The Influence of Cloud Chemical Processes on the Formation of Secondary Particulate Matter

  • Roland SchroednerEmail author
  • Ralf Wolke
  • Andreas Tilgner
  • Hartmut Herrmann
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)


As a pre-study for the 3-D-simulation of the hill cap cloud experiment HCCT 2010 the chemistry transport model COSMO-MUSCAT was tested in a 2-D-domain with a bell-shaped hill. The sensitivity of several target species (oxidants, pH, sulphate, organic mass, dicarboxylic acids, O/C-ratio) on the detail of the aqueous phase mechanism was investigated in a polluted urban and a clean continental rural air mass. For the treatment of aqueous phase chemistry the complex mechanism CAPRAM 3.0i in reduced version and the simple inorganic mechanism INORG was used. Differences between both mechanisms occurred for the oxidants which are not treated in INORG (HO2, OH, NO3) and the pH especially in the urban environment where much more organic reaction partners are also present in the aqueous phase. For O3, H2O2 and the overall sulphate mass both mechanisms agree mostly within 5 %. Additionally, the composition of the organic mass has been analysed.


Pyruvic Acid Liquid Water Content Organic Mass Nitrate Production Sulphate Mass 
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R.S. acknowledges personal funding by the scholarship program of the German Federal Environmental Foundation (DBU). The ZIH Dresden and the NIC Jülich supported this work. We gratefully acknowledge the DWD Offenbach for good cooperation.


  1. 1.
    Deguillaume L, Tilgner A, Schrodner R, Wolke R, Chaumerliac N, Herrmann H (2009) Towards an operational aqueous phase chemistry mechanism for regional chemistry-transport models: CAPRAM-RED and its application to the COSMO-MUSCAT model. J Atmos Chem 64(1):1–35. doi: 10.1007/s10874-010-9168-8
  2. 2.
    Renner E, Wolke R (2010) Modelling the formation and atmospheric transport of secondary inorganic aerosols with special attention to regions with high ammonia emissions. Atmos Environ 44:1904–1912CrossRefGoogle Scholar
  3. 3.
    Schättler U, Doms G, Schraff C (2013) A description of the nonhydrostatic regional COSMO-Model. Part I: Users guide. Deutscher Wetterdienst, Offenbach, 2013. Available from
  4. 4.
    Sehili AM, Wolke R, Knoth O, Simmel M, Tilgner A, Herrmann H (2005) Comparison of different model approaches for the simulation of multiphase processes. Atmos Environ 39:4403–4417CrossRefGoogle Scholar
  5. 5.
    Sun J, Ariya PA (2006) Atmospheric organic and bio-aerosols as cloud condensation nuclei (CCN): a review. Atmos Environ 40:795–820CrossRefGoogle Scholar
  6. 6.
    Tilgner A, Herrmann H (2010) Radical-driven carbonyl-to-acid conversion and acid degradation in tropospheric aqueous systems studied by CAPRAM. Atmos Environ 44:5415–5422CrossRefGoogle Scholar
  7. 7.
    Wolke R, Schroder W, Schrodner R, Renner E (2012) Influence of grid resolution and meteorological forcing on simulated European air quality: a sensitivity study with the modeling system COSMO-MUSCAT. Atmos Environ 53:110–130CrossRefGoogle Scholar
  8. 8.
    Wolke R, Knoth O, Hellmuth O, Schröder W, Renner E (2004) The parallel model system LM-MUSCAT for chemistry-transport simulations: coupling scheme, parallelization and application. In: Joubert GR, Nagel WE, Peters FJ, Walter WV (eds) Parallel computing: software technology, algorithms, architectures and applications. Elsevier, Amsterdam, pp 363–370Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Roland Schroedner
    • 1
    Email author
  • Ralf Wolke
    • 1
  • Andreas Tilgner
    • 1
  • Hartmut Herrmann
    • 1
  1. 1.Department of Modeling of Atmospheric ProcessesLeibniz Institute for Tropospheric Research (TROPOS)LeipzigGermany

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