Search

Over the last 20 years, infrasound signals have been used to investigate and monitor active volcanoes during eruptive and degassing activity. In particular, infrasound amplitude information has been used to estimate eruptive parameters such as plume height, magma discharge rate and lava fountain height. Active volcanoes are characterized by pronounced topography and, during eruptive activity, the topography can change rapidly, affecting the observed infrasound amplitudes. While the interaction of infrasonic signals with topography has been investigated by several authors over the past decade, the impact of changing topography on the infrasonic amplitudes has not yet been explored. In this work, the infrasonic signals accompanying 57 lava fountain paroxysms at Mount Etna (Italy) during 2021 were analyzed. In particular, the temporal and spatial variations of the infrasound amplitudes were investigated. During 2021, significant changes in the topography around the most active crater (the South-East Crater) took place and were reconstructed in detail through unoccupied aerial system surveys. Through analysis of the observed infrasound signals and numerical simulations of the acoustic wavefield, we demonstrate that the observed spatial and temporal variation in the infrasound signals can be explained by the combined effects of changes in the location of the acoustic source and changes in the near-vent topography. This work demonstrates the importance of accurate source locations and high-resolution topographic information, particularly in the near-vent region where the topography is most likely to change rapidly. Changing topography should be considered when interpreting local infrasound observations over long time-scales.

Rotational sensors have been deployed on several volcanoes worldwide including Kilauea, Stromboli, Etna and a few volcanoes in Iceland. Within this presentation we focus on our first experiment using a rotational sensor on Etna in Italy. We recorded the volcanic activity including degassing and vigorous strombolian activity in August to September 2019. We compare our results using a rotational sensor with a normal Trillium Compact seismometer and the seismic network maintained by the INGV. We detect LP events, VT events and volcanic tremor, study the wavefield and back azimuths of the events and derive phase velocities of the ground. Luckily, we were able to assess the quality of our results using the detailed earthquake catalogues and locations derived at the INGV. We can easily detect changes in the wavefield e. g. when strong strombolian activity kicks in and are looking forward to applications on other volcanoes where details of the volcanic activity or changes might go unnoticed if no rotational sensor is present.

Since September 2021, signs of unrest at Vulcano Island have been noticed after four years of quiescence, along with CO2 degassing and the occurrence of long-period and very long-period events. With the intention of improving the monitoring activities, a submarine fiber optic telecommunications cable linking Vulcano Island to Sicily was interrogated from 15 January to 14 February 2022. Of particular interest has been the recording of 1488 events with wide range of waveforms made up of two main frequency bands (from 3 to 5 Hz and from 0.1 to 0.2 Hz).With the aim of the automatic detection of seismic-volcanic events, different approaches were explored, particularly investigating whether the application of machine learning could provide the same performance as conventional techniques. Unlike many traditional algorithms, deep learning manages to guarantee a generalized approach by automatically and hierarchically extracting the relevant features from the raw data. Due to their spatio-temporal density, the data acquired by the DAS can be assimilated to a sequence of images; this property has been exploited by re-designing deep learning techniques for image processing, specifically employing Convolutional Neural Networks.The results demonstrate that deep learning not only achives good performance but that it even outperforms classical algorithms. Despite providing a generalized approach, Convolutional Neural Networks have been shown to be more effective than traditional tecniques in expoiting the high spatial and temporal sampling of the acquired data.

Monitoring the state of the sea is a fundamental task for economic activities in the coastal zone, such as transport, tourism and infrastructure design. In recent years, regular wave height monitoring for marine risk assessment and mitigation has become unavoidable as global warming impacts in more intense and frequent swells.In particular, the Mediterranean Sea has been considered as one of the most responsive regions to global warming, which may promote the intensification of hazardous natural phenomena as strong winds, heavy precipitation and high sea waves. Because of the high density population along the Mediterranean coastlines, heavy swells could have major socio-economic consequences. To reduce the impacts of such scenarios, the development of more advanced monitoring systems of the sea state becomes necessary.In the last decade, it has been demonstrated how seismometers can be used to measure sea conditions by exploiting the characteristics of a part of the seismic signal called microseism. Microseism is the continuous seismic signal recorded in the frequency band of 0.05 and 0.4 Hz that is likely generated by interactions of sea waves together and with seafloor or shorelines.In this work, in the framework of i-WaveNET INTERREG project, we performed a regression analysis to develop a model capable of predicting the sea state in the Sicily Channel (Italy) using microseism, acquired by onshore instruments installed in Sicily and Malta. Considering the complexity of the relationship between spatial sea wave height data and seismic data measured at individual stations, we used supervised machine learning (ML) techniques to develop the prediction model. As input data we used the hourly Root Mean Squared (RMS) amplitude of the seismic signal recorded by 14 broadband stations, along the three components, and in different frequency bands, during 2018 - 2021. These stations, belonging to the permanent seismic networks managed by the National Institute of Geophysics and Volcanology INGV and the Department of Geosciences of the University of Malta, consist of three-component broadband seismometers that record at a sampling frequency of 100 Hz.As for the target, the significant sea wave height data from Copernicus Marine Environment Monitoring Service (CMEMS) for the same period were used. Such data is the hindcast product of the Mediterranean Sea Waves forecasting system, with hourly temporal resolution and 1/24° spatial resolution. After a feature selection step, we compared three different kinds of ML algorithms for regression: K-Nearest-Neighbors (KNN), Random Forest (RF) and Light Gradient Boosting (LGB). The hyperparameters were tuned by using a grid-search algorithm, and the best models were selected by cross-validation. Different metrics, such as MAE, R2 and RMSE, were considered to evaluate the generalization capabilities of the models and special attention was paid to evaluate the predictive ability of the models for extreme wave height values.Results show model predictive capabilities good enough to develop a sea monitoring system to complement the systems currently in use.

