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Asian Journal of Atmospheric Environment - Vol. 12 , No. 2

[ Review Article ]
Asian Journal of Atmospheric Environment - Vol. 12, No. 2
Abbreviation: Asian J. Atmos. Environ
ISSN: 1976-6912 (Print) 2287-1160 (Online)
Print publication date 30 Jun 2018
Received 09 Sep 2017 Revised 29 Jan 2018 Accepted 14 Feb 2018

A Review Of Scientific Evidence On Indoor Air Of School Building: Pollutants, Sources, Health Effects And Management
Chithra, V.S* ; Shiva Nagendra, S.M
Department of Civil Engineering, Environmental and Water Resources Engineering Division, Indian Institute of Technology Madras, Chennai 600036, India

Correspondence to : *Tel: +918943943183, E-mail:


Schools are one of the critical social infrastructures in a society, the first place for social activity and the most important indoor environment for children besides the home. Poor IAQ in classrooms can increase the chance of long-term and short-term health problems for students and staffs; affects productivity of teachers; and degrade the student learning environment and comfort levels. The primary objective of this paper is to review and summarize available scientific evidence on indoor air quality of schools and related health effects in children. It was found that the indoor air pollutant levels in school buildings varied over a wide range in different parts of the world depending on site characteristics, climatic conditions, outdoor pollution levels, occupant activities, ventilation type and building practices. Among the indoor air pollutants, particulate matter concentrations were found to be very high in many schools. Outdoor pollutant sources also play a major role in affecting the IAQ of the school building. Hence, scientific knowledge on sources of indoor pollutants, quantification of emissions, temporal and spatial dispersion of pollutants, toxicological properties, chemical and morphological characteristics of the pollutants and associated health risk among children in the school buildings are essential to evaluate the adequacy and cost effectiveness of control strategies for mitigating the IAQ issues.

Keywords: Indoor Air Quality, Schools, Health effects, Pollutants, Children


Over the years, changes in building design to improve energy efficiency have made modern homes, schools and workplaces more airtight than the older buildings. These improvements have led to more energy efficient buildings with less operational costs. The increased use of synthetic materials in the buildings has contributed to increase of a large number of harmful compounds indoors. In addition, outdoor air pollutants can also enter into the building through ventilation intakes, open doors and windows, and leaks in the building envelope. In general, the concentration of a pollutant in the indoor environment depends on the relationship between the volume of air contained in the indoor space, the rate of production or release of the pollutant, the rate of removal of the pollutants (reaction or settling), the rate of air exchange with the outside atmosphere, and the outdoor pollutant concentration (Maroni et al., 1995).

The Indoor Air Quality (IAQ) of schools is gaining much attention in recent years. Children spend almost 25-30% of their time, inside classrooms and worldwide, the length of the education expectancy of children over the age of five increased from 10.1 years in 1999 to 11.0 years in 2007 (UNESCO, 2009). School environments differ from adult work environments because children have special habits such as unprotected coughs and sneezes, less likely to wash their hands, and more likely to share the “tools of the trade” such as pencils, that encourage the spread of infectious disease (Oliver and Shackleton, 1998). Moreover, children are more sensitive to air pollutants. Since their organs are in developing stage they breathe more air relative to their body size than adults (WHO, 2006a; Mendell and Health, 2005; Faustman et al., 2000). Poor IAQ can increase the chance of long-term and short-term health problems for students and staff; reduce productivity of teachers; and degrade the student learning environment and comfort levels. The National Center for Education Statistics of the Department of Education reported that approximately one in five U.S. public schools had unsatisfactory IAQ (U.S. EPA, 2012).

This paper presents a state of the art analysis of research in the area of health and wellbeing of children and their relationship to IAQ in school buildings. The focus of this paper is to review and summarize available scientific evidence on the various sources, types and level of indoor air pollutants in classrooms and further to establish a link between these IAQ parameters with the health and wellbeing of students. The paper also discusses the indoor air quality management practices across the world. This may help researchers of the future to establish a robust foundation for research in this area. In this study, quite an extensive range of literature was reviewed. The literature included refereed journals, books, refereed conference proceedings and reports available on the internet.


complex and their concentration levels and sources exhibit large variability among different microenvironments. The IAQ issues in schools may be very different from those observed in residential and commercial buildings. In residential and commercial buildings, pollutants can arise from a range of sources, such as environmental tobacco smoke, cooking, domestic chemicals and furnishings. Classrooms normally lack of typical indoor sources such as smoking and cooking. Yet, several studies reported that the pollutant concentrations measured inside classrooms were higher than the concentrations measured in residences and commercial buildings (Oeder et al., 2012; Lee et al., 2002). In general, schools have their own particular sources of pollutants: chalk dust; fungi, bacteria, and viruses brought to the school environment by children and adults; and vapors and fumes from laboratories, and art classes. Indoor air pollutants can originate within the building or be drawn in from outdoors. The pollutants present in the indoor air is classified into three major types namely, particulate matter (PM), gaseous pollutants and bioaerosols. The major indoor and outdoor sources of air pollutants in schools are summarized in Table 1.

Table 1. 
Indoor air pollutants and their sources in schools.
Pollutants Sources
Indoor Outdoor
Particulate Matter (PM) Chalk dust, soil dust, new furniture, cleaning activities,
resuspension of particles due to children’s movements,
combustion sources such as heaters, gas-and woodstoves
and smoking
Traffic and industrial emissions
Carbon monoxide (CO) Heaters, gas and woodstoves and smoking Traffic and industrial emissions
Nitrogen dioxide (NO2) Gas appliances, heaters and smoking Traffic and industrial emissions
Sulpher dioxide (SO2) - Burning of coal and other fuels
Ozone (O3) Ozone generators, electrostatic air cleaners, photocopiers
and laser printers
Secondary photochemical
Volatile organic compounds
Furnishings such as desks and shelves, resins of wood
products, adhesives, glues, paints, fibre board, plywood,
cleaning products and carpets
Traffic emissions
Bioaerosols Human occupants and heating, ventilation and
air-conditioning system

2. 1 Particulate Matter

The PM is a mixture of solid particles and liquid droplets found in the air. Atmospheric particles possess a range of morphological, chemical, physical and thermodynamic properties and its constituents typically vary in size, composition and origin. The distribution of particles with respect to size is an important physical parameter governing their behaviour. Particle diameters span more than four orders of magnitude, from a few nanometers to one hundred micrometers. They often are not spherical and have a range of densities. Therefore, their diameters are often described by an ‘equivalent’ diameter called aerodynamic diameter. It is defined as the diameter of a spherical particle with a density of 1 g/cm3 but with a settling velocity equal to that of the particle in question. Particles are generally classified as ‘coarse’ and ‘fine’ particles according to the aerodynamic diameter. The most commonly used PM size fractions in air quality research are as follows.

  • • Total suspended particulate matter (TSPM): Comprises all airborne particles up to 100 μm.
  • • PM10: Particles with an aerodynamic diameter <10μm with a 50% efficiency cut-off.
  • • PM2.5: Particles with an aerodynamic diameter <2.5μm with a 50% efficiency cut-off.

The size of the particles also determines the time they spend in the air. While sedimentation removes PM10 from the air within few hours of emission, PM2.5 may remain there for days or even a few weeks. Consequently, these particles can be transported over long distances (Krzyzanowski et al., 2005). Finer particles are of great concern to human health since they can penetrate deep into the respiratory system, take longer time to remove from the body (Miller, 2000) and associated with many respiratory and cardiovascular diseases (Mate et al., 2010; Wallenborn et al., 2009; Medina et al., 2004; Mohanraj and Azeez, 2004; Neuberger et al., 2004; Pope et al., 2004, 2002; WHO, 2003; Morris, 2001; Pearce and Crowards, 1996; Schwartz et al., 1996).

PM pollution has been identified to be a major indoor air pollution (IAP) problem in many schools. Particulate pollutants are emitted from a broader range of sources including chalk dust, soil dust, new furniture, cleaning activities, resuspension of particles due to children’s movements, combustion sources such as heaters, gas and wood stoves, smoking when allowed, outdoor traffic and industrial emissions. Traffic emissions are found to be one of the most important sources of indoor and outdoor air pollution in schools (Mazaheri et al., 2016; van der Zee et al., 2016; Demirel et al., 2014; Buonanno et al., 2013; Habil et al., 2013; Raysoni et al., 2013; Zwozdziak et al., 2013; Tran et al., 2012; Guo et al., 2010; Goyal and Khare, 2009; Yang et al., 2009; Stranger et al., 2008; Branis et al., 2005; Lee and Chang, 2000). Another main reason for elevated coarse PM concentrations in classrooms is due to intense occupant activities (Agarwal and Nagendra, 2016; Chithra and Nagendra, 2012; Diapouli, 2008; Fromme et al., 2008; Stranger et al., 2008; Branis et al., 2005; Poupard et al., 2005; Janssen et al., 1999, 1997). Human activities could act as an important indoor source for particulate generation in classrooms considering that the occupant density in the schools was several times higher than that in other buildings. Elevated indoor PM concentrations were predominantly generated by the activities of occupants such as movement of students and teachers inside the classroom, black board writing using chalk, cleaning/ sweeping etc. Major movement of occupants occurs at the start of the school day, breaks, and at the end of the school day. Thatcher and Layton (1995) reported that even low activity would have a significant impact on the concentration of airborne particles with diameters greater than 5 μm. Just walking into and out of the room can increase the mass of coarse suspended particles by almost 100%. From experiments, they concluded that the particles larger than 5 μm were subjected to resuspension, particles smaller than 5 μm were not readily resuspended, and particles smaller than 1 μm showed almost no resuspension, even with vigorous activity.

Many researchers analysed the effect of PM sources in the immediate vicinity of schools (Rufo et al., 2016; Fromme et al., 2007; John et al., 2007; Poupard et al., 2005) by monitoring PM in more than one school located in different sites like urban, rural, near traffic and industrial areas. Lee and Chang (2000) investigated the indoor and outdoor air quality at five schools in Hong Kong and found that high level of PM10 was due to vehicle exhaust emissions followed by emissions from industrial processes or construction activities. Janssen et al. (2001) also observed that PM2.5 and soot concentrations in both indoor and outdoor air of schools in the Netherland were significantly increased with increasing truck traffic. Gadkari (2010) studied the indoor fine PM among school communities in mixed urban-industrial environment in India and reported that school located near the steel plant have shown 5 to 6 times higher PM values compared to the National Ambient Air Quality Standards (NAAQS). Several investigators compared the PM concentration in different indoor environments in the school building like classrooms, library, administrative office, laboratory etc. (Gaidajis and Angelakoglou, 2009; Diapouli et al., 2008; Sawant et al., 2004) and concluded that the resuspension of particles due to occupants’ activities plays an important role in indoor coarse particle concentration. A study by Triantafyllou et al. (2008) reported that tobacco smoking was a major source of fine particles in schools. Location of the classroom inside school also plays an important role in the IAQ level. PM mass and number concentrations were measured in multilevel classrooms by Agarwal and Nagendra (2016). Result showed highest PM10 mass concentration in ground floor classroom and showed decreasing trend with increase in floor height. The highest particle number concentration (PNC) for particles of size 0.3-1 μm were observed in first floor classroom followed by second floor classroom and then ground floor classroom. Similarly, ElSharkawy (2014) also found that the average levels of pollutants inside the classrooms of the first floor were higher than that of the second floor.

Most of the previous studies conducted at school buildings were focused on PM10 and PM2.5 mass concentration. Few measurements were also reported on ultrafine particles (Mazaheri et al., 2016; Rufo et al., 2016; Dorizas et al., 2015; Rivas et al., 2015; Viana et al., 2015; Zhang and Zhu, 2012; Mullen et al., 2011; Morawska et al., 2009; Diapouli et al., 2008), which represent a significant fraction of the particulate emitted from combustion sources. It can remain suspended in the air for a long time and can easily penetrate deep portion of the lungs where the gas exchange occurs between the air and blood stream. The health effects of PM strongly depend on its composition, which consists of inorganic ions, organic carbon (OC), elemental carbon (EC), crustal elements and toxic metals. Recently, few attempts were also made to chemically characterize the particles in the school building. John et al. (2007) analysed trace elements and ions in the ambient fine PM at three elementary schools in Ohio and observed strong seasonal and regional variations in indoor PM. Most of the researchers observed that sulphate and calcium (caused by the use of chalk) were the major components of indoor PM in the school building (Rivas et al., 2015; Amato et al., 2014; Canha et al., 2014; Chithra and Nagendra, 2013; Pegas et al., 2012; Tran et al., 2012; Diapouli, 2008; Fromme et al., 2008; Stranger et al., 2008; John et al., 2007). Organic and elemental carbon was also found in indoor PM (Rivas et al., 2015; Alves et al., 2014; Chithra and Nagendra, 2013; Pegas et al., 2012). The influence of traffic at roadside is reflected in higher EC mass fractions. Tran et al. (2014) reported lower concentrations of carcinogen elements such as As, Cd, Cr, and Ni in French classrooms.

