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This paper addresses the classification of images depicting the eruptive activity of Mount Etna, captured by a network of ground-based thermal cameras. The proposed approach utilizes Convolutional Neural Networks (CNNs), focusing on pretrained models. Eight popular pretrained neural networks underwent systematic evaluation, revealing their effectiveness in addressing the classification problem. The experimental results demonstrated that, following a retraining phase with a limited dataset, specific networks such as VGG-16 and AlexNet, achieved an impressive total accuracy of approximately 90 % . Notably, VGG-16 and AlexNet emerged as practical choices, exhibiting individual class accuracies exceeding 90 % . The case study emphasized the pivotal role of transfer learning, as attempts to solve the classification problem without pretrained networks resulted in unsatisfactory outcomes. [ABSTRACT FROM AUTHOR]

This paper describes the successes and failures after 4 years of continuous operation of a network of sensors, communicating nodes, and gateways deployed on the Etna Volcano in Sicily since 2019, including a period of Etna intense volcanic activity that occurred in 2021 and resulted in over 60 paroxysms. It documents how the installation of gateways at medium altitude allowed for data collection from sensors up to the summit craters. Most of the sensors left on the volcanic edifice during winters and during this period of intense volcanic activity were destroyed, but the whole gateway infrastructure remained fully operational, allowing for a very fruitful new field campaign two years later, in August 2023. Our experience has shown that the best strategy for IoT deployment on very active and/or high-altitude volcanoes like Etna is to permanently install gateways in areas where they are protected both from meteorological and volcanic hazards, that is mainly at the foot of the volcanic edifice, and to deploy temporary sensors and communicating nodes in the more exposed areas during field trips or in the summer season. [ABSTRACT FROM AUTHOR]

On February 6, 2023, at 01 : 17 UTC, a M = 7.8 earthquake struck the southern area of Turkey near Gaziantep town and was followed by a second earthquake of M = 7.5 at 10 : 24 UTC with the epicenter in Elbistan city. Both events were associated with the Anatolian Fault System and have claimed over 50,000 victims, as reported by the Disaster and Emergency Management Authority, and caused serious damage in the regions of southern Turkey and northern Syria. Seismic waves related to strong Turkey earthquakes have been recorded both by seismic stations throughout the globe and on other devices such as the ground deformation (GNSS, strainmeters, or tiltmeters) networks. In this paper, we show and analyze the earthquake signals recorded by bore-hole tilt stations that monitor seismic and volcanic activities at Mt. Etna. Tilt stations showed very large variations, despite their distance from the epicenter (approximately 1950 km) with a period between 10 and 25 seconds. We compared tilt and seismic data for a co–located station evidencing a very similar waveform that highlight how tiltmeters respond to translational acceleration rather than ground tilt during a teleseism, suggesting that, for waves with this period, they may behave as horizontal seismometers. By using these signals, we evidence the different behaviors of two of the most used models of tiltmeters on volcanoes (Lily and Pinnacle) and how they are useful for instrument calibration. [ABSTRACT FROM AUTHOR]

HBr emissions from volcanoes lead rapidly to the formation of BrO within volcanic plumes and have an impact on tropospheric chemistry, at least at the local and regional scales. The motivation of this paper is to prepare a framework for further 3D modelling of volcanic halogen emissions in order to determine their fate within the volcanic plume and then in the atmosphere at the regional and global scales. The main aim is to evaluate the ability of the model to produce a realistic partitioning of bromine species within a grid box size typical of MOCAGE (Model Of atmospheric Chemistry At larGE scale) 3D (0.5 ∘ × 0.5 ∘). This work is based on a 1D single-column configuration of the global chemistry-transport model MOCAGE that has low enough computational cost to allow us to perform a large set of sensitivity simulations. This paper uses the emissions from the Mount Etna eruption on 10 May 2008. Several reactions are added to MOCAGE to represent the volcanic plume halogen chemistry. A simple plume parameterisation is also implemented and tested. The use of this parameterisation tends to only slightly limit the efficiency of BrO net production. Both simulations with and without the parameterisation give results for the partitioning of the bromine species, of ozone depletion and of the BrO/SO2 ratio that are consistent with previous studies. A series of test experiments were performed to evaluate the sensitivity of the results to the composition of the emissions (primary sulfate aerosols, Br radical and NO) and to the effective radius assumed for the volcanic sulfate aerosols. Simulations show that the plume chemistry is sensitive to all these parameters. We also find that the maximum altitude of the eruption changes the BrO production, which is linked to the vertical variability of the concentrations of oxidants in the background air. These sensitivity tests display changes in the bromine chemistry cycles that are generally at least as important as the plume parameterisation. Overall, the version of the MOCAGE chemistry developed for this study is suitable to produce the expected halogen chemistry in volcanic plumes during daytime and night-time. [ABSTRACT FROM AUTHOR]

This 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. [ABSTRACT FROM AUTHOR]

In this paper, we propose an update of the spatial probability map for flank eruptions from Etna (Italy), based on the distribution of the flank eruptive fissures that opened in the last 4000 years. The general procedure followed is to split the fissure dataset into training and testing subsets; then we build models on the training subset under different assumptions and test them on their likelihood of the testing subset. This allows selecting objectively the best models and assumptions. Furthermore, it allows testing whether (i) unavoidable incompleteness in the mapped fissures, and (ii) possible migration through time in the location of the flank activity, have an effect on the training models that can or cannot be neglected. We used different spatial models by exploiting different Kernel functions (Exponential, Cauchy, Uniform, and Gaussian), and calculated the degree of clustering of flank fissures in the training data. The results show that neither under-recording nor possible migration in time affect significantly the informativeness of the previous flank fissures in forecasting the location of the successive ones. Our study provides a canonical map of the spatial probability for future flank eruptions at Etna based on the location of flank fissures that opened in the last 4000 years. The map confirms a preferred location along a Northeast-to-South area, corresponding to the location of the most active rifts. It also shows that the Southern flank of the volcano, which is the most urbanized one, sits downhill of the largest cumulated-probability area for flank eruption. We also run sensitivity analyses to test the effect of (i) restricting the data to the most recent 400 years, and (ii) including the information on the unclamping stress induced on the mapped fissures by sources of deformation proposed in literature for recent eruptions of Etna. The results of the sensitivity analyses confirm the main features of the canonical map, and add information on the epistemic uncertainty attached to it. [ABSTRACT FROM AUTHOR]

At Mt. Etna volcano, flank eruptions are often accompanied by seismic swarms with damaging earthquakes; the most recent case‐history is the 2018 flank eruption, associated with a destructive earthquake (Mw 5.0). In this paper, we analyze the earthquake and eruptive catalogs from 1800 to 2018, to produce quantitative estimates of the earthquake rate under the influence of flank eruptions. We quantify that 30% of the flank eruption onsets precede a major (i.e., damaging, Ix ≥ V–VI EMS) earthquake by 30 days or less; 18% of the major earthquakes follow a flank eruption onset in 30 days or less. Thus, we show that the probability of major earthquakes increases 5–10 times after the onset of flank eruptions and this effect lasts for 30–45 days. This is also observed after the end of the eruptions. Results indicate different relationships depending on the location of the volcano‐tectonic systems considered individually (eruptive fissures, seismogenic faults). For instance, we describe a 10–20 times increased probability of earthquakes for 65–70 days after eruptions on the northeastern flank, and of new flank eruptions for 45–70 days after earthquakes of the Pernicana fault. Plain Language Summary: Historically, the flank eruptions of Mt. Etna have often been accompanied by destructive seismic events, although strong earthquakes have occurred during periods of volcanic quiescence too. As a result, the impact of both phenomena on local communities and territory is given by an alternation of two different hazards but still linked to each other. In this paper, by considering the up‐to‐date historical catalogs of earthquakes and eruptions at Mt. Etna, we quantify how probable it is, if compared to the average pattern, to have an earthquake temporally related to a flank eruption. That is, 30% of the flank eruption onsets precede a damaging earthquake by 30 days or less; the probability of strong earthquakes increases 5–10 times after the onset of flank eruptions and this effect lasts for 30–45 days. Thus, we show that the probability of damaging earthquakes drastically increases after the onset of flank eruptions and this effect lasts for several weeks. This is also observed after the end of the eruptions. Results provide the quantitative basis for a multihazard assessment that may enable better operative decisions to face future eruptive crises at Mt. Etna. Key Points: Flank eruptions at Mt. Etna are statistically compatible with Poisson processes with "slowly varying" rateThe major earthquakes and flank eruptions at Mt. Etna are not independentThe probability of major earthquakes increases by 5–10 times for 30–45 days after the onset and the end of a flank eruption [ABSTRACT FROM AUTHOR]