Volcanic activity produces a broad spectrum of seismic and acoustic signals whose characteristics provide important clues on the underlying magmatic processes. Networks and arrays of seismic and acoustic sensors are the backbone of most modern volcano monitoring programs. Investigation of the signals gathered by these instruments requires efficient workflows and specialist software. The high sampling rates, typically 50 Hz or greater, at which seismic and acoustic waveforms are recorded by multistation networks and dense arrays leads to the rapid accumulation of large volumes of data, making the implementation of efficient data analysis workflows for volcano surveillance a challenging task. Here, we present an open-source MATLAB graphical user interface, MISARA (Matlab Interface for Seismo-Acoustic aRray Analysis), designed to provide a user-friendly workflow for the analysis of seismoacoustic data in volcanic environments. MISARA includes efficient algorithm implementations of well-established techniques for seismic and acoustic data analysis. It is designed to support visualization, characterization, detection, and location of volcano seismoacoustic signals. Its intuitive, modular, structure facilitates rapid, semiautomated, inspection of data and results, thus reducing user effort. MISARA was tested using seismoacoustic data recorded at Etna Volcano (Italy) in 2010, 2011, and 2019, and is intended for use in education and research, and to support routine data analysis at volcano observatories.

On 13 May 2008, a strong eruption took place along a fracture opened on Mt. Etna's eastern flank accompanied by significant seismic activity. Recent studies show that seismic ambient noise is an effective method to observe the fluctuations of seismic wave velocities due to volcanic and seismic activities. In this study, we analyze the temporal seismic velocity changes (dv/v) from January 2007 to June 2008 at Mt. Etna by using seismic ambient noise. We retrieve a large dataset to calculate dv/v because of the large number of permanent seismic stations located at Mt. Etna. Daily cross-correlation functions (CCFs) are computed at 15 stations for 105 interstation pairs in the 1-2 Hz frequency band by using vertical components. We observe that the dv/v displays a gradual reduction and reaches down to -0.3% associated with the aforementioned volcanic activity. We compared our results with volcano-tectonic earthquakes and volcanic tremor. Our study shows a significant relationship between the magma intrusion and decrease of the dv/v.

Etna volcano in Italy is one of the most active volcanoes in Europe. We recorded the volcanic activity including degassing and vigorous strombolian activity using a seismometer and a rotational sensor in August to September 2019. We test the newly developed rotational sensor in the field in comparison to the broadband seismometer and seismic-network-based locations using the INGV network. We demonstrate that a single rotational sensor co-located with a seismometer can be used to identify specific seismic wave types, to estimate the back azimuth of wave arrivals and the local seismic phase velocities.Using the rotational sensor, we easily detected the dominant SH-type waves composing volcanic tremor during weak volcanic activity and the recorded VLP/ LP events. Changes in the composition of the tremor wavefield caused by the onset of vigorous volcanic activity are obvious and can be detected in near real-time if data is streamed. We discuss the changes in the wavefield composition from SH-type waves to a mixed wavefield in the context of the volcanic activity, the back azimuth of the signals and associated phase velocities. Our findings are consistent with observations by INGV and hence the rotational sensor reliably enlarges our sensor portfolio in volcanic environments. In fact, wavefield and ground properties can be derived using just one sensor instead of a sensor network, which makes experiments in remote areas cheaper and easier to maintain. In addition, you can observe phenomena that otherwise go unnoticed, like near vent block rotation.

Over the last few years, three tilt deep stations (27-30 meters) have been set up in the summit area of Mount Etna volcano. The aim of this challenging project is to record the ground deformations of the summit craters activity with high precision. We considered data related to the August 23-26, 2018, Strombolian and effusive activity. In this case, tiltmeters recorded variations in the order of 10−7 radians, not observed at the other stations. These changes suggest a shallow contraction source just south of the Southeast Crater. This result, related to the volcanic tremor source, points to the presence of a gas/magma reservoir feeding the Strombolian activity at 1200 m above sea level.

