Source Apportionment of Airborne Dust in Germany: Methods and Results

  • U. QuassEmail author
  • A. C. John
  • T. A. J. Kuhlbusch
Part of the The Handbook of Environmental Chemistry book series (HEC, volume 26)


Methodologies and results of approaches used for the source apportionment of particulate matter in Germany are reviewed. Due to the relatively large number of interested parties and stakeholders, in particular the 16 German Federal States and the Federal Environment Agency, the information was found to be quite dispersed.

Based on the PM levels measured in the state monitoring networks the incremental increase of PM from rural to hot-spot conditions is one of the most widely investigated aspects. As a general conclusion a large-scale PM10 background contribution of ca. 50% appears to be typical, with the other 50% originating from urban and local (traffic, industrial) influences. Combination of this spatial information with emission registers reveal detailed information on the shares of the various sources; however, PM formation processes not included in the emission inventories as well as trans-boundary impacts are neglected in such analyses. Complementary information thus is provided by receptor models and chemical dispersion models, both showing significant importance of secondary aerosol formation and, especially in the eastern part of the country, transboundary intrusion.

Many source categories have been investigated in more detail and are presented in separate sections, as e.g. exhaust and non-exhaust traffic emissions and domestic wood combustion.


Back-trajectories Chemical composition Chemical transport models Hot-spots Lenschow PM10 PMF Urban air 


  1. 1.
    Viana M, Kuhlbusch TAJ, Querol X, Alastuey A, Harrison RM, Hopke PK, Winiwarter W, Vallius M, Szidat S, Prévôt ASH, Hueglin C, Bloemen H, Wåhlin P, Vecchi R, Miranda AI, Kasper-Giebl A, Maenhaut W, Hitzenberger R (2008) Source apportionment of particulate matter in Europe: a review of methods and results. Aerosol Sci 39:827–849CrossRefGoogle Scholar
  2. 2.
    Moussiopoulos N, Douros J, Tsegas G (eds) (2010) Evaluation of source apportionment methods. Deliverable D4.6 MEGAPOLI scientific report 10-22 MEGAPOLI-25-REP-2010-12, 53 ppGoogle Scholar
  3. 3.
    Lenschow P, Abraham H-J, Kutzner K, Lutz M, Preuß J-D, Reichenbächer W (2001) Some ideas about the sources of PM10. Atmos Environ 35(Suppl 1):23–33CrossRefGoogle Scholar
  4. 4.
    UMEG (2005) Ursachenanalyse für PM10 im Rahmen der Erarbeitung von Luftreinhalte- und Aktionsplänen in Baden-Württemberg nach § 47 BImschG für das Jahr 2004. UMEG-Bericht Bericht-Nr.: 4-04/2005Google Scholar
  5. 5.
    Winiwarter W, Kuhlbusch TAJ, Viana M et al (2009) Quality considerations on European PM emission inventories. Atmos Environ 43:3819–3828CrossRefGoogle Scholar
  6. 6.
    Herrmann H, Brüggemann E, Franck U et al (2006) A source study of PM in Saxony by size-segregated characterisation. J Atmos Chem 55:103–130CrossRefGoogle Scholar
  7. 7.
    Beuck H, Quass U, Klemm O, Kuhlbusch TAJ (2011) Assessment of sea salt and mineral dust contributions to PM10 in NW Germany using tracer models and positive matrix factorization. Atmos Environ 45:5813–5821CrossRefGoogle Scholar
  8. 8.
    Denier van der Gon H, Jozwicka M, Hendriks E et al (2010) Mineral dust as a component of particulate matter. BOP report 500099003 PBL Netherlands Environmental Assessment AgencyGoogle Scholar
  9. 9.
    Gietl JK, Lawrence R, Thorpe AJ et al (2010) Identification of brake wear particles and derivation of a quantitative tracer for brake dust at a major road. Atmos Environ 44:141–146CrossRefGoogle Scholar
  10. 10.