Artificial intelligence is widely spreading in all modern technologies. Such a very powerful methodology can have important applications in radio astronomy technology, for instance, in the new DBBC4 VLBI backend development project and in the low frequency array AntArr under development on the Etna slopes in Italy. In the present paper, we describe the method currently adopted for those projects and some possible applications, which could provide substantial new features in this decade to the radio astronomy science and technology. [ABSTRACT FROM AUTHOR]

The detection ability of SO2 cameras has been improved effectively, while the calibration is still the main factor that limits their measurement accuracy. This paper presents a nonlinear calibration theory by considering the effect of light dilution due to the path radiance as well as the dependence of plume aerosol on scattering wavelength. This new spectral calibration method is used to retrieve the SO2 column density and emission rate of the Etna volcano. Results show that, compared with the DOAS calibration approach, the inversion error can be reduced by 13% if the new spectral calibration is adopted. The superiority of the proposed method will become more obvious for long-distance detection of optically thick plumes. [ABSTRACT FROM AUTHOR]

The method of 're-treading' the fieldwork of past geologists is analogous to the method of 're-staging' historically significant laboratory experiments. Neither provides any short cut to scientific or historical truth, nor grounds for celebrating or condemning the work of past scientists. Yet both can yield valuable insights into those scientists' on-the-spot thinking, their reasoning and their eventual presentation of their conclusions. As a historical research method, the 're-treading' of fieldwork has been relatively neglected, although it has many parallels with more traditional methods centred on the analysis of texts and their accompanying images. This paper summarises a few examples of 're-treading', drawn from the author's published research on fieldwork by European geologists in the decades around 1800; but the methods described here can be, and deserve to be, adopted much more widely. [ABSTRACT FROM AUTHOR]

Volcanic plume height is one the most important features of explosive activity; thus, it is a parameter of interest for volcanic monitoring that can be retrieved using different remote sensing techniques. Among them, calibrated visible cameras have demonstrated to be a promising alternative during daylight hours, mainly due to their low cost and low uncertainty in the results. However, currently these measurements are generally not fully automatic. In this paper, we present a new, interactive, open-source MATLAB tool, named 'Plume Height Analyzer' (PHA), which is able to analyze images and videos of explosive eruptions derived from visible cameras, with the objective of automatically identifying the temporal evolution of eruption columns. PHA is a self-customizing tool, i.e., before operational use, the user must perform an iterative calibration procedure based on the analysis of images of previous eruptions of the volcanic system of interest, under different eruptive, atmospheric and illumination conditions. The images used for the calibration step allow the computation of ad hoc expressions to set the model parameters used to recognize the volcanic plume in new images, which are controlled by their individual characteristics. Thereby, the number of frames used in the calibration procedure will control the goodness of the model to analyze new videos/images and the range of eruption, atmospheric, and illumination conditions for which the program will return reliable results. This also allows improvement of the performance of the program as new data become available for the calibration, for which PHA includes ad hoc routines. PHA has been tested on a wide set of videos from recent explosive activity at Mt. Etna, in Italy, and may represent a first approximation toward a real-time analysis of column height using visible cameras on erupting volcanoes. [ABSTRACT FROM AUTHOR]

The green transformation of the built environment is aimed at improving sustainability and can be supported by digitalization, which has become a significant tool to support the supply, integration, and management of information throughout the construction life cycle. In addition, climate change highly affects human comfort in the built environment and different strategies should be evaluated for adapting cities. This paper developed a digital workflow by integrating existing tools (i.e., Grasshopper, Ladybug, Honeybee, and Dragonfly) to evaluate how different green infrastructure strategies affected the thermal comfort by reducing the UTCI. The workflow was applied to a typical historical urban context (Catania, South of Italy), consisting of a square surrounded by three-floor buildings. Three basic scenarios were created that depended on the pavement material used in the built environment: a black stone pavement (reference material from Mount Etna), a permeable pavement, and grass. These three scenarios were combined with different green infrastructure strategies: tree pattern on the square, green walls and green roofs on the surrounding buildings, and the integrations of all these above-mentioned strategies. The results demonstrated that the integration of different green strategies (a grass square instead of pavement, with trees, and green walls and green roofs) increased the thermal comfort by reducing the UTCI by more than 8 °C compared to the existing urban context (black stone pavement and building envelope). However, this temperature reduction was highly affected by the location of the human body into the urban context and by the evaporation rates from vegetation. The workflow developed will be useful for designers to evaluate the effectiveness of different green strategies during the early-design stage in mitigating and adapting cities to climate change. [ABSTRACT FROM AUTHOR]

In this study, we focus on the eruption of Mount Etna on Christmas 2018, which emitted great amounts of S O 2 from 24th to 30th December into the free troposphere. Simulations based on two different estimations of S O 2 emission fluxes are conducted with the chemistry-transport model MOCAGE in order to study the impact of these estimations on the volcanic plume modeling. The two flux emissions used are retrieved (1) from the ground-based network FLAME, located on the flank of the volcano, and (2) from the spaceborne instrument SEVIRI onboard the geostationary satellite MSG. Multiple spaceborne observations, in the infrared and ultraviolet bands, are used to evaluate the model results. Overall, the model results match well with the plume location over the period of the eruption showing the good transport of the volcanic plume by the model, which is linked to the use of a realistic estimation of the altitude of injection of the emissions. However, there are some discrepancies in the plume concentrations of S O 2 between the two simulations, which are due to the differences between the two emission flux estimations used that are large on some of the days. These differences are linked to uncertainties in the retrieval methods and observations used to derive S O 2 volcanic fluxes. We find that the uncertainties in the satellite-retrieved column of S O 2 used for the evaluation of the simulations, linked to the instrument sensitivity and/or the retrieval algorithm, are sometimes nearly as large as the differences between the two simulations. This shows a limitation of the use of satellite retrievals of S O 2 concentrations to quantitatively validate modeled volcanic plumes. In the paper, we also discuss approaches to improve the simulation of S O 2 concentrations in volcanic plumes through model improvements and also via more advanced methods to more effectively use satellite-derived products. [ABSTRACT FROM AUTHOR]

During the last two decades, the Etna volcano has undergone several sequences of lava fountaining (LF) events that have had a major impact on road conditions, infrastructure and the local population. In this paper, we consider the LF episodes occurring between 2011 and 2022, calculating their erupted volumes using the images recorded by the monitoring thermal cameras and applying a manual procedure and a dedicated software to determine the lava fountain height over time, which is necessary to obtain the erupted volume. The comparison between the results indicates the two procedures match quite well, the main differences occurring when the visibility is poor and data are interpolated. With the aim of providing insights for hazard assessment, we have fitted some probabilistic models of both the LF inter-event times and the erupted volumes of pyroclastic material. In more detail, we have tested power-law distributions against log-normal, Weibull, generalised Pareto and log-logistic. Results show that the power-law distribution is the most likely among the alternatives. This implies the lack of characteristic scales for both the inter-event time and the pyroclastic volume, which means that we have no indication as to when a new episode of LF will occur and/or how much material will be erupted. What we can reasonably say is only that short inter-event times are more frequent than long inter-event times, and that LF characterised by small volumes are more frequent than LF with high volumes. However, if the hypothesis that magma accumulates on Etna at a rate of about 0.8 m 3 s − 1   holds, the material accumulated in the source region from the beginning of the observation period (2011) to the present (2022) has already been ejected. In simple terms, there is no accumulated magma in the shallow storage that is prone to be erupted in the near future. [ABSTRACT FROM AUTHOR]