During the COVID-19 pandemic, most countries put in place social interventions, restricting the mobility of citizens, to slow the spread of the epidemic. Italy, the first European country severely impacted by the COVID-19 outbreak, applied a sequence of progressive restrictions to reduce human mobility from the end of February to mid-March 2020. Here, we analysed the seismic signatures of these lockdown measures in densely populated eastern Sicily, characterized by the presence of a permanent seismic network used for earthquake and volcanic monitoring. We emphasize how the anthropogenic seismic noise decrease is visible even at stations located in remote areas (Etna and Aeolian Islands) and that the amount of this reduction (reaching ∼ 50 %–60 %), its temporal pattern and spectral content are strongly station-dependent. Concerning the latter, we showed that on average the frequencies above 10 Hz are the most influenced by the anthropogenic seismic noise. We found similarities between the temporal patterns of anthropogenic seismic noise and human mobility, as quantified by the mobile-phone-derived data shared by Google, Facebook and Apple, as well as by ship traffic data. These results further confirm how seismic data, routinely acquired worldwide for seismic and volcanic surveillance, can be used to monitor human mobility too.

Despite Mt. Etna's long-standing reputation as an effusive volcano, since 1986 there has been an evident increase in mid-intensity explosive eruptions from its summit craters, with more than 240 episodes, better known as paroxysms (otherwise called paroxysmal episodes). These are characterized by strong Strombolian to lava fountaining activity that lasts from tens of minutes to a few days, producing some km-high volcanic plumes and tephra fallouts up to hundreds of km on the ground. Most paroxysms give life to sequences which are clustered like “episodic” eruptions for periods of a few days to a few months, their frequent recurrence causing hazard to air traffic and impacting densely inhabited areas. Nonetheless, a list containing the dates and data of these eruptions is lacking. In this paper, we tried to fill this gap by compiling a complete record, including master data (date, crater), eruption style and seismic parameters for identifying, characterizing and quantifying both the individual episodes and the entire period. This information comes from a critical review of surveillance reports, raw-data analysis and scientific literature. A retrieval of homogenous and comparable seismic data was possible only for episodes after 2006 following the renewal of seismic stations. The eruption list provides a complete picture of the 1986–2021 paroxysms, allowing to evaluate their temporal distribution, make a statistical analysis of their time-interval, and undertake a comprehensive investigation of the features of volcanic tremor. The results show a high probability (72%) of having a paroxysmal episode in the 10 days following the previous one. Moreover, a scaling relationship associated with the number-size distribution of the amplitude increases of volcanic tremor accompanying the explosive activities has been constrained. During sequences of paroxysms, combining these outputs can help improve the hazard assessment in terms of frequency of the associated tephra fallouts, and predict the duration of the entire sequence.

During the COVID-19 pandemic, most countries worldwide put in place social interventions, consisting of restricting the mobility of citizens, aimed at slowing and mitigating the spread of the epidemic. In particular, Italy, as the first European country violently struck by the COVID-19 outbreak, applied a sequence of progressive restrictions to reduce both human mobility and human-to-human contacts from the end of February to mid-March 2020. Here, we analysed the seismic signatures of these lockdown measures in the densely populated Eastern Sicily, characterised by the presence of a permanent seismic network used for both seismic and volcanic monitoring. We specifically emphasize how the amount of the amplitude reduction of anthropogenic seismic noise (reaching ~50–60%), its temporal pattern and spectral content are strongly station-dependent. As for the latter, we exhibited that on average the frequencies above 10 Hz are the most influenced by the anthropogenic seismic noise. Finally, we found an impressive similarity between the temporal patterns of anthropogenic seismic noise and human mobility, as quantified by the mobile phone-derived data shared by Google, Facebook and Apple. These results further confirm how seismic data, routinely acquired worldwide for seismic and volcanic surveillance, can be used to monitor human mobility too.

Global warming is making extreme wave events more intense and frequent. Hence, the importance of monitoring the sea state for marine risk assessment and mitigation is increasing day-by-day. In this work, we exploit the ubiquitous seismic noise generated by energy transfer from the ocean to the solid earth (called microseisms) to infer the sea wave height data provided by hindcast maps. To this aim, we use a combined approach based on statistical analysis and machine learning. In particular, a random forest model shows very promising results in the spatial and temporal reconstruction of sea wave height by microseisms. The observed dependence of input importance from the distance sea grid cell-seismic station suggests how the reliable monitoring of the sea state in a wide area by microseisms needs data recorded by dense networks, comprising stations evenly distributed along the coastlines.

Syneruptive gas flux time series can, in principle, be retrieved from satellite maps of SO 2 collected during and immediately after volcanic eruptions, and used to gain insights into the volcanic processes which drive the volcanic activity. Determination of the age and height of volcanic plumes are key prerequisites for such calculations. However, these parameters are challenging to constrain using satellite-based techniques. Here, we use imagery from OMI and GOME-2 satellite sensors and a novel numerical procedure based on back-trajectory analysis to calculate plume height as a function of position at the satellite measurement time together with plume injection height and time at a volcanic vent location. We applied this new procedure to three Etna eruptions (12 August 2011, 18 March 2012 and 12 April 2013) and compared our results with independent satellite and ground-based estimations. We also compare our injection height time-series with measurements of volcanic tremor, which reflects the eruption intensity, showing a good match between these two datasets. Our results are a milestone in progressing towards reliable determination of gas flux data from satellite-derived SO 2 maps during volcanic eruptions, which would be of great value for operational management of explosive eruptions.

