TY - JOUR
AU - Kim, Y, J
AB - Abstract Radon exposure in schools is different from that in dwellings because the residence pattern is very different each other. So, when effective dose is calculated in schools, different approach should be considered from in dwellings. The aim of this study was to estimate actual effective dose due to inhaled radon considering the residence time in schools. It could help avoid overestimation when effective dose is calculated in schools. The range of radon concentration in 376 schools was 18.1–2810 Bq m−3 and that of annual effective dose was estimated 0.0902–8.92 mSv y−1 considering the residence time in spring and autumn semesters. INTRODUCTION Radon (222Rn) is produced by the radioactive decay of radium (226Ra), mainly present throughout the earth’s crust. This natural inert gas with a half-life of 3.8 days can travel across the pores in the soil to the surface, where it is harmlessly diluted in the atmosphere, unless it penetrates inside insufficiently protected buildings(1). Radon and its decay products have been classified as a human carcinogen based on epidemiological studies of miners exposed to high levels of radon and radon exposure is ranked as the second cause of lung cancer, growing this risk by 16% per 100 Bq m−3 increase in long-term average radon concentration(2–5). Nationwide surveys on radon were conducted to estimate annual average concentrations in Korean dwellings and the effective dose to the general public in 1989, 1999–2000 and 2002–05(6). In addition, other natural radiation sources were also surveyed and evaluated in 2002–05(7). From these studies, the annual effective dose to the public was estimated to be 3.08 mSv y−1 which consists of radon (1.40 mSv y−1), terrestrial gamma radiation (1.04 mSv y−1), radionuclides in food (0.38 mSv y−1) and cosmic ray (0.26 mSv y−1)(7). Due to inhaled radon was the largest fraction of natural radiation exposure, the most efficient way to decrease dose exposure is to manage radon exposure in home and workplaces. Management of radon in home is the most important and all homes would be surveyed as possible. Meanwhile, among workplaces, school is one of the important places both at the point of view of radon exposure because young students staying in the school for a long time and at the point of view of radon mapping because of almost even distribution and almost same building structures across the country. Because of these reasons, nationwide survey for 1100 buildings (63.4% were schools and 36.3% were local governmental offices) was conducted in 2008–09. Combining all data surveyed, Korea Institute of Nuclear Safety (KINS) proposed provisional radon-prone areas in 2012(8). At the point of view of radon exposure, radon survey was newly carried out in 103 schools in 2010(9). The result of the study showed that the range of school radon concentration was 26.0–2650 Bq m−3 and 14 schools were recommended for requiring urgent mitigation action. The locations of high-radon schools were closely related to the provisional radon-prone areas proposed in 2012. At that time, the effective dose of on-duty time was also assessed using active radon detectors. If the effective doses were calculated by using simply averaged radon concentrations without considering the radon concentration during school hour (or residence time), they could be highly overestimated, and so unnecessary remediation action could be applied. Because of this reason, when estimating effective doses in schools, including workplaces, it is necessary to use the radon concentration during school hour. To accomplish this, the continuous radon measurement using active detectors is necessary, but difficult to apply for large scale radon survey because of limitation of the active radon detectors, budget, radon measurement experts, etc. In this study, radon survey was conducted in 376 schools located in the provisional radon-prone areas, in six administrative districts, and estimation of actual radon exposure during residence time was also attempted without