scholarly journals Ground Deformation Detected by Permanent Tiltmeters on Mt. Etna Summit: The August 23-26, 2018, Strombolian and Effusive Activity Case

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Salvatore Gambino ◽  
Marco Aloisi ◽  
Giuseppe Di Grazia ◽  
Giuseppe Falzone ◽  
Angelo Ferro ◽  
...  
Keyword(s):  
Ground Deformation ◽  
Volcanic Tremor ◽  
Mount Etna ◽  
Etna Volcano ◽  
Strombolian Activity ◽  
Summit Area ◽  
Effusive Activity ◽  
Ground Deformations ◽  
Mt Etna ◽  
Set Up

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.

Deploying and operating an Absolute Quantum Gravimeter on the summit of Mount Etna volcano

2021 ◽  
Author(s):  
Daniele Carbone ◽  
Laura Antoni-Micollier ◽  
Filippo Greco ◽  
Jean Lautier-Gaud ◽  
Danilo Contrafatto ◽  
...  
Keyword(s):  
Gravity Data ◽  
Volcanic Tremor ◽  
Mount Etna ◽  
Quality Data ◽  
Etna Volcano ◽  
High Quality ◽  
Absolute Gravimetry ◽  
Superconducting Gravimeters ◽  
Mt Etna ◽  
Absolute Quantum

<p>The NEWTON-g project [1] proposes a paradigm shift in terrain gravimetry to overcome the limitations imposed by currently available instrumentation. The project targets the development of an innovative gravity imager and the field-test of the new instrumentation through the deployment at Mount Etna volcano (Italy). The gravity imager consists in an array of MEMS-based relative gravimeters anchored on an Absolute Quantum Gravimeter [2].<br>The Absolute Quantum Gravimeter (AQG) is an industry-grade gravimeter measuring g with laser-cooled atoms [3]. Within the NEWTON-g project, an enhanced version of the AQG (AQGB03) has been developed, which is able to produce high-quality data against strong volcanic tremor at the installation site.<br>After reviewing the key principles of the AQG, we present the deployment of the AQGB03 at the Pizzi Deneri (PDN) Volcanological Observatory (North flank of Mt. Etna; 2800 m elevation; 2.5 km from the summit active craters), which was completed in summer 2020. We then show the demonstrated measurement performances of the AQG, in terms of sensitivity and stability. In particular, we report on a reproducible sensitivity to gravity at a level of 1 μGal, even during intense volcanic activity.<br>We also discuss how the time series acquired by AQGB03 at PDN compares with measurements from superconducting gravimeters already installed at Mount Etna. In particular, the significant  correlation with gravity data collected at sites 5 to 9 km away from PDN proves that effects due to bulk mass sources, likely related to volcanic processes, are predominant over possible local and/or instrumental artifacts.<br>This work demonstrates the feasibility to operate a free-falling quantum gravimeter in the field, both as a transportable turn-key device and as a drift-free monitoring device, able to provide high-quality continuous measurements under harsh environmental conditions. It paves the way to a wider use of absolute gravimetry for geophysical monitoring.</p><p>[1] www.newton-g.com</p><p>[2] D. Carbone et al., “The NEWTON-g Gravity Imager: Toward New Paradigms for Terrain Gravimetry”, Front. Earth Sci. 8:573396 (2020)</p><p>[3] V. Ménoret et al., "Gravity measurements below 10−9 g with a transportable absolute quantum gravimeter", Nature Scientific Reports, vol. 8, 12300 (2018)</p>

scholarly journals Finite element analysis of ground deformation due to dike intrusion with applications to Mt. Etna volcano

2009 ◽  
Vol 47 (5) ◽  
Author(s):  
A. Occhipinti Amato ◽  
M. Elia ◽  
A. Bonaccorso ◽  
G. La Rosa
Keyword(s):  
Ground Deformation ◽  
Near Field ◽  
Elastic Half Space ◽  
Etna Volcano ◽  
Element Analysis ◽  
Dike Intrusion ◽  
Dislocation Models ◽  
Mt Etna ◽  
Realistic Topography ◽  
2001 Eruption

A 2D finite elements study was carried out to analyse the effects caused by dike intrusion inside a heterogeneous medium and with a realistic topography of Mt. Etna volcano. Firstly, the method (dimension domain, elements type) was calibrated using plane strain models in elastic half-spaces; the results were compared with those obtained from analytical dislocation models. Then the effects caused both by the topographic variations and the presence of multi-layered medium on the surface, were studied. In particular, an application was then considered to Mt. Etna by taking into account the real topography and the stratification deduced from seismic tomography. In these conditions, the effects expected by the dike, employed to model the 2001 eruption under simple elastic half-space medium conditions, were computed, showing that topography is extremely important, at least in the near field.

scholarly journals The coupling between very long period seismic events, volcanic tremor, and degassing rates at Mount Etna volcano

2013 ◽  
Vol 118 (9) ◽  
pp. 4910-4921 ◽  
Author(s):  
Luciano Zuccarello ◽  
Michael R. Burton ◽  
Gilberto Saccorotti ◽  
Christopher J. Bean ◽  
Domenico Patanè
Keyword(s):  
Volcanic Tremor ◽  
Mount Etna ◽  
Seismic Events ◽  
Etna Volcano ◽  
Long Period

scholarly journals Clustering activity at Mt Etna based on volcanic tremor: A case study

2021 ◽  
Author(s):  
Giuseppe Nunnari
Keyword(s):  
Machine Learning ◽  
Volcanic Activity ◽  
Roc Curve ◽  
Volcanic Tremor ◽  
Machine Learning Algorithms ◽  
Etna Volcano ◽  
Mt Etna ◽  
Geophysical Signal

AbstractThis paper deals with the classification of volcanic activity into three classes, referred to as Quite, Strombolian and Paroxysm. The main purpose is to give a measure of the reliability with which such a classification, typically carried out by experts, can be performed by Machine Learning algorithms, by using the volcanic tremor as a feature. Both supervised and unsupervised methods are considered. It is experimentally shown that at least the Paroxysm activity can be reliably classified. Performances are rigorously assessed, in comparison with the classification made by expert volcanologists, in terms of popular indices such as the f1-score and the Area under the ROC curve (AuC). The work is basically a case study carried out on a dataset recorded in the area of the Mt Etna volcano. However, as volcanic tremor is a geophysical signal widely available, considered methods and strategies can be easily applied to similar volcanic areas.

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