Magmatic degassing, typically measured as SO2 flux, plays a fundamental role in controlling volcanic eruption style and is one of the key parameters used by volcano observatories to assess volcanic unrest and detect eruption precursors. Volcanic tremor, the integrated amplitude of seismic energy release over a range of frequencies, is also a key parameter in volcano monitoring. A connection between volcanic degassing and tremor has been inferred through correlations between the signals which are often, but not always, observed during periods of unrest or eruption. However, data are often equivocal and our understanding of the physical processes, which couple degassing with tremor are still evolving. New insights into degassing-tremor coupling can be made by investigation of the long-term relationship between degassing and tremor, focusing on the frequency-dependence of tremor and passive degassing behavior. In this study, we examine how long-term SO2 emission rates and volcanic tremor on Mt. Etna, track rapid variability in eruptive dynamics. Correlations between SO2 flux and tremor are explored in both quiescent and eruptive periods, comparing the two parameters at both long and short time-scales (< < 1 day) for ∼2 years. Our analysis reveals that over ∼month-long timescales passive degassing of SO2 and tremor tend to be well-correlated, but these correlations are lost over shorter timescales. This reflects a coupling process between passive degassing and tremor, produced by a combination of gas flow through permeable magma and the convective flow of magma within the conduit. Short-term correlations are lost because variations in the continuous degassing process are relatively small compared with the overall degassing rate and fall below measurement noise. During eruptive periods strong correlations are observed between degassing and tremor, with a significant contribution of higher frequency signal in tremor, controlled by eruptive style. These observations suggest that in syn-eruptive periods the tremor source is dominated by the coupling between the eruption column and the ground through infrasonic waves, rather than conduit processes. Our results demonstrate the importance of high quality long-term observations and offer new insights into the physical mechanisms which couple degassing and volcanic tremor at active volcanoes.

Readings from a sensor for the radioactive gas near summit craters of the Italian volcano reveal signatures of such processes as seismic rock fracturing and sloshing of groundwater and other fluids.

Programma Nazionale Ricerche . Grant Number: PNRA14_00011 University of Catania FIR 2014 . Grant Numbers: 2F119B , PRA 2016‐18 , 22722132120

We analysed volcanic tremor recorded during ten lava fountain eruptions at Mount Etna volcano over the second half of 2011. The seis- mic signal, recorded by a network of 19 broadband stations, was corrected for site effects. The site amplification factors obtained for all the seismic stations were calculated using 18 regional earthquakes. To quantitatively estimate the goodness of the site correction, the vol- canic tremor source locations obtained by using site corrections were compared with those performed without such corrections. The seismic signal was filtered in two different frequency bands before applying correction: (i) the band 1-2 Hz, which contains most of the tremor energy, and (ii) the band 5-10 Hz, in which, likely due to scattering phenomena, the assumption of isotropic radiation behind the volcanic tremor source location method is valid. The results revealed that the seismic signal correction for site effects improved the tremor location results. Such improved tremor locations, together with volcanological and geodetic data, allowed us to identify two dis- tinct periods characterised by different tremor locations during lava fountains (July - August 20 and August 20 - November 15). Such differences were probably due to magma recharge phenomena, taking place during the former period.

In this paper, we analysed 3-component seismic signals recorded during 27 November 2016-10 January 2017 by two stations installed in Tethys Bay (Victoria Land, Antarctica), close to Mario Zucchelli Station. Due to the low noise levels, it was possible to identify three different kinds of signals: teleseismic earthquakes, microseisms, and icequakes. We focus on the latter two. A statistically significant relationship was found between microseism amplitude and both wind speed and sea swell. Thus, we suggest that the recorded microseism data are caused by waves at the shore close to the seismic stations rather than in the deep ocean during storms. In addition, we detected three icequakes, with dominant low frequencies (below 2 Hz), located in the David Glacier area with local magnitude of 2.4-2.6. These events were likely to have been generated at the rock-ice interface under the glacier. This work shows how seismic signals recorded in Antarctica provide insights on the interactions between the atmosphere-cryosphere-hydrosphere. Since climate patterns drive these interactions, investigations on Antarctic seismic signals could serve as a proxy indicator for estimating climate changes. © 2017 by Istituto Nazionale di Geofisica e Vulcanologia. All rights reserved.

Volcanoes generate a broad range of seismo-volcanic and infrasonic signals, whose features and variations are often closely related to volcanic activity. The study of these signals is hence very useful in the monitoring and investigation of volcano dynamics. The analysis of seismo-volcanic and infrasonic signals requires specifically developed techniques due to their unique characteristics, which are generally quite distinct compared with tectonic and volcano-tectonic earthquakes. In this work, we describe analysis methods used to detect and locate seismo-volcanic and infrasonic signals at Mt. Etna. Volcanic tremor sources are located using a method based on spatial seismic amplitude distribution, assuming propagation in a homogeneous medium. The tremor source is found by calculating the goodness of the linear regression fit (R 2) of the log-linearized equation of the seismic amplitude decay with distance. The location method for long-period events is based on the joint computation of semblance and R 2 values, and the location method of very long-period events is based on the application of radial semblance. Infrasonic events and tremor are located by semblance–brightness- and semblance-based methods, respectively. The techniques described here can also be applied to other volcanoes and do not require particular network geometries (such as arrays) but rather simple sparse networks. Using the source locations of all the considered signals, we were able to reconstruct the shallow plumbing system (above sea level) during 2011.

