–spring 2018)	Peaks at 0.3–1 µm in PM distributions could increase asthma diagnosis. PM2.5 mass concentration can be skewed by particles in the 1–2.5 µm interval hiding the effect of higher concentrations in the range of 0.3–1 µm. Large differences in PNC (33–168 particles/cm3) and PMC (1.7–6.8 µg/m3)	Larger particles not a main cause of asthma
Kim et al. 2015 [67]	Seoul (South Korea) 30 children with dermatitis	NO, NO2, PM10, PM2.5, PM1, VOCs in old/new daycare centres. 24 h/d, May 2009–Apr 2010	Toluene levels rose and fell as a cohort of 30 children moved to a new building, was ventilated and “baked out” (heating materials and furnishing to remove VOCs). It was found that reported cases of dermatitis increased by 12.7% (CI = −0.1–27.1) as toluene levels increased by 1 ppb.	Measured rise and fall of cases associated with new facilities
Madureira et al. 2015 [68]	Porto (Portugal) 20 primaries	T, RH, CO2, O3, NO2, PMs, VOCs, Over 5-day school week, November to March 2011–2013.	PM2.5, PM10, bacteria levels exceeded WHO air quality/national guidelines. High VOC, acetaldehyde, PM2.5 and PM10 result in greater odds of wheezing. Lower odds of wheeze in the previous year were in schools with higher levels of bacteria and of wheeze in the previous month among those in schools with higher levels of fungi. Higher bacterial levels significantly associated with increased coughing.	Unknown home exposures, possible selection bias in favour of asthmatics
Marks et al. 2010 [69]	New South Wales (Australia) 400 primary children at 22 schools	Exposure to NO2 and formaldehyde from flued/unflued gas heaters over three pairs of 2 week alternating flued/unflued	For unflued gas heaters exposure compared to flued: NO2 concentrations 1.8 (CI = 1.6–2.1) times higher Formaldehyde concentrations 9.4 (CI = 5.7–13.1) ppb higher Increased evening cough OR = 1.16 (CI = 1.01–1.34) Wheeze reported in the morning OR = 1.38 (CI = 1.04–1.83) Despite symptoms, no evidence of adverse effect on lung function.	Low usage of boilers due to warm weather, only acute health effects
Palumbo et al. 2018 [70]	Alba (Romania) 5 primaries	Perceived humidity, odour and moisture collected Oct–Dec 2011	Hot classrooms increased flu symptoms/ allergy. Noisy classrooms increased asthma-like symptoms	Symptoms from questionnaire
Provost et al. 2017 [71]	Flanders (Belgium) 221 children in 2 primary schools	PM2.5 indoor and outdoor and clinical retina examination (Nov–Feb 2012–2013 and 2013–2014)	10 μg/m3 increase in same-day PM2.5 exposure associated with 0.35 μm (CI = 0.09–0.61 μm) narrower retinal arterioles and 0.35 μm (CI = −0.03 to 0.73 μm) wider venules. Children living 100 m closer to a major road had 0.30 μm (CI = 0.05–0.54 μm) narrower arterioles.	Home effects neglected
Takaoka et al. 2017 [72]	Kansai (Japan) 4 secondaries	T, RH, collected dust allergen testing, early summer 2008–2009	High relative air humidity, high student density and airborne cat allergens at school may increase the risk of airway infections.	Symptoms from questionnaire
Yamazaki et al. 2014 [73]	Tokyo (Japan) 49 urban, 8 rural primaries	NOx, Elemental carbon, annually from 2005–2010	Asthma incidence OR was 1.07 (CI = 1.01–1.14) for each 0.1 mg/m3 EC 1.01 (CI = 0.99–1.03) for each 1 ppb NOx.	Symptoms from questionnaire
Zwozdziak et al. 2016 [74]	Wroclaw (Poland) 1 secondary	PM1, PM2.5 daily 141 pupil lung function tests on same day in 2009–2010	High indoor PM reduces lung function parameters: FEV1, FVC, (p < 0.05). Differences observed both for PM size and measured lung parameters. Changes per IQR were 1–2% only for FEV1 and FVC, 3.5–5.2% for peak expiratory flow testing (maximal flow)	Only looks at a single school

, we explore the association between exposure to indoor air pollution and health effects, as reported from individual studies, in addition to the established health effects reported across the academic and grey literature. Exposure to VOCs (e.g., limonene, formaldehyde, trichloroethylene and tetrachloroethylene), reported to be higher in schools than other public buildings [21], has been associated with asthma-related symptoms such as irritative cough and wheezing, nasal allergies and allergic rhinitis [23]. Hence, children who live near industrial sites with elevated VOC concentrations have a significantly higher risk of missing school due to sore throat, cough and cold symptoms [23]. Evidence surrounding the mechanisms through which air pollution triggers respiratory effects is limited but growing; for example, asthma development and exacerbation have been linked to oxidative stress and immune response to PAHs, which is a known family of neurotoxic chemicals [23].

Sick Building Syndrome symptoms have been causally related to exposure to VOCs, moulds and allergens [75], and to specific bacterial species [39]. In terms of chronic conditions, exposure to PAHs has been shown to increase blood pressure and affect neuropsychological development in pre-adolescent children, affecting learning and behaviour, as well as being linked to an increased risk of certain brain tumours [23]. Several VOCs commonly found indoors, such as benzene, trichloroethylene and formaldehyde, are also known carcinogens [23].

It has been demonstrated that 95% of respiratory infections are associated with exposure to five different viruses—rhinovirus, influenza, respiratory syncytial, adenovirus and coronavirus [76], each having different properties with respect to changes in temperature, air humidity and droplet size. Rhinovirus is the most common viral agent responsible for common colds, and repeated occurrences in early years can lead to chronic respiratory conditions, including asthma [76]. Distinct from seasonal infections, epidemics and even pandemics can occur due to mutations in existing influenza viruses (in the case of the swine flu pandemic of 2009) and coronaviruses (such as the COVID-19 pandemic). Novel symptoms may present, and often infection characteristics and transmission pathways can take months, or even years, to establish [77]. Potential for airborne transmission is dependent on typical concentrations found in aerosols, their size distribution, building environmental conditions (i.e., temperature, ventilation and humidity), and the number of people shedding the virus [76].

Given favourable conditions, droplets of diameter < 5 μm can be suspended in the air, whereas larger particles (>20 μm) are governed by gravity, so there is a complex relationship between these factors when determining exposure. Within the wider school context, building environmental conditions, organisational (social distancing/exclusion) and behavioural (personal and general hygiene) characteristics, as well as activities (lab, sports and singing) [76] all influence the effectiveness of transmission. A modelling study of the spread of COVID-19 in a Finnish day-care centre found that infection risk was highest in congested changing rooms, with limited air flow and high occupancy [78]. Mechanical ventilation can guarantee sufficient airflow to reduce transmission risk [77]. Studies also found other correlations of infections, for example, with the presence of Vanadium in indoor dust [63] and leaking roof and damp conditions [79], although controlling for the effects of low temperature and dryness of winter air has been identified as a key barrier to regression analysis [46]. An increased risk of respiratory infection due to airborne virus transmission in educational buildings can therefore be an immediate consequence of inadequately ventilated rooms.

More information on how students’ exposure is associated with PM_2.5, BC and UFP has been sought through epidemiological studies to allow correlations with number and surface area concentrations to be derived [25]. Exposure to NO₂, PM_2.5 and O₃ has been associated with irritative cough; PM₁₀ with lifetime allergic rhinitis and lower nasal patency; and PM_2.5 at day care centres with airway inflammation [23]. Secondary effects of NO₂, PM, VOCs, and formaldehyde, combined with dust mites or bacteria, can further increase the risk of asthma onset in children. While allergens from domestic pets can be higher in schools than in non-pet households [80], levels of cockroach and dust mite allergens can be elevated, respectively, in low socio-economic areas and relative humidities above 55%, leading to a complex interplay of factors. Long-term exposure to elemental carbon (EC), NO₂ and UFP was negatively associated with cognitive development through neuro-behavioural tests [23]. The limited evidence of cardiovascular and carcinogenic effects of air pollution specific to children suggests associations with the development of ill-health in the cardiovascular system and hypertension in later life [23].

Studies exploring associations with VOCs, particulate matter, and mould, among other pollutants, have relied on child or parental questionnaires as well as clinical skin and lung testing. Lung testing provides an objective means of determining respiratory symptoms, through metrics, such as the ratio of Forced Expiratory Volume to Forced Vital Capacity (FEV1/FVC) of the lungs, with values < 0.70 indicative of airflow obstruction. Subjective questionnaires are often required for health and for providing useful contextual socioeconomic [4], perception and building-related issues [81] for association or regression analysis. While these can be used to scale-up studies, they may be prone to various types of questionnaires or response bias [81,82] for association or regression analysis. Significant perception and response differences have been noted due to allergic/non-allergic pupils [81], and 67–84% of the association between observed IAQ and reported symptoms could be accounted for by parental worry alone [83]. To counteract these differences, focusing on treating the deteriorated environment rather than on a particular group is recommended [81]. In addition, since school-related psycho-social problems (teacher-student relations, stress) may account for 10% of the variation in perceived IEQ, these need to be reported alongside indoor air problems, providing context [36,84].

