Environmental Monitoring and Assessment

, Volume 184, Issue 2, pp 1063–1083 | Cite as

Assessment of the sources of suspended particulate matter aerosol using US EPA PMF 3.0

  • Md. Firoz KhanEmail author
  • Koichiro Hirano
  • Shigeki Masunaga


The main purpose of this paper was to carry out a source apportionment of suspended particulate matter (SPM) samples using positive matrix factorization procedure. The central and local Government of Japan introduced strict emission regulations in 2002/10 and 2003/10, respectively, in curbing SPM pollution from major metropolitans. This paper also highlighted the impact of the measures taken by the central and local Government of Japan on the reduction of SPM and the contributions of sources. SPM samples were collected for 6 years starting from 1999 to 2005 at two sites, i.e., site A (urban) and site B (suburban) of Yokohama, Japan. Microwave digestion and inductively coupled plasma-mass spectroscopy (ICP-MS) were employed to measure Mg, Al, Ca, V, Cr, Mn, Ni, Cu, Zn, Ga, As, Se, Rb, Sr, Ag, Cd, Cs, Ba, Pb and Bi, while water soluble ions (Na + , NH\(_{4}^{\ \,+}\), K + , Ca2 + , Mg2 + , Cl − , NO\(_{3}^{\ \,-}\) and SO\(_{4}^{\ \,2-})\) as well as carbonaceous mass (EC and OC) were analyzed using ion chromatograph and CHN analyzer, respectively. The sources identified at two sites were automobile, soil dust, marine aerosol, mixed sources, and secondarily formed aerosol. Also, source quantification was performed. Automobile and soil dust were striking contributors at site A. Automobile and soil dust of SPM aerosol might be produced from local origin at current study areas. Besides, Asian dust had an impact on high concentrations of SPM aerosol in some certain period of the year due to the outflows of East Asian emission. In contrast, secondary aerosol in the form of sulfate and ammonium as well as mixed sources (coal, long-transported Cs, and other unknown sources) were remarkable at site B. Stationary/industrial combustion has apparently more impact on the release of SPM components at site B than A. Automobile regulations in 2002 and 2003, respectively, resulted in reduction of SPM by 28% for site A and 16% for site B. There was also net reduction of automobile contribution at both sites due to the above measures being implemented.


Suspended particulate matter Carbonaceous aerosol Source apportionment 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Adachi, A., Okiayu, M., Nishikawa, A., & Kobayashi, T. (1995). Evaluation of source apportionment to suspended particulate matter in air samples collected from Kobe area by Chemical Mass Balance method. Japanese Journal of Toxicology and Environmental Health, 41(2), 167–171. Japanese.Google Scholar
  2. Anttila, P., Paatero, P., Tapper, U., & Vinen, O. (1995). Source identification of bulk wet deposition in Finland by positive matrix factorization. Atmospheric Environment, 29, 1705–1718.Google Scholar
  3. Báez, P. A., García, M. R., Torres, B. M., Del, C., Padilla, H. G., Belmont, R. D., et al. (2007). Origin of trace elements and inorganic ions in PM10 aerosols to the South of Mexico City. Atmospheric Research, 85(1), 52–63.Google Scholar
  4. Baumann, K., Jayanty, R. K. M., & Flanagan, J. B. (2008). Fine particulate matter source apportionment for the chemical speciation trends network site at Birmingham Alabama using positive matrix factorization. Journal of the Air & Waste Management Association, 58, 277–44.Google Scholar
