Journal of Cadastre & Land InformatiX (지적과 국토정보)

LX Spatial Information Research Institute (한국국토정보공사 공간정보연구원)
권호 표지
DOI QR코드

DOI QR Code

Spatial distribution of particulate matters in comparison with land-use and traffic volume in Seoul, Republic of Korea

서울시 토지이용과 교통량에 따른 미세먼지의 공간분포

  • 정종철 (남서울대학교 공간정보학과) ;
  • 이상훈 (한양대학교 도시대학원)
  • Received : 2018.05.04
  • Accepted : 2018.06.27
  • Published : 2018.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

To sustainably monitor air pollution in Seoul, the number of Air Pollution Monitoring Station has been gradually increased by Korea's Ministry of Environment. Although particulate matters(PM), one of the pollutants measured at the stations, have an significant influence on human body, the concentration of PM in Korea came in second among 35 OECD member countries. In this study, using the data of PM concentration from the stations, distribution maps of PM10 and PM2.5 concentrations over Seoul were generated, and spatial factors potentially related to PM distribution were investigated. Based on a circumscribed hexagon about a circle in radius of 500 meters created as a basic unit, Seoul was sectionalized and PM concentration map was generated using the interpolation technique of 'inverse distance weighting'. The distributions of PM concentrations were investigated with commuting time by administrative district and the outcome was related with land-use type and volume of traffic. Results from this analysis indicated distribution pattern of PM10 concentration was different from that of PM2.5 by administrative district and time. The distribution of PM concentration was strongly related to not only the size of business and trafficked areas among the land-use type, but also the existence of urban green. Further analysis of the relationship between the PM concentration and detailed land-use and urban green maps can be helpful to identify spatial factors which have an impact on the PM concentration on the regional scale.

서울시의 대기오염을 지속적으로 모니터링하기 위해, 그동안 환경부는 운영하고 있는 대기오염 측정망을 지속적으로 발전시켜왔다. 측정되는 대기오염 물질 중 미세먼지는 인체에 상당한 영향을 미치는데, 우리나라의 오염도는 OECD 국가 중에서도 두 번째로 높은 편이다. 따라서 본 연구에서는 측정된 미세먼지 농도 자료를 이용하여 서울시의 미세먼지 분포도를 PM10과 PM2.5에 대해 작성하고, 미세먼지 농도의 분포에 영향을 미칠 것으로 예상되는 공간적인 요인들과의 관계를 조사하였다. 반경 500m의 원을 포함하는 헥사곤을 기준단위로 하여 서울 전역을 구획화하고 보간법 중 거리반비례기법을 이용하여 미세먼지 농도분포도를 작성하였다. 출, 퇴근 시간대의 미세먼지 농도분포를 지역별로 분석하고, 토지이용도 및 교통량과의 관계를 분석하였다. 분석결과, PM10과 PM2.5의 농도분포는 지역별, 시간대별로 각기 다른 패턴을 나타내었고, 토지이용형태 측면에서는 상업지역 및 교통지역의 면적이 미세먼지 농도분포와 높은 관련성을 보였으며, 녹지의 유무도 농도의 분포 변화에 관계가 있는 것으로 판단되었다. 추후 세부적인 토지이용도 및 녹지분포도 등을 통하여 상관관계를 분석하면 미세먼지의 농도에 영향을 미치는 지역 수준에서의 공간요소를 밝히는데 도움이 될 것으로 기대된다.

