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An Estimation of Mean Background Concentrations of Greenhouse Gases Observed on Ulleungdo

울릉도 온실기체 관측자료를 이용한 배경대기 평균농도 산정

  • Lim, Yun-Kyu (Department of Environmental Education, Korea National University of Education) ;
  • Moon, Yun-Seob (Department of Environmental Education, Korea National University of Education) ;
  • Kim, Jin-Seog (Cent for gas analysis, Korea Research Institute of Standards and Science) ;
  • Song, Sang-Keun (Division of Earth Environmental System, Pusan National University) ;
  • Hong, Ji-Hyung (Atmospheric Engineering Research Division, National Institute of Environmental Research)
  • 임윤규 (한국교원대학교 환경교육과) ;
  • 문윤섭 (한국교원대학교 환경교육과) ;
  • 김진석 (한국표준과학연구원 대기환경표준센터) ;
  • 송상근 (부산대학교 지구환경시스템학부) ;
  • 홍지형 (국립환경과학원 대기공학연구과)
  • Received : 2011.11.10
  • Accepted : 2012.02.21
  • Published : 2012.02.29

Abstract

Mean background concentrations of greenhouse gases such as $CO_2$ and $CH_4$ were estimated on Ulleungdo using PICARRO Cavity Ring-Down Spectroscopy (CRDS) analyzer. To improve the accuracy of $CO_2$ and $CH_4$ concentrations, a standardized QA${\cdot}$QC (Quality Assurance Quality Control) procedure was employed with three steps: 1) the inspection procedure of physical limitation (e.g. the exclusion of data corresponding to the number of data of ${\leq}$50%) for hourly mean values, 2) a stage inspection (e.g. the use of data corresponding to ${\geq}15$ observations per day) for daily mean values, and 3) a fast fourier transform (FFT) analysis using curve-fitting methods for the investigation of climatic characteristics. The monthly mean concentrations of $CO_2$ and $CH_4$ derived from three-step QA${\cdot}$QC procedure were then compared with those observed at Anmyundo (Korea) and Ryori (Japan). Overall, the error of mean $CO_2$ and $CH_4$ concentrations estimated in this study distinctly decreased. However, in comparison with their concentrations monitored at Ryori, the $CO_2$ concentration at estimated at Ulleungdo is soemwhat lower than that of Anmyundo due to the missing data, which is statistically significant. On the other hand, the former has a statistically significant higher value of $CH_4$ that of the latter.

본 연구에서는 울릉도 온실기체 관측장비(CRDS)에서 관측된 $CO_2$$CH_4$ 농도를 정형화된 QA${\cdot}$QC 처리절차를 통해 온실기체 평균 배경대기 농도값으로 활용하기 위한 정확도를 향상시켰다. QA${\cdot}$QC 처리절차는 총 3단계로 구성되었다. 첫 번째는 관측자료의 시간별 평균값을 구하기 위한 물리적 한계검사, 기후범위 검사 및 1시간 측정 자료수가 50% 이하인 자료는 제외시키는 과정으로 이루어져 있다. 두 번째는 일평균자료 산출을 위한 단계검사, 앞뒤로 같은 값일 경우는 제외, 하루 중 관측횟수가 15회 이상 및 일관측 자료의 표준편차가 일표준편차 평균의 3배 이하인 자료만 허용하는 과정이다. 세 번째는 기후적 특성분석 활용을 위한 Curve-fitting methods를 이용한 FFT 적용단계이다. 이상의 QA${\cdot}$QC 절차에 의한 $CO_2$$CH_4$의 월평균농도 값을 안면도 지구대기감시센터 자료와 일본 료리 관측자료와 비교 분석한 결과 $CO_2$에 있어서는 울릉도 관측자료 누락에 의한 영향이 다소 크게 나타나 안면도 관측값이 배경대기 평균농도 값으로 유효하였고, $CH_4$는 안면도 보다 오히려 울릉도 관측값이 한반도 배경대기 평균농도 값으로 더 적절한 것으로 추정되었다.

Keywords

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