In the last decade, video surveillance cameras have experienced a great technological advance, making capturing and processing of digital images and videos more reliable in many fields of application. Hence, video-camera-based systems appear as one of the techniques most widely used in the world for monitoring volcanoes, providing a low cost and handy tool in emergency phases, although the processing of large data volumes from continuous acquisition still represents a challenge. To make these systems more effective in cases of emergency, each pixel of the acquired images must be assigned to class labels to categorise them and to locate and segment the observable eruptive activity. This paper is focused on the detection and segmentation of volcanic ash plumes using convolutional neural networks. Two well-established architectures, the segNet and the U-Net, have been used for the processing of in situ images to validate their usability in the field of volcanology. The dataset fed into the two CNN models was acquired from in situ visible video cameras from a ground-based network (Etna_NETVIS) located on Mount Etna (Italy) during the eruptive episode of 24th December 2018, when 560 images were captured from three different stations: CATANIA-CUAD, BRONTE, and Mt. CAGLIATO. In the preprocessing phase, data labelling for computer vision was used, adding one meaningful and informative label to provide eruptive context and the appropriate input for the training of the machine-learning neural network. Methods presented in this work offer a generalised toolset for volcano monitoring to detect, segment, and track ash plume emissions. The automatic detection of plumes helps to significantly reduce the storage of useless data, starting to register and save eruptive events at the time of unrest when a volcano leaves the rest status, and the semantic segmentation allows volcanic plumes to be tracked automatically and allows geometric parameters to be calculated. [ABSTRACT FROM AUTHOR]

Volcanoes are a known source of halogens to the atmosphere. HBr volcanic emissions lead rapidly to the formation of BrO within volcanic plumes. BrO, having a longer residence time in the atmosphere than HBr, is expected to have an impact on tropospheric chemistry, at least at the local and regional scales. The objective of this paper is to prepare a framework for further 3-D modelling of volcanic halogen emissions in order to determine their fate within the volcanic plume and then in the atmosphere at the regional and global scales. This work is based on a 1-D configuration of the global chemistry transport model MOCAGE whose low computational cost allows us to perform a large set of sensitivity simulations. This paper studies the Mount Etna eruption on 10 May, 2008. Several reactions are added to MOCAGE to represent the halogen chemistry occurring within the volcanic plume. A simple sub-grid scale parameterization of the volcanic plume is also implemented and tested. The use of this parameterization tends to limit slightly the efficiency of BrO net production. Both simulations with and without the parameterization give similar results for the partitioning of the bromine species, ozone depletion and of the BrO/SO2 ratio that are consistent with previous studies and with the BrO/SO2 ratio in the volcanic plume estimated from GOME-2 spaceborne observations. A series of test experiments were performed to evaluate the sensitivity of the results to the composition of the emissions, and, in particular, primary sulphate aerosols, the Br radical, and NO. Simulations show that the plume chemistry is sensitive to these assumptions. Another series of tests on the effective radius assumed for the volcanic sulphate aerosols shows that BrO net production is sensitive to this parameter with lower BrO concentrations reached when larger aerosols (smaller total surface area) are assumed. We also find that the maximum altitude of the eruption changes the BrO production, which is linked to the vertical variability of the concentrations of oxidants. These sensitivity tests display changes in the bromine chemistry cycles that are generally at least as important as the subgrid scale plume parameterization. Overall, the version of the MOCAGE chemistry developed for this study is suitable to produce the expected halogen chemistry in volcanic plumes during daytime and night. These results will be used to guide the implementation of volcanic halogen emissions in the 3-D configuration of MOCAGE for regional and global simulations. [ABSTRACT FROM AUTHOR]

The Etna volcano is renowned worldwide for its extraordinary lava fountains that rise several kilometers above the vent and feed eruptive columns, then drift hundreds of kilometers away from the source. The Italian Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo (INGV-OE) is responsible for the monitoring of Mt. Etna, and for this reason, has deployed a network of visible and thermal cameras around the volcano. From these cameras, INGV-OE keeps a keen eye, and is able to observe the eruptive activity, promptly advising the civil protection and aviation authorities of any changes, as well as quantifying the spread of lava flows and the extent of pyroclastic and ash plumes by using a careful analysis of the videos recorded by the monitoring cameras. However, most of the work involves analysis carried out by hand, which is necessarily approximate and time-consuming, thus limiting the usefulness of these results for a prompt hazard assessment. In addition, the start of lava fountains is often a gradual process, increasing in strength from Strombolian activity, to intermediate explosive activity, and eventually leading to sustained lava fountains. The thresholds between these different fields (Strombolian, Intermediate, and lava fountains) are not clear cut, and are often very difficult to distinguish by a manual analysis of the images. In this paper, we presented an automated routine that, when applied to thermal images and with good weather conditions, allowed us to detect (1) the starting and ending time of each lava fountain, (2) the area occupied by hot pyroclasts, (3) the elevation reached by the lava fountains over time, and (4) eventually, to calculate in real-time the erupted volume of pyroclasts, giving results close to the manual analysis but more focused on the sustained portion of the lava fountain, which is also the most dangerous. This routine can also be applied to other active volcanoes, allowing a prompt and uniform definition of the timing of the lava fountain eruptive activity, as well as the magnitude and intensity of the event. [ABSTRACT FROM AUTHOR]

In November 2017, the China Meteorological Administration launched a new polar orbiting satellite in its Fengyun (FY) series: FY-3D. With its main purpose being the collection of meteorological data, FY-3D featured a comprehensive payload that is equally exploitable by various Earth Science disciplines. One of its sensors, the MEdium Resolution Spectral Imager-2 (MERSI-2), provides visible and infrared imagery at spatial resolutions of 250 – 1000 m. These characteristics make MERSI-2 suitable for volcanological remote sensing and make it comparable to the National Aeronautics and Space Administration's (NASA's) Moderate Resolution Imaging Spectroradiometer (MODIS) sensors which themselves, have been widely used in volcanological applications. This paper evaluates the first clear and near-coincident MODIS – MERSI-2 images of Mount Etna (Italy) during an active volcanic phase in 2019 and in turn, provides the first assessment of MERSI-2's utility in observing volcanic activity in the Thermal InfraRed (TIR). To ensure the comparability of both scenes, data from each were converted to Land Surface Temperature (LST) and comparisons were encouraging, with an r2 of 0.92, a mean temperature discrepancy of 0.26 K and a root mean squared error of 0.75 K. Having ascertained comparability, we focussed on the absolute temperatures detected at the eruption site, with the highest being 317.3 K and 328.1 K for MODIS and MERSI-2, respectively. The 20 minute gap between the acquisitions is the most likely the cause of this temperature discrepancy, suggesting variations in lava effusion rates and activity were occurring at Mount Etna over such timescales. This study confirms the applicability of MERSI-2 for observing volcanic activity and emphasises the significance of TIR volcanic monitoring and the importance that additional spaceborne platforms might have in reducing temporal gaps between image acquisitions. Given its unique characteristics, future studies should investigate the applicability of MERSI-2 in more varied volcanic settings. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of mild explosive activity is a fundamental tool for hazard assessment at open conduit volcanoes. This is a particularly critical task for Etna volcano. Etna is in fact characterized by frequent, mild explosive activity, punctuated by lava flows and paroxysmal events ('lava fountains'), which, because of their greater impact, have been the main target for hazard studies, whereas more frequent Strombolian activity has been overlooked. As a result, their impact and associated hazards have been never quantified, despite the extensive monitoring and surveillance activities carried out on this volcano. In this paper, we analyze video recordings of a sequence of Strombolian explosions occurring at the summit craters of Mt. Etna, in Italy, in February 2020. Data were also integrated with a petrographic analysis of collected samples, and drone surveys were performed at the same time as the video recordings. We estimate the frequency of explosions (20–12 per min); particle exit speeds (1–50 m/s), and erupted mass (100–102 kg) of those explosions. A very regular, small-scale activity (marked by a single burst of gas breaking the magma free surface into bombs and lapilli fragments) was occasionally punctuated by larger explosions, (at least one every 5 min), with a longer duration, fed by larger magma volumes, and consisting of two to three distinct pulses followed by a stationary phase. We found that the repose times between explosions follows a log logistic distribution, which is in agreement with the behavior of open vent explosive activity. The four largest explosions of the sequence were analyzed in detail: they emitted particles with median diameters (Mdphi) ranging from −10.1 to −8.8 phi, with bimodal distributions. [ABSTRACT FROM AUTHOR]

