DOI QR코드

DOI QR Code

Source Identification and Estimation of Source Apportionment for Ambient PM10 in Seoul, Korea

  • Yi, Seung-Muk (Department of Environmental Health, School of Public Health, Seoul National University) ;
  • Hwang, InJo (Department of Environmental Engineering, Daegu University)
  • Received : 2014.04.15
  • Accepted : 2014.08.05
  • Published : 2014.09.30

Abstract

In this study, particle composition data for $PM_{10}$ samples were collected every 3 days at Seoul, Korea from August 2006 to November 2007, and were analyzed to provide source identification and apportionment. A total of 164 samples were collected and 21 species (15 inorganic species, 4 ionic species, OC, and EC) were analyzed by particle-induced x-ray emission, ion chromatography, and thermal optical transmittance methods. Positive matrix factorization (PMF) was used to develop source profiles and to estimate their mass contributions. The PMF modeling identified nine sources and the average mass was apportioned to secondary nitrate (9.3%), motor vehicle (16.6%), road salt (5.8%), industry (4.9%), airborne soil (17.2 %), aged sea salt (6.2%), field burning (6.0%), secondary sulfate (16.2%), and road dust (17.7%), respectively. The nonparametric regression (NPR) analysis was used to help identify local source in the vicinity of the sampling area. These results suggest the possible strategy to maintain and manage the ambient air quality of Seoul.

