Journal of the Korean Society of Environmental Restoration Technology (한국환경복원기술학회지)

The Korea Society of Environmental Restoration Technology (한국환경복원기술학회)
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A Study on Green Space Location Selection to Reduce Particulate Matter by Projecting Distributions of Emission Source and Vulnerable Groups - focusing on Seongdong-gu, Seoul -

미세먼지 배출원과 취약계층 분포 추정을 통한 미세먼지 저감 녹지 입지 선정 연구 - 서울시 성동구를 대상으로 -

  • Shin, Ye-Eun (Dept. of Forestry and Landscape Architecture, Graduate School of Konkuk University) ;
  • Park, Jin-Sil (Dept. of Forestry and Landscape Architecture, Konkuk University) ;
  • Kim, Su-Yeon (Dept. of Forestry and Landscape Architecture, Graduate School of Konkuk University) ;
  • Lee, Sang-Woo (Dept. of Forestry and Landscape Architecture, Konkuk University) ;
  • An, Kyung-Jin (Dept. of Forestry and Landscape Architecture, Konkuk University)
  • 신예은 (건국대학교 대학원 산림조경학과) ;
  • 박진실 (건국대학교 산림조경학과) ;
  • 김수연 (건국대학교 대학원 산림조경학과) ;
  • 이상우 (건국대학교 산림조경학과) ;
  • 안경진 (건국대학교 산림조경학과)
  • Received : 2020.11.12
  • Accepted : 2021.01.10
  • Published : 2021.02.26
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Abstract

The study aims to propose a locating method of green space for reducing Particulate Matter (PM) in ambient air in conjunction with its source traces and vulnerable groups. In order to carry out the aims and purposes, a literature review was conducted to derive indicators of vulnerable area to PM. Based on the developed indicators, the vulnerable areas and green spaces creation strategies for each cluster were developed for the case of Seongdong-gu, Seoul. As a result, six indicators for vulnerability analysis were came out including the vulnerable groups (children's facilities, old people's facilities), emission sources (air pollutant emission workplaces, roads), and environmental indicators (particulate matter concentration, NDVI). According to the six selected indicators, the target area was divided into 39 hexagons and analyzed to result the most vulnerable areas to particulate matter. As a result of comprehensive vulnerability analysis, the Seongsu-dong area was found to be the most vulnerable to particulate matter, and 5 clusters were derived through k-means cluster analysis. Cluster 1 was analyzed as areas that most vulnerable to particulate matter as a result of the comprehensive analysis, therefore urgent need to create green spaces to reduce particulate matter. Cluster 2 was areas that mostly belonged to the Han River. Cluster 3 corresponds to the largest number of hexagons, and since many vulnerable groups are distributed, it was analyzed as a cluster that required the creation of a green spaces to reduce particulate matter, focusing on facilities for vulnerable groups. Three hexagons are included in cluster 4, and the cluster has many roads and lacks vegetation in common. Cluster 5 has a lot of green spaces and is generally distributed with fewer vulnerable groups and emission sources; however, it has a high level of particulate matter concentration. In a situation where various green spaces creation projects for reducing particulate are being implemented, it is necessary to consider the vulnerable groups and emission sources and to present green space creation strategies for each space characteristic in order to increase the effectiveness of such projects. Therefore, this study is regarded as meaningful in suggesting a method for selecting a green area for reducing PM.

Keywords

Acknowledgement

본 연구는 산림청(한국임업진흥원) 산림과학기술 연구개발사업'(2019153B10-2021-0101)'의 지원에 의하여 이루어진 것입니다.

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