Source Identification of PM-10 in Suwon Using the Method of Positive Matrix Factorization

PMF 방법론을 이용한 수원지역 PM-10의 오염원 확인

  • 황인조 (경희대학교 환경응용화학부 대기오염연구실 및 산학협력기술연구원) ;
  • 김태오 (금오공과대학교 토목·환경 및 건축공학부) ;
  • 김동술 (경희대학교 환경응용화학부 대기오염연구실 및 산학협력기술연구원)
  • Published : 2001.02.01

Abstract

The receptor modeling is one of the statistical methods to achieve reasonable air pollution strategies. The pur-pose of this study was to survey the concentration variability oi inorganic elements and ionic species in the PM-10 particles, to qualitatively characterize emission sources by an advanced algorithm called positive matrix factoriza-tion(PMF) as a receptor model that can strictly provide results in every loading matrix. A total of 254 samples was collected by a PM-10 high volume air sampler from Mar. 1997 to Feb. 1998 in Kyung Hee University at Suwon Campus. Fourteen chemical species(Zn, Cu, Fe, Pb, Al, Mn, $Na^{+}$, NH$_4$+, $K^{+}$, $Mg^{2+}$, $Ca^{2+}$, $SO_4^{2-}$, $NO_{3}^{-}$, and $Cl^{-}$) were determined by AAS and IC methods. The study results showed that the average monthly concentration of PM-10 particles were 86.3$\mu\textrm{g}$/$\textrm{m}^3$ in March (maximum) and 28.5$\mu\textrm{g}$/$\textrm{m}^3$ in August(minimum), respectively. The concentrations of Na+, NH$_4$+, $K^{+}$ and $Cl^{-}$ in winter, $Mg^{2+}$, $Ca^{2+}$ and $NO_{3}^{-}$, in spring, and $SO_4^{2-}$ in summer showed the largest peak concentration for the respective season. Through and app-lication of a PMF program of Pm-10 concentration data of Suwon, 9 sources were qualitatively identified , such as incineration source, oil burning source, soil related source, open burning source automobile source, coal burning sources, secondary sulfate related source, and secondary nitrate related source.

Keywords

References

  1. 다변량 통계자료분석 김기영;전명식
  2. 한국대기보전학회지 v.9 no.1 입경분류에 입각하여 목표변환 인자분석법을 이용한 수원지역 분진 오염원의 정량적 기여도 추정 김동술;이태정
  3. 한국대기보전학회지 v.14 no.6 1994~1997년 중부지방에 내린 강수의 화학적 특성에 관한 연구 조하만;최재천;김지영;전영신;김산
  4. 한국대기보전학회지 v.10 no.2 대기 에어로졸 중 음이온 성분에 대한 입경분포의 변화 특성 최금찬;박정호;임경택
  5. 한국대기보전학회지 v.11 no.2 소백산 대기 중 입자상 물질의 화학적 특성에 관한 연구(II) 최만식;이선기;최재천;이민영
  6. 한국대기보전학회지 v.6 no.2 대기부유분진중 미량유해물질들의 통계적 오염 해석 허문영;유기선;김경호;손동헌
  7. 한국대기보전학회지 v.14 no.1 Submicron 부유분진의 화학적 조성 및 분포에 관한 연구 황인조;김동술
  8. Atmospheric Environment v.29 no.14 Source identification of bulk wet deposition in Finland by positive matrix factorization Anttila, P.;P. Paatero;U. Tapper;Jarvinen
  9. Atmospheric Environment v.1 A factor analysis model of large scale pollution Blifford, I.H;G.O. Meeker
  10. Environ. Sci. & Technol. v.14 Dispersion modeling Budiansky, S.
  11. Multivariate Behavioral Research v.1 The scree test for the number of factors Cattell, R.B.
  12. Journal of Air & Waste Management Association v.45 Measurement methods to determine compliance with ambient air quality standards for suspended particle Chow, J.C.
  13. Atmospheric Environment v.26A PM10 source apportionment in California's San Joaquin Valley Chow, J.C.;J.G. Watson;D.H. Lowenthal;P.A. Solomom;K. Magliano;S. Ziman;L.W. Richards
  14. Atmospheric Environment v.34 no.20 Investigation of source of atmospheric aerosol at urban and suburban residential areas in Thailand by positive matrix factorization Chueinta, W.;P.K. Hopke;P. Paatero
  15. JAPCA v.30 no.10 Receptor oriented methods of air particulate source apportionment Cooper, J.A;G.W. John
  16. Environ. Sci. & Technol. v.7 Chemical element blances and identification of air pollution sources Friedlander, S.K.
  17. Atmospheric Environment v.33 no.19 Temporal variations of source impacts at the receptor, as derived from air particulate monitoring data in Ho Chi Minh City, Vietnam Hien, P.D.;N.T. Binh;Y. Truong;N.T. Ngo
  18. Receptor Modeling in Environmental Chemistry Hopke, P.K.
  19. Atmospheric Environment v.33 no.14 Testing and optimizing two factor-analysis techniques on aerosol at Narragansett Rhode Island Huang, S.;K.A. Rahn;R. Arimoto
  20. Environmetrics v.5 Analysis of daily precipitation data by positive matrix factorization Juntto, S.;P. Paatero
  21. Educational and Psychological Measurement v.20 The application of electronic computers to factor analysis Kaiser, H.F.
  22. Atmospheric Environment v.33 no.19 Application of positive matrix factorization in source apportionment of particulate pollutants in Hong Kong Lee, E.;C.K. Chan;P. Paatero
  23. J. Colloid and Inter. Science v.39 no.1 A chemical element blance for the Pasadena aerosol Miller, M.S.;S.K. Friedlander;G.M. Hindy
  24. User's guide for positive matrix factorization program PMF2 and PMF3 Paatero, P.
  25. Environmetrics v.5 Positive matrix factorization : A non-negative factor model with optimal utilization of error estimates of data values Paatero, P.;U. Tapper
  26. Environ. Sci. & Technol. v.33 no.4 Analysis of air quality data using positive matrix factorization Paterson, K.G.;J.L. Sagady;D.L. Hooper;S.T. Bertman;M.A. Carroll;P.B. Shepson
  27. Atmospheric Environment v.30 no.12 Multivariate analysis of a 1992 SONTOS data subset Poissant, L.;J.W. Bottenheim;P. Roussel;N.W. Reid;H. Niki
  28. Atmospheric Environment v.33 no.30 Source apportionment and source/sink relationships of PAHs in the coastal atmosphere of Chicago and Lake Michigan Simcik, M.F.;S.J. Elsenreich;P.J. Lioy
  29. EPA/600/P-99/002a v.I Air quality criteria for particlate matter U.S. EPA