  5. Begum, B. A., Kim, E., Biswas, S. K., & Hopke, P. K. (2004). Investigation of sources of atmospheric aerosol at urban and semi-urban areas in Bangladesh. Atmospheric Environment, 38, 3025–3038.Google Scholar
  6. Buzica, D., Gerboles, M., Borowiak, A., Trincherini, P., Passarella, R., & Pedroni, V. (2006). Comparison of voltammetry and inductively coupled plasma-mass spectrometry for the determination of heavy metals in PM10 airborne particulate matter. Atmospheric Environment, 40, 4703–4710.Google Scholar
  7. Canepari, S., Cardarelli, E., Giuliano, A., & Pietrodangelo, A. (2006). Determination of metals metalloids and non-volatile ions in airborne particulate matter by a new two-step sequential leaching procedure part A: Experimental design and optimization. Talanta, 69, 581–587.Google Scholar
  8. Chan, Y.-C., Hawas, O., Hawker, D., Vowles, P., Cohen, D. D., Stelcer, E., et al. (2011). Using multiple type composition data and wind data in PMF analysis to apportion and locate sources of air pollutants. Atmospheric Environment, 45(2), 439–449.Google Scholar
  9. Chueinta, W., Hopke, P. K., & Paatero, P. (2000). Investigation of sources of atmospheric aerosol at urban and suburban residential areas in Thailand by positive matrix factorization. Atmospheric Environment, 34, 3319–3329.Google Scholar
  10. Conant, W. C., Nenes, A., & Seinfeld, J. H. (2002). Black carbon radiative heating effects on cloud microphysics and implications for aerosol indirect forcing, 1, Extended Köhler theory. Journal of Geophysical Research, 107(D21), 4604. doi: 10.1029/2002JD002094.Google Scholar
  11. Fujimura, M., Suzuki, H., Sekine, Y., & Winchester, J. W. (1993). Resolution of air-pollution from regional aerosol components in western Japan by factor-analysis of elemental concentrations measured by PIXE. Nuclear Instruments and Methods in Physics Research Section B-Beam interactions with Materials and Atoms, 75, 292–295.Google Scholar
  12. Fukuyama, T., & Fujiwara, H. (2008). Contribution of Asian dust to atmospheric deposition of radioactive cesium (137Cs). The Science of the Total Environment, 405(1–3), 389–395.Google Scholar
  13. Funasaka, K., Miyazaki, T., Kawaraya, T., Tsuruho, K., & Mizuno, T. (1998). Characteristics of particulates and gaseous pollutants in a highway tunnel. Environmental Pollution, 102, 171–176.Google Scholar
  14. Funasaka, K., Sakai, M., Shinya, M., Miyazaki, T., Kamiura, T., Kaneco, S., et al. (2003). Size distributions and characteristics of atmospheric inorganic particles by regional comparative study in Urban Osaka, Japan. Atmospheric Environment, 37, 4597–4605.Google Scholar
  15. Gao, N., Cheng, M.-D., & Hopke, P. K. (1994). Receptor modeling of airborne ionic species collected in SCAQS. Atmospheric Environment, 28, 1447–1470.Google Scholar
  16. Garg, B., Cadle, S. H., Mulawa, P. A., Groblicki, P. J., Laroo, C., & Parr, G. A. (2000). Brake wear particulate matter emissions. Environmental Science & Technology, 21, 4463–4469.Google Scholar
  17. Guo, H., Wang, T., & Louie, P. K. K. (2004). Source apportionment of ambient non-methane hydrocarbons in Hong Kong: Application of a principal component analysis/absolute principal component scores (PCA/APCS) receptor model. Environmental Pollution, 129, 489–498.Google Scholar
  18. Harrison, R. M., Smith, D. J. T., Pio, C. A., & Castro, L. M. (1996). Source apportionment of atmospheric polycyclic aromatic hydrocarbons collected from an urban location in Birmingham, UK. Environmental Science & Technology, 30(3), 825–832.Google Scholar
