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The Superstatistical Nature and Interoccurrence Time of Atmospheric Mercury Concentration Fluctuations

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  • F. Carbone, CNR-Institute of Atmospheric Pollution Research, Rende
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  • A. G. Bruno, CNR-Institute of Atmospheric Pollution Research, Rende, UNICAL-Polifunzionale
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  • A. Naccarato, CNR-Institute of Atmospheric Pollution Research, Rende
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  • F. De Simone, CNR-Institute of Atmospheric Pollution Research, Rende
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  • C. N. Gencarelli, CNR-Institute of Atmospheric Pollution Research, Rende
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  • F. Sprovieri, CNR-Institute of Atmospheric Pollution Research, Rende
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  • I. M. Hedgecock, CNR-Institute of Atmospheric Pollution Research, Rende
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  • M. S. Landis, United States Environmental Protection Agency
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  • H. Skov
  • K. A. Pfaffhuber, Norsk Institutt for Luftforskning
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  • K. A. Read, York University
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  • L. Martin, South African Weather Service
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  • H. Angot, Univ. Grenoble Alpes, Massachusetts Institute of Technology
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  • A. Dommergue, Univ. Grenoble Alpes
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  • O. Magand, Univ. Grenoble Alpes
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  • N. Pirrone, CNR-Institute of Atmospheric Pollution Research, Rome

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.

Original languageEnglish
JournalJournal of Geophysical Research
Volume123
Issue2
Pages (from-to)764-774
Number of pages11
ISSN0148-0227
DOIs
Publication statusPublished - 27 Jan 2018

    Research areas

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

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