    Ebert M, Weinbruch S, Hoffmann P, Ortner HM (2004) The chemical characterization and complex refractive index of rural and urban influenced aerosols determined by individual particle analysis. Atmos Environ 38:6531–6545CrossRefGoogle Scholar
  11. 11.
    Worringen A, Ebert M, Weinbruch S (2010) Entwicklung von Methoden zur qualitativen und quantitativen Quellzuordnung von Aerosolpartikeln an einem Verkehrs-Hotspot. Endbericht zum Forschungsvorhaben. TU Darmstadt, Institut für Angewandte Geowissenschaft, Fachgebiet Umweltmineralogie, Darmstadt (Juni 2010)Google Scholar
  12. 12.
    Schauer JJ, Lough GC, Shafer et al (2006) Characterization of metals emitted from motor vehicles. Report no. 133. Health Effects InstituteGoogle Scholar
  13. 13.
    Quass U, Kuhlbusch TAJ, Koch M (2004) Identifizierung von Quellgruppen für die Feinstaubfraktion. IUTA report LP15/2004. Download from, Accessed 5 Feb 2012
  14. 14.
    IVU (2003) Ursachenanalyse von Feinstaub (PM10)-Immissionen in Berlin unter Berücksichtigung von Messungen der Staubinhaltsstoffe am Stadtrand in der Innenstadt und in einer Straßenschlucht (Los 4 und 5 Ausbreitungsrechnung und Ursachenanalyse für die urbane und lokale Skala) IVU Umwelt GmbH Senate. Department of Urban Development, BerlinGoogle Scholar
  15. 15.
    IVU (2012) IMMIS air quality models. Web information, Accessed 5 Feb 2012
  16. 16.
  17. 17.
  18. 18.
    Stern R, Builtjes P, Schaap M et al (2008) A model inter-comparison study focussing on episodes with elevated PM10 concentrations. Atmos Environ 42:4567–4588CrossRefGoogle Scholar
  19. 19.
    Koo B, Wilson GM, Morris RE, Dunker Yarwood G (2009) Comparison of source apportionment and sensitivity analysis in a particulate matter air quality model. Environ Sci Technol 43:6669–6675CrossRefGoogle Scholar
  20. 20.
    Stohl A (1998) Computation accuracy and applications of trajectories – a review and bibliography. Atmos Environ 32:947–966CrossRefGoogle Scholar
  21. 21.
    Draxler RR, Hess GD (1998) An overview of the HYSPLIT_4 modeling system of trajectories, dispersion, and deposition. Aust Meteorol Mag 47:295–308Google Scholar
  22. 22.
    Stohl A, Eckhardt S, Forster C et al (2002) A replacement for simple back trajectory calculations in the interpretation of atmospheric trace substance measurements. Atmos Environ 36:4635–4648CrossRefGoogle Scholar
  23. 23.
    Stohl A (1996) Trajectory statistics – a new method to establish source-receptor relationships of air pollutants and its application to the transport of particulate sulfate in Europe. Atmos Environ 30:579–587CrossRefGoogle Scholar
  24. 24.
    Ashbaugh LL, Malm WC, Zadeh WZ (1985) A residence time probability analysis of sulfur concentrations at grand canyon national park. Atmos Environ 19:1263–1270CrossRefGoogle Scholar
  25. 25.
    Zeng Y, Hopke PK (1989) A study of the sources of acid precipitation in Ontario, Canada. Atmos Environ 23:1499–1509CrossRefGoogle Scholar
  26. 26.
    Wang YQ, Zhang XY, Draxler RR. (2009) TrajStat: GIS-based software that uses various trajectory statistical analysis methods to identify potential sources from long-term air pollution measurement data. Environ Modell Softw 24:938. Download of product from, Accessed 5 Feb 2012
  27. 27.
    Quass U, Kuhlbusch TAJ, Hugo A et al (2007) German contribution to the EMEP TFMM assessment report on particulate matter. IUTA-Report Nr. LP 34/2007. Available at, Accessed 5 Feb 2012
  28. 28.
