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The Variation Analysis on Spatial Distribution of PM10 and PM2.5 in Seoul

서울시 PM10과 PM2.5의 공간적 분포 변이분석

  • 정종철 (남서울대학교 공간정보공학과)
  • Received : 2018.08.19
  • Accepted : 2018.10.19
  • Published : 2018.12.31

Abstract

PM(Particulate Matter) cause serious diseases of air pollution. Most of the studies have analyzed local distribution trends using satellite images or modeling techniques. However,the method using the spatial interpolation method based on the meteorological value is insufficient in Korea. In this study, monthly spatial distribution of $PM_{10}$ and $PM_{2.5}$ in January, February, March, and April of 2018 Seoul Metropolitan City were analyzed based on 39 PM monitoring networks. In addition, a distribution map showing the difference between $PM_{10}$ and $PM_{2.5}$ was based on the distribution obtained through this study. The regions of high $PM_{10}$ and $PM_{2.5}$ emissions were selected. In addition, the correlation between $PM_{10}$ and $PM_{2.5}$ was confirmed through the distribution map. This study analyzed the spatial distribution variation results of analyzing $PM_{10}$ and $PM_{2.5}$ in Seoulthrough spatial analysis technique. As a result of this study, it was confirmed that $PM_{10}$ shows high measured value on the roadside measurement station.

미세먼지는 대기오염 중 심각한 질병을 야기할 수 있는 대기오염 원인물질이다. 이에 대부분의 연구는 위성영상을 활용하거나 모델링 기법을 이용하여 지역적 미세먼지 분포경향을 분석하였다. 하지만 측정소값을 기준으로 공간보간기법을 적용하여 분석하는 방법은 국내에서 부족한 실정이다. 본 연구에서는 서울시 39개의 미세먼지 측정망을 기준으로 2018년도 서울시의 1월, 2월, 3월, 4월 $PM_{10}$$PM_{2.5}$의 월별 공간적인 분포 변이를 분석하였다. 또한 본 연구를 통해 얻어진 분포도를 기반으로 $PM_{10}$$PM_{2.5}$의 차이값을 보여주는 분포도를 제작하였으며, $PM_{10}$의 배출량이 많은 지역과 $PM_{2.5}$의 배출량이 많은 지역을 선정하였다. 또한 $PM_{10}$$PM_{2.5}$의 분포를 비율로 계산하여 분포지도를 제작함으로 각 지역별 $PM_{10}$$PM_{2.5}$의 상호관계를 확인하였다. 본 연구는 공간분석 기법을 통하여 서울시 $PM_{10}$$PM_{2.5}$를 분석하는 공간적 분포변이 결과를 해석하였다. 본 연구의 결과 $PM_{10}$은 도로변 측정소에 높은 측정값을 나타내는 것을 확인할 수 있었다.

Keywords

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Figure 1. Spatial location of PM Monitoring Stations(MS) in Seoul

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Figure 2. Research flow chart.

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Figure 3. PM10 distribution map in 2018 across Seoul. (a) Jan, (b) Feb, (c) Mar, (d) Apr

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Figure 4. PM2.5 distribution map in 2018 across Seoul. (a) Jan, (b) Feb, (c) Mar, (d) Apr

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Figure 5. PM measurement value by 39 monitoring stations in 2018 across Seoul. (a) Jan, (b) Feb, (c) Mar, (d) Apr

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Figure 6. PM10 - PM2.5 distribution map in 2018 across Seoul. (a) Jan, (b )Feb, (c) Mar, (d) Apr

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Figure 7. PM10-PM2.5/PM10 distribution map.

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Figure 8. PM2.5/PM10 distribution map.

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