Estimation of aerosol particle number distributions with Kalman Filtering – Part 1: Theory, general aspects and statistical validity
T. Viskari,T. Viskari,Eija Asmi,Pekka Kolmonen,Henri Vuollekoski,Tuukka Petäjä,Heikki Järvinen +6 more
TLDR
In this paper, Extended Kalman Filter (EKF) is introduced as a method to estimate aerosol particle number size distributions from multiple simultaneous observations and validated by calculating the bias and the standard deviation for the estimated size distributions with respect to the raw measurements.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 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.read more
Citations
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Journal ArticleDOI
Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin
Yiguo Wang,Yiguo Wang,Yiguo Wang,Karine Sartelet,Marc Bocquet,Marc Bocquet,Patrick Chazette,Michaël Sicard,Giuseppe D'Amico,Jean-François Léon,Lucas Alados-Arboledas,Aldo Amodeo,Patrick Augustin,Jordi Bach,Livio Belegante,Ioannis Binietoglou,X. Bush,Adolfo Comerón,Hervé Delbarre,David Garcia-Vizcaino,Juan Luis Guerrero-Rascado,Maxime Hervo,Marco Iarlori,Panagiotis Kokkalis,Diego Lange,Francisco Molero,Nadège Montoux,Alvaro Muñoz,Constantino Munoz,Doina Nicolae,A. Papayannis,Gelsomina Pappalardo,J. Preissler,J. Preissler,Vincenzo Rizi,Francesc Rocadenbosch,Karine Sellegri,Frank Wagner,Frank Wagner,François Dulac +39 more
TL;DR: In this article, a data assimilation (DA) algorithm based on the optimal interpolation method developed in the Polair3D chemistry transport model (CTM) of the Polyphemus air quality modelling platform is employed to assimilate hourly averaged normalised range-corrected lidar signals.
Journal ArticleDOI
Estimation of aerosol particle number distribution with Kalman Filtering – Part 2: Simultaneous use of DMPS, APS and nephelometer measurements
TL;DR: In this article, an Extended Kalman Filter (EKF) is used to estimate particle size distributions from observations, where the prior state estimate is updated with size-segregating measurements from Differential Mobility Particle Sizer (DMPS) and Aerodynamic ParticleSizer (APS) as well as integrating measurements from a nephelometer.
Journal ArticleDOI
Combining instrument inversions for sub-10 nm aerosol number size-distribution measurements
Dominik Stolzenburg,Juha Kangasluoma,Dominik Stolzenburg,Matthew Ozon,Markku Kulmala,Kari E. J. Lehtinen,Kari E. J. Lehtinen,Katrianne Lehtipalo,Katrianne Lehtipalo,Juha Kangasluoma +9 more
TL;DR: With regularization, this work can reconstruct the size-distribution measured by up to 4 different mobility particle size spectrometer systems and several particle counters for datasets from Hyytiala and Helsinki, Finland, revealing the sub-10 nm aerosol dynamics in more detail compared to a single instrument assessment.
Journal ArticleDOI
Aerosol formation and growth rates from chamber experiments using Kalman smoothing
Matthew Ozon,Dominik Stolzenburg,Lubna Dada,Lubna Dada,Lubna Dada,Aku Seppänen,Kari E. J. Lehtinen,Kari E. J. Lehtinen +7 more
TL;DR: In this paper, a fixed interval Kalman smoother (FIKS) method was proposed to estimate the size distribution between possible size gaps in the measurement in such a way that it is consistent with aerosol size distribution dynamics theory, and this method gives rise to direct and reliable estimation of size distribution and process rate uncertainties.
Journal ArticleDOI
Retrieval of process rate parameters in the general dynamic equation for aerosols using Bayesian state estimation: BAYROSOL1.0
Matthew Ozon,Aku Seppänen,Jari P. Kaipio,Jari P. Kaipio,Kari E. J. Lehtinen,Kari E. J. Lehtinen +5 more
TL;DR: In this paper, the temporal evolution of aerosol size distributions is modeled with the general dynamic equation (GDE) equipped with stochastic terms that account for the uncertainties of the process rates.
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