    Birmili W, Engler C (2011) Studie zur Charakterisierung und Quantifizierung der räumlichen Herkunft der PM10-Belastung an hoch belasteten Orten. Ausarbeitung für das Umweltbundesamt Fachgebiet II 4.2 Förderkennzeichen 31201283. Download 4 Jan 2012
  29. 29.
    Stern R (2006) Der Beitrag des Ferntransports zu den PM10-und den NO2-Konzentrationen in Deutschland unter besonderer Betrachtung der polnischen Emissionen: Eine Modellstudie. Final report to UBA R&D projects no. 204 42 202/03 and 202 43 270. . Accessed 4 Jan 2012
  30. 30.
    IHU (2008) Untersuchung zur Zusammensetzung des Feinstaubs in Schleswig-Holstein und Hamburg. Institut für Hygiene und Umwelt Hamburg/Staatliches Umweltamt ItzehoeGoogle Scholar
  31. 31.
    Hainsch A (2003) Ursachenanalyse der PM10-Immission in urbanen Gebieten am Beispiel der Stadt Berlin. Dissertation. Technische Universität, BerlinGoogle Scholar
  32. 32.
    John AC, Kuhlbusch TAJ (2004) Ursachenanalyse von Feinstaub (PM10)-Immissionen in Berlin. Report to the Department on Urban Development of Berlin, IUTA-report LP 09/2004aGoogle Scholar
  33. 33.
    LAU (2010) Immissionsschutzbericht Sachsen-Anhalt 2010. Landesanstalt für Umweltschutz Sachsen-Anhalt. Download: Accessed 10 Jan 2012
  34. 34.
    Cyrys J, Stolzel M, Heinrich J et al (2003) Elemental composition and sources of fine and ultrafine ambient particles in Erfurt, Germany. Sci Total Environ 305:143–156CrossRefGoogle Scholar
  35. 35.
    Yue W, Stolzel M, Cyrys J (2008) Source apportionment of ambient fine particle size distribution using positive matrix factorization in Erfurt Germany. Sci Total Environ 398:133–144CrossRefGoogle Scholar
  36. 36.
    TLUG (2008) Web presentation of Thüringer Landesanstalt für Umwelt und Geologie. Accessed 14 Jan 2012
  37. 37.
    Gietl JK, Klemm O (2009) Source identification of size-segregated aerosol in Münster, Germany, by factor analysis. Aerosol Sci Technol 43:828–837CrossRefGoogle Scholar
  38. 38.
    Kuhlbusch TAJ, John AC, Romazanowa et al (2003) Identifizierung von PM10-Emissionsquellen im Rahmen der Maßnahmenplanung zur Reduktion der PM10-Immissions belastung in Rheinland-Pfalz. Report to State Environmental Protection Agency of Rhineland-Palatinate IUTA-report LP 06/2003Google Scholar
  39. 39.
    John A, Quass U, Jacobi S et al (2008) Combined Lenschow and PMF source apportionment for the area Frankfurt/Main Germany. Presentation at European Aerosol Conference 2008, ThessalonikiGoogle Scholar
  40. 40.
    Quass U, John AC, Kuhlbusch TAJ (2009) Quellenzuordnung für Feinstaub in Hessen: Frankfurt/Main und Kleiner Feldberg. IUTA report LP 41/2007Google Scholar
  41. 41.
    Gu J, Pitz M, Schnelle-Kreis J et al (2011) Source apportionment of ambient particles: comparison of positive matrix factorization analysis applied to particle size distribution and chemical composition data. Atmos Environ 45:1849–1857CrossRefGoogle Scholar
  42. 42.
    LUBW (2009) Untersuchung von massenrelevanten Inhaltsstoffen in Feinstaub PM10 an drei Messstationen in Baden-Württemberg in den Jahren 2006 und 2007. Dok-No. 72-02/2009. Accessed 4 Jan 2012
  43. 43.
