Sequential Monte Carlo estimation of aerosol size distributions

Computational Statistics and Data Analysis

Volumn 48, Issue 4, 2005, Pages 887-908

  Voutilainen, Arto ^a   Kaipio, Jari P ^a  

^a UNIVERSITY OF EASTERN FINLAND   (Finland)

Author keywords

Aerosol measurement; Particle filter; Sequential Monte Carlo; Size distribution

Indexed keywords

APPROXIMATION THEORY; COMPUTER SIMULATION; INVERSE PROBLEMS; KALMAN FILTERING; MATHEMATICAL MODELS; MONTE CARLO METHODS; PARAMETER ESTIMATION; PARTICLE SIZE ANALYSIS; PARTICLES (PARTICULATE MATTER);

AEROSOL MEASUREMENTS; PARTICLE FILTERS; SEQUENTIAL MONTE CARLO ESTIMATION; SIZE DISTRIBUTION;

AEROSOLS;

EID: 10444266011     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2004.03.011     Document Type: Article

References (45)

1. Anderson, B.D.O., Moore, J.B., 1979. Optimal Filtering. Prentice-Hall, Englewood Cliffs, NJ.
2. Bashurova, V.S., Koutzenogil, K.P., Pusep, A.Y., Shokhirev, N.V., 1991. Determination of atmospheric size distribution functions from screen diffusion battery data: mathematical aspects. J. Aerosol Sci. 22, 373-388.
3. Bassini, A., Musazzi, S., Paganini, E., Perini, E., Ferri, F., Giglio, M., 1992. Optical particle sizer based on the Chahine inversion scheme. Opt. Eng. 31, 1112-1117.
4. Butterweck-Dempewolf, G., Schuler, Ch., Vezzù, G., Reineking, A., 1999. Improved determination of bimodal size distributions from measurements with diffusional classification. Aerosol Sci. Technol. 31, 383-391.
5. Carpenter, J., Clifford, P., Fearnhead, P., 1999. Improved particle filter for nonlinear problems. IEE P-Radar Son. Nav. 146, 2-7.
6. Chui, C.K., Chen, G., 1987. Kalman Filtering with Real-Time Applications. Springer, New York.
7. Dahneke, B., 1983. Simple kinetic theory of Brownian diffusion in vapors and aerosols. In: Meyer, R.E. (Ed.), Theory of Dispersed Multiphase Flow. Academic Press, New York, pp. 97-133.
8. Doucet, A., Godsill, S., Andrieu, C., 2000. On sequential Monte Carlo sampling methods for Bayesian filtering. Statist. Comput. 10, 197-208.
9. Doucet, A., de Freitas, N., Gordon, N. (Eds.), 2001. Sequential Monte Carlo Methods in Practice. Springer, New York.
10. Dzubay, T.G., Hasan, H., 1990. Fitting multimodal lognormal size distributions to cascade impactor data. Aerosol Sci. Technol. 13, 144-150.
11. Fearnhead, P., 2002. Markov chain Monte Carlo, sufficient statistics, and particle filters. J. Comput. Graph. Statist. 11, 848-862.
12. Fuchs, N.A., 1964. The Mechanics of Aerosols. Pergamon Press, Oxford.
13. Gelb, A. (Ed.), 1974. Applied Optimal Estimation. MIT Press, Cambridge, MA.
14. Gordon, N.J., Salmond, D.J., Smith, A.F.M., 1993. Novel approach to nonlinear/non-Gaussian Bayesian state estimation. IEE Proc.-F 140, 107-113.
15. Havlicek, M. TSI Inc., 2002. Personal communication.
16. Helsper, C., Fissan, H., Kapadia, A., Liu, B.Y.H., 1982. Data inversion by simplex minimization for the electrical aerosol analyzer. Aerosol Sci. Technol. 1, 135-146.
17. Jacobson, M.Z., 1999. Fundamentals of Atmospheric Modeling. Cambridge University Press, Cambridge, UK.
18. Kaijser, T., 1983. A simple inversion method for determining aerosol size distributions. J. Comput. Phys. 52, 80-104.
19. Kaipio, J., Somersalo, E., 1999. Nonstationary inverse problems and state estimation. J. Inverse Ill-Posed Probl. 7, 273-282.
20. Kalman, R.E., 1960. A new approach to linear filtering and prediction problems. Trans. ASME - J. Basic Eng. 82, 35-45.
21. Kandlikar, M., Ramachandran, G., 1999. Inverse methods for analysing aerosol spectrometer measurements: a critical review. J. Aerosol Sci. 30, 413-437.
