A Comparative Study on PM10 Source Contributions in a Seoul Metropolitan Subway Station Before/After Installing Platform Screen Doors

서울시 지하철 승강장의 스크린도어 설치 전·후 PM10 오염원의 기여도 비교 연구

  • Lee, Tae-Jung (Department of Environmental Science and Engineering, Kyung Hee University) ;
  • Jeon, Jae-Sik (Seoul Metropolitan Government Research Institute of Public Health and Environment) ;
  • Kim, Shin-Do (Department of Environmental Engineering, University of Seoul) ;
  • Kim, Dong-Sool (Department of Environmental Science and Engineering, Kyung Hee University)
  • 이태정 (경희대학교 환경학 및 환경공학과) ;
  • 전재식 (서울특별시 보건환경연구원) ;
  • 김신도 (서울시립대학교 환경공학과) ;
  • 김동술 (경희대학교 환경학 및 환경공학과)
  • Received : 2010.05.18
  • Accepted : 2010.09.03
  • Published : 2010.10.31


Almost five million citizens a day are using subways as a means of traffic communication in the Seoul metropolitan. As the subway system is typically a closed environment, indoor air pollution problems frequently occurs and passengers complain of mal-health impact. Especially $PM_{10}$ is well known as one of the major pollutants in subway indoor environments. The purpose of this study was to compare the indoor air quality in terms of $PM_{10}$ and to quantitatively compare its source contributions in a Seoul subway platform before and after installing platform screen doors (PSD). $PM_{10}$ samples were collected on the J station platform of Subway Line 7 in Seoul metropolitan area from Jun. 12, 2008 to Jan. 12, 2009. The samples collected on membrane filters using $PM_{10}$ mini-volume portable samplers were then analyzed for trace metals and soluble ions. A total of 18 chemical species (Ba, Mn, Cr, Cd, Si, Fe, Ni, Al, Cu, Pb, Ti, $Na^+$, $NH_4^+$, $K^+$, $Mg^{2+}$, $Ca^{2+}$, $Cl^-$, and ${SO_4}^{2-}$) were analyzed by using an ICP-AES and an IC after performing proper pre-treatments of each sample filter. Based on the chemical information, positive matrix factorization (PMF) model was applied to identify the source of particulate matters. $PM_{10}$ for the station was characterized by three sources such as ferrous related source, soil and road dust related source, and fine secondary aerosol source. After installing PSD, the average $PM_{10}$ concentration was decreased by 20.5% during the study periods. Especially the contribution of the ferrous related source emitted during train service in a tunnel route was decreased from 59.1% to 43.8% since both platform and tunnel areas were completely blocked by screen doors. However, the contribution of the fine secondary aerosol source emitted from various outside combustion activities was increased from 14.8% to 29.9% presumably due to ill-managed ventilation system and confined platform space.


