제8회 EDISON SW 활용 경진대회

Does Sulfur Dioxide in Ulsan Affect Nearby Cities?

손지수, 서동주, 최다솔, 김준하* 지구환경공학부, 광주과학기술원, 광주광역시 북구 첨단과기로 123 E-mail: [email protected], [email protected]*

The SO2 concentration of Ulsan and nearby cities are analyzed as an indicator of air pollution. Various statistical analysis methods like Kruskal-Wallis test, Spearman’s rank correlation and cross correlation coefficient are used with collected data. Ulsan and Incheon had highest SO2 concentration among 7

metropolitan cities. Ulsan’s SO2 concentration is related with atmospheric factors.

Ulsan and nearby cities’ cross correlation analyses are performed. Ulsan’s SO2 concentration affect to nearby cities with few hours of time lag, but the correlation is not strong.

1. Introduction In this paper, sulfur dioxide concentration is analyzed with various variables and statistical The air quality issue has become an methods to find the relationship between sulfur important environmental problem recently. dioxide and other variables. At first, seven main People concern about PM10 and other air metropolitan cities of Korea are compared that pollutants because these air pollutants are which city has notable sulfur dioxide known as sources of various disease. Especially concentration. Then the correlation of atmospheric condition variables and SO the sulfur dioxide (SO2) is an important factor 2 of the air pollution. Sulfur dioxide itself is a concentration in Ulsan is analyzed. Cross correlation analyses of SO concentration of harmful material to the human respiratory 2 Ulsan and nearby cities; Gyeongsan, Gyeongju, system and also to the plants and trees. Well- and Yangsan are conducted to find the known environmental problem, acid rain is also influence of Ulsan to other city. If SO2 from one caused by sulfur dioxide. When sulfur dioxide city could cause air pollution to nearby cities, it reacts with other small particles in the air, it should be considered in further air quality plans. grows up to particulate matters (PM). Moreover, main source of sulfur dioxide is combustion of 2. Methods and Materials fossil fuels in power plants and other industrial Air data of Seoul, Busan, Daejeon, Daegu, facilities, which also causes other air pollutants Incheon, Gwangju, Ulsan, Gyeongju, Gyeongsan, like carbon monoxide and PM10. Therefore, Yangsan are collected from Air Korea and Korea sulfur dioxide can be treated as an indicator of Meteorological Administration (KMA). From Air air pollution. Korea, data of sulfur dioxide (SO2), carbon

monoxide (CO), ozone (O3), nitrogen dioxide

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Does Sulfur Dioxide in Ulsan Affect Nearby Cities? (NO2), particulate matters with 10 micrometers the null hypothesis of test was rejected. Thus or less in diameter (PM10) are collected. From the SO concentration of 7 cities were 2 KMA, average temperature (Temp), average significantly different. Then box plot and post 손지수, 서동주, 최다솔, 김준하* wind speed (WS), average relative humidity (RH), hoc analysis are done to find difference 지구환경공학부, 광주과학기술원, 광주광역시 북구 첨단과기로 123 average pressure (Pa). Daily station data of between cities and the city with highest SO E-mail: [email protected], [email protected]* 2 2013.01.01 ~ 2017.12.31 is collected, and hourly concentration. According to the post hoc