In the De Raptu Proserpinae , Claudian refocuses the natural cycles of regeneration that color the myth of Proserpina and Ceres by placing a significant emphasis on the landscape in which his poem's events unfold: the island of Sicily. This paper argues that the focus on Sicilian landscape in the DRP makes manifest the central concerns of the poem, allowing Claudian to rearticulate the cyclical focus of his epic. Through an examination of the progression of DRP 's three extended Sicilian ekphrases, we can see how Sicily, and, specifically, the volcanic Mt. Etna as its figurative center, embodies the paradoxical cycle of destruction and renewal. [ABSTRACT FROM AUTHOR]

In this paper, a method is presented to classify volcano activity into three classes, namely quiet, strombolian, and paroxysm. The method is based on training a six-layered deep neural network (DNN) model using these signals as inputs (features): time series of the number of distances of infrasonic events, radar backscatter power, RMS of tremor in five stations close to craters of the volcano, tilt derivative, and seismic tremor source depth. The method was tested on the data related to a period of five years, and the results were concluded using indexes of precision, recall, F1 score, and Cohen's Kappa coefficient were calculated to evaluate the qualification of the classification. Also, the results were compared to Bayesian network (BN), K-nearest neighbors (KNN), and decision tree (DT) methods. Decision learning trees and KNN are popular machine learning algorithms belonging to the class of supervised learning algorithms. They mimic the human level thinking and, differing from neural networks, are not black box models. The comparisons reveal the proposed method, especially in classifying both strombolian and paroxysm classes. This advantage makes the presented method a more reliable tool for practical use in the volcano monitoring control rooms. [ABSTRACT FROM AUTHOR]

Although magma migration is a necessary condition for the occurrence of a volcanic eruption, static analytical models for ground deformations consider stationary sources that undergo a change only in forces acting in the Earth's interior, such as changes in pressure or volume in a geometrically defined body. The variations in pressure or volume are mostly linked to the fluid dynamics or the superficializing of magma batches. Detection and tracking of magma motion in volcanic areas represent fundamental capabilities in predicting possible eruptions and therefore in reducing their associated risks. In the 3‐dimensional space, a magma migration defines a starting volume in depression and an arrival volume in overpressure. These end members can be modeled with two bonded point sources. Such a double‐point source can be considered the equivalent of a physical dipole. Here, the analytical solutions to predict ground deformations caused by a dipole source are presented and analyzed. The dipole analytical source allows modeling the effects on ground deformation of magma migration and vice versa. Estimating the magma migration from the measured ground deformation through data inversion. The dipole solution is compared with the basic volumetric source to discern its distinctive peculiarities and range of applicability. In addition, a discrepancy analysis with the equivalent numerical model was conducted to evaluate the approximation errors of the analytical model. To evaluate the practical value of the proposed model, two case studies on Sinabung volcano and Mt. Etna are presented. The analysis of continuous deformation data from GNSS (Global Navigation Satellite System) stations on Mt. Etna shows that a dipole source activates days before the December 2018 eruption, thus allowing the identification of the final magma rise. Plain Language Summary: Traditional analytical models for ground deformations focus on fixed sources and do not consider the possibility that magma may move, which is important for predicting volcanic eruptions. To better understand and predict eruptions, it is crucial to track magma migration. The dipole analytical source is a tool that helps model how magma movement affects ground deformation. It estimates magma migration by analyzing measured ground deformation data. This method provides information on the source's strength, location, and migration direction. Two case studies on Sinabung volcano and Mt. Etna show the practical value of the dipole source. In the Mt. Etna case, a dipole source was identified days before the December 2018 eruption, demonstrating its potential for early detection. Key Points: Analytical solutions for ground deformations caused by a dipole source are presented and analyzedThe differential dipole model can describe a movement of magma within the plumbing systemThe dipole model can be useful in identifying the magmatic rising phase that potentially anticipate an eruption [ABSTRACT FROM AUTHOR]

Volcanic rocks are considered reliable recorders of past changes in the Earth's magnetic field. Recent flows, however, sometimes fail to produce the known magnetic field at the time of cooling. Previous research on Mt. Etna suggests paleomagnetic data might not be accurately recorded. Here we test the accuracy of paleomagnetic data obtained from Mt. Etna lavas by comparing paleomagnetic data from historical flows to direct measurements of the magnetic field above the current topography. The inclinations and intensities in both data sets are biased toward lower values, while there is no such trend for the declination. Inclinations are on average 2.9° lower than expected; intensities are on average 8.8 µT lower. The deviations from the expected values depend on the height above the flow. Moreover, the inclinations and intensities vary as a function of topography. Both are higher above ridges and lower in gullies; the variations within a site are up to 14.1° in inclination and 12.9 µT for intensity. To suppress this paleomagnetic data bias it is important to take samples several meters apart and from different parts of the flow whenever possible. While this leads to a higher degree of scatter in paleodirections, the results better represent the Earth's magnetic field at the time of cooling. This emphasizes the importance of reporting paleomagnetic sampling strategies in detail. Plain Language Summary: Paleomagnetic data from lavas is routinely used in the Earth Sciences to for example, reconstruct the past behavior of the Earth's magnetic field, or make models of past plate motions. Very young flows for which the ambient magnetic field at the time of cooling is known, however, sometimes fail to produce the known reference values. Lava flows from Mt. Etna are extensively studied in the past and the paleomagnetic data obtained does often not agree with the known magnetic field value in which the lavas cooled. Here we show that the topography of volcanic terrain may influence the magnetic signal of new, overlying, flows, and we make recommendations for sampling strategies that suppress these terrain effects as much as possible. Key Points: Paleomagnetic data from Mt. Etna does often not reproduce the known geomagnetic field wellLocal magnetic anomalies explain bias in paleomagnetic data as function of topographyOptimizing the paleomagnetic sampling strategy may suppress this bias in paleomagnetic data [ABSTRACT FROM AUTHOR]

On 21 May 2023, a hidden eruption occurred at the Southeast Crater (SEC) of Etna (Italy); indeed, bad weather prevented its direct and remote observation. Tephra fell toward the southwest, and two lava flows propagated along the SEC's southern and eastern flanks. The monitoring system of the Istituto Nazionale di Geofisica e Vulcanologia testified to its occurrence. We analyzed the seismic and infrasound signals to constrain the temporal evolution of the fountain, which lasted about 5 h. We finally reached Etna's summit two weeks later and found an unexpected pyroclastic density current (PDC) deposit covering the southern lava flow at its middle portion. We performed unoccupied aerial system and field surveys to reconstruct in 3D the SEC, lava flows, and PDC deposits and to collect some samples. The data allowed for detailed mapping, quantification, and characterization of the products. The resulting lava flows and PDC deposit volumes were (1.54 ± 0.47) × 106 m3 and (1.30 ± 0.26) × 105 m3, respectively. We also analyzed ground-radar and satellite data to evaluate that the plume height ranges between 10 and 15 km. This work is a comprehensive analysis of the fieldwork, UAS, volcanic tremor, infrasound, radar, and satellite data. Our results increase awareness of the volcanic activity and potential dangers for visitors to Etna's summit area. [ABSTRACT FROM AUTHOR]

