ABSTRACT
ABSTRACT
Scientific evidence associates indoor environment pollutants with respiratory effects (asthma and allergies), and children constitute one of most sensitive groups. Indoor air quality (IAQ) in schools may indeed be a significant health factor for children, with effects on school attendance and performance. Our aim was to characterize IAQ of classrooms in Maia County (north of Portugal) for which there was no information available. The study was conducted in 21 of the 40 primary schools, selected by stratified random sampling. Depending on the dimension, one or two classrooms were tested at each school. Walkthrough surveys of school grounds, buildings, and individual classrooms were done. Continuous measurements were taken of temperature, relative humidity, airborne respirable particles, total volatile organic compounds, and carbon dioxide, whereas bioaerosols were counted on Plate Count Agar during regular school activities. The indoor arithmetic mean for PM10, CO2, TCOV, and bioaerosol concentrations were 0.14 mg/m3, 999 ppm, 0.41 mg/m3, and 4140 UCF/m3, respectively. The values of PM10 and CO2 were close to their acceptable maximum values, but bioaerosols were much higher. This study supports previous studies conducted in school environments and emphasizes the need for proactive indoor air quality audits in school buildings.
INTRODUCTION
Nowadays, education has become a crucial component of a child's social development. Worldwide, the average number of years of schooling grew from 7.9 years in 1970 to 11.0 years in 2008; in Portugal, it already attained 12.9 years in 2008 (UNESCO 2010). Additionally, children spend on average 7 to 11 h/day (5 days per week) at school (Almeida et al. 2010), so a major fraction of their time is actually spent within school premises. Consequently, the air quality in and around schools has major health implications for this particularly susceptible portion of the population. The health effects of exposure to air pollutants have been extensively documented and reviewed; children, particularly those with asthma and allergies, are more susceptible thereto (Cartieaux et al. 2011; Dor et al. 2010; Jones et al. 2010; Kim et al. 2011; Kulkarni and Grigg 2008; Mejía et al. 2011; Zhao et al. 2008).
The causes of indoor air pollution are a combination of physical, chemical, and biological factors, and the adequacy of ventilation in the environment. The strong contribution of outdoor pollution is coupled with a very specific pollution associated with classroom activities (use of paints, markers, glues, and adhesives)—besides classroom cleaning and maintenance (use of cleaning supplies, furnishing supplies, waxes, pesticides, and spray repellents). Several pollutants have been reported in classrooms, such as bacteria, fungi, and volatile organic compounds (Geiss et al. 2011), as well as micro particles (Almeida et al. 2010; Kim et al. 2011). However, there is a large variation in personal exposure between individual children (and classrooms) caused by differences in building design, indoor and outdoor sources, and activity patterns (Ashmore and Dimitroupoulou 2009).
Therefore this study aimed at characterizing indoor environmental air of primary classrooms of Maia County as a case study of public Portuguese schools. We assessed the variability in pollutant levels between classrooms and correlations with classroom ventilation rates, occupancy rate, and other factors. This study also aimed at checking the impact of indoor air quality (IAQ) awareness as a public health problem in the environmental quality of schools.
In Portugal, only two studies have been done concerning indoor environmental air of schools: one in southern Portugal (Lisbon), focusing on concentrations of coarse particles (Almeida et al. 2010), and the other in northern Portugal (Porto), focusing on health teachers and the influence of traffic emissions on IAQ (Madureira et al. 2009). Considering the importance of this subject, more studies are obviously in order—namely in Portugal, to confirm or not the similarity of results for different places and regions. Additionally, the results could reinforce the need for implementation of good practices to improve classrooms’ air quality and thus contribute to a favourable learning environment for students and productivity for teachers and staff, besides an overall feeling of comfort, health, and well-being (Jones et al. 2010).
Portugal is definitely in great need of implementation of public policies and strategies to promote superior indoor air quality. Environment and health are so intimately linked that environmental and health policies should be as well; however, health impacts are hard to quantify in financial terms (Remoundou and Koundouri 2009). A program was successfully implemented in the United States that included mechanical ventilation, air-conditioning systems, moisture and mold control, pest management, cleaning and maintenance, material selection, and source control as priorities (Jones et al. 2010).