2. 2 Gaseous Pollutants

Gaseous pollutants include both VOCs and inorganic gases. The major gaseous pollutants found in the school buildings are carbon dioxide (CO2), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), ozone (O3) and VOCs.

2. 2. 1 Carbon Dioxide

It is a colourless, odourless gas exhaled by humans continuously due to the metabolic processes. Although CO2 is produced by the combustion of fossil fuels, it is not classified as an air pollutant. At low concentrations typically occurring indoors, CO2 is harmless and is not perceived by humans. Exhaled air is usually the largest source of CO2 in classrooms. CO2 concentrations are often used as a surrogate of the rate of outside supply air per occupant. Indoor CO2 concentrations above 1,000 ppm are generally regarded as indicative of ventilation rates that are unacceptable with respect to body odours. Norback et al. (1990) studied the incidence of sick building syndrome (SBS) in six primary schools. This study showed that the average CO2 concentrations in all sites were greater than 800 ppm and indicated inadequate ventilation. Similarly, Lee and Chang (2000) investigated IAQ of five classrooms in Hong Kong and reported that the CO2 concentrations often exceeded 1,000 ppm in classrooms. In most of the classrooms the CO2 concentrations were found to be exceeding 1,000 ppm (Buonanno et al., 2013; Pegas et al., 2012; Yang et al., 2009; Fromme et al., 2007; Godwin and Batterman, 2007), indicating inadequate ventilation. However, Kim et al. (2007, 2005), Smedje and Norback (2000) and Chithra and Nagendra (2012) reported CO2 concentrations below this limit value.

Most of the available information on CO2 concentration in schools comes from measurements performed in mechanically ventilated classrooms. In order to evaluate the existing knowledge on CO2 concentration in schools, Santamouris et al. (2008) conducted a comprehensive review on CO2 concentration in naturally (287 classrooms of 182 schools) and mechanically ventilated (900 classrooms of 220 schools) buildings. A higher average CO2 concentration was observed in naturally ventilated schools (median=1,420 ppm) than the mechanically ventilated ones (median=910 ppm). Only 25% of the naturally ventilated schools present concentrations lower than 1,000 ppm, while for the mechanically ventilated schools the figure increases to 52%. Available information on the CO2 concentrations in naturally ventilated schools comes mainly from measurements under closed windows conditions, or measurements under static conditions where the area of the opened windows remains constant (Santamouris et al., 2008).

2. 2. 2 Carbon Monoxide

CO is a colourless, odourless toxic gas formed by incomplete combustion of fuel. It is a nonreactive species in the air, does not react rapidly with surfaces and has low water solubility. Once it is released to the atmosphere, its main fate is oxidation, by reaction with OH· to CO2. In school buildings, CO mainly derives from combustion sources such as heaters, gas and wood stoves, and smoking when allowed (Triantafyllou et al., 2008). Main outdoor sources of CO in urban schools are vehicular emissions (Chithra and Nagendra, 2012; Yang et al., 2009; Chaloulakoua and Mavroidis, 2002). Yang et al. (2009) measured the indoor and outdoor CO concentrations at 55 different schools from six metropolitan areas in Korea. The indoor/outdoor (I/O) CO concentration ratios in the classrooms, laboratories and computer rooms were 0.71, 0.20 and 0.14, respectively. The CO concentrations in the school buildings were found to be very low in most of the studies, since they are mainly originated from outdoor vehicular emissions. Tran et al. (2014) reported that cigarette smoking also contribute indoor CO concentrations.

2. 2. 3 Nitrogen Dioxide

It is a corrosive gas with a pungent odour and it has low water solubility. The sources of NO2 emissions in the indoor environment are gas appliances, heaters, and smoking of cigarettes. The presence of these sources is very limited in most of the schools. Hence, outdoor air can act as an important source for indoor NO2 pollution in school buildings. NO2 is generally considered as a marker for traffic emissions. In the absence of indoor emission sources, levels of NO2 in classrooms generally correlate well with those observed outdoors (Stranger et al., 2008; Lee and Chang, 2000). Also, the indoor concentrations of NO2 were higher than outdoor concentrations. In most of the previous studies in schools reported very low NO2 concentrations (Rivas et al., 2015; Demirel et al., 2014; Raysoni et al., 2013; Poupard et al., 2005; Lee and Chang, 2000) expect in Antwerp, Belgium where the maximum concentration reached up to 159 μg/m3 (Stranger et al., 2008). The increased values for NO2 concentrations in schools of Belgium were related to elevated O3 levels in the warmer season, promoting increased nitric oxide (NO) to NO2 conversion and with the consequent O3 formation in the presence of VOCs and sunlight.

2. 2. 4 Ozone

O3 is a secondary air pollutant that forms at ground level when hydrocarbons and oxides of nitrogen react with ultraviolet radiation in sunlight to produce photochemical smog. In general, indoor O3 concentrations are substantially lower than outdoor concentrations unless there is an important O3 source such as ozone generators, electrostatic air cleaners, photocopiers and laser printers exist (Stranger et al., 2008). In general, O3 concentrations in schools were higher in outdoors than indoors (Demirel et al., 2014; Jovanovic et al., 2014; Mi et al., 2006; Poupard et al., 2005). There is evidence to suggest that a lower I/O ratio for O3 in the classroom was resulted from deposition on various solid surfaces, and chemical reactions in the indoor air, rather than the filtering of the ventilation air when entering the building (Demirel et al., 2014; Poupard et al., 2005). Absence of the major sources at classrooms such as photocopy machines or ozone generators may also result in lower indoor O3 concentrations (Stranger et al., 2008).

2. 2. 5 Sulphur Dioxide

It is a colourless gas with a strong pungent odour. It is readily soluble in water and can be oxidised within airborne water droplets. SO2 is a precursor to sulphates, which is one of the main components of respirable particles in the atmosphere. SO2 is produced by the oxidation of sulphur present in the coal and other fuels. SO2 levels were generally lower in indoors than outdoors. Only very few studies have been reported on SO2 concentration in school buildings (Stranger et al., 2008; Lee and Chang, 2000). Lee and Chang (2000) investigated IAQ of five classrooms in Hong Kong and observed that the SO2 levels ranged from 5 to 16 μg/m3. Stranger et al. (2008) measured SO2 concentrations in 27 primary schools located in Antwerp, Belgium and reported that the indoor SO2 concentrations were on average 70% lower than the corresponding outdoor levels, with a very low average I/O ratio of 0.3±0.1, confirming the outdoor origins of indoor SO2.

2. 2. 6 Volatile Organic Compounds

According to U.S. EPA, volatile organic compounds means any compound of carbon, excluding carbon monoxide, carbon dioxide, carbonic acid, metallic carbides or carbonates, and ammonium carbonate, which participates in atmospheric photochemical reactions. VOCs are organic chemical compounds whose compositions make it possible for them to evaporate under normal indoor atmospheric conditions of temperature and pressure. This general definition of VOCs is used in the scientific literature, and is consistent with the definition used for IAQ. The European Union uses the boiling point, rather than its volatility in its definition of VOCs. A VOC is any organic compound having an initial boiling point less than or equal to 250°C measured at a standard atmospheric pressure of 101.3 kPa. VOCs are sometimes categorized by the ease they will be emitted. For example, WHO categorizes indoor organic pollutants as very volatile, volatile, and semi-volatile. Very volatile organic compounds (VVOCs) are so volatile that they are difficult to measure and are found almost entirely as gases in the air rather than in materials or on surfaces. The least volatile compounds (SVOCs) found in air constitute a far smaller fraction of the total present indoors.

VOCs include a variety of chemicals and the concentrations of many VOCs are consistently higher indoors (up to ten times higher) than outdoors. VOCs are emitted by a wide array of products which includes paints and lacquers, paint strippers, cleaning supplies, pesticides, building materials and furnishings, office equipment such as copiers and printers, correction fluids and carbonless copy paper, graphics and craft materials including glues and adhesives, permanent markers, and photographic solutions (U.S. EPA, 2014). VOCs have low boiling points which means that they readily offgas vapours into indoor air. In any given environment, the concentration of individual VOCs will be very variable and depend upon the presence or absence of an extremely wide range of potential emission sources.

The known emission sources of VOCs in schools are construction materials, furnishings such as desks and shelves, resins of wood products, adhesives, glues, paints, cleaning products and carpets (Alves et al., 2016; Jovanovic et al., 2014; Yang et al., 2009; Godwin and Batterman, 2007). The levels of VOCs found in schools indoor can be much higher than those found outdoor. VOC concentration may be much higher than typical ambient levels in newly constructed school buildings, or those in which decorations have recently taken place. VOCs in schools can also contribute from outdoor air (traffic emissions). Measurements of total and speciated VOCs in schools were reported in the literature (Demirel et al., 2014; Jovanovic et al., 2014; Raysoni et al., 2013; Pegas et al., 2012; Yang et al., 2009; Stranger et al., 2008; Godwin and Batterman, 2007). The most common species of VOCs found were benzene, toluene, ethylbenzene and xylene (BTEX). Among BTEX, toluene concentrations were found to be higher in classrooms than other compounds (Madureira et al., 2015; Demirel et al., 2014; Jovanovic et al., 2014; Raysoni et al., 2013). Formaldehyde is another VOC present in the classrooms, which is used widely to manufacture building materials and numerous other products. In school buildings, it is emitted via glues, fibre board, pressed board, plywood, insulating materials, carpet backing, fabrics, paints, cleaning and other consumer products (Madureira et al., 2015; Yang et al., 2009). Formaldehyde concentrations in the classrooms were also found to be very low and sometimes even below detectable limit (Yang et al., 2009; Lee and Chang, 2000). However, a study reported by Jovanovic et al. (2014) in Serbian schools indicated that the average value of formaldehyde in all classrooms was significantly higher than recommended value.

2. 3 Bioaerosols

Bioaerosols refers to a diverse variety of agents from biological sources found in indoor environments, which include: viruses; bacteria, endotoxins released from bacteria; allergens; and fungi. This definition includes all airborne microorganisms regardless of viability or ability to be recovered by culture; it comprises whole microorganisms as well as fractions, biopolymers and products from all varieties of living things (ACGIH, 1999). Major indoor sources of bioaerosols at schools include human occupants, as well as the heating, ventilation and air-conditioning (HVAC) system. The air-conditioning system controls the air humidity, temperature and particulate content, etc. by means of various components such as filters, humidifiers, fresh air supply, cooling and heating systems. At the same time, the system may induce a serious indoor microbial contamination problem. Water spray humidifiers containing stagnant water, filters packed with organic dust, cooling coils covered with condensation, condensate pans being undrained and any excessively humid interior might all offer suitable environments for microbial proliferation. Airborne Bacteria Count (ABC) in an indoor environment is a good indicator of the cleanliness of the HVAC system and one of the important parameters to evaluate IAQ (Mui et al., 2008). Human bodies can generate bioaerosols through activities like talking, sneezing, and coughing. Qian et al. (2012) estimated size-resolved emission rates of airborne bacteria and fungi in an occupied classroom. Particle size distributions of total airborne PM, bacterial genomes, and fungal genomes were measured under occupied and vacant conditions, and a material balance model was applied to determine the per person emission rates of bacterial and fungal size-fractionated particles attributable to occupancy.

The bioaerosols levels in the school buildings were found to be very high with maximum bacterial concentration of 5,525 CFU/m3 was found in Korean schools (Yang et al., 2009). They observed a significant correlation between CO2 and bacterial concentrations and indicated that low ventilation may be the cause of increased bacteria. Another study conducted in Korea also reported higher concentrations of bacterial and fungal aerosols (Jo and Seo, 2005). In contrast, Lee and Chang (2000) observed lower concentrations of bioaerosols (<1,000 CFU/m3) in Hong Kong schools. Deng et al. (2016) reported the presence of both gram-positive and gram-negative bacteria in the kindergartens of Hong Kong. Gram-positive bacilli were the most dominant genus. Other gram-positive bacteria, including Staphylococcus, Coprococcus, Ruminococcus, Micrococcus, and Corynebacterium, were found in all the samples. Gram-negative bacteria, including Bacteroidetes, Escherichia, Rhizobium, and Enterobacter, also made up a large proportion. The most commonly found fungal species in the classroom are Cladosporium, Penicillium, Aspergillus, and Alternaria. The indoor bioaerosols concentrations in classrooms were found to be higher than outdoors in all the studies.

