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| Titel |
Estimation of aerosol particle number distributions with Kalman Filtering – Part 1: Theory, general aspects and statistical validity |
| VerfasserIn |
T. Viskari, E. Asmi, P. Kolmonen, H. Vuollekoski, T. Petäjä, H. Järvinen |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 12, no. 24 ; Nr. 12, no. 24 (2012-12-17), S.11767-11779 |
| Datensatznummer |
250011660
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| Publikation (Nr.) |
 copernicus.org/acp-12-11767-2012.pdf |
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| Zusammenfassung |
| 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
particle number size distributions obtained from raw measurements by a
inversion of the instrument kernel matrix method. Despite the assumptions
made in the EKF implementation, EKF was found to be more accurate than the
inversion of the instrument kernel matrix in terms of bias, and compatible
in terms of standard deviation. Potential further improvements of the EKF
implementation are discussed. |
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