Details regarding associations relating to detrimental school indoor environmental conditions have been summarised in Table 2. Odds ratios (OR) are expressed relating various symptoms to pollutant exposure, with confidence intervals (CI) given at 95% confidence level unless stated otherwise. p-values, showing significance of associations, are also described, where applicable. Individual school/classroom studies found to have an enhanced understanding of (a) mechanisms (or lack thereof) causing specific symptoms, (b) how the school environment can be altered to avert health impacts, or (c) broader insights with novel implications are also included.

Adverse health outcomes, such as respiratory infection or asthma associated with poor IAQ, can not only be consequential to the level of attendance in educational institutions but also to impaired organ function (e.g., lungs, brain) and cognitive development. Furthermore, ventilation is an integral part of IAQ; therefore, ventilation rates can be indicative of IAQ. It can be speculated that both attendance and impaired organ function or cognitive development may further affect students’ educational attainment in the short term (e.g., missing school or university lectures due to infection) and the long term (e.g., lower exam grades, lower-income jobs and other socio-economic impacts), which are explored in the following sections.

4.2. Absenteeism

It has been identified that, behind acoustics and impact on cognitive performance, the impact of air quality on absenteeism is the second most studied indoor environmental parameter [14]. There is also evidence of associations with temperature, with one study finding a 1.28-fold higher probability of respiratory illness-related absenteeism in high indoor temperature (between 27 °C and 30 °C), though associations with academic performance are less clear. The linkage of absenteeism directly with respiratory infection has been described in terms of evidence of negative associations between asthma and children’s school performance [85]. It has been further demonstrated in a recent study [86], which showed a decrease in absences from 22 to 13 students over a seven-week period (winter) when using air purifiers, a posterior probability of 91% of reduced infection risk and fewer symptomatic students in class based on coughing frequency, although a similar detection rate in saliva for viruses was found, regardless of purifier usage [85]. Most comparisons of increased frequency of absenteeism due to reported infections attempt to establish relationships with the presence of other pollutants, such as SO₂ and NO₂ [87]. Bypassing air pollutant concentrations, an association has been established in the literature between low classroom ventilation rates, increased respiratory symptoms and student performance, attendance, and health [17,57]. A review on classroom ventilation rates found that 4 out of 5 studies showed statistically significant reductions in absence rate with increased ventilation or reduced CO_2, with the strongest of these studies reporting a 1.6% decrease in absence for each 1 L/s/person increase in ventilation using multivariate analysis modelling [17].

Classroom ventilation rates are a factor affecting IAQ, and improved respiratory health and academic achievement outcomes are a result of decreased concentrations of indoor-generated pollutants through increased ventilation [17]. However, it is unclear whether the ventilation rate itself or the resultant improvement in IAQ is responsible for any reported changes in illness-related absenteeism. Evidence of direct associations between IAQ and absenteeism has increased over the last couple of decades [57]; for example, the association between indoor PM_2.5 and absence rates in schools has only recently been found to be significant [87]. A 1 μg/m³ increase in outdoor PM_2.5 has been related to a 1.58% increase in “chronic” (due to health or reasons beyond the control of children/parents) absence rates in a US study [88]. However, in a Chinese study for coarser outdoor ambient PM₁₀, no significant association was observed [89].

Often linked to socio-economic factors, children staying at home can also impact parent/guardian absenteeism from work, as well as the impact of lower quality of learning on the child’s future career and salary [21] through lower attainment, e.g., lower grade point averages [17,90]. There is a perception that lower absenteeism is a key benefit of having an IEQ program [91].

Table 3. Relationships derived between pollutants, hygrothermal conditions, ventilation rates and absenteeism.

Pollutant	Reference	Details	Relationship with Absenteeism
CO2	Shendell et al. (2004) [95]	409 traditional, 25 portable classrooms, 22 schools in Midwest, USA.	1000 ppm increase in difference between indoor and outdoor associated with 0.5–0.9% decrease in attendance. (p < 0.05).
	Wargocki et al. (2020) [9]	Function based on weighting/averaging [92,93,95]	Reducing CO2 from 4100 to 1000 ppm would increase daily attendance by 2.4%.
	Deng et al. (2021) [94]	85 elementary classrooms, Midwest USA	3% increase in illness-related absenteeism with a 100 ppm increase of CO2 (heating season only).
	Gaihre et al. (2014) [93]	60 naturally ventilated Scottish classrooms	0.2% increase in attendance for each 100 ppm reduction in CO2
PM10	Marcon et al. (2014) [96]	Recorded absenteeism at school near cement factory in Fumane, Italy	10 μg/m3 increase over 5 days associated with 2.4% (CI = 1.2–3.5%) in absenteeism 2 days later, driven by longer exposures rather than peak.
PM2.5	Deng et al. (2021) [94]	85 elementary classrooms, Midwest USA	3% increase in illness-related absenteeism with 1,000,000 counts/L PM2.5 increase (heating season)
	Deng et al. (2023) [87]	3105 pupils, 144 classrooms, 31 schools, Midwest USA	Mean indoor PM2.5 is 3.6 μg/m3, every additional 1 μg/m3 increase associated with 7.36 increase in days with absences/year
SO2	Ponka (1990) [46]	Day care, nurseries and office in Helsinki, Finland	Correlation with day care absences only, despite significant correlation between SO2 and reported URIs (p < 0.0001) and tonsilitis (p = 0.0098). 2-day lag correlation highest (exposure to onset)
NO2	Ponka (1990) [46]	Day care, nurseries and office in Helsinki, Finland	No correlation with absences, significant correlation between NO2 and URIs from health centres (p = 0.0225).
	Pilotto et al. (1997) [97]	388 pupils, 41 classroom 4 electric (low exposure), 4 gas-heated (high) primaries Focus on short term hourly peak levels of NO2	Short, hourly NO2 peaks of ~80 ppb, (20 ppb ambient), caused respiratory absences, significant dose-response relationships as NO2 increased. During heating period, cold symptoms last >7 days (average) when highly exposed rather than 4 days.
Mould	Simons et al. (2009) [8]	Condition and absentee data for 2751 New York schools	Where visible mould was reported, OR = 2.22 (CI = 1.34–3.68)
Humidity	Simons et al. (2009) [8]	Building Condition and absentee data. 2751 New York schools	OR = 3.07 (CI = 1.37–6.89)
Temperature	Ponka (1990) [46]	Low temperatures in Finnish day care, nurseries	Correlation of low temperature with day care and school absences, significant for URIs, tonsilitis.
	Toyinbo (2023) [10]	Literature review of thermal discomfort	Up to 1.3-fold increase in absenteeism
Ventilation Rate (VR)	Deng et al. (2023) [87]	3105 pupils, 144 classrooms, 31 schools, Midwest USA	5.8% reduction in absence rate for each additional 1 L/s/person
	Mendell et al. (2013) [92]	Model based on VR and IA from 162 classrooms in 28 elementary schools, 3 California school districts	Increasing VR from 4 L/s/person (average) to 7.1 L/s/person (California minimum standard) reduces illness related absenteeism by 3.4%.
	Toftum et al. (2015) [34]	820 classrooms in 389 Danish primary/secondary	No significant relationship between VR and absence rate
	Wargocki et al. (2020) [9]	VR calculated from CO2 levels (see above) using mass balance model.	Doubling VR from 2 to 4 L/s/person increases daily attendance by 1%, 4 to 8 L/s/person by 0.5%.

summarises the associations of absenteeism with various pollutants and indoor environmental conditions (temperature, humidity and ventilation rate). Differences with studies relating to the outdoor environment are noted; there are no significant studies in schools in high-income countries relating VOCs and O₃ in the indoor environment with absenteeism, although they exist in other types of buildings (e.g., homes) [14]. Ranges provided in Table 3 are usually conditional on classroom operating parameters such as activity levels of students, steady state conditions and a specific range of the pollutants [9]. Results for the impact of ventilation rates are in general agreement; however, a one unit increase in ventilation rate (1 L/s/person) has been reported to reduce absence rate from 1.4–1.6% [92] to 5.8% [87], which is a large range. When reported in similar terms, impacts on absenteeism from indoor CO₂, ranging from 0.2% [93] to 3% [94] per 100 ppm, are broad, indicative not only of differences between measurement periods [94] but also of the contexts of the indoor environment in the schools being monitored. This variation indicates that, without considering other indoor environmental quality parameters (such as IAQ and thermal comfort), ventilation alone cannot explain the causes of absenteeism.