The geochemical monitoring of volcanic activity today relies largely on remote sensing, but the combination of this approach together with soil gas monitoring, using the appropriate parameters, is still not widely used. The main purpose of this study was to correlate data from crater gas emissions with flank emissions of soil gases at Mt. Etna volcano from June 2006 to December 2020. Crater SO2 fluxes were measured from fixed stations around the volcano using the DOAS technique and applying a modeled clear-sky spectrum. The SO2/HCl ratio in the crater plume was measured with the OP-FTIR technique from a transportable instrument, using the sun as an IR source. Soil CO2 efflux coupled with the 220Rn/222Rn activity ratio in soil gases (named SGDI) were measured at a fixed monitoring site on the east flank of Etna. All signals acquired were subject both to spectral analysis and to filtering of the periodic signals discovered. All filtered signals revealed changes that were nicely correlated both with other geophysical signals and with volcanic eruptions during the study period. Time lags between parameters were explained in terms of different modes of magma migration and storage inside the volcano before eruptions. A comprehensive dynamic degassing model is presented that allows for a better understanding of magma dynamics in an open-conduit volcano. [ABSTRACT FROM AUTHOR]

An innovative mobile lidar device, developed to monitor volcanic plumes during explosive eruptions at Mt. Etna (Italy) and to analyse the optical properties of volcanic particles, was upgraded in October 2023 with the aim of improving volcanic plume retrievals. The new configuration of the lidar allows it to obtain new data on both the optical and the microphysical properties of the atmospheric aerosol. In fact, after the upgrade, the lidar is able to measure three backscattering coefficients, two extinction coefficients and two depolarisation ratios in a configuration defined as "state-of-the-art lidar", where properties such as particle size distribution and the refractive index can be derived. During the lidar implementation, we were able to test the system's performance through specific calibration measurements. A comparison in an aerosol-free region (7.2–12 km) between lidar signals at 1064 nm, 532 nm and 355 nm and the corresponding pure molecular profiles showed a relative difference of <1% between them for all the wavelengths, highlighting the good dynamic of the signals. The overlap correction allowed us to reduce the underestimation of the backscattering coefficient from 50% to 10% below 450 m and 750 m at both 355 and 532 nm, respectively. The correct alignment between the laser beam and the receiver optical chain was tested using the signal received from the different quadrants of the telescope, and the relative differences between the four directions were comparable to zero, within the margin of error. Finally, the first measurement results are shown and compared with results obtained by other instruments, with the aim of proving the ability of the upgraded system to more precisely characterise aerosol optical and microphysical properties. [ABSTRACT FROM AUTHOR]

Ground-based infrared cameras can be used effectively and safely to provide quantitative information about small to moderate-sized volcanic eruptions. This study describes an infrared camera that has been used to measure emissions from the Mt. Etna and Stromboli (Sicily, Italy) volcanoes. The camera provides calibrated brightness temperature images in a broadband (8–14 µm) channel that is used to determine height, plume ascent rate and volcanic cloud/plume temperature and emissivity at temporal sampling rates of up to 1 Hz. The camera can be operated in the field using a portable battery and includes a microprocessor, data storage and WiFi. The processing and analyses of the data are described with examples from the field experiments. The updraft speeds of the small eruptions at Stromboli are found to decay with a timescale of ∼10 min and the volcanic plumes reach thermal equilibrium within ∼2 min. A strong eruption of Mt. Etna on 1 April 2021 was found to reach ∼9 km, with ascent speeds of 10–20 ms−1. The plume, mostly composed of the gases CO2, water vapour and SO2, became bent over by the prevailing winds at high levels, demonstrating the need for multiple cameras to accurately infer plume heights. [ABSTRACT FROM AUTHOR]

This work introduces a new Ground Motion Model (GMM) to predict the horizontal and vertical components of PGA, PGV and acceleration response spectra up to 5s for the volcanic events in Italy. The model updates the GMM for the horizontal components, recently developed by Lanzano & Luzi [1], and shows relevant amplitudes in near-source and a frequency content richer in intermediate-to-low frequencies. The comparison with an event not used for the calibration and belonging to another volcanic district in Italy is promising for the extension of the model to other areas. Finally, we present a case study of a site, in the proximity of Mount Etna in eastern Sicily region, which allows us to evaluate the impact of these models in the framework of a Probabilistic Seismic Hazard Analysis (PSHA). • a ground motion model for the vertical component of volcanic earthquakes in Italy is proposed. • The ground motion can be high in near-source conditions for shallower events. • The shallow volcanic events attenuates with distance rapidly than the active crustal ones. • The peak frequency content of volcanic events is shifted to lower frequencies. • a PSHA case study is discussed with focus on the impact of the use of the GMM proposed in the paper. [ABSTRACT FROM AUTHOR]

An in-depth analysis of the orophilous vegetation dominated by Juniperus hemisphaerica in Sicily, based on literature data and unpublished relevés, is presented. A total of 156 phytosociological relevés were processed and analyzed using classification and ordination methods. Overall, 151 vascular plant species were recorded, of which 38% were endemic species, with a dominant hemicryptophytic biological form (49%). Classification of the relevés, supported by ordination, showed two main vegetation groups: one including the Juniperus communities of Mt. Madonie (Cerastio tomentosi–Juniperetum hemisphaericae and Pruno cupanianae–Juniperetum hemisphaericae), and the other including the vegetation of Mt. Etna (Bellardiochloo aetnensis–Juniperetum hemisphaericae and Roso siculae–Juniperetum hemisphaericae ass. nova). Furthermore, a new alliance, Berberido aetnensis–Juniperion hemisphericae, is proposed for Sicily. [ABSTRACT FROM AUTHOR]

Volcanic eruptions pose a major natural hazard influencing the environment, climate and human beings at different temporal and spatial scales. Nevertheless, several volcanoes worldwide are poorly monitored and assessing the impact of their eruptions remains, in some cases, challenging. Nowadays, different numerical dispersion models are largely employed in order to evaluate the potential effects of volcanic plume dispersion due to the transport of ash and gases. On 28 August 2019, both Mt. Etna and Stromboli had eruptive activity; Mt. Etna was characterised by mild-Strombolian activity at summit craters, while at Stromboli volcano, a paroxysmal event occurred, which interrupted the ordinary typical-steady Strombolian activity. Here, we explore the spatial dispersion of volcanic sulphur dioxide (SO 2 ) gas plumes in the atmosphere, at both volcanoes, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) considering the ground-measured SO 2 amounts and the plume-height as time-variable eruptive source parameters. The performance of WRF-Chem was assessed by cross-correlating the simulated SO 2 dispersion maps with data retrieved by TROPOMI and OMI sensors. The results show a feasible agreement between the modelled dispersion maps and TROPOMI satellite for both volcanoes, with spatial pattern retrievals and a total mass of dispersed SO 2 of the same order of magnitude. Predicted total SO 2 mass for Stromboli might be underestimated due to the inhibition from ground to resolve the sin-eruptive SO 2 emission due to the extreme ash-rich volcanic plume released during the paroxysm. This study demonstrates the feasibility of a WRF-Chem model with time-variable ESPs in simultaneously reproducing two eruptive plumes with different SO 2 emission and their dispersion into the atmosphere. The operational implementation of this method could represent effective support for the assessment of local-to-regional air quality and flight security and, in case of particularly intense events, also on a global scale. [ABSTRACT FROM AUTHOR]

