DOI QR코드

DOI QR Code

Compensation of Light Scattering Method for Real-Time Monitoring of Particulate Matters in Subway Stations

지하역사 내 미세먼지 실시간 모니터링을 위한 광산란법 보정

  • Kim, Seo-Jin (Department of Chemical Engineering, Konkuk University) ;
  • Kang, Ho-Seong (Department of Chemical Engineering, Konkuk University) ;
  • Son, Youn-Suk (Department of Advanced Technology Fusion, Konkuk University) ;
  • Yoon, Sang-Lyeor (Department of Environmental Engineering, Konkuk University) ;
  • Kim, Jo-Chun (Department of Advanced Technology Fusion, Konkuk University) ;
  • Kim, Gyu-Sik (Department of Electrical and Computer Engineering, University of Seoul) ;
  • Kim, In-Won (Department of Chemical Engineering, Konkuk University)
  • 김서진 (건국대학교 화학공학과) ;
  • 강호성 (건국대학교 화학공학과) ;
  • 손윤석 (건국대학교 신기술융합학과) ;
  • 윤상렬 (건국대학교 환경공학과) ;
  • 김조천 (건국대학교 신기술융합학과) ;
  • 김규식 (서울시립대학교 전자전기컴퓨터공학부) ;
  • 김인원 (건국대학교 화학공학과)
  • Received : 2010.05.10
  • Accepted : 2010.08.20
  • Published : 2010.10.31

Abstract

The $PM_{10}$ concentrations in the underground should be monitored for the health of commuters on the underground subway system. Seoul Metro and Seoul Metropolitan Rapid Transit Corporation are measuring several air pollutants regularly. As for the measurement of $PM_{10}$ concentrations, instruments based on $\beta$-ray absorption method and gravimetric methods are being used. But the instruments using gravimetric method give us 20-hour-average data and the $\beta$-ray instruments can measure the $PM_{10}$ concentration every one hour. In order to keep the $PM_{10}$ concentrations under a healthy condition, the air quality of the underground platform and tunnels should be monitored and controlled continuously. The $PM_{10}$ instruments using light scattering method can measure the $PM_{10}$ concentrations every less than one minute. However, the reliability of the instruments using light scattering method is still not proved. The purpose of this work is to study the reliability of the instruments using light scattering method to measure the $PM_{10}$ concentrations continuously in the underground platforms. One instrument using $\beta$-ray absorption method and two different instruments using light scattering method (LSM1, LSM2) were placed at the platform of the Jegi station of Seoul metro line Number 1 for 10 days. The correlation between the $\beta$-ray instrument and the LSM2 ($r^2$=0.732) was higher than that between the $\beta$-ray instrument and the LSM1 ($r^2$=0.393). Thus the LSM2 was chosen for further analysis. Three different regression analysis methods were tested: Linear regression analysis, Nonlinear regression analysis and Orthogonal regression analysis. When the instruments using light scattering method were used, the data measured these instruments have to be converted to actual $PM_{10}$ concentrations using some factors. With these analyses, the factors could be calculated successfully as linear and nonlinear forms with respect to the data. And the orthogonal regression analysis was performed better than the ordinary least squares method by 28.45% reduction of RMSE. These findings propose that the instruments using light scattering method light scattering method can be used to measure and control the $PM_{10}$ concentrations of the underground subway stations.

Keywords

$PM_{10}$;Light scattering method;$\beta$-ray absorption method;Particulate matters;Real-time monitoring