station data of 2017.07.01 ~ 2017.07.21 of analysis, every city pair had p-value 0, The SO2 concentration of Ulsan and nearby cities are analyzed as an indicator of Ulsan, Gyeongju, Gyeongsan, and Yangsan is significantly different mean value of SO air pollution. Various statistical analysis methods like Kruskal-Wallis test, 2 collected. concentration. With the box plot in Figure 1., Spearman’s rank correlation and cross correlation coefficient are used with R studio program is used to analyze the data Incheon had the highest SO2 concentration and collected data. Ulsan and Incheon had highest SO2 concentration among 7 set with statistical analysis. All analyses are Ulsan ranked on second. However, Ulsan had metropolitan cities. Ulsan’s SO2 concentration is related with atmospheric factors. conducted on the basis of each null hypothesis the highest peak SO2 concentration and this Ulsan and nearby cities’ cross correlation analyses are performed. Ulsan’s SO2 (H0) and the significance level () was set to had been an issue that industrial complex in concentration affect to nearby cities with few hours of time lag, but the 0.05. Kolmogorov-Smirnov test is used to check Ulsan caused SO2 pollution. In this reason, correlation is not strong. the normality of all samples. Kruskal-Wallis test Ulsan’s air data is mainly analyzed. is used to determine the existence of significant 1. Introduction In this paper, sulfur dioxide concentration is difference among non-normal samples. Post- analyzed with various variables and statistical hoc test of Kruskal-Wallis test is done to The air quality issue has become an methods to find the relationship between sulfur investigate which group means are different. important environmental problem recently. dioxide and other variables. At first, seven main Spearman’s rank correlation coefficient is used People concern about PM10 and other air metropolitan cities of Korea are compared that to measure the closeness among variables. pollutants because these air pollutants are which city has notable sulfur dioxide Cross correlation test is used to analyze the known as sources of various disease. Especially concentration. Then the correlation of dependency and correspondence between the the sulfur dioxide (SO ) is an important factor atmospheric condition variables and SO2 2 data measured from the sites. of the air pollution. Sulfur dioxide itself is a concentration in Ulsan is analyzed. Cross correlation analyses of SO concentration of harmful material to the human respiratory 2 3. Result and Discussion

Ulsan and nearby cities; Gyeongsan, Gyeongju, Figure 1 Box plot of SO2 concentration of 7 system and also to the plants and trees. Well- Kolmogorov-Smirnov tests for normality and Yangsan are conducted to find the Seoul, Busan, Daegu, Incheon, Gwangju, known environmental problem, acid rain is also check of data set were done. All air pollutant Daejeon and Ulsan. influence of Ulsan to other city. If SO2 from one caused by sulfur dioxide. When sulfur dioxide city could cause air pollution to nearby cities, it data did not follow the normality, so every reacts with other small particles in the air, it should be considered in further air quality plans. analysis was performed with non-parametric grows up to particulate matters (PM). Moreover, method. main source of sulfur dioxide is combustion of 2. Methods and Materials 3.1. SO concentration comparison for 7 cities fossil fuels in power plants and other industrial 2 Air data of Seoul, Busan, Daejeon, Daegu, facilities, which also causes other air pollutants The SO concentrations of 7 metropolises; Incheon, Gwangju, Ulsan, Gyeongju, Gyeongsan, 2 like carbon monoxide and PM10. Therefore, Seoul, Incheon, Daejeon, Daegu, Gwangju, Yangsan are collected from Air Korea and Korea Ulsan and Busan during 2013 ~ 2017 are sulfur dioxide can be treated as an indicator of Meteorological Administration (KMA). From Air air pollution. compared by Kruskal-Wallis test to find the Korea, data of sulfur dioxide (SO2), carbon Figure 2 Spearman's correlation of SO2 and significant difference. The p-value of test was 0, monoxide (CO), ozone (O3), nitrogen dioxide other variables of Ulsan

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3.2. Ulsan’s SO2 concentration analysis with other variables

Kruskal-Wallis tests were done with SO2 concentration and other variables of Ulsan to confirm which variables significantly affect to

SO2 concentration. The variables included are

SO2, CO, O3, NO2, PM10, Temp, WS, RH, and Pa. As a result, Temp, WS, RH, Pa had the 0 p-value, thus these variables significantly affect to the

SO2 concentration. Then the Spearman’s rank correlation coefficient analysis was done with variables of Ulsan to find how 4 factors affect to the SO2 concentration. In Figure 2., Temp and

RH had positive correlation with SO2 concentration. WS and Pa had negative correlation with SO2 concentration. With these results, atmospheric conditions have certain degree of correlation with SO2 concentration.

3.3. Effect of Ulsan’s SO2 concentration to the 3 nearby cities; Gyeongju, Gyeongsan, and Yangsan

Gyeongsan, Gyeongju, and Yangsan are nearby cities of Ulsan. Distance of each city from Ulsan is 51.2km, 37.3km, and 33.6km. Kruskal-Wallis tests and post hoc analysis of

SO2 concentration of Ulsan, Gyeongju, Gyeongsan, and Yangsan were done. The p- values of tests were all 0. Thus the SO2 concentration of 4 cities were significantly different.