  19. Henry, R. C. (1987). Current factor analysis receptor models are ill-posed. Atmospheric Environment, 21, 1815–1820. 1967.Google Scholar
  20. Henry, R. C., & Hidy, G. M. (1979). Multivariate analysis of particulate sulfate and other air quality variables by principal components-Part I: Annual data from Los Angeles and New York. Atmospheric Environment, 13, 1581–1596.Google Scholar
  21. Henry, R. C., & Hidy, G. M. (1982). Multivariate analysis of particulate sulfate and other air quality variables by principal components-II. Salt Lake City, Utah and St. Louis, Missouri. Atmospheric Environment, 16, 929–938, 940–943.Google Scholar
  22. Hien, P. D., Bac, V. T., & Thinh, N. T. H. (2004). PMF receptor modelling of fine and coarse PM10 in air masses governing monsoon conditions in Hanoi, northern Vietnam. Atmospheric Environment, 38, 189–201.Google Scholar
  23. Ho, K. F., Cao, J. J., Lee, S. C., & Chan, C. K. (2006). Source apportionment of PM2.5 in urban area of Hong Kong. Journal of Hazardous Materials, 138, 73–85.Google Scholar
  24. Hong, Z., Chak, K. C., Fang, M., & Wexler, A. S. (1999). Formation of nitrate and non-sea-salt sulfate on coarse particles. Atmospheric Environment, 33, 4223–4233.Google Scholar
  25. Hopke, P. K., Gladney, E. S., Gordon, G. E., Zoller, W. H., & Jones, A. G. (1976). The use of multivariate analysis to identify sources of selected elements in the Boston urban aerosol. Atmospheric Environment, 10, 1015–1025.Google Scholar
  26. Hopke, P. K., Ito, K., Mar, T., Christensen, W. F., Eatough, D. J., Henry, R. C., et al. (2006). PM source apportionment and health effects: 1. Intercomparison of source apportionment results. Journal of Exposure Science & Environmental Epidemiology, 16, 275–286.Google Scholar
  27. Husain, L., & Dutkiewicz, V. A. (1990). A long term (1975–1988) study of atmospheric SO\(_{4}^{\ \,2-}\); regional contributions and concentration trends. Atmospheric Environment, 24A, 1175–1187.Google Scholar
  28. Huang, S., Rahn, K. A., & Arimoto, R. (1999). Testing and optimizing two factor-analysis techniques on aerosol at Narragansett, Rhode Island. Atmospheric Environment, 33, 2169–2185.Google Scholar
  29. Huang, S., Arimoto, R., & Rahn, K. A. (2001). Sources and source variations for aerosol at Mace Head, Ireland. Atmospheric Environment, 35, 1421–1437.Google Scholar
  30. Japan Environmental Council (2003). Future policy for motor vehicle emission reduction (eighth report). February 22, 2005.Google Scholar
  31. Jorquera, H. (2009). Source apportionment of PM10 and PM2.5 at Tocopilla, Chile (22°05 S, 70°12 W). Environmental Monitoring and Assessment, 153, 235–251.Google Scholar
  32. Kanai, Y., Ohta, A., Kamioka, H., Imai, N., Shimizu, H., Takahashi, Y., et al. (2005). Observation of mass concentration and particle size of atmospheric aerosol in East Asia and dry deposition in Tsukuba in combination with optical particle counter observation. Bulletin. Geological Survey of Japan, 56(7/8), 273–301.Google Scholar
  33. Kaneyasu, N., Ohta, S., & Murao, N. (1995). Seasonal variation in the chemical composition of atmospheric aerosols and gaseous species in Sapporo, Japan. Atmospheric Environment, 29, 1559–1568.Google Scholar
  34. Karasawa, M., Mizuta, H., Kawai, Y., Ito, H., & Kogiso, T. (1994). Source apportionment of suspended particulate matter. Toyota Central R & D Laboratory, 29(2), 23–34. Japanese.Google Scholar