Geophysical data provide the chance to investigate a volcano's dynamics; considerable information can especially be gleaned on the stress and strain patterns accompanying the internal processes and the effect of magma ascent on the main structures triggering earthquakes. Here, we analysed in detail the seismicity recorded over the last two decades on Etna volcano (southern Italy), focusing on earthquakes distribution and focal mechanism clustering; the ground deformation pattern affecting the volcanic edifice with the inflation and deflation phases was also examined. Analysed data were compared in order to shed light on possible relationships with the volcanic activity and to better understand the internal dynamics of the volcano over time. Significant steps during or shortly before major eruptions in the seismic strain release and ground deformation temporal series highlight a straightforward relationship between seismicity occurring at shallow level, inflation/deflation and volcanism. Furthermore, at depths greater than 5–7 km, down to about 20 km, the orientation of the P- and T-axes clearly indicate the existence of a pressure source in the central part of the volcano. All the results underline that the stress field related to the volcano plumbing system interferes with the regional field, partly overriding it. [ABSTRACT FROM AUTHOR]

Timely estimations of magma volumes emitted during an eruption or a sequence of explosive events are vital for investigating the eruptive activity and evaluating the associated hazard. A reliable method for estimating erupted volumes is based on the analysis of digital surface models that nowadays can be obtained subsequently using stereo or tri‐stereo optical satellite imagery. However, the real‐time estimation of the erupted volumes is still an open challenge. Here, we explore the capacity of extracting volume estimates from continuous measurements of volumetric strain changes recorded by borehole dilatometers. We compare the volumes derived from numerous high spatial resolution satellite images with high precision strain records at Etna during 2020–2022, when more than 60 lava fountains occurred. The good correlation between the two data sets shows that strain changes can be used as a proxy to estimate the emitted volumes both over time and in real‐time. Plain Language Summary: Quantifying erupted volumes is fundamental in volcanology to provide a robust characterization of eruptions. To date, estimates of erupted volumes have been calculated after the eruptions have ended and the real‐time estimation of the erupted volumes is still an on‐going challenge. In recent decades, the sequences of lava fountain‐type eruptions at Etna, with dozens of episodes close in time and more than 100 episodes occurring since 2011, has made the task of estimating the volumes in real‐time during each single eruption ever more essential. This would enable providing precise information to Civil Protection authorities and contribute toward hazard evaluation. In this study, we took on this new challenge by exploring the potential to extract erupted volume estimates from continuous measurements of strain changes, recorded by high‐precision borehole instruments installed on the volcano's flanks. We compared and validated the volumes deriving from numerous high spatial resolution satellite images with high‐precision strain records at Etna during 2020–2022, when more than 60 lava fountains occurred. The good correlation between the two data sets shows that strain changes can be used effectively as a proxy to estimate the emitted volumes, both over time and, more importantly, in real‐time. Key Points: Detection of strain changes during sequences of lava fountain eruptions from continuous recording high‐precision borehole instrumentsQuantifying erupted volumes from strain changes, comparison and validation with the volumes calculated from high spatial resolution satellite measurementsNew method to estimate the erupted volumes in real‐time by using the continuous strain recording [ABSTRACT FROM AUTHOR]

Volcano eruption identification and watching is crucial to better understanding volcano dynamics, namely the near real-time identification of the eruption start, end, and duration. Eruption watching allows hazard assessment, eruption forecasting and warnings, and also risk mitigation during periods of unrest, to enhance public safety and reduce losses from volcanic events. The near real-time fire radiative power (FRP) product retrieved using information from the SEVIRI sensor onboard the Meteosat Second Generation (MSG) satellite are used to identify and follow up volcanic activity at the pan-European level, namely the Mount Etna and Cumbre Vieja eruptions which occurred during 2021. The FRP product is designed to record information on the location, timing, and fire radiative power output of wildfires. Measuring FRP from SEVIRI/MSG and integrating it over the lifetime of a fire provides an estimate of the total Fire Radiative Energy (FRE) released. Together with FRP data analysis, SO2 data from the Copernicus Atmosphere Monitoring Service (CAMS) is used to assess the relationship between daily emitted concentrations of SO2 and the radiative energy released during volcanic eruptions. Results show that the FRE data allows us to evaluate the amount of energy released and is related to the pollutant concentrations from volcanic emissions during the considered events. A good agreement between FRP detection and SO2 atmospheric concentrations was found for the considered eruption occurrences. The adopted methodology, due to its simplicity and near real-time availability, shows potential to be used as a management tool to help authorities monitor and manage resources during ongoing volcanic events. [ABSTRACT FROM AUTHOR]

Volcanoes are known to be important emitters of atmospheric gases and aerosols, which for certain volcanoes can include halogen gases and in particular HBr. HBr emitted in this way can undergo rapid atmospheric oxidation chemistry (known as the bromine explosion) within the volcanic emission plume, leading to the production of bromine oxide (BrO) and ozone depletion. In this work, we present the results of a modelling study of a volcanic eruption from Mt Etna that occurred around Christmas 2018 and lasted 6 d. The aims of this study are to demonstrate and evaluate the ability of the regional 3D chemistry transport model Modèle de Chimie Atmosphérique de Grande Echelle (MOCAGE) to simulate the volcanic halogen chemistry in this case study, to analyse the variability of the chemical processes during the plume transport, and to quantify its impact on the composition of the troposphere at a regional scale over the Mediterranean basin. The comparison of the tropospheric SO2 and BrO columns from 25 to 30 December 2018 from the MOCAGE simulation with the columns derived from the TROPOspheric Monitoring Instrument (TROPOMI) satellite measurements shows a very good agreement for the transport of the plume and a good consistency for the concentrations if considering the uncertainties in the flux estimates and the TROPOMI columns. The analysis of the bromine species' partitioning and of the associated chemical reaction rates provides a detailed picture of the simulated bromine chemistry throughout the diurnal cycle and at different stages of the volcanic plume's evolution. The partitioning of the bromine species is modulated by the time evolution of the emissions during the 6 d of the eruption; by the meteorological conditions; and by the distance of the plume from the vent, which is equivalent to the time since the emission. As the plume travels further from the vent, the halogen source gas HBr becomes depleted, BrO production in the plume becomes less efficient, and ozone depletion (proceeding via the Br+O3 reaction followed by the BrO self-reaction) decreases. The depletion of HBr relative to the other prevalent hydracid HCl leads to a shift in the relative concentrations of the Br- and Cl- ions, which in turn leads to reduced production of Br2 relative to BrCl. The MOCAGE simulations show a regional impact of the volcanic eruption on the oxidants OH and O3 with a reduced burden of both gases that is caused by the chemistry in the volcanic plume. This reduction in atmospheric oxidation capacity results in a reduced CH4 burden. Finally, sensitivity tests on the composition of the emissions carried out in this work show that the production of BrO is higher when the volcanic emissions of sulfate aerosols are increased but occurs very slowly when no sulfate and Br radicals are assumed to be in the emissions. Both sensitivity tests highlight a significant impact on the oxidants in the troposphere at the regional scale of these assumptions. All the results of this modelling study, in particular the rapid formation of BrO , which leads to a significant loss of tropospheric ozone, are consistent with previous studies carried out on the modelling of volcanic halogens. [ABSTRACT FROM AUTHOR]

