Abstract

Background. Air pollution exposure has a detrimental effect on children who spend more than 17% of their weekdays inside a school building. The purpose of this study is to look into the effects of particulate matter (PM) and toxic gases on health of the school children. Between April and November 2018, samples were collected in real time from ten different schools (both indoor and outdoor) over four hours on two consecutive days at each school. During the first two hours, when students were present in the classroom, measurements were conducted inside the classroom. After that the measurements were conducted outside the classroom but within the school premises - when students were playing on the playground or eating breakfast outside of classroom. Method. To evaluate the impact of air pollution, 250 students (on average 20 students from each school) aged from 9 to 12 were selected from ten schools. Automatic monitors (AEROCET 531S, USA) were employed to measure PM1.0, PM2.5, and PM10 concentrations. NO2, TVOC, and CO2 concentrations were measured using an AEROQUAL (500S, New Zealand), and the respiratory rate is measured by BSMI Peak Flow Meter (Made: BSMI, Origin: China). Monitors were placed at about 2.0 meters above the floor at breathing height and no student wore the sensors. The ANOVA test was conducted to see the statistical significance between air quality parameters and peak flow meter readings. Results. The mean ± standard deviation of PM1.0, PM2.5, and PM10 concentrations were 19.1 ± 3.6, 34.2 ± 10.1, and 131.3 ± 58.6 μgm−3, respectively. PM2.5 and PM10 concentrations exceeded WHO standards (15 and 45 μgm−3 of 24 h) by 2.3 and 2.9 times. The highest concentrations of toxic gases were found on school campuses where vehicle densities (measured manually) were high. The mean Hazard Quotient (HQ) for PM10 (2.5 ± 2.2 indoor; 3.6 ± 2.6 outdoor) and PM2.5 (1.8 ± 0.8 indoor; 1.9 ± 1.0 outdoor) among all participating students was >1 indicating an unacceptable risk for human health. Lung function associated with the PEF value has a negative correlation with PM1.0 and PM2.5 concentrations in most cases. Conclusions. The findings of this study are useful in gaining a general understanding of the school environment in Dhaka. It aimed to understand how children were personally exposed in school and to develop effective control strategies to mitigate negative effects.

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