주성분 분석과 퍼지 논리를 활용한 대전 미세먼지 취약지도 제작에 관한 연구
A Study on the Vulnerability Mapping of Fine Dust Using Principal Component Analysis (PCA) and Fuzzy Logic in Daejeon, Korea
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A fine dust vulnerability map was generated to efficiently manage the concentration of fine dust pollution. By applying the fourteen indicators used for assessing the vulnerability to fine dust, including fine dust pollution source and concentration, fine dust vulnerability classes, and usage facilities, the vulnerable regions were derived through the analyses of the principal components and fuzzy logics. As a result of this study, it was displayed that in Daejeon, the greatest number of vulnerable regions were distributed in Yuseong-gu, followed by the order of Seo-gu, Daedeok-gu, Jung-gu, and Dong-gu. In Yuseong-gu, a traffic congestion section around the terminal, a large-scale apartment complex, and an energy industry combustion facility are located. Due to which, types of surface and mobile pollution, vulnerable groups, and point pollution appeared together. In Seo-gu, the type of surface and mobile pollution and vulnerable groups were seen in the areas adjacent to the city hall. This is because that large-scale apartment complexes, elementary schools, and administrative agencies are concentrated around the city hall, which leads to traffic congestion. It was identified that Jung-gu and Dong-gu are vulnerable groups because many large-scale apartment complexes, elementary schools, and rehabilitation hospitals are located in the regions. In Daedeok-gu, types of vulnerable groups were seen in the areas with aged population. Furthermore, types of pollution were shown in the regions where the Daedeok Industrial Complex, energy industry combustion facilities, and waste treatment facilities are located. The result of this study can be utilized as basic data to establish a customized policy for fine dust reduction according to the identified types of vulnerabilities.
Abstract
A fine dust vulnerability map was generated to efficiently manage the concentration of fine dust pollution. By applying the fourteen indicators used for assessing the vulnerability to fine dust, including fine dust pollution source and concentration, fine dust vulnerability classes, and usage facilities, the vulnerable regions were derived through the analyses of the principal components and fuzzy logics. As a result of this study, it was displayed that in Daejeon, the greatest number of vulnerable regions were distributed in Yuseong-gu, followed by the order of Seo-gu, Daedeok-gu, Jung-gu, and Dong-gu. In Yuseong-gu, a traffic congestion section around the terminal, a large-scale apartment complex, and an energy industry combustion facility are located. Due to which, types of surface and mobile pollution, vulnerable groups, and point pollution appeared together. In Seo-gu, the type of surface and mobile pollution and vulnerable groups were seen in the areas adjacent to the city hall. This is because that large-scale apartment complexes, elementary schools, and administrative agencies are concentrated around the city hall, which leads to traffic congestion. It was identified that Jung-gu and Dong-gu are vulnerable groups because many large-scale apartment complexes, elementary schools, and rehabilitation hospitals are located in the regions. In Daedeok-gu, types of vulnerable groups were seen in the areas with aged population. Furthermore, types of pollution were shown in the regions where the Daedeok Industrial Complex, energy industry combustion facilities, and waste treatment facilities are located. The result of this study can be utilized as basic data to establish a customized policy for fine dust reduction according to the identified types of vulnerabilities.
참고문헌 (23)
- 최광용, "MODIS 위성영상에 탐지된 동아시아 지역 초미세 먼지의 시·공간적 패턴", 기후연구, 16(3), pp.229~245 (2021), 기후연구소[DOI]
- 최효, "가을 황사발생 시 고비사막에서 수송된 극미세입자가 입자상물질 농도 (PM10, PM2.5, PM1)에 미친 영향 -2003년 10월 27일 사례-", 기후연구, 5(3), pp.219~233 (2010), 기후연구소
- 은상규, "Fuzzy set을 이용한 실시간 지점단위 농경지 침수위험 지수 산정", 농촌계획, 20(2), pp.1~10 (2014), 한국농촌계획학회[DOI]
- 한진희, "미세먼지 발생 레미콘시설에서의 대기확산모델 CALPUFF와 AERMOD 비교 분석", 한국환경보건학회지, 47(3), pp.267~278 (2021), 한국환경보건학회[DOI]
- 황승연, "R을 이용한 서울시 교통량과 미세먼지 발생의 상관관계 분석", 한국인터넷방송통신학회 논문지, 19(4), pp.139~149 (2019), 한국인터넷방송통신학회[DOI]
- 강정은, "퍼지모형과 GIS를 활용한 기후변화 홍수취약성 평가 - 서울시 사례를 중심으로 -", 한국지리정보학회지, 15(3), pp.119~136 (2012), 한국지리정보학회
- 김대욱, "GIS 기반 대구시 대기오염지도 구축에 관한 연구", 대구경북연구, 18(3), pp.25~47 (2019), 재단법인 경북연구원[DOI]
- Kim, D. Y, "Establishment of Investigation System on Air Pollutants Emission Facilities in Gyeonggi-Do", Gyeonggi Research Insititute, 2017(81), pp.1~136 (2017)
- 김형갑, "진주지역 시정과 미세먼지(PM10) 농도와의 상관관계", 한국환경과학회지, 26(4), pp.535~542 (2017), 한국환경과학회[DOI]
- 김성호, "주성분분석을 활용한 우리나라 주요 기업의 특허 경쟁력 분석", 산업혁신연구, 36(4), pp.213~241 (2020), 산업개발연구소[DOI]
- 고재철, "대기확산모델을 이용한 산업단지 내 미세먼지 확산 특성 분석", 한국환경기술학회지, 19(4), pp.366~374 (2018), 한국환경기술학회[DOI]
- 이명호, "GIS 공간분석을 활용한 사회 취약지역의 분석에 관한 연구 : 서울특별시를 중심으로", 대한공간정보학회지, 24(4), pp.47~58 (2016), 대한공간정보학회[DOI]
- 이슬찬, "GLDAS 수문기상인자를 이용한 초미세먼지 농도 추정", 대한원격탐사학회지, 35(6-1), pp.919~932 (2019), 대한원격탐사학회[DOI]
- 이원정, "부산지역 미세먼지에 대한 건강 취약성 평가", 한국환경보건학회지, 40(5), pp.355~366 (2014), 한국환경보건학회[DOI]
- Ministry of Environment, "Fine Dust, What Is It?" (2016)
- Report of High-concentration Fine Dust Contribution Rate Analysis in March at Domestic and Foreign, "National Institute of Environment Research", ~ (2018)
- 박진우, "대기오염확산모델을 이용한 유동인구의 대기오염 노출에 관한 연구", 국토지리학회지, 52(2), pp.193~204 (2018), 국토지리학회
- 류형원, "미세먼지(PM10) 오염농도와 토지피복간의 상관성 분석을 통한 GWR 모델의 적합성 평가", 한국사진지리학회지, 29(1), pp.73~84 (2019), 한국사진지리학회[DOI]
- Stempvoort, D. V, "Aquifer vulnerablity index: a GIS–compatible method for groundwater vulnerability mapping", Canadian Water Resources Journal, 18(1), pp.25~37 (2013)
- 원태연, "도로 주변 지역의 CCTV영상을 이용한 야간시간대 미세먼지 농도 추정", 한국측량학회지, 39(6), pp.393~399 (2021), 한국측량학회[DOI]
- "AirKorea"[URL]
- "Daejeon Metropolitan City"[URL]
- "National Air Emission Inventory and Research Center"[URL]