    Draheim T (2012) Personal communication on chemical composition data from state environment agency of Mecklenburg-VorpommernGoogle Scholar
  44. 44.
    Kuhlbusch TAJ, John AC, Quass U (2009) Sources and source contributions to fine particles. Biomarkers 14(S1):23–28CrossRefGoogle Scholar
  45. 45.
    Gerwig H (2004) Korngrößendifferenzierte Feinstaubbelastungin Straßennähe in Ballungsgebieten Sachsens. Materialien zur Luftreinhaltung. Sächsisches Landesamt für Umwelt und Geologie, DresdenGoogle Scholar
  46. 46.
    John AC, Quass U, Kuhlbusch TAJ (2004) Comparison study of the chemical composition of PM10 for days with high mass concentrations in three regions in Germany. Presentation at European Aerosol Conference 2004, BudapestGoogle Scholar
  47. 47.
    Warneck P (1999) Chemistry of the natural atmosphere. Academic, San DiegoGoogle Scholar
  48. 48.
    Hasager CB, Birmili W, Pappalardo G et al (2010) Atmospheric implications of the volcanic eruptions of Eyjafjallajökull Iceland 2010. Atmos Chem Phys (special issue)., Accessed 5 Feb 2012
  49. 49.
    Bruckmann P, Birmili W, Straub W et al (2008) An outbreak of Saharan dust causing high PM10 levels north of the Alps. Gefahrst Reinhalt Luft 68:490–498Google Scholar
  50. 50.
    Jaenicke R (2005) Abundance of cellular material and proteins in the atmosphere. Science 308:73CrossRefGoogle Scholar
  51. 51.
    NatAir (2007) Improving and applying methods for the calculation of natural and biogenic emissions and assessment of impactsto the air quality. Final report of the FP6 project. Download from Accessed 6 Jan 2012
  52. 52.
    Womiloju TO, Miller JD, Mayer PM et al (2003) Methods to determine the biological composition of particulate matter collected from outdoor air. Atmos Environ 37:4335–4344CrossRefGoogle Scholar
  53. 53.
    Lau APS, Lee AKY, Chan CK et al (2006) Ergosterol as a biomarker for the quantification of the fungal biomass in atmospheric aerosols. Atmos Environ 40:249–259CrossRefGoogle Scholar
  54. 54.
    Wagener S, Langner M, Hansen U (2012) Spatial and seasonal variations of biogenic tracer compounds in ambient PM10 and PM1 samples in Berlin, Germany. Atmos Environ 47:33–42CrossRefGoogle Scholar
  55. 55.
    Manders AMM, Schaap M, Querol X et al (2010) Sea salt concentrations across the European continent. Atmos Environ 44:2434–2442CrossRefGoogle Scholar
  56. 56.
    Vester BP, Ebert M, Barnert EB et al (2007) Composition and mixing state of the urban background aerosol in the Rhein-main area (Germany). Atmos Environ 41:6102–6115CrossRefGoogle Scholar
  57. 57.
    Putaud JP, Van Dingenen R, Dell’Acqua A et al (2004) Size-segregated aerosol mass closure and chemical composition in Monte cimone (I) during MINATROC. Atmos Chem Phys 4:889–902CrossRefGoogle Scholar
  58. 58.
    Holst J, Mayer H, Holst T (2008) Effect of meteorological exchange conditions on PM10 concentration. Meteorol Z 17:273–282CrossRefGoogle Scholar
  59. 59.
    Rauterberg-Wulff A (2000) Untersuchungen über die Bedeutung der Staubaufwirbelung für die PM10-Immission an einer Hauptverkehrsstraße. Im Auftrag der Senatsverwaltung für Stadtentwicklung, Umweltschutz und Technologie. TU Berlin (Januar 2000)Google Scholar
  60. 60.