Building condition-related and social confounding factors, such as the age of the building, vermin issues or home environmental conditions, have often been difficult to control for when trying to establish an association between one specific pollutant and absenteeism [8]. For example, younger children are impacted by building condition problems due to their activity levels, smaller airways and relative proximity to the floor [8]. Portable classrooms have also been found to impact absenteeism, with annual attendance 2% higher in “traditional classrooms” [95]. Extensive state-wide datasets of both absenteeism and building conditions are required to control for confounders [8]. As well as visible mould and humidity (see Table 3), strong associations between absenteeism, vermin, “poor” ventilation, and a range of building condition problems were found, particularly among younger children within lower socio-economic districts [8].

By association, context-specific building, location, and age group details of studies are as important for absenteeism caused by exposure to poor IAQ as reported for health symptoms in Section 3.2. However, methods used to assess health and absenteeism are also critical, since differences in reasons recorded for absences have been reported between different school districts [87], as well as differences between self-reported symptoms and sick absence reports [8].

In terms of a causal pathway linking poor air quality to absenteeism and subsequently to performance, as evaluated in test scores, a distinction between illness-reported absenteeism and general absenteeism should be made [98]. However, this study also demonstrated that non-illness-related absence has a stronger association with performance than illness-related absence, demonstrating a willingness for students to catch up after recovery from short-term illness. This indicates the possibility of neurological symptoms owing to lower ventilation rates affecting present students, as explored in the next section, rather than performance being affected purely through absence. There is also evidence of a negative association of absenteeism as a “mediator” of IEQ, causing underperformance, arguing that socio-economic factors such as student ethnicity and percentage of free school meals are more significant [59]. However, in this study, a basic 0–100 scoring index consolidating only CO₂, relative humidity and temperature has been used as an analogue for IAQ. Other conflicting studies, which indicate an improvement in performance associated with increasing attendance, have a tenuous link to IAQ via “environmental programs” [58].

4.3. Educational Attainment and Performance

Associations of ill-health with negative learning outcomes in both mathematics and reading comprehension have been found [10], alongside decreased attendance due to acute or chronic illness [17]. In addition, there is evidence of direct associations between learning outcomes, including academic performance in coursework and exam assignments, as well as physiological and cognitive function tests, and classroom environmental conditions [4,10,17]. Academic performance is often further confounded by other factors such as socio-economic status (SES), which is strongly related to cognitive and academic outcomes [4].

Academic performance is evaluated in several ways within the existing literature. Some studies focus on long-term attainment in various subjects, such as exam results or standardised test scores (e.g., Grade Point Average (GPA)) in mathematics, reading and comprehension, often on school- or district-level. An exception is a few studies (e.g., [56]) that link large databases or indoor environmental conditions with student-level attainment. Focusing on attainment can be a direct route to evaluating air pollution effects on achievement over a longer period [4].

Other studies measure performance through controlled tests of students’ executive function, which dictates the state of concentration, working memory and cognitive flexibility, among other factors vital to information processing and learning [4]. Numerical or language-based tests are often implemented to examine working memory, attention, episodic memory, visual processing speed, reaction time, non-verbal reasoning, and coordination [99].

We have analysed literature pertaining to all measures of performance evaluation, recognising that there are benefits and limitations to each in terms of study design, sample size and period of time necessary for the establishment of any potential IEQ effects on educational performance.

4.3.1. IAQ Impacts on Academic Performance

There is established evidence on the impacts on children’s health and learning performance due to poor IAQ in primary and secondary schools [21]. Inadequate ventilation rates can be indicative of poor IAQ; therefore, linkages can be made directly with ventilation rates, as will be described in Section 4.3.2. However, there are also examples in the literature of links between concentrations of specific pollutants and the performance of schoolchildren. The evidence for older adolescents and adults at colleges or universities seems to be less established, as adults’ health and productivity tend to be studied in office-type settings rather than, e.g., lecture theatres. Sources of pollutants commonly found in educational buildings vary, and can infiltrate from outside (e.g., TRAP), or be generated indoors. A large nationwide survey of kindergartens and elementary schools in France identified the presence of 152 chemicals found in cleaning product safety data sheets [100]. Their presence in some school environments is concerning, given that typical substances commonly contain irritants and endocrine disruptors.

Phosphororganic compounds (POC) have been used as plasticisers, flame retardants and floor sealants, and the POC tris(2-chloroethyl)-phosphate (TCEP) is commonly found in indoor school air samples, despite being listed by the European Union as a compound of high concern [101]. Exposure to PAHs, such as benzo[a]pyrene, at school during pre-adolescent age has been associated with changes in the caudate nucleus in a previous study [23], which could affect several cognitive and behavioural processes. There is currently limited evidence of associations of VOCs and semi-volatile organic compounds (SVOCs) with school performance. One of the few studies investigating the effect of SVOC (e.g., phthalates and POC) on health and performance of 6- to 8-year-old pupils in Austrian schools found that the presence of SVOCs, TCEP in dust or particulates, and phenanthrene negatively affected cognitive performance [101].

Recent reviews have focused particularly on TRAP levels in and around schools with detrimental effects on executive function, behavioural outcomes, and mental health in primary school-aged [4,24] and older [5] children, some with a focus on LEED-standard schools [14]. Associations of indoor TRAP with behavioural disorders, mental wellbeing and inattention problems have been found [5], which could contribute to lower academic achievement. Neurotypical students are usually considered, while neurodivergent pupils may adapt to indoor environmental conditions through changes in engagement or attention, and vulnerability of autistic students to indoor pollution may be heightened due to increased sensory sensitivity, potentially manifesting as lower attainment [102]. We found no reviews focusing on higher education catering to older adolescents or adults, other than an example providing interdisciplinary insights into aspects of student wellbeing as a broader consequence of IEQ [103], which highlights a need for more research in this area.

Individual studies investigating acute or chronic effects of exposure to pollution in classrooms on the executive or cognitive function of students across different ages yield mixed results, some of which are presented in

Table 4. Studies detailing IAQ impacts on student performance.

Authors	Type of Educational Setting/Study/Location	Type of Performance Measure	Key Question	Key Findings
Hutter et al., 2013 [101]	Cross-sectional study, 9 elementary schools in Austria (436 children aged 6–8 years)	Health status and environmental conditions (parents’ survey); cognitive function measured by Standard Progressive Matrices (SPM)—non-verbal assessment measuring reasoning.	Investigating the relationship between school indoor air pollutants (SVOCs) and cognitive performance	Statistically significant negative correlations of cognitive performance with tris(2-chlorethyl)-phosphate (TCEP) concentrations in PM10 (r = −0.147), PM2.5 (r = −0.149) and dust samples (r = −0.154); also, with increasing CO2 concentrations (r = −0.102). Evidence of negative correlation with phenanthrene (PAH), (r = −0.097).
Saenen et al., 2016 [104]	Panel study of primary schools (310 children), part of COGNAC study, Belgium	Repeated neuro-behavioural tests (selective and sustained attention, short-term memory and visual processing speed). Recent PM10 and PM2.5 measured in classroom and at home on test day; chronic exposure measured at home.	Effect sizes between recent/chronic exposure to PM and neuro-behavioural performance	Recent (classroom) PM2.5 and PM10 exposure significantly associated with selective attention and visual processing speed. Selective attention: 42.7 ms [CI −0.40 to 85.8 ms] and 50.2 ms [CI 8.55 to 91.8 ms] longer mean reaction time for an IQR increment in PM2.5 and PM10 exposure, respectively. Visual processing speed: 2.05 s (0.43 to 3.66 s) and 1.9 s latency for PM2.5 and PM10, respectively. Chronic PM negatively associated with sustained and selective attention.
Sunyer et al., 2015 [105]	39 Primary schools (Barcelona, Spain). Prospective study of approximately 2500 students (7–10 years old) from the longitudinal BREATHE cohort; 12 months.	Computerised tests assessing cognitive development (working memory, superior working memory and inattentiveness (hit reaction time standard error)	Assessing whether chronic TRAP (EC, NO2 and UFP) affected the expected development of working memory over a 12-month period.	Lower improvement in cognitive development (7.4% [95% CI 5.6–8.8%]) in children attending highly-polluted than less polluted schools (11.5% [95% CI 8.9–12.5%]). A change from the first to the fourth quartile in indoor EC reduced the gain in working memory by 13.0% (95% CI 4.2–23.1%) Exposure to UFP significantly affecting working memory
Forns et al., 2017 [106]	39 Primary schools (Barcelona, Spain). 1439 students from the BREATHE cohort; 3.5 years.	Working memory as a measure of cognitive development (computerised n-back tests)	A continuation of over a period of 3.5 years, to determine whether modest associations between TRAP and working memory persisted over a longer period. Linear mixed effects model.	One IQR increase in outdoor NO2 and indoor UFP associated with a −20% (95% CI: −30.1, −10.7) and −19.9 (95% CI: −31.5, −8.4) change in annual working memory development.
Gignac et al., 2021 [107]	High schools (Barcelona, Spain); Randomised controlled trial of 2123 pupils (13–16 years old) in 33 schools.	Computerised tasks of attention tests, measuring response speed.	Does purifying the air of classrooms produce short-term changes in attention?	During the 1.5 h experiment, average concentration levels of PM2.5 and BC were lower than in control classroom by 89% and 87%, respectively. No substantial difference found in median hit reaction time standard error (HRT-SE) and other secondary attention outcomes.
Wargocki et al., 2008 [108]	Elementary schools (Denmark); Approximately 190 pupils in five pairs of classrooms (from two different schools); Two independent crossover experiments in one week during winter and spring.	Six exercises exemplifying different aspects of schoolwork, as part of normal lessons.	Determine whether reducing the concentration of airborne particles in school classrooms improves children’s performance.	Considerable reduction of particles. Some positive effect of speed of task performance. No effect on the percentage of errors in tasks.
Lyu et al., 2024 [109]	University lecture theatre (University College London, UK); 669 university students in 36 lecture theatres. Winter.	Self-reported concentration levels	Examining the influence of (subjective) IEQ on students’ concentration levels through self-reported questionnaires. Multiple regression model.	Although concentration levels of students were positively correlated (r = 0.122, so significance level provided) with (own perception of) IAQ, the most influential factor was the lecture theatre environment as a whole.

