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  • Articles  (16)
  • 04.08. Volcanology  (13)
  • Mt. Etna
  • Open Access
  • Elsevier B.V.  (8)
  • Agu  (4)
  • American Chemical Society (ACS)
  • HTWK Leipzig - OA-Hochschulverlag
  • MDPI Publishing
  • Springer Nature
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  • 1
    Publication Date: 2024-06-13
    Description: A detailed study of past eruptive activity is crucial to understanding volcanic systems and associated hazards. We present a meticulous stratigraphic analysis, a comprehensive chronological reconstruction, thorough tephra mapping, and a detailed analysis of the interplay between primary and secondary volcanic processes of the post-900 AD activity of La Fossa caldera, including the two main systems of La Fossa volcano and Vulcanello cones (Vulcano Island, Italy). Our analyses demonstrate how the recent volcanic activity of La Fossa caldera is primarily characterized by effusive and Strombolian activity and Vulcanian eruptions, combined with sporadic sub-Plinian events and both impulsive and long-lasting phreatic explosions, all of which have the capacity to severely impact the entire northern sector of Vulcano island. We document a total of 30 eruptions, 25 from the La Fossa volcano and 5 from Vulcanello cones, consisting of ash to lapilli deposits and fields of ballistic bombs and blocks. Volcanic activity alternated with significant erosional phases and volcaniclastic re-sedimentation. Large-scale secondary erosion processes occur in response to the widespread deposition of fine-grained ash blankets, both onto the active cone of La Fossa and the watersheds conveying their waters into the La Fossa caldera. The continuous increase in ground height above sea level, particularly in the western sector of the caldera depression where key infrastructure is situated, is primarily attributed to long-term alluvial processes. We demonstrate how a specific methodological approach is key to the characterization and hazard assessment of low-to-high intensity volcanic activity, where tephra is emitted over long time periods and is intercalated with phases of erosion and re-sedimentation.
    Description: Open access funding provided by Istituto Nazionale di Geofisica e Vulcanologia within the CRUI-CARE Agreement.
    Description: Published
    Description: 47
    Description: OSV2: Complessità dei processi vulcanici: approcci multidisciplinari e multiparametrici
    Description: JCR Journal
    Keywords: Active caldera; Aeolian archipelago; Historical eruptions; Island of Vulcano; Tephra; Volcano stratigraphy ; 04.08. Volcanology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
    Publication Date: 2023-02-07
    Description: Objective: To study the blood levels of selected trace elements (TE) in Multiple Sclerosis (MS) patients living in high-incidence cluster areas in the Etna volcano region. Methods: MS patients living in the province of Catania have been retrospectively enrolled among those followed by the Neurologic Clinic of the AOU Policlinico “G. Rodolico-San Marco” who had the disease onset between 2005 and 2020.Aserumsample was used for the determination of TE levels (As,Cd, Cr, Cu, Fe, Mg, Mn, Ni, Se, Zn). All the analyses have been conducted with an ICPMS with the standard addition technique, previous digestion of the samples with nitric acid. MS patients living the high incidence clusters were frequency matched with MS patients living outside the clusters. Comparisons of TE across the groups were conducted using the Mann-Whitney test. Results: A total of 86 (48 women; 55.8%) MS patients was recruited, with a mean age of 41.6±13.1 years, a mean disease duration of 2.0±2.6 years and a mean Expanded Disability Status Scale of 2.3±1.7. Of these patients, 40 belonged to high incidence clusters and 46 were outside the clusters. No differences were found in demographic characteristics between the groups. Concerning TE, we found a significant higher concentration of Mn in incluster patients (6.7±16.6 μg/L vs 2.5±5.9 μg/L). Discussion: Several environmental factors may modulate the pathogenesis of the disease, and among them TE play an important role. Our findings suggest that Manganese, which has several toxic effects, might contribute to the higher incidence of MS previously observed in a cluster of communalities in the south-eastern flank of the Etna volcano, where volcanic ashes rich in TE usually fall due to the prevailing winds. Conclusions: Exposition to high levels of Mn could be a cofactor in the pathogenesis of MS.
