Journal of Environmental Science International (한국환경과학회지)

The Korean Environmental Sciences Society (한국환경과학회)
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A Correlation Analysis between Visibility and PM10 in Jinju

진주지역 시정과 미세먼지(PM10) 농도와의 상관관계

  • Kim, Hyoung-Kab (Department of Environmental Engineering, Gyeongnam National University of Science and Technology) ;
  • Suh, Jeong-Min (Department of Bio-Environmental Energy, Pusan National University) ;
  • Park, Jeong-Ho (Department of Environmental Engineering, Gyeongnam National University of Science and Technology)
  • 김형갑 (경남과학기술대학교 환경공학과) ;
  • 서정민 (부산대학교 바이오환경에너지학과) ;
  • 박정호 (경남과학기술대학교 환경공학과)
  • Received : 2017.02.21
  • Accepted : 2017.04.03
  • Published : 2017.04.30
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Abstract

This study was conducted to investigate how $PM_{10}$ concentration and Relative Humidity (RH) affected visibility in Jinju, Korea. A 9-yr dataset of 1 h averages for visibility, $PM_{10}$, and RH data was analyzed to examine the correlation between these variables. On average, visibility decreased by 1.4 km for every $10{\mu}g/m^3$ increase in $PM_{10}$ and by 2.1 km for every 10% increase in RH. In general, a negative correlation was observed between visibility and and $PM_{10}$ concentration. However, under conditions of low $PM_{10}$ concentration(< $15{\mu}g/m^3$) and visibility(< 2 km), there was a positive correlation between these two variables. In this case, RH levels were high (> 75%). A high correlation analysis between two variables need to be under control conditions with RH < 75%, $PM_{10}$ $15{\sim}100{\mu}g/m^3$, and visibility > 2 km.

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References

  1. Dayan, U., Levy, I., 2004, The influence of meteorological conditions and atmospheric circulation types on $PM_{10}$ and visibility in Tel Aviv, J. Appl. Meteor., 44, 606-619.
  2. Interagency Monitoring of Protected Visual Environments (IMPROVE), 2016, http://vista.cira.colostate.edu/improve
  3. Kim, K. W., 2009, Physico-chemical characteristics of visibility impairment in a national park area, KOSAE, 25(4), 325-338. https://doi.org/10.5572/KOSAE.2009.25.4.325
  4. Korea Meteorological Administration (KMA), 2011, Climatological normals of Korea, 1981-2010.
  5. Korea Meteorological Administration (KMA), 2016, http://web.kma.go.kr/communication/elearning/
  6. Lee, H. J., Lee, E. H., Lee, S. S., Kim, S. B., 2012, Study of methodology for estimating $PM_{10}$ concentration of asian dust using visibility data, Atmosphere, 22(1), 13-28. https://doi.org/10.14191/Atmos.2012.22.1.013
  7. Li, Y., Chen, Q., Zhao, H., Wang, L., Tao, R., 2015, Variations in $PM_{10}$, $PM_{2.5}$ and $PM_{1.0}$ in an urban area of the Sichuan Basin and their relation to meteorological factors, Atmosphere, 6, 150-163. https://doi.org/10.3390/atmos6010150
  8. Ministry of Environment (MoE), 2016, Annual report of air quality in Korea, 2015.
  9. National Climate Data Service System (NCDSS), 2016, https://data.kma.go.kr
  10. National Institute of Environmental Research (NIER), 2013, The study of the visual characteristics for the improvement of bodily sensation air pollution level, NIER-RP2013-191.
  11. Park, J. S., Park, S. M., Song, I. H., Shin, H. J., Hong, Y. D., 2015, Characteristics of visibility impairment by semi-continuous optical and chemical property monitoring of aerosols in Seoul, KOSAE, 31(4), 319-329. https://doi.org/10.5572/KOSAE.2015.31.4.319
  12. Zorita, E., Storch, H., 1999, The analog method as a simple statistical downscaling technique: Comparison with more complicated methods, J. Climate, 12, 2474-2489. https://doi.org/10.1175/1520-0442(1999)012<2474:TAMAAS>2.0.CO;2