Journal of the Korean Data and Information Science Society

한국데이터정보과학회 (The Korean Data and Information Science Society)
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GEV 분포를 이용한 대구·경북 지역 일산화탄소 농도 추정

The estimation of CO concentration in Daegu-Gyeongbuk area using GEV distribution

  • 류수락 (대구대학교 대학원 통계학과) ;
  • 엄은진 (대구대학교 대학원 통계학과) ;
  • 권태용 (대구대학교 대학원 통계학과) ;
  • 윤상후 (대구대학교 전산통계학과)
  • Ryu, Soorack (Department of Statistics, Daegu University) ;
  • Eom, Eunjin (Department of Statistics, Daegu University) ;
  • Kwon, Taeyong (Department of Statistics, Daegu University) ;
  • Yoon, Sanghoo (Department of Statistics and Computer Science, Daegu University)
  • 투고 : 2016.06.30
  • 심사 : 2016.07.19
  • 발행 : 2016.07.31
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초록

대기오염물질이 인간의 건강에 악영향을 미치는 사실은 잘 알려져 있다. 유엔 환경 계획 (united nations environment program; UNEP) 보고서에 따르면, 미세먼지와 일산화탄소 오염물질로 연간 전 세계에서 430만 명이 목숨을 잃었다. 일산화탄소는 탄소와 산소로 구성된 화합물로 가정에서 생성되는 독성 가스 중 가장 위험한 가스이다. 연구를 위하여 2004년부터 2013년까지 10년간 대구 경북 지역의 대기오염관측소에서 관측된 1시간, 6시간, 12시간, 24시간 평균 일산화탄소 농도 자료를 사용하였다. 일반화 극단치 분포의 모수는 최우추정법과 L-적률추정법을 통해 추정하였고 적합도 검정을 수행하였다. 본 연구의 표본 수가 크지 않으므로 L-적률추정법이 최대우도법에 비해 모수추정에 적합하였다. 또한, 5년, 10년, 20년, 40년 재현수준을 추정하여 대구 경북 지역 일산화탄소 위험지역을 살펴보았다.

It is well known that air pollutants exert a bad influence on human health. According to the United Nations Environment Program, 4.3 million people die from carbon monoxide and particulate matter annually from all over the world. Carbon monoxide is a toxic gas that is the most dangerous of the gas consisting of carbon and oxygen. In this paper, we used 1 hour, 6 hours, 12 hours, and 24 hours average carbon monoxide concentration data collected between 2004 and 2013 in Daegu Gyeongbuk area. Parameters of the generalized extreme value distribution were estimated by maximum likelihood estimation and L-moments estimation. An evalution of goodness of fitness also was performed. Since the number of samples were small, L-moment estimation turned out to be suitable for parameter estimation. We also calculated 5 year, 10 year, 20 year, and 40 year return level.

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참고문헌

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피인용 문헌

  1. 지진 재현수준 예측에 대한 로그-로지스틱 분포와 일반화 극단값 분포의 비교 vol.33, pp.1, 2016, https://doi.org/10.5351/kjas.2020.33.1.107