    Description: Published
    Description: Milano
    Description: 6A. Geochimica per l'ambiente e geologia medica
    Keywords: Multiple Sclerosis ; Mt. Etna ; 05. General
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: Conference paper
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  • 3
    Publication Date: 2022-02-11
    Description: Magmatism accompanies rifting along divergent plate boundaries, although its role before continental breakup remains poorly understood. For example, the magma-assisted Northern Main Ethiopian Rift (NMER) lacks current volcanism and clear tectono-magmatic relationships with its contiguous rift portions. Here we define its magmatic behaviour, identifying the most recent eruptive fissures (EF) whose aphyric basalts have a higher Ti content than those of older monogenetic scoria cones (MSC), which are porphyritic and plagioclase-dominated. Despite these differences, calculations highlight a similar parental melt for EF and MSC products, suggesting only a different evolutionary history after melt generation. While MSC magmas underwent a further step of storage at intermediate crustal levels, EF magmas rose directly from the base of the crust without contamination, even below older polygenetic volcanoes, suggesting rapid propagation of transcrustal dikes across solidified magma chambers. Whether this recent condition in the NMER is stable or transient, it indicates a transition from central polygenetic to linear fissure volcanism, indicative of increased tensile conditions and volcanism directly fed from the base of the crust, suggesting transition towards mature rifting.
    Description: Published
    Description: 21821
    Description: 2V. Struttura e sistema di alimentazione dei vulcani
    Description: JCR Journal
    Keywords: 04.08. Volcanology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 4
    Publication Date: 2022-10-28
    Description: From the 2010s on, pattern classification has proven an effective method for flagging alerts of volcano unrest before eruptive activity at Mt. Etna, Italy. The analysis has been applied online to volcanic tremor data, and has supported the surveillance activity of the volcano that provides timely information to Civil Protection and other authorities. However, after declaring an alert, no one knows how long the volcano unrest will last and if a climactic eruptive activity will actually begin. These are critical aspects when considering the effects of a prolonged state of alert. An example of longstanding unrest is related to the Christmas Eve eruption in 2018, which was heralded by several months of almost continuous Strombolian activity. Here, we discuss the usage of thresholds to detect conditions leading to paroxysmal activity, and the challenges associated with defining such thresholds, leveraging a dataset of 52 episodes of lava fountains occurring in 2021. We were able to identify conservative settings regarding the thresholds, allowing for an early warning of impending paroxysm in almost all cases (circa 85% for the first 4 months in 2021, and over 90% for the whole year). The chosen thresholds also proved useful to predict that a paroxysmal activity was about to end. Such information provides reliable numbers for volcanologists for their assessments, based on visual information, which may not be available in bad weather or cloudy conditions.
    Description: Project IMPACT (A multidisciplinary Insight on the kinematics and dynamics of Magmatic Processes at Mt. Etna Aimed at identifying preCursor phenomena and developing early warning sysTems). IMPACT belongs to the Progetti Dipartimentali INGV [DIP7], https://progetti.ingv.it/index.php/it/progetti-dipartimentali/vulcani/impact#informazioni-sul-progetto.
    Description: Published
    Description: 17895
    Description: 4V. Processi pre-eruttivi
    Description: JCR Journal
    Keywords: Volcanic tremor ; Volcano monitoring ; Pattern recognition ; Self Organizing maps ; Fuzzy clustering ; Mt. Etna ; 04.06. Seismology ; 04.08. Volcanology ; 05.01. Computational geophysics
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 5
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    Elsevier B.V.
