In-soil radon at Mt. Etna (2015-2023): Insights into magma dynamics and applications to volcano monitoring
Journal
JOURNAL OF VOLCANOLOGY AND GEOTHERMAL RESEARCH
ISSN
0377-0273
Date Issued
2026-02-21
Author(s)
DOI
10.1016/j.jvolgeores.2026.108575
Abstract
Volcano monitoring is essential, especially in densely populated areas like Mt. Etna. This study investigates insoil radona naturally occurring noble gas-as a novel parameter for tracking magma dynamics and crustal/subcrustal fluid movements along active volcano-tectonic structures. We present and analyse continuous radon data from a station on Mt. Etna's southeastern flank, part of the Istituto Nazionale di Geofisica-Osservatorio Etneo network, spanning 2015-2023. This dataset represents the longest radon time series on Mt. Etna and among the most extended globally for active volcanoes, covering a wide range of eruptive styles from effusive to highly explosive events. To isolate volcanic signals from environmental noise, we applied innovative mathematical algorithms to the long-term radon series. The filtered data revealed both long-and short-term variations correlated with volcanic activity. Notably, significant anomalies coincided with paroxysmal eruptions (e.g., Voragine 2015-2016, the 2020-2022 sequence at the South East Crater) and seismic swarms linked to shallow magma intrusions. To validate these findings, we integrated the radon record with a petrological dataset documenting major recharge phases during the same period. This multidisciplinary approach provided new insights into magmatic storage, transfer, and interaction within the Etnean plumbing system. While further investigation is needed, our results highlight the promising role of in-soil radon as a complementary tool for volcano monitoring. By demonstrating its effectiveness in detecting precursory magma movements, this study contributes to advancing geochemical surveillance methods and reinforces the role of integrated approaches in Earth science research and volcanic hazard mitigation.
Project(s)
GRINT
Funding(s)
This research was partly funded from project Geoscience Research INfracstructure of ITaly (GRINT); project code PIR01_00013.