  35. Kawashima, H., Kubota, S., Sasayama, K., Kimura, Y., & Masunaga, S. (2005). Source apportionment for PM25 in Yokohama city. Abstracts of Annual Meeting of the Geochemical Society of Japan, 52, 179.Google Scholar
  36. Kertész, Z., Szoboszlai, Z., Angyal, A., Dobos, E., & Borbély-Kiss, I. (2010). Identification and characterization of fine and coarse particulate matter sources in a middle-European urban environment. Nuclear Instruments and Methods in Physics Research. Section B: Beam Interactions with Materials and Atoms, 268(11–12), 1924–1928.Google Scholar
  37. Khan, M. F., Shirasuna, Y., Hirano, K., & Masunaga, S. (2010a). Urban and suburban aerosol in Yokohama, Japan: A comprehensive chemical characterization. Environmental Monitoring and Assessment, 171, 441–456.Google Scholar
  38. Khan, M. F., Shirasuna, Y., Hirano, K., & Masunaga, S. (2010b). Characterization of PM2.5, PM2.5–10 and PM>10 in ambient air, Yokohama, Japan. Atmospheric Research, 196, 159–172.Google Scholar
  39. Khan, M. F., Shirasuna, Y., Hirano, K., & Masunaga, S. (2010c). Quantifying the sources of hazardous elements of suspended particulate matter aerosol collected in Yokohama, Japan. Atmospheric Environment, 44, 2646–2657.Google Scholar
  40. Kim, K.-S., & Masunaga, S. (2005). Behavior and source characteristic of PCBS in urban ambient air of Yokohama, Japan. Environmental Pollution, 138, 290–298.Google Scholar
  41. Kim, E., Hopke, P. K., & Edgerton, E. (2003). Source identification of Atlanta aerosol by positive matrix factorization. Journal of the Air & Waste Management Association, 53, 731–739.Google Scholar
  42. Larson, T., Gould, T., Simpson, C., Sally, L. L. J., Candis, C., & Joellen, L. (2004). Source apportionment of indoor, outdoor, and personal PM2.5 in Seattle, Washington, using positive matrix factorization. Journal of the Air & Waste Management Association, 54, 1175–1187.Google Scholar
  43. 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, 3201–3212.Google Scholar
  44. Lee, J. H., & Hopke, P. K. (2006). Apportioning sources of PM2.5 in St. Louis, MO using speciation trends network data. Atmospheric Environment, 40, 360–377.Google Scholar
  45. Li, Z., Hopke, P. K., Husain, L., Qureshi, S., Dutkiewicz, V. A., Schwab, J. J., et al. (2004). Sources of fine particle composition in New York City. Atmospheric Environment, 38, 6521–6529.Google Scholar
  46. Liu, W., Wang, Y., Russell, A., & Edgerton, E. S. (2005). Atmospheric aerosol over two urban-rural pairs in the southeastern United States: Chemical composition and possible sources. Atmospheric Environment, 39, 4453–4470.Google Scholar
  47. Maenhaut, W., & Cafmeyer, J. (1987). Particle induced X-ray emission analysis and multivariate techniques: An application to the study of the sources of respirable atmospheric particles in Gent, Belgium. Journal of Trace and Microprobe Techniques, 5, 135–158.Google Scholar
  48. Malm, W. C., Gebhart, K. A., & Henry, R. C. (1990). An investigation of the dominant source regions of fine sulfur in the western United States and their areas of influence. Atmospheric Environment. Part A: General Topics, 24, 3047–3060.Google Scholar
  49. Mar, T. F., Norris, G. A., Koenig, J. Q., & Larson, T. V. (2000). Association between air pollution and mortality in Phoenix 1995–1997. Environmental Health Perspective, 108(4), 347–353.Google Scholar
  50. Marmur, A., Mulholland, J. A., & Russell, A. G. (2007). Optimized variable source-profile approach for source apportionment. Atmospheric Environment, 41, 493–505.Google Scholar
