CO2 and Radon Emissions as Precursors of Seismic Activity

AbstractThis paper reports a review on the relationship between seismic activity and the emissions of CO2 and radon. Direct, indirect and sampling methods are mainly employed to measure CO2 flux and concentration in seismic areas. The accumulation chamber technique is the mostly used in the literature. Radon gas emission in seismic areas can be considered as a short-term pre-seismic precursor. The study and the measurement of radon gas activity prior to earthquakes can be performed through active techniques, with the use of high-precision active monitors and through passive techniques with the use of passive detectors. Several investigators report models to explain the anomalous behavior of in-earth fluid gasses prior to earthquakes. Models are described and discussed

Electromagnetic radiation and Radon-222 gas emissions as precursors of seismic activity

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonEarthquakes are amongst the most destructive of natural phenomena and have been the subject of significant research effort over many decades, to predict the onset of seismic events. Electromagnetic emissions detected prior to earthquakes provide a potential data source for seismic predictions and research suggests that specific pre-seismic electromagnetic activity can be directly related to specific earthquakes although it is still an open issue as to the precise links between these electromagnetic emissions and subsequent earthquakes. In this research, findings of the long memory or the self-organization of several pre-earthquake MHz electromagnetic time-series provide significant outcomes regarding the earthquake prediction. It is also recognised that enhanced radon gas emission has an equally long history as being associated with seismic activity. In general, several anomalous soil radon emissions have been observed prior to earthquakes and this has been recorded all over the world. The abnormal soil radon exhalation from the interior of the earth has been associated with earthquakes and is considered as an important field of research. The research reported in this thesis compared and contrasted the merits of combining electromagnetic emission data and radon exhalation data as precursors of earthquakes with the aim of enhancing earthquake prediction methodology. The findings from the long-memory analysis of radon disturbances in the soil indicated a very significant issue: the radon disturbances in the soil prior to earthquakes exhibit similar behaviour as the MHz RF disturbances of general failure. So, the radon precursors and the MHz electromagnetic correspond to the same pre-earthquake phase. Geological explanations were proposed in view of the asperity model. Persistent and anti-persistent MHz anomalies were due to the micro-cracking of the heterogeneous medium of the earth's crust which may have led the system's evolution towards the global failure. Fractal methods have been used on historical data, to investigate MHz electromagnetic time-series spectra on emissions preceding major earthquakes over the period 2007 to 2014 and the characteristics of enhanced radon emissions have been studied over the period 2008 to 2015 for seismic events occurring in the Aegean Region. It has been found that both the electromagnetic emissions and the radon exhalation data exhibit similar fractal behaviour and are associated with impending seismic activity. Hence both phenomena are relevant to earthquake predictions and should both be employed in any systematic approach to this problem as the varying geological and geographic conditions under which earthquakes can occur, might preclude one or other data from being measurable. According to the several techniques applied in this thesis, all should be employed in sequential steps, albeit the power-law spectral fractal analysis is the most significant to trace long-memory patterns of 1/f processes as those of the processes of earthquakes

Multifractal Patterns in 17-Year PM₁₀ Time Series in Athens, Greece

This paper reports the multifractal characteristics of lengthy PM10 time series from five stations in the Greater Athens Area (GAA), Greece. A novel methodology based on the multifractal detrended fluctuation analysis (MFDFA) is applied to raw and shuffled series in 74 segments in 11 date-periods, previously located, with very strong self-organised critical (SOC) and fractal properties. The MFDFA identified multifractality in all segments. Generalised and classical Hurst exponents are in the range 0.8–1.5 and 9–4.5 for the raw and shuffled series, while the multifractal f(a)−a is within 0.5–1.2 and 0.1–2, respectively. The f(a)−a data are fitted to polynomials to calculate the multifractal parameters W, FWHM and fmax. While these are bimodal, a new parameter, FWHM/fmax, is normally distributed, and due to this, it is employed to locate the important multifractal behaviour via the FWHM/fmax outliers. Five date-periods are found. The date-period 8 January 2015 has extraordinary multifractality for raw and shuffled series for both the AGP and LYK stations. This date-period is one of the three reported in the most recent combination study. Finally, sliding window MFDFA evolution plots of all the series are given. The results provide very strong evidence of the multifractality of the PM10 time series

Fractal and Long-Memory Traces in PM₁₀ Time Series in Athens, Greece

This work examines if chaos and long memory exist in PM10 concentrations recorded in Athens, Greece. The algorithms of Katz, Higuchi, and Sevcik were employed for the calculation of fractal dimensions and Rescaled Range (R/S) analysis for the calculation of the Hurst exponent. Windows of approximately two months’ duration were employed, sliding one sample forward until the end of each utilized signal. Analysis was applied to three long PM10 time series recorded by three different stations located around Athens. Analysis identified numerous dynamical complex fractal time-series segments with patterns of long memory. All these windows exhibited Hurst exponents above 0.8 and fractal dimensions below 1.5 for the Katz and Higuchi algorithms, and 1.2 for the Sevcik algorithm. The paper discusses the importance of threshold values for the postanalysis of the discrimination of fractal and long-memory windows. After setting thresholds, computational calculations were performed on all possible combinations of two or more techniques for the data of all or two stations under study. When all techniques were combined, several common dates were found for the data of the two combinations of two stations. When the three techniques were combined, more common dates were found if the Katz algorithm was not included in the meta-analysis. Excluding Katz’s algorithm, 12 common dates were found for the data from all stations. This is the first time that the results from sliding-window chaos and long-memory techniques in PM10 time series were combined in this manner

Fractal evolution of MHz electromagnetic signals prior to earthquakes: results collected in Greece during 2009

This paper addressed a fractal evolution of 11 one-month lasting MHz electromagnetic disturbances, recorded in Greece prior to nine significant earthquakes of 2009. Time-space wavelet-based power spectral techniques were employed in the analysis. All investigated signals evolved naturally to epochs of fractal organization in space and time. Continuous organization was detected in seven signals. Significant number of successive () power-law -values were observed lying between 1.5 and 3.0 or above. The majority of fractal segments exhibited anti-persistent () or persistent () behaviour. Switching between persistency and anti-persistency was also found. Locality and sensitivity were traced. Findings were considered indicative of self-organized critical states of the last stages of preparation of the investigated earthquakes. Results implied fractional Brownian modelling. Explanations were proposed in view of the asperity model. Persistent–anti-persistent MHz anomalies were due to self-organized micro-cracking of the heterogeneous medium of the earth's crust which may have led the system's evolution towards global failure. The precursory value of the signals was discussed