The indoor air pollutants and their levels in schools in different regions of the world during the last two decades were summarized in Table 2. Among the indoor air pollutants, PM concentrations were found to be very high in many schools. The maximum PM10 concentrations (1,181 μg/m3) were observed in Delhi, India (Goyal and Khare, 2009) and the minimum PM10 (3 μg/m3) levels were observed in Porto, Portugal (Branco et al., 2014). PM concentrations in urban schools of India were much higher than those measured in European countries and elsewhere. Indoor air pollutant levels in school buildings varied over a wide range in different parts of the world depending on site characteristics, climatic conditions, outdoor pollution levels, occupant activities, ventilation type and building practices. Hence, while considering the student exposure to pollutants at school, one need to take into account both the outdoor and the indoor sources. In case of outdoor sources their type, location in terms of the distance from the school as well as their intensity and frequency of emission are important. The various factors that affect the IAQ of school buildings are presented in the subsequent sections.

Table 2. 
Indoor air pollutants and their concentration levels in schools across the world.
Location Site characteristics Pollutants concentrations References
Urban, non-industrial PM10=45.9-74.4 μg/m3 Janssen et al., 1997
Hong Kong Urban, residential, industrial,
rural, natural and mechanical
PM10=21-617 μg/m3; SO2=5-16 μg/m3;
NO=18-115 μg/m3; NO2=31-67 μg/m3;
HCHO=<MDL*-27 μg/m3;
Bioaersols=<1,000 CFU/m3; CO2>1,000 ppm
Lee and Chang, 2000
Athens, Greece Urban, naturally ventilated CO=1.17-3.96 ppm Chaloulakoua and Mavroidis, 2002
California, USA Semi-rural, mechanically ventilated PM2.5=16.3 μg/m3; Carbonyl=38-105 μg/m3 Sawant et al., 2004
Czech Republic
Urban, naturally ventilated PM10=42.3 μg/m3; PM2.5=21.9 μg/m3;
PM1=13.7 μg/m3
Branis et al., 2005
Daegu, Korea Urban, mechanically ventilated Bacteria=269-1,621 CFU/m3;
Fungi=28-616 CFU/m3
Jo and Seo, 2005
La Rochelle,
Urban, traffic, industrial,
residential, rural, seaside,
natural and mechanical
O3=15-41 ppb; NO=1-52 ppb;
NO2=1-27 ppb; PM0.3-0.4=17,026-117,690/L;
Poupard et al., 2005
Munich, Germany Urban residential, naturally
CO2=480-4,172 ppm; PM10=105 μg/m3;
PM2.5=23 μg/m3
Fromme et al., 2007
Michigan, USA Suburban, mechanically
Total VOCs=58 μg/m3;
Bioaerosols=505 CFU/m3; CO2>1,000 ppm
Godwin and Batterman, 2007
Ohio, USA Urban, suburban, rural,
PM2.5=15.56-17.3 μg/m3 John et al., 2007
Montana, USA Urban PM2.5=4.6-54 μg/m3 Ward et al., 2007
Athens, Greece Urban, naturally ventilated PM10=229±182 μg/m3; PM2.5=82±56 μg/m3;
Ultrafine PM=24,000/cm3
Diapouli et al., 2008
Munich, Germany Urban residential, naturally
PM10=118.2 μg/m3; PM2.5=37.4 μg/m3 Fromme et al., 2008
Antwerp, Belgium Urban, naturally ventilated PM2.5=57±10 μg/m3; SO2=<MDL*-3.5 μg/m3;
O3=<MDL*-9.9 μg/m3; NO2=14-159 μg/m3;
BTEX=0.12-10.6 μg/m3
Stranger et al., 2008
Kozani, Greece Suburban, naturally ventilated PM10=107 μg/m3; O3=1-10 ppb; CO=0-1 ppm Triantafyllou et al., 2008
Delhi, India Urban roadside, naturally
PM10=133.5-1,181.1 μg/m3;
PM2.5=54.6-366.1 μg/m3;
PM1=27.8-221.7 μg/m3
Goyal and Khare, 2009
Urban, mechanically ventilated Max ultrafine PM=1.4×105 cm-3 Morawska, 2009
Chiang Mai,
Urban, naturally ventilated PM0.3-0.5=1.6×108 m-3; PM0.5-1.0=1.7×107 m-3;
PM1.0-2.5=1.2×106 m-3; PM2.5-5.0=4.1×105 m-3
Tippayawong, 2009
Korea Urban PM10=8-403 μg/m3; CO=0.1-5.4 ppm;
TVOCs=20-1,501 μg/m3;
HCHO=0.01-0.8 ppm; TBC=97-5,525 CFU/m3;
CO2=268-3,000 ppm
Yang et al., 2009
Suburban, industrial,
residential, traffic, naturally
RPM=188.8±43.9 μg/m3 Gadkari, 2010
Urban, mechanically ventilated PM0.015-0.79=3.19×103 cm-3;
PM2.5=6.7±0.2 μg/m3
Guo et al., 2010
California, USA Urban, residential, traffic,
natural and mechanical
Ultrafine PM=10,800 cm-3 Mullen et al., 2011
Lisbon, Portugal Urban, residential, traffic,
naturally ventilated
PM10=30-146 μg/m3; PM2.5=10 μg/m3;
PM2.5-10=73 μg/m3
Almeida et al., 2011
Porto, Portugal Urban, residential, traffic,
naturally ventilated
PM10=140 μg/m3; PM2.5=95 μg/m3;
PM1=91 μg/m3
Madureira et al., 2012
Munich, Germany Urban, naturally ventilated PM10=117±48 μg/m3 Oeder et al., 2012
Aveiro, Portugal Urban, suburban, naturally
CO2=833-2,540 mg/m3;
NO2=10.63-20.93 μg/m3;
PM10=9.7-108.6 μg/m3; TVOC=145-175 μg/m3
Pegas et al., 2012
Calais, France
Urban, rural, industrial,
naturally ventilated
PM10=72.7-85.3 μg/m3 Tran et al., 2012
Texas, USA Urban, rural, mechanical
Ultrafine PM=0.6×103-29.3×103 cm-3 Zhang and Zhu, 2012
Chennai, India Urban, naturally ventilated PM10=95-149 μg/m3; PM2.5=32-61 μg/m3;
PM1=18-43 μg/m3; CO=0.1-0.11ppm
Chithra and Nagendra, 2012
Cassino, Italy Urban, suburban, naturally
PM=2.0×104-3.5×104 cm-3; CO2=3,000 ppm Buonanno et al., 2013
Gaza strip,
Urban, suburban, naturally
PM10=349.49±196.57 μg/m3;
PM2.5=103.96±84.96 μg/m3
Elbayoumi et al., 2013
Agra, India Urban, residential, roadside,
naturally ventilated
PM10=215.99-324.32 μg/m3;
PM2.5=70.42-106.41 μg/m3;
PM1=40.16-73.96 μg/m3
Habil et al., 2013
Lublin, Poland Urban, naturally ventilated PM10=39-263 μg/m3; PM2.5=19-167 μg/m3;
PM1=18-166 μg/m3; TSP=73-740 μg/m3
Polednik, 2013
Texas, USA Urban, mechanically ventilated PM10=6.5-100 μg/m3; PM2.5=3.4-37 μg/m3;
BC=0-0.96 μg/m3; NO2=1.38-14.13 ppb;
Benzene=0.2-1.67 μg/m3;
Toluene=0.36-17.06 μg/m3;
Ethyl benzene=0.09-2.11 μg/m3;
m,p-xylene=0.12-2.67 μg/m3;
o-xylene=0.08-1.05 μg/m3
Raysoni et al., 2013
Wrocław, Poland Urban, naturally ventilated PM10=12.6-93.1 μg/m3; PM2.5=8.9-86.6 μg/m3;
PM1=4.2-33.4 μg/m3
Zwozdziak et al., 2013
Aveiro, Portugal Urban, naturally ventilated PM10=37-399 μg/m3 Alves et al., 2014
Barcelona, Spain Urban PM2.5=1-192 μg/m3 Amato et al., 2014
Porto, Portugal Urban, naturally and
mechanically ventilated
PM10=3.25-197.25 μg/m3;
PM2.5=3.25-158 μg/m3; PM1=2.75-145 μg/m3;
PMtotal=3.25-605 μg/m3
Branco et al., 2014
Eskişehir, Turkey Urban, suburban Benzene=0.83-0.92 μg/m3;
Toluene=10.63-42.01 μg/m3;
Ethyl benzene=0.32-0.39 μg/m3;
m,p-xylene=0.67-0.74 μg/m3;
o-xylene=0.46-0.51 μg/m3;
NO2=8.42-27.06 μg/m3; O3=16.93-23.76 μg/m3
Demirel et al., 2014
Zajecar, Serbia Urban, naturally ventilated PM10=37-103 μg/m3; PM2.5=26-63 μg/m3;
PAHs=10-198 μg/m3; VOC=39-61 μg/m3;
HCHO=42-88 μg/m3; O3=8-15 μg/m3;
NO2=7-22 μg/m3; CO2=1-1.1 μg/m3
Jovanovic et al., 2014
Attika, Greece Urban, naturally ventilated CO=0-13.9 ppm; CO2=538-5,049 ppm;
VOC=0-39.7 ppm, TPM=41-1,867 μg/m3;
PM10=21-1,618 μg/m3; PM5=11-709 μg/m3;
PM2.5=2-68 μg/m3; PM1=0.82-28 μg/m3;
PM0.5=0.39-19.57 μg/m3; UFP=751-36,641
Dorizas et al., 2015
Porto, Portugal Urban, naturally ventilated PM10=139 μg/m3; PM2.5=94 μg/m3;
VOC=172 μg/m3; HCHO=19.8 μg/m3;
CO=0.48 mg/m3; CO2=1,669 ppm;
Bacteria=3,600 CFU/m3; Fungi=300 CFU/m3
Madureira et al., 2015
Sant Cugat del
Valles, Spain
Urban, naturally and
mechanically ventilated
NO2=5-69 μg/m3; PM2.5=8-95 μg/m3;
UFP=3,233-41,407 cm-3
Rivas et al., 2015
Chennai, India Urban, naturally ventilated PM10=942±248 μg/m3; PM2.5=61±17 μg/m3;
PM1=16±3 μg/m3; CO=0.93±0.43 ppm;
CO2=458±58 ppm
Agarwal and Nagendra, 2016
Australia and
Barcelona, Spain
Urban, naturally ventilated PNC=8.35×103-8.5×103 cm-3 (Brisbane);
PNC=9.29×103-1.37×104 cm-3 (Barcelona)
Mazaheri et al., 2016
Porto and Trofa,
Urban and rural, naturally
UFP=5.7×103-10.4×103 cm-3 Rufo et al., 2016
Urban, mechanically ventilated PM10=5.8±35.6 μg/m3;
PM2.5=5.5±21.8 μg/m3;
Black Carbon=0.49-2.03 μg/m3
van der Zee et al., 2016
*MDL=Minimum Detection Limit


The factors namely ventilation rate, temperature and relative humidity (RH), outdoor air pollution levels and outdoor meteorological conditions affect the IAQ of school building.

3. 1 Comfort Parameters

The comfort parameters that affect IAQ are ventilation rate, temperature and relative humidity. Ventilation is one of the most important factors for maintaining acceptable IAQ in buildings. Ventilation is used to remove unpleasant smells/odours and moisture, introduce outside air, to keep interior building air circulating, and to prevent stagnation of the interior air. Buildings are typically ventilated using three mechanisms: natural ventilation, mechanical ventilation and infiltration. Natural ventilation is the flow of air through open windows, doors, grilles, and other planned building envelope penetrations, and it is driven by natural and/or artificially produced pressure differences. Mechanical (or forced) ventilation is the intentional movement of air into and out of a building using fans, air conditioners and intake and exhaust vents. Infiltration is the flow of outdoor air into a building through cracks and other unintentional openings and through the normal use of exterior doors for entrance and egress (ASHRAE, 2009).

Inadequate ventilation is the major issue in many of the classrooms in developed countries. It is expressed in terms of CO2 concentrations. Although inadequate ventilation is often suspected to be an important condition leading to reported health symptoms, only few studies have reported on ventilation rates in schools (Toyinbo et al., 2016; Dorizas et al., 2015; Elbayoumi et al., 2013; Habil et al., 2013; Mullen et al., 2011; Goyal and Khare, 2009). Daisey et al. (2003) compiled the average ventilation rates and ranges reported in the scientific literature for US and European schools (Casey et al., 1995; Turk et al., 1987; Nielsen et al., 1984). In poorly ventilated classrooms, students are likely to be less attentive on instructions given by teachers. Low ventilation rates in classrooms significantly reduce pupils’ attention and vigilance, and negatively affect memory and concentration (Bakó-Biró et al., 2012). Inadequate ventilation was mostly observed in air-conditioned buildings than naturally ventilated buildings.