    Publication Date: 2021-02-01
    Description: In supervised classification, we search criteria allowing us to decide whether a sample belongs to a certain class of patterns. The identification of such decision functions is based on examples where we know a priori to which class they belong. The distinction of seismic signals, produced from earthquakes and nuclear explosions, is a classical problem of discrimination using classification with supervision. We move on from observed data—signals originating from known earthquakes and nuclear tests—and search for criteria on how to assign a class to a signal of unknown origin. We begin with Principal Component Analysis (PCA) and Fisher's Linear Discriminant Analysis (FLDA), identifying a linear element separating groups at best. PCA, FLDA, and likelihood-based approaches make use of statistical properties of the groups. Considering only the number of misclassified samples as a cost, we may prefer alternatives, such as the Multilayer Perceptrons (MLPs). The Support Vector Machines (SVMs) use a modified cost function, combining the criterion of the minimum number of misclassified samples with a request of separating the hulls of the groups with a margin as wide as possible. Both SVMs and MLPs overcome the limits of linear discrimination. A famous example for the advantages of the two techniques is the eXclusive OR (XOR) problem, where we wish to form classes of objects having the same parity—even, e.g., (0,0), (1,1) or odd, e.g., (0,1), (1,0). MLPs and SVMs offer effective methods for the identification of nonlinear decision functions, allowing us to resolve classification problems of any complexity provided the data set used during earning is sufficiently large. In Hidden Markov Models (HMMs), we consider observations where their meaning depends on their context. Observations form a causal chain generated by a hidden process. In Bayesian Networks (BNs) we represent conditional (in)dependencies between a set of random variables by a graphical model. In both HMMs and BNs, we aim at identifying models and parameters that explain observations with a highest possible degree of probability.
    Description: Published
    Description: 33-85
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Keywords: pattern recognition ; supervised learning ; Support Vector Machines ; Multilayer Perceptrons ; Hidden Markov Models ; Bayesian Networks ; 04.04. Geology ; 04.06. Seismology ; 04.07. Tectonophysics ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 6
    Publication Date: 2021-02-01
    Description: Patterns and objects are described by a variety of characteristics, namely features and feature vectors. Features can be numerical, ordinal, and categorical. Patterns can be made up of a number of objects, such as in speech processing. In geophysics, numerical features are the most common ones and we focus on those. The choice of appropriate features requires a priori reasoning about the physical relation between patterns and features. We present strategies for feature identification and procedures suitable for pattern recognition. In time series analysis and image processing, the direct use of raw data is not feasible. Procedures of feature extraction, based on locally encountered characteristics of the data, are applied. Here we present the problem of delineating segments of interest in time series and textures in image processing. In transformations, we “translate” our raw data to a form suitable for learning. In Principal Component Analysis, we rotate the original features to a system of uncorrelated variables, limiting redundancy. Independent Component Analysis follows a similar strategy, transforming our data into variables independent of each other. Fourier transform and wavelet transform are based on the representation of the original data as a series of basis functions—sines and cosines or finite-length wavelets. Redundancy reduction is achieved considering the contributions of the single basis functions. Even though a large number of features help to solve a classification problem, feature vectors with high dimensions pose severe problems. Besides the computational burden, we encounter problems known under the term “curse of dimensionality.” The curse of dimensionality entails the necessity of feature selection and reduction, which includes a priori considerations as well as redundancy reduction. The significance of features may be evaluated with tests, such as Student’s t or Hotelling's T2, and, in more complex problems, with cross-validation methods.
