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http://dx.doi.org/10.5467/JKESS.2020.41.5.447

Cluster Analysis of Synoptic Scale Meteorological Characteristics on High PM10 Concentration Episodes in the Southeastern Part of Korean Peninsula  

Chae, DaEun (Department of Earth Science, Pusan National University)
Lee, Kangyeol (Division of Earth Environmental System, Pusan National University)
Lee, Soon-Hwan (Department of Earth Science Education, Pusan National University)
Publication Information
Journal of the Korean earth science society / v.41, no.5, 2020 , pp. 447-458 More about this Journal
Abstract
This study presents the K-means clustering analysis-based classification of the meteorological patterns affecting the occurrence of high PM10 concentration in the southeastern region of the Korean peninsula for the last five years (2014-2018). Regional differences in Busan, Ulsan, and Gyeongnam related to high PM10 episodes, were clarified through the statistical comparison study using synoptic scale meteorological elements using NCEP (National Centers for Environmental Prediction/FNL (Final Operational Global Analysis) re-analysis meteorological data. Meteorological patterns were classified into a total of five categories (C1-C5). The incidence of each cluster was 24.8% (C1), 21.3% (C2), 20.4% (C3), 17.3% (C4), and 16.2% (C5), respectively. The high PM10 concentration in the southeastern region resulted from long and short range transports (C1, C3, C5) from outside of the region, and the emissions (C2, C4) inside the region. In the high PM10 episodes in Busan, Ulsan, and Gyeongnam regions, meteorological characteristics such as different geopotential height and wind speed at 500 hPa in each cluster and the change in the location of high pressure over Korean Peninsula is strongly associated with the dispersion of PM10 around inventories in the region and the tendency of long-range transportation of PM10 emitted from outside of region.
Keywords
$PM_{10}$; K-means clustering analysis; re-analysis data; long and short range transports; meteorological pattern;
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Times Cited By KSCI : 7  (Citation Analysis)
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1 Ahmed, E., Kim, K.H., Shon, Z.H., and Song, S.K., 2015, Long-term trend of airborne particulate matter in Seoul, Korea from 2004 to 2013. Atmospheric Environment 101, 125-133.   DOI
2 Hong, S.H. and Lee, S.H., 2017, Characteristic of $PM_{10}$ Distribution Related to Precise Local Wind Patterns in Busan Metropolitan Area. Journal of Environmental Science International, 26(12), 1375-1387.   DOI
3 Jeon, B.I., 2012, Meteorological Characteristics of the Wintertime High $PM_{10}$ concentration Episodes in Busan. Journal of the Environmental Sciences, 21(7), 815-824.   DOI
4 Jeon, W.B., Choi, Y.S., Lee, H.W., Lee, S.H., Yoo, J.W., Park, J.H., and Lee, H.J, 2015, A quantitative analysis of grid nudging effect on each process of $PM_{2.5}$ production in the Korean Peninsula. Atmospheric Environment 122, 763-774.   DOI
5 Jeon, W.B., Lee, H.W., Lee, T.J., Yoo, J.W., Mun, J.H., Lee, S.H., and Choi, Y.S., 2019, Impact of Varying Wind Patterns on $PM_{10}$ Concentrations in the Seoul Metropolitan Area in South Korea from 2012 to 2016. Journal of Applied Meteorology and Climatology, 58(12), 2734-2755.
6 Kim, E.H., Bae, C.H., Yoo, C., Kim, B.U., Kim, H.C., and Kim, S.T., 2018, Evaluation of the Effectiveness of Emission Control Measures to Improve PM2.5 Concentration in South Korea. Journal of Korean Society for Atmospheric Environment, 34(3), 469-485.   DOI
7 Lee, J.H. and Kim, K,Y., 2018, Analysis of source regions and meteorological factors for the variability of spring $PM_{10}$ concentrations in Seoul, Korea. Atmospheric Environment 175, 199-209.   DOI
8 Kim, H.C., Kim, S.T., Kim, B.U., Jin, C.S., Hong, S.Y., Park, R.J., Son, S.W., Bae, C.H., Bae, M.A., Song, C.G., and Stein, A., 2017, Recent increase of surface particulate matter concentrations in the Seoul Metropolitan Area, Korea. Scientific Reports 7:4710.
9 Kim, J.H. and Kang, S.W., Analysis of Factors Influencing $PM_{10}$ Pollution in Korea, 2018, Korea Environmental Economics Association, 779-791.
10 Kim, M.K., Juong, W.S., Lee, H.W., Do, W.G., Cho, J.G., and Lee, K.O., 2013, Analysis on Meteorological Factors related to the Distribution of $PM_{10}$ Concentration in Busan. Journal of Environmental Science International, 22(9), 1213-1226.   DOI
11 Lee, K.Y., Lee, S.H., and Kim, E.J., 2016, Assessment of Global Air Quality Reanalysis and Its Impact as Chemical Boundary Conditions for a Local PM Modeling System. Journal of Environmental Science International, 25(7), 1029-1042.   DOI
12 Lee, S.H. and Lee, K.Y., 2015, Evaluation of Contribution Rate of PM Concentrations for Regional Emission Inventories in Korean Peninsula Using Brute-force Sensitivity Analysis, Journal of the Environmental Sciences, 24(11), 1525-1540.   DOI
13 Lee, S.M., Ho, C.H., and Choi, Y.S., 2011, High-$PM_{10}$ concentration episodes in Seoul, Korea: Background sources and related meteorological conditions. Atmospheric Environment 45, 7240-7247.   DOI
14 Lee, S.M., Ho, C.H., Lee, Y.G., Choi, H.J., and Song, C.K., 2013, Influence of transboundary air pollutants from China on the high-$PM_{10}$ episode in Seoul, Korea for the period October 16-20, 2008. Atmospheric Environment 77, 430-439.   DOI
15 Souri, A.H., Choi, Y.S., Li, X., Kotsakis, A., and Jiang, X., 2016, A 15-year climatology of wind pattern impacts on surface ozone in Houston, Texas. Atmospheric Research 174-175, 124-134.   DOI
16 Seo, Y.S., 2016, An Empirical Study on Air Pollution in Korea's Geographical Characteristics, The Journal of Euraian Studies, 12(4), 89-110.