Impact of fine particulate matter and toxic gases on the health of school children in Dhaka, Bangladesh

Long-term exposure to ambient air pollution has been associated with a range of unfavorable health effects, including mortality, cancer, and cardiovascular disease (CVD) [1]. PM with an aerodynamic diameter ≤ 10 μm (PM₁₀) can be deposited within the respiratory tract including those PM_2.5 (Particulate matter with an aerodynamic diameter ≤2.5 μm) has been connected to asthma aggravation and cognitive impairment in children [2]. PM_2.5 makes up around 80% of PM₁₀ mass, and various studies in Europe have looked into it, notably, the Central European Study on Air Pollution and Respiratory Health, have looked into it [3]. Associations of source specific PM_2.5 with mortality from natural causes, cardiovascular disease, non-malignant respiratory diseases, and lung cancer were observed in several areas across Europe in the ELAPSE pooled cohort. For the increase in the interquartile range for each exposure in the pooled cohort, hazard ratios and 95% confidence intervals are presented: 2.86 μgm⁻³ of traffic; 0.25 μgm⁻³ of oil; 0.95 μgm⁻³ of soil; 4.32 μgm⁻³ of biomass and agriculture; 1.09 μgm⁻³ of industry; and 4.49 μgm⁻³ of PM_2.5 mass [4]. However, mega city Dhaka has been experiencing very high emission of air pollution from a variety of sources [5–9]. Every year about 80 thousand people is dying and thousands of people has been suffering from various diseases due to the high air pollution in Dhaka. Automobile emissions, anthropogenic activities, biomass burning, and emissions from coal-based brick kilns contribute significantly to the exceptionally high pollution density [5–9]. Fossil fuels accounted for 44.3% of the total PM_2.5 mass in Dhaka during the monsoon season, whereas burning biomass accounted for 41.4% of the total PM_2.5 mass throughout the remaining months of the year [10].

PM_2.5 has a negative impact on health, causing an increase in fatalities from cardiovascular and respiratory disorders, as well as lung cancer. Increased PM_2.5 concentrations raise the probability of emergency hospital admissions for cardiovascular and respiratory reasons, while PM₁₀ has an impact on respiratory morbidity, as evidenced by hospital admissions for respiratory disease [8]. Children are exposed to more air pollutants than adults due to their higher levels of physical activity. As children spend more time outdoors than adults, they are more susceptible to outside air pollution, which affects the development of lung function, worsens asthma, and causes other respiratory symptoms like cough and bronchitis [11]. The origins and components of PM_2.5 vary according to the microenvironments where children live, learn, and play. PM_2.5 exposures with health implications may occur in the school classroom, where children spend a vast majority of their time subjected to one of the major microenvironments. School closeness to local traffic [12] and traffic encountered on the way to school [13] leading to lower neurocognitivity among school children. Postnatally, 80% of lung alveoli are formed, and lung changes continue into adolescence [14]. A 5.0 μg m⁻³ increase in daily exposure to spatially and temporally weighted particulate matter was statistically associated with a 4.1% reduction in total heart rate variability [15]. In healthy person, an experimental research found that particle deposition can be 4.5 times higher during moderate bicycle exertion than at rest [16]. By reducing proximity to motorized traffic while bicycling to work, exposure to ultrafine particles, which are often linked to combustion emissions from motorized traffic, can be greatly reduced without appreciably lengthening the commute [17]. In a case study of the health surveillance of children under the age of five between 2005 and 2014 in Kamalapur, Bangladesh discovered that elevated ambient PM_2.5 correlates to an increased incidence of child pneumonia in urban Dhaka, and that this association varies among days with diverse source compositions of PM_2.5 [18].