Acknowledgement

Supported by : 서울시

References

  1. 국립환경과학원 환경건강연구부(2008) 실내공기질 공정시험기준 개선 연구.
  2. 채경철(1990) 직교 회귀의 역학적 고찰, 응용통계연구, 3(1), 1047-1058.
  3. Aarnio, P., T. Yli-Tuomi, A. Kousa, T. Makela, A. Hirsikko, K. Hameri, M. Raisanen, R. Hillamo, T. Koskentalo, and M. Jantunen (2005) The concentrations and composition of and exposure to fine particle $(PM_{2.5})$ in the Helsinki subway system, Atmospheric Environment, 39, 5059-5066. https://doi.org/10.1016/j.atmosenv.2005.05.012
  4. Adams, H.S. (2001) Exposure assessment of urban transport user to particulate air pollution, Ph. D., Imperial College London, Department of Environmental Science and Technology, University of London.
  5. Ahn, Y.J., W.T. Kwon, and Y.W. Kim (2004) Estimation of tool life by simple & multiple linear regression analysis of $Si_3N_4$ ceramic cutting tools, Transaction of the Korean Society of Machine Tool Engineers, 13(4), 23-29.
  6. Branis, M. (2006) The contribution of ambient sources to particulate pollution in spaces and trains of the Prague underground transport system, Atmospheric Environment, 40, 348-356. https://doi.org/10.1016/j.atmosenv.2005.09.060
  7. Chan, L.Y., W.L. Lau, S.C. Lee, and C.Y. Chan (2002a) Commuter exposure to particulate matter in public transportation modes in Hong Kong, Atmospheric Environment, 36(21), 3363-3373. https://doi.org/10.1016/S1352-2310(02)00318-7
  8. Chan, L.Y., W.L. Lau, S.C. Zou, Z.X. Cao, and S.C. Lai (2002b) Exposure level of carbon monoxide and respirable suspended particulate in public transportation modes while commuting in urban area of Guangzhou, China, Atmospheric Environment, 36 (38), 5831-5840. https://doi.org/10.1016/S1352-2310(02)00687-8
  9. Cheng, Y.H., Y.L. Lin, and C.C. Liu (2008) Level of $PM_{10}\;and\;PM_{2.5}$ in Taipei Transit System, Atmospheric Environment, 42(31), 7242-7249. https://doi.org/10.1016/j.atmosenv.2008.07.011
  10. Chillrud, S.N.D. Epstein, J.M. Ross, S.N. Sax, D. Pederson, J.D. Spengler, and P.L. Kinney (2004) Elevated airborne exposures of teenagers to manganese, chromium, and iron from steel dust and New York City’s subway system, Environmental Science and Technology, 38(3), 732-737. https://doi.org/10.1021/es034734y
  11. 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)
  12. Fox, J. (2002) Nonlinear regression and nonlinear least squares, Appendix to an R and S-PLUS companion to applied regression.
  13. Furuya, K., Y. Kudo, K. Okinagua, M. Yamuki, K. Takahashi, Y. Araki, and Y. Hisamatsu (2001) Seosonal variation and their characterization of suspended particulate matter in the air of subway stations, Journal of Trace abd Microprobe Technique, 19(4), 469-485. https://doi.org/10.1081/TMA-100107583
  14. Jung, C.H., Y.S. Cho, S.M. Hwang, Y.G. Jung, J.C. Ryu, and D.S. Shin (2007) Analysis of measurement error for PM-10 mass concentration by inter-comparison study, J. Korean Soc. Atmos. Environ., 23(6), 689-698. (in Korean with English abstract) https://doi.org/10.5572/KOSAE.2007.23.6.689
  15. Kim, M.Y. and I.H. Jung (1998) The measurement of airborne particulate matter using different methods at City Hall Station of Subway in Seoul, Journal of the Korean Society for Environment Analysis, 1(3), 227-238.
  16. Kim, N.J., S.S. Lee, J.S. Jeon, J.H. Kim, and M.H. Kim (2006) Evaluation of factors to affect $PM_{10}$ concentration in Subway Station, Proceeding of the 43rd Meeting of Korean Society for Atmospheric Environment, 571-572.
  17. Lee, M.K. and H.S. Hur (1995) Performance evaluation of linear regression, back-propagation neural network, and linear hebbian neural network for fitting linear functions, The Korean Operations Research and Management Science Society, 20(3), 17-29.
  18. Leng, L., T. Zhang, L. Kleinman, and W. Zhu (2007) Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science, Journal of Physics, 78, 1-5.
  19. Park, H.M., C.M. Lee, Y.M. Noh, Y.S. Kim, and D.S. Park (2006) A study on the indoor air quality of Seoul subway passenger cabin, Proceeding of the 41st Meeting of Korean Society for Atmospheric Environment, 557-558.
  20. Park, M.S., H.M. Pyo, J.R. Shon, and S.H. Byeon (2008) A study on the sound level exposure at Seoul Metro, J. Korean Soc. Atmos. Environ., 5(3), 251-257. (in Korean with English abstract)
  21. Quok, M. and M. McDougall (2006) Comparison of the ARB continuous PM-2.5 monitoring network to the PM2.5 federal reference method network, California Air Resources Boards Report, 1-21.
  22. Seber, G.A.F. (1997) Linear Regression Analysis, John Wiley & Sons, New York, 80-130.
  23. Shon, J.R., J.C. Kim, M.Y. Kim, Y.S. Son, and Y. Sunwoo (2008) Particulate behavior in subway airspace, Asian Journal of Atmospheric Environment, 2-1, 54-59.
  24. The Ministry for the Environment (2003) Monitoring of PM10 in New Zealand, Air Quality Technical Report, 40.
  25. Tittarelli, A., A. Borgini, M. Bertoldi, E. De Saeger, A. Ruprecht, R. Stefanoni, G. Tagliabue, P. Contiero, and P. Crosignani (2008) Estimation of particle mass concentration in ambient air using a particle counter, Atmospheric Environment, 42, 8543-8548. https://doi.org/10.1016/j.atmosenv.2008.07.056

Cited by

  1. Visualization of the Comparison between Airborne Dust Concentration Data of Indoor Rooms on a Building Model vol.26, pp.4, 2015, https://doi.org/10.6107/JKHA.2015.26.4.055
  2. PM10 and Associated Trace Elements in the Subway Cabin of Daejeon by Instrumental Neutron Activation Analysis vol.38, pp.8, 2016, https://doi.org/10.4491/KSEE.2016.38.8.459
  3. Implementation of Indoor Air Quality Monitoring System for Subway Stations vol.50, pp.6, 2013, https://doi.org/10.5573/ieek.2013.50.6.294
  4. Subway PM10 measurement and development of correction equation using the light scattering method vol.17, pp.1, 2018, https://doi.org/10.15250/joie.2018.17.1.45