DOI QR코드

DOI QR Code

An Exploratory Study on the Effect of LCZ Type on Particulate Matter

LCZ 유형이 미세먼지에 미치는 영향에 관한 탐색적 연구

  • Yeonju Kim (Department of Urban Planning and Engineering, Pusan National University) ;
  • Hansol Mun (Department of Urban Planning and Engineering, Pusan National University) ;
  • Juchul Jung (Department of Urban Planning and Engineering, Pusan National University)
  • Received : 2023.09.27
  • Accepted : 2023.10.19
  • Published : 2023.10.31

Abstract

As of 2019, Korea's fine dust is the most severe among 38 OECD countries, and in the same year, 「the Framework on Disaster and Safety Management」 was revised to define fine dust as a social disaster. Currently, the government is working to achieve its emission reduction goals by preparing a comprehensive fine dust management plan (2022-2023) consisting of a total of five areas, 42 tasks, and 177 detailed tasks. However, it is necessary to come up with measures in consideration of the various spatial characteristics of the city, not just as a source of emission. Therefore, in this study, the shape of the city was classified using the LCZ (Local Climate Zone) classification system into 17 types by building type and land cover type in Busan, and the average annual PM10 and PM2.5 concentration were mapped using the IDW technique. In addition, Fragstats and Moving Window were used to quantify the LCZ classification system. Finally, correlation analysis and regression analysis were conducted to analyze the relationship between the LCZ classification system and PM10 and PM2.5. As a result, it was confirmed that the type of low height of the building and the type of green space with trees had a positive effect on the concentration of PM10 and PM2.5. Therefore, this study is expected to be used as basic data to establish fine dust reduction policies based on efficient spatial planning.

2019년 기준 우리나라는 OECD 38개 국가들 중에서 미세먼지가 가장 심각한 수준이며 같은 해 「재난 및 안전관리 기본법」을 개정하여 미세먼지를 사회재난으로 규정하였다. 현재 정부는 총 5대 분야, 42개 과제, 177개 세부과제로 구성된 미세먼지 관리 종합계획(2022년~2023년)을 마련하여 배출량 저감 목표를 달성하기 위해 노력하고 있다. 하지만 단순히 배출원으로만 저감대책을 세우는 것이 아니라, 도시의 다양한 공간 특성을 고려하여 대책을 마련할 필요가 있다. 따라서 본 연구에서는 부산광역시를 대상으로 도시의 건축물유형과 토지피복유형별 17개의 형태로 분류된 LCZ(Local Climate Zone)분류체계를 활용하여 도시의 형태를 분류하였고, IDW기법을 활용하여 연평균 PM10, PM2.5 농도를 매핑하였다. 또한, LCZ분류체계를 정량화하기 위해 Fragstats와 Moving window를 활용하였다. 마지막으로 상관분석과 회귀분석을 실시하여 LCZ분류체계와 PM10, PM2.5 간의 관계를 분석하였다. 그 결과, 건축물의 높이가 낮은 유형과 나무가 있는 녹지 유형은 PM10, PM2.5 농도에 긍정적인 영향을 주는 것을 확인할 수 있었다. 따라서 본 연구는 효율적인 공간계획에 기반한 미세먼지 저감 정책 수립을 위해 기초 자료로 활용될 것으로 기대된다.

Keywords

Acknowledgement

이 논문은 국토교통부의 스마트시티 혁신인재육성사업과 환경부 「기후변화특성화대학원사업」의 지원으로 수행되었습니다.

