Search

A passive seismic experiment is carried out at the non-volcanic highly degassing site of Mefite d'Ansanto located at the northern tip of the Irpinia region (southern Italy), where the 1980 MS 6.9 destructive earthquake occurred. Between 2020 and 2021, background seismic noise was recorded by deploying a broadband seismic station and a seismic array composed of seven 1 Hz three-component sensors. Using two different array configurations, we were allowed to explore in detail the 1–20 Hz frequency band of the seismic noise wavefield as well as Rayleigh wave phase velocities in the 400–800 m/s range. Spectral analyses and array techniques were applied to one year of data showing that the frequency content of the signal is very stable in time. High frequency peaks are likely linked to the emission source, whereas at low frequencies seismic noise is clearly correlated to meteorological parameters. The results of this study show that small aperture seismic arrays probe the subsurface of tectonic CO2-rich emission areas and contribute to the understanding of the link between fluid circulation and seismogenesis in seismically active regions. [ABSTRACT FROM AUTHOR]

One of the strategies to detect the precursors of an eruption is to define the background dynamical state of a volcano for a prompt recognition of deviations from the basic condition. Mt. Vesuvius (Italy), currently in a quiescent state, is one of the most monitored volcanoes in the world, inciting multidisciplinary advanced studies. Hence an understanding of the links among the different monitored parameters is mandatory. In recent decades the joint analyses of ground tilt and seismicity have added to the understanding of the volcano's activity. In this paper, we outline the first steps towards a comprehension of the link between Mt. Vesuvius earthquakes and co-seismic ground tilt, after excluding the contribution of other external forces acting on the ground, such as tides, landslides or exceptional meteorological phenomena. We used the seismicity with a duration magnitude ≥ 2.0 recorded at Mt. Vesuvius in the period 2018–2020 to estimate the source parameters and to calculate the associated static displacement. Then, we compared the ground inclination retrieved from the estimated seismic deformation with the long-term ground motion trend measured by tiltmeters. We found that in most cases the two vectors have a comparable size and direction. [ABSTRACT FROM AUTHOR]

This work is devoted to the analysis of the background seismic noise acquired at the volcanoes (Campi Flegrei caldera, Ischia island, and Vesuvius) belonging to the Neapolitan volcanic district (Italy), and at the Colima volcano (Mexico). Continuous seismic acquisition is a complex mixture of volcanic transients and persistent volcanic and/or hydrothermal tremor, anthropogenic/ambient noise, oceanic loading, and meteo-marine contributions. The analysis of the background noise in a stationary volcanic phase could facilitate the identification of relevant waveforms often masked by microseisms and ambient noise. To address this issue, our approach proposes a machine learning (ML) modeling to recognize the "fingerprint" of a specific volcano by analyzing the background seismic noise from the continuous seismic acquisition. Specifically, two ML models, namely multi-layer perceptrons and convolutional neural network were trained to recognize one volcano from another based on the acquisition noise. Experimental results demonstrate the effectiveness of the two models in recognizing the noisy background signal, with promising performance in terms of accuracy, precision, recall, and F1 score. These results suggest that persistent volcanic signals share the same source information, as well as transient events, revealing a common generation mechanism but in different regimes. Moreover, assessing the dynamic state of a volcano through its background noise and promptly identifying any anomalies, which may indicate a change in its dynamics, can be a practical tool for real-time monitoring. [ABSTRACT FROM AUTHOR]

In the last decades, thermal infrared ground-based cameras have become effective tools to detect significant spatio-temporal anomalies in the hydrothermal/volcanic environment, possibly linked to impending eruptions. In this paper, we analyzed the temperature time-series recorded by the ground-based Thermal Infrared Radiometer permanent network of INGV-OV, installed inside the Solfatara-Pisciarelli area, the most active fluid emission zones of the Campi Flegrei caldera (Italy). We investigated the temperatures' behavior in the interval 25 June 2016–29 May 2020, with the aim of tracking possible endogenous hydrothermal/volcanic sources. We performed the Independent Component Analysis, the time evolution estimation of the spectral power, the cross-correlation and the Changing Points' detection. We compared the obtained patterns with the behavior of atmospheric temperature and pressure, of the time-series recorded by the thermal camera of Mt. Vesuvius, of the local seismicity moment rate and of the CO2 emission flux. We found an overall influence of exogenous, large scale atmospheric effect, which dominated in 2016–2017. Starting from 2018, a clear endogenous forcing overcame the atmospheric factor, and dominated strongly soil temperature variations until the end of the observations. This paper highlights the importance of monitoring and investigating the soil temperature in volcanic environments, as well as the atmospheric parameters. [ABSTRACT FROM AUTHOR]

In the present paper, we analyse ground tilt and seismicity at Campi Flegrei caldera and Ischia Island, two volcanic areas located in the south of Italy. These areas have been well studied for many years from a petrological, volcanological and geophysical view point. Moreover, due to the high seismic and volcanic risk for the populations living there, they are continuously monitored by networks of geophysical and geochemical sensors. We summarize the most important results that we obtained so far, concerning the observations of relationships between seismic activity and ground tilt anomalies, focusing on the time interval 2015–2018. First, we present a detailed description of the tiltmeter and seismic networks in both the investigated areas, as well as their development and improvement over time that has enabled high quality data collection. From the joint analysis of the seismic and borehole tiltmeter signals, we often notice concurrence between tilt pattern variations and the occurrence of seismicity. Moreover, the major tilt anomalies appear to be linked with the rate and energy of volcano-tectonic earthquakes, as well as with exogenous phenomena like solid Earth tides and hydrological cycles. The analysis that we present has potential applicability to other volcanic systems. Our findings show how the joint use tilt and seismic data can contribute to better understanding of the dynamics of volcanoes. [ABSTRACT FROM AUTHOR]