1. Introduction
Many countries have enacted school health acts to protect growing children from the risk of air pollution in the classroom where children spend up to 8 hours of their day [1]. Fine particulate matters and carbonaceous materials are critical pollutants found in urban schools. Carbonaceous matters attached to suspended particles in the air are classified into organic carbon (OC) and elemental carbon (EC) which are major components of ambient atmospheric aerosols that originate from natural and anthropogenic combustion sources. EC can also be subdivided into black carbon and brown carbon. Airborne carbons are obviously correlated with PM2.5, which is classified as a carcinogen [2]. In addition to PM2.5, this carbonaceous matter is of broad concern due to its significant impact on students’ health, particularly in schools [3]. Consistent exposure to black carbon causes an increased risk of developing respiratory and cardiovascular ailments [4]. Long-term exposure to a black carbon-rich atmosphere may induce an inflammatory response, cause respiratory diseases, asthma, cardiovascular disease and decrease lung function and intellectual quality. Children, whose respiratory systems are not fully developed, are particularly susceptible to air pollution.
Black carbon found in urban areas is emitted mainly by high-temperature combustion processes, including diesel engines and biomass combustion [5]. The contribution of biomass burning or open burning of carbonaceous materials in the atmosphere show high emission factors, but automobiles are a dominant source in large cities such as Seoul, the capital city of Korea. A study on the vertical distribution revealed that black carbon is mainly distributed at low altitudes of less than 40 m in the urban atmosphere. Since school buildings in Korea are typically five stories or less, black carbon in the surrounding environment directly affects indoor air quality (IAQ) through wall cracks or gaps of windows and doors [1]. Black carbon is a valuable additional air quality indicator to study the health risks associated with combustion-related activities [6].
Although studies on the atmospheric black carbons started in the 1990s with various investigations of source apportion and health effects, studies on public spaces including schools have rarely been carried out due to limited access to research works [7]. A work fulfilled at 39 primary schools of Barcelona in Spain found through a real-time measurement that indoor black carbon was related to outdoor pollution, particularly traffic conditions [8]. Exposure to traffic-related air pollution is associated with a variety of short- and long-term health effects, and most urban schools are adjacent to roads [9]. The speed limit for automobiles around schools in Korea is 30 km/hr, and there are also 20-cm-high speed humps in front of main open gates, which leads to high emissions of potential black carbon (0.03–0.27 mg/km) [10]. Carbon particles directly emitted from internal combustion engines such as automobiles are very tiny, around 50 nm in size, and these are associated with an increase in genotoxicity (DNA damage) [11].
Although black carbon in the atmosphere is a potential hazard to humans due to its chemical composition, recent attention is focused more on solar radiation related to global warming [12]. There have been a limited number of studies concerning carbonaceous pollutants around school environments [13]. Thus, this study evaluated relative concentrations of carbonaceous materials and PMs, while paying attention to school class hours and break time. In order to increase our understanding of the relationship between carbon and PM according to students’ activities, real-time monitoring and cumulative mass analysis of particulate matters by size were concurrently carried out.
2. Method
2.1. Site Description and Sampling
The study was conducted in 24 schools located in the west region of the country including Seoul, Incheon, Gyeonggi (Suwon, Yongin, Anyang, Yangju, Hwasung, Pyungtaek, and Paju), Chungnam (Dangjin, and Seochon) and Chungbuk (Chungju), as depicted in Fig. 1. This area includes large industrial complexes, and places with direct impacts of long-distance air pollution even from inland Asia. In particular, there are several large-scale coal power plants in Dangjin and Seochon. Seoul, Incheon and Gyeonggi are the areas where more than half of the population is concentrated with heavy traffic (Table 1). The government has specially managed the air quality in these areas by establishing the Metropolitan Air Quality Management Office. Most test schools were adjacent to roads with more than 4 lanes, and pathways are paved.