References

  1. Air quality standard substances. 2023. AirKorea. Available from: https://www.airkorea.or.kr/web/airMatter?pMENU_NO=130
  2. Basic status. 2023. Busan. 2023. Available from: https://www.busan.go.kr/index
  3. Brousse O, Martilli A, Foley M, Mills G, Bechtel B. 2016. WUDAPT, an efficient land use producing data tool for mesoscale models? Integration of urban LCZ in WRF over Madrid. Urban Climate, 17: 116-134. https://doi.org/10.1016/j.uclim.2016.04.001
  4. Cho HL, Jeong JC. 2009. The distribution analysis of PM10 in Seoul using spatial interpolation methods. Journal of Environmental Impact Assessment, 18(1): 31-39. [Korean Literature]
  5. Demuzere M, Kittner J, Bechtel B. 2021. LCZ Generator: a web application to create Local Climate Zone maps. Frontiers in Environmental Science, 9: 637455.
  6. Ebi KL, McGregor G. 2008. Climate change, tropospheric ozone and particulate matter, and health impacts. Environmental health perspectives, 116(11): 1449-1455.
  7. Efforts to reduce fine dust. 2023. National Fine dust information Center. Available from: https://www.air.go.kr/main.do
  8. Fine dust (PM2.5) concentration. 2022. Kindicator. Available from: https://www.index.go.kr/unify/idx-info.do?idxCd=4275
  9. Gottschalk TK, Bertling M, Wolters V, Biermann J. 2008. A new MW algorithm to speed up landscape index calculation of high resolution maps. Geoinformatics paves the highway to digital Earth. Institut fur Geoinformatik und Fernerkundung, University of Osnabruck, Osnabruck, pp. 29-32.
  10. Hankey S, Marshall JD. 2017. Urban form, air pollution, and health, Current Environmental Health Reports, 4: 491-503. https://doi.org/10.1007/s40572-017-0167-7
  11. Jeong HJ, Lee YJ, Lee SY, Han JY, Kim YW, Lee SJ. 2021. Association between farmers' perceived susceptibility to fine dust exposure and attitudes toward wearing masks and participating in respiratory disease prevention education. Rural Medicine.Regional Health, 46(2): 78-88. [Korean Literature]
  12. Jha DK, Sabesan M, Das A, Vinithkumar NV, Kirubagaran R. 2011. Evaluation of Interpolation Technique for Air Quality Parameters in Port Blair, India. Universal Journal of Environmental Research & Technology, 1(3).
  13. Kang JE, Choi HS, Hwang HS, Lee SH. 2018. Analysis of Ecological Network According to Invalidation of Decision on Urban Parks: Focused on Busan. Journal of Environmental Impact Assessment, 27(6): 618-634. [Korean Literature]
  14. Kang SJ. 2021. Analysis of correlation between urbanization type and fine dust: Cases of five metropolitan cities. GRI Research Journal, 23(3): 1-16. [Korean Literature]
  15. Kang SW, Moon HS, Park HM, Jeong JC. 2023. Applicability analysis of urban climate zones using land use/cover (LULC) data. Journal of the Korean Geographic Information Society, 26(1): 69-88. [Korean Literature]
  16. Kang YH, Kim ST, Yoo SH. 2020. Evaluation of the impact of ship emissions on ultrafine dust concentrations in the Busan area. Proceedings of the Korean Society of Atmospheric Environment Conference, pp. 68-68. [Korean Literature]
  17. Kang WM, Ko IS, Park CH, Lee DW. 2012. An Analysis of Changes in Forest Fragmentation and Morphology in Surrounding Landscapes of Maeulsoops and Jinan-gun. Korean Journal of Environmental and Ecology, 26(6): 941-951. [Korean Literature]
  18. Kwon SS, Choi SH. 2012. A Study of the Landscape Analysis at Su-ji/Gi-heung in Young-in city using the FRAGSTATS Model. Journal of Environmental Impact Assessment, 21(5): 781-787. [Korean Literature]
  19. Kim K, Eom JH. 2017. Local Climate Zone classification using WUDAPT Protocol - Seoul Metropolitan City as an example. Journal of the Korean Society of Landscape Architecture, 45(4): 131-142. [Korean Literature]