Air pollution causes between 2.6 and 4.4 million premature deaths each year [19]. The WHO has set annual (15 μgm⁻³) and 24 h (45 μgm⁻³) criteria for PM₁₀, and 5 μgm⁻³, and 15 μgm⁻³, respectively for PM_2.5 concentrations in the ambient air, to prevent harmful health effects [20]. The movement and mixing of pollutants are influenced by school building characteristics such as age, construction materials, and ventilation, as well as factors such as occupant density per classroom volume, posing a health risk to occupants and often affecting their academic performance [21]. Building materials may behave as irritative reservoirs, causing gas-to-particle interactions and lowering the quality of the air in classrooms [22]. Occupant actions can boost pollution concentrations by re-suspending previously deposited particles and introducing new particles through clothing and shoes [23]. A vast number of studies around the world have shown the significance of indoor air quality in school contexts [24–26]. Interior PM levels are impacted by a variety of factors, including rates of air exchange and infiltration, levels of outdoor air pollution, types and intensities of interior activities, and particle aerodynamic diameters [27]. Vehicle emissions, generator fumes, bush/crop burning, and gas flaring are the primary drivers of air pollution [28]. Researchers have discovered through the use of wearable sensors to monitor the personal exposure of 250 students to NO₂ and PM_2.5 in London, that children are exposed to high amounts of pollution while at school and even more so while traveling to and from it [29]. Due to the heterogeneity in some characteristics of schools and their surroundings, concentrations of air pollutants like NO₂ might differ even across schools that are part of the same local authority [30]. Numerous cities in Europe, North America, and China have reported that NO₂ concentrations have a detrimental effect on the development of a child's lungs [31]. In infants and children, TVOC (Total Volatile Organic Compounds) can cause respiratory, allergic, or immune effects [32]. Long-term exposure to VOCs including benzene, toluene, and others raises the risk of developing cancer [33]. Wood paint solvents are widely known for emitting VOCs when applied freshly [34, 35]. Indoor CO₂ concentrations are challenging to define since they fluctuate with occupancy and ventilation rate, both of which alter with time. In the classrooms of Albanian schools during the winter, Hwang et al [36] discovered extremely poor ventilation rates, high CO₂ concentrations, and very stuffy air because of the low temperature and high occupancy. CO₂ has a range of effects, including physiologic (e.g., ventilatory stimulation), toxic (e.g., cardiac arrhythmias and convulsions), anesthetic (substantially reduced CNS activity), and fatal (severe acidosis and anoxia). The displacement of O₂ by CO₂ adds greatly to toxicity in high-level CO₂ exposure.

Children's lung development has been linked to prolonged exposure to PM_2.5 [11]. There is growing evidence that, in addition to age, gender, and height inequalities for PEF, there are variances in lung function across people of different races [37]. Pulmonary function, which is assessed in terms of lung volume changes can be useful in determining the effects of acute PM_2.5 exposure on the lungs [38]. Therefore, finding information on childhood lung function is crucial because the following evaluation and diagnosis of respiratory health. A 10 μgm⁻³ increase in acute PM₁₀ exposure was linked to a 0.19 l min⁻¹ (95% CI: 0.30, 0.09) change in PEF, according to an assessment of 22 effect estimates from 15 studies [39]. According to Wu et al [40], in Beijing, where air pollution levels were high, healthy university students' nighttime PEF readings decreased with the increasing concentration of PM_2.5. Furthermore, Rice et al [41] showed that short-term exposure to relatively low ambient PM_2.5 levels lowered the PEF values in adult men and women.

Bangladesh is the number one country in the World for the human death due to the environmental problem. It is also the topmost polluted country in the world for PM_2.5 concentrations for last five years consecutively (2018–2022). The country has been experiencing massive population growth as well as rapid industrial, commercial, infrastructure development, and also changing the basis of economy from agriculture to industry. As a result, the major components of the city environment are adversely affected resulting in continuous deterioration of air quality. The Dhaka city is also the top listed polluted capital in the World. The elderly and children have suffered the most because of the severe air pollution. Therefore, we have chosen the school children in Dhaka as our target subjects in this study.

However, we have focused on the overall school environment, collecting data on particulate matter, toxic gases, and the pulmonary function of the students. As far as we know, this is the first of its kind in Bangladesh. This study aims to characterize the exposure to a variety of particulate matter and toxic gases in school's environment in Dhaka city and their impact on children's health by comparing measured concentrations with relevant standards and suggesting ways to reduce the exposure of school children to unacceptable pollutants.

2.1. Study area and sampling sites

In total, samples were obtained from ten schools in Dhaka. Kamlapur High School (S1), New Model Bohumukhi High School (S2), University Laboratory High School (S3), Khilgaon Girls School and College (S4), Motijheel Model High School (S5), Maniknagar Model High School (S6), Maniknagar Model High School (S7), Nawabkatra Government High School (S8), Nababpur Government High School (S9) and Badda High School (S10) were the 10 schools. The schools were selected from a variety of sites in Dhaka city (figure 1). These were selected on the basis of overcrowded areas, residential areas associated with low vehicle traffic, dense traffic area, and less populated areas surrounded by plants and lakes. Each school occupies the entire structure, and each floor is solely dedicated to schoolwork. From April to November 2018, all of the schools were subjected to two-day indoor and outdoor air quality tests, as well as PEF measurements.