In this work, we report the results of an integrated approach using both seismological and geodetic data provided by the INGV-CT (Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Catania) Stromboli volcano monitoring systems, in order to improve the knowledge of its plumbing system. In particular, we investigated the relationships between the June 1999 seismic swarm, occurring in the area of Stromboli, and the possible activation of the NE–SW oriented volcano-tectonic structure. We analyzed this seismic swarm proposing new locations and a morphological analysis of the waveforms. This approach allowed us to demonstrate that there are relationships between the tectonic activity near Stromboli and the rising of magma. This evidence supports the hypothesis that during the 1999 swarm an intrusive process started from a crustal level where earthquakes were located (about 10–15 km b.s.l.). As already testified by other similar episodes (deformation anomaly recorded between December 1994 and March 1995 after the November 1994 swarm), months after the 1999 seismic activity, the tiltmeters and the GPS permanent stations deployed in Stromboli, showed slow variations over three months (May–July 2000). We performed an analytical inversion of these geodetic observations and found that the modelled sources are characterized by NE–SW trend, compatible with the regional faults cutting the volcano. The modelled sources could represent the rising pathway connecting the “deep” plumbing system (about 10–15 km b.s.l.) to the “shallow” one located in the body of the Stromboli volcano (about 500 m a.s.l.). These new evidences support the hypothesis of the existence of a simple plumbing system with different levels of magma storage, where batches of magma are periodically pushed up along the main NE–SW tectonic trend.

SUMMARY Seismicity in Eastern Sicily as recorded by the Submarine Network-1 seafloor observatory (SN1) in the period from 2002 October to 2003 May is examined with the aim of identifying the as yet poorly known seismogenic zones placed in the Ionian basin, where some of the strongest earthquakes have occurred. A comparison between the seismic recordings of land networks and the seafloor station has allowed us to focus on low-magnitude seismicity only recorded by SN-1. We have analysed 239 high-quality events from among a total of 485 seismic signals not included in the land-based network bulletins. The waveform features and the possible source zones for those events are investigated by means of polarization and particle motion techniques. Most of the 239 events (213) are characterized by high values of rectilinearity typical of P- and S-arrival particle motions, while the remaining 26 events have different polarization features, with an emergent first phase and prevalently planar polarization. We have interpreted the latter signals as being associated to submarine landslides. From particle motion analysis, we have determined the azimuthal distribution of the events and the incidence angles of P waves in respect to the Observatory with the aim of determining their distribution in relation to the active but scarcely known structural setting of the off-shore area. Moreover, the integrated locations of some earthquakes occurring in the study area and recorded by SN-1 and land stations was performed to determine the apparent P-wave velocity necessary to calculate source-station distances. As an additional result of the integration, we have obtained more accurate locations of earthquakes occurring in the coastal and off-shore areas of Eastern Sicily, associated with reduced horizontal and vertical errors and significantly lower values of azimuthal gaps. Lastly, a location distribution of the 213 analysed events was obtained by setting two conditions: (1) a maximum epicentral distance to a fixed depth coinciding with the depth of the seafloor station and (2) a minimum epicentral distance associated to the maximum depth of events. Accordingly, two patterns of seismicity were determined for the maximum and the minimum expected spread of the hypocentres. The main features of both patterns are a diffuse seismicity in the Western Ionian basin with a major epicentre density SE of SN-1 and a depth of most of the events within 60 km. Local magnitude determination was also performed, taking into account an attenuation law proposed for Southeastern Sicily. Despite the uncertainties in the location distribution using single-station recordings, the results show diffuse seismicity all around SN-1 and, in particular, in the off-shore area.

Following the installation of a broadband network on Mt. Etna, sustained Long-Period (LP) activity was recorded accompanying a period of total quiescence and the subsequent onset of the 2004– 2005 effusive episode. From about 56000 events detected by an automatic classification procedure, we analyse a subset of about 3000 signals spanning the December 17th, 2003– September 25th, 2004, time interval. LP spectra are characterised by several, unevenly-spaced narrow peaks spanning the 0.5– 10 Hz frequency band. These peaks are common to all the recording sites of the network, and different from those associated with tremor signals. Throughout the analysed time interval, LP spectra and waveforms maintain significant similarity, thus indicating the involvement of a non-destructive source process that we interpret in terms of the resonance of a fluid-filled buried cavity. Polarisation analysis indicates radiation from a non-isotropic source involving large amounts of shear. Concurrently with LP signals, recordings from the summit station also depict Very-Long-Period (VLP) pulses whose rectilinear motion points to a region located beneath the summit craters at depths ranging between 800 and 1100 m beneath the surface. Based on a refined repicking of similar waveforms, we obtain robust locations for a selected subset of the most energetic LP events from probabilistic inversion of travel-times calculated for a 3D heterogenous structure. LP sources cluster in a narrow volume located beneath the summit craters, and extending to a maximum depth of ≈ 800 m beneath the surface. No causal relationships are observed between LP, VLP and tremor activities and the onset of the 2004– 2005 lava effusions, thus indicating that magmatic overpressure played a limited role in triggering this eruption. These data represent the very first observation of LP and VLP activity at Etna during non-eruptive periods, and open the way to the quantitative modelling of the geometry and dynamics of the shallow plumbing system.

