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The detailed analysis of volcanic seismicity can allow the identification of the processes occurring in a volcanic system and obtain information about its state and evolution. In the last decades, the seismicity of Mt. Vesuvius has consisted mainly of volcano-tectonic (VT) seismic events, with an average rate of some hundreds of earthquakes per year with magnitudes between −1.0 and 2.5, located up to 6-7 km below sea level (b.s.l.). Unusual low-frequency (LF) seismicity has also been observed, localized at a depth of 5-7 km. Previous seismic source analyses applied conventional methodologies based on first pulse characteristics, which are difficult due to high background noise, low magnitude and emergent first arrivals. To overcome these challenges, we analyze here the Mt. Vesuvius seismicity over the past 20 years by using a robust probabilistic seismic source inversion tool. This methodology provides the results in terms of moment tensor solutions estimated by using seismic waveforms and waveform attributes. In agreement with previous studies, two clusters of seismicity are clearly evidenced, both in terms of depth (0-4 km and 5-7 km b.sl. for VT and LF events, respectively) and frequency content (5-15 Hz and 2-6 Hz, respectively). Our preliminary results show that: a) the probabilistic approach for the whole waveform inversion provides acceptable results even for small magnitude earthquakes, and b) both seismicity clusters show strongly heterogeneous focal mechanisms, confirming past literature studies. We attribute the latter result to a highly heterogeneous stress field beneath Mt. Vesuvius., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Flow-like landslides, which occur mainly in shallow granular deposits resting on steep bedrock, represent a major natural hazard worldwide. The pore water pressure distribution and the soil water content directly affect the soil shear strength, thus controlling the triggering of these landslides. Criticalgeomorphological and topographical settings, together with peculiar stratigraphic and hydrogeological features, are commonly recognized as predisposing factors for flow-like landslides occurrence. Hence, investigating the spatial and temporal variability of hydraulic slope conditions is a fundamental activity that consists of identifying local geological factors and seasonal monitoring of the subsurface water regime. The present work proposes an integrated geological, geophysical and geotechnical approach to identify the spatial variability of the local stratigraphic setting and hydrogeological conditions in a partially saturated slope, in order to set up a procedure able to provide a prediction of the flow-like landslides occurrence atslope scale. The multidisciplinary study has been applied to a test site on Mt. Faito, in the Lattari Mts. (Southern Italy), where extensive geophysical, geological and geotechnical soil characterization and in situmonitoring data collected over two years are available.

The coupled effects of climate change and land sinking make deltas and coastal areas prone to inundation and flooding, meaning that reliable estimation of land subsidence is becoming crucial. Commonly, land subsidence is monitored by accurate continuous and discrete measurements collected by terrestrial and space geodetic techniques, such as Global Navigation Satellite System (GNSS), Interferometry Synthetic Aperture Radar (InSAR), and high precision leveling. In particular, GNSS, which includes the Global Positioning System (GPS), provides geospatial positioning with global coverage, then used for deriving local displacements through time. These site-positioning time series usually exhibit a linear trend plus seasonal oscillations of annual and semi-annual periods. Although the periodic components observed in the geodetic signal affect the velocity estimate, studies dealing with the prediction and prevention of risks associated with subsidence focus mainly on the permanent component. Periodic components are simply removed from the original dataset by statistical analyses not based on the underlying physical mechanisms. Here, we propose a systematic approach for detecting the physical mechanisms that better explain the permanent and periodic components of subsidence observed in the geodetic time series. It consists of three steps involving a component recognition phase, based on statistical and spectral analyses of geodetic time series, a source selection phase, based on their comparison with data of different nature (e.g., geological, hydro-meteorological, hydrogeological records), and a source validation step, where the selected sources are validated through physically-based models. The application of the proposed procedure to the Codigoro area (Po River Delta, Northern Italy), historically affected by land subsidence, allowed for an accurate estimation of the subsidence rate over the period 2009–2017. Significant differences turn out in the retrieved subsidence velocities by using or not periodic trends obtained by physically based models.

