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라이다 관측자료를 이용한 미세먼지 농도 산정

Estimation of Particle Mass Concentration from Lidar Measurement

  • 김만해 (서울대학교 지구환경과학부) ;
  • 여희동 (서울대학교 지구환경과학부) ;
  • ;
  • 임한철 (기상청 기후변화감시센터) ;
  • 이철규 (기상청 기후변화감시센터) ;
  • 허복행 (기상청 기후변화감시센터) ;
  • 유영석 (기상청 기후변화감시센터) ;
  • 손병주 (서울대학교 지구환경과학부) ;
  • 윤순창 (서울대학교 지구환경과학부) ;
  • 김상우 (서울대학교 지구환경과학부)
  • Kim, Man-Hae (School of Earth and Environmental Sciences, Seoul National University) ;
  • Yeo, Huidong (School of Earth and Environmental Sciences, Seoul National University) ;
  • Sugimoto, Nobuo (National Institute of Environmental Studies) ;
  • Lim, Han-Cheol (Korea Global Atmosphere Watch Center, Korea Meteorological Administration) ;
  • Lee, Chul-Kyu (Korea Global Atmosphere Watch Center, Korea Meteorological Administration) ;
  • Heo, Bok-Haeng (Korea Global Atmosphere Watch Center, Korea Meteorological Administration) ;
  • Yu, Yung-Suk (Korea Global Atmosphere Watch Center, Korea Meteorological Administration) ;
  • Sohn, Byung-Ju (School of Earth and Environmental Sciences, Seoul National University) ;
  • Yoon, Soon-Chang (School of Earth and Environmental Sciences, Seoul National University) ;
  • Kim, Sang-Woo (School of Earth and Environmental Sciences, Seoul National University)
  • 투고 : 2014.12.23
  • 심사 : 2015.02.02
  • 발행 : 2015.03.31

초록

Vertical distribution of particle mass concentrations was estimated from 8-year elastic-backscatter lidar and sky radiometer data, and from ground-level PM10 concentrations measured in Seoul. Lidar ratio and mass extinction efficiency were determined from aerosol optical depth (AOD) and ground-level PM10 concentrations, which were used as constraints to estimate particle mass concentration. The mean lidar ratio (with standard deviation) and mass extinction efficiency for the entire 8-year study period were $60.44{\pm}23.17$ sr and $3.69{\pm}3.00m^2g^{-1}$, respectively. The lidar ratio did not vary significantly with the ${\AA}ngstr{\ddot{o}}m$ exponent (less than ${\pm}10%$); however, the mass extinction efficiency decreases to $1.82{\pm}1.67m^2g^{-1}$ (51% less than the mean value) when the ${\AA}ngstr{\ddot{o}}m$ exponent is less than 0.5. This result implies that the particle mass concentration from lidar measurements can be underestimated for dust events. Seasonal variation of the particle mass concentration estimated from lidar measurements for the boundary layer, was quite different from ground-level PM10 measurements. This can be attributable to an inhomogeneous vertical distribution of aerosol in the boundary layer.

키워드

참고문헌

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피인용 문헌

  1. The KALION Automated Aerosol Type Classification and Mass Concentration Calculation Algorithm vol.32, pp.2, 2016, https://doi.org/10.7780/kjrs.2016.32.2.5