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All of the schools opened their doors between 7:00 and 8:00 a.m., and in the meanwhile, basic maintenance was completed. The school buildings in all cases are naturally ventilated via openable windows and doors, and they have white painted concrete walls, chalkboards, and dusters, as well as concrete cement flooring. The number of students in each classroom was between 35 and 40. The arrangement of classrooms differs from school to school. In essence, most classrooms were located on the 1st floor, but others also comprised the 2nd, 3rd, and 4th floors. Table 1 contains information about each sampling site as well as site-specific parameters.

Table 1. Description of the schools in Dhaka, Bangladesh, from April to November 2018.

Code no	Name of the school	Location and characteristics of schools	Number of selected students	Weather	Position of the measuring locations
S1	Kamlapur High School	23° 23' 0' North, 91° 13' 0' East, area: Mugda, Heavy traffic, Roadside	20	Cloudy	3rd floor and Playground
S2	New Model Bohumukhi High School	23° 45' 0' North, 90° 23' 0' East, area: Shukrabad , Heavy traffic, Roadside	25	Cloudy	3rd floor and Playground
S3	University Laboratory High School	23° 73' 40' North, 90° 39' 28' East, area: University of Dhaka, Heavy traffic, Residential Area	25	Sunny	2nd floor and Playground
S4	Khilgaon Girls School and College	23° 32' 0' North, 90° 22' 0' East, area: Khilgaon, Low traffic, Residential Area	21	Sunny	4th floor and Playground
S5	Motijheel Model High School	23° 73' 30' North, 90° 41' 72' East, area: Motijheel, Populated, Colony	25	Sunny	4th floor and Playground
S6	Maniknagar Model High School	23° 47' 0' North, 90° 20' 0' East, area: Maniknagar, low traffic, inside a lane	25	Sunny	2nd floor and Playground
S7	Ahmedbag High School	23.7426° North, 90.4308° East, area: Ahmedbagh, low traffic, inside a lane	26	Cloudy	1st floor and Playground
S8	Nawabkatra Government High School	23° 46' 37' North, 90° 23' 58' East, area: Puran Dhaka, Over-populated, inside a lane	25	Cloudy	1st floor and Playground
S9	Nababpur Government High School	23° 43' 0' North, 90° 25' 0' East area: Wari, Low traffic, Near a Bazar	25	Sunny	1st floor and Playground
S10	Badda High School	23° 46' 0' North, 90° 26' 0' East, area: Badda, Low traffic, Beside a lake	20	Sunny	1st floor and Playground

2.2. Sampling periods

2.3. Measurement and instrumentation

2.4. Relationship between indoor and outdoor particles (I/O)

The I/O ratio is widely used to represent the relationship between indoor and outdoor particles [42].

$$\begin{eqnarray}&&{\rm{I}}/{\rm{O}}={{\rm{C}}}_{{\rm{in}}}/{{\rm{C}}}_{{\rm{out}}}\end{eqnarray} \tag{ 1 }$$

The indoor and outdoor particle concentrations are represented by C_in and C_out, respectively.

2.5. Risk assessment for health

Human health risk assessment refers to the process of determining the likelihood of adverse health effects from contaminated environment exposure. The chronic daily intake (CDI) was computed using equation (2), and the exposure was assessed by measuring how much PM₁₀ and PM_2.5 impacted human health [43].

$$\begin{eqnarray}&&{\rm{CDI}}=\displaystyle \frac{C\,\times IR\,\times ET\times EF\times ED}{BW\,\times AT}\end{eqnarray} \tag{ 2 }$$

Where, C is the contaminant concentration (μgm⁻³), IR is the average inhalation rate (m³/day), ET is the exposure time (hours/ day), ED is the exposure duration for scenario (years), EF is the exposure frequency, BW is the body weight (kg), and AT is the average time for a lifetime (days). The hazard quotient (HQ) was calculated by using equation (3).

$$\begin{eqnarray}&&{\rm{HQ}}=\displaystyle \frac{CDI}{Rfd}\end{eqnarray} \tag{ 3 }$$

Where, Rfd is the inhalation reference dose (μg/kg/day) sought from WHO recommended values. To calculate the senses of control, the non-hazard level is HQ < 1, and the hazard level is HQ > 1 [43].