Nelle aree vulcaniche, come l’Isola d’Ischia, l’ampia variabilità litologica e l’alto gradiente geotermico richiedono analisi sempre più accurate per la definizione di specifici modelli di velocità e di attenuazione delle onde sismiche. Nel distretto vulcanico campano, modelli di velocità e attenuazione sempre più accurati sono stati ottenuti per il Vesuvio e per l’area dei Campi Flegrei, meno o del tutto assenti per quel che riguarda l’attenuazione per l’isola d’Ischia. È ben noto come la dettagliata conoscenza del modello di velocità possa fornire risultati più affidabili in termini di localizzazione dei terremoti locali. A tal proposito, è bene ricordare che, dal 1999, almeno 78 terremoti sono stati registrati ad Ischia (elenco aggiornato al 21 febbraio 2018) e sono stati localizzati utilizzando il modello disponibile per i Campi Flegrei, scelto sulla base di similarità geologiche e vulcanologiche. Pertanto, l’obiettivo di questo lavoro è la definizione di un modello 1-D in velocità e attenuazione della crosta più superficiale (fino a 2 km di profondità) di Ischia utilizzando tecniche di array applicate al rumore sismico e rapporti spettrali valutati su segnali sismici registrati da sismometri a larga banda installati sull’isola ai fini della sorveglianza e del monitoraggio.

This study provides deeper insights on our knowledge of the 847 AD earthquake that struck a large area in Central-Southern Italy causing diffuse damages in northern Campania, Molise, and Latium. Through the integration of archaeoseismic observations, geological and geophysical surveys together with a critical review of historical written sources, it was possible to identify evidence of seismic effects on ancient Medieval buildings or structures uncovered during archaeological excavations.

In the last twenty years a growing interest is noticed in studying the process of carbon dioxide degassing from the geosphere in various field of Earth Sciences, with the aim of defining relationship between gas flux on the ground and tectonic structures, quantifying deeply derived CO2 released into the atmosphere and studying volcanic and non-volcanic degassing processes (Frondini et al., 2018). While it is already recognized that volcanic degassing can introduce huge quantities of carbon dioxide into the atmosphere, only recent studies (Kerrick and Seward, 1996; Chiodini et al., 2000) have shown that non-volcanic degassing may be a globally significant input of CO2 into the atmosphere and that many areas where large emissions of non-volcanic carbon dioxide take place are also characterized by a some degree of permeability of the crust that often coincides with seismically active zones. Indeed, seismic data demonstrate the existence of a positive spatial correlation between gas discharges and extensional tectonic regimes and confirms that such processes would play a key role in creating pathways for the rising gases at micro- and macro-scales, increasing the rock permeability and connecting the deep crust to the earth surface. Therefore, the identification and the geometric characterization of the CO2-permeable active faults is fundamental, not only for the definition of the seismic-active zone geometry, but also for the understanding of the processes that govern the flow of fluids along the damage zone that convey the gases towards the surface. In this framework, numerical simulations of fluid flow in three-dimensional faulted models can help to identify the primary control parameters of fault-related fluid flow, their interactions, and to model the temporal evolution of the investigated system. In this work, we present the results of a numerical simulation of CO2 flow along an active fault in the Ciorlano area of Matese Ridge (Southern Apennines, Italy), which recent accurate geological and geochemical analyses classify as the area with the highest non-volcanic natural emissions of CO2 ever measured on Earth (Ascione et al., 2018).

Understanding the behavior and the evolution of hydrothermal systems is of great interest for both scientific and commercial purposes, such as volcanic hazard assessment and geothermal energy exploitation. To this aim, a novel approach based on continuous magnetotelluric (MT) data is proposed for characterizing and monitoring hydrothermal systems. To test the effectiveness of the proposed approach, a sensitivity analysis has been performed by simulating different evolution scenarios of a hydrothermal system and calculating the MT response at different time intervals corresponding to different stages of the system dynamics. The study proved to be essential for understanding the degree of sensitivity of the MT method to changes of the hydrothermal system with reference to its possible temporal evolutions.

On August 21, 2017, at 18:57 UTC, an earthquake of MD 4.0 occurred in Casamicciola, district of Ischia island at about 2 km depth. In volcanic areas, such as the Ischia Island, the precise localization of the earthquakes requires specific velocity models, both for the wide lithological variability and for the high geothermal gradient. These models are available, for example, for the Vesuvius and for the Campi Flegrei areas, but not for the Island of Ischia because they need to use the local seismicity. Since 1999, at least 78 earthquakes have been recorded on Ischia (updated to 21 February 2018) and have been localized using the model used for the Campi Flegrei, on the basis of the similar geological and volcanological context of the two volcanoes. Therefore, the aim of this work is the definition of average 1-D shear-wave velocity model of the shallower crust of Ischia using ambient noise array techniques and spectral ratios evaluated on broad band seismic signals recorded by mobile and permanent networks deployed in the last year.

