DOI QR코드

DOI QR Code

Statistically Analyzed Effects of Coal-Fired Power Plants in West Coast on the Surface Air Pollutants over Seoul Metropolitan Area

통계적 기법을 활용한 서해안 화력발전소 오염물질 배출에 따른 수도권 지표면 대기오염농도 영향의 분석

  • Ju, Jaemin (Department of Earth Science Education, Chungbuk National University) ;
  • Youn, Daeok (Department of Earth Science Education, Chungbuk National University)
  • 주재민 (충북대학교 지구과학교육과) ;
  • 윤대옥 (충북대학교 지구과학교육과)
  • Received : 2019.12.23
  • Accepted : 2019.12.30
  • Published : 2019.12.31

Abstract

The effects of the coal-fired power plant emissions, as the biggest point source of air pollutants, on spatiotemporal surface air pollution over the remote area are investigated in this study, based on a set of date selection and statistical technique to consider meteorological and geographical effects in the emission-concentration (source-receptor) relationship. We here proposed the sophisticated technique of data processing to separate and quantify the effects. The data technique comprises a set of data selection and statistical analysis procedure that include data selection criteria depending on meteorological conditions and statistical methods such as Kolmogorov-Zurbenko filter (K-Z filter) and empirical orthogonal function (EOF) analysis. The data selection procedure is important for filtering measurement data to consider the meteorological and geographical effects on the emission-concentration relationship. Together with meteorological data from the new high resolution ECMWF reanalysis 5 (ERA5) and the Korea Meteorological Administration automated surface observing system, air pollutant emission data from the telemonitoring system (TMS) of Dangjin and Taean power plants as well as spatio-temporal air pollutant concentrations from the air quality monitoring system are used for 4 years period of 2014-2017. Since all the data used in this study have the temporal resolution of 1 hour, the first EOF mode of spatio-temporal changes in air pollutant concentrations over the Seoul metropolitan area (SMA) due to power plant emission have been analyzed to explain over 97% of total variability under favorable meteorological conditions. It is concluded that SO2, NO2, and PM10 concentrations over the SMA would be decreased by 0.468, 1.050 ppb, and 2.045 ㎍ m-3 respectively if SO2, NO2, and TSP emissions from Dangjin power plant were reduced by 10%. In the same way, the 10% emission reduction in Taean power plant emissions would cause SO2, NO2, and PM10 decreased by 0.284, 0.842 ppb, and 1.230 ㎍ m-3 over the SMA respectively. Emissions from Dangjin power plant affect air pollution over the SMA in higher amount, but with lower R value, than those of Taean under the same meteorological condition.

본 연구는 화력발전소 배출로 인한 지표면 오염물질 농도의 시·공간적 영향을 실측 자료를 바탕으로 정량적으로 분석하려는 목적으로 수행되었다. 배출과 농도 관계의 정량적 분석을 위해 우선 기상 조건과 주변 배출원의 영향을 고려하였다. 이를 위해 자료의 선택과 관측지점 선정 과정을 제안하였고, 선정된 지표면 시·공간 자료에 K-Z 필터와 경험직교함수(EOF) 분석 기법을 적용하였다. 사용된 자료는 2014-2017년 4년의 기간 동안 당진과 태안 화력발전소 굴뚝 자동측정기기의 농도값을 이용하여 산출한 한 시간 평균 배출량 자료와 지표면 대기오염농도 측정망 자료이다. 기상 자료로는 최근 배포 중인 ERA5 재분석자료와 기상청 종관기상관측소 한 시간 평균 자료가 사용되었다. 발전소만의 영향이 최대한 보이도록 기상 효과와 지리적인 요인을 고려하여 선택한 시간대의 선정된 관측소 자료만을 이용하여 분석한 결과, 지표면 대기오염물질의 EOF 첫 번째 모드는 SO2, NO2, PM10 모두에 대해 97% 이상의 변동성을 설명하였다. 또한 지표면 농도장의 EOF 첫 번째 모드의 시계열은 화력발전소 배출과 유의미한 상관성을 보였다. 결과적으로 당진화력발전소 SO2, NO2, TSP 시간 당 배출량이 각각 10%가 감소하면, 남서풍 계열의 바람에 의해 직접 영향을 받는 서울 수도권 지표면 평균 SO2 농도는 0.468 ppb (R=0.384), NO2는 1.050 ppb (R=0.572), PM10은 2.045 ㎍ m-3 (R=0.343) 정도가 감소한다고 판단할 수 있다. 태안화력발전소의 경우, SO2, NO2, TSP 배출량을 각각 시간당 10% 씩 감축하면, SO2는 0.284 ppb (R=0.648), NO2는 0.842 ppb (R=0.683), PM10은 1.230 ㎍ m-3 (R=0.575) 정도가 감소될 수 있음을 확인하였다. 태안화력발전소는 당진화력발전소에 비해 수도권지역 농도에 미치는 영향은 작았으나, 상관관계는 더 높았다.