    Schmidt W, Düring I, Lohmeyer A (2011) Einbindung des HBEFA 3.1 in das FIS Umwelt und Verkehr sowie Neufassung der Emissionsfaktoren für Aufwirbelung und Abrieb des Strassenverkehrs. Ingenieurbüro Lohmeyer, Karlsruhe. Download from Accessed 21 Jan 2012
  61. 61.
    UBA (2010) Handbuch Emissionsfaktoren des Straßenverkehrs, Version 3.1/Januar 2010. Dokumentation zur Version Deutschland erarbeitet durch INFRAS AG Bern/Schweiz in Zusammenarbeit mit IFEU Heidelberg. Hrsg.: Umweltbundesamt, Berlin., Accessed 5 Feb 2012
  62. 62.
    Stein G, Wünstel E, Travnicek-Pagaimo W (2009) Reifenabrieb in Feinstaub - Bewertung auf Basis einer neu entwickelten Messmethode In: Reifen - Fahrwerk - Fahrbahn im Spannungsfeld von Sicherheit und Umwelt: VDI-Berichte 2086. VDI-Verlag, DüsseldorfGoogle Scholar
  63. 63.
    Bukowiecki N, Lienemann P, Hill M et al (2009) Real-world emission factors for antimony and other brake wear related trace elements: size-segregated values for light and heavy duty vehicles. Environ Sci Technol 43:8072–8078CrossRefGoogle Scholar
  64. 64.
    Quass U, John A, Beyer M et al (2008) Ermittlung des Beitrages von Reifen-, Kupplungs-, Brems- und Fahrbahnabrieb an den PM10-Emissionen von Strassen. Strassenverkehrstechnik 5:304Google Scholar
  65. 65.
    Bukowiecki N, Gehrig R, Lienemann et al (2009) PM10-Emissionsfaktoren von Abriebspartikeln des Straßenverkehrs (APART). Forschungsauftrag ASTRA 2005/007. Bundesamt für Strassen (August 2009)Google Scholar
  66. 66.
    LUBW (2010) Bestimmung des Beitrags der Holzfeuerung zum PM10-Feinstaub. Dok.-No. 64–01/2010. Accessed 29 Jan 2012
  67. 67.
    Ehrlich C, Noll G, Kalkoff W-D (2007) Determining PM-emission fractions (PM10, PM2.5, PM1.0) from small-scale combustion units and domestic stoves using different types of fuels including biofuels like wood pellets and energy grain. In: DustConf 2007, Maastricht., Accessed 5 Feb 2012
  68. 68.
    UBA (2006) Hintergrundpapier: Die Nebenwirkungen der Behaglichkeit: Feinstaub aus Kamin und Holzofen. Umweltbundesamt, Dessau (9. März 2006)Google Scholar
  69. 69.
    Brandt C, Kunde R, Dobmeier B et al (2011) Ambient PM10 concentrations from wood combustion – emission modeling and dispersion calculation for the city area of Augsburg, Germany. Atmos Environ 45:3466–3474CrossRefGoogle Scholar
  70. 70.
    Pacyna EG, Pacyna JM, Fudala J et al (2007) Current and future emissions of selected heavy metals to the atmosphere from anthropogenic sources in Europe. Atmos Environ 41:8557–8566CrossRefGoogle Scholar
  71. 71.
    Quass U, Fermann M, Bröker G (2004) The European dioxin Air emission inventory project – final results. Chemosphere 54:1319–1327CrossRefGoogle Scholar
  72. 72.
    Ehrlich C, Noll G, Kalkoff W-D et al (2007) PM10, PM2.5 and PM1.0 – emissions from industrial plants – results from measurement programmes in Germany. Atmos Environ 41:6236–6254CrossRefGoogle Scholar
  73. 73.
    Kappert W, Bruckmann P, Gladtke D et al (2007) High population density and heavy industry: the challenge for air quality management in North Rhine Westphalia with special focus on the steel production at Duisburg. In: DustConf 2007, Maastricht., Accessed 5 Feb 2012
  74. 74.