Three classrooms were selected for each school. Field sampling and measurements were carried out at 5–6 schools every semester from the 1st semester of 2020 (March to the mid of July) to the 1st semester of 2022. Particulate matters were collected for 8 hours a day from 8:00 in the morning to 16:00 in the afternoon. Sampling was performed at the same time both indoors (in a classroom with children) and outdoors (at the playground) for 8 hours a day for 4 weekdays a week. This period included the pandemic of COVID-19, particularly in the 2nd semester of 2020 and 1st semester of 2021, in which class activities were partially restricted. This study was carried out only in schools with normal timetables.
Indoor PM10 and PM2.5 were sampled by four mini-volume air samplers with impactors classifying 10 μm and 2.5 μm particulates, respectively (Model BMW 2500, Total Eng., Seoul, Korea) (Fig. 2). A Teflon filter (Anow, Beijing, China) for quantitative concentration and a quartz filter for carbons (47 mm diameter; QM-A1851, Whatman, England) were inserted into the sampler of particulate matters. Filters were kept in an electric desiccator (The electric dehumidification system, Korea Ace Sci., Daejeon, Korea) at constant temperature (20±1°C) and humidity (45±5%). The dust was weighed three times using an analytical balance (Dry active, Kastech, England) with a sensitivity of 0.001 mg, and the results were averaged. Quartz filters were baked at 700°C for 1 hour, and then reserved in a petri dish until sampling. After collection, particulate matters were sealed and stored in a freezer for analysis. During the sampling periods, personal operation of mechanical ventilation by central control systems or natural ventilation through windows in the classroom was allowed without any arbitrary requests. As seen in Fig. 2(b), Outdoor sampling was performed with the same equipment as indoor sampling on a podium usually about 5 m away from the classroom building and 1.5 m high, in order to avoid the direct influence of playground surface dust.
2.2. Measurement and Analysis
While the mini-volume air sampler provides the average weight concentration during the sampling period, the light scattering device can measure airborne dust particles by size. Simultaneously with gravimetric sampling, real-time concentration of particulate matters was monitored every 10 minutes in the range from 0.253 μm to 35.13 μm using portable aerosol spectrometers (PAS) (11-D/11-A/1.109, Grimm Aerosol Technik, Germany), which are one of the most reliable light scattering device for airborne particle analysis. They were periodically calibrated by the Korean Testing Laboratory, an official national institute [14]. In addition, to ensure reliable PM readings, simultaneous pre-measuring for 15 minutes at the same place was fulfilled prior to the actual measurement in all schools. The instruments showed reproducibility within 30% error. This device consists of 31 channels and also provides cumulated data including PM10, PM2.5 and PM1.0.
Black carbon (BC) concentration was monitored concurrently inside and outside using two portable aethalometers (AE51, AethLabs, San Francisco, USA) with a 1-min time resolution. This device provides data of equivalent black carbon (eBC in μg/m3) derived from absorption values [15]. Thus, absorption values were converted to the eBC concentration by correction against in-situ and simultaneous off-line measurements of EC determined by the thermal-optical transmission method on particulate matter samples collected on quartz filters according to the NIOSH thermal protocol. The data were automatically stored in the instrument, and regularly downloaded to a PC for calculations.
The bulk carbonaceous content of the PM2.5 such as OC and EC were quantified with a TOT analyzer (Thermal/Optical Transmittance, Sunset Lab., Tigard, USA). The concentration of OC was measured in a helium atmosphere at 31°C to 840°C, and the EC was measured in an oxygen atmosphere at 550°C to 870°C. One punch of 1.5 cm2 filter paper with dust was directly analyzed following the procedure reported in the protocol of the National Institute for Occupational Safety & Health (NIOSH 5040) [16]. The outdoor meteorological conditions of each school such as temperature and relative humidity were recorded for data evaluation. The precision of the OC and EC measurements was 0.95 or higher for each sample as a result of two repeated analyses of the field samples. Accuracy was estimated with a carbon content of 50 μg per artificially manufactured sucrose, and the difference was less than 5% for seven repetitions. The method detection limits for OC and EC concentrations were 3.939 and 0.000 μg/cm2, respectively, calculated as three times of the standard deviation of a blank sample [14].