continuous radon measurement. A correction factor was used to estimate actual radon exposure, derived from the previous survey(9) and statistical method using one-way analysis of variance (ANOVA). MATERIALS AND METHODS Measurement of school radon concentration The target schools were selected in six administrative districts of Korea considering previous radon survey results. The information about administrative district, area, population and number of measured schools was shown in Table 1. Since students do not stay in the schools during the vacation, the survey was conducted in two semesters. All of the detectors were installed ~1–2 m above the floor in the first floor, away from the fans, the air conditioner, the heater and the open window to avoid interference of air dilution. The structure, the area and the shape of classroom and teacher’s office are almost same in all schools located in countryside, and so, strict selection of classroom or office to be measured does not seem to be important. To avoid loss of detectors by careless or curious students, lot of teacher’s offices (~60%) were selected instead of the classrooms. Table 1. The information and survey results of each administrative district. Administrative district Gangwon Gyeonggi Gyeongbuk Jeonbuk Chungnam Chungbuk Areaa 16 875 10 184 19 028 8055 8598 7432 Populationb 1 542 604 12 348 078 2 677 686 1 871 725 2 060 971 1 579 037 Number of measured schools 66 46 119 17 27 101 Mean value in spring semester (Bq m−3) 74.6 58.4 80.2 103 73.4 59.4 Range in spring semester (Bq m−3) 22.7–609 19.2–212 23.0–2760 34.4–590 32.5–221 18.1–314 Mean value in autumn semester (Bq m−3) 116 91.2 110 133 123 131 Range in autumn semester (Bq m−3) 32.2–893 23.2–492 22.5–2810 42.8–891 52.7–351 37.8–1770 Arithmetic mean (Bq m−3) 120 ± 114 90.3 ± 71.2 150 ± 292 177 ± 209 115 ± 76 117 ± 144 Geometric mean (Bq m−3) 93.2 ± 1.9 73.0 ± 1.9 93.9 ± 2.2 117 ± 2 95.1 ± 1.8 88.1 ± 2.0 [Rn] ≥ 170c Bq m−3 (%) 18.2 6.52 20.2 29.4 22.2 9.90 [Rn] ≥ 600d Bq m−3 (%) 0 0 4.20 11.8 0 1.00 Administrative district Gangwon Gyeonggi Gyeongbuk Jeonbuk Chungnam Chungbuk Areaa 16 875 10 184 19 028 8055 8598 7432 Populationb 1 542 604 12 348 078 2 677 686 1 871 725 2 060 971 1 579 037 Number of measured schools 66 46 119 17 27 101 Mean value in spring semester (Bq m−3) 74.6 58.4 80.2 103 73.4 59.4 Range in spring semester (Bq m−3) 22.7–609 19.2–212 23.0–2760 34.4–590 32.5–221 18.1–314 Mean value in autumn semester (Bq m−3) 116 91.2 110 133 123 131 Range in autumn semester (Bq m−3) 32.2–893 23.2–492 22.5–2810 42.8–891 52.7–351 37.8–1770 Arithmetic mean (Bq m−3) 120 ± 114 90.3 ± 71.2 150 ± 292 177 ± 209 115 ± 76 117 ± 144 Geometric mean (Bq m−3) 93.2 ± 1.9 73.0 ± 1.9 93.9 ± 2.2 117 ± 2 95.1 ± 1.8 88.1 ± 2.0 [Rn] ≥ 170c Bq m−3 (%) 18.2 6.52 20.2 29.4 22.2 9.90 [Rn] ≥ 600d Bq m−3 (%) 0 0 4.20 11.8 0 1.00 aMinistry of land, infrastructure and transport. bMinistry of the Interior. cRecommended value which takes tentative actions in Korean schools. dRecommended value which takes urgent actions in Korean school. Table 1. The information and survey results of each administrative district. Administrative district Gangwon Gyeonggi Gyeongbuk Jeonbuk Chungnam Chungbuk Areaa 16 875 10 184 19 028 8055 8598 7432 Populationb 1 542 604 12 348 078 2 677 686 1 871 725 2 060 971 1 579 037 Number of measured schools 66 46 119 17 27 101 Mean value in spring semester (Bq m−3) 74.6 58.4 80.2 103 73.4 59.4 Range in spring semester (Bq m−3) 22.7–609 19.2–212 23.0–2760 34.4–590 32.5–221 18.1–314 Mean value in autumn semester (Bq m−3) 116 91.2 110 133 123 131 Range in autumn semester (Bq m−3) 32.2–893 23.2–492 22.5–2810 42.8–891 52.7–351 37.8–1770 Arithmetic mean (Bq m−3) 120 ± 114 90.3 ± 71.2 150 ± 292 177 ± 209 115 ± 76 117 ± 144 Geometric mean (Bq m−3) 93.2 ± 1.9 73.0 ± 1.9 93.9 ± 2.2 117 ± 2 95.1 ± 1.8 88.1 ± 2.0 [Rn] ≥ 170c Bq m−3 (%) 18.2 6.52 20.2 29.4 22.2 9.90 [Rn] ≥ 600d Bq m−3 (%) 0 0 4.20 11.8 0 1.00 Administrative district Gangwon Gyeonggi Gyeongbuk Jeonbuk Chungnam Chungbuk Areaa 16 875 10 184 19 028 