  20. Kim HJ, Jo WK. 2012. Assessment of PM-10 monitoring stations in Daegu using GIS interpolation. Journal of Korean Society for Geospatial Information Science, 20(2): 3-13. [Korean Literature] https://doi.org/10.7319/kogsis.2012.20.2.003
  21. Kim JH, Choi JH, Kim CS. 2010. Comparative Evaluation of Interpolation Accuracy for CO2 Emission using GIS. Journal of Environmental Impact Assessment, 19(6): 647-656. [Korean Literature]
  22. Kim YS, Sim KM, Jung MP, Choi IT. 2014. Accuracy comparison of air temperature estimation using spatial interpolation methods according to application of temperature lapse rate effect. Journal of Climate Change Research, 5(4): 323-329 [Korean Literature] https://doi.org/10.15531/ksccr.2014.5.4.323
  23. Kim WS, Yoon DK. 2023. Examining the Impacts of Urban Compactness on Fine Particulate Matter Concentration in Korea. Journal of Korea Planning Association, 58(2): 116-130 [Korean Literature] https://doi.org/10.17208/jkpa.2023.04.58.2.116
  24. Lee GW. 2023. Reconsideration of reduction calculation methods for fine dust reduction techniques at the urban and architectural planning stage - Focusing on the unit method. KIEAE Journal, 23(4): 13-22. [Korean Literature] https://doi.org/10.12813/kieae.2023.23.4.013
  25. Lee SB. 2007. Study on Landscape Ecological Methodology for Ecological Ridgeline Analysis. Korea Environment Institute. [Korean Literature]
  26. Lee IS, Yoon EJ. 2008. Analysis of Scale Sensitivity of Landscape Indices for the Assessment of Urban Green Areas. Journal of the Korean Institute of Landscape Architecture, 36(2): 69-79. [Korean Literature]
  27. Lee TS, Song BG, Han CB, Park KH. 2011.Analysis of the GIS-based water cycle system for effective rainwater management of Gyeongsangnam-do. Journal of the Korean Association of Geographic Information Studies, 14(2): 82-95 [Korean Literature] https://doi.org/10.11108/kagis.2011.14.2.082
  28. McGarigal K. 1995. FRAGSTATS: spatial pattern analysis program for quantifying landscape structure (Vol. 351). US Department of Agriculture, Forest Service, Pacific Northwest Research Station.
  29. McGarigal K. 2015. FRAGSTATS help. University of Massachusetts: Amherst, MA, USA, p. 182.
  30. McGarigal K, Cushman SA. 2005. The gradient concept of landscape structure. Issues and perspectives in landscape ecology. Cambridge University Press, Cambridge, 112-119.
  31. Mun HS, Li MI, Jung JC. 2022. Spatial-temporal characteristics and influencing factors of particulate matter: Geodetector approach. Land, 11(12): 2336. [Korean Literature]
  32. Mun HS, Song BG, Seo KH, Kim TH, Park KH. 2020. PM2 using GIS spatial interpolation. 5 Analysis of distribution characteristics - targeting urban areas in Changwon City. Journal of the Korean Geographic Information Society, 23(2): 1-20. [Korean Literature]
  33. Oh KS, Koo JH, Cho CJ. 2005. mpact of urban form components on regional air pollution: Seoul as a case study. National Territorial Planning, 40(3): 159-170. [Korean Literature]
  34. Shi Y, Ren C, Lau KKL, Ng E. 2019. Investigating the influence of urban land use and landscape pattern on PM2.5 spatial variation using mobile monitoring and WUDAPT. Landscape and Urban Planning, 189: 15-26. https://doi.org/10.1016/j.landurbplan.2019.04.004
  35. Stewart ID, Oke TR. 2012. Local climate zones for urban temperature studies. Bulletin of the American Meteorological Society, 93(12): 1879-1900. https://doi.org/10.1175/BAMS-D-11-00019.1
  36. Yuan C, Ng E, Norford LK. 2014. Improving air quality in high-density cities by understanding the relationship between air pollutant dispersion and urban morphologies. Building and Environment, 71: 245-258. https://doi.org/10.1016/j.buildenv.2013.10.008
  37. Yang H, Leng Q, Xiao Y, Chen W. 2022. Investigating the impact of urban landscape composition and configuration on PM2.5 concentration under the LCZ scheme: A case study in Nanchang, China. Sustainable Cities and Society, 84: 104006.