According to ASHRAE “Thermal comfort is that condition of the mind that expresses satisfaction with the thermal environment” (ASHRAE, 1992). The ASHRAE’s standard-55 (ASHRAE, 1992) recommends indoor temperatures in the winter and summer are between (20 and 23.8°C) and (22.7 and 26.1°C), respectively with a relative humidity level between 30 and 60%. The temperature and humidity above or below this range in the building may affect the comfort and productivity of the occupants, as well as the emission of chemicals from building materials. Elevated relative humidity can promote the growth of mold, bacteria, and dust mites, which can aggravate allergies and asthma. Many previous IAQ studies in school buildings reported that the temperature and humidity were not in the acceptable limits (Almeida and de Freitas, 2014; Montazami et al., 2012; Twardella et al., 2012; Yang et al., 2009; Geelen et al., 2008; Santamouris et al., 2008; Theodosiou and Ordoumpozanis, 2008; Grimsrud et al., 2006; Jo and Seo, 2005; Kim et al., 2005; Lee and Chang, 2000).

3. 2 Meteorological Parameters

Outdoor meteorological parameters are the main factor, which affects the IAQ of naturally ventilated buildings. The substantial difference in the climatic environment between indoors and outdoors could bring vastly different pollutant levels and dispersion characteristics. Recently, U.S. EPA (2011) reported that local climate change also has the potential to affect the IAQ. Climate change increases the frequency of heat waves and hot weather in many urban environments. As a result, building envelopes can become hotter during heat waves, adding to thermal stress and adverse health consequences in vulnerable populations (White-Newsome et al., 2012). It is now appreciated that climate change will impact ambient air pollution through increased emission rates and faster chemical reaction rates associated with higher temperatures. PM and O3 levels are projected to increase in the ambient environment, which can penetrate indoors and subjected further reactions (Spengler, 2012; IOM, 2011).

The important meteorological parameters that affect IAQ of naturally ventilated building are wind speed and direction, temperature, relative humidity, precipitation, atmospheric pressure and solar radiation. In the past, few studies have been carried out to examine the relationship between air pollution and meteorological processes in different indoor environments. It was found that the correlation between indoor and outdoor pollutant concentrations varied over a wide range in different areas with different emission rate and meteorological characteristics. Chan (2002) studied the indoor-outdoor relationships of the PM and NO2 under different ambient meteorological conditions. It is found that temperature, humidity and solar radiation played a vital role in the variation of the I/O ratio. On the other hand, both pressure and wind speed seems to have relatively little effect on the I/O ratio. Similarly, Gupta and Cheong (2007) reported that the temperature (R2=0.543) plays the most significant role in affecting the I/O ratio of PM followed by the relative humidity (R2=0.539) and wind speed (R2=0.379). It was observed that with an increase in ambient temperature enhances more particle migration to indoors. This may be attributed to the temperature gradient that is established between the indoor and outdoor locations, which favours the motion of the particles. Tippayawonget al. (2009) observed a significant negative correlation (R2=0.195-0.679) between temperatures and indoor PM2.5 concentrations during daytime and positive correlation (R2=0.187-0.675) at night. Among all the meteorological variables, wind speed has been the most closely analyzed since it influences the dispersion and dilution of pollutants. Cheng and Li (2010) and Chithra and Nagendra (2014) reported that low wind speeds and low mixing-layer heights lead to high indoor PM10 and PM2.5 levels. Massey et al. (2012) observed that I/O PM ratios decrease with increasing temperature and wind speed, whereas a good relationship was not found between PM ratios and humidity. Riain et al. (2003) found that wind direction has considerable impact on fine PM and CO concentration levels in naturally ventilated buildings. For a constant wind speed, the I/O ratios of CO and PM varied by 50-60% and 20-30%, respectively for varied wind direction.

The indoor air pollutant concentrations at school also exhibit seasonal variations. Fromme et al. (2007) evaluated IAQ in 64 schools in the city of Munich and surrounding area and reported that the median indoor CO2 concentration in a classroom was 1,603 ppm in winter and 405 ppm in summer. A median PM2.5=19.8 μg/m3 and PM10=91.5 μg/m3 were observed during winter period. In summer, a reduced PM concentration were reported (median PM2.5=12.7 μg/m3 and median PM10 =64.9 μg/m3). Few other researchers were also found that the pollutant concentrations in classrooms were higher during winter when compared to summer (Rivas et al., 2015; Chithra and Nagendra, 2014; Elbayoumi et al., 2014; Goyal and Khare, 2009; Chaloulakou and Mavroidis, 2002). However, Yang et al. (2009) observed that the indoor bacterial concentrations in classrooms were significantly higher during summer and autumn than during winter. This means that students’ exposure is subjected to these variations according to the season of the year. Therefore, studies covering longer periods and a broader range of rooms are required in order to compare the exposure-effect of indoor and outdoor associations between the seasons.

3. 3 Outdoor Air Pollution Levels

Many studies reported that outdoor air pollution is having a significant effect of IAQ of naturally ventilated buildings (Chithra and Nagendra, 2014; Pegas et al., 2012; Tran et al., 2012; Lawson et al., 2011; Lim et al., 2011; Riain et al., 2003; Chao and Wong, 2002; Koponen et al., 2001; Kingham et al., 2000). Especially, in buildings close to industrial areas or roadways, outdoor pollutants can migrate to the indoor environment through open doors and windows. Therefore, understanding the relationship between indoor and outdoor pollutant concentrations is quite important. The I/O ratio directly represents the relationship between indoor and outdoor pollutant concentrations, which is very easy to understand and widely used. The measurement method for I/O ratio is relatively simple. The most common method is installing two monitors inside and outside the building, and then the I/O ratio can be obtained. I/O ratio >1 implies the major sources of pollutants are indoor and I/O <1 means the predominance of outdoor sources.

In school building, the IAQ is mostly discussed in terms of I/O ratios. The I/O ratios vary considerably due to the difference in indoor emission rates, cracks in building envelopes, and the air exchange rates. Chaloulakou and Mavroidis (2002) carried out a study to investigate the indoor and outdoor CO concentration at a public school building in Athens, Greece. The mean daily I/O CO concentration ratios ranged between 0.49 and 0.79 and 0.53 and 0.89 in the summer and winter periods, respectively. Triantafyllou et al. (2008) reported that the average indoor PM10 values in the school building were found to be lower than the respective outdoor values when building was unoccupied and I/O ratio ranged between 0.2 and 1.6. When it was occupied, this ratio ranged between 0.7 and 11.4. Diapouli et al. (2008) also observed that variation of mean I/O ratios depending on the indoor activities and the outdoor concentration levels. The I/O ratios for PM10 and PM2.5 were ranged between 0.54 and 2.46 and 0.67 and 2.77, respectively. The corresponding ratio for ultrafine particles was smaller than 1, because vehicular traffic was presumed to be the main source. Similar observations were made by Goyal and Khare (2009) and Chithra and Nagendra (2012).


Better IAQ in schools is important to provide a safe, healthy, productive, and comfortable environment for students, teachers, and staffs. It is very important for children because early childhood is also a critical period for the continued development and maturation of several biological systems such as the brain, lung, and immune system and air toxics can impair lung function and neurodevelopment, or exacerbate existing conditions, such as asthma. Since children’s organs are in developing stage they breathe more air relative to their body size than adults (WHO, 2006a; Mendell and Health, 2005; Faustman et al., 2000). They also spent a significant part of their school hours doing physical activity, especially during recess and physical education, therefore, their air pollutant intake is generally higher during these times.

The assessment of the health effects from air pollution exposure at school is faced with a number of challenges: seasonal variability, pollutant interactions, heterogeneity, effects of daily variations in physical activity on air pollutant inhalation rates, and the contribution of non-school based exposures (Mejía et al., 2011). Few studies have assessed relationships of various health outcomes among students with indoor environmental factors in schools (Table 3). Most studies considered respiratory health such as asthma, current asthma, wheezing, or allergies as assessed by standardized self-administered questionnaires. Fewer studies considered lung function, nasal patency, or acoustic rhinometry (Altuğ et al., 2013; Simoni et al., 2010; Shendell et al., 2004). Significant association between formaldehyde concentrations and health outcomes were observed by Zhao et al. (2008) and Annesi-Maesano et al. (2012). Formaldehyde has been related to the nocturnal attack of breathlessness and cumulative asthma overall in nonallergic children (Zhao et al., 2008) and related to an increased risk of rhinitis (Annesi-Maesano et al., 2012). Mi et al. (2006) reported that 10 μg/m3 increase in the indoor concentration of NO2 was associated with current asthma, asthma attacks, and asthma medication. Zhao et al. (2008) reported an increased risk of 1.27 for the nocturnal attack of breathlessness for each rise of 100 μg/m3 of SO2 concentration. Protective effects of O3 on daytime breathlessness were recorded inside and outside schools by Mi et al. (2006), while Zhao et al. (2008) found that O3 was linked to an increase in nocturnal attacks of breathlessness.

Table 3. 
Children exposures to environmental pollutants in schools and associated health symptoms.
IAQ parameters Health symptoms References
CO2, air exchange rates,
particle counts
Nasal congestion, sore throat, headache Kinshella et al., 2001
Bioaerosols Asthma, allergic rhinitis, atopic eczema Meklin et al., 2002
VOCs, bioaerosols Respiratory irritation, asthmatic symptoms, common
viral respiratory infection
Putus et al., 2004
CO2, allergens Wheeze, asthma, respiratory symptoms Kim et al., 2005
CO2, NO2, O3 Asthma, wheeze, breathlessness Mi et al., 2006
SO2, NO2, O3, HCHO Asthma, wheezing, breathlessness Zhao et al., 2008
CO2, PM10 Dry cough, rhinitis, nasal patency Simoni et al., 2010
PM Rhinitis, asthma Canha et al., 2011
PM10, PM2.5, PM1 Allergies, dry flaking skin, dizziness Habil and Taneja, 2011
PM2.5, NO2, acrolein, HCHO,
Rhinoconjunctivitis, Asthma Annesi-Maesano et al., 2012
SO2, NO2, O3 Impaired lung function Altuğ et al., 2013
CO2, Temperature Fatigue, stuffy nose, headache, wheezing, cough with
wheezing, fever
Turunen et al., 2014
CO2, PM10, PM2.5 Difficulties in focusing, heavy headed and dizziness,
feeling thirsty, feeling uncomfortable, heavy sweating,
muscle pain
Elbayoumi et al., 2015
CO2, Temperature,
Relative humidity, Bacteria
Respiratory symptoms, Gastrointestinal symptoms Haverinen-Shaughnessy et al., 2015

The presence bioaerosols were linked to adverse health outcomes such as respiratory irritation, asthmatic symptoms, and increased occurrence of common viral respiratory infections in school children (Putus et al., 2004; Meklin et al., 2002). Some studies of health symptoms and pollutant exposures in classrooms have used surrogates of exposure (e.g. presence of molds on walls) (Simons et al., 2010). Even though the exposure of PM concentration in school building was very high, only few studies attempted it to relate with children’s health. It was well documented that the exposure to PM has been linked to adverse health effects, including acute and chronic respiratory disorders, lung cancer, morbidity and mortality in children (Maté et al., 2010; Wallenborn et al., 2009; Neuberger et al., 2004; WHO, 2003; Pope et al., 2002; Pearce and Crowards, 1996). Canha et al. (2011) reported the presence of rhinitis and asthma in school children exposed to higher PM levels. Additionally, Annesi-Maesano et al. (2012) observed an increased prevalence of past year asthma was found in the classrooms with high levels of PM2.5 in France.

There are concerns that health problems caused by poor IAQ may impair performance and reduce attendance of students. Some studies incorporated children’s performance and absenteeism because of exposure to poor air quality in schools (Simons et al., 2010; Shendell et al., 2004). Shendell et al. (2004) explored student attendance in relation to dCO2 (the difference between simultaneously measured indoor and outdoor CO2 level) in 434 classrooms in the states of Washington and Idaho, USA. A 1,000 ppm increase in dCO2 was associated with a 0.5-0.9% decrease in annual average attendance after controlling for many other factors known or suspected to be associated with absence. Mendell and Heath (2005) reviewed the existing evidence for direct associations between indoor environmental quality and performance or attendance of school children. Persuasive evidence links higher indoor concentrations of NO2 to reduced school attendance, and suggestive evidence links low ventilation rates to reduced performance. These evidences suggest that poor IAQ in schools is adversely affecting the performance and attendance of students, primarily through health effects from indoor pollutants. Most of the scientific literature providing evidence for the health impacts of IAP comes from studies conducted in developed country settings within North America and Western Europe, which was used for exposure and risk assessment. However, the differences between developed and developing countries in exposure concentrations, the nature of pollutants, baseline health, and determinants of susceptibility add uncertainties while extrapolating exposure-response relationships across countries.