    Description: Published
    Description: 3-13
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Keywords: pattern recognition ; objects ; features ; 04.04. Geology ; 04.06. Seismology ; 04.07. Tectonophysics ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 7
    Publication Date: 2021-01-07
    Description: https://www.sciencedirect.com/science/article/abs/pii/S0012821X20303897
    Description: Published
    Description: 116445
    Description: 2V. Struttura e sistema di alimentazione dei vulcani
    Description: JCR Journal
    Keywords: 3D model ; multi-source ; elastic medium ; ground deformation ; 04. Solid Earth ; 04.08. Volcanology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
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  • 8
    Publication Date: 2021-02-01
    Description: In this chapter, we deal with a posterior analysis of supervised and unsupervised learning techniques. Concerning supervised learning, we discuss methods of cross-validation and assessment of uncertainty of tests by means of the “Receiver Operation Curve” and the “Kappa-Statistics.” We show the importance of appropriate target information. Furthermore, features are critical; when they are not properly chosen, they fail to describe objects in a unique way. A critical attitude is mandatory to validate the success of an application. A high score of success does not automatically mean that a method is truly effective. At the same time, users should not despair when the desired success is not achieved. A posteriori analysis on the reasons for an apparent failure may provide useful insights into the problem. Targets may not be appropriately defined, features can be inadequate, etc. Problems can be often fixed by adjusting a few choices; sometimes a change of strategy may be necessary to improve results. In unsupervised learning, we ask whether the structures revealed in the data are meaningful. Cluster analysis offers rules giving formal answers to this question; however, such rules are not generally applicable. In some cases, a heuristic approach may be necessary.
    Description: Published
    Description: 237-259
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Keywords: pattern recognition ; a posteriori analysis ; supervised learning ; unsupervised learning ; cross validation ; assessment of uncertainty ; Receiver Operation Curve ; Kappa-Statistics ; 04.04. Geology ; 04.06. Seismology ; 04.07. Tectonophysics ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 9
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    Elsevier B.V.
    Publication Date: 2021-02-01
    Description: Unsupervised learning is based on the definition of an appropriate metrics defining the similarity of patterns. On the basis of the metrics, we form groups or clusters of patterns following various strategies. In partitioning cluster analysis, we form disjoint clusters. Being faced with data, where clusters still exhibit heterogeneities or subclusters, we may adopt the strategy of hierarchical clustering, which leads to the generation of the so-called dendrograms. In the partitioning strategy, we choose a priori the number of clusters we wish to form, whereas in the hierarchical strategy, the number of clusters depends on the resolution we want to have. Density-based clustering considers local structures of a data set. We consider a unit volume in our data space and derive the density of samples within this volume. Moving toward neighboring volumes, we verify whether the number of samples has dropped below a threshold. If this is the case, we identify a heterogeneity, otherwise we join the neighboring volumes to a common cluster. Self-Organizing Maps (SOMs) provide a way of representing multidimensional data in much lower dimensional spaces than the original data set. The process of reducing the dimensionality of vectors is essentially a data compression technique known as vector quantization. The SOM technique creates a network that stores information in a way that it maintains the topological relationships within the patterns of the data set. Each node of the network represents a number of patterns. Assigning a color code to the nodes, the representation of pattern characteristics with high-dimensional feature vectors becomes extremely effective.
    Description: Published
    Description: 87-124
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Keywords: pattern recognition ; unsupervised learning ; cluster analysis ; Density-based clustering ; Self-Organizing Maps ; 04.04. Geology ; 04.06. Seismology ; 04.07. Tectonophysics ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 10
    Publication Date: 2021-02-01
    Description: This chapter demonstrates how Unsupervised Learning can be applied in Geophysics. It starts with an example of clustering seismic spectra obtained on Stromboli volcano. K-means clustering as well as clustering using the Adaptive Criterion are applied. The latter criterion is preferred as it better matches the statistical characteristics of the data. Clusters show close relation to the state of volcanic activity. Density based clustering reveals groups whose hulls can be of irregular shape. This makes the method attractive, among others, for the identification of structural elements in geology, which often do not have a simple geometry. An example application is discussed considering the distribution of earthquake locations on Mt Etna, which clearly evidence structures already identified by other, independent evidences. Using SOM we aim at data reduction and effective graphical visualization. In an example for climate data we demonstrate the application of SOM for zoning purposes. Besides, the temporal evolution of spectral seismic data recorded on Mt Etna can be effectively monitored using SOM. We further illustrate the use of SOM for directional data, which can be handled best using a toroidal sheet geometry. We discuss this using a data set of seismic moment tensors of Mediterranean earthquakes.
