Estimation of aerosol particle number distribution with Kalman Filtering - Part 2: Simultaneous use of DMPS, APS and nephelometer measurements

by T. Viskari, E. Asmi, A. Virkkula, P. Kolmonen, T. Petäjä, H. Järvinen
Atmospheric Chemistry and Physics ()
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Abstract

Extended Kalman Filter (EKF) is used to estimate particle size\ndistributions from observations. The focus here is on the practical\napplication of EKF to simultaneously merge information from different\ntypes of experimental instruments. Every 10 min, the prior state\nestimate is updated with size-segregating measurements from Differential\nMobility Particle Sizer (DMPS) and Aerodynamic Particle Sizer (APS) as\nwell as integrating measurements from a nephelometer. Error covariances\nare approximate in our EKF implementation. The observation operator\nassumes a constant particle density and refractive index. The state\nestimates are compared to particle size distributions that are a\ncomposite of DMPS and APS measurements. The impact of each instrument on\nthe size distribution estimate is studied. Kalman Filtering of DMPS and\nAPS yielded a temporally consistent state estimate. This state estimate\nis continuous over the overlapping size range of DMPS and APS. Inclusion\nof the integrating measurements further reduces the effect of\nmeasurement noise. Even with the present approximations, EKF is shown to\nbe a very promising method to estimate particle size distribution with\nobservations from different types of instruments.

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