8055 8598 7432 Populationb 1 542 604 12 348 078 2 677 686 1 871 725 2 060 971 1 579 037 Number of measured schools 66 46 119 17 27 101 Mean value in spring semester (Bq m−3) 74.6 58.4 80.2 103 73.4 59.4 Range in spring semester (Bq m−3) 22.7–609 19.2–212 23.0–2760 34.4–590 32.5–221 18.1–314 Mean value in autumn semester (Bq m−3) 116 91.2 110 133 123 131 Range in autumn semester (Bq m−3) 32.2–893 23.2–492 22.5–2810 42.8–891 52.7–351 37.8–1770 Arithmetic mean (Bq m−3) 120 ± 114 90.3 ± 71.2 150 ± 292 177 ± 209 115 ± 76 117 ± 144 Geometric mean (Bq m−3) 93.2 ± 1.9 73.0 ± 1.9 93.9 ± 2.2 117 ± 2 95.1 ± 1.8 88.1 ± 2.0 [Rn] ≥ 170c Bq m−3 (%) 18.2 6.52 20.2 29.4 22.2 9.90 [Rn] ≥ 600d Bq m−3 (%) 0 0 4.20 11.8 0 1.00 aMinistry of land, infrastructure and transport. bMinistry of the Interior. cRecommended value which takes tentative actions in Korean schools. dRecommended value which takes urgent actions in Korean school. Radon concentrations were measured by using solid state nuclear track detector (Raduet, Radosys Ltd, Hungary), which consists of two diffusion chambers (the low-exchange rate and the high exchange rate). After exposure, the detectors were sealed in radon-proof bags and sent to the laboratory. CR-39 chips which were included in chambers were etched in for 3.67 h at 90°C in 25% NaOH solution. The number of etched tracks was counted by microscope reader (RSV-6, Radosys Ltd, Hungary). Radon concentration can be calculated from track density by the following equation(10, 11): CRn=CF[a11(A−Nbkg)+a12(B−Nbkg)]T−1 (1) where, CRn is the mean radon concentration (Bq m−3) in the exposed period, CF is the calibration factor (Bq h mm2 track−1 m−3) provided by Radosys Ltd., A is the track density (track mm−2) of the CR-39 chip in low air exchange-rate chamber of Raduet, B is the track density (track mm−2) of the CR-39 chip in high air exchange-rate chamber of Raduet, Nbkg is the background track density (track mm−2), a11 is the Rn conversion factor for the track density of the CR-39 chip in the low air exchange-rate chamber, a12 is the Rn conversion factor for the track density of the CR-39 chip in the high air exchange-rate chamber, T is the exposure time. Estimation of annual effective dose The annual effective dose can be estimated from the following equation: ERn=CRn×T×FC×DRn (2) where, ERn is the effective dose in the spring and autumn semester (nSv), CRn is the indoor radon concentration in spring and autumn semester (Bq m−3), T is the residence time in school (h) and FC is the equilibrium factor (0.4) for indoor environment between radon and its decay products suggested by UNSCEAR(12) and ICRP(13). DRn is 12 nSv Bq−1 h−1 m3 proposed by ICRP(13). T is assumed 2000 h based on the Labor Standard Law, which specifies a full-time worker must work <2000 h a year. Since students have supplementary classes, study hall after school and a short vacation, residence time is not different between students and teachers in Korea. In general, radon concentration is daily fluctuated by various factors such as temperature difference between day and night, ventilation rate difference between on and off duty time, etc.(9), shown in Figure 1. In night time (high-radon level), the radon exposure to students and teachers is not actually occurred, which should be considered in estimating the annual effective dose in school to decide further measures. To estimate actual effective dose during staying in schools, a correction factor considering daily fluctuation of radon concentration during exposure was used as the following equation(9): EW=ERn×FW (3) where, EW is the actual effective dose during staying in schools and FW is the correction factor for the radon concentration during staying in school. It is calculated as the following equation (4) from survey results of the previous study(9). FW=[Rn]onduty([Rn]semester) (4) Figure 1. Open in new tabDownload slide An example of daily fluctuation of indoor radon concentration in a school for 6 days(9). Figure 1. Open in new tabDownload slide An example of daily fluctuation of