The relative contributions from indoor and outdoor sources are needed to evaluate the adequacy and cost effectiveness of control strategies for mitigating the IAQ issues. Resource allocation to control air pollution depend on adequate information about important emission sources (i.e. source identification), chemical and physical properties of emissions (i.e. emissions characterization), the effects of important source categories on air quality (i.e. source apportionment), as well as the health effects resulting from exposures. While the major indoor sources have been identified, comparatively little is known about the chemical nature of associated airborne emissions, especially particle-phase and vapor-phase organic compounds. Furthermore, the relative impact of indoor and outdoor emissions on exposures has not been addressed in a systematic and comprehensive manner (Abt et al., 2000; Sexton and Hayward, 1987). Source apportionment of indoor air pollution has its challenge because indoor air pollution is controlled by both indoor and outdoor sources, ventilation, outdoor meteorology and long-range transport pollutants (Uhde and Salthammer, 2007).

Passive sampling is more suitable for in-situ measurements of emissions. The estimation of the emission rate of organic compounds released from various types of indoor materials can be performed using the flux sampler. The formaldehyde emission rates from building and furniture materials in 24 student rooms were measured using a passive sampling method by Blondel and Plaisance (2011). Data analysis revealed that the emissions released from furniture and building materials are the main contributions to the indoor formaldehyde concentrations with 45 and 43% on average. Similarly, Poulhet et al. (2014) investigated formaldehyde sources in French schools using a passive flux sampler. More than 29 sources of formaldehyde were characterized in each investigated classroom, with higher emissions from building materials compared to furnishing materials.

A wide variety source oriented and receptor oriented models were applied to outdoor air, to apportion the sources of PM and VOCs. Among this, receptor-based apportionment method is most commonly used for the source apportionment purpose. The fundamental principle of receptor modelling is the mass and species conservation in the atmosphere. An overview of the wide range of statistical models and modelling approaches that is currently available in the literature. One of the main differences between the models is the degree of knowledge required about the pollution sources prior to the application of receptor models. The two main receptor models widely used in source apportionment are chemical mass balance (CMB) and multivariate models (Viana et al., 2008).

Relatively few attempts were made to use receptor-oriented methods like Positive Matrix Factorization (PMF) (Amato et al., 2014; Minguillón et al., 2012; Larson et al., 2004), Cluster Analysis (CA) (Tran et al., 2012), Factor analysis (Krugly et al., 2014), Principal Component Analysis (PCA) (Madureira et al., 2016; Guo, 2011; Lim et al., 2011) and CMB (Pervez et al., 2012; Arhami et al., 2010) to apportion the sources of indoor air pollutants. Most of the source apportionment studies have reported on PM concentrations in residential buildings. Sources and properties of indoor aerosols exhibit large variability among different microenvironments. The composition and toxicity of indoor particles are very complex, as it is a mixture of particles emitted indoors, ambient particles that have infiltrated indoors, and particles formed through the reactions of gas phase precursors. The major sources identified in these studies were outdoor traffic emissions and soil dust for PM, while the VOCs were mainly originated from building materials and household products. John et al. (2007) conducted a study at elementary schools in Ohio indicated that the primary sources at the study region were industrial, fossil fuel combustion and geological sources. A study conducted in French classrooms reported that resuspension dust, traffic and marine aerosols were the major sources of PM in classrooms (Tran et al., 2012). Another source apportionment study using PMF model was conducted by Amato et al. (2014) in 39 primary schools of Barcelona. Results indicated that on average 47% of indoor PM2.5 measured concentrations was found to be generated indoors due to continuous resuspension of soil particles (13%) and a mixed source (34%) comprising organic (skin flakes, clothes fibers, possible condensation of VOCs) and Ca-rich particles (from chalk and building deterioration). Madureira et al. (2016) reported that the influence of activities or building features as major sources of indoor CO2, PM10 and VOCs levels in schools of Portugal. A critical review of receptor modelling for particulate matter in India suggest CMB model for source apportionment for PM rather than other multivariate receptor models (Pant and Harrison, 2012). But its application on source contribution of indoor PM is very limited. Gadkari and Pervez (2008) analysed the elemental composition of indoor PM among school communities in central India. Source apportionment of personal exposure shows that industrial emissions and road traffic dust are the major sources of personal exposure of fine particulates.


As the importance of the human exposure to IAP are increasingly recognized, national and international organizations proposed IAQ standards and guidelines for improving air quality in indoor environments. IAQ standards suggested by Occupational Safety & Health Administration (OSHA), ASHRAE, NIOSH and WHO are mostly used in many countries for assessing the IAQ. The American Conference of Industrial Hygienists (ACGIH) TLVs (Threshold Limit Values) are often applied in industrial environments. Industrial workers are generally exposed to larger concentrations of contaminants, and worker exposure is controlled by using personal protective equipment and other protective methods. In non-industrial settings such as offices, homes and schools, occupants are more commonly exposed to low levels of many contaminants. However, only few such standards or guidelines apply to nonindustrial indoor settings. For example, the ASHRAE has established guidelines for ventilation rates (ASHRAE, 1999) and thermal comfort (ASHRAE, 1992) for a variety of indoor settings. ASHRAE recommends a minimum ventilation rate of 8 L/s-person (15 cfm/person) for classrooms. For typical occupant density of 33 per 90 m2 (1,000 ft2) and a ceiling height of 3 m (10 ft), the current ASHRAE standard would require 3 air changes per hour (ACH) for a classroom (Daisey et al., 2003). Table 4 summarizes the standards and guidelines international agencies for pollutants commonly found indoors.

Table 4. 
Indoor air quality standards and guidelines.
CO2 - 5,000 ppm (8 h)
30,000 ppm (15 min)
5,000 ppm (8 h)
30,000 ppm (15 min)
5,000 ppm (8 h)
30,000 ppm (15 min)
CO 9 ppm (8 h)
35 ppm (1 h)
35 ppm (8 h) 35 ppm (8 h) 25 ppm (8 h) 90 (15 min)
50 (30 min)
25 (1 h)
10 (8 h)
NO2 100 ppb (1 h)
53 ppb (Annual)
1 ppm (15 min) 1 ppm (15 min) 3 ppm (8 h)
5 ppm (1 min)
200 μg/m3 (1 h)
40 μg/m3 (Annual)
SO2 75 ppb (1 h, Primary)
0.5 ppm
(3 h, Secondary)
2 ppm (8 h)
5 ppm (15 min)
2 ppm (8 h)
5 ppm (15 min)
2 ppm (8 h)
5 ppm (15 min)
500 μg/m3 (10 min)
20 μg/m3 (24 h)
O3 0.075 ppm (8 h) 0.1 ppm (8 h)
0.3 ppm (15 min)
0.1 ppm (8 h) - 100 μg/m3 (8 h)
PM2.5 35 μg/m3 (24 h)
12 μg/m3
(Annual, Primary)
15 μg/m3
(Annual, Secondary)
5 mg/m3 (8 h,
respirable fraction)
- 3 mg/m3 (8 h) 25 μg/m3 (24 h)
10 μg/m3 (Annual)
PM10 150 μg/m3 (24 h) - - 10 mg/m3 (8 h) 50 μg/m3 (24 h)
20 μg/m3 (Annual)
HCHO - 0.75 ppm (8 h)
2 ppm (15 min)
0.016 ppm (8 h)
0.1 ppm (15 min)
0.3 ppm (8 h) -
Lead 0.15 μg/m3 (3 months) 0.05 mg/m3 (8 h) 0.1 mg/m3 (10 h) 0.05 mg/m3 (8 h) 0.5 μg/m3 (Annual)
Bioaerosol - - 1,000 CFU/m3
(total bioaerosol)
1,000 CFU/m3
(total bioaerosol)
500 CFU/m3
(total bacteria)

The NAAQS were developed by the U.S. EPA for outdoor air quality, but they are also applicable for indoor environment. The WHO air Quality Guidelines (WHO, 2006b) for PM, O3, NO2, and SO2 specified that they can be applied in all non-occupational environments, including indoors in households, schools, vehicles, etc. They are intended for application to both indoor and outdoor exposures. But, these are guidelines rather than an enforceable standard. There are also standards and guidelines for other organic and inorganic compound present in the indoor air. The WHO has also provided health-based guidelines for 55 airborne inorganic and organic compounds for carcinogenic and non-carcinogenic health endpoints. ACGIH has published TLVs for more than 700 chemical substances and physical agents. Permissible exposure limits (PELs) are set by OSHA to protect workers against the health effects of exposure to 500 hazardous substances (Charles et al., 2005). In some countries, including Australia (Worksafe Australia, 2013), Canada (Health Canada, 1989), China (AQSIQ, 2002), Finland (FiSIAQ, 2001), Germany (Federal Republic of Germany, 2000), Hong Kong (HKEPD, 1999), Japan (MHLW, 2009), Malaysia (DOSH, 2010) and Singapore (Institute of Environmental Epidemiology, 1996) air quality guidelines have been developed or suggested also for indoor air.


The indoor air pollutants include wide variety of compounds with varying concentrations and are emitted from several sources. Several instruments and techniques are available for measuring air pollutants in the ambient environment. But, the physical size, noise, airflow rates, power consumption, difficulty in installation etc. of these instruments restricts their applicability in the indoor environment (U.S. EPA, 1990). Therefore, it is important to know the sampling and measurement techniques that can be used in indoor environments. Many governmental agencies and research organizations have developed indoor air monitoring protocols for industrial workplaces. However, the instrumentation requirements for non-industrial microenvironments (residential, commercial and institutional buildings) differ from those of ambient or industrial applications. At present, developed countries have set up guidelines for IAQ Assessment (CPCB, 2014; ASTM, 2012; HKEPD, 2003; U.S. EPA, 2003, 1990; Macher, 1999; U.S. EPA and NIOSH, 1991), which may not be suitable for developing nations, because of the difference in climatic and socioeconomic conditions and building design and construction practices.

There are many programs exists in developed countries to improve IAQ in schools. The U.S. EPA has developed useful documents to assist building operators and managers. These documents provide guidance on how to prevent IAQ problems and how to establish an organizational structure to manage IAQ events (U.S. EPA and NIOSH, 1991). U.S. EPA has developed an IAQ Tools for Schools Action Kit, which provides best practices, industry guidelines, sample policies and a sample IAQ management plan to improve IAQ in schools at little or no cost (U.S. EPA, 2013). In the US, 42% of schools were having an IAQ management program and each year new schools are added to this program. Nearly half of these schools use the U.S. EPA’s IAQ Tools for Schools program (Moglia et al., 2006). The SINPHONIE (Schools Indoor Pollution and Health Observatory Network in Europe) project is a complex research project funded by the European Union (EU), intended to improve air quality in schools and kindergartens, to reduce respiratory disease due to outdoor and indoor air pollution in children and teachers, and to define policy recommendations on remedial measures in the school environment. Twenty-three countries from all of Europe are involved in this project (SINPHONIE, 2013). In other countries, the state of knowledge on IAQ is schools are very limited. There are no programmes or guidelines currently exist for IAQ assessment and monitoring in different indoor environments (i.e. commercial, institutional, residential and sensitive buildings) in most of developing and undeveloped countries.


Over the last years, public attention on IAQ and indoor comfort has been increased. One of the main reasons is the fact that people usually spend most of their time in indoor environments, such as home, workplace, in transit, educational and recreational facilities. In developed countries, many studies were conducted during the past decade with the aim of understanding IAQ of the school environment. Many researchers have widely investigated the composition of indoor pollutants, sources, physical and chemical characteristics, and effects on human health. The composition of indoor pollutants is quite complex and their concentrations are greatly different. It was reported that particulate matter plays a major role in affecting the IAQ of the school building. If the ambient PM concentrations are already high, that could further deteriorate the IAQ of the building. This is particularly true for developing countries like India and China where the world’s highest levels of PM have been reported.

In many countries, there are no programs in place at the national or state level to improve the indoor environmental quality in schools. Also, there is no standard protocol available for IAQ assessment for developing countries. Considering the public concern and limited knowledge in IAQ in schools, there is a need to determine the extent of IAQ problems in schools located in urban areas. Scientific knowledge on sources of indoor air pollutants, quantification of emissions, temporal and spatial dispersion of pollutants, toxicological properties of the pollutants, chemical and morphological characteristics and associated health risk among children in the school buildings are essential to evaluate the adequacy and cost effectiveness of control strategies for mitigating the IAQ issues. Hence, there is a need for high quality research to investigate the characteristics of IAQ and associated health risk in school buildings. The knowledge established as part of this paper would be helpful for designers, engineers, facilities maintenance managers and researchers who endeavour to undertake research in this area.

