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JDR Vol.11 No.1 pp. 72-84
(2016)
doi: 10.20965/jdr.2016.p0072

Paper:

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Investigation and Separation of Turbulent Fluctuations in Airborne Measurements of Volcanic Ash with Optical Particle Counters

Jonas Elíasson*1,*2, Konradin Weber*3, Andreas Vogel*3 Thorgeir Pálsson*4, Junichi Yoshitani*2 and Daisuke Miki*2

*1Earthquake Research Institute, University of Iceland
Austurvegur 2a, Selfoss, Iceland

*2Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan

*3Environmental Measurement Techniques, University of Applied Sciences, Dü{u}sseldorf, Germany

*4School of Science and Engineering, Reykjavik University, Reykjavik, Iceland

Received:
July 21, 2015
Accepted:
January 18, 2016
Published:
February 1, 2016
Creative Commons License
Keywords:
volcanic ash, airborne measurements, modeling, fluctuations separation, filtering
Abstract
The science of measuring airborne volcanic ash concentrations supports research in such fields as atmospheric environmental science and the modeling of atmospheric pollution from volcanoes, and is thus very valuable to the aviation industry. These measurements show large scatter directly traceable to turbulent fluctuations responsible for diffusing volcanic dust. Before semistationary components in observations can be compared to each other or to simulation results, they must be separated from fluctuations. In the design of the separation process, however, neither seasonal or diurnal periodicity nor random disturbance with known properties exists to serve as a guideline. It has been suggested that fluctuations could be eliminated through repeated convolutions of a simple 3-point filter enough times. The number of convolutions is chosen from the change in the rate of increase of a special variability parameter. When semistationary concentrations are separated from fluctuations, their statistics are compared to turbulence parameters and the autocorrelation of the series. The method is demonstrated using three measurement series from Sakurajima, Japan measured in 2013. It is concluded that this new method is simple and trustworthy where knowledge and experience of the environmental parameters can be utilized to support the results. They indicate a variability of 40% in the relative fluctuations of the PM10 and around 20% of the PM2.5. The relative fluctuations may be considered completely random, but normally distributed rather than a white noise with an evenly distributed variance spectrum.
Cite this article as:
J. Elíasson, K. Weber, A. Pálsson, J. Yoshitani, and D. Miki, “Investigation and Separation of Turbulent Fluctuations in Airborne Measurements of Volcanic Ash with Optical Particle Counters,” J. Disaster Res., Vol.11 No.1, pp. 72-84, 2016.
Data files:
References
  1. [1] Definition of K, 2012, http://en.wikipedia.org/wiki/Turbulent textunderscore diffusion [accessed Jan. 9, 2015]
  2. [2] T. Elbir, “Comparison of model predictions with the data of an urban air quality monitoring network in Izmir, Turkey,” Atmospheric Environment, Vol.37, No.15, pp. 2149-2157, 2003.
  3. [3] J. Eliasson, J. Yoshitani, K. Weber, N. Yasuda, M. Iguchi, and A. Vogel, “Airborne Measurement in the Ash Plume from Mount Sakurajima: Analysis of Gravitational Effects on Dispersion and Fallout,” Int. Journal of Atmospheric Sciences, 2014.
  4. [4] J. Eliasson, K. Weber, and A. Vogel, “Airborne measurements of dust pollution over airports in Keflavik, Reykjavik and vicinity during the Grimsvotn eruption May 2011 at the request of ISAVIA Air Navigation Service Provider of Iceland,” Earthquake Engineering Research Centre, University of Iceland, Austurvegur 2a, 800 Selfoss, Research Report 11007, 2011.
  5. [5] J. Eliasson, A. Palsson, and K. Weber, “Monitoring ash clouds for aviation,” Nature, Vol.475, No.7357, pp. 455, 2011.