METHODS
School Sampling
This study was performed during the heating season (May to October 2010) and the cooling season (January to March 2011) in primary schools located in Maia County (Portugal). Twenty-one schools were randomly selected from the total of 42 primary schools. The school administrators were contacted, and they all agreed to participate. One or two representative classrooms were investigated in each of the 21 schools, depending on their size.
Description of Schools
A walkthrough inspection and a checklist were completed for each school. The information collected included such building characteristics as: age and details on construction, type of heating and ventilation system, common area, space usage, finishing materials and their conditions concerning floor, walls, and ceilings; preventive maintenance, renovation, and cleaning routines. A classroom form was completed for each classroom that included information on area and volume, operable windows and vents, and presence of plants and sources of pollutants. The rate of occupancy (number of children and teacher per classroom area) was also recorded.
Environmental Sampling
Air pollutants consisting of airborne respirable particulate matter with aerodynamic diameter less than 10 μm (PM10), carbon dioxide (CO2), total volatile organic compounds (TVOC), and climatic factors that consisted of temperature (T), and relative humidity (RH) were all measured, and bioaerosols (bacteria and fungi) were sampled—both indoor classrooms and outdoor recreational facilities. Indoor measurements were recorded during class activities, with the equipment placed on representative locations out of children's reach and at least 0.6 m above the floor and away from windows, doors, and sources of potential pollutants. Simultaneous chemical and climate factors were measured outdoors, and bioaerosol samples were duly collected at least in one representative location in each school away from direct sunlight.
Environmental Parameter Determination
Indoor and outdoor T and RH parameters and PM10, CO2, and TVOC concentrations were measured with a direct-reading instrument, with built-in data logger (EVM–7 Multiparameter Environmental Monitor, Quest Tecnhnology–3M, WI, USA). This monitor included the following sensors: a 90° optical light-scattering laser photometer for PM10, a CO2 non-dispersive infrared sensor, a photoionization detector to measure TVOC, and a junction diode and a capacitive sensor to measure T and RH, respectively. The equipment was supplied with a factory calibration certificate, which was doubled-checked prior to use. Sampling was at 1-min average interval, and measurements were performed for at least 50 minutes.
Bioaerosol sampling was based on the European standard EN 13098 (CEN 2000). Airborne viable bacteria and fungi were collected on plates containing sterilized agar media (Plate Count Agar, VWR, Spain) by impact, using a single stage sampler (MAS 100-NT®, Merck, MA, USA) at a calibrated flow rate of 100 L/min. The sampling volumes were 15, 25, 30, and 50 L, indoors, and 25, 50, and 100 L, outdoors. After each sampling, the media plates were removed from the sampler, kept refrigerated, and brought at once to our laboratory. The bioaerosol sampler was sterilized with isopropyl alcohol prior to sampling. In order to monitor contamination during storage, transport and sample collection, blank samples that remained unopened were carried into sampling sites. All samples were incubated at 25°C for 3 d, and then total colonies were counted. The MAS 100-NT® equipment was calibrated automatically, and confirmed by a manufacturer's certificate.
Statistical Analyses
Statistical analysis of the data based on two-tailed tests, at the 5% level of significance, was performed using IBM SPSS Statistics v. 19 for Windows. A Kolmogorov-Smirnov (n > 30) or a Shapiro-Wilk (n < 30) test were performed, to assess data distribution. Temperature and RH data showed a normal distribution but PM10, CO2, and bioaerosol data showed a log-normal distribution; TVOC data did not show any of these behaviors. For such reasons, the arithmetic formula and the geometric formula for the means and standard deviations were used. The differences in measured environmental parameters by localization (indoor/outdoor) and by season (heating/cooling) were analyzed by Independent Samples T-test (for normal distributions) or by Mann-Whitney U test (for non-normal distributions). Correlations between indoor air pollutant concentrations and classroom factors were analyzed by Spearman's rho coefficient.
RESULTS
Typical Characteristics of Schools
The schools studied were constructed with concrete and bricks and none had mechanical ventilation, but all schools possessed heating systems. The floor material of classrooms was wood (67%), linoleum (26%), or ceramic tiles (7%) and the walls were painted. Signs of moisture, water damage, or indoor mold growth could be observed in 24% of the schools and very few classrooms had indoor plants. The mean number ± standard deviation of people (students and teacher) per classroom was 24.5 ± 3.6 (range: 13–27) and each student occupied 2.6 ± 0.6 m2 (range: 1.9–4.0). All classrooms depended only on natural ventilation through existing vents, windows, and doors. From the classrooms sampled (n = 39), 15.4% had closed windows, 38.5% had windows opened occasionally, and the other 46.1% had windows opened frequently.