Keywords

References

  1. Choi IJ, Jo WK, Sin SH. 2016. Evaluation of Air Pollution Monitoring Networks in Seoul Metropolitan Area using Multivariate Analysis. Journal of Environmental Science International. 25(5):673-681. https://doi.org/10.5322/JESI.2016.25.5.673
  2. Duan J, Tan J, Wang S, Hao J, Chai F. 2012. Size distributions and souirces of elements in particulate matter at curbside, urban and rural sites in Beijing. Journal of Environmental Sciences. 24(1):87-94. https://doi.org/10.1016/S1001-0742(11)60731-6
  3. Han SW, Lee SH, Lee HW. 2015. Study on the characteristics of PM distribution in coastal and inland cities correlation and its correlation. Journal of Environmental Science International. 24(11):1513-1523. https://doi.org/10.5322/JESI.2015.24.11.1513
  4. Jeong JC. 2014. A Spatial Distribution Analysis and Time Series Change of PM10 in Seoul City. Journal of the Korean Association of Geographic Information Studies. 17(1):61-69. https://doi.org/10.11108/kagis.2014.17.1.061
  5. Ju JH, Hwang IJ. 2011. A Study for Spatial Distribution of Principal Pollutants in Daegu Area Using Air Pollution Monitoring Network Data. Journal of Korean Society for Atmospheric Environment. 27(5):545-557. https://doi.org/10.5572/KOSAE.2011.27.5.545
  6. Jung JH, Lee HD, Shon BH. 2012. Assessment of location of the air quality monitoring stations according to the analysis of wind sector division in Pohang. Journal of the Korea Academia-Industrial cooperation Society. 13(4):1931-1938. https://doi.org/10.5762/KAIS.2012.13.4.1931
  7. Jung JH, Choi WJ, Leem HH, Shon BH. 2010. Health and Environmental Risk Assessment of Pollutants in Pohang. Journal of the Korea Academia-Industrial cooperation Society. 11(7):2719-2726. https://doi.org/10.5762/KAIS.2010.11.7.2719
  8. Kim AY and Kwon CH. 2016. Study on optimal location of air pollution monitoring networks in urban area using GIS:Focused on the case of Seoul city. Journal of the Korea Society of disaster information. 12(4):358-365. https://doi.org/10.15683/kosdi.2016.12.31.358
  9. Lee HD, Lee GH, Kim ID, Kang JS, Oh KJ. 2013. The influences of concentration distribution and movement of air pollutants by sea breeze and mist around Onsan Industrial Complex. Clean Technology. 19(2):95-104. https://doi.org/10.7464/ksct.2013.19.2.095
  10. Lee KS. 2008. Spatio-temporal analysis of urban population exposure to traffic related air pollution. Journal of the Economic Geographical Society of Korea. 11(1):59-77. https://doi.org/10.23841/egsk.2008.11.1.59
  11. Lee YK, Lee KJ, Lee JS, Shin ES. 2012. Regional Characteristics of Particle Size Distribution of PM10. Journal of Korean Society for Atmospheric Environment. 28(6):666-674. https://doi.org/10.5572/KOSAE.2012.28.6.666
  12. ME. 2013. Guidelines for action plan of area air quality regulations. Ministry of Environment.
  13. NIER. 2013. Planning research on building a management system for advancing Korea's air pollution measurement network. National Institute of Environmental Research(NIER), Ministry of Environment, Seoul, Republic of Korea.
  14. Park JK, Choi YJ, Jung WS. 2015., An analysis on the distribution characteristics of PM10 concentration and its relation of the death from Asthma in Seoul, Korea. Journal of Environmental Science International. 24(7):961-968. https://doi.org/10.5322/JESI.2015.24.7.961
  15. Park JK, Choi YJ, Jung WS. 2016. Understanding on regional characteristics of particular matter in Seoul - distribution of concentration in borough spatial area and relation with the number of registered vehicles. Journal of Environmental Science International. 26(1):55-65. https://doi.org/10.5322/JESI.2017.26.1.55
  16. Park MH, Park MS, Kim HD. 2007. Comparative study on the exhaust of air pollution from Daegu-si between 1998 and 2004. Proceedings of the Korean Environmental Sciences Society Conference. p. 174-178.
  17. Park NW. 2011. Time-series mapping and uncertainty modeling of environmental variables: a case study of PM10 concentration mapping. Journal of the Korean Earth Science Society. 32(3):249-264. https://doi.org/10.5467/JKESS.2011.32.3.249
  18. Samet JM, Dominici F, Curriero FC, Coursac I, Zeger SL. 2000. Fine particulate air pollution and mortality in 20 U.S cities, 1987-1994. The New England Journal of Medicine. 343:1742-1749. https://doi.org/10.1056/NEJM200012143432401
  19. Schwartz J. 1994. Air pollution and daily mortality : a review and meta analysis. Environmental Research. 64(1):36-52. https://doi.org/10.1006/enrs.1994.1005
  20. Shen G, Xue M, Chen Y, Yang C, Li W, Shen H, Huang Y, Zhang Y, Chen H, Zhu Y, Wu H, Ding A, Tao S. 2014. Comparison of carbonaceous particulate matter emission factors among different solid fuels burned in residential stoves. Atmospheric Environment. 89:337-345. https://doi.org/10.1016/j.atmosenv.2014.01.033
  21. Shin DC. 2007. Health effects of ambient particulate matter. Journal of the Korean Medical Association. 50(2):175-182. https://doi.org/10.5124/jkma.2007.50.2.175
  22. Sun Y, Zhuang G, Wang Y, Han L, Guo J, Dan M, Zhang W, Wang Z, Hao Z. 2004. The air-borne particulate pollution in Beijing - concentration, composition, distribution and sources. Atmospheric Environment. 38(35):5991-6004. https://doi.org/10.1016/j.atmosenv.2004.07.009
  23. Wang S, Zhou C, Wang Z, Feng K, Hubacek K. 2017. The Characteristics and drivers of fine particulate matter(PM2.5) distribution in China. Journal of Cleaner Production. 142(4):1800-1809. https://doi.org/10.1016/j.jclepro.2016.11.104