Instrumental seismic catalogues are an essential tool for the zonation of the territory and the production of seismic hazard maps. They are also a valuable instrument for detailed seismological studies regarding active volcanoes and, above all, for interpreting the magma dynamics and the evolution of eruptive phenomena. In this paper, we show the first instrumental earthquake catalogue of Mt. Etna, for the period 2000-2010, with the purpose of producing a homogeneous dataset of 10 years of seismological observations. During this period, 16,845 earthquakes have been recorded by the seismic network run by the Istituto Nazionale di Geofisica and Vulcanologia, Osservatorio Etneo, in Catania. A total of 6,330 events, corresponding to approximately 40% of all earthquakes recorded, were located by using a one-dimensional VP velocity model. The magnitude completeness of the catalogue is equal to about 1.5 for the whole period, except for some short periods in 2001 and 2002-2003 and at the end of 2009. The reliability of the data collected is supported by the good values of the main hypocentral parameters through the time. The spatial distribution of seismicity allowed the highlighting of several seismogenetic areas characterized by different seismic rates and focal depths. This seismic catalogue represents a fundamental tool for several research aiming to a better understanding of the behavior of an active volcano such as Mt. Etna.

Starting off from a review of previous literature on kinematic models of the unstable eastern flank of Mt. Etna, we propose a new model. The model is based on our analysis of a large quantity of multidisciplinary data deriving from an extensive and diverse network of INGV monitoring devices deployed along the slopes of the volcano. Our analysis had a twofold objective: first, investigating the origin of the recently observed slow-slip events on the eastern flank of Mt. Etna; and second, defining a general kinematic model for the instability of this area of the volcano. To this end, we investigated the 2008–2013 period using data collected from different geochemical, geodetic, and seismic networks, integrated with the tectonic and geologic features of the volcano and including the volcanic activity during the observation period. The complex correlations between the large quantities of multidisciplinary data have given us the opportunity to infer, as outlined in this work, that the fluids of volcanic origin and their interrelationship with aquifers, tectonic and morphological features play a dominant role in the large scale instability of the eastern flank of Mt. Etna. Furthermore, we suggest that changes in the strain distribution due to volcanic inflation/deflation cycles are closely connected to changes in shallow depth fluid circulation. Finally, we propose a general framework for both the short and long term modeling of the large flank displacements observed.

During 2013 Mount Etna volcano experienced intense eruptive activity at the summit craters, foremost at the New Southeast Crater and to a minor degree at the Voragine and Bocca Nuova (BN), which took place in two cycles, February–April and September–December. In this work, we mainly focus on the period between these cycles, applying a multiparametric approach. The period from the end of April to 5 September showed a gradual increase in the amplitude of long-period (LP) events and volcanic tremor, a slight inflation testified by both tilt and GPS data, and a CO2 flux increase. Such variations were interpreted as due to a gradual pressurization of the plumbing system, from the shallowest part, where LP and volcanic tremor are located, down to about 3–9 km below sea level, pressure source depths obtained by both geodetic and CO2 data. On 5 September, at the same time as a large explosion at BN, we observed an instantaneous variation of the aforementioned signals (decrease in amplitude of LP events and volcanic tremor, slight deflation, and CO2 flux decrease) and the activation of a new infrasonic source located at BN. In the light of it, the BN explosion probably caused the instantaneous end of the pressurization, and the opening of a new vent at BN, that has become a new steady source of infrasonic events. This apparently slight change in the plumbing system also led to the gradual resumption of activity at the New Southeast Crater, culminating with the second lava fountain cycle of 2013.

The July 17 – August 9, 2001 flank eruption of Mt. Etna was preceded and accompanied by remarkable changes in volcanic tremor. Based on the records of stations belonging to the permanent seismic network deployed on the volcano, we analyze amplitude and frequency content of the seismic signal. We find considerable changes in the volcanic tremor which mark the transition to different styles of eruptive activity, e.g., lava fountains, phreatomagmatic activity, Strombolian explosions. In particular, the frequency content of the signal decreases from 5 Hz to 3 Hz at our reference station ETF during episodes of lava fountains, and further decreases at about 2 Hz throughout phases of intense lava emission. The frequency content and the ratios of the signal amplitude allow us to distinguish three seismic sources, i.e., the peripheral dike which fed the eruption, the reservoir which fed the lava fountains, and the central conduit. Based on the analysis of the amplitude decay of the signal, we highlight the migration of the dike from a depth of ca. 5 km to about 1 km between July 10 and 12. After the onset of the effusive phase, the distribution of the amplitude decay at our stations can be interpreted as the overall result of sources located within the first half kilometer from the surface. Although on a qualitative basis, our findings shed some light on the complex feeding system of Mt. Etna, and integrate other volcanological and geophysical studies which tackle the problem of magma replenishment for the July–August, 2001 flank eruption. We conclude that volcanic tremor is fundamental in monitoring Mt. Etna, not only as a marker of the different sources which act within the volcano edifice, but also of the diverse styles of eruptive activity.