Environmental Parameters
Depicted in Table 1 are the results of environmental monitoring made in 21 schools (corresponding to 39 classrooms). IAQ and climate parameters were analyzed according to the criteria of the National System for Energy and Indoor Air Quality Certification of Buildings (RSECE 2006), transposed to Portuguese legislation from the European Directive 2002/91/CE. This legal document establishes the following acceptable maximum values (AMV): 0.15 mg/m3 for PM10, 1000 ppm for CO2, 0.6 mg/m3 for TVOC, and 1000 CFU/m3 for total viable bacteria and fungi. For comfort climate parameters, the recommended values are 25°C for the heating season and 20°C for the cooling season, and 50% for relative humidity all year round.
Table 1 Descriptive statistics of environmental indoor and outdoor data.
According to the National Air Quality Strategy guidelines (RSECE 2006), one observed that: (i) PM10 and CO2 concentrations in classrooms were near AMV, but this value was exceeded in 32% and 58%, respectively, of the classrooms; (ii) TVOC concentrations were less than AMV, but the results obtained in 6% of classrooms were greater than the proposed target threshold; (iii) bioaerosol values were well above AMV, and this fact was found in almost all classrooms (96%); and (iv) temperature and relative humidity values were generally in agreement with those recommended, although temperature and relative humidity were out of the range 20–25°C and 40–60%, in 37% and 35% of the total classrooms, respectively. As schools have typically no mechanical ventilation systems, temperature and relative humidity are imposed mainly by local climate conditions.
Indoor/Outdoor Ratios
To evaluate how the indoor air quality was affected by outdoor air pollution, the ratios between indoor/outdoor concentrations were calculated, as shown in Table 2. The indoor/outdoor ratio for TVOC (I/O = 1) indicates that outdoor sources were the primary contributors, as expected. In Portugal, children's activities included use of non-solvent based products (water-based glues and paints) and most schools stood well away from road traffic lines.
Table 2 Values of indoor to outdoor ratio, during the heating and cooling seasons for the indoor air quality parameters tested.
The indoor/outdoor ratios for PM10 and bioaerosols point out at indoor sources, and no statistically significant differences between the two seasons were found (p > .05). Children move around at high frequencies, so the mechanics of cloth brushing against their skin dislodge skin scales and dust particles that contain many millions of microbial organisms. Otherwise, respiratory morbidity among children—mainly in winter time, may also contribute to airborne spread of bioaerosols and higher levels of indoor bacteria.
The indoor/outdoor ratio for CO2 pointed out mainly at indoor sources, but significant differences between the two seasons were found (p < .01). Occupants are the dominant indoor source of CO2 and the indoor CO2 concentration is often considered to be a surrogate for the rate of ventilation per occupant. Our results found unfolded inadequate ventilation in the classrooms. The indoor/outdoor ratio for CO2 was greater in the cooling season, when the windows were closed most of the time, thus reducing the amount of fresh air supplied.
Correlation Coefficients
This last realization is also confirmed by the data in Table 3 via the correlation coefficients between IAQ parameters and some classroom characteristics. Negative significant correlation coefficients were obtained between CO2 and ventilation—global and by open windows, thus meaning that natural ventilation is necessary to maintain CO2 levels low as an alternative to mechanical ventilation. One also observes that TVOC concentration increased significantly with ventilation via open windows, as expected, knowing that outdoor air is its main source.
Table 3 Spearman's rho correlation coefficients between IAQ parameters and classroom characteristics.
DISCUSSION
PM10 Concentration
The PM10 concentration values found in this study pertaining to the Northern region of Portugal were essentially similar to those reported by Almeida et al. (2010), who studied the Lisbon area (Southern Portugal), but much higher than those reported by Madureira et al. (2009) pertaining to Porto (also in Northern Portugal). Borrego et al. (2008) reported that PM10 values were higher in Porto than in Lisbon. A wide variability of data concerning IAQ in schools exists, so standard procedures and continuous monitoring of air quality are needed to guarantee similar conditions in IAQ in schools all over Portugal.