indoor radon concentration in a school for 6 days(9). The value of the correction factor (⁠ FW ⁠) was statistically derived using one-way ANOVA and the results of previously continuous radon measurements since the locations of the schools surveyed in this study were in the same administrative districts of the previous study(9). RESULTS AND DISCUSSION Measurement of school radon concentration The frequency distribution of radon concentrations was shown in Figure 2. Indoor radon data usually follow a log-normal distribution(14). A normal probability plot for the log transformed radon concentration data was shown in Figure 3, and the slopes can be divided into two groups. The group with high slope can be inferred to require urgent measure for radon mitigation. The low end from log-normality with indoor radon concentration data are usually attributed to the contribution that outdoor radon makes to indoor concentrations and random uncertainties in radon measurements(15, 16). The distribution of radon concentration is well fitted by log-normal function, as indicated by r2 values of 0.945. Figure 2. Open in new tabDownload slide Frequency distribution of indoor radon concentration in 376 schools. Figure 2. Open in new tabDownload slide Frequency distribution of indoor radon concentration in 376 schools. Figure 3. Open in new tabDownload slide Normal probability plot to test for log-normal distribution. Figure 3. Open in new tabDownload slide Normal probability plot to test for log-normal distribution. An arithmetic and geometric mean were calculated by each administrative district and each semester (Table 1). The minimum detectable activity of the detectors used in this study is 3 Bq m−3 and the maximum activity is 5556 Bq m−3 with a 3-month exposure. The school radon concentration varied from 18.1 to 2760 Bq m−3 with an average value of 96.9 Bq m−3 in the spring semester and from 22.5 to 2810 Bq m−3 with an average value of 158 Bq m−3 in the autumn semester. Indoor radon concentrations in the autumn semester presented higher than those in the spring semester. One of the major reasons can be inferred to be the difference of ventilation rate depending on temperature between the spring semester and the autumn semester. Meanwhile, so far, there was no reference level in Korea, indeed, no recommendation value to schools. In this study, two recommendation values (170 and 600 Bq m−3) are suggested for radon management in Korean schools. The value of 170 Bq m−3 is, as an entry level of radon awareness, the corresponding value derived from occupancy time (2000 h) in workplace and the population-weighted annual average effective dose in Korea due to inhaled radon. The value of 600 Bq m−3 is, as required level for active control, calculated based on the value of 6 mSv y−1. Although ICRP suggested that a level of dose of around 10 mSv from radon where action would almost certainly be warranted to reduce exposure(17), the value of 6 mSv is determined for conservative point of view considering that young students are exposed. Among 376 schools, 60 schools had radon concentrations higher than 170 Bq m−3 and four schools had radon concentrations higher than 600 Bq m−3. In this study, the schools are classified into four groups depending on criteria (the group A has radon concentration lower than 170 Bq m−3 both semesters, the group B has radon concentration higher than 170 Bq m−3 at one of two semesters, the group C has radon concentration higher than 170 Bq m−3 both semesters and the group D has radon concentration higher than 600 Bq m−3). The distribution of schools classified by the four groups is shown in Figure 4. As shown in Figure 4, the high-radon schools are located in north part of Gyeongbuk province, which is known as one of the high-radon areas(7, 18). Figure 4. Open in new tabDownload slide The distribution of schools against the criteria. Figure 4. Open in new tabDownload slide The distribution of schools against the criteria. In addition, the management strategy for indoor radon in existing schools as