Open AccessLong‐Term Monitoring and Characterization of Soil Radon Emission in a Seismically Active Area
Author(s) -
D'Alessandro Antonino,
Scudero Salvatore,
Siino Marianna,
Alessandro Giuseppe,
Mineo Rosario
Publication year - 2020
Publication title -
geochemistry, geophysics, geosystems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.928
H-Index - 136
ISSN - 1525-2027
DOI - 10.1029/2020gc009061
Subject(s) - radon , geology , soil gas , induced seismicity , seismology , anomaly (physics) , characterization (materials science) , wavelet , soil science , soil water , physics , materials science , condensed matter physics , quantum mechanics , artificial intelligence , computer science , nanotechnology
Radon ( 222 Rn) is a radioactive gas, which originates everywhere in rocks of Earth's crust through a process of natural decay of other radioactive elements. The monitoring of soil radon can be useful to address a multitude of geological and environmental issues. However, some difficulties arise when trying to use radon as earthquake precursor because the earthquake‐related anomaly cannot be easily and univocally discriminated from other anomalies of different origin. To explore the relationship between soil radon emission and seismicity, a local network is operating in southeastern Sicily (Italy). Its peculiarities are the uniform geological condition of the monitoring sites and the long data record with simultaneous measures of radon and the main climate variables. In this paper, we applied continuous wavelet transformation to a ≈ 3.5 years long soil radon time series to detect periodic variations. Results indicate the occurrence of cycles at annual, semiannual, and monthly periodicity, which are ascribable to the effects of the climatic‐environmental parameters. The periodic components have been modeled and the signal conveniently filtered. We show as the characterization of the long‐term behavior of radon signals is essential to recognize anomalies in radon emission, which can be related to geological/environmental phenomena. The methodology proposed in this work provides a reliable characterization of the radon time series and can be applied at various spatial/temporal scales, depending on the scientific objectives to be achieved. This approach can also represent the base for further analysis like the investigation of the modulation between the periodic components and short‐term forecasts.