. It appears that the length scale of study (e.g., hours versus years) is a key factor in determining the extent and permanency of learning outcomes due to pollutant exposure. One study analysed differences in neuro-behavioural performance (selective, sustained and short-term memory, and visual processing speed) of primary schoolchildren with recent versus chronic exposure to PM [104], finding that neither acute nor chronic exposure to PM_2.5, PM₁₀ and BC significantly affected short-term memory, though significant associations were found with visual processing speed. Negative and time-increasing associations of indoor PM with working memory, attention, and other cognitive outcomes have been demonstrated [4]; meanwhile, NO₂ exposure is associated with working memory but not necessarily with other executive functions [16]. Chronic exposure to higher NO₂ and BC concentrations related to local vehicle traffic was associated with detrimental effects on the development of working memory, while higher PM_2.5 exposure was associated with a 22% reduction in annual improvement in children’s working memory and an 11% annual change in inattention [105]. Similarly, there is a degree of confidence in the possible negative association of PM_2.5 with standardised test scores in LEED schools [14]. There is some evidence to suggest that a longer study period is necessary to observe significant effects. For example, the longitudinal studies on the association of indoor and outdoor TRAP and cognitive development in the BREATHE cohort [105,106] found that children attending schools in highly polluted areas had significantly lower development of working memory and attention functions over a 12 month period associated with NO₂ and EC, though the effect was modest; the association was further observed during the extended study over a 3.5 year period. The strongest detrimental effects of TRAP on working memory development were found for outdoor NO₂ and indoor UFP.

The longer the study period, the more difficult it is to distinguish effects of indoor and outdoor air pollution exposure pathways because the location of the building (in a low or high-pollution area) is a confounding factor itself, as students spend time both in and out of the building during the course of the day, as well as commuting. One study that focused on pollutant exposure during foot-commuting did not find significant effects of PM_2.5 or BC exposure on inattention over the course of a year [110]. Another confounder relating to building location is SES, where schools located in areas of higher deprivation tend to have disproportionately high outdoor pollution, in addition to other SES-related determinants of health and level of education [111].

Studies that investigate reducing classroom pollution in the short term through air cleaning technologies yield further mixed conclusions. In one study, no significant differences in an attention test measuring response speed (hit reaction time standard error) were found between a classroom with an air purifier and a control setting, despite a significant reduction in PM_2.5 and BC [107]. The authors speculate that the timing between exposure to TRAP, manifestation of harmful effects and subsequent removal of the exposure and timing for recovery needs to be considered—the short experiment time (1.5 h) may not be long enough to observe such an effect. This finding is consistent with another study, where the reduction of PM due to electrostatic air cleaners did not appear to affect the percentage of errors in schoolwork [108]. Any significant effects were related to the speed of task completion but were inconsistent across different types of exercise. Moreover, the intervention spanned a longer period (one week). The increasing strength of PM (particularly PM_2.5) and NO₂ on working memory over a longer period supports the notion that TRAP is detrimental to its development, which could directly affect school achievement, but it is still unclear whether it is only important in a specific school-age window or whether there is a cumulative effect of continued pollution exposure. Long-term exposure and its potential effects on executive function are difficult to assess, and to date, they have not been explicitly tested, though it is possible that they may have a prolonged detrimental effect on academic achievement [4].

The age of the subjects also needs to be considered, as many neurodevelopmental studies centre on early childhood. Acute effects of pollution on measures of school performance may differ between young children and adolescents due to different stages of organ development [107]. A recent study involving adults found that after 4 h of exposure to PM, aspects of executive functioning were compromised (e.g., selective attention and emotion discrimination) but not working memory or psychomotor vigilance, suggesting that inflammation from PM could have socio-cognitive impairments in healthy adults—this effect may be more significant in more vulnerable groups, such as children [112].

4.3.2. Ventilation Rates and Thermal Comfort Impacts on Performance

Educational buildings have been found to suffer from inadequate ventilation rates, leading to high CO₂ concentrations [21], especially during the heating season within naturally ventilated buildings [99]. However, a widespread failure to reach the minimum standards is observed and is not limited to naturally ventilated buildings [17]. Although they are not perfect, there exist methods for converting classroom CO₂ concentrations to ventilation rates [113]. Various energy conservation measures often practised in school buildings, such as a reduction of the ventilation rate, can result in concentrations of CO₂ exceeding 1000 ppm during occupied hours [47]. Minimising heating or cooling, to reduce energy use, can lead to thermal conditions that are unfavourable to learning, with summertime classroom temperatures in the 27–30 °C range reported to decrease student performance by as much as 30% [47]. In the above study, the association derived from the literature indicates that doubling the outdoor air supply rate could show an improvement in the speed of task completion by 8–14% [47]. A major study concluded that a reduction of CO₂ from 2100 to 900 ppm would improve performance speed by 12% and accuracy by 2%; meanwhile, a reduction of CO₂ from 4200 ppm to 1000 ppm would increase attendance by 2.5% [9]. Regarding ventilation rates, it is suggested that an increase from 2 to 7.5 L/s per person could improve pupils’ performance in national tests by 5%, and attendance by 1.5%, highlighting that these effects are stronger than those expected for adults performing office-based work in similar conditions [9]. Although no data were examined for conditions under 900 ppm, it is likely that reducing CO₂ concentrations even further would be favourable to pupils’ performance, given the log-linear associations for office work performed by adults [21]. Although increased ventilation improves short-term IAQ, the effect on cognitive performance was inconsistent among selected studies in a recent review [99], but the authors attribute this result to weak study designs.

A series of blind crossover design experiments investigated the effect of raised classroom temperature and ventilation rate on schoolwork [114,115]. For one week at a time, considering the effect of outdoor air supply rate and presence of air filters, the air temperature and outdoor air supply rate were manipulated, while several numerical and language-based exercises were performed as part of normal lessons. Performance significantly improved when the temperature was reduced from 25 °C to 20 °C, and when the outdoor air supply rate increased from 5.2 to 9.6 L/s per person. A similar experiment was redesigned [116], finding that increasing the ventilation rate from an average of 1.7 to 6.6 L/s per person increased the number of correct answers in all four performance tests by 3.2 to 7.4%, but there was no significant effect on the error rate, similar to the original experiments [114,115]. Conversely, an association between schools that did not meet the recommended ventilation rate and lower test results in mathematics was found, proposing that any ventilation system needs to be scaled to reflect the number of occupants in the room to ensure adequate airflow [16].

Although temperature, ventilation rate and type are often studied together (as shown by the multitude of studies in

Table 5. Examples of studies investigating potential associations between ventilation rate or CO₂ concentrations and temperature, with educational attainment across different age ranges.