1. Abt, E., Suh, H.H., Catalano, P., Koutrakis, P., (2000), Relative contribution of outdoor and indoor particle sources to indoor concentrations, Environmental Science & Technology, 34(17), p3579-3587.
2. ACGIH, (1999), Bioaerosols: Assessment and Control, 1st Ed., Cincinnati, OH: American Conference of Governmental Industrial Hygienists.
3. Agarwal, N., Nagendra, S.S., (2016), Modelling of particulate matters distribution inside the multilevel urban classrooms in tropical climate for exposure assessment, Building and Environment, 102, p73-82.
4. Almeida, S.M., Canha, N., Silva, A., Freitas, M.D.C., Pegas, P., Alves, C., Evtyugina, M., Pio, C.A., (2011), Children exposure to atmospheric particles in indoor of Lisbon primary schools, Atmospheric Environment, 45(40), p7594-7599.
5. Almeida, R.M., de Freitas, V.P., (2014), Indoor environmental quality of classrooms in Southern European climate, Energy and Buildings, 81, p127-140.
6. Altuğ, H., Gaga, E.O., Döğeroğlu, T., Özden, Ö., Örnektekin, S., Brunekreef, B., Meliefste, K., Hoek, G., Van Doorn, W., (2013), Effects of air pollution on lung function and symptoms of asthma, rhinitis and eczema in primary school children, Environmental Science and Pollution Research, 20(9), p6455-6467.
7. Alves, C.A., Urban, R.C., Pegas, P.N., Nunes, T., (2014), Indoor/Outdoor relationships between PM10 and associated organic compounds in a primary school, Aerosol and Air Quality Research, 14, p86-98.
8. Alves, C., Duarte, M., Ferreira, M., Alves, A., Almeida, A., Cunha, Â., (2016), Air quality in a school with dampness and mould problems, Air Quality, Atmosphere & Health, 9(2), p107-115.
9. Amato, F., Rivas, I., Viana, M., Moreno, T., Bouso, L., Reche, C., Àlvarez-Pedrerol, M., Alastuey, A., Sunyer, J., Querol, X., (2014), Sources of indoor and outdoor PM2.5 concentrations in primary schools, Science of the Total Environment, 490, p757-765.
10. AnnesiM-aesano, I., Hulin, M., Lavaud, F., Raherison, C., Kopferschmitt, C., de Blay, F., Charpin, D.A., Denis, C., (2012), Poor air quality in classrooms related to asthma and rhinitis in primary schoolchildren of the French 6 Cities Study, Thorax, 67(8), p682-688.
11. AQSIQ, (2002), Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China. Ministry of Environmental Protection and Ministry of Health.
12. Arhami, M., Minguillón, M.C., Polidori, A., Schauer, J.J., Delfino, R.J., Sioutas, C., (2010), Organic compound characterization and source apportionment of indoor and outdoor quasi-ultrafine particulate matter in retire - ment homes of the Los Angeles Basin, Indoor Air, 20(1), p17-30.
13. ASHRAE, (1992), Standard 551-992, Thermal environmental conditions for human occupancy, American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Atlanta, GA.
14. ASHRAE, (1999), Standard 62-1999, Ventilation for Acceptable Indoor Air Quality, American Society for Heating, Refrigerating and Air Conditioning Engineers, Atlanta, GA.
15. ASHRAE, (2009), ASHRAE Fundamentals Handbook, Ventilation, Air Conditioning, and Refrigeration Systems Inc, American Society of Heating, Refrigerating and Air-Conditioning Engineers, Atlanta, GA.
16. ASTM, (2012), Standard D5791-95, Standard Guide for Using Probability Sampling Methods in Studies of Indoor Air Quality in Buildings, ASTM International.
17. BakóB-iró, Z., Clements-Croome, D.J., Kochhar, N., Awbi, H.B., Williams, M.J., (2012), Ventilation rates in schools and pupils' performance, Building and Environment, 48, p215-223.
18. Blondel, A., Plaisance, H., (2011), Screening of formaldehyde indoor sources and quantification of their emission using a passive sampler, Building and Environment, 46(6), p1284-1291.
19. Branco, P.T.B.S., Alvim-Ferraz, M.C.M., Martins, F.G., Sousa, S.I.V., (2014), Indoor air quality in urban nurseries at Porto city: Particulate matter assessment, Atmospheric Environment, 84, p133-143.
20. Buonanno, G., Fuoco, F.C., Morawska, L., Stabile, L., (2013), Airborne particle concentrations at schools measured at different spatial scales, Atmospheric Environment, 67, p38-45.
21. Canha, N., Almeida, M., Freitas, M.D.C., Almeida, S.M., Wolterbeek, H.T., (2011), Seasonal variation of total particulate matter and children respiratory diseases at Lisbon primary schools using passive methods, Procedia Environmental Sciences, 4, p170-183.
22. Canha, N., Almeida, S.M., do Carmo Freitas, M., Trancoso, M., Sousa, A., Mouro, F., Wolterbeek, H.T., (2014), Particulate matter analysis in indoor environments of urban and rural primary schools using passive sampling methodology, Atmospheric Environment, 83, p21-34.
23. Casey, M.E., Braganza, E.B., Shaughnessey, R.J., Turk, B.H., (1995), Ventilation improvements in two elementary school classrooms, In Proceedings, Engineering Solutions to Indoor Air Quality Problems Symposium, Pittsburgh, PA.
24. Chaloulakou, A., Mavroidis, I., (2002), Comparison of indoor and outdoor concentrations of CO at a public school. Evaluation of an indoor air quality model, Atmospheric Environment, 36(11), p1769-1781.
25. Chan, A.T., (2002), Indoor-outdoor relationships of partic - ulate matter and nitrogen oxides under different outdoor meteorological conditions, Atmospheric Environment, 36(9), p1543-1551.
26. Chao, C.Y., Wong, K.K., (2002), Residential indoor PM10 and PM2.5 in Hong Kong and the elemental composition, Atmospheric Environment, 36(2), p265-277.
27. Charles, K.E., Magee, R.J., Won, D., Lusztyk, E., (2005), Indoor air quality guidelines and standards, Institute for Research in Construction, National Research Council Canada.
28. Cheng, Y.H., Li, Y.S., (2010), Influences of traffic emissions and meteorological conditions on ambient PM10 and PM2.5 levels at a highway toll station, Aerosol and Air Quality Research, 10, p456-462.
29. Chithra, V.S., Nagendra, S.M.S., (2012), Indoor air quality investigations in a naturally ventilated school building located close to an urban roadway in Chennai, India, Building and Environment, 54, p159-167.
30. Chithra, V.S., Nagendra, S.M.S., (2013), Chemical and morphological characteristics of indoor and outdoor particulate matter in an urban environment, Atmospheric Environment, 77, p579-587.
31. Chithra, V.S., Nagendra, S.S., (2014), Impact of outdoor meteorology on indoor PM10, PM2.5 and PM1 concentrations in a naturally ventilated classroom, Urban Climate, 10, p77-91.
32. CPCB, (2014), accessed on 10th, March 2016.
33. Daisey, J.M., Angell, W.J., Apte, M.G., (2003), Indoor air quality, ventilation and health symptoms in schools: an analysis of existing information, Indoor Air, 13(1), p53-64.
34. Demirel, G., Özden, Ö., Döğeroğlu, T., Gaga, E.O., (2014), Personal exposure of primary school children to BTEX, NO2 and ozone in Eskişehir, Turkey: Relationship with indoor/outdoor concentrations and risk assessment, Science of The Total Environment, 473, p537-548.
35. Deng, W., Chai, Y., Lin, H., So, W.W., Ho, K.W.K., Tsui, A.K.Y., Wong, R.K.S., (2016), Distribution of bacteria in inhalable particles and its implications for health risks in kindergarten children in Hong Kong, Atmospheric Environment, 128, p268-275.
36. Diapouli, E., Chaloulakou, A., Mihalopoulos, N., Spyrellis, N., (2008), Indoor and outdoor PM mass and number concentrations at schools in the Athens area, Environmental Monitoring and Assessment, 136(1-3), p13-20.
37. Dorizas, P.V., Assimakopoulos, M.N., Helmis, C., Santamouris, M., (2015), An integrated evaluation study of the ventilation rate, the exposure and the indoor air quality in naturally ventilated classrooms in the Mediterranean region during spring, Science of the Total Environment, 502, p557-570.
38. DOSH (Department of Occupational Safety and Health), (2010), Industry Code of Practice on Indoor Air Quality, Department of Occupational Safety and Health, Ministry of Human Resources, Malaysia.
39. Elbayoumi, M., Ramli, N.A., Md Yusof, N.F.F., Al Madhoun, W., (2013), Spatial and seasonal variation of particulate matter (PM10 and PM2.5) in Middle Eastern classrooms, Atmospheric Environment, 80, p389-397.
40. Elbayoumi, M., Ramli, N.A., Yusof, N.F.F.M., Yahaya, A.S.B., Al Madhoun, W., UlS-aufie, A.Z., (2014), Multivariate methods for indoor PM10 and PM2.5 modelling in naturally ventilated schools buildings, Atmospheric Environment, 94, p11-21.
41. Elbayoumi, M., Ramli, N.A., Yusof, N.F.F.M., Madhoun, W.A., (2015), Seasonal variation in schools' indoor air environments and health symptoms among students in an eastern Mediterranean climate, Human and Ecological Risk Assessment: An International Journal, 21(1), p184-204.
42. El-Sharkawy, M.F.M., (2014), Study the indoor air quality level inside governmental elementary schools of Dammam City in Saudi Arabia, International Journal of Environmental Health Engineering, 3(1), p22.
43. Faustman, E.M., Silbernagel, S.M., Fenske, R.A., Burbacher, T.M., Ponce, R.A., (2000), Mechanisms underlying Children's susceptibility to environmental toxicants, Environmental Health Perspectives, 108(Suppl 1), p13-21.
44. Federal Republic of Germany, (2000), Maximum Concentrations at the Workplace and Biological Tolerance Values for Working Materials, Commission for the Investigation of Health Hazards of Chemical Compounds in the Work Area, Germany.
45. Fromme, H., Diemer, J., Dietrich, S., Cyrys, J., Heinrich, J., Lang, W., Kiranoglu, M., Twardella, D., (2008), Chemical and morphological properties of particulate matter (PM10, PM2.5) in school classrooms and outdoor air, Atmospheric Environment, 42(27), p6597-6605.
46. Fromme, H., Twardella, D., Dietrich, S., Heitmann, D., Schierl, R., Liebl, B., Rüden, H., (2007), Particulate matter in the indoor air of classrooms-exploratory results from Munich and surrounding area, Atmospheric Environment, 41(4), p854-866.
47. Gadkari, N.M., (2010), Study of personal-indoor -ambient fine particulate matters among school communities in mixed urban-industrial environment in India, Environ - mental Monitoring and Assessment, 165(1-4), p365-375.
48. Gadkari, N., Pervez, S., (2008), Source apportionment of personal exposure of fine particulates among school communities in India, Environmental Monitoring and Assessment, 142(1-3), p227-241.
49. Gaidajis, G., Angelakoglou, K., (2009), Indoor air quality in university classrooms and relative environment in terms of mass concentrations of particulate matter, Journal of Environmental Science and Health Part A, 44(12), p1227-1232.
50. Geelen, L.M., Huijbregts, M.A., Ragas, A.M., Bretveld, R.W., Jans, H.W., Van Doorn, W.J., Evertz, S.J.C.J., Van Der Zijden, A., (2008), Comparing the effectiveness of interventions to improve ventilation behavior in primary schools, Indoor Air, 18(5), p416-424.
51. Godwin, C., Batterman, S., (2007), Indoor air quality in Michigan schools, Indoor Air, 17(2), p109-121.
52. Goyal, R., Khare, M., (2009), Indooro-utdoor concentrations of RSPM in classroom of a naturally ventilated school building near an urban traffic roadway, Atmospheric Environment, 43(38), p6026-6038.
53. Grimsrud, D., Bridges, B., Schulte, R., (2006), Continuous measurements of air quality parameters in schools, Building Research & Information, 34(5), p447-458.
54. Guo, H., (2011), Source apportionment of volatile organic compounds in Hong Kong homes, Building and Environment, 46(11), p2280-2286.
55. Guo, H., Morawska, L., He, C., Zhang, Y.L., Ayoko, G., Cao, M., (2010), Characterization of particle number concentrations and PM2.5 in a school: influence of outdoor air pollution on indoor air, Environmental Science and Pollution Research, 17(6), p1268-1278.
56. Gupta, A., Cheong, D.K.W., (2007), Physical characterization of particulate matter and ambient meteorological parameters at different indooro-utdoor locations in Singapore, Building and Environment, 42(1), p237-245.
