Atmos. Chem. Phys. Discuss., 12, 18853-18887, 2012
www.atmos-chem-phys-discuss.net/12/18853/2012/
doi:10.5194/acpd-12-18853-2012
© Author(s) 2012. This work is distributed
under the Creative Commons Attribution 3.0 License.
Review Status
This discussion paper has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP.
Estimation of aerosol particle distributions with Kalman Filtering – Part 1: Theory, general aspects and statistical validity
T. Viskari1,2, E. Asmi1, P. Kolmonen1, H. Vuollekoski2, T. Petäjä2, and H. Järvinen1
1Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
2Department of Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland

Abstract. Aerosol characteristics can be measured with different instruments providing observations that are not trivially inter-comparable. Extended Kalman Filter (EKF) is introduced here as a method to estimate aerosol particle number size distributions from multiple simultaneous observations. The focus here in Part 1 of the work was on general aspects of EKF in the context of Differential Mobility Particle Sizer (DMPS) measurements. Additional instruments and their implementations are discussed in Part 2 of the work. University of Helsinki Multi-component Aerosol model (UHMA) is used to propagate the size distribution in time. At each observation time (10 min apart), the time evolved state is updated with the raw particle mobility distributions, measured with two DMPS systems. EKF approach was validated by calculating the bias and the standard deviation for the estimated size distributions with respect to the raw measurements. These were compared to corresponding bias and standard deviation values for distributions calculated with a mathematical inversion method. Despite the assumptions made in the EKF implementation, EKF was found to be more accurate than the mathematical inversion in terms of bias, and compatible in terms of standard deviation. Potential further improvements of the EKF implementation are discussed.

Citation: Viskari, T., Asmi, E., Kolmonen, P., Vuollekoski, H., Petäjä, T., and Järvinen, H.: Estimation of aerosol particle distributions with Kalman Filtering – Part 1: Theory, general aspects and statistical validity, Atmos. Chem. Phys. Discuss., 12, 18853-18887, doi:10.5194/acpd-12-18853-2012, 2012.
 
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