3.1. Temporal trends of particulate matter concentrations

The study took place over six months (April 2018 to October 2018) in indoor and outdoor schools in Dhaka city, Bangladesh. Table A1 (Appendix-A) summarizes the indoor and outdoor particulate matter concentrations (average, standard deviation, and I/O ratio) in each school area. During the study period, the four-hour average (indoor and outdoor) PM_2.5 concentrations for all of the schools were 32.8 ± 7.8 μgm⁻³ and 35.6 ± 12.4 μgm⁻³, respectively. The concentration of PM_2.5 both indoors and outdoors varied slightly (figure 2). The average indoor PM_2.5 concentrations for roadsides ranged from 27.8 ± 20.3 to 64.9 ± 35.9 μgm⁻³, for residential sites ranged from 23.0 ± 13.7 to 40.7 ± 17.9 μgm⁻³, and for the schools that situated inside a lane ranged from 14.4 ± 1.9 to 43.3 ± 4.8 μgm⁻³. In case of outdoor PM_2.5 concentrations, for roadsides it varied from 17.3 ± 8.9 μgm⁻³ to 46.9 ± 32.4 μgm⁻³, for residential sites varied from 10.7 ± 3.7 μgm⁻³ to 53.9 ± 21.8 μgm⁻³ and for the schools that situated inside a lane ranged from 16.0 ± 4.3 μgm⁻³ to 48.7 ± 37.8 μgm⁻³. There was significant variation in the concentration of PM₁₀ indoors and outdoors. The average indoor PM₁₀ concentration for roadsides ranged from 155.5 ± 123.9 to 469.7 ± 352.9 μgm⁻³, for residential sites ranged from 110.3 ± 72.6 to 130.8 ± 129.1 μgm⁻³, and for the schools situated inside a lane ranged from 33.8 ± 13.8 to 110.6 ± 57.9 μgm⁻³. On the other hand, the outdoor PM₁₀ concentration for roadsides ranged from 70.1 ± 38.9 to 402.2 ± 219.5 μgm⁻³, for residential sites ranged from 56.6 ± 42.2 to 313.3 ± 228.2 μgm⁻³ and for schools located within a lane ranged from 64.1 ± 50.7 to 157.4 ± 121.6 μgm⁻³.

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3.2. Indoor and outdoor sources contribution to PM

Indoor/outdoor ratios (I/O) have been used for a long time to assess the difference between indoor and outdoor concentrations as an indicator of indoor sources [44].

Figure 3(a) shows the average I/O ratio of PM varies from 0.1 to 1.8. It observed that there were in total 4 schools (S3, S4, S5, and S9) that gave I/O ratio less than 1 for PM₁₀, whereas there are in total 3 schools (S5, S6, S9) which showed an I/O ratio less than 1 for PM_1.0 and PM_2.5. Due to the location of these schools, their outdoor air is more polluted in comparison with the indoor air. The I/O ratios of PM₁₀ were highest for S2 and S10 with the values of 1.8 and 1.3 whereas Badda high school (S10) had the highest I/O ratio of PM_2.5 with the range of 1.3–2.6.

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Figures 3(a), (b), (c) pointed a weak relationship between indoor and outdoor PM concentrations. The strongest correlation between PM_1.0, PM_2.5, and PM₁₀ was reported in PM_1.0 (R² = 0.372), indicating that outdoor concentrations can only explain 37% of the variation in indoor concentrations. The lowest correlation found in PM_2.5 (R² = 0.007) and PM₁₀ (R² = 0.021) indicate that the indoor and outdoor PM concentration was quite independent of each other. Because of their smaller size and lower mass, PM_1.0 particles can float upwards or disperse further, but they can also fit through unsealed gaps in windows and doors, among other things. As a result, most of them can enter the classroom from the school playground causing an impact on indoor particle concentration. For PM₁₀, the greater source of PM₁₀ in indoor environment is caused due to the number of students, poor ventilation system, dust in shoes, particle from chalk and other activities in the classroom.

