Journal of Korean Society for Quality Management (품질경영학회지)

Korean Society for Quality Management (한국품질경영학회)
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Regional Analysis of Extreme Values by Particulate Matter(PM2.5) Concentration in Seoul, Korea

서울시 초미세먼지(PM2.5) 지역별 극단치 분석

  • Oh, Jang Wook (Department of Industrial.Information Systems Engineering, Soongsil University) ;
  • Lim, Tae Jin (Department of Industrial.Information Systems Engineering, Soongsil University)
  • 오장욱 (숭실대학교 산업.정보시스템공학과) ;
  • 임태진 (숭실대학교 산업.정보시스템공학과)
  • Received : 2019.02.07
  • Accepted : 2019.02.25
  • Published : 2019.03.31
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Abstract

Purpose: This paper aims to investigate the concentration of fine particulate matter (PM2.5) in the Seoul area by predicting unhealthy days due to PM2.5 and comparing the regional differences. Methods: The extreme value theory is adopted to model and compare the PM2.5 concentration in each region, and each best model is selected through the goodness of fitness test. The maximum likelihood estimation technique is applied to estimate the parameters of each distribution, and the fitness of each model is measured by the mean absolute deviation. The selected model is used to estimate the number of unhealthy days (above $75{\mu}g/m^3$ PM2.5 concentrations) in each region, with which the actual number of unhealthy days are compared. In addition, the level of PM2.5 concentration in each region is analyzed by calculating the return levels for periods of 6 months, 1 year, 3 years, and 5 years. Results: The Mapo (MP) area revealed the most unhealthy days, followed by Gwanak (GW) and Yangcheon (YC). On the contrary, the number of unhealthy days was low in Seodaemun (SDM), Songpa (SP) and Gangbuk (GB) areas. The return level of PM2.5 was high in Gangnam (GN), Dongjak (DJ) and YC. It will be necessary to prepare for PM2.5 than other regions. On the contrary, Gangbuk (GB), Nowon (NW) and Seodaemun (SDM) showed relatively low return levels for PM2.5. However, in most of the regions of Seoul, PM25 is generated at a very poor level ($75{\mu}g/m^3$) every 6months period, and more than $100{\mu}g/m^3$ PM2.5 occur every 3 years period. Most areas in Seoul require more systematic management of PM2.5. Conclusion: In this paper, accurate prediction and analysis of high concentration of PM2.5 were attempted. The results of this research could provide the basis for the Seoul Metropolitan Government to establish policies for reducing PM2.5 and measuring its effects.

Keywords

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Figure 1. Boxplots of PM2.5 concentration for the districts in Seoul

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Figure 2. Analysis procedure of this research

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Figure 3. Diagnostic plots of GEV and GPD fitting for Dong-Jak(DJ) district

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Figure 4. The residuals and MAD of fitted distributions for Dong-Jak(DJ) district

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Figure 5. Return level maps of the PM2.5 concentration classified by districts

Table 1. Glossary of Terms

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Table 2. Basic statistics of PM2.5 concentration for each district in Seoul (2014.01~2018.06)

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Table 3. The PDF and CDF of fitted distributions

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Table 4. Selection of the best model and the MLE for each district

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Table 5. Predicted number of unhealthy days (above 75μg/m3 PM2.5) for each district

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Table 6. Return levels of the PM2.5 concentration for each district

PJGOB9_2019_v47n1_47_t0006.png 이미지

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