well as newly constructed schools was proposed in Figure 5. Figure 5. Open in new tabDownload slide Recommendation of management protocol for indoor radon in schools. Figure 5. Open in new tabDownload slide Recommendation of management protocol for indoor radon in schools. Estimation of annual effective dose As mentioned before, the radon concentration is daily fluctuated by various factors. In addition, teachers and students do not stay in schools during night in general. Because of these reasons, it is necessary to consider the radon concentration in the period of staying in school of teacher or student for estimating the actual effective dose. Otherwise, it could be overestimated. To obtain the value of the correction factor (⁠ FW ⁠) in equation (3), the result of continuous radon measurement during a certain period is required, but it is impossible for large scale radon survey. The use of one-way ANOVA is helpful to find a significant difference between more than three groups. A p-value calculated by one-way ANOVA is that lower than 0.05 is set as the threshold for a statistically difference or above 0.05 allowed us to merge each group based on statistical similarities. The one-way ANOVA is calculated regarding classified six groups on the administrative district. The one-way ANOVA was performed on the correction factor of administrative district. A p-value lower than 0.001 between six groups confirms that for each administrative district, statistical heterogeneity was validated by one-way ANOVA. The correction factors were categorized by the administrative districts and shown in Table 2. Table 2. The correction factor derived by the one-way ANOVA based on the previous study(9) on the six groups considering the daily fluctuation of the radon concentration on the administrative district criterion. Administrative district Correction factor (⁠ FW ⁠) n Median Mean Standard deviation Gangwon 43 0.650 0.693 0.157 Gyeonggi 8 0.840 0.807 0.133 Gyeongbuk 20 0.325 0.334 0.193 Jeonbuk 6 0.675 0.608 0.244 Chungnam 2 0.650 0.650 0.127 Chungbuk 23 0.335 0.405 0.220 Administrative district Correction factor (⁠ FW ⁠) n Median Mean Standard deviation Gangwon 43 0.650 0.693 0.157 Gyeonggi 8 0.840 0.807 0.133 Gyeongbuk 20 0.325 0.334 0.193 Jeonbuk 6 0.675 0.608 0.244 Chungnam 2 0.650 0.650 0.127 Chungbuk 23 0.335 0.405 0.220 χ2 = 82.9585 with five degree of freedom (p-value between six groups ≤0.001; statistically significant difference). Table 2. The correction factor derived by the one-way ANOVA based on the previous study(9) on the six groups considering the daily fluctuation of the radon concentration on the administrative district criterion. Administrative district Correction factor (⁠ FW ⁠) n Median Mean Standard deviation Gangwon 43 0.650 0.693 0.157 Gyeonggi 8 0.840 0.807 0.133 Gyeongbuk 20 0.325 0.334 0.193 Jeonbuk 6 0.675 0.608 0.244 Chungnam 2 0.650 0.650 0.127 Chungbuk 23 0.335 0.405 0.220 Administrative district Correction factor (⁠ FW ⁠) n Median Mean Standard deviation Gangwon 43 0.650 0.693 0.157 Gyeonggi 8 0.840 0.807 0.133 Gyeongbuk 20 0.325 0.334 0.193 Jeonbuk 6 0.675 0.608 0.244 Chungnam 2 0.650 0.650 0.127 Chungbuk 23 0.335 0.405 0.220 χ2 = 82.9585 with five degree of freedom (p-value between six groups ≤0.001; statistically significant difference). As shown in Table 3, the annual effective dose estimated by using the mean radon concentration ranged from 0.206 to 26.7 mSv y−1 with a mean value of 1.22 mSv y−1. However, the annual effective dose reflected with the staying in school was in the range of 0.0902–8.92 mSv y−1 with a mean value of 0.599 mSv y−1 (Table 4). These results indicate that the actual effective dose considering daily fluctuation of radon concentration was estimated not to be significantly high. Therefore, it is necessary to use the effective dose considering the daily fluctuation to decide radon mitigation action instead of simply averaged radon concentration. Table 3. Annual effective dose estimated by using mean radon concentrations. Administrative district Annual effective