57. Habil, M., Massey, D.D., Taneja, A., (2013), Exposure of children studying in schools of India to PM levels and metal contamination: sources and their identification, Air Quality, Atmosphere & Health, 6(3), p575-587.
58. Habil, M., Taneja, A., (2011), Children's exposure to indoor particulate matter in naturally ventilated schools in India, Indoor and Built Environment, 20(4), p4304-48.
59. Haverinen-Shaughnessy, U., Shaughnessy, R.J., Cole, E.C., Toyinbo, O., Moschandreas, D.J., (2015), An assessment of indoor environmental quality in schools and its association with health and performance, Building and Environment, 93, p35-40.
60. Health Canada, (1989), Exposure Guidelines for Residential Indoor Air Quality A Report of the Federal-Provincial Advisory Committee on Environmental and Occupational Health, Health Canada (Federal-Provincial Advisory Committee).
61. HKEPD, (2003), Indoor Air Quality Information Centre, Indoor air quality certification schemes for offices and public places. China: Hong Kong Environmental Protection Department, Government of the Hong Kong Special Administrative Region.
62. Institute of Environmental Epidemiology, (1996), Guidelines for Good Indoor Air Quality in Office Premises, Ministry of the Environment, Singapore.
63. IOM, (2011), Climate Change, the Indoor Environmental and Health, Institute of Medicine, Washington, DC.
64. Janssen, N.A., Hoek, G., Brunekreef, B., Harssema, H., (1999), Mass concentration and elemental composition of PM10 in classrooms, Occupational and Environmental Medicine, 56(7), p482-487.
65. Janssen, N.A., Hoek, G., Harssema, H., Brunekreef, B., (1997), Childhood exposure to PM10: relation between personal, classroom, and outdoor concentrations, Occupational and Environmental Medicine, 54(12), p888-894.
66. Janssen, N.A., van Vliet, P.H., Aarts, F., Harssema, H., Brunekreef, B., (2001), Assessment of exposure to traffic related air pollution of children attending schools near motorways, Atmospheric Environment, 35(22), p3875-3884.
67. Jo, W.K., Seo, Y.J., (2005), Indoor and outdoor bioaerosol levels at recreation facilities, elementary schools, and homes, Chemosphere, 61(11), p1570-1579.
68. John, K., Karnae, S., Crist, K., Kim, M., Kulkarni, A., (2007), Analysis of trace elements and ions in ambient fine particulate matter at three elementary schools in Ohio, Journal of the Air & Waste Management Association, 57(4), p394-406.
69. Jovanović, M., Vučićević, B., Turanjanin, V., Živković, M., Spasojević, V., (2014), Investigation of indoor and outdoor air quality of the classrooms at a school in Serbia, Energy, 77, p42-48.
70. Kim, J.L., Elfman, L., Mi, Y., Johansson, M., Smedje, G., Norbäck, D., (2005), Current asthma and respiratory symptoms among pupils in relation to dietary factors and allergens in the school environment, Indoor Air, 15(3), p170-182.
71. Kim, J.L., Elfman, L., Mi, Y., Wieslander, G., Smedje, G., Norbäck, D., (2007), Indoor molds, bacteria, microbial volatile organic compounds and plasticizers in schoolsassociations with asthma and respiratory symptoms in pupils, Indoor Air, 17(2), p153-163.
72. Kingham, S., Briggs, D., Elliott, P., Fischer, P., Lebret, E., (2000), Spatial variations in the concentrations of traffic-related pollutants in indoor and outdoor air in Hud - dersfield England, Atmospheric Environment, 34(6), p905-916.
73. Kinshella, M.R., Van Dyke, M.V., Douglas, K.E., Martyny, J.W., (2001), Perceptions of indoor air quality associated with ventilation system types in elementary schools, Applied Occupational and Environmental Hygiene, 16(10), p952-960.
74. Koponen, I.K., Asmi, A., Keronen, P., Puhto, K., Kulmala, M., (2001), Indoor air measurement campaign in Helsinki, Finland 1999-the effect of outdoor air pollution on indoor air, Atmospheric Environment, 35(8), p14651-477.
75. Krugly, E., Martuzevicius, D., Sidaraviciute, R., Ciuzas, D., Prasauskas, T., Kauneliene, V., Stasiulaitiene, I., Kliucininkas, L., (2014), Characterization of particulate and vapor phase polycyclic aromatic hydrocarbons in indoor and outdoor air of primary schools, Atmospheric Environment, 82, p298-306.
76. Krzyzanowski, M., Bundeshaus, G., Negru, M.L., Salvi, M.C., (2005), Particulate matter air pollution: how it harms health, World Health Organization Fact sheet EURO/04/05.
77. Larson, T., Gould, T., Simpson, C., Liu, L.J.S., Claiborn, C., Lewtas, J., (2004), Source apportionment of indoor, outdoor, and personal PM2.5 in Seattle, Washington, using positive matrix factorization, Journal of the Air & Waste Management Association, 54(9), p1175-1187.
78. Lawson, S.J., Galbally, I.E., Powell, J.C., Keywood, M.D., Molloy, S.B., Cheng, M., Selleck, P.W., (2011), The effect of proximity to major roads on indoor air quality in typical Australian dwellings, Atmospheric Environment, 45(13), p2252-2259.
79. Lee, S.C., Chang, M., (2000), Indoor and outdoor air quality investigation at schools in Hong Kong, Chemosphere, 41(1), p109-113.
80. Lee, S.C., Guo, H., Li, W.M., Chan, L.Y., (2002), Interc-omparison of air pollutant concentrations in different indoor environments in Hong Kong, Atmospheric Environment, 36(12), p1929-1940.
81. Lim, J.M., Jeong, J.H., Lee, J.H., Moon, J.H., Chung, Y.S., Kim, K.H., (2011), The analysis of PM2.5 and associated elements and their indoor/outdoor pollution status in an urban area, Indoor Air, 21(2), p145-155.
82. Macher, J., (1999), Bioaerosols: assessment and control, American Conference of Governmental Industrial Hygienists.
83. Madureira, J., Paciência, I., de Oliveira Fernandes, E., (2012), Levels and indooro-utdoor relationships of sizespecific particulate matter in naturally ventilated Portuguese schools, Journal of Toxicology and Environmental Health, Part A: Current Issues, 75(22-23), p1423-1436.
84. Madureira, J., Paciência, I., Pereira, C., Teixeira, J.P., Fernandes, E.D.O., (2015), Indoor air quality in Portuguese schools: levels and sources of pollutants, Indoor Air, p1-12.
85. Madureira, J., Paciência, I., Rufo, J., Severo, M., Ramos, E., Barros, H., de Oliveira Fernandes, E., (2016), Source apportionment of CO2, PM10 and VOCs levels and health risk assessment in naturally ventilated primary schools in Porto, Portugal, Building and Environment, 96, p198-205.
86. Maroni, M., Seifert, B., Lindvall, T., (1995), Indoor Air Quality a Comprehensive Reference Book, Elsevier, Amsterdam.
87. Massey, D., Kulshrestha, A., Masih, J., Taneja, A., (2012), Seasonal trends of PM 10, PM 5.0, PM 2.5 and PM 1.0 in indoor and outdoor environments of residential homes located in North-Central India, Building and Environment, 47(22), p223-231.
88. Maté, T., Guaita, R., Pichiule, M., Linares, C., Díaz, J., (2010), Short-term effect of fine particulate matter (PM2.5) on daily mortality due to diseases of the circulatory system in Madrid (Spain), Science of the Total Environment, 408(23), p5750-5757.
89. Mazaheri, M., Reche, C., Rivas, I., Crilley, L.R., ÁlvarezPedrerol, M., Viana, M., Tobias, A., Alastuey, A., Sunyer, J., Querol, X., Morawska, L., (2016), Variability in exposure to ambient ultrafine particles in urban schools: Comparative assessment between Australia and Spain, Environment International, 88, p142-149.
90. Medina, S., Plasencia, A., Ballester, F., Mücke, H.G., Schwartz, J., (2004), Apheis: public health impact of PM10 in 19 European cities, Journal of Epidemiology and Community Health, 58(10), p831-836.
91. Meklin, T., Husman, T., Vepsäläinen, A., Vahteristo, M., Koivisto, J., Halla-Aho, J., Hyvärinen, A., Moschan-dreas, D., Nevalainen, A., (2002), Indoor air microbes and respiratory symptoms of children in moisture damaged and reference schools, Indoor Air, 12(3), p175-183.
92. Mendell, M.J., Heath, G.A., (2005), Do indoor pollutants and thermal conditions in schools influence student performance? A critical review of the literature, Indoor Air, 15(1), p27-52.
93. MHLW, (2009), Ministry of Health, Labor and Welfare, Japanese Law for Maintenance of Sanitation in Buildings.
94. Mi, Y.H., Norbäck, D., Tao, J., Mi, Y.L., Ferm, M., (2006), Current asthma and respiratory symptoms among pupils in Shanghai, China: influence of building ventilation, nitrogen dioxide, ozone, and formaldehyde in classrooms, Indoor Air, 16(6), p454-464.
95. Miller, F.J., (2000), Dosimetry of particles: critical factors having risk assessment implications, Inhalation Toxicology, 12(S3), p389-395.
96. Minguillón, M.C., Schembari, A., Triguero-Mas, M., de Nazelle, A., Dadvand, P., Figueras, F.J., Salvado, A., Grimalt, J.O., Nieuwenhuijsen, M., Querol, X., (2012), Source apportionment of indoor, outdoor and personal PM2.5 exposure of pregnant women in Barcelona, Spain, Atmospheric Environment, 59, p426-436.
97. Moglia, D., Smith, A., MacIntosh, D.L., Somers, J.L., (2006), Prevalence and implementation of IAQ programs in US schools, Environmental Health Perspectives, 114(1), p141.
98. Mohanraj, R., Azeez, P.A., (2004), Health effects of airborne particulate matter and the Indian scenario, Current Science, 87(6), p741-748.
99. Montazami, A., Wilson, M., Nicol, F., (2012), Aircraft noise, overheating and poor air quality in classrooms in London primary schools, Building and Environment, 52, p129-141.
100. Morawska, L., He, C., Johnson, G., Guo, H., Uhde, E., Ayoko, G., (2009), Ultrafine particles in indoor air of a school: possible role of secondary organic aerosols, Environmental Science & Technology, 43(24), p9103-9109.
101. Morris, R.D., (2001), Airborne particulates and hospital admissions for cardiovascular disease: a quantitative review of the evidence, Environmental Health Perspectives 109(Suppl 4), p495-500.
102. Mui, K.W., Wong, L.T., Hui, P.S., (2008), Risks of unsatisfactory airborne bacteria level in air-conditioned offic - es of subtropical climates, Building and Environment, 43(4), p475-479.
103. Mullen, N.A., Bhangar, S., Hering, S.V., Kreisberg, N.M., Nazaroff, W.W., (2011), Ultrafine particle concentrations and exposures in six elementary school classrooms in northern California, Indoor Air, 21(1), p77-87.
104. Neuberger, M., Schimek, M.G., Horak, F. Jr, Moshammer, H., Kundi, M., Frischer, T., Gomiscek, B., Puxbaum, H., Hauck, H., (2004), Acute effects of particulate matter on respiratory diseases, symptoms and functions: epidemiological results of the Austrian Project on Health Effects of Particulate Matter (AUPHEP), Atmospheric Environment, 38(24), p3971-3981.
105. Nielsen, O., (1984), Quality of air and the amount of fresh air in classrooms, In:, Berglund, B., Lindvall, T., and (eds) Sundell, J., Indoor Air: Buildings, Ventilation and Thermal Climate, Stockholm Swedish Council for Building Research, 5, p221-226.
106. Oeder, S., Dietrich, S., Weichenmeier, I., Schober, W., Pusch, G., Jörres, R.A., Schierl, R., Nowak, D., Fromme, H., Behrendt, H., Buters, J.T.M., (2012), Toxicity and elemental composition of particulate matter from outdoor and indoor air of elementary schools in Munich, Germany, Indoor Air, 22(2), p148-158.
107. Pant, P., Harrison, R.M., (2012), Critical review of receptor modelling for particulate matter: a case study of India, Atmospheric Environment, 49, p1-12.
108. Pearce, D., Crowards, T., (1996), Particulate matter and human health in the United Kingdom, Energy Policy, 24(7), p609-619.
109. Pegas, P.N., Nunes, T., Alves, C.A., Silva, J.R., Vieira, S.L.A., Caseiro, A., Pio, C.A., (2012), Indoor and outdoor characterisation of organic and inorganic compounds in city centre and suburban elementary schools of Aveiro, Portugal, Atmospheric Environment, 55, p80-89.
