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| Titel |
Estimation of aerosol particle number distribution with Kalman Filtering – Part 2: Simultaneous use of DMPS, APS and nephelometer measurements |
| VerfasserIn |
T. Viskari, E. Asmi, A. Virkkula, P. Kolmonen, 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.11781-11793 |
| Datensatznummer |
250011661
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| Publikation (Nr.) |
 copernicus.org/acp-12-11781-2012.pdf |
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| Zusammenfassung |
| Extended Kalman Filter (EKF) is used to estimate particle size distributions
from observations. The focus here is on the practical application of EKF to
simultaneously merge information from different types of experimental
instruments. Every 10 min, the prior state estimate is updated with
size-segregating measurements from Differential Mobility Particle Sizer
(DMPS) and Aerodynamic Particle Sizer (APS) as well as integrating
measurements from a nephelometer. Error covariances are approximate in our
EKF implementation. The observation operator assumes a constant particle
density and refractive index. The state estimates are compared to particle
size distributions that are a composite of DMPS and APS measurements. The
impact of each instrument on the size distribution estimate is studied.
Kalman Filtering of DMPS and APS yielded a temporally consistent state
estimate. This state estimate is continuous over the overlapping size range
of DMPS and APS. Inclusion of the integrating measurements further reduces
the effect of measurement noise. Even with the present approximations, EKF
is shown to be a very promising method to estimate particle size
distribution with observations from different types of instruments. |
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