The I/O ratio for PM10 was greater than unity (almost twice). This observation agrees with other studies and may be explained by the strong influence of human occupancy (Blondeaux et al. 2005; Branis et al. 2009; Goyal and Khare 2009; Yang et al. 2009; Yoon et al. 2011). However, no significant correlation was obtained between PM10 and occupancy rate in this study (Table 3). Some authors (Guo et al. 2008; Parker et al. 2008) reported that there is an inverse relationship between air exchange rate and particulate number concentration, yet no significant correlation between PM10 concentration and ventilation was found here. Another factor that influences PM10 indoor concentration is the level of activity by children, which could not be taken into account in this study.
Some authors (Brandis et al. 2009; Blondeaux et al. 2005; Fromme et al. 2008; Yoon et al. 2011) have reported that the I/O PM10 ratio was higher during children's activity time than during unoccupied periods; studies proved indeed that the activities of children cause resuspension in the air of coarse particulate matter inside buildings (Fromme et al. 2008; Kingham et al. 2008). On the other hand, some authors (Goyal and Khander 2009; Heudorf et al. 2009; Yoon et al. 2011; Zhao et al. 2008) showed that I/O for PM10 was statistically higher in rural than urban regions. Although Maia County is of an urban type, it has a high level of agricultural activities, as well as a considerable percent of green spaces, but it also has a lot of traffic. This could have influenced the average values for PM10 concentrations, since some were close to (or even higher than) 0.15 mg/m3. Finally, Heudorf et al. (2009) reported significant negative correlations between PM10 and intensity of cleaning. This factor was not considered in our study, but should be taken into account as a standard procedure to be implemented in schools.
CO2 Concentration
The concentration of CO2 increased with class time and decreased significantly after children left the classroom (Cartieux et al. 2011; Heudorf et al. 2009; Santamouris et al. 2008). For this reason, samplings were done for 50 min inside the classroom, while children's activities were in progress. The values obtained lie in the same range as those reported by several authors (Cartieux et al. 2011; Madureira et al. 2009; Yang et al. 2009), but were lower than those reported elsewhere (Almeida et al. 2010; Kim et al. 2011). This difference might be explained by the fact that in 46% of classrooms the windows were open for natural ventilation, thus causing a significant decrease in CO2 concentration (Table 3). The I/O ratio of CO2 levels found was statistically higher in the cooling season (owing to the tendency of having the windows closed) than in the heating season (with a prevailing tendency to open the windows). The same discussion does not hold regarding the occupancy rate, because no significant correlation was found; the reason for this finding remains unclear. Other authors (Almeida et al. 2010; Cartieux et al. 2011) showed that both occupation rate and ventilation efficiency significantly influence the CO2 concentration.
TCOV Concentration
Some studies showed important sources of TVOC in the classroom environment were wooden floors and furniture (Ichiba et al. 2009), as well as use of cleaning products (Geiss et al. 2011) and perfumes (Cartieux et al. 2011; Zhao et al. 2008). The mean average and the I/O values for TVOC in this study were lower than those reported by Yoon et al. (2011), similar to those by Yang et al. (2009), and higher than those reported by Madureira et al. (2009). However, from Table 1 one concludes that the variability is large, and actually similar in the three studies. Once again, this fact indicates the need for strategies and policies to control IAQ in schools so as to guarantee similar environmental conditions throughout the country.
Bioaerosols Concentration
The high values found for bioaerosols in the classroom, as well the high values for the I/O ratio (almost 6) had also been reported by Pegas et al. (2010) and Yang et al. (2009). However, both outdoor and indoor values were much higher in the Porto study (Madureira et al. 2009), which is near Maia (about 30 km distant). The high numbers of microbes, both indoors and outdoors, found in this study may probably derive from several factors, including high seasonal level of bioaerosols in outdoor air from agricultural activities, and significant number and size of green spaces around. However, the range of bioaerosol concentration was large and consistent with Cardieux et al. (2011), who reported that the bacterial flora is more important indoors than outdoors and may in addition change fast. According to Mandin (2005), the level of bioaerosols correlates inversely with the rate of renovation of air, and with the time the children spend in the classroom, but a similar correlation could not be found in this study.