Keywords

References

  1. Gyeonggi-do (2012) Industrial Complex Environment Management Office, http://iemo.gg.go.kr.
  2. Henry, R.C., Chang, Y.S., Spiegelman, C.H. (2002) Location nearby sources of air pollution by nonparametric regression of atmospheric concentrations on wind direction. Atmospheric Environment 36, 2237-2244. https://doi.org/10.1016/S1352-2310(02)00164-4
  3. Heo, J.B., Dulger, M., Olson, M.R., McGinnis, J.E., Shelton, B.R., Matsunaga, A., Sioutas, C., Schauer, J.J. (2013) Source apportionments of PM2.5 organic carbon using molecular marker Positive Matrix Factorization and comparison of results from different receptor models. Atmospheric Environment 73, 51-61. https://doi.org/10.1016/j.atmosenv.2013.03.004
  4. Heo, J.B., Hopke, P.K., Yi, S.M. (2009) Source apportionment of PM2.5 in Seoul, Korea. Atmos Chem Phys. 9, 4957-4971. https://doi.org/10.5194/acp-9-4957-2009
  5. Hopke, P.K. (1985) Receptor Modeling in Environmental Chemistry. New York, John Willy & Sons.
  6. Hwang, I.J. (2009) Estimation of source apportionment for semi-continuous PM2.5 and identification of location for local point sources at the St. Louis Supersite, USA. Journal of Korean Society for Atmospheric Environment 25, 154-166 (in Korean). https://doi.org/10.5572/KOSAE.2009.25.2.154
  7. Hwang, I.J., Hopke, P.K. (2006) Comparison of source apportionments of fine particulate matter at two San Jose Speciation Trends Network sites. Journal of the Air and Waste Management Association 56, 1287-1300. https://doi.org/10.1080/10473289.2006.10464586
  8. Hwang, I.J., Hopke, P.K. (2007) Estimation of source apportionment and potential source locations of PM2.5 at a west coastal IMPROVE site. Atmospheric Environment 41, 506-518. https://doi.org/10.1016/j.atmosenv.2006.08.043
  9. Hwang, I.J., Hopke, P.K. (2011) Comparison of source apportionment of PM2.5 using PMF2 and EPA PMF version 2. Asian Journal of Atmospheric Environment 5, 86-96. https://doi.org/10.5572/ajae.2011.5.2.086
  10. Hwang, I.J., Hopke, P.K., Pinto, J.P. (2008) Source apportionment and spatial distributions of coarse particles during the Regional Air Pollution Study. Environmental Science and Technology 42, 3524-3530. https://doi.org/10.1021/es0716204
  11. Hwang, I.J., Kim, D.S. (2003) Estimation of quantitative source contribution of ambient $PM_{10}$ using the PMF model. Journal of Korean Society for Atmospheric Environment 19, 719-731 (in Korean).
  12. KEWP (Korea East-West Power Company) (2011) Korea East-West Power Sustainability Report. KEWP.
  13. Kim, E., Hopke, P.K. (2004) Comparison between Conditional Probability Function and Nonparametric Regression for Fine Particle Source Directions. Atmospheric Environment 38, 4667-4673. https://doi.org/10.1016/j.atmosenv.2004.05.035
  14. Kim, E., Hopke, P.K. (2007) Source identifications of airborne fine particles using positive matrix factorization and U.S. Environmental Protection Agency positive matrix factorization. Journal of Air and Waste Management Association 57(7), 811-819. https://doi.org/10.3155/1047-3289.57.7.811
  15. Kim, K.S., Hwang, I.J., Kim, D.S. (2001) Development of a receptor methodology for quantitative assessment of ambient $PM_{10}$ sources in Suwon area. Journal of Korean Society for Atmospheric Environment 17, 119-131 (in Korean).
  16. KMA(Korea Meteorological Administration) (2007) Monthly weather report (March, 2007). KMA (in Korean).
  17. KMOE (Ministry of Environment, Korea) (2006) White Paper of Environment 2006. KMOE (in Korean).
  18. Lall, R., Ito, K., Thurston, G.D. (2011) Distributed lag analyses of daily hospital admissions and source-apportioned fine particle air pollution. Environmental Health Perspectives 119(4), 455-460.
  19. Lee, E., Chan, C.K., Paatero, P. (1999) Application of positive matrix factorization in source apportionment of particulate pollutants in Hong Kong. Atmospheric Environment 33(19), 3201-3212. https://doi.org/10.1016/S1352-2310(99)00113-2
  20. NIER (2006) Investigation of formation process and establishment of emission reduction strategy for $PM_{10}$. Korea National Institute of Environmental Research.
  21. Paatero, P. (1997) Least squares formulation of robust nonnegative factor analysis. Chemometrics and Intelligent Laboratory Systems 37, 23-35. https://doi.org/10.1016/S0169-7439(96)00044-5
  22. Paatero, P., Hopke, P.K. (2003) Discarding or downweighting high-noise variables in factor analytic models. Analytica Chimica Acta 490, 277-289. https://doi.org/10.1016/S0003-2670(02)01643-4
  23. Pitts. F.B.J., Pitts, J.N. (2000) Chemistry of the Upper and Lower Atmosphere. San Diego, Academic Press.
  24. Polissar, A.V., Hopke, P.K., Paatero, P., Malm, W.C., Sisler. J.F. (1998) Atmospheric aerosol over Alaska 2. Elemental composition and sources. Journal of Geophysical Research 103(D15), 19045-19057. https://doi.org/10.1029/98JD01212
  25. Seinfeld, J.H., Pandis, S.N. (1998) Atmospheric Chemistry and Physics, from Air Pollution to Climate Change. New York, John Wiley & Sons.
  26. US EPA. (1999) Air quality criteria for particulate matter, Volume I. EPA 600/P-99/002a, Washington, DC.
  27. Yoo, J.S., Kim, D.S., Kim, Y.S. (1995) Quantitative source estimation of PM-10 in Seoul area. Journal of Korean Air Pollution Research Association 11, 279-290 (in Korean).
  28. Zhao, W., Hopke, P.K. (2004) Source identification for fine aerosols in Mammoth Cave National Park. Atmospheric Research 80, 309-322.

Cited by

  1. Evaluating the applicability of a semi-continuous aerosol sampler to measure Asian dust particles vol.17, pp.3, 2015, https://doi.org/10.1039/C4EM00404C
  2. Source Apportionment of PM2.5 in Gyeongsan Using the PMF Model vol.31, pp.6, 2015, https://doi.org/10.5572/KOSAE.2015.31.6.508
  3. Source Apportionment of PM10 at Pyeongtaek Area Using Positive Matrix Factorization (PMF) Model vol.34, pp.6, 2018, https://doi.org/10.5572/KOSAE.2018.34.6.849
  4. Human health risks assessment for airborne PM10-bound metals in Seoul, Korea vol.26, pp.23, 2014, https://doi.org/10.1007/s11356-019-05213-y
  5. PMF 모델을 이용한 도심지역 PM2.5 오염원 기여도 분석 vol.36, pp.3, 2014, https://doi.org/10.12925/jkocs.2019.36.3.905