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Interpretation of Atmospheric Aerosol Measurements by Means of a Numerical Simulator of New Particle Formation Events

Category: Aerosol Physics and Instrumentation

Volume: 16 | Issue: 4 | Pages: 930-942
DOI: 10.4209/aaqr.2015.08.0511
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To cite this article:
Luts, A., Hõrrak, U., Salm, J., Vana, M. and Tammet, H. (2016). Interpretation of Atmospheric Aerosol Measurements by Means of a Numerical Simulator of New Particle Formation Events. Aerosol Air Qual. Res. 16: 930-942. doi: 10.4209/aaqr.2015.08.0511.

Aare Luts , Urmas Hõrrak, Jaan Salm, Marko Vana, Hannes Tammet

  • Institute of Physics, University of Tartu, Ülikooli 18, EE-50090, Tartu, Estonia


We studied a new method that automatically estimates NPF parameters.
The method was applied to all NPF events observed within a measurement campaign.
Automatically estimated NPF parameters have adequate values.
Simulated NPF event evolution curves are close to the measured data.
In addition to common NPF parameters, we obtained charging state characteristics.


We performed a more comprehensive test of a new NPF parameter estimator published recently. The estimator considers measurements as test data and automatically adjusts the values of its physical control parameters according to the criterion of best fit. The parameters estimated within this procedure include nucleation rate, particle growth rate, birth size of nanoparticles etc. We analyzed all new particle formation events recorded during a measurement campaign at Hyytiälä, Finland. The results show a good performance in reproducing the time series of the concentrations of small air ions and aerosol nanoparticles in the diameter interval of 2.8–8.6 nm. The numerically estimated values of the parameters are in accordance with the results known from certain other studies carried out at Hyytiälä. We conclude the new method may appear useful in the analysis of several air ion and atmospheric aerosol measurements during new particle formation events.


Atmospheric aerosols Aerosol dynamics Nanoparticle evolution model Numerical simulation Fitting to measurements

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DOI: 10.4209/aaqr.2019.08.0371