Keywords

References

  1. Achakulwisut, P., Mickley, L. J., and Anenberg, S. C., 2018, Drought-sensitivity of fine dust in the US Southwest: Implications for air quality and public health under future climate change, Environmental Research Letters, 13(5), 054025. https://doi.org/10.1088/1748-9326/aabf20
  2. Cai, W., Li, K., Liao, H., Wang, H., and Wu, L., 2017, Weather conditions conductive to Beijing severe haze more frequent under climate change, National Climate Change, 7, 257-262. https://doi.org/10.1038/nclimate3249
  3. Cheng, L., Wang, S., Gong, Z., Li, H., Yang, Q., and Wang, Y., 2018, Regionalization based on spatial and seasonal variation in ground-level ozone concentrations across China, Journal of Environmental Science, 67, 179-190. https://doi.org/10.1016/j.jes.2017.08.011
  4. Eskridge, R. E., Ku, J. Y., Rao, S. T., Porter, P. S., and Zurbenko, I. G., 1997, Separating different scales of motion in time series of meteorological variables, Bulletin of the American Meteorological Society, 78, 1473-1483. https://doi.org/10.1175/1520-0477(1997)078<1473:SDSOMI>2.0.CO;2
  5. Hannachi, A., Jolliffie, I. T., and Stephenson, D. B., 2007, Empirical orthogonal functions and related techniques in atmospheric science: a review, International Journal of Climatology, 27, 1119-1152. https://doi.org/10.1002/joc.1499
  6. Kim, J.-H., Kim, M.-K., Ho, C.-H., Park, R. J., Kim, M. J., Lim, J., Kim, S.-Y., and Song, C.-K., 2019, Possible Link Between Arctic Sea Ice and January $PM_{10}$ Concentrations in South Korea, Atmosphere, 10(10), 619. https://doi.org/10.3390/atmos10100619
  7. Kim, K.-J., Kim, D.-S., Cho, J., Hong, S.-W., and Lee, Y.-W., 2013, EOF analysis of satellite-based drought indices: a case of inner mongolian region. Journal of Climate Research, 8, 309-319. https://doi.org/10.14383/cri.2013.8.4.309
  8. Kim, Y., Seo, J., Kim, J. Y., Lee, J. Y., Kim, H., and Kim, B. M., 2018, Characterization of PM 2.5 and identification of transported secondary and biomass burning contribution in Seoul, Korea, Environment Science and Pollution Research, 25, 4330-4343. https://doi.org/10.1007/s11356-017-0772-x
  9. Li, P., Wang, Y., and Dong, Q., 2017, The analysis and application of a new hybrid pollutants forecasting model using modified Kolmogorov-Zurbenko filter, Science of Total Environment, 583, 228-240. https://doi.org/10.1016/j.scitotenv.2017.01.057
  10. Mijling, B., van der A. R. J., and Zhang, Q., 2013, Regional nitrogen oxides emission trends in East Asia observed from space, Atmospheric Chemistry and Physics, 13, 12003-12012. https://doi.org/10.5194/acp-13-12003-2013
  11. Milanchus, M. L., Rao, S. T., and Zurbenko, I. G., 1998, Evaluating the effectiveness of Ozone management efforts in the presence of meteorological variability, Journal of the Air & Waste Management Association, 48, 201-215. https://doi.org/10.1080/10473289.1998.10463673
  12. Na, J. Y., Han, S. K., Seo, J. W., No, Y. G., and Kang, I. S., 1997, Empirical orthogonal function analysis of surface pressure, sea surface temperature and winds over the East Sea on the Korea (Japan Sea), Korean Journal of Fisheries and Aquatic Sciences, 30, 188-202. (in Korean)
  13. NIER (National Institute of Environmental Research), 2019, Annual report of ambient air quality in Korea, 2018 (NIER-GP2019-053), National Institute of Environmental Research, Incheon, South Korea, available at: http://webbook.me.go.kr/DLi-File/NIER/09/024/5683728.pdf (last access: 2 December 2019)
  14. Rao, S. T. and Zurbenko, I. G., 1994, Detecting and tracking changes in ozone air quality, Journal of the Air & Waste Management Association, 44, 1089-1092.
  15. Rao, S. T., Zurbenko, I. G., Neagu, R., Porter, P. S., Ku, J. Y., and Henry, R. F., 1997, Space and time scales in ambient ozone data, Bulletin of the American Meteorological Society, 78, 2153-2166. https://doi.org/10.1175/1520-0477(1997)078<2153:SATSIA>2.0.CO;2
  16. Ray, S. and Kim, K.-H., 2014, The pollution status of sulfur dioxide in major urban areas of Korea between 1989 and 2010, Atmospheric Research, 147-148, 101-110. https://doi.org/10.1016/j.atmosres.2014.05.011
  17. Seo, J., Kim, J. Y., Youn, D., Lee, J. Y., Kim, H., Lim, Y. B., Kim, Y., and Jin, H. C., 2017, On the multiday haze in the Asian continental outflow: the important role of synoptic conditions combined with regional and local sources, Atmospheric Chemistry and Physics, 17, 9311-9332. https://doi.org/10.5194/acp-17-9311-2017
  18. Seo, J., Park, D.-S. R., Kim, J. Y., Youn, D., Lim, Y. B., and Kim, Y., 2018, Effects of meteorology and emissions on urban air quality: a quantitative statistical approach to long-term records (1999-2016) in Seoul, South Korea, Atmospheric Chemistry and Physics, 18, 16121-16137. https://doi.org/10.5194/acp-18-16121-2018
  19. Shi, Y., Matsunaga, T., Yamaguchi, Y., Li, Z., Gu, X., and Chen, X., Long-term trends and spatial patterns of satellite retrieved PM2.5 concentrations in South and Southeast Asia from 1999 to 2014, Science of the Total Environment, 615, 177-186. https://doi.org/10.1016/j.scitotenv.2017.09.241
  20. Simpson, J. E., 1994, Sea breeze and local winds, Cambridge University Press, UK.
  21. Wise, E. K., and Comrie, A. C., 2005, Extending the Kolmogorov-Zurbenko filter: Application to ozone, particulate matter, and meteorological trends, Journal of the Air & Waste Management Association, 55, 1208-1216. https://doi.org/10.1080/10473289.2005.10464718
  22. Zou, Y., Wang, Y., Zhang, Y., and Koo, J.-H., 2017, Arctic sea ice, Eurasia snow, and extreme winter haze in China, Science Advances, 3, e1602751 https://doi.org/10.1126/sciadv.1602751