    Description: Published
    Description: 189-234
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Keywords: pattern recognition ; unsupervised learning ; Density based clustering ; Stromboli ; earthquakes ; volcanic activity ; structural data ; seismic moment tensors ; 04.04. Geology ; 04.06. Seismology ; 04.07. Tectonophysics ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 11
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    Elsevier B.V.
    Publication Date: 2021-02-01
    Description: In this chapter, we present scripts and programs that accompany this book. Five MATLAB scripts regard simple examples related to supervised learning, that is, linear discrimination, the perceptron, support vector machines, and hidden Markov models. Seven scripts are devoted to unsupervised learning, such as K-means and fuzzy clustering, agglomerative clustering, density-based clustering, and clustering of patterns where features are correlated. These scripts provide a starting point for the reader, who can adjust and modify the codes with respect to proper needs. Besides, we provide sources and executables of programs that can be readily applied to larger and more complex datasets. These programs regard supervised learning using multilayerperceptron and support vector machines. KKAnalysis is a toolbox for unsupervised learning and offers various options of clustering and the use of self-organizing maps. The programs offer graphical user interfaces (GUI) to facilitate their use and create both graphical and alphanumeric output that can be used in further processing steps. The programs come along with real-world datasets that are also discussed in the example applications presented in various chapters of the book. Other propaedeutic material can be found in a folder called “miscellaneous.”
    Description: Published
    Description: 261-313
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Keywords: pattern recognition ; software manuals ; MATLAB scripts ; 04.04. Geology ; 04.06. Seismology ; 04.07. Tectonophysics ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 12
    Publication Date: 2021-02-15
    Description: This chapter presents applications of supervised learning in various geophysical disciplines, being them seismology, geodesy, magnetism, and others. For all examples, we provide a brief introduction to the geophysical background. Practical aspects, such as normalization issues and feature selection, are discussed. A posteriori considerations shed light on the geophysical problem, such as the importance of model parameters in regression, the possible nonuniqueness in inversion, and flaws in the definition of targets. We demonstrate multilayer perceptrons (MLPs) as classifiers of seismic waveforms. Besides, we show how the use of MLP is straightforward in the context of inversion of various kinds of data, for example, seismic, geodetic, and magnetic. Regression with MLP is applied to magnetotelluric and seismic data. Multiclass classification with support vector machine (SVM) is discussed for infrasound waveforms and volcanic rocks using geochemical characteristics. We introduce the use of SVM in the context of regression, which is formally less immediate than for MLP, but yields good results. An example deals with empirical ground motion estimation during earthquakes. In hidden Markov models and Bayesian networks one considers the interrelation between observations rather than single patterns. We show their benefits in various applications, from seismic waveform classification aimed at the forecast of volcanic unrest up to their use in tsunami early-warning systems.
    Description: Published
    Description: 127-187
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Keywords: pattern recognition ; supervised learning ; multilayer perceptrons ; seismic data ; magnetotelluric data ; infrasound waveforms ; volcanic rocks ; geochemical characteristics ; 04.04. Geology ; 04.06. Seismology ; 04.07. Tectonophysics ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 13
    Publication Date: 2020-03-24
    Description: An edited version of this paper was published by AGU. Copyright (2019) American Geophysical Union
    Description: Tectonic and magmatic activity may couple at volcanic arcs, even though any relationship is less defined in smaller arcs, experiencing limited activity. Here we use gas geochemistry data collected during the 2011–2012 unrest at Santorini (Greece) to understand better the dynamics of the Aegean Volcanic Arc with regard to its tectonic setting. Since the most recent eruption in 1950 and before the unrest, minor seismicity and CO2 degassing (mainly from the fumaroles of Nea Kameni islet) were observed at Santorini. On January 2011, anomalous seismicity along the NE‐SW trending Kameni Line was accompanied by an inflation north of Nea Kameni. Fumarolic gas composition changed and gas release notably increased. We carried out geochemical study on both Kameni and Thera islands from January 2012 to June 2013. We repeated surveys of diffuse soil CO2 degassing and of in‐soil gas concentration, and we analyzed fumaroles and gas dissolved in thermal waters for chemical and isotopic composition. In agreement with previous studies, our geochemical data, particularly the diffuse soil CO2 flux increase, the increase of H2 content, and of CO2/CH4 and 3He/4He ratios in fumarolic gases, support geophysical data in indicating that unrest was associated with the emplacement of new mafic magma. This unrest had limited effect on the regional setting, with gas emissions focusing along the regional NE‐SW structures, without triggering by any seismic event, conversely to the 1950 eruption, which probably occurred in a frame of general tectonic reorganization of the Aegean microplate.
