Atmosphere (대기)

Korean Meteorological Society (한국기상학회)
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Improvement and Evaluation of Automatic Quality Check Algorithm for Particulate Matter (PM10) by Analysis of Instrument Status Code

부유분진(PM10) 측정기 상태 코드 분석을 통한 자동 품질검사 알고리즘 개선 및 평가

  • Kim, Mi-Gyeong (Environmental Meteorology Research Division, National Institute of Meteorological Sciences) ;
  • Park, Young-San (Environmental Meteorology Research Division, National Institute of Meteorological Sciences) ;
  • Ryoo, Sang-Boom (Environmental Meteorology Research Division, National Institute of Meteorological Sciences) ;
  • Cho, Jeong Hoon (Environmental Meteorology Research Division, National Institute of Meteorological Sciences)
  • 김미경 (국립기상과학원 환경기상연구과) ;
  • 박영산 (국립기상과학원 환경기상연구과) ;
  • 류상범 (국립기상과학원 환경기상연구과) ;
  • 조정훈 (국립기상과학원 환경기상연구과)
  • Received : 2019.08.09
  • Accepted : 2019.11.12
  • Published : 2019.11.30
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Abstract

Asian Dust is a meteorological phenomenon that sand particles are raised from the arid and semi-arid regions-Taklamakan Desert, Gobi Desert and Inner Mongolia in China-and transported by westerlies and deposited on the surface. Asian dust results in a negative effect on human health as well as environmental, social and economic aspects. For monitoring of Asian Dust, Korea Meteorological Administration operates 29 stations using a continuous ambient particulate monitor. Kim et al. (2016) developed an automatic quality check (AQC) algorithm for objective and systematic quality check of observed PM10 concentration and evaluated AQC with results of a manual quality check (MQC). The results showed the AQC algorithm could detect abnormal observations efficiently but it also presented a large number of false alarms which result from valid error check. To complement the deficiency of AQC and to develop an AQC system which can be applied in real-time, AQC has been modulated. Based on the analysis of instrument status codes, valid error check process was revised and 6 status codes were further considered as normal. Also, time continuity check and spike check were modified so that posterior data was not referred at inspection time. Two-year observed PM10 concentration data and corresponding MQC results were used to evaluate the modulated AQC compared to the original AQC algorithm. The results showed a false alarm ratio decreased from 0.44 to 0.09 and the accuracy and the probability of detection were conserved well in spite of the exclusion of posterior data at inspection time.

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References

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