3.3. Temporal trends of NO₂, CO_2, and TVOC concentrations

NO₂, CO_2, and TVOC levels were measured on an hourly basis in selected schools in Dhaka city (figure 4). All the gases are collected for four hours including the first two hours in the indoor environment and the remaining hours in the outdoor environment. The NO₂ concentration ranged from 0.061 to 0.102 ppm. It had been seen that the concentration of NO₂ was quite high in the outdoor environment (9:30 to 11:30 am) of S6 with the value of 0.122 ppm, because of the presence of the cooking stove beside the playground. The lowest concentration was observed at S4 with the average value of 0.061 ppm, which is placed in a residential area related to a very low amount of traffic.

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The drop in TVOC concentration table B1 (Appendix-B) during the morning hours at all sites could be attributed to the opening of floor doors and windows for various causes. Because of the temporary increase in ventilation, the TVOC concentration inside the floor may have been diluted. The TVOC concentration was significantly higher in S4 (1439.250 ppm) than in other sites, which could be attributed to the painting of a new building adjacent to the playground during the sampling period. The following table also showed that the indoor concentration of TVOC was very high at S7 with the average value 1994 ppm. This school was placed inside a busy lane. Many tea stalls also welding shops were situated around the school area. The classroom of the school was placed on the 1st floor where TVOC concentration was measured. Thus, it was easily affected by the adjacent tea stalls and welding shop attributed to the high value of TVOC.

The measurements revealed that CO₂ concentrations increased in the early morning and decreased before lunch. The highest concentrations are caused by insufficient ventilation (closed windows) in the morning (1135.0 ppm). Following the start of class, the windows were opened, and CO₂ concentrations began to fall until early or late afternoon when they settled near the lowest amount (550.0 ppm).

3.4. The relationship between fine particulate matter and peak flow rate

The baseline survey targeted around 250 students (115 boys and 135 girls) of class 5 to class 7 around 9–12 years old of 10 schools in Dhaka City (table 2). Children were randomly selected from each classroom to understand the average health difficulties of the students while avoiding a group of students with a particular illness. All students in these classes were given a structured questionnaire (age, gender, health issues) and told to fill it out with their parents and submit it to their respective class teachers. All of the students were instructed on how to apply Peak Flow Meter. During sampling, their health conditions are also collected. It was observed that most of the students suffered from cough and respiratory problems. The high concentration of particulate matter in every school is mainly responsible for this issue. The status of other health problems was given in table C1 (Appendix-C). From the ages of 9 to 12 years, there was no significant difference in body height and weight between boys and girls. The selection of the sampling location ensures that it completely encompasses the entire city of Dhaka.

Table 2. Participants number, average peak flow rate and related data obtained in this research work.

School	Location	Participants	Number of boys	Number of girls	Average peak flow rate (L/min)	a PM1.0 (μgm−3)	a PM2.5 (μgm−3)
S1	Roadsides	20	8	12	269.8	24.57	55.92
S2	Roadsides	27	15	12	282.4	10.51	22.56
S3	Residential sites	25	14	11	291.8	21.985	34.06
S4	Residential sites	25	—	25	278.3	10.735	28.515
S5	Residential sites	25	—	25	293.0	22.885	48.535
S6	Inside a lane	25	10	15	309.0	11.1	15.22
S7	Inside a lane	26	16	10	296.7	33.83	49.645
S8	Beside local market	26	26	—	263.8	28.31	37.16
S9	Beside local market	27	15	12	271.4	17.285	38.71
S10	Inside a lane	24	11	13	290.5	24.57	55.92

^a Here the overall concentrations (indoor and outdoor) of PM_1.0 and PM_2.5 had been given.

Figure 5 shows the link between particulate matter and lung function of students. According to the associations between indoor-outdoor four-hour averages of PM_1.0 and PM_2.5 concentrations and lung function measures among school occupants, it was observed that in most schools, the average value of the Peak Expiratory Flow Meter is negatively associated with increasing exposure. The average PEF rate for boys and girls in each school is listed in table E.1 (Appendix-E). Also using linear regression figure D1 (Appendix-D), we found that the association between PEF and PM_1.0, PM_2.5 data is very weak. The link between particulate matter and peak expiratory flow rate is not statistically significant, according to the results of the ANOVA test, which showed that the p-values for PM_1.0 (0.53) and PM_2.5 (0.19) are more than 0.05.