2.3. Statistical Analysis
Statistical analysis of real-time indoor and outdoor monitoring data was performed using SPSS, version 22 (IBM Inc.). The statistical significance was set at p ≤ 0.05, and marginal significance was at 0.05 < p ≤ 0.1. Prior to analysis, normality was verified for fine dust and BC concentration data using the Kolmogorov-Smirnov test. Since most of the data did not follow a normal distribution, the correlation analysis was performed using Spearman's correlation test in this study [17]. Paired-Student t-tests were performed to examine differences between paired measurements, for example, concentrations based on PAS and gravimetric PM measurements, indoor to outdoor ratio for particulate size, and eBC to PM ratio. Spearman's correlation coefficients were computed to examine correlations among indoor and outdoor measurements of PM and eBC.
3. Results and Discussion
3.1. Concentration Distribution of Particulate Pollutants in Schools
3.1.1. Overall distribution of PM10 and PM2.5
The weight average concentration of fine dust inside and outside the classroom was evaluated by a gravimetric method with sampling during class-hours. A light scattering method was used to observe the real-time variation. As seen in Fig. 3, which displays data collected from all schools, light scattering measurements with high time resolution reflected instantaneous variation and showed wider distributions than the gravimetric method for both PM10 and PM2.5 although some infrequently observed outlier data points were excluded. Students' activity as well as opening frequency of doors or windows could lead to instantaneous variation of suspended particulate matters inside. The resuspension of particles previously deposited on the floor by walking students is a significant source of indoor particulate matter. It directly influences the level of PM10 rather than PM2.5 in the classroom [18,19]. In addition, re-entrainment into the air of particles adhered in children's clothes or bodies cannot be ignored. In accordance, the difference between the two measurement methods was larger in the classroom than outside, particularly for PM10. Nevertheless, the average values for all school classrooms were similar for both methods. The present national standard requires time-consuming weight-based data, but it was confirmed that even light scattering devices providing a relatively rapid response could show reliable values.
3.1.2. Size distribution of particulate matters
In general, indoor fine dust originated from outside through gaps of windows and doors, and cracks in a building, but some were directly generated from the inside [10]. Since school classrooms do not have combustion sources such as cooking or smoking, the indoor concentration is mainly determined by the outdoor air quality, the ventilation rate, and the student activity. Fig. 4 shows the summarized average ratio of indoor to outdoor (I/O) particulate matters focusing on the presence of students. When students were in the classroom during the class hours (occupied), the I/O value increased as the dust particle size increased.
After school hours from 4 pm to 8 am the next day (vacant), the smaller the size showed the higher I/O values. The I/O ratio was less than 1.0 for most particulates smaller than 10 μm, and they decreased with increasing particulate size because there would be no resuspension of settled particles by students. However, the I/O ratio temporarily increased in the fine regime of 0.2 to 0.9 μm. In particular, in the size range below 0.4 μm, indoor concentration was higher when students were present than when there were no students inside. In the case of particles smaller than 0.4 μm, the deviation range was much larger depending on the school than when occupied. This indicates that the characteristics of fine dust were directly affected by the external air quality.
3.2. Distribution of Carbonaceous Materials with Particulate Matter
Table 2 summarizes the results of carbonaceous materials contained in particulate matters, analyzed in 80 classrooms. The average PM2.5 concentration was 22.7±8.2 μg/m3 and 34.0±14.5 μg/m3 in classrooms and playgrounds. From results of the t-test statistical method, PM2.5, PM10, and EC concentration of classrooms during the sampling period was significantly lower than the outdoor (p < 0.001). But the average OC concentration was 9.6±2.2 μg/m3 and 6.8±1.7 μg/m3 in classrooms and playgrounds, indicating significantly higher values indoors than outdoors (p < 0.001). In comparison, OC occupied 42.3% and 20% of PM2.5 indoors and outdoors, respectively. This indicates the presence of potential indoor OC sources, such as SVOCs (semi-volatile organic compounds) emitted from school supplies, building interior materials, personal sanitation items, furniture and electronics [20].