110. Pervez, S., Dubey, N., Watson, J.G., Chow, J., Pervez, Y., (2012), Impact of different household fuel use on source apportionment results of house-indoor RPM in Central India, Aerosol and Air Quality Resarch, 12(1), p49-60.
111. Polednik, B., (2013), Particulate matter and student exposure in school classrooms in Lublin, Poland, Environmental Research, 120, p134-139.
112. Pope, C.A. III, Burnett, R.T., Thun, M.J., Calle, E.E., Krewski, D., Ito, K., Thurston, G.D., (2002), Lung cancer, cardiopulmonary mortality, and longt-erm exposure to fine particulate air pollution, Journal of the American Medical Association, 287(9), p1132-1141.
113. Pope, C.A., Burnett, R.T., Thurston, G.D., Thun, M.J., Calle, E.E., Krewski, D., Godleski, J.J., (2004), Cardiovascular mortality and long-term exposure to particu - late air pollution epidemiological evidence of general pathophysiological pathways of disease, Circulation, 109(1), p71-77.
114. Poulhet, G., Dusanter, S., Crunaire, S., Locoge, N., Gaudion, V., Merlen, C., Kaluzny, P., Coddeville, P., (2014), Investigation of formaldehyde sources in French schools using a passive flux sampler, Building and Environment, 71, p111-120.
115. Poupard, O., Blondeau, P., Iordache, V., Allard, F., (2005), Statistical analysis of parameters influencing the relationship between outdoor and indoor air quality in schools, Atmospheric Environment, 39(11), p2071-2080.
116. Putus, T., Tuomainen, A., Rautiala, S., (2004), Chemical and microbial exposures in a school building: adverse health effects in children, Archives of Environmental Health: An International Journal, 59(4), p194-201.
117. Qian, J., Hospodsky, D., Yamamoto, N., Nazaroff, W.W., Peccia, J., (2012), Size-resolved emission rates of air - borne bacteria and fungi in an occupied classroom, Indoor Air, 22(4), p339-351.
118. Raysoni, A.U., Stock, T.H., Sarnat, J.A., Montoya Sosa, T., Ebelt Sarnat, S., Holguin, F., Greenwald, R., Johnson, B., Li, W.W., (2013), Characterization of traffic-related air pollutant metrics at four schools in El Paso, Texas, USA: Implications for exposure assessment and siting schools in urban areas, Atmospheric Environment, 80, p140-151.
119. Riain, N., Mark, D., Davies, M., Harrison, R.M., Byrne, M.A., (2003), Averaging periods for indoor-outdoor ratios of pollution in naturally ventilated non-domestic buildings near a busy road, Atmospheric Environment, 37(29), p4121-4132.
120. Rivas, I., Viana, M., Moreno, T., Bouso, L., Pandolfi, M., Alvarez-Pedrerol, M., Forns, J., Alastuey, A., Sunyer, J., Querol, X., (2015), Outdoor infiltration and indoor contribution of UFP and BC, OC, secondary inorganic ions and metals in PM2.5 in schools, Atmospheric Environment, 106, p129-138.
121. Rufo, J.C., Madureira, J., Paciência, I., Slezakova, K., do Carmo Pereira, M., Aguiar, L., Teixeira, J.P., Moreira, A., Fernandes, E.O., (2016), Children exposure to indoor ultrafine particles in urban and rural school environments, Environmental Science and Pollution Research, p1-9.
122. Santamouris, M., Synnefa, A., Asssimakopoulos, M., Livada, I., Pavlou, K., Papaglastra, M., Gaitani, N., Kolokotsa, D., Assimakopoulos, V., (2008), Experimental investigation of the air flow and indoor carbon dioxide concentration in classrooms with intermittent natural ventilation, Energy and Buildings, 40(10), p1833-1843.
123. Sawant, A.A., Na, K., Zhu, X., Cocker, K., Butt, S., Song, C., Cocker, D.R. III, (2004), Characterization of PM2.5 and selected gas-phase compounds at multiple indoor and outdoor sites in Mira Loma California, Atmospheric Environment, 38(37), p6269-6278.
124. Schwartz, J., Dockery, D.W., Neas, L.M., (1996), Is daily mortality associated specifically with fine particles?, Journal of the Air & Waste Management Association, 46(10), p927-939.
125. Sexton, K., Hayward, S.B., (1987), Source apportionment of indoor air pollution, Atmospheric Environment, (1967), 21(2), p407-418.
126. Shendell, D.G., Prill, R., Fisk, W.J., Apte, M.G., Blake, D., Faulkner, D., (2004), Associations between classroom CO2 concentrations and student attendance in Washington and Idaho, Indoor Air, 14(5), p333-341.
127. Simoni, M., Annesi-Maesano, I., Sigsgaard, T., Norback, D., Wieslander, G., Nystad, W., Canciani, M., Sestini, P., Viegi, G., (2010), School air quality related to dry cough, rhinitis and nasal patency in children, European Respiratory Journal, 35(4), p742-749.
128. Simons, E., Hwang, S.A., Fitzgerald, E.F., Kielb, C., Lin, S., (2010), The impact of school building conditions on student absenteeism in upstate New York, American Journal of Public Health, 100(9), p1679.
129. SINPHONIE, (2013),, accessed on 1st, March 2014.
130. Smedje, G., Norbäck, D., (2000), New ventilation systems at select schools in Swedene-ffects on asthma and exposure, Archives of Environmental Health: An International Journal, 55(1), p18-25.
131. Spengler, J.D., (2012), Climate change, indoor environments, and health, Indoor Air, 22, p89-95.
132. Stranger, M., Potgieter-Vermaak, S.S., Van Grieken, R., (2008), Characterization of indoor air quality in primary schools in Antwerp, Belgium, Indoor Air, 18(6), p454-463.
133. Thatcher, T.L., Layton, D.W., (1995), Deposition, resuspension, and penetration of particles within a residence, Atmospheric Environment, 29, p1487-1497.
134. Theodosiou, T.G., Ordoumpozanis, K.T., (2008), Energy, comfort and indoor air quality in nursery and elementary school buildings in the cold climatic zone of Greece, Energy and Buildings, 40(12), p2207-2214.
135. Tippayawong, N., Khuntong, P., Nitatwichit, C., Khunatorn, Y., Tantakitti, C., (2009), Indoor/outdoor relationships of sizer-esolved particle concentrations in naturally ventilated school environments, Building and Environment, 44(1), p188-197.
136. Toyinbo, O., Shaughnessy, R., Turunen, M., Putus, T., Metsämuuronen, J., Kurnitski, J., Haverinen-Shaughnessy, U., (2016), Building characteristics, indoor environmental quality, and mathematics achievement in Finnish elementary schools, Building and Environment, 104, p114-121.
137. Tran, D.T., Alleman, L.Y., Coddeville, P., Galloo, J.C., (2012), Elemental characterization and source identification of size resolved atmospheric particles in French classrooms, Atmospheric Environment, 54, p250-259.
138. Tran, D.T., Alleman, L.Y., Coddeville, P., Galloo, J.C., (2014), Indoor-outdoor behavior and sources of sizeresolved airborne particles in French classrooms, Building and Environment, 81, p183-191.
139. Triantafyllou, A.G., Zoras, S., Evagelopoulos, V., Garas, S., (2008), PM10, O3, CO concentrations and elemental analysis of airborne particles in a school building, Water, Air, & Soil Pollution: Focus, 8(1), p77-87.
140. Turk, B.H., Grimsrud, D.T., Brown, J.T., Geisling-Sobotka, K., Harrison, J., Prill, R.J., (1987), Commercial building ventilation rates and particle concentrations, In: Proceedings of Indoor Air '87: The 4th International Conference on Indoor Air Quality and Climate, West Berlin, West Germany, 1, p610-614.
141. Turunen, M., Toyinbo, O., Putus, T., Nevalainen, A., Shaughnessy, R., HaverinenS-haughnessy, U., (2014), Indoor environmental quality in school buildings, and the health and wellbeing of students, International Journal of Hygiene and Environmental Health, 217(7), p733-739.
142. Twardella, D., Matzen, W., Lahrz, T., Burghardt, R., Spegel, H., Hendrowarsito, L., Frenzel, A.C., Fromme, H., (2012), Effect of classroom air quality on students' concentration: results of a cluster-randomized cross-over experimental study, Indoor Air, 22(5), p378-387.
143. Uhde, E., Salthammer, T., (2007), Impact of reaction products from building materials and furnishings on indoor air quality-a review of recent advances in indoor chemistry, Atmospheric Environment, 41(15), p3111-3128.
144. UNESCO, (2009), Global Education Digest 2009: Comparing education statistics across the world, UNESCO Institute for Statistics, Montreal, Quebec, Canada.
145. U.S. EPA, (1990), Compendium of Methods for the Determination of Air Pollutants in Indoor Air, US EPA Office of Research and Development, Research Triangle Park, NC.
146. U.S. EPA, (2003), A Standardized EPA Protocol for Characterizing Indoor Air Quality in Large Office Buildings, Office of Research and Development and Office of Air and Radiation, U.S. Environmental Protection Agency, Washington, DC.
147. U.S. EPA, (2011), IAQ and climate readiness, U.S. Environmental Protection Agency, Washington, DC.
148. U.S. EPA, (2012),, accessed on 1st, July 2012.
149. U.S. EPA, (2013),, accessed on 1st, October 2013.
150. U.S. EPA, (2014),, accessed on 1st, March 2014.
151. U.S. EPA and NIOSH, (1991), 1991, U.S. Environmental Protection Agency and National Institute of Occupational Safety and Health, Washington, DC.
152. van der Zee, S.C., Strak, M., Dijkema, M.B.A., Brunekreef, B., Janssen, N.A.H., (2016), The impact of particle filtration on indoor air quality in a classroom near a highway, Indoor Air.
153. Viana, M., Kuhlbusch, T.A.J., Querol, X., Alastuey, A., Harrison, R.M., Hopke, P.K., Winiwarter, W., Vallius, M., Szidat, S., Prévôt, A.S.H., Hueglin, C., Bloemen, H., Wåhlin, P., Vecchi, R., Miranda, A.I., Kasper-Giebl, A., Maenhaut, W., Hitzenberger, R., (2008), Source apportionment of particulate matter in Europe: a review of methods and results, Journal of Aerosol Science, 39(10), p827-849.
154. Viana, M., Rivas, I., Querol, X., Alastuey, A., ÁlvarezPedrerol, M., Bouso, L., Sioutas, C., Sunyer, J., (2015), Partitioning of trace elements and metals between quasiultrafine, accumulation and coarse aerosols in indoor and outdoor air in schools, Atmospheric Environment, 106, p392-401.
155. Wallenborn, J.G., Schladweiler, M.J., Richards, J.H., Kodavanti, U.P., (2009), Differential pulmonary and cardiac effects of pulmonary exposure to a panel of particulate matter-associated metals, Toxicology and Applied Pharmacology, 241(1), p71-80.
156. Ward, T.J., Noonan, C.W., Hooper, K., (2007), Results of an indoor size fractionated PM school sampling program in Libby, Montana, Environmental Monitoring and Assessment, 130(1-3), p163-171.
157. White-Newsome, J.L., Sánchez, B.N., Jolliet, O., Zhang, Z., Parker, E.A., Timothy Dvonch, J., O'Neill, M.S., (2012), Climate change and health: indoor heat exposure in vulnerable populations, Environmental Research, 112, p20-27.
158. WHO, (2003), Health Aspects of Air Pollution with Particulate Matter, Ozone and Nitrogen Dioxide, Report on a WHO Working Group Bonn, Germany.
159. WHO, (2006a), Principles for evaluating health risks in children associated with exposure to chemicals, World Health Organization, Geneva, Switzerland.
160. WHO, (2006b), WHO Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide: global update 2005: summary of risk assessment, World Health Organization, Geneva, Switzerland.
161. Worksafe Australia, (2013), Workplace Exposure Standards for Airborne Contaminants, Worksafe Australia.
162. Yang, W., Sohn, J., Kim, J., Son, B., Park, J., (2009), Indoor air quality investigation according to age of the school buildings in Korea, Journal of Environmental Management, 90(1), p348-354.
163. Zhang, Q., Zhu, Y., (2012), Characterizing ultrafine particles and other air pollutants at five schools in South Texas, Indoor Air, 22(1), p33-42.
164. Zhao, Z., Sebastian, A., Larsson, L., Wang, Z., Zhang, Z., Norbäck, D., (2008), Asthmatic symptoms among pupils in relation to microbial dust exposure in schools in Taiyuan, China, Pediatric Allergy and Immunology, 19(5), p455-465.
165. Zwoździak, A., Sówka, I., Krupińska, B., Zwoździak, J., Nych, A., (2013), Infiltration or indoor sources as determinants of the elemental composition of particulate matter inside a school in Wrocław, Poland?, Building and Environment, 66, p173-180.