  51. Matsuo, K., Kikuchi, M., Iwabuchi, M., Hara, M., Takahashi, A., & Kidokoro, Y. (2000). Study of suspended particulate matter in Kawasaki City (1991–1998). Annual report of Kawasaki City Research Institute for Environmental Protection, 20, 12–25. Japanese.Google Scholar
  52. Maykut, N. N., Lewtas, J., Kim, E., & Larson, T. V. (2003). Source Apportionment of PM2.5 at an Urban IMPROVE Site in Seattle, Washington. Environmental Science & Technology, 37, 5135–5142.Google Scholar
  53. Ministry of the Environment Japan (1997). ‘Manual for Prediction of Pollution of Atmospheric Particulate Matter’ Suuri-Keikaku Tokyo, pp 269–284.Google Scholar
  54. Ministry of land, infrastructure and transport, Japan (2005). Report of road traffic census in Yokohama.Google Scholar
  55. Morishita, M., Keeler, G. J., Wagner, J. G., & Harkema, J. R. (2006). Source identification of ambient PM2.5 during summer inhalation exposure studies in Detroit, MI. Atmospheric Environment, 40, 3823–3834.Google Scholar
  56. Morishita, M., Keeler, G. J., Kamal, A. S., Wagner, J. G., Harkema, J. R., & Rohr, A. C. (2011). Identification of ambient PM2.5 sources and analysis of pollution episodes in Detroit, Michigan using highly time-resolved measurements. Atmospheric Environment, 45(8), 1627–1637.Google Scholar
  57. Moteki, N., Kondo, Y., Miyazaki, Y., Takegawa, N., Komazaki, Y., Kurata, G., et al. (2007). Evolution of mixing state of black carbon particles: Aircraft measurements over the western Pacific in March 2004. Geophysical Research Letters, 34, L11803. doi: 10.1029/2006GL028943.Google Scholar
  58. Mukai, H., Tanaka, A., Fujii, T., & Nakao, M. (1994). Lead isotope ratios of airborne particulate matter as tracers of long-range transport of air pollutants around Japan. Journal of Geophysical Research, 99(D2), 3717–3726.Google Scholar
  59. Murakami, Y., & Ono, M. (2006). Myocardial infarction deaths after high level exposure to particulate matter. Journal of Epidemiology and Community Health, 60, 262–266.Google Scholar
  60. Norris G, Vedantham R, Wade K, Brown S, Prouty J, Foley C (2008). EPA Positive Matrix Factorization (PMF) 3.0. Fundamentals User Guide US Environmental Protection Agency, Office of Research and Development Washington DC, 20460, USA.Google Scholar
  61. Ogulei, D., Hopke, P. K., Zhou, L., Patrick, P. J., Nair, N., & Ondov, J. M. (2006). Source apportionment of Baltimore aerosol from combined size distribution and chemical composition data. Atmospheric Environment, 40, 396–410.Google Scholar
  62. Okamoto, S., Hayashi, M., Nakajima, M., Kainuma, Y., & Shiozawa, K. (1990). A factor analysis–multiple regression model for source apportionment of suspended particulate matter. Atmospheric Environment, 24, 2089–2097.Google Scholar
  63. Okuda, T., Tenmoku, M., Kato, J., Junya, M., Sato, T., Yokochi, R., et al. (2006). Long-term observation of trace metal concentration in aerosols at a remote island Rishiri Japan by using inductively coupled plasma mass spectrometry equipped with laser ablation. Water, Air, and Soil Pollution, 174(1–4), 3–17.Google Scholar
  64. Omori, T., Fujimoto, G., Yoshimura, I., Nitta, H., & Ono, M. (2003). Effects of particulate matter on daily mortality in 13 Japanese cities. Journal of Epidemiology, 13(6), 314–322.Google Scholar
  65. Oura, Y., Iguchi, H., Nagahata, T., Nakamatsu, H., Otoshi, T., & Ebihara, M. (2007). Elemental compositions of atmospheric particulates collected in Japan from 2002 to 2004. Journal of Radioanalytical and Nuclear Chemistry, 272(2), 381–385.Google Scholar
