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WRF-CMAQ 모델링 시스템을 활용한 PM2.5 농도변동 원인 분석: 2016년과 2017년의 가을철을 중심으로

Analysis of the Changesin PM2.5 Concentrations using WRF-CMAQ Modeling System: Focusing on the Fall in 2016 and 2017

  • 남기표 (국립환경과학원 기후대기연구부 대기질통합예보센터) ;
  • 임용재 (국립환경과학원 기후대기연구부 대기질통합예보센터) ;
  • 박지훈 (국립환경과학원 기후대기연구부 대기환경연구과) ;
  • 김덕래 (국립환경과학원 기후대기연구부 환경위성센터) ;
  • 이재범 (국립환경과학원 기후대기연구부 대기질통합예보센터) ;
  • 김상민 (국립환경과학원 기후대기연구부 환경위성센터) ;
  • 정동희 (국립환경과학원 기후대기연구부 대기환경연구과) ;
  • 최기철 (국립환경과학원 기후대기연구부 대기질통합예보센터) ;
  • 박현주 (국립환경과학원 기후대기연구부 대기질통합예보센터) ;
  • 이한솔 (국립환경과학원 기후대기연구부 대기질통합예보센터) ;
  • 장임석 (국립환경과학원 기후대기연구부 대기질통합예보센터) ;
  • 김정수 (국립환경과학원 기후대기연구부)
  • Nam, Ki-Pyo (Air Quality Forecasting Center, Climate and Air Quality Research Department, NIER) ;
  • Lim, Yong-Jae (Air Quality Forecasting Center, Climate and Air Quality Research Department, NIER) ;
  • Park, Ji-Hoon (Air Quality Research Division, Climate and Air Quality Research Department, NIER) ;
  • Kim, Deok-Rae (Environmental Satellite Center, Climate and Air Quality Research Department, NIER) ;
  • Lee, Jae-Bum (Air Quality Forecasting Center, Climate and Air Quality Research Department, NIER) ;
  • Kim, Sang-Min (Environmental Satellite Center, Climate and Air Quality Research Department, NIER) ;
  • Jung, Dong-Hee (Air Quality Research Division, Climate and Air Quality Research Department, NIER) ;
  • Choi, Ki-Chul (Air Quality Forecasting Center, Climate and Air Quality Research Department, NIER) ;
  • Park, Hyun-Ju (Air Quality Forecasting Center, Climate and Air Quality Research Department, NIER) ;
  • Lee, Han-Sol (Air Quality Forecasting Center, Climate and Air Quality Research Department, NIER) ;
  • Jang, Lim-Seok (Air Quality Forecasting Center, Climate and Air Quality Research Department, NIER) ;
  • Kim, Jeong-Soo (Air Quality Research Department, NIER)
  • 투고 : 2018.03.22
  • 심사 : 2018.04.05
  • 발행 : 2018.04.30

초록

본 연구에서는 지상 기상 및 $PM_{2.5}$ 농도, GOCI 위성의 AOD 등 다양한 관측 자료와 WRF-CMAQ 모델링을 통해 2016년과 2017년의 우리나라 가을철 $PM_{2.5}$ 농도변화 원인을 분석하였다. 지상에서 관측된 2017년 전국 평균 $PM_{2.5}$ 농도는 2016년에 비해 약 12.3% ($3.0{\mu}g/m^3$) 감소한 것으로 나타났다. 두 해간 $PM_{2.5}$ 농도 차이는 10월과 11월의 두 사례(사례1: 10월 11일~10월 20일, 사례2: 11월 15일~19일) 기간에 주로 발생하였으며, 2017년의 기상조건이 2016년에 비하여 국외로부터 대기오염물질의 장거리 수송이 어렵고, 국내의 대기환기 효과를 증가시키는 방향으로 변화한 것이 주요한 원인으로 분석되었다. WRF-CMAQ 모델링 시스템을 이용하여 기상조건 변화가 $PM_{2.5}$ 농도에 미치는 정량적인 영향을 평가한 결과, $PM_{2.5}$ 모의농도는 2016년 대비 2017년의 사례1 기간에는 64.0% ($23.1{\mu}g/m^3$) 감소, 사례2 기간에는 35.7% ($12.2{\mu}g/m^3$) 감소한 것으로 나타나, 관측 농도 기반 감소율인 53.6% (사례1)와 47.8% (사례2)에 상응하는 감소율을 보였다. 따라서 기상조건 변화가 우리나라 가을철 $PM_{2.5}$ 농도 변화에 큰 영향을 미치는 것으로 분석되었다. 기상조건 변화로 인한 우리나라 $PM_{2.5}$ 농도 감소에 미친 국내외 기여율은 사례1 기간에 국외로부터의 장거리 수송영향이 52.8% 그리고 대기환기 효과에 따른 국내영향이 47.2% 로 국내외 영향이 유사하게 나타나지만, 사례2 기간에는 국외영향이 66.4% 그리고 국내영향이 33.6%로서 국외영향의 감소효과가 더 크게 나타났다.

It was analyzed to identify the cause of $PM_{2.5}$ concentration changes for the fall in 2016 and 2017 in South Korea using ground measurement data such as meterological variables and $PM_{2.5}$, AOD from GOCI satellite, and WRF-CMAQ modeling system. The result of ground measurement data showed that the $PM_{2.5}$ concentrations for the fall in 2017 decreased by 12.3% ($3.0{\mu}g/m^3$) compared to that of 2016. The difference of $PM_{2.5}$ concentrations between 2016 and 2017 mainly occurred for 11 Oct. - 20 Oct. (CASE1) and 15 Nov. - 19 Nov. (CASE2) when weather conditions were difficult to long-range transport from foreign regions and favored atmospheric ventilation in 2017 compared to 2016. Simulated $PM_{2.5}$ concentrations in 2017 decreased by 64.0% ($23.1{\mu}g/m^3$) and 35.7% ($12.2{\mu}g/m^3$) during CASE1 and CASE2, respectively. These results corresponded to the changes in observed $PM_{2.5}$ concentrations such as 53.6% for CASE1 and 47.8% for CASE2. It is implied that the changes in weather conditions affected significantly the $PM_{2.5}$ concentrations for the fall between 2016 and 2017. The contributions to decreases in $PM_{2.5}$ concentrations was assessed as 52.8% by long-range transport from foreign regions and 47.2% by atmospheric ventilation effects in domestic regions during CASE1, whereas their decreases during CASE2 were affected by 66.4% from foreign regions and 33.6% in domestic regions.

키워드

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