Computational Methods for the Estimation of the Aerosol Size Distributions

  • A. Voutilainen
  • V. Kolehmainen
  • F. Stratmann
  • J. P. Kaipio

Abstract

Aerosol particles play an important role in many physical and chemical processes in the atmosphere1. Physical and chemical behaviour of aerosol particles is strongly dependent on particle size and thus the size cannot be ignored in the evaluation and theoretical prediction of the effects caused by airborne particles. Since the particle diameter d p can range from few nanometers to about 100 micrometers, a size distribution function is used to describe how certain property, e.g. number, surface area or mass, of particles per unit gas volume is distributed on different particle sizes. The determination of the size distribution function is a very important fundamental task in aerosol research. However, the size distribution cannot be measured directly but it has to be reconstructed on the basis of indirect observations using computational methods. From the mathematical point of view the determination of the size distribution function is an ill-posed problem since the problem does not have a unique solution. The purpose of this chapter is to describe the problem and give a brief review on some computational methods proposed for the reconstruction of particle size distributions.

Keywords

Markov Chain Monte Carlo Posterior Density Tikhonov Regularization Observation Error Markov Chain Monte Carlo Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • A. Voutilainen
    • 1
  • V. Kolehmainen
    • 1
  • F. Stratmann
    • 2
  • J. P. Kaipio
    • 1
  1. 1.Departament of Applied PhysicsUniversity of KuipioKuipioFinland
  2. 2.Institute for Tropospheric ResearchLeipzigGermany

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