The purpose of the present paper is to investigate the effects of variable eruption source parameters on volcanic plume transport in the Mediterranean basin after the paroxysm of Mount Etna on 23 November 2013. This paroxysm was characterized by a north-east transport of ash and gas, caused by a low-pressure system in northern Italy. It is evaluated here in a joint approach considering the WRF-Chem model configured with eruption source parameters (ESPs) obtained elaborating the raw data from the VOLDORAD-2B (V2B) Doppler radar system. This allows the inclusion of the transient and fluctuating nature of the volcanic emissions to accurately model the atmospheric dispersion of ash and gas. Two model configurations were considered: the first with the climax values for the ESP and the second with the time-varying ESP according to the time profiles of the mass eruption rate recorded by the V2B radar. It is demonstrated that the second configuration produces a considerably better comparison with satellite retrievals from different sensors platforms (Ozone Mapping and Profiler Suite, Meteosat Second-Generation Spinning Enhanced Visible and Infrared Imager, and Visible Infrared Imaging Radiometer Suite). In the context of volcanic ash transport dispersion modeling, our results indicate the need for (i) the use of time-varying ESP, and (ii) a joint approach between an online coupled chemical transport model like WRF-Chem and direct near-source measurements, such as those carried out by the V2B Doppler radar system. [ABSTRACT FROM AUTHOR]

SUMMARY: Mt. Etna is a perfect laboratory for testing new approaches and new technologies in a very active geodynamic environment. It offers, in fact, the opportunity for measuring active crustal deformation, related to volcanic activity as well as to seismic faulting on its flanks. In this work, a network of low-cost/low-power Global Navigation Satellite System stations has been installed and tested on Mt. Etna, across a very active fault, the Provenzana–Pernicana system, cutting its north-eastern flank. During the test period, a lateral eruption occurred (starting on 2018 December 24), with a forceful dyke intrusion that stressed all the flanks of the volcano, soliciting all the main faults dissecting the edifice. Also the Provenzana–Pernicana fault system, where this network was recording, was activated during the dyke intrusion, producing a significant seismic swarm. The low-cost/low-power network data analysis allowed the fault slip during the intrusion to be clearly traced in time and space at all the stations lying on the hangingwall mobile block of the fault. All the stations lying south of the fault trace showed an eastward displacement, in very good agreement with the usual kinematics of the fault and the temporal duration of the M 3.5 December 24 earthquake, related to the seaward dislocation of the eastern mobile flank of the volcano, promoted and accelerated by dyke emplacement on the upper part of the edifice. [ABSTRACT FROM AUTHOR]

Mesoscale eddies are frequently observed in the Eastern Tropical North Atlantic (ETNA), yet their effects on the transport and distribution of biogeochemical solutes, and specifically on the production and remineralization of dissolved organic matter (DOM) remain difficult to elucidate. Here, we investigated the submesoscale variability of chromophoric DOM (CDOM) and fluorescent DOM (FDOM) together with microbial production and remineralization processes in two cyclonic eddies (CEs) in the ETNA during summer and winter 2019. One CE, formed near the coast off Mauritania during the post‐upwelling season, was sampled along a ∼900 km zonal corridor between Mauritania and the Cape Verde Islands. The other CE, formed nearby Brava Island, was out of coastal influence. Four fluorescent components were identified with parallel factor analysis, two humic‐like, and two protein‐like components. Humic‐like FDOM components correlated to optode‐based community respiration and were also good indicators of upwelling associated with the Brava Island CE as they correlated to physical parameters (e.g., temperature) and to dissolved inorganic nitrogen. The tryptophan‐like FDOM components correlated with the carbon and nitrogen content of semi‐labile DOM, phytoplankton biomass, community respiration, and bacterial production. Overall, our study revealed that DOM optical properties are suitable for tracing freshly produced organic matter and the transport of remineralized DOM within offshore eddies. Plain Language Summary: Mesoscale eddies are ubiquitous circulation features in the ocean with horizontal scales on the order of 100 km and lifetimes of days to months. Their swirling motion can cause nutrients from deeper waters to be transported to the surface, stimulating phytoplankton biomass and resulting in the production of dissolved organic matter. However, these effects are difficult to quantify and proxies (biomarkers) are needed to monitor the impact of eddies at high resolution. In this work, we used the optical properties of the dissolved organic matter, especially the fraction capable of fluorescence (FDOM) as biomarker in two cyclonic eddies, one formed in an eastern boundary upwelling system and one formed offshore by winds/Island interaction. We identified four FDOM components, among which an indicator of cyclonic eddy productivity and two indicators of dissolved organic matter recycling, which also tracked nutrient transport in the offshore cyclonic eddy. Our study highlights that continuous FDOM data obtained with sensors could help to follow eddy development and influence on seawater biogeochemistry. Key Points: Four fluorescent dissolved organic matter (FDOM) components were studied in two cyclonic eddies (CEs) in the Eastern Tropical North AtlanticTryptophan‐like FDOM was an indicator of the CEs' productivity as it correlated with semi‐labile dissolved organic matter and microbial metabolic activitiesHumic‐like FDOM was a by‐product of microbial respiration; its distribution within an offshore CE covaried with nutrient upwelling [ABSTRACT FROM AUTHOR]

Volcanic emissions (ash, gas, aerosols) dispersed in the atmosphere during explosive eruptions generate hazards affecting aviation, human health, air quality, and the environment. We document for the first time the contamination of airspace by very fine volcanic ash due to sequences of transient ash plumes from Mount Etna. The atmospheric dispersal of sub-10 μm (PM10) ash is modelled using the WRF-Chem model, coupled online with meteorology and aerosols and offline with mass eruption rates (MERs) derived from near-vent Doppler radar measurements and inferred plume altitudes. We analyze two sequences of paroxysms with widely varied volcanological conditions and contrasted meteorological synoptic patterns in October–December 2013 and on 3–5 December 2015. We analyze the PM10 ash dispersal simulation maps in terms of time-averaged columnar ash density, concentration at specified flight levels averaged over the entire sequence interval, and daily average concentration during selected paroxysm days at these flight levels. The very fine ash from such eruption sequences is shown to easily contaminate the airspace around the volcano within a radius of about 1000 km in a matter of a few days. Synoptic patterns with relatively weak tropospheric currents lead to the accumulation of PM10 ash at a regional scale all around Etna. In this context, closely interspersed paroxysms tend to accumulate very fine ash more diffusively at a lower troposphere and in stretched ash clouds higher up in the troposphere. Low-pressure, high-winds weather systems tend to stretch ash clouds into ~100 km wide clouds, forming large-scale vortices 800–1600 km in diameter. Daily average PM10 ash concentrations commonly exceed the aviation hazard threshold, up to 1000 km downwind from the volcano and up to the upper troposphere for intense paroxysms. Vertical distributions show ash cloud thicknesses in the range 0.7–3 km, and PM10 sometimes stagnates at ground level, which represent a potential health hazard. [ABSTRACT FROM AUTHOR]

Mt Etna in Sicily hosts a bryophyte floristic richness of 306 taxa, corresponding to 259 mosses, 43 liverworts, and 4 hornworts. Species richness shows a hump-shaped relationship with the elevation, with a peak at 1200–1700 m a.s.l. Chorotype patterns clearly change along an altitudinal gradient, from the Mediterranean, located at 0–300 m a.s.l., to Arctic-montane and boreo-Arctic montane at 1800–2700 m a.s.l., showing a correlation with the bioclimatic belts identified for the Mt Etna. In regard to the life form pattern, the turf species are the most represented in each elevation gradient, except at 2300–2700 m a.s.l. where the tuft species are prevalent. The life strategy pattern shows the colonists as the prevailing species, featured by an increasing trend up to 2200 m of elevation; above this limit, they are exceeded by the perennial stayers. Furthermore, taking into consideration the red-listed species (at the European and/or Italian level), as well as the species of phytogeographical interest, it was possible to identify the high bryophyte conservation priority areas; these areas are located in thermo-Mediterranean and oro-Mediterranean bioclimatic belts, the latter corresponding to the oldest substrates of the volcano where some of the most interesting bryophyte glacial relicts find refuge. [ABSTRACT FROM AUTHOR]