    Description: Published
    Description: 1033-1049
    Description: 2V. Struttura e sistema di alimentazione dei vulcani
    Description: 4V. Processi pre-eruttivi
    Description: 6V. Pericolosità vulcanica e contributi alla stima del rischio
    Description: JCR Journal
    Keywords: Extensive and systematic geochemical surveys followed the anomalous degassing during Santorini unrest, both in the caldera center and on the inner caldera walls; ; Gas ratios and isotopic composition indicate deep mafic magma refilling into the shallow dacitic plumbing system; ; Unrest has limited apparent relations with the longer-term tectonic evolution of the Arc, conversely to the 1950 eruption ; 04.08. Volcanology ; 04.06. Seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
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  • 14
    Publication Date: 2021-06-25
    Description: In a Strombolian volcanic eruption, bursting of a pressurized gas pocket produces and accelerates a mixture of gas and pyroclasts along a conduit and out of a vent. While mixture ejection at the vent is the subject of direct geophysical measurements, and a key to eruption understanding, the dynamics of how the mixture moves in the conduit are not observable and only partly understood. Here, we use analog, transparent shock tube experiments to study the dynamics of gas and particles under fast gas decompression in a vertical tube. Maximum particle exit velocity increases linearly with increasing energy (pressure times volume) of the pressurized gas, and, subordinately, with decreasing particle size and depth in the tube. Particles, initially at rest, are at first accelerated and dispersed in the conduit by the expanding gas. When the gas decelerates or even reverts its motion due to pressure changes in the tube, the particles, moving under their inertia, are then decelerated by the gas drag. Deceleration lasts longer for lower initial gas energy and for deeper particle starting position. Experiments and eruptions share two key vent ejection dynamics: 1) particles exit the vent already decelerating, and 2) the exit velocity of the particles decays over time following the same non-linear law. Friction with slower, or even back-flowing gas likely causes pyroclast deceleration in volcanic conduits during Strombolian explosions. Pyroclast deceleration, in turn, affects their exit velocity at the vent, as well as current estimates of the source depth of the explosions.
    Description: Published
    Description: e2019JB019182
    Description: 5V. Processi eruttivi e post-eruttivi
    Description: JCR Journal
    Keywords: Strombolian explosion ; volcanic conduit ; shock tube ; pyroclast ejection ; 04.08. Volcanology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
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  • 15
    Publication Date: 2017-04-04
    Description: We report here on the real-time measurement of CO2 and SO2 concentrations in the near-vent volcanic gas plume of Mount Etna, acquired by the use of a field portable gas analyzer during a series of periodic field surveys on the volcano’s summit. During the investigated period (September 2004 to September 2005), the plume CO2/SO2 ratio ranged from 1.9 to 10.8, with contrasting composition for Northeast and Voragine crater plumes. Scaling the above CO2/SO2 ratios by UV spectroscopy determined SO2 emission rates, we estimate CO2 emission rates from the volcano in the range 0.9–67.5 kt d 1 (average, 9 kt d 1). About 2 kt of CO2 were emitted daily on average during quiescent passive degassing, whereas CO2 emission rates from Etna’s summit were 10–40 times larger during the 2004–2005 effusive event (with a cumulative CO2 release of 3800 kt during the 6 months of the eruption). Such a syneruptive increase, ascribed to the replenishment of the shallow (〈6 km) volcanic plumbing system by CO2-rich (0.25 wt %) more primitive magmas, supports the potential of CO2 output rates as key parameters for volcanic hazard assessment.