Monitoring hydrothermal systems is of crucial interest for different applications, such as volcanic hazard assessment and geothermal energy exploitation. In this work, the feasibility of using continuous magnetotelluric (MT) measurements for monitoring hydrothermal systems developing within active volcanoes is investigated. The MT method is indeed a good candidate for characterizing the dynamics of a volcano-hydrothermal system as it is suitable for deep exploration of the subsoil (from one hundred meters to hundreds of kilometers) in terms of electrical resistivity values, which are strongly sensitive to variations in temperature and underground fluids distributions. To test the proposed methodology, a reliable model of the Campi Flegrei (Southern Italy) volcanic complex based on geochemical and geophysical data is built and a sensitivity study is carried out by changing the fluid flow rate of the hydrothermal source and the permeability distribution of the system. In particular, for each evolution scenario the MT sensitivity has been studied by evaluating the time intervals needed for observing significant resistivity variations. The simulations have shown that the MT monitoring is much more sensitive to changes in rock permeability rather than in the fluid flow rate emitted by the source. In general, time intervals not useful for volcano monitoring purposes (i.e., longer than 10 years) are found if only changes in fluid flow rate are assumed to govern the hydrothermal system dynamics. Conversely, by increasing the permeability of the hosting rocks up to about one order of magnitude, consistent resistivity variations are observed over a period ranging from one year and a half to three months. Such findings are promising and encourage the use of the continuous MT measurements in active volcano-hydrothermal areas.

We study the statistical features of eruptive events causing the emptying of a closed magma chamber by using a discrete dynamical system where magma spreads through self- organized fracture networks. Specifically, the complex interactions between magma and rock are modelled by means of three dynamical variables that, respectively, control the occurrence of self-organized crack networks, the magma diffusion and the formation of high-density dikes, which magma uses to eventually reach the surface. In particular, the numerical analysis has been carried out for investigating the main features of erupted volumes and repose times statistical distributions. Interestingly, the model predicts that erupted magma is, generally, a mixture of magma that has continuously stopped during the whole ascent path from the chamber to the surface, except for eruptions above a given size threshold, for which it is possible to distinguish two dominant components deriving from specific depth ranges. Such a finding can provide a theoretical framework for the general feature of many volcanic eruptions whose deposits are characterized by two different magmas. Furthermore, in the distribution of repose times a timescale separation between short and long more probable repose times is found, which increases by deepening of the magma chamber. The identification of two different types of repose times suggests the presence of different patterns, which could help the understanding of the processes responsible for different eruptive regimes.

In the last decades, an increasing number of global optimization algorithms has been proposed to solve geophysical inverse problems. Indeed, an inverse problem can be posed as an optimization problem where the function to be optimized, usually called objective function, misfit function or fitness, provides an estimate of the difference between observed data and synthetic data computed by a trial model. In the framework of probabilistic global optimization methods, some algorithms use statistical distributions inspired by physical processes to get suggestion on which solution candidate has to be tested next, as for example the Simulated Annealing algorithms, which select the next solution candidate according to the Boltzmann probability factor of atom configurations of cooling metals. Other algorithms, such as the Genetic Algorithms, are instead inspired by Darwinian evolution processes and treat solution candidates as individuals that compete in a virtual environment controlled by the genetic mechanisms of mutation, reproduction and crossover. In this work, we present and discuss some applications of a new hybrid global optimization algorithm, GPA, recently proposed by the authors for quantitative interpretations of potential field data. The proposed approach includes a mutation operator in a controlled random search algorithm and its effectiveness has been proved on several synthetic and field data concerning single self-potential (SP) anomalies. Here, the results of a numerical study focused on multiple self-potential anomalies are shown for two of the main application fields of the SP method, i.e. for volcanic and soil contamination risk.

