Applications of Fractal Approaches in Seismology and Atmospheric Science

Dear Colleagues,

Several types of systems can be described by fractals. This is because nature exhibits a scaling behaviour in various processes. This behaviour is revealed when the corresponding systems are dilated, translated, or rotated in space. Oftentimes, the related physical procedures are characterised as self-affine or self-similar, meaning that any part of the system is a small- or large-scale representation of it. Due to this, the fractal systems can be described by analysing their parts. Moreover, the scaling and fractal properties are linked with the properties of long memory and complexity, in contrast to simple systems which are characterised by linear mechanisms and order. Complex fractal systems with long memory show complex non-Markovian associations of presence, past, and future leading to solutions which yield to the unavoidable evolution collapse of the system in terms of space and time. Fractal approaches are robust and significant for the scientific analysis of such systems. 

Fractal approaches have been used extensively in seismology, and in the last decades, in atmospheric science. In atmospheric science, fractal approaches have been employed in PM₁₀ and PM_2.5 urban air pollution traces in environmental ozone time series, as well as in NO₂, SO₂, and CO variations. In seismology, electromagnetic disturbances from ultra-low frequencies (ULF) between 0.001 and 1 Hz, low frequencies (LF) between 1 and 10 kHz, high frequencies (HF) between 40 and 60 MHz, and up to very high frequencies (VHF) of the order of 300 MHz are a subject of analysis. Remote sensing techniques and satellite data are also used nowadays since they provide a multi-process framework. For many years, radon has been acknowledged as an undoubted earthquake precursor. The related research includes radon in soil, atmosphere, and groundwater. Fractal approaches have also been employed in the last decade for seismological-induced radon disturbances. Other gases have been also used, such as CO₂ and ions in atmosphere, most importantly in active faults.

The fractal approaches in seismology and atmospheric science include, among others, the DFA and MFDFA methods, the R/S analysis, the Power-law spectral analysis with wavelets and Fourier transform, fractal dimensions, Fourier analysis, Hurst and Lyapunov exponents, entropy analysis, symbolic dynamics, and several signal processing methods. Since the related procedures are multifaceted, the related analysis focus on the dynamic exchange between the fractal and stochastic behaviour of the investigated systems.

Due to the aforementioned reasons, I invite you to submit papers on your most recent works, experimental studies, and case studies related to the subjects mentioned above. Papers that discuss how the aforementioned subjects are related are highly welcomed.

In order to determine early on if your submitted contribution fits with the goals of this Special Issue, I kindly ask that you email me a brief synopsis stating the purpose of the research and the main findings.

Below you may find key points of interest for this Special Issue:

Prof. Dr. Dimitrios Nikolopoulos
Guest Editor

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• fractals
• self-organised systems
• nonlinear dynamics and chaos
• radon
• electromagnetism
• urban air pollution
• earthquakes
• modelling and simulation
• data analysis: algorithms and implementation
• data management