Since January 2011, Mt. Etna volcano has been affected by more than forty paroxysmal eruptions at the summit (New South East Crater; NSEC). On the basis of their very variable duration, seven eruptions have been selected among the twenty-five of 2011–2012 in order to decipher potential differences in their triggering mechanism. Paroxysms have been investigated through a multidisciplinary approach that integrates data from volcanic tremor and petrology (textures and micro-analysis on plagioclase crystals). Our results lead to the conclusion that close relationships exist between the duration of the eruptions and the temporal evolution of the volcanic tremor amplitude, especially during the Strombolian phase preceding the paroxysmal activity. In this regard, we distinguished: 1) paroxysms preceded by long-lasting initial Strombolian phases, characterized by low rate of volcanic tremor amplitude increase; and 2) eruptions preceded by short initial Strombolian phases, showing high rate of volcanic tremor amplitude increase. Based on the pattern of volcanic tremor amplitude increase, the former mainly showed a ramp-shaped morphology, while the latter a bell-shaped trend. Location of the volcanic tremor centroid during the quiescent intervals between the paroxysmal eruptions has highlighted the presence of a magmatic volume at 1–2 km a.s.l. beneath the North East Crater (NEC). During the syn-eruptive Strombolian and lava fountaining phases, the centroid of volcanic tremor migrates below the NSEC. This leads to the consideration that the magma batch residing beneath NEC played an important role in the volcanic activity at NSEC during the considered period. Also the textures and compositional zoning (anorthite and iron variations) in selected plagioclase crystals of the analyzed lavas suggest relations between duration of the paroxysms and dynamics of pre-eruptive magmatic processes at depth. Particularly, two mechanisms have been accounted for triggering of eruptions at the NSEC on the basis of the concordant or discordant behavior of anorthite and iron in plagioclase coupled with disequilibrium textures at the rim. Concordant anorthite and iron increases in plagioclase crystals with sieve-textured rims indicate recharge by more mafic, gas-rich magma. This textural-compositional behavior has been related to long-lasting eruptions, whose volcanic tremor amplitude evolution produced ramp-shaped increase of the volcanic tremor amplitude before the paroxysmal phase. On the contrary, crystals with sieve-textures at the rim, characterized by increasing iron at rather constant or decreasing anorthite, suggest the prominent role of gas injections into the residing system. In this instance, the compositional behavior has been linked with short-lasting eruptions, whose volcanic tremor amplitude evolution led to a sudden increase of the seismic amplitude before the climax of the eruption. Thus, our work put forward the idea that the evolution and duration of the Strombolian phase preceding the paroxysmal eruptions of 2011–2012 at Mt. Etna are strongly controlled by the eruption triggering mechanism, which can be either gas burst or gas-rich magma recharge.

In this paper we report seismological evidence regarding the emplacement of the dike that fed the July 18 - August 9, 2001 lateral eruption at Mt. Etna volcano. The shallow intrusion and the opening of the eruptive fracture system, which mostly occurred during July 12, and July 18, were accompanied by one of the most intense seismic swarms of the last 20 years. A total of 2694 earthquakes (1 £ Md £ 3.9) were recorded from the beginning of the swarm (July 12) to the end of the eruption (August 9). Seismicity shows the upward migration of the dike from the basement to the relatively thin volcanic pile. A clear hypocentral migration was observed, well constraining the upwards propagation of a near-vertical dike, oriented roughly N-S, and located a few kilometers south of the summit region. Earthquake distribution and orientation of the P-axes from focal mechanisms indicate that the swarm was caused by the local stress source related to the dike intrusion.

Advances in volcano monitoring and forecasting need a multidisciplinary collaborative framework. In light of this, a Bayesian Event Tree (BET) approach was performed by the application of the BET for Eruption Forecasting (BET_EF) code to analyze the space-time distribution of the volcanic activity of Mount Etna from 2001-2005. First, a reliable monitoring dataset was set up after some sessions to elicit geophysical, volcanological and geochemical 'precursor' parameters. A constant unrest probability of 100%, with a magma involvement usually greater than 95%, was computed throughout the time period analyzed. Eruption probabilities higher than 90% were estimated a few days before the onsets of the 2001 and 2002-2003 flank eruptions. Values slightly higher than 75% were observed during the lava fountaining period in June-July 2001. However, the probabilities flattened to around 30% for the 2004-2005 flank eruption. With suitable data, a good depiction of the actual location of the eruptive scenario for the 2001 and 2002-2003 events was provided. Conversely, the size of the eruptions was not indicated. © 2011 by the Istituto Nazionale di Geofisica e Vulcanologia. All rights reserved.