  66. Paatero, P. (1997). Least squares formulation of robust non-negative factor analysis. Chemometrics and Intelligent Laboratory Systems, 37, 23–35.Google Scholar
  67. Paatero, P., & Tapper, U. (1994). Positive matrix factorization: a non-negative factor model with optimal utilization of error estimates of data values. Environmetrics, 5, 111–126.Google Scholar
  68. Paatero, P., & Hopke, P. K. (2003). Discarding or downweighting high-noise variables in factor analytic models. Analytica Chimica Acta, 490, 277–289.Google Scholar
  69. Park, S. S., & Kim, Y. J. (2005). Source contributions to fine particulate matter in an urban atmosphere. Chemosphere, 59, 217–226.Google Scholar
  70. Paterson, K. G., Sagady, J. L., Hooper, D. L., Bertman, S. B., Carroll, M. A., & Shepson, P. B. (1999). Analysis of air quality data using positive matrix factorization. Environmental Science & Technology, 33, 635–641.Google Scholar
  71. Polissar, A. V., Hopke, P. K., Malm, W. C., & Sisler, J. F. (1998a). Atmospheric aerosol over Alaska 1. Spatial and seasonal variability. Journal of Geophysical Research, 103, 19045–19057.Google Scholar
  72. Polissar, A. V., Hopke, P. K., Paatero, P., Malm, W. C., & Sisler, J. F. (1998b). Atmospheric aerosol over Alaska 2. Elemental composition and sources. Journal of Geophysical Research, 103, 19045–19057.Google Scholar
  73. Polissar, A. V., Hopke, P. K., & Poirot, R. L. (2001). Atmospheric aerosol over Vermont: chemical composition and sources. Environmental Science & Technology, 35, 4604–4621.Google Scholar
  74. Pope, C. A., III, Thun, M. J., Namboodiri, M. M., Dockery, D. W., Evans, J. S., Speizer, F. E., et al. (1995a). Particulate air pollution as a predictor of mortality in a prospective study of US adults. American Journal of Respiratory and Critical Care, 151, 669–674.Google Scholar
  75. Pope, C. A., Dockery, D. W., & Schwartz, J. (1995b). Review of epidemiological evidence of health effects of particulate air pollution. Inhalational Toxicology, 7, 1–18.Google Scholar
  76. Qin, Y., & Oduyemi, K. (2003). Atmospheric aerosol source identification and estimates of source contributions to air pollution in Dundee, UK. Atmospheric Environment, 37, 1799–1809.Google Scholar
  77. Qin, Y., Kim, E., & Hopke, P. K. (2006). The concentrations and sources of PM2.5 in metropolitan New York City. Atmospheric Environment, 40, 312–332.Google Scholar
  78. Ramadan, Z., Song, X. H., & Hopke, P. K. (2000). Identification of sources of Phoenix aerosol by positive matrix factorization. Journal of the Air & Waste Management Association, 50, 1308–1320.Google Scholar
  79. Ramanathan, V., & Carmichael, G. (2008). Global and regional climate changes due to black carbon. Nature Geoscience, 1, 221–227.Google Scholar
  80. Ramanathan, V., Ramana, M. V., Roberts, G., Kim, D., Corrigan, C., Chung, C., et al. (2007). Warming trends in Asia amplified by brown cloud solar absorption. Nature, 448, 575–579.Google Scholar
  81. Rodriguez, S., Querol, X., Alastuey, A., Viana, M. M., Alarcon, M., Mantilla, E., et al. (2004). Comparative PM10-PM2.5 source contribution study at rural urban and industrial sites during PM episodes in Eastern Spain. The Science of the Total Environment, 328(1–3), 95–113.Google Scholar