22. Keady, P.B., Quant, F.R., Sem, G.J., 1983. Differential mobility particle sizer: a new instrument for high-resolution aerosol size distribution measurement below l μm. TSI Quart. 9, 3-11.
23. Kitagawa, G., 1996. Monte Carlo filter and smoother for non-Gaussian nonlinear state space models. J. Comput. Graph. Statist. 5, 1-25.
24. Knutson, E.O., Whitby, K.T., 1975. Aerosol classification by electric mobility: apparatus, theory and applications. J. Aerosol Sci. 6, 443-451.
25. Liu, J.S., Chen, R., 1998. Sequential Monte Carlo methods for dynamic systems. J. Amer. Statist. Assoc. 93, 1032-1044.
26. Musso, C., Oudjane, N., Le Gland, F., 2001. Improving regularized particle filters. In: Doucet, A., de Freitas, N., Gordon, N. (Eds.), Sequential Monte Carlo Methods in Practice. Springer, New York, pp. 247-271.
27. Pitt, M.K., Shephard, N., 1999. Filtering via simulation: auxiliary particle filters. J. Amer. Statist. Assoc. 94, 590-599.
28. Raabe, O.G., 1978. A general method for fitting size distributions to multicomponent aerosol data using weighted least-squares. Environ. Sci. Technol. 12, 1162-1167.
29. Ramachandran, G., Kandlikar, M., 1996. Bayesian analysis for inversion of aerosol size distribution data. J. Aerosol Sci. 27, 1099-1112.
30. Reid, R.C., Prausnitz, J.M., Poling, B.E., 1987. Properties of Gases and Liquids, 4th Edition. McGraw-Hill, New York.
31. Seinfeld, J.H., Pandis, S.N., 1998. Atmospheric Chemistry and Physics. From Air Pollution to Climate Change. Wiley, New York.
32. Somersalo, E., Voutilainen, A., Kaipio, J.P., 2003. Non-stationary magnetoencephalography by Bayesian filtering of dipole moments. Inverse Problems 19, 1047-1063.
33. Stolzenburg, M.R., 1988. An ultrafine aerosol size distribution measuring system. Ph.D. Thesis, University of Minnesota.
34. TSI Inc. web'site, URL: 〈http://www.tsi.com〉
35. Twomey, S., 1975. Comparison of constrained linear inversion and an iterative non-linear algorithm applied to the indirect estimation of particle size distributions. J. Comput. Phys. 18, 188-200.
36. Voutilainen, A., Kaipio, J.P., 2001. Estimation of non-stationary size distributions using the state space approach. J. Aerosol Sci. 32, 631-648.
37. Voutilainen, A., Kaipio, J.P., 2002. Estimation of time-varying aerosol size distributions - exploitation of modal aerosol dynamical models. J. Aerosol Sci. 33, 1181-1200.
38. Voutilainen, A., Stratmann, F., Kaipio, J.P., 2000. A non-homogeneous regularization method for the estimation of narrow aerosol size distributions. J. Aerosol Sci. 31, 1433-1445.
39. Voutilainen, A., Kolehmainen, V., Kaipio, J.P., 2001. Statistical inversion of aerosol size measurement data. Inv. Probl. Eng. 9, 67-94.
40. Whitby, E.R., McMurry, P.H., 1997. Modal aerosol dynamics modeling. Aerosol Sci. Technol. 27, 673-688.
41. Wiedensohler, A., 1988. An approximation of the bipolar charge distribution for particles in the submicron size range. J. Aerosol Sci. 19, 387-389.
42. Wiedensohler, A., Orsini, D., Covert, D.S., Coffmann, D., Cantrell, W., Havlicek, M., Brechtel, F.J., Russell, L.M., Weber, R.J., Gras, J., Hudson, J.G., Litchy, M., 1997. Intercomparison study of the size-dependent counting efficiency of 26 condensation particle counters. Aerosol Sci. Technol. 27, 224-242.
43. Winklmayr, W., Reischl, G.P., Lindner, A.O., Berner, A., 1991. A new electromobility spectrometer for the measurement of aerosol size distributions in the size range from 1 to 1000 nm. J. Aerosol Sci. 22, 289-296.
44. Wolfenbarger, J.K., Seinfeld, J.H., 1990. Inversion of aerosol size distribution data. J. Aerosol Sci. 21, 227-247.
45. Yeh, H.-C., 1993. Electrical techniques. In: Willeke, K., Baron, P.A. (Eds.), Aerosol Measurement: Principles, Techniques and Applications. Van Nostrand Reinhold, NY, pp. 410-426.