Browse > Article
http://dx.doi.org/10.13087/kosert.2022.25.1.41

Spatial clustering of PM2.5 concentration and their characteristics in the Seoul Metropolitan Area for regional environmental planning  

Lim, Chul-Hee (College of General Education, Kookmin University)
Park, Deuk-Hee (College of General Education, Kookmin University)
Publication Information
Journal of the Korean Society of Environmental Restoration Technology / v.25, no.1, 2022 , pp. 41-55 More about this Journal
Abstract
Social interest in the fine particulate matter has increased significantly since the 2010s, and various efforts have been made to reduce it through environmental plans and policies. To support such environmental planning, in this study, spatial cluster characteristics of fine particulate matter (PM2.5) concentrations were analyzed in the metropolitan area to identify high-risk areas spatially, and the correlation with local environmental characteristics was also confirmed. The PM2.5 concentration for the recent 5 years (2016-2020) was targeted, and representative spatial statistical methods Getis-Ord Gi* and Local Moran's I were applied. As a result of the analysis, the cluster form was different in Getis-Ord Gi* and Local Moran's I, but they show high similarity in direction, therefore complementary results could be obtained. In the high concentration period, the hotspot concentration of the Getis-Ord Gi* method increased, but in Local Moran's I, the HH region, the high concentration cluster, showed a decreasing trend. Hotspots of the Getis-Ord Gi* technique were prominent in the Pyeongtaek-Hwaseong and Yeoju-Icheon regions, and the HH cluster of Local Moran's I was located in the southwest, and the LL cluster was located in the northeast. As in the case of the metropolitan area, in the results of Seoul, there was a phenomenon of division between the northeast and southwest regions. The PM2.5 concentration showed a high correlation with the elevation, vegetation greenness and the industrial area ratio. During the high concentration period, the relation with vegetation greenness increased, and the elevation and industrial area ratio increased in the case of the annual average. This suggests that the function of vegetation can be maximized at a high concentration period, and the influence of topography and industrial areas is large on average. This characteristic was also confirmed in the basic statistics for each major cluster. The spatial clustering characteristics of PM2.5 can be considered in the national land and environmental plan at the metropolitan level. In particular, it will be effective to utilize the clustering characteristics based on the annual average concentration, which contributes to domestic emissions.
Keywords
fine particulate matter; spatial cluster; spatial statistics; environmental planning; Seoul metropolitan area;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Seok Y, Song K, Han H, Lee J. 2021. Derivation of Green Infrastructure Planning Factors for Reducing Particulate Matter -Using Text Mining-. Journal of the Korean Institute of Landscape Architecture. 49(5), 79-96. [Korean Literature]   DOI
2 Shin, YE, Park JS, Kim SY, LEE SW, An KJ. 2021. 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-. Journal of Korean Environmental Restoration Technology, 24(1), 53-68. [Korean Literature]
3 Sung SY. 2020. Environmental Planning Contermeasures Considering Spatial Distribution and Potential Factors of Particulate Matters Concentration. Journal of Korean Environmental Restoration Technology, 23(1), 89-96. [Korean Literature]
4 Statistics of Korea. 2021. Korean Statistics Information Service (https://kosis.kr/index/index.do), Daejeon. Korea.
5 van Donkelaar A, Hammer MS, Bindle L, Brauer M, Brook JR, Garay MJ, Martin RV. 2021. Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty. Environmental Science & Technology, 55(22), 15287-15300.   DOI
6 World Health Organization (WHO), 2017. Evolution of WHO air quality guidelines: past, present and future. WHO Regional Office for Europe, Copenhagen.
