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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 16, issue 11
Atmos. Chem. Phys., 16, 7067-7090, 2016
https://doi.org/10.5194/acp-16-7067-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 16, 7067-7090, 2016
https://doi.org/10.5194/acp-16-7067-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 10 Jun 2016

Research article | 10 Jun 2016

Using a combined power law and log-normal distribution model to simulate particle formation and growth in a mobile aerosol chamber

Miska Olin1, Tatu Anttila1,a, and Miikka Dal Maso1 Miska Olin et al.
  • 1Aerosol Physics Laboratory, Department of Physics, Tampere University of Technology, P.O. Box 692, 33101 Tampere, Finland
  • anow at: Finnish Meteorological Institute, Erik Palménin aukio 1, P.O. Box 503, 00101 Helsinki, Finland

Abstract. We present the combined power law and log-normal distribution (PL+LN) model, a computationally efficient model to be used in simulations where the particle size distribution cannot be accurately represented by log-normal distributions, such as in simulations involving the initial steps of aerosol formation, where new particle formation and growth occur simultaneously, or in the case of inverse modeling. The model was evaluated against highly accurate sectional models using input parameter values that reflect conditions typical to particle formation occurring in the atmosphere and in vehicle exhaust. The model was tested in the simulation of a particle formation event performed in a mobile aerosol chamber at Mäkelänkatu street canyon measurement site in Helsinki, Finland. The number, surface area, and mass concentrations in the chamber simulation were conserved with the relative errors lower than 2% using the PL+LN model, whereas a moment-based log-normal model and sectional models with the same computing time as with the PL+LN model caused relative errors up to 17 and 79%, respectively.

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We introduce a new representation of particle size distribution, in which a power law form is used in addition to the most commonly used log-normal representation. The new representation is beneficial in simulations involving the initial steps of aerosol formation, where power law behaviour is typically seen, instead of less accurate pure log-normal representation or computationally more expensive sectional representation.
We introduce a new representation of particle size distribution, in which a power law form is...
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