Authors	Type of Educational Setting/Study/Location	Type of Performance Measure	Key Question	Key Findings
Ito and Mukarami et al. (2010) [15]	A model small college in Japan, 3 storeys. Numerical model predictions.	Relative standardised test scores.	Demonstrating the cost effectiveness of HVAC, and any associations with improved academic performance.	Increased ventilation rate from 10 to 30 and from 10 to 60 m3/h per person would improve academic by approximately 4% and 6.4%, respectively. A reduction of temperature by 1 °C and by 2 °C (from 28 to 27 °C, and from 28 to 26 °C) would improve performance by 26% and 43%, respectively.
Toyinbo et al. (2016) [16]	108 classrooms in 60 schools in Finland (4248 students) at sixth grade.	Results from a national student achievement assessment program (Linear mixed model for the percentage of correct answers in mathematics test); Data on school environment and students’ health from questionnaires; Temperature measured.	To study IEQ (ventilation) in elementary school buildings and its association with students’ learning outcomes.	Only schools with a mechanical supply and exhaust type of ventilation met the recommended ventilation rate per student (6 L/s per person), though the recommended level was exceeded only in 52% of those schools. An association was found between lower mathematics test results and schools that did not meet the recommended ventilation rate. The association is not confounded by the type of ventilation system. Upgrades to heating, ventilation, and air conditioning (HVAC) systems correlated significantly with airflow measurement, ventilation rate per student and per area, and mean temperature.
Toftum et al. (2015) [34]	389 Schools in Denmark (820 classrooms), measuring CO2 and temperature. Retrospective analysis.	Academic achievement indicator calculated from scores of standardised Danish test scheme.	To study the associations between ventilation mode and other classroom-related parameters (e.g., school year, room volume, occupancy) and learning.	Pupils in schools with some means of mechanical ventilation had higher national test scores than those in schools with natural ventilation. Naturally ventilated schools had the lowest achievement indicator, significant for subject areas of Danish (1.29%) and maths (1.96%). No consistent relation found between achievement indicator and person specific room volume, construction/renovation year, or occupancy. Naturally ventilated classrooms had elevated CO2 concentrations
Haverinen-Shaughnessy et al. (2015) [56]	70 Elementary schools in southwest USA (3109 students). Multilevel analyses using linear mixed models).	Standardised test scores and socioeconomic data.	The study helps to understand the potential benefits of effectively managing indoor environmental factors in schools.	Statistically significant association between ventilation rates and mathematics scores, made stronger by filtering classrooms with high ventilation rates (>7.1 L/s per person). Mean mathematics scores (average 2286 points) increased by up to 11 points (0.5%) per each L/s per person increase in ventilation rate within the range of 0.9–7.1 L/s per person. An additional increase of 12–13 points per each 1 °C decrease in temperature within the range 20–25 °C (estimated effect size 67 points).
Wargocki et al. (2019) [60]	10 studies in elementary schools across Europe and USA used to develop the relationship	Psychological tests, school tasks, standard exam results	To develop a relationship addressing thermal conditions in classrooms and their impact on the performance of schoolwork, based on existing literature.	Performance of psychological tests and school tasks expected to increase by 20% with classroom temperatures lowered from 30 °C to 20 °C. Optimal performance temperature is lower than 22 °C (valid only for temperate climates).
Wargocki et al. (2007) [114]	Elementary schools (10–12) in Denmark	Field experiments in existing classrooms. Performance measured as speed and error.	Investigating the effects of increased outdoor air supply rate on schoolwork performance (continuation of two other experiments in the same series)	Performance improved both in numerical tasks (concentration and logical thinking) and language-based tasks. Speed of task performance improved, and the effects in four cases reached statistical significance; in two cases they approached significance. Increasing the outdoor air supply rate improved the performance of schoolwork. The effect was mainly on speed, especially on numerical tasks, with no effects on the language-based tasks.
Wargocki et al. (2007) [115]	Elementary schools (10–12) in Denmark. Two experiments: (1) crossover design exchanging air supply filters; winter. (2) crossover design with ventilation rate changed while new supply filter is in place; summer.	Field experiments in existing classrooms. Performance measured as speed and error.	Investigating whether classroom air quality affects schoolwork by changing outdoor air supply rates and by renewing used supply air particle filters in the HVAC system.	Speed of task performance improved with no effects on errors. Of the five significant effects on speed, four occurred in Experiment 1 (winter) and one in Experiment 2 (summer). Reading and comprehension task was the only one with significant effect. An improvement in performance was found when classroom ventilation rate increased from about 3.0 to 8.5 L/s per person. It is suggested that the observed effects are due to improved indoor air quality. No significant effects of replacing a used filter with a new one on the performance of schoolwork could be shown.
Petersen et al. (2016) [116]	2 schools in Denmark. 4 study classrooms with fresh or recirculated air (paired up as a 2 × 2 crossover intervention double-blind experiment). Children aged 10–12 years.	Numerical and language-based tests, one per day in normal lesson setting—concentration, motivation, short-term memory, and logical understanding. Tests developed by [114,115].	Investigate whether increased ventilation rate in classrooms influenced the performance of schoolwork	Improvements (i.e., number of correct answers made within 10 min) in addition (6.3%), number comparison (4.8%), grammatical reasoning (3.2%), and reading and comprehension (7.4%) were observed when outdoor air supply rate increased from 1.7 to 6.6 L/s per person (CO2 concentration decreased from 1500 ppm to 900 ppm). No association with the number of errors made.
Kim et al. (2020) [117]	College students (20 healthy subjects: 16 M, 4 F) aged 23–32. South Korea, Seoul.	Climate chamber experiment; EEG measurements for brain activity/alertness.	Investigating the relationship of learning performance with psychophysiological responses at different thermal conditions.	Optimum learning performance at 25.7 °C. Alertness and working memory ability in the warm condition (33 °C) decreased by 7%. Executive ability, mental workload, alertness and mental fatigue in the cold condition (17 °C); performance decreased by 9.9%.
Haverinen-Shaughnessy et al. (2011) [118]	100 Elementary schools in Midwest USA (5th grade)	Annual standardised, state-wide test results for mathematics and reading	To study association between ventilation rates and academic achievement.	87% classrooms had ventilation rates below ASHRAE recommended guidelines. Linear association found between classroom ventilation rates (range 0.9–7.1 L/s per person) and students’ academic achievement. For every unit increase in ventilation rate, it is expected that the proportion of students passing standardised test increases by 2.9% (95%CI 0.9–4.8%) for maths and 2.7% (0.5–4.9%) for reading.
Bako-Biro et al. (2012) [119]	16 classrooms in 8 primary schools in England (332 children)	computerised performance tasks (reaction times, memory, classification, recognition)	Install mobile ventilation systems (with fresh or recirculated air) to establish a direct link between pupils’ health, well-being and cognitive performance, and classroom IAQ, using CO2 as ventilation proxy.	Higher level of focused attention in higher ventilation scenario (faster and more accurate responses in Choice RT and Colour Word Vigilance tasks). The magnitude of negative effects with inadequate ventilation was higher for tasks requiring complex skills (spatial working memory and verbal ability). Where ventilation was good, pupils reacted significantly faster in simple tasks when temperatures reduced from slightly elevated levels to a more comfortable range.

), some studies separate the effects of temperature (either objectively measured or perceived as thermal comfort) without investigating changes in ventilation. A key meta-analysis by Wargocki (2019) [60] derived a temperature-response function for resultant changes in the speed of task completion by schoolchildren, concluding that decreasing classroom temperature from 30 °C to 20 °C would increase performance by 20%. Furthermore, the “optimum” temperature for learning differs across ages and climates; the above meta-analysis concludes that an optimal temperature for children’s performance in temperate climates is <22 °C [99]. Meanwhile, college students in Seoul perform better at 25–26 °C [98].

The consensus from several reviews and studies within the last two decades is that, broadly speaking, learning outcomes improve as ventilation rate increases. There are nuances within this statement, i.e., there are several different components of cognitive and executive function testing that are affected differently by temperature or rate of ventilation (e.g., task speed and accuracy; or working memory and visual processing), and thus far we have not come across any studies that attempt to translate these types of tests into a predictor of final exam grade.

4.4. Interventions

Achieving optimal IAQ and thermal comfort in educational buildings is a complex process that requires (i) minimising indoor air pollution emissions; (ii) providing adequate, controlled, and well-maintained ventilation; (iii) using air purifiers; and (iv) employing energy efficient systems for heating, ventilation and air conditioning (HVAC); all the above can contribute towards good IAQ and help maintain temperature ranges optimal for learning [99].

4.4.1. Source Control

The first step in improving IAQ is minimising the sources of both indoor and outdoor air pollutants that eventually penetrate indoors [2,13]. Strategies such as planning the location of new educational buildings away from busy roads and industrial sites, as well as regulating traffic around existing schools, especially in drop-off zones, and creating green areas around schools or pedestrianisation can reduce the impact of outdoor air pollution on the indoor environment [5]. Building renovation can eliminate existing microbes and fungi, although cleaning is required to maintain low levels [41]. Source control can also curtail emissions from continuous indoor sources of chemicals, such as wood-based furniture and flooring, carpets, curtains and sun blinds, and building materials (e.g., plastics, resins, glues), as shown in

Table 6. Source control of pollutant emissions from indoor sources (derived from [13,120]).