  82. Roscoe, B. A., Hopke, P. K., Dattner, S. L., & Jenks, J. M. (1982). The use of principal component factor analysis to interpret particulate compositional data sets. Journal of the Air Pollution Control Association, 32(6), 637–642.Google Scholar
  83. Sayaka, S., Izumi, W., & Katsuji, K. (2002). Heavy metal accumulation in the street dust, roadside soil, and roadside tree leaves nearby main street in Tokyo, Japan. Journal of Environmental Chemistry, 12(4), 829–837.Google Scholar
  84. Seinfeld, J., & Pandis, S. N. (2006). Atmospheric Chemistry and Physics: From air pollution to climate change. New York: Wiley.Google Scholar
  85. Schwartz, J. (1993). Air pollution and daily mortality in Birmingham Alabama. American Journal of Epidemiology, 137, 1136–1147.Google Scholar
  86. Schwartz, J. (2004). The effects of particulate air pollution on daily deaths: a multi-city case crossover analysis. Occupational and Environmental Medicine, 61, 956–961.Google Scholar
  87. Song, X.-H., Polissar, A. V., & Hopke, P. K. (2001). Sources of fine particle composition in the northeastern US. Atmospheric Environment, 35, 5277–5286.Google Scholar
  88. Song, Y., Xie, S., Zhang, Y., Zeng, L., Salmon, L. G., & Zheng, M. (2006). Source apportionment of PM2.5 in Beijing using principal component analysis/absolute principal component scores and UNMIX. Science of The Total Environment, 372, 278–286.Google Scholar
  89. Sörme, L., Bergbäck, B., & Lohm, U. (2001). Goods in the anthroposphere as a metal emissions source—a case study of Stockholm, Sweden. Water, Air, & Soil Pollution: Focus, 1, 213–227.Google Scholar
  90. Srivastava, A., Gupta, S., & Jain, V. K. (2008). Source apportionment of total suspended particulate matter in coarse and fine size ranges over Delhi. Aerosol and Air Quality Research, 8(2), 188–200.Google Scholar
  91. Sternbeck, J., Sjodin, A. A., & Andreasson, K. (2002). Metal emissions from road traffic and the influence of resuspension-results from two tunnel studies. Atmospheric Environment, 36, 4735–4744.Google Scholar
  92. Takahashi K, Minoura H, Sakamoto (2008). Chemical composition of atmospheric aerosols in the general environment and around a trunk road in the Tokyo metropolitan area. Atmospheric Environment, 42, 113–125.Google Scholar
  93. Thurston, G. D., & Spengler, J. D. (1985). A quantitative assessment of source contribution to inhalable particulate matter pollution in Metropolitan Boston. Atmospheric Environment, 19, 9–25.Google Scholar
  94. Vaccaro, S., Sobiecka, E., Contini, S., Locoro, G., Free, G., & Gawlik, B. M. (2007). The application of positive matrix factorization in the analysis characterization and detection of contaminated soils. Chemosphere, 69, 1055–1063.Google Scholar
  95. Vallius, M., Janssen, N. A. H., Heinrich, J., Hoek, G., Ruuskanen, J., Cyrys, J., et al. (2005). Sources and elemental composition of ambient PM2.5 in three European cities. Science of The Total Environment, 337, 147–162.Google Scholar
  96. Viana, M., Querol, X., Götschi, T., Alastuey, A., Sunyer, J., Forsberg, B., et al. (2007). Source apportionment of ambient PM2.5 at five Spanish centres of the European community respiratory health survey (ECRHS II). Atmospheric Environment, 41, 1395–1406.Google Scholar
  97. Viana, M., Pandolfi, M., Minguillón, M. C., Querol, X., Alastuey, A., Monfort, E., et al. (2008). Inter-comparison of receptor models for PM source apportionment: Case study in an industrial area. Atmospheric Environment, 42, 3820–3832.Google Scholar