dose (mSv y−1) Minimum Maximum Mean Gangwon 0.283 5.56 1.16 Gyeonggi 0.206 3.38 0.866 Gyeongbuk 0.270 26.7 1.44 Jeonbuk 0.395 7.00 1.70 Chungnam 0.426 2.45 1.11 Chungbuk 0.306 10.0 1.13 Administrative district Annual effective dose (mSv y−1) Minimum Maximum Mean Gangwon 0.283 5.56 1.16 Gyeonggi 0.206 3.38 0.866 Gyeongbuk 0.270 26.7 1.44 Jeonbuk 0.395 7.00 1.70 Chungnam 0.426 2.45 1.11 Chungbuk 0.306 10.0 1.13 Table 3. Annual effective dose estimated by using mean radon concentrations. Administrative district Annual effective dose (mSv y−1) Minimum Maximum Mean Gangwon 0.283 5.56 1.16 Gyeonggi 0.206 3.38 0.866 Gyeongbuk 0.270 26.7 1.44 Jeonbuk 0.395 7.00 1.70 Chungnam 0.426 2.45 1.11 Chungbuk 0.306 10.0 1.13 Administrative district Annual effective dose (mSv y−1) Minimum Maximum Mean Gangwon 0.283 5.56 1.16 Gyeonggi 0.206 3.38 0.866 Gyeongbuk 0.270 26.7 1.44 Jeonbuk 0.395 7.00 1.70 Chungnam 0.426 2.45 1.11 Chungbuk 0.306 10.0 1.13 Table 4. Annual effective dose considering the daily fluctuation of the radon concentration. Administrative district Annual effective dose on residence time (mSv y−1) Minimum Maximum Mean Standard error Gangwon 0.196 3.86 0.801 0.077 Gyeonggi 0.166 2.72 0.699 0.071 Gyeongbuk 0.0902 8.92 0.480 0.084 Jeonbuk 0.241 4.26 1.04 0.270 Chungnam 0.277 1.60 0.718 0.077 Chungbuk 0.124 4.05 0.456 0.043 Administrative district Annual effective dose on residence time (mSv y−1) Minimum Maximum Mean Standard error Gangwon 0.196 3.86 0.801 0.077 Gyeonggi 0.166 2.72 0.699 0.071 Gyeongbuk 0.0902 8.92 0.480 0.084 Jeonbuk 0.241 4.26 1.04 0.270 Chungnam 0.277 1.60 0.718 0.077 Chungbuk 0.124 4.05 0.456 0.043 Table 4. Annual effective dose considering the daily fluctuation of the radon concentration. Administrative district Annual effective dose on residence time (mSv y−1) Minimum Maximum Mean Standard error Gangwon 0.196 3.86 0.801 0.077 Gyeonggi 0.166 2.72 0.699 0.071 Gyeongbuk 0.0902 8.92 0.480 0.084 Jeonbuk 0.241 4.26 1.04 0.270 Chungnam 0.277 1.60 0.718 0.077 Chungbuk 0.124 4.05 0.456 0.043 Administrative district Annual effective dose on residence time (mSv y−1) Minimum Maximum Mean Standard error Gangwon 0.196 3.86 0.801 0.077 Gyeonggi 0.166 2.72 0.699 0.071 Gyeongbuk 0.0902 8.92 0.480 0.084 Jeonbuk 0.241 4.26 1.04 0.270 Chungnam 0.277 1.60 0.718 0.077 Chungbuk 0.124 4.05 0.456 0.043 Meanwhile, the rounded value of equilibrium factor (0.4) between radon and its progenies was used for radon dose calculation in this study. However, the value may show variation with places and time. It will be necessary to study the equilibrium factor in the future in schools. CONCLUSION Indoor radon measurements have been performed in 376 schools during a year except vacation. The result of the survey shows that the radon concentrations of 16.0% schools exceed 170 Bq m−3 and those of 1.06% schools exceed 600 Bq m−3. The annual effective dose was estimated to be 0.0902–8.92 mSv y−1 considering the daily fluctuation of radon concentration. This study suggests that it is necessary to use the actual effective exposure dose considering staying in schools to decide radon mitigation action instead of simply averaged radon concentration. FUNDING This study was supported by the Student health and safety strengthening program of the Ministry of Education in Korea. ACKNOWLDGEMENT The authors would like to thank education officers for distributing, installing and collecting detector. We also want to thank Mr J. H. Lee for supporting the chemical treatment and alpha track counting in radon measurement. REFERENCES 1 Frutos Vázquez , B. , Olaya Adán , M. , Quindós Poncela , L. S. , Sainz Fernandez , C. and Fuente Merino , I. 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TI - RADON SURVEY IN SCHOOL AND ESTIMATION OF EFFECTIVE DOSE USING CORRECTED RADON CONCENTRATION
JO - Radiation Protection Dosimetry
DO - 10.1093/rpd/ncx216
DA - 2018-04-01
UR - https://www.deepdyve.com/lp/oxford-university-press/radon-survey-in-school-and-estimation-of-effective-dose-using-m83plj9VYa
SP - 101
VL - 179
IS - 2
DP - DeepDyve
ER -