Potential Indoor Sources	Pollutants	Source Control/Mitigation Measures
Furniture and wooden products (for example, pressed board, plywood, particle board, fibreboard furniture, flooring, panelling, doors)	formaldehyde, acetaldehyde, benzene, α-pinene	Choose certified, eco-labelled materials with low VOC emissions for floor/wall/ceiling coverings and furniture
Flooring materials (e.g., PVC flooring with adhesive, carpet backings)	formaldehyde, acetaldehyde, benzene, ethylbenzene, xylenes, styrene, toluene	Implement renovations and refurbishments in the first month of the summer holidays Use woven or knotted textile carpets instead of synthetic ones
Wall paints, solvent-based (water-resistant)	benzene, xylenes, styrene, toluene	Implement renovations and refurbishments in the first month of the summer holidays Use water-based paints
DIY products (for example, solvents, paints, wallpapers, glues, adhesives, varnishes, lacquers)	formaldehyde, acetaldehyde, benzene, ethylbenzene, trimethylbenzene, xylenes, styrene, toluene, tetrachloroethylene trichloroethylene, n-butyl-acetate, naphthalene, benzo(a)pyrene	Implement renovations and refurbishments in the first month of the summer holidays Use smaller quantities of or green alternatives to paints, solvents, adhesives and science laboratory chemicals Increase ventilation, e.g., open windows when working with chemicals
Painted or varnished coatings	benzene, ethylbenzene, xylenes, toluene, dichlorobenzene, n-butyl-acetate	Choose certified, eco-labelled materials Limit the use of chemical products
Paint and varnish removers stain removers, wood cleaners	α-pinene, tetrachloroethylene, trichloroethylene	Choose certified, eco-labelled materials Limit the use of chemical products
Electronic equipment (e.g., photocopy machines)	formaldehyde, acetaldehyde	Place photocopiers and printers in separately ventilated rooms
Plastics	trimethylbenzene, styrene
New books, magazines, newspapers	formaldehyde, toluene	Locate in dedicated rooms /library, well ventilated
Cleaning products and disinfectants	formaldehyde, trimethylbenzene, toluene, limonene, α-pinene, trichloroethylene naphthalene	Use fragrance-free cleaning materials,
Dry-cleaned textiles, curtains, carpets	tetrachloroethylene	Use washable textiles for classrooms instead of textiles that require dry-cleaning
Air fresheners	dichlorobenzene, limonene	Do not use air fresheners in classrooms,
Human activities (cooking)	formaldehyde, acetaldehyde, benzo(a) pyrene	Install extractor fans in kitchens to be on during cooking activity
Secondary formation	formaldehyde, acetaldehyde	Reduce ozone emissions indoors

.

Ideally, VOC and formaldehyde emissions from building products and furnishings should not be a concern in classrooms if they are subject to quality control measures and, where possible, low-emission materials are used [25]. Furthermore, good ventilation practices should be used where VOC levels may be high due to recent refurbishment, maintenance, or cleaning. Indoor lab and class/art activities, use of equipment such as printers, as well as cleaning and disinfecting products within schools, are also known to emit chemicals, such as formaldehyde and a range of VOCs [13,25,45]. Minimising the use of chemicals, using smaller quantities, as recommended by the product label, and using low VOC-emitting materials and products, as well as carrying out the lab activities and using printers in dedicated and well-ventilated areas, can all reduce indoor emissions. Such approaches are not always possible due to teaching requirements, lack of funding for refurbishment and lack of control over external conditions; hence, ventilation and air cleaning-based solutions must be investigated.

4.4.2. Ventilation, Filtration and Air Cleaning Technologies

Although natural ventilation is the most common and usually cheapest system employed in schools, it is subject to climate change, meteorological conditions and outdoor air and noise pollution levels, and can affect indoor hygrothermal conditions with little to no control [10]. It can also be ineffective where safety standards restrict window opening to a small gap [119].

Mechanical ventilation can help achieve a desired air flow rate when used correctly, but it has an associated cost and can contribute significantly to an educational building’s energy budget [10,25]. Mechanical ventilation can take many forms, for example, exhaust-only or mechanical supply-and-exhaust systems [10]. Concentrations of indoor pollutants such as PM₁₀, formaldehyde and TVOC have been found to decrease by using mechanical ventilation by around 41%, 35% and 45%, respectively [121]. Filters within HVAC units can help ensure that the incoming outdoor air is as clean as possible, especially where filters of high Minimum Efficiency Reporting Values (e.g., MERV 13) are used; unfortunately, low-efficiency filters (e.g., MERV 5) have been found to increase the classroom indoor-outdoor ratio of PM_2.5 with runtime, demonstrating their inability to fully eliminate the ingress of outdoor PM_2.5 [122]. Standalone air cleaners can also remove pollutants from indoor air; classrooms with air purifiers had approximately 35% lower PM_2.5 or PM₁₀ concentrations than those without [24]; reductions of PM and bioaerosols due to air cleaners were observed in daycare centres by 49 to 86% and 40 to 68%, respectively [99]. Central HVAC systems can be more efficient at improving IAQ than standalone air purification systems, but the expense of upgrading the systems, especially in older buildings, can be costly [24]. Mechanical air filters, such as High Efficiency Particulate Air (HEPA) filters, can be used in locations with high outdoor air pollution. Studies have demonstrated their high efficiency in reducing indoor PM_2.5 concentrations, particularly when used in tandem with HVAC air recirculation [24]. Changing the timing of the HVAC system’s operation to start one hour before rush-hour traffic can also be effective in reducing indoor PM_2.5 and UFP concentrations by 43% and 34%, respectively [99].

A review of healthy building measures associated with LEED schools and their impact on health and performance, including interventions that consisted of electrostatic air cleaners, high-rating MERV filters on air handling units, and other air conditioning systems, found that the use of electrostatic filters improved performance on cognitive tests (relating to semantic memory) by 25%, but other tasks did not show significant improvements [14]. Similarly, inconsistent effects on performance were found by another study [108], concluding that any improvements were related to the speed of task completion, rather than error rate. It was noted that even though PM_2.5 may be associated with adverse performance in the classroom, its reduction through electrostatic filters does not always lead to improvements in academic outcomes. It was suggested that the effects on performance may be related to gaseous pollutants, as their composition is unlikely to be affected by the recirculation air cleaning systems [47]; this hypothesis is supported by studies of adults and office-based tasks [123]. Notably, though the association of higher ventilation rates with improved performance and health is presumed to be attributable to the consequential reduction of indoor-generated pollutants, it is still unclear which specific pollutants are detrimental to students’ health and performance outcomes [17]. It is suggested that air cleaners can be more cost-effective than ventilation systems, although their deployment can be hindered by user experience of increased noise and space limitations [14,86].

Since airborne transmission has been reported to be the dominant route of respiratory virus spread, utilising ventilation to reduce viral concentrations, and controlling relative humidity and temperature to minimise the survival of viruses, could limit the spread of respiratory infections in daycare centres [76], subsequently reducing the absenteeism of both children and staff. Two monitoring studies comparing ventilation strategies with respiratory infections in daycare centres in Denmark and Finland demonstrated a positive association of respiratory infection decrease with increased ventilation rates and a preference for mechanical ventilation, albeit with methodological biases [76]. Studies focusing on schools in the US and Italy demonstrated a reduced incidence of SARS-CoV-2 infections where ventilation was enhanced, and further upon using additional preventative measures such as UV irradiation [76]. A recent study of naturally-ventilated UK schools evaluated the impact of HEPA air cleaners on PM_2.5 concentrations alongside viral RNA, finding a reduction of PM_2.5 by 40–60%, and viral RNA of 30–50% [124]. Another modelling study in the USA assessed outdoor air ventilation rates and HVAC filtration methods against infection transmission, finding a reduction in the infection probability of 29% upon using HVAC with air filtration (MERV 13 or above) in school buildings [125]. It concluded that HVAC with filtration was superior to 100% outdoor air ventilation in both disease transmission control and energy use. However, one modelling study on air cleaning methods with HEPA filters suggests that since filters are more efficient at removing particles with diameter larger than 5 µm (the threshold diameter defined by the Centres for Disease Control and Prevention (CDC) for droplet nuclei), they may not be as effective at preventing the spread of respiratory infections as mask-wearing in classrooms [86]. Mechanical ventilation (both with and without mask-wearing) was estimated to be significantly more effective than natural ventilation at minimising the spread of viruses such as SARS-CoV-2 in a modelling study of Italian schools, reducing the infection risk by up to a factor of 3 [126]. Furthermore, many viruses responsible for the respiratory infections commonly experienced by children in daycare centres and schools are inactivated within a relative humidity of 40–60% and a temperature of 20–24 °C; therefore, maintaining this range with MVHR can further prevent infection spread [76,126].

In terms of associations with absenteeism, several studies report no direct associations of air filtration with absenteeism, while other studies find some degree of association between ventilation and absenteeism [14].

Another recent study explored the effects of using negative air ions (NAIs) on cognitive performance and health of college students, where CO₂ is at the outdoor concentrations (500 ppm) and high (2500 ppm) [127]. Incorporating NAIs in both scenarios had a significant effect on cognitive performance after one hour of the intervention, improving reasoning skills, short-term memory, and verbal skills, with the most noticeable effects in cognitive performance in the low CO₂ condition. Although the biological mechanism through which NAIs result in cognitive performance improvement is not yet clear, it is suggested that the improvement could be associated with the reduction in PM due to the electric field produced by the NAIs and subsequent deposition on indoor surfaces. They also note that NAIs could reduce symptoms of nasal and skin irritation or dryness, lethargy and elevated heart rate normally associated with very high CO₂ concentrations [127].