Suitable estimation of the land subsidence is crucial in deltas and coastal areas, where the climate variability effects (e.g., frequent and intense rain storms, peaks in river discharge and sea level fluctuations), coupled with natural or anthropogenic land sinking, represent serious factors of inundation risk. Nowadays, continuous GNSS (Global Navigation Satellite Systems) networks have become precision monitoring tools of the ground displacement. Customarely GNSS site-position time series exhibit a linear trend plus seasonal oscillations of annual and semi-annual periods. These periodic variations may be due to the joint contributions of surface mass redistribution (atmosphere, ocean, snow and soil moisture), frequently masked by the superposition of several correlated or uncorrelated noise sources. These signals have to be recognised and properly modelled in order to estimate the vertical ground lowering. Several authors investigate the seasonal component by using the “peering approach”, which is based on the comparison between the joint contribution of established individual geophysical sources (not removed during the data processing phase) and the observed seasonal variations. This approach allows to quantify influence, distribution and magnitude of the individual sources and to understand the main processes affecting the geodetic time series. Differently from this approach, we propose a procedure based on two steps: multi-disciplinary and multi-methodological comparative analyses are first performed for selecting the physical mechanism (individual source) that better explain the seasonal signals clearly exhibited by the GPS time series. Then, a physically-based model is used for enhancing the extraction of the geodetic trend and thus estimating the geodetic velocity without seasonal oscillations. The proposed approach is applied to the Codigoro test site (southern part of the Po Delta – Northern Italy), which is an area historically affected by both anthropogenic and natural subsidence and influenced by climatic changes.

In the last decades, the magnetotelluric (MT) method has been proved to be a useful geophysical tool in different contexts, from geothermal reservoir characterization to crustal structures studies. Nevertheless, the MT method is very sensitive to the presence of noise. Indeed, as the method is based on the measurement of both the electric and magnetic components of the natural electromagnetic (EM) field, it fails when these components are affected by noises of different nature. In particular, in industrialized and urbanized context, the MT time series could be strongly affected by man-made noise and, as a consequence, the impedance tensor estimates, given by the ratio between the electric and magnetic components of the MT field, could be unreliable. To improve the reliability of these estimates, most of the proposed approaches rely on the robust evaluation of the impedance tensor as well as on the use of remote reference MT stations or on the combination of both approaches. However, these methods are not always effective. The robust methods fail when most of the data are affected by noise, giving as result a biased impedance tensor, while the remote reference approach is ineffective when the noise is correlated between reference and local MT station. In recent years, alternative procedures have been proposed to obtain reliable estimates of the MT impedance tensor. In the present work, a different approach based on the use of Discrete Wavelet Transform (DWT) and Self-Organizing Map (SOM) neural network analysis is proposed for improving the magnetotelluric impedance tensor estimates. The approach has been tested by changing type, level and window length of the noise affecting MT time series. Furthermore, in order to identify the most reliable apparent resistivity and phase values among the different impedance tensors clusters provided by the SOM analysis for each analyzed period, a selection criterion is provided and tested on synthetic and field MT data.

The structure of a volcanic edifice depends on composition, volume of erupted magma, and mechanism of eruption. In particular, pressure variations with depth due to density variations of the volcanic rocks are crucial for magma degassing processes as well as buoyancy mechanisms. In this paper, we analyze the effects of three different pressure profiles with depth on the probability of occurrence of simulated eruptive events. We describe the dynamics of magma ascent by means of a time dependent Self-Organized-Criticality field, which controls the opening of crack networks through which discrete magma batches are allowed to rise. We find a characteristic power-law behavior for the number of eruptions with erupted volume in all considered cases. As concerns the probability of occurrence of an eruptive event with a given percentage of gas losses, we find that extreme events, i.e., events with the lowest percentage of gas losses, are more likely to occur if a step function is used to describe the relationship between rock density and depth.

The immunocompromised district is a novel concept referring to a site in which there is an obstacle to the normal trafficking of immunocompetent cells through lymphatic channels, or an interference with the signals that the neuropeptides and neurotransmitters, released by peripheral nerves, send to cell membrane receptors of immunocompetent cells. The connection between immunocompromised district and benign proliferative diseases has never been considered. Lymphostasis and paraplegia have a common denominator: the induction of a regional immunocompromise. There is a well-founded suspicion that papillomatosis cutis ‘lymphostatica’ in patients affected both by lymphostasis and with paraplegia could be hinged upon this common mechanism. The altered production of neuroimmunomediators, cytokines and growth factors could explain the genesis of the hyperproliferative stimulus underlying the appearance of a verrucous proliferation like papillomatosis cutis.

Gli obiettivi di questo lavoro sono quelli di ricostruire, con metodologie geofisiche integrate, le principali geometrie tettoniche ed idrogeologiche del territorio di Panza nell'isola di Ischia. La zona è stata scelta in quanto caratterizzata da un'intensa attività idrotermale e deformativa connessa con la presenza di un reservoir geotermico.