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

摘要

Extended Kalman Filter (EKF) is used to estimate particle size distributionsfrom observations. The focus here is on the practical application of EKF tosimultaneously merge information from different types of experimentalinstruments. Every 10 min, the prior state estimate is updated withsize-segregating measurements from Differential Mobility Particle Sizer(DMPS) and Aerodynamic Particle Sizer (APS) as well as integratingmeasurements from a nephelometer. Error covariances are approximate in ourEKF implementation. The observation operator assumes a constant particledensity and refractive index. The state estimates are compared to particlesize distributions that are a composite of DMPS and APS measurements. Theimpact of each instrument on the size distribution estimate is studied.Kalman Filtering of DMPS and APS yielded a temporally consistent stateestimate. This state estimate is continuous over the overlapping size rangeof DMPS and APS. Inclusion of the integrating measurements further reducesthe effect of measurement noise. Even with the present approximations, EKFis shown to be a very promising method to estimate particle sizedistribution with observations from different types of instruments.