7 Park S, Kim SJ, Yu H, Lim CH, Park E, Kim J, Lee WK. 2020. Developing an adaptive pathway to mitigate air pollution risk for vulnerable groups in South Korea. Sustainability, 12(5), 1790.   DOI
8 Lim CH, Ryu J, Choi Y, Jeon SW, Lee WK. 2020. Understanding global PM2. 5 concentrations and their drivers in recent decades (1998-2016). Environment International, 144, 106011.   DOI
9 Yoon EJ. 2020. Application of Environmental Planning Considering the Trend of PM10 in Ambient Air. Journal of Environmental Impact Assessment, 29(3), 210~218. [Korean Literature]   DOI
10 Yeo MJ & Kim YP. 2019. Trends of the PM10 Concentrations and High PM10 Concentration Cases in Korea. Journal of Korean Society for Atmospheric Environment, 35(2), 249-264. [Korean Literature]   DOI
11 Yue H, Huang Q, He C, Zhang X, Fang Z. 2020. Spatiotemporal patterns of global air pollution: A multi-scale landscape analysis based on dust and sea-salt removed PM2.5 data. Journal of Cleaner Production 252, 119887.   DOI
12 Zhang Q, Jiang X, Tong D, Davis SJ, Zhao H, Geng G, Feng T, Zheng B, Lu Z, Streets DG, Ni R, Brauer M, van Donkelaar A, Martin RB, Huo H, Liu Z, Pan D, Kan H, Yan Y, Lin J, He K, Guan D. 2017. Transboundary health impacts of transported global air pollution and international trade. Nature 543 (7647), 705-709.   DOI
13 van Donkelaar A, Martin RV, Brauer M, Hsu NC, Kahn RA, Levy RC, Lyapustin A, Sayer AM, Winker DM. 2016 Global estimates of fine particulate matter using a combined geophysical-statistical method with information from satellites, models, and monitors. Environmental Science & Technology 50(7), 3762-3772.   DOI
14 Kim S, Lim CH, Lim YJ, Moon J, Song C, Lee WK. 2016. Analyzing Climate Zones Using Hydro-Meteorological Observation Data in Andong Dam Watershed, South Korea. Journal of Climate Change Research 7(3), 269-282. [Korean Literature]   DOI
15 Anselin L. 1995 Local indicators of spatial association - LISA -.Geographical Analysis 27(2): 93-115.   DOI
16 Getis A & Ord JK. 1992. The analysis of spatial association by use of distance statistics. Geographical Analysis 24(3): 189-206.   DOI
17 Gyeonggi Research Institute(GRI). 2019. Assessment and Mapping of PM High-risk Region in Seoul Metropolitan Area. Policy Research. 2019-51. [Korean Literature]
18 Kim DY, Choi M, Yoon B. 2019. Analysis of PM Hot-spot Emission Zone in Seoul Metropolitan Area. Journal of Korean Society for Atmospheric Environment, 35(4), 476-501. [Korean Literature]   DOI
19 Kim E, Bae C, Yoo C, Kim BU, Kim HC, Kim S. 2018. Evaluation of the Effectiveness of Emission Control Measures to Improve PM2.5 Concentration in South Korea. Journal of Korean Society for Atmospheric Environment, 34(3), 469-485. [Korean Literature]   DOI
20 Kim SW, Lee DK, Bae CY. 2021. Analysis of the effect of street green structure on PM2.5 in thewalk space -Using microclimate simulation-. Journal of Korean Environmental Restoration Technology, 24(4), 61-75. [Korean Literature]
21 Apte JS, Brauer M, Cohen AJ, Ezzati M, Pope III CA. 2018. Ambient PM2.5 reduces global and regional life expectancy. Environ. Sci. Technol. Lett. 5 (9), 546-551.   DOI
22 Ko YJ, Cho KH. 2020. Analysis of Areas Vulnerable to Urban Heat Island Using Hotspot Analysis -A Case Study in Jeonju City, Jeollabuk-do-. Journal of the Korean Institute of Landscape Architecture. 48(5), 67-79. [Korean Literature]   DOI
23 Park DH, & Lim CH. 2021. A social network analysis of tourism activity patterns among domestic tourists influenced by fine particulate matter (PM2.5) concentration. Korean Journal of Hospitality and Tourism. 30(7), 237-252. [Korean Literature]   DOI
24 Ministry of Environment (MOE). 2019. Management Master Plan of Fine Particulate Matter (2020-2024). Sejong. Korea.
25 Ministry of Environment (MOE). 2020. Annual Report of Atmospheric Environment 2020. Sejong. Korea
26 Oh KS. 2021. A Study on the Governance of SDGs Projects and Environmental Policy between Korea and China: Focusing on Transboundary Fine dust from China. THE JOURNAL OF INTERNATIONAL RELATIONS 24(1), 129-152. [Korean Literature]   DOI
27 Park S, Allen RJ, Lim CH. 2020. A likely increase in fine particulate matter and premature mortality under future climate change. Air Quality, Atmosphere & Health, 13(2), 143-151.   DOI
28 Park S, & Shin H. 2017. Analysis of the Factors Influencing PM2.5 in Korea: Focusing on Seasonal Factors. Envrionmental Policy. 25(1), 227-248. [Korean Literature]
29 Peeters A, Zude M, Kathner J, unlu M, Kanber R, Hetzroni A, Gebbers R, Ben-Gal A. 2015. Getis-Ord's hot-and cold-spot statistics as a basis for multivariate spatial clustering of orchard tree data. Computers and Electronics in Agriculture, 111, 140-150.   DOI
30 Ryoo JY, Kwon TH, Kang IS, Lee KS, Jo CW, Kim JS, Kim HH, Jang W, Park JJ, Yoo TS. 2019. A Study for Characteristics of Fine Particulate Matter and Atmospheric Stagnation Considering Elevation and Backward Trajectory. Journal of Korean Society for Atmospheric Environment, 35(6), 701-712. [Korean Literature]   DOI
31 Ryu YH & Min SK. 2020. What matters in public perception and awareness of air quality? Quantitative assessment using internet search volume data. Environmental Research Letters, 15(9), 0940b4.   DOI
32 Moon KJ, Cheo H, Jeon K, Yang X, Meng F, Kim D, Park HJ, Kim J. 2018. Review on the Current Status and Policy on PM2.5 in China. Journal of Korean Society for Atmospheric Environment, 34(3), 373-392. [Korean Literature]   DOI