Relative humidity and concentrations of airborne moulds can also be controlled through improvements in ventilation; for example, dehumidification with HEPA filtration led to reductions in airborne fungal spore counts, and another study found reduced asthma symptoms among students with ventilation interventions [80]. The presence of allergens, such as those from dogs and cats, in classrooms and daycare facilities can be effectively avoided through a combination of measures, e.g., improved ventilation systems, underfloor ventilation, controlling excess moisture and regular cleaning, as found through extensive restorations in a Swedish school [80].

A study examining the lungs of 150 asthmatic students in Boston through forced expiratory volume testing (FEV1%), before and after HEPA filters were installed, correlated the response with mould levels found in classroom dust [128]. For those students exposed to a higher Group 1 mould level (those in high concentrations specifically in mouldy homes) in their pre-intervention classroom than home (n = 94), the FEV1% results for those students were significantly inversely correlated with the Group 1 level in their classrooms. After the HEPA intervention, the average Group 1 level and ERMI values were significantly lowered, and the average FEV1% test results significantly increased by an average of 4.22% for students in HEPA compared to Sham classrooms.

4.5. Deriving Economic Benefit/Impact

Improving IAQ while maintaining thermal comfort is a delicate balance involving reduction or dilution of indoor-generated pollutants through source control or ventilation, filtration of outdoor pollutants, heat retention (during cold conditions) and cooling (during warm conditions), which comes at a capital, operational and maintenance cost. Although it is difficult to assign monetary values to net benefits associated with human factors, such as improved performance, health or wellbeing, traditional assessment metrics for improving building parameters should try to account for them [129]. In this section, we summarise the literature on the topic of monetising the benefits of both building- and human-related factors.

To justify the cost of interventions, cost-benefit analyses should consider short- and long-term health, performance and financial impacts, in addition to the underlying health and social conditions of the occupants and building condition and location. Some studies have calculated the capital and running costs of installing high-MERV filters, comparing them with predicted changes in Disability-Adjusted Life Years (DALYs) or illness-absence days due to reduced health conditions, such as asthma [111]. They estimated that upgrading MERV 5 filters to MERV 8, 12, and 14 levels in schools would reduce the annual asthma burden associated with PM_2.5 by 8, 13, and 14%, respectively, amounting to a healthcare cost saving of 0.5–0.9 million USD per year. However, many of the benefits from improving ventilation are embodied within difficult-to-quantify learning and attendance improvements [10]. Attempting to consolidate these, a study within Danish schools estimated the economic benefit of improving ventilation from the current average of 6.0 L/s/ person to the Swedish building code requirement of 8.4 L/s/person [27]. Using a macroeconomic model, this study converted the resulting improvement in IAQ into improvements in schoolwork performance and completion of studies, estimating a subsequent increase the Gross Domestic Product (GDP) by 173 million EUR per annum, and public finances by 37 million EUR per annum over the next 20 years [130]. Guidelines on how to conduct impact assessments of better air quality within national public budgets have been proposed, based on student performance in terms of the Program for International Student Assessment (PISA) score and teacher performance in terms of absences [130].

Absenteeism can impact funding—for example, in the UK, a pupil premium is provided to school districts based on average daily attendance. A Midwest USA study used a funding rate of 12.08 USD/student-day (in 2004 terms), a class of 20 children and an academic year group of 185 pupils to convert a 1% increase in absenteeism in one classroom into the equivalent of 450 USD/class/year of reduced funding [95]. Building on that, a longitudinal study [92] found that the 3.4% decrease in illness-related absenteeism from increasing ventilation rates from 4 L/s/person (California average) to 7.1 L/s/person (California minimum standard) would increase attendance-linked funding to schools by 33 million USD annually, compared to costs by only 4 million USD. Although the focus of this review is the health of children, additional related benefits for adults include decreased costs for time caregivers stayed at home with a sick child, amounting to 80 million USD [92] and reduced absence from work [10,93]. Bridging the gap between absenteeism and performance, it has been estimated that the annual benefit from reduced teacher absences in Danish schools achieved by increasing the ventilation rate from 6 to 8.4 L/s/person would be close to 6 million EUR [27].

The annual benefit of reduced healthcare requirements, as well as monetary benefits, across all indoor and outdoor settings upon achieving WHO guidelines for PM was estimated to total 31 billion EUR across 25 European countries [25,131]. Such improvements have been tracked in children through measured lung function within a cohort and could be monetised [132]. However, splitting this top-down figure into components based on residential, work, transport, external and educational environments over entire populations is challenging due to the different influences of each environment on the health of individuals. In terms of academic performance, pass rates improved by 3% at ventilation rates greater than 7/L/s per person [90]. Improved academic performance due to better thermal conditions could alone justify 20–40% of the cost of HVAC systems in Japanese schools [15]. A modelling study of IEQ, ventilation and building envelope improvements in UK schools found a reduction in asthma of 676 cases/100,000 children, which resulted in 64,310 GBP reduced hospital utilisation costs [133].

However, such benefits must also be balanced against intervention costs [10]. A key issue is that benefits and intervention costs have not traditionally been compared directly within a cost-benefit analysis [14] due to their complexity, except in studies investigating a single intervention rather than a range of options or microenvironments. In principle, the cost of investing in improved ventilation systems can be viewed as insignificant when pitched against, e.g., the estimate that the energy and capital costs of HVAC filtration systems are <0.1% of overall US spending on public elementary and secondary education [17]. Despite this, such decisions to intervene, in ways described in Section 4.4, often remain unmade by local administrative bodies due to budgetary demands and overregulation, which need to be overcome through more transparent quantitative analysis of both the benefits and costs.

Increasing ventilation rate would incur additional operating costs based on (a) energy required to heat air in cooler climates, (b) dehumidify in warmer climates and (c) drive air through HVAC systems, and (d) capital costs of providing these systems [17]. Some capital costs are easy to quantify, such as 250 USD per portable air cleaner unit [86], or 1000–2000 GBP per standalone HEPA filter unit for a UK classroom [17], which tend to be cheaper than installing whole-building HVAC systems. Operating costs are variable, as energy consumption increases by ~37% and HVAC total cost by ~26% upon doubling the ventilation rate from 10 to 20 m³/h/person (approximately equivalent to 2.8 to 5.6 L/s per person) [15]. The energy cost of a standalone HEPA filter may be equivalent to 2% of a typical UK classroom’s heating cost [124]. Also, capital costs of materials, replacements, procedures and staff training have proved harder to ascertain and are essential within the decision-making process [99]. In climates with cooling seasons only, such as Florida [17] and California [92], capital costs for HVAC systems, required for cooling, have mostly already been incurred; hence, the main variation in cost is dependent on the setting of desired indoor temperature relative to outdoor temperatures and capacity. It was estimated that an increase of 5 L/s per person would result in additional operating energy costs of about 2–7 USD/year per person, and costs of increased capacity of 2–3 USD/year per person, totalling <10 USD/year per person [17]. A recent attempt to derive energy costs of heating additional air required to fulfil ventilation requirements was based firstly on replacing gas boilers with heat pumps before improving indoor environmental conditions as a secondary process [133]. The costs of upgrading from the most basic (MERV5) to the most efficient filters (MERV 14) was calculated at a marginal cost of 2–3 USD/year per person or 20–32 USD/year per asthmatic person, which was well below the benefit of avoided asthma exacerbations of 49–79 USD/year for each asthmatic person described above [122].

5. Discussion

5.1. Limitations

There are obvious health and academic performance benefits to improved IAQ, ventilation and thermal comfort in educational environments, but their associations and causal pathways are not yet fully understood. One might expect that reduced symptoms of ill-health due to better environmental conditions would reduce absenteeism, improve a student’s ability to concentrate on a task in the classroom and therefore enable higher academic attainment. It must be noted that while improved ventilation or air filtration can improve IAQ, thermal conditions and associated health outcomes, this does not always translate to improved academic performance, and any direct associations between specific pollutants, such as VOCs, and academic performance are not fully established. Unfortunately, quantifying such associations is challenging, due to (i) low availability of long-term measurements in educational settings of IEQ parameters other than CO₂ in tandem with health or performance outcomes; (ii) predominance of self-reported IAQ and thermal comfort perception and health data over quantifiable health measurements such as lung capacity; and (iii) the various different ways of assessing performance that yield varying conclusions. Unless a modelling study is carried out rigorously, studying the effects of interventions to improve IAQ and thermal comfort in situ requires installing the measure, training staff to use it correctly and maintaining its standards, which is costly and serves as an additional task for staff to undertake. Researchers are likely to be further limited by policy and local authorities’ agendas from carrying out experiments involving building alterations [99].