  1. 서울시(2007) 서울시 통계연보, 2006.
  2. 인천메트로(2008) 인천메트로 내부자료.
  3. Choi, H.W., I.J. Hwang, S.D. Kim, and D.S. Kim (2004) Determination of source contribution based on aerosol number and mass concentration in the Seoul Subway Station, J. Korean Soc. Atmos. Environ., 20(1), 17-31. (in Korean with English abstract)
  4. Chueinta, W., P.K. Hopke, and P. Paatero (2000) Investigation of sources of atmospheric aerosol at urban and suburban residential area in Thailand by positive matrix factorization, Atmospheric Environment, 34(20), 3319-3329.
  5. Cooper, J.A. and J.G. Watson (1980) Receptor oriented methods of air particulate source apportionment, J. of the Air Pollution Control Association, 30(10), 1116-1125.
  6. Han, G.H. (2002) Source Contribution Studies bt SEM/EDX in Seoul Subway Station, Master’s thesis of Kyung Hee University.
  7. Hopke, P.K., Z. Ramadana, P. Paaterob, G.A. Norrisc, M.S. Landisc, R.W. Williamsc, and C.W. Lewisc (2003) Receptor modeling of ambient and personal exposure samples: 1998 Baltimore Particulate Matter Epidemiology-Exposure Study, Atmospheric Environment, 37, 3289-3302.
  8. Kim, E., P.K. Hopke, and E.S. Edgerton (2004) Improving source identification of Atlanta aerosol using temperature resolved carbon fractions in Positive Matrix Factorization, Atmospheric Environment, 38(2), 3349-3362.
  9. Kim, E., P.K. Hopke, and Y. Qin (2005) Estimation of organic carbon blank values and error structures of the speciation trend network data for source apportionment, Air & Waste Management Association, 55, 1190-1199.
  10. Lee, E., C.K. Chan, and P. Paatero (1999) Application of positive matrix factorization in source apportionment of particulate pollutants in Hong Kong, Atmospheric Environment, 33(19), 3201-3212.
  11. Lee, H.W., T.J. Lee, S.S. Yang, and D.S. Kim (2008) Identification of atmospheric $PM_{10}$ sources and estimating their contributions to the Yongin-Suwon bordering area by using PMF, J. Korean Soc. Atmos. Environ., 24(4), 439-454. (in Korean with English abstract)
  12. Lee, J.H., Y. Youshida, B.J. Turpin, P.K. Hopke, R.L. Poirot, P.J. Lioy, and J.C. Oxley (2002) Identification of sources contributing to Mid-Atlantic regional aerosol, Air & Waste Management Association, 52(10), 1186-1205.
  13. Li, Z., P.K. Hopke, L. Husain, S. Qureshi, V.A. Dutkiewicz, J.J. Schwab, F. Drewnick, and K.L. Demerjian (2004) Sources of fine particle composition in New York city, Atmospheric Environment, 38(38), 6521-6529.
  14. Nitta, H., M. Ichikawa, M. Sato, S. Konishi, and M. Ono (1994) A new approach based on a covariance structure model to source apportionment of indoor fine particles in Tokyo, Atmospheric Environment, 28(4), 631-636.
  15. Oh, M.S., T.J. Lee, and D.S. Kim (2009) Source identification of ambient size-by-size particulate using the positive matrix factorization model on the border of Yongin and Suwon, Journal of Korean Society for Atmospheric Environment, 25(2), 108-121.
  16. Paatero, P. (1997) Least squares formulation of robust nonnegative factor analysis, Chemom. Intell. Lab. Syst., 37, 23-35.
  17. Paatero, P. (1998) User’s Guide for Positive Matrix Factorization Program PMF2 and PMF3, Part 1: Tutorial, University of Helsinki.
  18. Paatero, P. and U. Tapper (1993) Analysis of different models of factor analysis as least squares fit problems, Chemom. Intell. Lab. Syst., 18, 183-194.
  19. Paatero, P. and U. Tapper (1994) Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values, Environmetrics, 5, 111-126.
  20. Paatero, P., P.K. Hopke, B.A. Begum, and S.K. Biswas (2005) A graphical diagnostic method for assessing the rotation in factor analytical models of atmospheric pollution, Atmospheric Environment, 39, 193-201.
  21. Pilinis, C. and R.J. Farber (1991) Evaluation of the effects of emission reductions on secondary particulate matter in the south coast air basin of California, Air & Waste Management Association, 41(5), 702-709.
  22. Polissar, A.V., P.K. Hopke, P. Paatero, W.C. Malm, and J.F. Sisler (1998) Atmospheric aerosol over Alaska, 2. Elemental composition and sources, J. of Geophysical Research, 103(D15), 19045-19057.
  23. Ramadan, Z., X.H. Song, and P.K. Hopke (2000) Identification of sources of phoenix aerosol by positive matrix factorization, Air & Waste Management Association, 50(8), 1308-1320.
  24. Song, X.H., A.V. Polissar, and P.K. Hopke (2001) Source of fine particle composition in the northeastern US, Atmospheric Environment, 35(31), 5277-5286.
  25. U.S. EPA (1999) Air quality criteria for particulate matter, Volume I, EPA/600/P-99/002a.
  26. U.S. EPA (2006) SPECIATE Ver 4.0.
  27. Yoo, J.S., D.S. Kim, and Y.S. Kim (1995) Quantitative source estimation of PM-10 in Seoul area, Journal of Korean Society for Atmospheric Environment, 11(3), 279-290.
  28. Zhao, W. and P.K. Hopke (2006) Source identification for fine aerosols in Mammoth Cave National Park, Atmospheric Research, 80, 309-322.
  29. Zhao, W., P.K. Hopke, E.W. Gelfand, and N. Rabinovitch (2007) Use of an expanded receptor model for personal exposure analysis in schoolchildren with asthma, Atmospheric Environment, 41(19), 4084-4096.

Cited by

  1. in the Subway Passenger Cabins vol.27, pp.5, 2011,
  2. A Noticeable Change in Indoor Radon Levels After Platform Screen Doors Installation in Seoul Subway Station vol.28, pp.1, 2012,
  3. Indoor Radon Levels in the Subway Cabins of the Seoul Metropolitan Area vol.28, pp.4, 2012,
  4. Management Policy and Control Technology for Indoor Air Quality in Korea vol.29, pp.4, 2013,
  5. Field measurement and estimation of ventilation flow rates by using train-induced flow rate through subway vent shafts vol.28, pp.7, 2014,
  6. Evaluation on Indoor Air Quality by Statistical Analysis of Indoor Air Pollutants Concentration in a Seoul Metropolitan Underground Railway Station vol.30, pp.3, 2014,
  7. A study on the improvement of the air exhaust system at the PSD installed subway station vol.17, pp.3, 2015,
  8. Concentration and Properties of Particulate Matters (PM10 and PM2.5) in the Seoul Metropolitan vol.31, pp.2, 2015,
  9. Comparison of PM2.5 Pollution Status at a Major Transit Subway Station in Seoul vol.31, pp.3, 2015,
  10. The Size-Oriented Particulate Mass Ratios and Their Characteristics on the Seoul Metropolitan Subway Lines vol.10, pp.4, 2016,
  11. Transient variation of aerosol size distribution in an underground subway station vol.188, pp.6, 2016,
  12. Characterizing Par ticle Matter on the Main Section of the Seoul Subway Line-2 and Developing Fine Particle Pollution Map vol.32, pp.2, 2016,
  13. in a subway tunnel using positive matrix factorization vol.64, pp.12, 2014,
  14. Status of particulate matter pollution in urban railway environments vol.17, pp.4, 2018,