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3.5. Hazard quotient assessment and associated health risks

The Hazard Quotient (HQ) calculated for school children at different locations in Dhaka city, Bangladesh was shown in figure 6. The results of 250 participants studying in schools were collected to further determination of health risks. The ages of subjects enrolled were between 9 to 12 years including (60.5%) for girls whereas the rest of the students are boys. Details of average body weight are obtained from [45]. The Exposure frequency days yearly were estimated as the active period that students have to attend school. Data used in this calculation are tabulated in table S4. The mean HQ for PM₁₀ (2.5 ± 2.2 for indoor and 3.6 ± 2.6 for outdoor) and PM_2.5 (1.8 ± 0.8 for indoor and 1.9 ± 1.0 for outdoor) among all participants was >1, indicating a risk to human health that is unacceptable.

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We collected the particulate matter data from ten schools in Dhaka city and the observations indicated that indoor and outdoor PM₁₀ concentrations in majority of the schools were above the WHO 2021 recommended standard value of 45 μgm⁻³ over a 24 h period for PM₁₀. With the exception of S6, the indoor PM_2.5 concentrations of all schools did not meet the WHO 24 h PM_2.5 (15 μgm⁻³) recommended value, WHO 2021. The outdoor concentrations of PM_1.0, PM_2.5, and PM₁₀ were low at S10, which is adjacent to a lake, with limited traffic. In addition, the highest concentration of PM_1.0 was observed at S7 which is in an area where local tea stalls are placed beside the school playground. In addition, Mugda bishow road, one of the busiest places, had the greatest indoor concentration of PM_2.5 and PM₁₀. The highest outdoor concentration of PM₁₀ is at Motijheel (S5) which is located in a residential area, but there was a large amount of dust in the school playground, and also the area of the playground is bounded by buildings rather than an open space. S1 and S9 exhibited a higher outdoor PM₁₀ concentration due to the high number of vehicles. The average outdoor concentration in most schools was higher than the average indoor concentration. These values are also higher than those reported in school-based research in Texas [46], where the outdoor concentration was 13.4 μgm⁻³, and in Sweden [47] where the outdoor concentration was 9.7 μgm³.

The I/O ratios of PM were determined to quantify the impact of outdoor air and indoor sources on indoor air quality. The I/O ratio can vary significantly depending on factors such as location, building design, and inhabitant activities [48]. The I/O ratio varies from site to site depending on many influencing factors such as indoor source, ventilation pattern, different household activities, penetration factor, particle deposition rate, and outdoor concentration. The I/O ratios of PM₁₀ were highest in S2 and S10, which used chalk duster on the blackboard to instruct their students in the classroom, while the rest of the schools used black marker on the white board to instruct their students in the classroom. The majority of them have more students in the classroom and a poor ventilation system, both of which affect the concentration of particles inside. In contrast, the I/O ratio of PM_1.0, PM_2.5, and PM₁₀ are quite low for S5, S6, and S9. Because interior PM levels were more likely to be influenced by indoor sources such as the presence of students and the intensity of their indoor activities, it was discovered that the number of students at these schools was relatively low in comparison to the classroom size. S10 had the highest I/O ratio of PM_2.5 which also indicate that the outdoor PM_2.5 concentration of the school is quite low in comparison with the indoor PM_2.5 concentrations. Because the school was built beside a lake, there was less activities or emission of particulate matter [49] that helped to improve the outdoor environment. Ventilation and infiltration have a role in the transfer of contaminants from the outdoors to the inside environment. Air contaminants from the outdoors can enter the inside environment in a variety of ways, diluting or accumulating depending on the ventilation condition.

Both outdoor and indoor factors may have an impact on the increasing NO₂ concentration. Previous research has found that NO₂ concentrations in schools in urban, industrial, and rural areas of Central and Southern Spain were as follows: In rural areas, 0.004 ppm for kindergarten and 0.005 ppm for primary classrooms; in urban areas, 0.021 ppm for kindergarten and 0.015 ppm for primary classrooms; and in industrial areas, 0.013 ppm for kindergarten and 0.014 ppm for primary classrooms. The median NO₂ values in the outdoor environment, on the other hand, were 0.001 ppm, 0.007 ppm, and 0.005 ppm, respectively, for rural, urban, and industrial areas [50]. In schools of Dhaka city, the gas stoves at the canteen, chalk dust, and road traffic are the main source of NO₂. Concentrations of NO₂ are varied due to the daily traffic pattern. Traffic densities were measured manually. Previous studied also showed that traffic density has very high correlation with atmospheric particulate pollution [51]. It had been seen that the concentration of NO₂ was quite high in the outdoor environment (9:30 to 11:30 am) of S6 because of the presence of the cooking stove beside the playground. The lowest concentration was observed at S4 which is placed in a residential area related to a very low amount of traffic. It is well known that when paint solvents are applied freshly, they emit VOCs into the air [34]. The majority of urethane coating and paint solvents are bonded to urethane formaldehyde, causing formaldehyde to be released into the atmosphere and causing pollution [52].