    Gladtke D, Volkhausen W, Bach B (2009) Estimating the contribution of industrial facilities to annual PM10 concentrations at industrially influenced sites. Atmos Environ 43:4655–4665CrossRefGoogle Scholar
  75. 75.
    Bach B, Volkhausen W (2010) The influence of natural and man-made sources on PM10 and PM2.5 concentrations at industrially influenced sites. Gefahrst Reinhalt Luft 70:488–492Google Scholar
  76. 76.
    Monteny G-J (2007) Ammonia emissions in agriculture. Wageningen Academic Pub. ISBN: 908686029X and 9789086860296, 403 ppGoogle Scholar
  77. 77.
    Dämmgen U (2002) Fine particles and their constituents in Germany - results of denuder filter measurements. In: Hinz T, Rönnpagel B, Linke S (eds) Particulate matter in and from agriculture. Landbauforschung Völkenrode Sonderheft, p 235., Accessed 5 Feb 2012
  78. 78.
    Goossens D, Gross J, Spaan W (2001) Aeolian dust dynamics in agricultural land areas in lower Saxony, Germany. Earth Surf Process Landforms 26:701–720CrossRefGoogle Scholar
  79. 79.
    Seedorf J (2004) An emission inventory of livestock-related bioaerosols for lower Saxony, Germany. Atmos Environ 38:6565–6581CrossRefGoogle Scholar
  80. 80.
    Lutz M, Rauterberg-Wulff A (2010) Berlin’s Low Emission Zone – top or flop? Results of an impact analysis after 2 years in force. In: 14th ETH conference on combustion generated particles, ZurichGoogle Scholar
  81. 81.
    Donaldson K, Stone V, Clouter A et al (2001) Ultrafine particles. Occup Environ Med 58:211–216CrossRefGoogle Scholar
  82. 82.
    Ibald-Mulli A, Wichmann H-E, Kreyling W et al (2002) Epidemiological evidence on health effects of ultrafine particles. J Aerosol Med 15:189–201CrossRefGoogle Scholar
  83. 83.
    Janssen NA, Hoek G, Simic-Lawson M, Fischer P, van Bree L, ten Brink H, Keuken M, Atkinson RW, Anderson HR, Brunekreef B, Cassee FR (2011) Black carbon as an additional indicator of the adverse health effects of airborne particles compared with PM10 and PM2.5. Environ Health Perspect 119:1691–1699CrossRefGoogle Scholar
  84. 84.
    Birmili W, Weinhold K, Nordmann S et al (2009) Atmospheric aerosol measurements in the German ultrafine aerosol network (GUAN). Part 1. Soot and particle number size distributions. Gefahrst Reinhalt Luft 69:137–145Google Scholar
  85. 85.
    Lohmeyer A et al (2004) Aerosolbudget in einem landwirtschaftlich geprägten Gebiet in Niedersachsen (Atmospheric aerosols in an agriculture-related area of Lower Saxony, Germany). Report for Niedersächsisches Landesamt für Ökologie, 18 p,
  86. 86.
    Ebert M and Weinbruch S (2007) Elektronenmikroskopische Einzelpartikelanalyse atmosphärischer Aerosolpartikel. Report to LANUV NRWGoogle Scholar
  87. 87.
    Vester BP, Ebert M, Barnert EB, Schneider J, Kandler K, Schutz L et al. (2007) Composition and mixing state of the urban background aerosol in the Rhein-Main area (Germany). Atmos Environ 41:6102–6115CrossRefGoogle Scholar
  88. 88.
    Bavarian State Ministry of the Environment and Public Health (2010): Daten+Fakten+Ziele Feinstaub: diffuser Staub -klares Handeln. Download from (accession 20.04.2012)
  89. 89.
    Bruckmann P (2010) From Smog to Blue Skies-Remaining Challenges. Conference “Air Quality Management in European Regions–Challenges and success stories” Essen 2010Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Institute of Energy and Environmental Technology (IUTA e.V.), Air Quality & Sustainable Nanotechnology UnitDuisburgGermany

Personalised recommendations