    Description: Published
    Description: B09207
    Description: JCR Journal
    Description: reserved
    Keywords: carbon dioxide ; Mt. Etna ; 04. Solid Earth::04.04. Geology::04.04.12. Fluid Geochemistry
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
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  • 16
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    In:  Froger, J.-L., O. Merle, and P. Briole (2001), Active spreading and regional extension at Mount Etna imaged by SAR interferometry, Earth Planet. Sci. Lett., 187, 245–258. Gvirtzman, Z., and A. Nur (1999), The formation of Mount Etna as the consequence of slab rollback, Nature, 401, 782–785. Leslie, S. C., G. F. Moore, J. K. Morgan, and D. J. Hills (2002), Seismic stratigraphy of the frontal Hawaiian moat: Implications for sedimentary processes at the leading edge of an oceanic hotspot trace, Mar. Geol., 184, 143–162. Lundgren, P., F. Casu, M. Manzo, A. Pepe, P. Berardino, E. Sansosti, and R. Lanari (2004), Gravity and magma induced spreading of Mount Etna volcano revealed by satellite radar interferometry, Geophys. Res. Lett., 31, L04602, doi:10.1029/2003GL018736. Maramai, A., L. Graziani, G. Alessio, P. Burrato, L. Colini, L. Cucci, R. Nappi, A. Nardi, and G.Vilardo (2005), Near- and far-field survey report of the 30 December 2002 Stromboli (Southern Italy) tsunami, Mar. Geol., 215, 93– 106. Moore, J. G., D. A. Clague, R. T. Holcomb, P. W. Lipman, W. R. Normak, and M. E. Torresan (1989), Prodigious submarine landslides on the Hawaiian ridge, J. Geophys. Res., 94, 17,465–17,484. Morgan, J. K., F. M. Moore, J. Hills, and S. Leslie (2000), Overthrusting and sediment accretion along Kilauea’s mobile south flank, Hawaii: Evidence for volcanic spreading from marine seismic reflection data, Geology, 28, 667–670. Monaco, C., P. Tapponier, L. Tortorici, and P. Y. Gillot (1997), Late quaternary slip-rates on the Acireale-Piedimonte normal fault and tectonic origin of Mt. Etna (Sicily), Earth Planet. Sci. Lett., 147, 125– 139. Nicolich, R., M. Laigle, A. Hirn, L. Cernobori, and J. Gallart (2000), Crustal structure of the Ionian margin of Sicily: Etna volcano in the frame of regional evolution, Tectonophysics, 329, 121– 139. Romano, R., and C. Sturiale (1982), The historical eruptions of Mt. Etna (volcanological data), in Mt. Etna Volcano, edited by R. Romano, Mem. Soc. Geol. It., 23, 75–97. von Huene, R., C. R. Ranero, and P. Watts (2004), Tsunamigenic slope failure along Middle America Trench in two tectonic settings, Mar. Geol., 203, 303– 317. Yilmaz, O. (1987), Seismic data processing, Invest. Geophys., vol. 2, Soc. of Explor. Geophys., 562 pp., Tulsa, Okla.
    Publication Date: 2017-04-04
    Description: High resolution seismic data, we collected in the Ionian sea, reveal large submarine landslide deposits offshore from Mt. Etna (Italy), spatially consistent with the eastern flank collapse of this volcano. A large debris-avalanche deposit, we relate to the Valle del Bove scar, displays long offshore run-outs (till 20 km) and a volume of a few tens of cubic kilometres (16–21 km3). Other landslide deposits are also imaged, in particular a striking unique record of the relative timing of multiple submarine large slump events.
    Description: Published
    Description: L13302
    Description: JCR Journal
    Description: reserved
    Keywords: submarine landslides ; Mt. Etna ; 04. Solid Earth::04.04. Geology::04.04.04. Marine geology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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