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Volume 15, No. 4, August 2015, Pages 1166-1177 PDF(972 KB)  
doi: 10.4209/aaqr.2014.10.0232   

A Method for Automated Estimation of Parameters Controlling Aerosol New Particle Formation

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

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


  • We developed a new method for inverse application of NPF model.
  • Method uses measurements as reference and estimates NPF parameters.
  • The method was tested on two real NPF events observed in Hyytiälä, Finland.
  • Automatically estimated NPF parameters have adequate values.
  • Simulated NPF event evolution curves are close to the measured data.



We use a previously published simulator of aerosol new particle formation (NPF) events as the core component of the new method for automated estimation of its input parameters. The simulator has a large number of physical input parameters (e.g., nucleation and growth rates), and it yields results about the dynamics of particle concentrations and their size distributions as its output. Our new method automatically solves the inverse problem. It estimates the physical input parameters by recurrent simulations according to the criterion of best fit of the simulated output parameters with the known data. The method is implemented as a computer program that includes the previous simulator as a subroutine. The method enables the estimation of several physical parameters, e.g., the nucleation rate, particle growth rate, contribution from ion-induced and neutral nucleation, and particle charging state. The program was tested using the results of two NPF events measured at Hyytiälä, Finland. The measured time series of the concentration of atmospheric ions and nanoparticles in the diameter interval of 2.8–8.6 nm were well reproduced by our method. The estimated values of the analyzed input parameters are in agreement with the results known from many other studies carried out at Hyytiälä. The proposed method of inverse simulator may appear useful in the analysis and interpretation of air ion and atmospheric aerosol measurements during new particle formation events.



Keywords: Atmospheric aerosols; Aerosol dynamics; Nanoparticle evolution model; Numerical simulation; Fitting to measurements.



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