Because of their smaller size, particulate materials (PM_1.0 and PM_2.5) have a greater surface area-to-mass ratio of the tissue in which they can move, as well as a high probability of contact, oxidative stress, and inflammation, which occurs in extrapulmonary organs [53]. PEF levels are used to assess how effectively the lungs are functioning and responding to treatment. Furthermore, several students experienced cold-related health issues, implying that there is an effect of air pollution on their breathing. The child specialist would be preferred to provide any type of treatment based on the child's health condition, while we only recommend ways to improve the school environment. Notably, the current findings revealed that inhalation exposure to various outdoor air pollutants, as well as indoor air pollutants, poses considerable danger. The weak linear regression value of the association between PEF and PM_1.0, and PM_2.5 data means that the lung function is quite good when the PM exposure rate is low. It also found that the average PEF value is low and indicates that lung function decreases when the particulate concentration is high. Chen et al [54] found that higher exposure to PM led to reduced lung function. The level of physical activity during exposure and the individuals' prior exposure to traffic-related air pollution both affect the relationships between different pollutant exposures and respiratory measurements [55]. The literature contains a variety of reference values that vary by demographic, ethnic group, age, sex, height, and weight of the patient. For each age and sex, we compared the mean PEF values of Bangladeshi school children to those of Turkish (N-2,791), British (N-339), Chinese (N-3,196), Irish (N-2,828) and Greek (N-522) children. In most cases, the PEF values of Bangladeshi school children for both sexes according to age were lower than those of Chinese, Irish, Turkish, and British children [37]. Controlling PM sources, increasing ventilation, and employing air cleaners are all examples of ways to improve school classrooms and playgrounds [56]. In this study, the hazard quotient (HQ) is calculated to evaluate the potential for children (non-cancer health hazards) to occur from exposure to a contaminant with available non-cancer health guidelines [57]. HQs less than 1 indicate a non-cancer hazard should not be an issue. When an HQ is greater than 1, retain those contaminants and conduct an in-depth toxicological effects analysis. In other words, an HQ above 1 means there is an exceedance of the non-cancer health guideline.

Air quality and its relationship with the health of the school children were investigated in the highly populated and populated megacity Dhaka, Bangladesh from April to November 2018. Relatively high particulate matter concentration was observed at the school premises. A poor correlation was obtained between indoor and outdoor particulate matter. Indoor and outdoor NO₂, TVOC, and CO₂ concentrations at ten different schools revealed that the concentrations were raised in schools near the road including an overcrowded and high-traffic density region. The HQ for PM₁₀ and PM_2.5 had a moderate health risk of 9 to 12 years aged school children in Dhaka. A negative correlation between the concentrations of PM_1.0, and PM_2.5 with the peak flow meter reading were found among the children in ten different schools in Dhaka. The very high indoor PM levels and increased inhalation of fine particulate matter may be clogging the airways and lowering lung performance. The study has several limitations (e.g., number of schools, students, and sampling time/period) as it was a pilot study. In future, longer sampling periods with more students form many schools at different seasons (e.g., winter, monsoon) will be needed with primary health data of the students. According to our study, we believe that schools in Dhaka city need to learn more about air pollution. The school grounds need to have a healthy atmosphere because students spend most of the time there. However, the policy makers need to take immediate actions to improve the air quality situations in the school premises in Dhaka, Bangladesh by changing the design of the school building, classroom materials, and emission control from vehicles with proper traffic management during children pick and drop off. It might also be possible to continuously monitor the school environment by setting up a real-time particulate matter detector for 24 h.

Authors acknowledge the support from all the school authorities for allowing us to conduct the sampling in their premises. Authors also acknowledge the financial support for the instruments used in this study from the Ministry of Education, The Government Republic of Bangladesh (Project no.: PS 14138).

The data that support the findings of this study are available upon reasonable request from the authors.