  98. Wang, H., & Shooter, D. (2001). Water soluble ions of atmospheric aerosols in three New Zealand cities: seasonal changes and sources. Atmospheric Environment, 35, 6031–6040.Google Scholar
  99. Wang, X., Sato, T., Xing, B., Tamamura, S., & Tao, S. (2005). Source identification size distribution and indicator screening of airborne trace metals in Kanazawa, Japan. Journal of Aerosol Science, 36, 197–210.Google Scholar
  100. Wang, X., Sato, T., & Xing, B. (2006). Size distribution and anthropogenic sources apportionment of airborne trace metals in Kanazawa, Japan. Chemosphere, 65, 2440–2448.Google Scholar
  101. Wang, Q., Shao, M., Liu, Y., William, K., Paul, G., Li, X., et al. (2007). Impact of biomass burning on urban air quality estimated by organic tracers: Guangzhou and Beijing as cases. Atmospheric Environment, 41, 8380–8390.Google Scholar
  102. Watson, J. G., & Chow, J. C. (2001). Source characterization of major emission sources in the Iperial and Mexicali Valleys along the US/Mexico border. The Science of the Total Environment, 276, 33–47.Google Scholar
  103. Xie, Y.-L., Hopke, P. K., Paatero, P., Barrie, L. A., & Li, S.-M. (1999). Identification of Source Nature and Seasonal Variations of Arctic Aerosol bypositive matrix factorization. Journal of Atmospheric Sciences, 56, 249–260.Google Scholar
  104. Xie, R., Seip, H. M., Wibetoe, G., Nori, S., & Mcleod, C. W. (2006). Heavy coal combustion as the dominant source of particulate pollution in Taiyuan, China, corroborated by high concentrations of arsenic and selenium in PM10. The Science of the Total Environment, 370, 409–415.Google Scholar
  105. Yagi, Y., & Tainosho Y. (2003). Chemical characteristic of the street dusts and suspended particulate matter in Kobe city. Proceedings: International Symposium of the Kanazawa University 21 st -Century COE Program. Kanazawa University, Kanazawa, Japan.Google Scholar
  106. Yamazaki, S., Nitta, H., Ono, M., Green, J., & Fukuhara, S. (2007). Intracerebral haemorrhage associated with hourly concentration of ambient particulate matter: case-crossover analysis. Journal of Occupational and Environmental Medicine, 64, 17–24.Google Scholar
  107. Yorifuji, T., Yamamoto, E., Tsuda, T., & Kawakami, N. (2005). Health impact assessment of particulate matter in Tokyo, Japan. Archives of Environmental & Occupational Health, 60(4), 179–185.Google Scholar
  108. Yoshizumi, K. (1990/91). Source Apportionment of Aerosols in the Tokyo Metropolitan Area by Chemical Element Balances. Energy and Buildings, 15–16, 711–717.Google Scholar
  109. Zhang, F. S., Yamasaki, S., & Nanzyo, M. (2002). Waste ashes for use in agricultural production: I. Liming effect, contents of plant nutrients and chemical characteristics of some metals. The Science of the Total Environment, 284, 215–225.Google Scholar
  110. Zheng, J., Tan, M. G., Shibata, Y., Tanaka, A., Li, Y., Zhang, G. L., et al. (2004). Characteristics of lead isotope ratios and elemental concentrations in PM10 fraction of airborne particulate matter in Shanghai after the phase-out of leaded gasoline. Atmospheric Environment, 38, 1191–1200.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Md. Firoz Khan
    • 1
    • 3
    Email author
  • Koichiro Hirano
    • 2
  • Shigeki Masunaga
    • 1
  1. 1.Graduate School of Environment & Information SciencesYokohama National UniversityHodogaya-kuJapan
  2. 2.Yokohama City Research Institute for Environmental ScienceIsogo-kuJapan
  3. 3.Research Center for Advanced Science and TechnologyUniversity of TokyoMeguro-kuJapan

Personalised recommendations