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The Superstatistical Nature and Interoccurrence Time of Atmospheric Mercury Concentration Fluctuations

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  • Francesco Carbone
  • A. G. Bruno
  • A. Naccarato
  • Francesco De Simone
  • Christian N. Gencarelli
  • Francesca Sprovieri
  • Ian M. Hedgecock
  • M. S. Landis
  • Henrik Skov
  • K. A. Pfaffhuber
  • K. A. Read
  • C. L. Martin
  • Helene Angot
  • Aurélien Dommergue
  • O. Magand
  • Nicola Pirrone


Publication details

JournalJournal of Geophysical Research G: Biogeosciences
DateAccepted/In press - 30 Nov 2017
DateE-pub ahead of print - 19 Jan 2018
DatePublished (current) - 27 Jan 2018
Issue number2
Number of pages11
Pages (from-to)764-774
Early online date19/01/18
Original languageEnglish


The probability density function (PDF) of the time intervals between subsequent extreme events in atmospheric Hg0 concentration data series from different latitudes has been investigated. The Hg0 dynamic possesses a long-term memory autocorrelation function. Above a fixed threshold Q in the data, the PDFs of the interoccurrence time of the Hg0 data are well described by a Tsallis q-exponential function. This PDF behavior has been explained in the framework of superstatistics, where the competition between multiple mesoscopic processes affects the macroscopic dynamics. An extensive parameter μ, encompassing all possible fluctuations related to mesoscopic phenomena, has been identified. It follows a χ2 distribution, indicative of the superstatistical nature of the overall process. Shuffling the data series destroys the long-term memory, the distributions become independent of Q, and the PDFs collapse on to the same exponential distribution. The possible central role of atmospheric turbulence on extreme events in the Hg0 data is highlighted.

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©2017. American Geophysical Union. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

    Research areas

  • atmospheric turbulence, interoccurrence times, mercury, superstatistics, universal scaling

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