Temperature and Humidity Values
Portugal is a country characterized by a typical Atlantic climate—slightly humid, but essentially temperate. This fact is in agreement with the results tabulated in Table 1, as well to those by Madureira et al. (2009) pertaining to the Northern region of Portugal. According to Cartieux et al. (2011), ventilation assures renovation of air, while contributing to regulate temperature and relative humidity. As mentioned before, 46% of all classrooms maintained their windows open, thus making outdoor and indoor temperature and relative humidity close to each other. Additionally, those authors claimed that the increase in number of children per classroom raised the level of relative humidity. This might be explained by respiration that generates vapour, thus producing slightly higher levels of relative humidity indoors as compared to outdoors.
CONCLUSIONS
Most IAQ parameters pertaining to primary schools in Maia (0.14 mg/m3 for PM10, 999 ppm for CO2, and 0.41 mg/m3 for TVOC) were only slightly less than their corresponding acceptable maximum values (0.15 mg/m3, 1000 ppm, and 0.60 mg/m3, respectively); however, the numbers of total bacteria and fungi were much higher (4140 CFU/m3) than the AMV (1000 CFU/m3). One thus concludes that actions are needed to improve the overall microbiological quality of air in primary schools in that county, such as increases in ventilation rate, particulate matter cleaning, and control of bioaerosol concentration. Comparing the results of this study to similar studies performed in school environments, one realises that the intrinsic variability remains large, so there is a need for proactive indoor air quality audits in schools. The previous studies in this area did not create awareness sufficient to drive increase in IAQ. Therefore, one proposes that IAQ audits should be undertaken by trained occupational hygienists at regular time intervals and should involve both physical inspection of representative items and measurement of IAQ parameters.
| Environmental parameters | Local | Range | Median | p5 | p95 | AM ± ASD | GM ± GSD | >AMV (%) |
|---|---|---|---|---|---|---|---|---|
| PM10 (mg/m3) | Outdoor | 0.01–0.45 | 0.07 | 0.02 | 0.28 | 0.12 ± 0.13 | 0.08 ± 5.72 | n.a. |
| Indoor | 0.04–0.37 | 0.12 | 0.05 | 0.29 | 0.14 ± 0.07 | 0.13 ± 3.19 | 32 | |
| CO2 (ppm) | Outdoor | 10–315 | 55 | 12 | 407 | 85 ± 78 | 91 ± 13 | n.a. |
| Indoor | 148–2158 | 899 | 446 | 2125 | 999 ± 477 | 865 ± 6 | 58 | |
| TVOC (mg/m3) | Outdoor | 0.00–1.80 | 0.20 | 0.00 | 1.12 | 0.31 ± 0.40 | n.a. | n.a. |
| Indoor | 0.00–1.60 | 0.40 | 0,00 | 1.13 | 0.41 ± 0.28 | n.a. | 11 | |
| Bioaerosols (UFC/m3) | Outdoor | 238–5100 | 750 | 234 | 3424 | 1195 ± 1142 | 937 ± 6 | n.a. |
| Indoor | 262–7840 | 4020 | 1192 | 7828 | 4140 ± 1785 | 3627 ± 4 | 96 | |
| Temperature (°C) | Outdoor | 12.1–24.2 | 18.3 | 14.9 | 28.1 | 18.8 ± 3.4 | 20.8 ± 1.6 | n.a. |
| Indoor | 14.3–26.1 | 20.5 | 16.6 | 25.9 | 20.3 ± 2.8 | 21.1 ± 1.4 | 37 | |
| Relative Humidity (%) | Outdoor | 41.2–71.4 | 57.4 | 41.8 | 70.2 | 57.3 ± 9.1 | 54.0 ± 1.5 | n.a. |
| Indoor | 45.0–75.7 | 60.8 | 45.0 | 72.0 | 60.3 ± 8.3 | 58.3 ± 1.4 | 35 | |
| p5: 5th percentile; p95: 95th percentile; AM: arithmetic mean; ASD: arithmetic standard deviation; GM: geometric Mean; GSD: geometric standard deviation; AMV: acceptable maximum value, according to Portuguese legislation (RSECE, 2006); n.a.: not applicable. | ||||||||
| Indoor/Outdoor ratio | |||
|---|---|---|---|
| Season | AM1 | Range | |
| PM10 | Heating | 2.2 | 0.9–2.8 |
| Cooling | 1.6 | 0.9–2.5 | |
| CO2 | Heating | 6.9 | 1.8–15.0 |
| Cooling | 11.2 | 5.1–27.0 | |
| TVOC | Heating | 1.0 | 0.8–2.7 |
| Cooling | 1.0 | 0.6–2.3 | |
| Bioaerosols | Heating | 5.9 | 1.9–10.0 |
| Cooling | 6.3 | 2.1–18.5 | |