[1] Influences of distant earthquakes on volcanic systems by dynamic stress transfer are well documented. We analyzed seismic signals and volcanic activity at Mount Etna during two periods, January 2006 and May 2008, that clearly showed variations coincident with distant earthquakes. In the first period, characterized by mild volcano activity, the effect of the dynamic stress transfer, caused by an earthquake in Greece (M = 6.8), was twofold: (1) banded tremor activity changed its features and almost disappeared; (2) a swarm of volcano-tectonic (VT) earthquakes took place. The changes of the banded tremor were likely due to variations in rock permeability, caused by fluid flows driven by dynamic strain. The VT earthquake swarm probably developed as a secondary process, promoted by the dynamically triggered activation of magmatic fluids. The second period, May 2008, showed an intense explosive activity. During this interval, the dynamic stress transfer, associated with the arrival of the seismic waves of the Sichuan earthquake (M = 7.9), affected the character of the seismo-volcanic signals and on the following day triggered an eruption. In particular, we observed changes in volcanic tremor and increases of both occurrence rate and energy of long period events. In this case, we suggest that dynamic stress transfer caused nucleation of new bubbles in volatile-rich magma bodies with consequent buildup of pressure, highlighted by the increase of long period activity, followed by the occurrence of an eruption. We conclude that stresses from distant earthquakes are capable of modifying the state of the volcano.

Large variations of the CO2 flux through the soil were observed between November 2002 and January 2006 at Mt. Etna volcano. In many cases, the CO2 flux was strongly influenced by changes in air temperature and atmospheric pressure. A new filtering method was then developed to remove the atmospheric influences on soil CO2 flux and, at the same time, to highlight the variations strictly related to volcanic activity. Successively, the CO2 corrected data were quantitatively compared with the spectral amplitude of the volcanic tremor by cross correlation function, cross-wavelet spectrum and wavelet coherence. These analyses suggested that the soil CO2 flux variations preceded those of volcanic tremor by about 50 days. Given that volcanic tremor is linked to the shallow (a few kilometer) magma dynamics and soil CO2 flux related to the deeper (~12 km b.s.l.) magma dynamics, the “delayed similarity” between the CO2 flux and the volcanic tremor amplitude was used to assess the average speed in the magma uprising into the crust, as about 170–260 m per day. Finally, the large amount of CO2 released before the onset of the 2004–2005 eruption indicated a deep ingression of new magma, which might have triggered such an eruption.

[1] The unrest of Stromboli volcano leading to the February 27–April 2, 2007 eruptive period and to the March 15 paroxysm is constrained by combining broad-band seismic data and 1-Hz GPS (High Rate GPS – hereinafter HRGPS) measurements. During the pre-eruptive stage, the simultaneous examination of seismic and HRGPS data, together with weather parameters, suggests the possible influence of external perturbations on the magmatic system, which evolved toward a critical state after January 2007. Some days after the onset of the eruption, a sudden change of the seismic and eruptive behaviour was recognized, while ground deformation began to show a deflation. The March 15 paroxysm was preceded, about two days before, by a peak of the HRGPS spectral power densities (a small inflation) and by the occurrence of a few VT earthquakes located at depths down to 3.5 km b.s.l. These findings constrain, for the first time at Stromboli volcano, the deep origin of a fast rising magma batch, rich in gas, that led to a strong explosive event.

[1] Source and Qp parameters were estimated from the inversion of first arrival P waveform durations of about 300 microearthquakes recorded at a digital seismic network operating in southeastern Sicily. The average risetime and pulse width at each station do not show large differences, allowing us to exclude significant differential attenuation site effects. A first Qp estimate was obtained by applying the classical risetime method, under the assumption of a point-like source time function. In order to investigate the effect of directivity due to the finiteness of seismic sources, new nonlinear relationships, based on a circular crack model rupturing at a constant velocity, were numerically built. These relationships were used to formulate a nonlinear inverse method for retrieving source (radius, dip, and strike of the circular crack) and Qp parameters from the inversion of risetime and pulse width data. The application of the method produced a better fit of the observed data and a Qp value higher than that obtained by applying the risetime method. The discrepancy between the different Q estimates may be due to a trade-off among source dimension and Qp, as we inferred from a test on a subset of low-magnitude events (Ml ≤ 2.5). A good agreement with independent estimates of fault plane solutions, as inferred from P polarities and S polarizations, was found. The estimated stress drops are generally very low (0.1–10 bars). This suggests that the background seismic activity in southeastern Sicily is related to fault segments and/or weakened zones where great stress accumulations are hindered.

The monitoring of seismic activity inSoutheastern Sicily (Italy) has beenrecently improved by a digital seismicnetwork. This effort has produced ahomogeneous and complete dataset which weused to define a reference 1-D velocitymodel. We have inverted P- and S-wavearrival times from 51 selected localearthquakes by using several initialvelocity and layer thickness models. Then,the range of possible velocity modelsobtained was tested with earthquakelocations to select the best velocitymodel. Improvements in location accuracy byusing the Minimum 1-D velocity model, withrespect to the locations obtained by usingthe routine velocity model, were evidencedfrom the reduced residuals, the smallerestimated location errors, and theincreased tendency of foci to cluster. Thedistribution of relocated hypocentersconfirmed the lack of seismic activity inthe central part of the area.