The body of literature surrounding school-based interventions to improve students’ health is limited, many studies suffer from selection and attrition bias, and the time between IAQ, thermal condition or ventilation intervention and measured health or academic outcome is often too short to discern robust conclusions [99]. Most literature on IEQ interventions, such as those in LEED-certified educational buildings, focuses on the reduction of pollutants, with limited assessment of academic outcomes that may even be contradictory, depending on study design [14]. Several field monitoring and numerical modelling studies of classroom air quality failed to report key details of study design and were therefore not able to evaluate their validity [21]. Parent/child questionnaires have been used to scale-up findings on health outcomes from individual schools to entire school districts, although inherent response biases, when compared to clinical testing, must be accounted for. Other confounding factors to health and learning outcomes, which are often not accounted for, are seasonality (i.e., whether a study is conducted over just the heating season or throughout the whole year), exposure to pollution and unfavourable IEQ conditions at home, and other complex socio-economic factors (i.e., some students may be more susceptible to pollution than others due to their socio-economic background and current health status, despite experiencing a similar schooltime exposure). Furthermore, more research focusing on older adolescent and adult populations in educational buildings (e.g., lecture theatres, seminar classrooms and libraries at universities and colleges) is required, as students may be obtaining their highest form of formal education in these settings, which may affect future career, income, and other socio-economic factors.

Analysing the effect of IAQ and thermal comfort on school absenteeism requires context-specific building, age-group and socio-economic home and school district details. There is a risk of viewing absenteeism as a homogeneous term; however, the definition (illness or non-illness related) and format (records and quality) of the data can impact studies trying to quantify the association with attainment. Although studies demonstrate an association of high levels of absenteeism in schools within highly polluted areas with lower academic achievement, the strength of this association is difficult to establish without addressing the underpinning complex interplay between demographics, outdoor air quality, and SES with academic performance [14].

Few studies perform a direct cost-benefit analysis of improving IAQ and thermal conditions in educational environments and the effect on health or academic performance, with linkages to socio-economic outcomes (e.g., [21,122,133]). It is also not yet clear whether poor IAQ or thermal comfort in classrooms would have acute or long-term academic performance outcomes, and the strength of other confounding factors such as exposure to pollutants outside of the classroom and socio-economic background.

At the population level, the benefits of preventing illness and any associated absence due to improved IAQ and thermal conditions are likely to be significant [86], though additional research needs to be conducted on this specific topic. The figure of increased GDP from improved classroom ventilation assumes that education would be completed under more favourable learning conditions, resulting in better exam results and higher productivity in adult life [27], the testing of which may require a costly cohort study.

5.2. Recommendations

Recommendations for relevant stakeholders, such as local authorities, decision-makers and teachers, for protecting students’ health, wellbeing and academic attainment from poor IAQ and thermal conditions include [13,24,45,115] the following:

(1)

Eliminating sources of indoor and outdoor pollution. This is the simplest and cheapest measure to improve IAQ, especially in naturally ventilated buildings, though its effectiveness may be limited and dependent on existing building materials, site location, or other factors. For example, reducing occupant density in classrooms (to minimise CO₂ and bio-effluents); ventilating laboratories or art classrooms during activities, using only the minimal necessary quantities of products (e.g., during chemistry experiments or painting) to minimise VOC emissions; or discouraging vehicles used for student drop-off or pick-up from idling outside the building to reduce traffic-related PM_2.5 and NO_x emissions from entering indoors (behavioural intervention).

(2)

Ensuring the provision of adequate classroom ventilation through well-maintained hybrid or mechanical systems, depending on the budget available. Studies reviewed in the present paper have consistently shown that hybrid, demand-controlled and fully mechanical systems with high MERV filters outperform natural ventilation in terms of pollution control while maintaining consistent indoor temperature, as well as for respiratory infection transmission and asthma symptoms.

(3)

Adhering to national ventilation guidelines and standards. The literature reviewed herein demonstrated that although standards vary per country, there is a widespread failure of publicly funded educational buildings to meet them, either through a lack of funding or provision, or a lack of awareness. Collaboration across relevant stakeholders, from local MPs and politicians to headteachers, could lead to increased public funding for providing sufficient ventilation in educational buildings and increasing awareness of the benefits of doing so to encourage behavioural change.

It could be argued that the cost of implementing and maintaining structural intervention measures to improve IAQ and thermal comfort is high for educational environments, which already face pressures to justify public funding decisions. Improvement of state-wide or national funding for schools would enable them to implement structural changes required to control sources and adhere to ventilation standards. Unfortunately, over half of U.S. school districts do not have any sort of IAQ policy in place [134]—this is concerning, given the demonstrated importance of maintaining adequate IAQ for health and learning. To reduce implementation costs, behavioural interventions aiming to control sources and the provision of ventilation, especially in naturally ventilated educational buildings, should also be considered. Any costs incurred by providing the above interventions should be morally offset by the resultant improvement in young people’s health and wellbeing, which is arguably worth bearing the price [17].

Future Net Zero initiatives to reduce building energy consumption are certainly going to further affect IAQ and thermal conditions in educational buildings. Care must be taken to prevent the unintended consequences of these actions on IAQ, relative humidity and temperature, among other factors, but also any secondary effects on pupils’ health and learning.

However, even implementing current evidence into practice would be a significant step forward to improving IAQ and thermal conditions in educational buildings, and associated health and academic outcomes, despite the research gaps that still exist. Future studies should focus on the impact of different pollutants on health, cognitive development and academic performance, both in terms of acutely testing the cognitive function as well as conducting long-term studies and sufficient follow-up of cohorts. It would also be beneficial to determine the effects across different age groups, as effects on young children are likely to be different from those on adolescents, whose organs are further developed. Lastly, it would be beneficial to consider neurodivergent pupils, who are often not the main subject of such studies but may be particularly susceptible to sensory effects due to the environmental conditions, including auditory and visual, which may be detrimental to learning.

6. Conclusions

We have reviewed the latest available literature on the potential benefits and drawbacks of improving indoor air quality, ventilation and thermal comfort in terms of health, wellbeing and academic attainment of students, across the whole spectrum of educational buildings, from daycare centres to colleges and universities. It is evident that there are net socio-economic benefits from improved health and performance of students at all ages associated with reduced classroom pollution, increased ventilation and optimal indoor temperature. These benefits include, among others, improved cognitive development, performance in some physiological tasks and end-of-year exam grades; as well as reduced respiratory health outcomes such as asthma and airborne virus transmission, resulting in decreased illness-related absenteeism. However, technological interventions to improve the indoor environmental conditions may be relatively expensive to implement in some institutions, especially in older educational building stock that may rely solely on natural ventilation, and in cases where the educational buildings have other structural issues that require prioritisation within limited public budgets. Additionally, continuous operation, regular maintenance and upgrading of existing systems can help achieve national ventilation standards.

The main conclusions to be drawn from this review are as follows:

• Adverse respiratory and neurological health outcomes associated with exposure to indoor air pollutants can secondarily impact educational attainment both in the short and long term.
• Few studies succeeded in isolating the effects of exposure in the education environment from exposures in the home, while also accounting for socio-economic confounders (e.g., health inequalities across more deprived communities).
• Attributing health effects to individual pollutants can be challenging, which some studies account for by using an index covering multiple pollutants.
• A holistic approach of both repairing damage to buildings and improving ventilation should ensure that health effects relating to, e.g., damp conditions or uncontrolled ingress of outdoor pollution are minimised.
• Together with source control, the provision of adequate ventilation can achieve optimal IAQ in educational buildings. Increasing classroom ventilation rates often results in better performance (e.g., speed of task completion), but there are inconsistencies relating to, e.g., cognitive performance and task error rate, caused by difficulties delineating the impacts of different pollutants on academic performance. Maintaining indoor temperature between 20 °C and 22 °C through natural or hybrid ventilation can also improve academic outcomes.
• There is evidence of associations between absenteeism and chronic PM exposure, mould, and low ventilation rates. There is a lack of substantial evidence to confirm the associations of absenteeism with VOC or O₃ exposure.
• Traffic-related air pollution has been found to impact the executive function through task completion speed, as well as exam grades and language/numeracy testing. There is evidence of negative associations between PM_2.5 and working memory; NO₂ and UFP with reduced cognitive development compounded by long-term exposure; and VOCs and PAHs with cognitive function.
• Mechanical and hybrid ventilation systems systematically outperform natural ventilation strategies in terms of achieving a desired air flow rate to provide adequate conditions for both learning and reducing respiratory infection transmission. However, ventilation standards remain unmet in a concerningly large proportion of educational buildings, especially schools, even when mechanical ventilation is in place. Depending on national or state public school funding, the capital and operating costs of mechanical ventilation and/or air filtration devices to improve indoor conditions can represent a relatively small fraction of a typical state school budget.

Since a time-lag between the intervention and cognitive development or learning benefits has been demonstrated within the literature, quantifying these longer-term impacts can be more difficult than the more immediate aspects, such as illness-related absences. Any cost-benefit analyses of interventions should therefore consider both short- and long-term health and performance outcomes, alongside student wellbeing, to provide the best possible indoor environmental conditions for the next generation to academically thrive.