The ratio of OC/EC depends on emission source and season. In domestic atmospheres high values are usually found in spring and winter. The 8-hr average outdoor OC/EC was 8.5 for 24 schools, which was higher than other works [21]. Indoor OC/EC ranged from 10.4 to 18.7 depending on school, with an average of 13.7 for the entire classroom. The indoor average absolute concentration of EC (0.7 μg/m3) was lower than that of outdoor air (0.8 μg/m3), but the relative value to PM2.5 (EC/PM2.5) was higher in the classroom (3.1). This can be inferred because EC (behaving as PM1.0) had a higher rate of inflow into the room than PM2.5 and stayed in the classroom for a long time. To verify the effect of outdoor air on indoor carbonaceous particulate matters, respective relationships between indoors and outdoors were investigated through scatter plots shown in Fig. 5. The indoor EC increased linearly with the outdoor (R2 = 0.73, p < 0.01), which implies approximately 88% of indoor EC infiltrated from the outside. The R2 of OC was low at 0.31, but a low p-value (less than 0.01) indicates a significant effect of outdoor OC on the indoor OC concentration. Also, a high intercept of y-axis with 4.76 μg/m3 implies greater indoor generation of OC than EC.
3.3. Real-time Analysis of Black Carbon and Particulate Matters
Children in elementary schools in large cities in Korea are exposed to high concentrations of black carbon and fine dust [22]. To understand the relationship between black carbon and the fine dust in the air, eBC data obtained in real-time were considered together with particulate matters measured by the light scattering method. The obtained data were averaged at 10-minute intervals for correlation evaluation. As can be seen from the statistical analysis in Table 3, the average value of indoor concentration (eBC) for all schools was 1.04±0.37 μg/m3, while the outdoor average was 1.42±0.39 μg/m3, showing higher values outdoors than indoors with (p < 0.05). This is more obvious in a better selection of data with 99.99% confidence interval, exhibiting 1.0–1.08 μg/m3 and 1.36–1.49 μg/m3 for indoor and outdoor BC, respectively. This indoor level was lower than that observed in a few previous school studies published in Korea (1.93±2.45 μg/m3) [22]; in Italy (1.9–13.9 μg/m3) [23]; in Spain (1.3 μg/m3 indoor) [8]; in Rwanda (8.15 μg/m3) [9]. These data can be used figure out the approximate environmental condition around schools for this study.
While the absolute concentration of black carbon was higher outdoors than indoors, the relative value of eBC/PM2.5 was higher indoors (5.3) than outdoors (5.0). Since most particulate black carbons are distributed below 1 μm, they tend to behave as PM1.0 in air. Thus, the penetration rate of black carbon through building gaps is probably higher than PM2.5, and the residence time in the indoor space is relatively long. As a result, the amount of indoor black carbon relative to PM1.0 (7.8) was higher than the value of PM2.5 (5.3). The size characteristics of black carbon were indirectly identified through the correlation of real-time concentrations between fine dust and black carbons, and the calculated Spearman's correlation is plotted in Fig. 6. The Spearman's correlation coefficient (Spearman's rho) used in this analysis indicates a moderate quantitative linear relationship at 0.3–0.7, and a strong quantitative linear relationship at 0.7–1.0, like the Pearson correlation coefficient (R) [24]. Although there were some differences depending on classroom and measurement time, the maximum correlation of indoor eBC appeared in the range of 1.0 μm or less (site-specific maximum correlation coefficient: 0.67–0.97). Combustible carbon components with a size of several tens of nanometers or less do not only exist attached to fine particulate matters in the air, but also exist as primary particles [25]. Thus, they can be discovered mainly in tiny modes even among suspended particles.
High site-specific maximum correlation coefficients (0.65–0.97) were found outdoors for a relatively wide range of particle sizes of less than 2.5 μm. On comprehensive analysis of all 24 school data, outdoor black carbon was highly correlated with 0.3 μm-particles having a Spearman's rho (0.716), and indoor BC had the highest coefficient (0.755) with 0.6 μm-particles. A domestic investigation of outdoor testing also showed a high correlation with BC at the same particle size (0.3 μm) [26].
