Ambient Noise Analysis Reveals Seismic Velocity Changes during the 2021 Unrest at Vulcano Island

The detection of volcanic unrest is a critical component of volcanic monitoring and risk mitigation, especially for volcanoes with persistent hydrothermal activity and no recent eruptions. Identifying early signs of reactivation in such systems is particularly challenging due to the complex interplay between magmatic and hydrothermal processes.

Vulcano, one of the seven volcanic islands in the Aeolian archipelago (Southern Italy), is characterized by fumarolic activity and well-documented historical eruptions. The last eruptive event, occurring in 1888–1890 AD, featured episodic explosive activity of varying intensity, with the most violent explosions ejecting bombs and blocks over 1 km from the crater. Due to its small size and the proximity of active volcanic features to densely populated and tourist areas, Vulcano represents a critical site for volcanic risk management. In mid-September 2021, the island experienced significant degassing episodes at La Fossa cone, marking a period of unrest without eruptive activity. This unique scenario makes Vulcano an ideal natural laboratory for studying volcanic unrest in the absence of eruptions, providing valuable insights into the underlying magmatic-hydrothermal system.

Using continuous seismic records from Vulcano, we analyze relative seismic velocity changes (dv/v) through the cross-correlation of ambient noise, employing the MSNoise package \citep{lecocq2014msnoise}. Our analysis covers the pre-unrest, unrest, and post-unrest periods from 2016 to 2024, offering a long-term perspective on the temporal evolution of the system. Preliminary results show significant changes in dv/v that appear to be related to the 2021 episode of unrest, which corresponds to increased seismic activity, variations in gas emissions, and ground deformation. Long-term monitoring of Vulcano is crucial for identifying early signs of reactivation, which can significantly improve eruption forecasting and risk mitigation strategies. These findings highlight the potential of seismic noise analysis for real-time monitoring and to advance our understanding of the dynamics of volcanic unrest.

References
_{Lecocq, T., Caudron, C., & Brenguier, F. (2014). Msnoise, a python package for monitoring seismic velocity changes using ambient seismic noise. Seismological Research Letters, 85 (3), 715–726.}