| 1AM: arithmetic mean. | |||
| Classroom characteristics | ||||
|---|---|---|---|---|
| IAQ | Occupancy | Global ventilation | Ventilation | Presence of moisture |
| parameters | rate | (windows and vents) | (opened windows) | and molds |
| PM10 | 0.044 | 0.022 | −0.080 | −0.2461 |
| CO2 | −0.030 | −0.1971 | −0.5342 | 0.100 |
| TVOC | 0.169 | 0.165 | 0.2101 | 0.153 |
| Bioaerosols | 0.092 | 0.010 | −0.127 | 0.074 |
| 1Correlation significant, at 0.05 level (2-tailed); 2correlation significant, at 0.01 level (2-tailed). | ||||
ACKNOWLEDGMENTS
This work was supported by MAIÊUTICA—Cooperativa do Ensino Superior C.R.L., and Câmara Municipal da Maia, under the auspices of a collaboration protocol. The staff of the several schools tested is hereby acknowledged for their helpful cooperation.
The conclusions and interpretations reported herein are the sole responsibility of the authors, and should not be interpreted as representing the views of the funding agencies.
REFERENCES
- Almeida, S, Canha, NSilva, A. 2010. Children exposure to atmospheric particles in indoor of Lisbon primary schools. Atmosph Environ, doi:10.1016/j.atmosenv.2010.11.052 [Crossref], [Google Scholar]
- Ashmore, M and Dimitroulopoulou, C. 2009. Personal exposure of children to air pollution. Atmosph Environ, 43: 128–41. [Crossref], [Web of Science ®], [Google Scholar]
- Blondeaux, P, Iordache, VPoupard, O. 2005. Relationship between outdoor and indoor air quality in eight French schools. Indoor Air, 15: 2–12. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Borrego, C, Monteiro, EFerreira, J. 2008. Forecasting human exposure to atmospheric pollutants in Portugal—A modelling approach. Atmosph Environ, 43: 5796–806. [Web of Science ®], [Google Scholar]
- Branis, M, Safránek, J and Hytychová, A. 2009. Exposure of children to airborne particulate matter of different size fractions during indoor physical education at school. Build Environ, 44: 1246–52. [Crossref], [Web of Science ®], [Google Scholar]
- Cartieux, E, Rezpka, M and Cunny, D. 2011. Qualité de l’air à l’intérieur des écoles. Archives de Pédiatriques, 18: 789–96. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- CEN (Committee of European Normalization). 2000. Workplace Atmosphere—Guidelines for Measurement of Airborne Micro-Organisms and Endotoxin. EN 13098 Brussels, , Belgium [Google Scholar]
- Dor, F, Mandin, C and Kirchner, S. 2010. La qualité de l’air intérieur: une thématique en dynamique. Archives des Maladies Professionnelles et de l’Environnement, 71: 806–12. [Crossref], [Web of Science ®], [Google Scholar]
- Fromme, H, Diemer, JDietrich, S. 2008. Chemical and morphological properties of particulate matter (PM10, PM2.5) in school classrooms and outdoor air. Atmosph Environ, 42: 6597–605. [Crossref], [Web of Science ®], [Google Scholar]
- Geiss, O, Giannopoulos, GTirendi, S. 2011. The AIRMEX study—VOC measurements in public buildings and schools/kindergartens in eleven European cities: Statistical analysis of the data. Atmosph Environ, 45: 3676–84. [Crossref], [Web of Science ®], [Google Scholar]
- Goyal, R and Khare, M. 2009. Indoor-outdoor concentrations of RSPM in classroom of a naturally ventilated school building near an urban traffic roadway. Atmosph Environ, 43: 6026–38. [Crossref], [Web of Science ®], [Google Scholar]
- Guo, H, Morawska, LHo, G. 2008. Impact of ventilation scenario on air exchange rates and on indoor particle number concentrations in air-conditioned classroom. Atmosph Environ, 42: 757–78. [Crossref], [Web of Science ®], [Google Scholar]