Cross correlation analyses of SO2 concentration of Ulsan and nearby cities; Gyeongju, Gyeongsan, and Yangsan were done Figure 3 Cross correlation of SO concentration with daily data (In Figure 3., a1~c1). The results 2 of Ulsan and Gyeongsan (a), Gyeongju (b), and showed that time lag value 0 with Gyeongju Yangsan (c) with daily (1) and hourly (2) data

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3.2. Ulsan’s SO2 concentration analysis with and Yangsan. Gyeongsan had 45 days of t ime to be related with wind direction of the period. other variables lag with day zero peak also. From this result, Kruskal-Wallis tests were done with SO 2 Ulsan and nearby cities’ SO2 correlation can be 감사의 글 concentration and other variables of Ulsan to guessed to occur within a day. confirm which variables significantly affect to This research was supported by the EDISON Therefore, cross correlation analyses with the SO2 concentration. The variables included are Program through the National Research hourly data set were done. The hourly data SO2, CO, O3, NO2, PM10, Temp, WS, RH, and Pa. Foundation of Korea(NRF) funded by the As a result, Temp, WS, RH, Pa had the 0 p-value, period was 2017.07.01 ~ 2017.07.21. During this Ministry of Science & ICT(NRF-2011-0020576) thus these variables significantly affect to the period, wind direction of each city was Ulsan 223 degree, Gyeongsan 266 degree, Gyeongju 참고문헌 SO2 concentration. Then the Spearman’s rank 234 degree, and Yangsan 228 degree. Thus it correlation coefficient analysis was done with [1] http://www.airkorea.or.kr/index Air Korea can be assumed that the wind passes from variables of Ulsan to find how 4 factors affect (Website) Gyeongju to Ulsan and Yangsan, and to the SO2 concentration. In Figure 2., Temp and Gyeongsan is not on same the path. In Figure [2] http://www.kma.go.kr/home/index.jsp Korea RH had positive correlation with SO2 Meteorological Administration (Website) concentration. WS and Pa had negative 3. (a2 ~ c2), the result showed that Gyeongsan had 11 hours of time lag, Gyeongju had 6 hours correlation with SO2 concentration. With these [3] https://www.epa.gov/ United States of time lag, and Yangsan had 1 hour of time lag. results, atmospheric conditions have certain Environmental Protection Agency (EPA) (Website) Data sets are plotted in time series graphs with degree of correlation with SO2 concentration. [4] Oh et.al., Korean Society for Atmospheric consideration of time lag. The case of Yangsan fits with Ulsan’s data more than other cases, so Environment. 32, 4th (2016.8) (Conference 3.3. Effect of Ulsan’s SO2 concentration to the wind possibly transported SO . Proceedings) 3 nearby cities; Gyeongju, Gyeongsan, and 2

Yangsan 4. Conclusion [5] http://www.edison.re.kr. EDISON . (Website) Gyeongsan, Gyeongju, and Yangsan are Among 7 metropolitan cities in Korea, nearby cities of Ulsan. Distance of each city Incheon and Ulsan were the two cities that had from Ulsan is 51.2km, 37.3km, and 33.6km. the highest SO2 concentration values. Incheon Kruskal-Wallis tests and post hoc analysis of and Ulsan is both port city and have large SO2 concentration of Ulsan, Gyeongju, petrochemical industrial complex. Main source Gyeongsan, and Yangsan were done. The p- of sulfur dioxide is knowns as coal-fired values of tests were all 0. Thus the SO2 powerplant and ship. This easily explains why concentration of 4 cities were significantly these two cities had the highest concentration. different. Atmospheric conditions factors are correlated

Cross correlation analyses of SO2 with SO2 concentration in Ulsan. It was hard to concentration of Ulsan and nearby cities; see clear correlation of SO2 concentration Gyeongju, Gyeongsan, and Yangsan were done between three cities (Gyeongju, Gyeongsan, Figure 3 Cross correlation of SO concentration with daily data (In Figure 3., a1~c1). The results 2 Yangsan) and Ulsan. However, Yangsan showed of Ulsan and Gyeongsan (a), Gyeongju (b), and showed that time lag value 0 with Gyeongju Yangsan (c) with daily (1) and hourly (2) data stronger correlation with Ulsan and this seems

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