3.4. Concentration of eBC during Class Hours
As discussed above, the I/O of particulate matters increased as the particle size increased during class (defined as 'classrooms are occupied'), and the I/O ratio for after school ('classrooms are vacant') showed a large value for small particles as seen in Fig. 7. Paired t-tests indicated that the I/O ratio of eBC for occupied classrooms (0.92) was significantly (p < 0.05) higher than the vacant classrooms (0.92 versus 0.73). In vacant classrooms, the I/O ratio of eBC was greater than PM1.0, implying that the size of black carbon present in school classrooms may be less than 1.0 μm. While there were students in the classroom, the inside amount was relatively higher than the outside, particularly for PM10. Black carbon was also more widely distributed in occupied classrooms despite spatial behavior close to PM1.0. Consequently, the distribution width of the I/O ratio of eBC was wider than that of particulate matters. This means that the black carbon concentration in a classroom can vary greatly depending on the window opening or students' activity under the condition without emission sources inside.
3.5. Comparison of eBC Level between High Traffic and Residential Areas
To examine the traffic effect, test schools were classified into traffic and residential areas in suburbs based on the land cover type in a nearby area of 1 km × 1 km. Due to the nature of urban areas, more than 50% of schools were located close to a main road. According to references investigating combustion activities in the atmosphere, the relative values of NO3−/SO42− determine the mobile sources of automobiles or stationary sources including industrial combustion and open burning [27]. Thus, in this work, average values larger than 2.0 for the NO3−/SO42− ratio were chosen as traffic zones (which included 5 schools), and the schools where values were less than 1.0 on average were identified as for residential (3 schools).
As generally expected, Fig. 8 shows a high concentration (avg. 2.7 μg/m3) in the morning and low concentration (avg. 1.5) in the afternoon at traffic areas, respectively. Lower levels were found in residential areas, 2.2 μg/m3 and 0.6 μg/m3 in the morning and afternoon, respectively. In the classroom, the absolute concentration was distributed from 0.3 to 0.8 μg/m3 in the residential area, and 1.3 to 2.2 μg/m3 in the traffic area. The value of indoor eBC/PM2.5 was maintained above 0.04 in traffic areas, in which particularly high in the morning rush hours, but it was mostly below 0.04 in residential areas. The high levels of eBC/PM2.5 in the traffic areas are probably due to the large amount of black carbon particles coming in from outside with students. The size dependency of eBC also cannot be ignored. When subdividing by size, black carbon in traffic areas depends more on 0.3 μm particles, and residential areas were more affected by 0.9 μm particles. Thus, tiny particulate black carbons may be apt to penetrate indoors.
4. Conclusions
The present study evaluated particulate matters and carbonaceous materials in the indoor and outdoor air for 24 urban schools. In order to evaluate practical indoor air quality, this study was carried out without intentional control for the classroom condition. The average PM2.5 and PM10 concentrations in classrooms (22.7 μg/m3 and 43.3 μg/m3) were lower than outdoors (34.0 μg/m3 and 54.3 μg/m3) on a gravimetric basis. Airborne carbonaceous matter, which is particularly harmful for children, was found to be related particularly to submicron particulate matters. As OCs in the classroom may contain potential gaseous hydrocarbons [28], the concentration of organic carbons was 13.7 times higher than elemental carbons. The mean indoor and outdoor concentrations of black carbon monitored in real-time were 1.04 and 1.42, respectively. Indoor black carbon was highly associated with airborne PM1.0, indicating that it was mostly introduced from outside. Schools adjacent large roads were more vulnerable to black carbon exposure than residential areas with low traffic. In addition, the amount of black carbon containing fine particulates (eBC/PM2.5) in traffic areas tended to be higher indoors than outdoors. Thus, the emission source of black carbon should be constrained even around the school.
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