- Heudorf, U, Neitzert, V and Spark, J. 2009. Particulate matter and carbon dioxide in classrooms—The impact of cleaning and ventilation. Internat J Hyg Envir Health, 212: 45–55. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Ichiba, M, Takahashi, TYamashita, Z. 2009. Approach to sick building problems in schools: A workshop “Saga Forum on Environment” Project. Japan J Hyg, 64: 26–31. [Crossref], [PubMed], [Google Scholar]
- Jones, S, Smith, AWheeler, L. 2010. School policies and practices that improved indoor air quality. J. Sch Health, 80: 280–86. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Kim, J, Elfman, LWieslander, G. 2011. Respiratory Health among Korean pupils in relation to home, school and outdoor environment. J Korean Med Sci, 26: 166–73. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Kingham, S, Durand, MHarrison, J. 2008. Temporal variations in particulate exposure to wood smoke in a residential school environment. Atmosph Environ, 42: 4619–31. [Crossref], [Web of Science ®], [Google Scholar]
- Kulkarni, N and Grigg, J. 2008. Effect of air pollution on children. Paediatrics and Child Health, 18: 238–43. [Crossref], [Google Scholar]
- Madureira, J, Alvim-Ferraz, MRodrigues, S. 2009. Indoor air quality in schools and health symptoms among Portuguese teachers. Hum Ecol Risk Assess, 15: 159–69. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Mandin, C. 2005. Qualité de l’air dans les écoles: Émergence d’une priorité de santé publique. L’air intérieur. Air Pur, 69: 18–21. [Google Scholar]
- Mejía, J, Choy, SMengersen, K. 2011. Methodology for assessing exposure and impacts of air pollutants in school children: Data collection, analysis and health effects—A literature review. Atmosph Environ, 45: 813–23. [Crossref], [Web of Science ®], [Google Scholar]
- Parker, J, Larson, REskelson, E. 2008. Particle size distribution and composition in a mechanically ventilated school building during air pollution episodes. Indoor Air, 18: 386–93. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Pegas, P, Evtyugina, MAlves, C. 2010. Outdoor/Indoor air quality in primary schools in Lisbon: A preliminary study. Quim Nova, 33: 1145–59. [Crossref], [Web of Science ®], [Google Scholar]
- Remoundou, K and Koundouri, P. 2009. Environmental effects on public health: An economic perspective. Internat J Environ Res Public Health, 6: 2160–78. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- RSECE (Regulamento dos Sistemas Energéticos de Climatização em Edifícios). 2006. Decreto-Lei no. 79/2006, de 04/04/2006, Ministério das Obras Públicas, Transportes e Comunicações Lisbon, , Portugal Portuguese Decree-Law no. 79/2006—Regulation of Energy Systems of Air Conditioning in Buildings, 04/04/2006, Ministry of Public Construction, Transport, and Communications [Google Scholar]
- Santamouris, M, Synneta, AAssimakopoulos, M. 2008. Experimental investigation of the air flow and indoor carbon dioxide concentration in classrooms with intermittent natural ventilation. Energy and Buildings, 40: 1833–43. [Crossref], [Web of Science ®], [Google Scholar]
- UNESCO (United Nations Educational, Scientific and Cultural Organization). 2010. Global Education Digest 2010: Comparing Education Statistics across the World, pp 14,192–201, Montreal, Quebec, Canada: UNESCO Institute for Statistics. [Google Scholar]
- Yang, W, Sohn, JKim, J. 2009. Indoor air quality investigation according to age of the school buildings in Korea. J Environ Manag, 90: 348–54. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Yoon, C, Lee, K and Park, D. 2011. Indoor quality differences between urban and rural preschools in Korea. Environ Sci Pollut Res, 18: 333–45. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Zhao, Z, Zhang, ZWang, Z. 2008. Asthmatic symptoms among pupils in relation to winter indoor and outdoor air pollution in schools in Taiyuan, China. Environ Health Persp, 116: 90–6. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