  6. [6] U. Högström, J. C. R. Hunt, and A. S. Smedman, “Theory and measurements for turbulence spectra and variances in the atmospheric neutral surface layer,” Boundary-Layer Met., Vol.103, pp. 101-124, 2002.
  7. [7] J. C. Kaimal and J. J. Finnigan, “Atmospheric boundary layer flows,” Oxford University Press, 1994.
  8. [8] J. C. Kaimal and J. J. Finnigan, “Atmospheric Boundary Layer Flows : Their Structure and Measurement,” p. 304, Oxford University Press, 1993.
  9. [9] J. C. Kaimal and J. C. Wyngaard, “The Kansas and Minnesota experiments,” Boundary-Layer Meteorol., Vol.34, No.31, p. 47, 1990.
  10. [10] P. C. Kyriakidis and A. G. Journel, “Stochastic modeling of atmospheric pollution: a spatial time-series framework. Part I: methodology,” Atmospheric Environment, Vol.35, pp. 2331-2337, 2001.
  11. [11] K. Makra, I. Matyasovszky, and J. Á. Deák, “Trends in the characteristics of allergenic pollen circulation in Central Europe based on the example of Szeged, Hungary,” Atmospheric Environment, Vol.45, pp. 6010-6018, 2011.
  12. [12] B. G. Martinson, J. Friberg, S. M. Andersson, A. Weigelt, M. Hermann, D. Assmann, J. Voigtl”ander, C. A. M. Brenninkmeijer, P. J. F. van Velthoven, and A. Zahn, “Comparison between CARIBIC aerosol samples analysed by accelerator-based methods and optical particle counter measurements,” Atmospheric Measurement Techniques, Vol.7, No.8, pp. 2581-2596, 2014.
  13. [13] A. S. Monin and A. M. Obukhov, “Basic laws of turbulent mixing in the ground layer of the atmosphere,” Trans. Geophys. Inst. Akad. Nauk USSR, Vol.151, No.163, pp. 187, 1954.
  14. [14] F. Pasquill, “Atmospheric Diffusion,” second ed., p. 429, Halstead Press, 1974.
  15. [15] J. A. Pena, J. M. Norman, and D. W. Thomson, “Isokinetic Sampler for Continuous Airborne Aerosol Measurements,” Journal of the Air Pollution Control Association, Vol.27, No.4, pp. 337-341, 1977.
  16. [16] P. D. Rosenberg, A. R. Dean, P. I. Williams, J. R. Dorsey, A. Minikin, M. A. Pickering, and A. Petzold, “Particle sizing calibration with refractive index correction for light scattering optical particle counters and impacts upon PCASP and CDP data collected during the Fennec campaign,” Atmospheric Measurement Techniques, Vol.5, No.5, pp. 1147-1163, 2012.
  17. [17] Scire, S. Joseph, Strimaitis, G. David, Yamartino, and J. Robert, “A Users Gude for the CALPUFF Dispersion Model,” Earth Tech, Inc.; January 2000 (Report).
  18. [18] C. Searcy, K. Dean, and W. Stringer, “PUFF: A Lagrangian Trajectory Volcanic Ash Tracking Model,” Journal of Volcanology and Geothermal Research, Vol.80, pp. 1-16, 1998.
  19. [19] T. Suzuki, “A Theoretical Model for Dispersion of Thephra; Ar Volcanism: Physics and Tectonics,” pp. 95-113, Terra Scientific Publishing Co, 1983.
  20. [20] Van der Hoven, Isaac, “Power Spectrum of Horizontal Wind Speed in the Frequency Range From 0.0007 to 900 Cycles Per Hour,” Journal of Meteorology, Vol.14, No.2, pp. 160-164, 1957.
  21. [21] K. Weber, J. Eliasson, A. Vogel, C. Fischer, T. Pohl, G. van Haren, M. Meier, B. Grobéty, and D. Dahmann, “Airborne in-situ investigations of the Eyjafjallajökull volcanic ash plume on Iceland and over North-Western Germany with light aircrafts and optical particle counters,” Atmospheric Environment, Vol.48, pp. 9-21, 2012.
  22. [22] K. Weber, J. Eliasson, A. Vogel, C. Fischer, T. Pohl, G. van Haren, M. Meier, B. Grobéty, and D. Dahmann, “Airborne in-situ investigations of the Eyjafjallajökull volcanic ash plume on Iceland and over North-Western Germany with light aircrafts and optical particle counters; VDI-Berichte 2113 “Neue Entwicklungen bei der Messung und Beurteilung der Luftqualit”at,” VDI-Verlag Düsseldorf, pp. 131-146, 2011.
  23. [23] Wiener filter, 2015, Wikipedia https://en.wikipedia.org/wiki/ Wienertextunderscore filter [accessed Jan. 9, 2015]

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