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 ?, encompassing all possible fluctuations related to mesoscopic phenomena, has been identified. It follows a ?2-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.

The superstatistical nature and interoccurrence time of atmospheric mercury concentration fluctuations

Carbone F;Naccarato A;De Simone F;Gencarelli C N;Sprovieri F;Pirrone N
2018

Abstract

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 ?, encompassing all possible fluctuations related to mesoscopic phenomena, has been identified. It follows a ?2-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.
2018
Istituto sull'Inquinamento Atmosferico - IIA
Pollution: ur
Statistical analysis
Probability distributions
heavy and fat-tailed
Scaling: spatial and temporal
Turbulence
Superstatistics
Mercury
interoccurrence times
Universal scaling
Atmospheric Turbulence
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/338430
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