Saponaria sicula Raf. grows in Sicily, Sardinia, and Algeria on limestone cliffs and volcanic sands 1300–2500 m above sea level. The aim of the present study was to investigate how the pedo-climatic conditions influence the micromorphological, phytochemical, and biological properties of Sicilian S. sicula leaves collected in the Madonie Mountains (SsM) and on Etna Mt (SsE). Micromorphological investigations revealed that leaves from SsM had a higher amount of calcium oxalate druses in the mesophyll and a more intense blue–green staining with Toluidine blue O, indicating a higher content of polyphenols. These data were confirmed by phytochemical analyses carried out on hydroalcoholic extracts, which showed a higher content of total phenols (8.56 ± 0.57 g GAE/100 g DE) and flavonoids (6.09 ± 0.17 g RE/100 g DE) in SsM. Sixty-four compounds were identified by LC-DAD-ESI-MS analysis with propelargonidin dimer as the most abundant compound (10.49% and 10.19% in SsM and SsE, respectively). The higher polyphenol content of SsM leaves matches also with their biological activity, identifying SsM extract as the strongest plant complex (IC50 2.75–477.30 µg/mL). In conclusion, the present study experimentally demonstrates that not only climatic differences but also soil characteristics affect the micromorphological, phytochemical, and biological features of this plant species. [ABSTRACT FROM AUTHOR]

Tephra dispersal and fallout resulting from explosive activity of Mt. Etna (Italy) represent a significant threat to the surrounding inhabited areas as well as to aviation operations. An early-warning system aimed at foreseeing the onset of paroxysmal activity has been developed, combining a thermal infrared camera, infrasonic network, and a weather radar. In this way, it is possible to identify the onset of a lava fountain as well as to determine the associated mass eruption rate (MER) and top plume height (HTP). The new methodology, defined as the paroxysmal early-warning (PEW) alert system, is based on the analysis of some explosive eruptions that occurred between 2011 and 2021 at Etna, simultaneously observed by the thermal camera and infrasound systems dislocated around the summit eruptive craters, and by the weather radar, located at about 32 km from the summit craters. This work represents an important step towards the mitigation of the potential impact associated with the tephra dispersal and fallout during paroxysms at Etna, which can be applied to other volcanoes with similar activity and monitoring strategies. [ABSTRACT FROM AUTHOR]

Landslides on the flanks of stratovolcanoes can significantly modify the structure of the volcano. Macroscopic factors that determine the stability of volcanic deposits are well understood, but the microscopic interactions between particles and their impact on deposit cohesion remain poorly understood. Deposit cohesion is related to the energy of interaction between particles, and its calculation depends on the surficial properties of the eruptive materials. The purpose of this study was to perform a preliminary comparative analysis of the surficial properties of volcanic materials from various tectonic settings, including electrical (zeta potential) and thermodynamic (surface free energy) components and to calculate the total interaction energy between particles under different environmental conditions. We analyzed samples of eruptive materials obtained from volcanic flows characteristic of six active volcanoes (El Hierro, Pico Do Fogo, Vulcano, Stromboli, Mt. Etna, and Deception Island). The results show that deposit cohesion varies among volcanoes and changes drastically with the pH of the medium. Among the volcanic systems investigated, El Hierro (pH = 3) has the most cohesive materials, while Mt. Etna (pH = 8) has the least cohesive materials. Our results suggest that microscopic electrical and thermodynamic properties play a role in the stability of volcanic deposits, and confirm the need for a greater research focus in this area. [ABSTRACT FROM AUTHOR]

The south-eastern sector of the Mount Etna, Italy, is characterized by numerous active faults, in particular the Belpasso–Ognina lineament, the Tremestieri–San Gregorio–Acitrezza fault, the Trecastagni fault and the Fiandaca–Nizzeti fault including the Timpe Fault System. Their activity is the result of both volcanism and tectonics. Here, we analyse the ground deformation occurred from 2016 to 2019 across those active faults by using the GNSS data acquired at 22 permanent stations and 35 campaign points observed by the Etna Observatory (INGV) and by the University of Catania. We also use the time-series of line of sight displacement of permanent scatterers SENTINEL-1 A-DInSAR obtained by using the P-SBAS tool of the ESA GEP-TEP (Geohazards Thematic Exploitation Platform) service. We discriminate the contributions of the regional tectonic strain, the inflations, the deflations of the volcano and the gravitational sliding in order to analyse the deformation along the faults of the south-eastern flank of Etna. The shallow and destructive M w = 4.9 earthquake of 2018 December 26 occurred within the studied area two days after a dyke intrusion, that propagated beneath the centre of the volcano accompanied by a short eruption. Both GNSS and InSAR time-series document well those events and allow to investigate the post-seismic sliding across the faults of south-eastern flank. We analyse the slow slip events (SSE) that are observed in the GNSS and InSAR time-series in the vicinity of the Acitrezza fault. We quantify and discuss the tectonic origin of the Belpasso–Ognina lineament that we interpreted as a tear fault. [ABSTRACT FROM AUTHOR]

The search for pre‐eruptive observables that can be used for short‐term volcanic forecast remains a scientific challenge. Pre‐eruptive patterns in seismic data are usually identified by analyzing seismic catalogs (e.g., the number and types of recorded seismic events), the evolution of seismic energy, or changes in the tensional state of the volcanic medium as a consequence of changes in the volume of the volcano. However, although successful volcanic predictions have been achieved, there is still no generally valid model suitable for a large range of eruptive scenarios. In this study, we evaluate the potential use of Shannon entropy as short‐term volcanic eruption forecasting extracted from seismic signals at five well studied volcanoes (Etna, Mount St. Helens, Kilauea, Augustine, and Bezymianny). We identified temporal patterns that can be monitored as short‐term eruptive precursors. We quantified the decay of Shannon entropy prior to eruptions, noting that changes appear between 4 days and 12 hr before. When Shannon entropy is combined with the temporal evolution of other features (i.e., energy, kurtosis, and the frequency index), we can elaborate physical models according to the occurring volcanic processes. Our results show that pre‐eruptive variation in Shannon entropy is a confident short‐term volcanic eruption monitoring tool. Plain Language Summary: Volcanic eruptions represent a major natural hazard. Despite decades of research, the forecasting of volcanic eruptions remains a scientific challenge. Subsurface volcanic processes generate seismic waves, which can be measured at the surface using seismometers. To date, the most successful examples of eruption forecasting have been based on seismic data. However, we still lack a early warning model that can be applied across the wide range of eruption styles seen around the world. In this study, we implemented a new approach for the analysis of seismo‐volcanic data aimed at warning eruptions. We used advanced signal processing algorithms to analyze continuous seismic signals from a suite of well‐studied volcanoes (Mount St. Helens, Mt. Etna, Kilauea, Augustine, and Bezymianny) in order to create a new database of features found within the seismic signals. We found that pre‐eruptive variation in the Shannon entropy (a statistical parameter associated to the coherence of the seismic sources) of seismic signals offers a successfully feature for short‐term volcanic eruption alert. The relationship between pre‐eruptive seismic signals and Shannon entropy is based on changes in the probability distributions of the type of seismic waves, independent of the signal source. Key Points: While successful volcanic forecasting has been achieved, there is no generally valid model suitable for large range of eruptive scenariosWe used feature extraction to analyze seismic data from five well studied volcanoes to identify short‐term eruptive precursorsShannon entropy has a uniform temporal pattern of pre‐eruptive change and is a recurrent and transferable feature [ABSTRACT FROM AUTHOR]

On 13 December 2020, Etna volcano entered a new eruptive phase, giving rise to a number of paroxysmal episodes involving increased Strombolian activity from the summit craters, lava fountains feeding several-km high eruptive columns and ash plumes, as well as lava flows. As of 2 August 2021, 57 such episodes have occurred in 2021, all of them from the New Southeast Crater (NSEC). Each paroxysmal episode lasted a few hours and was sometimes preceded (but more often followed) by lava flow output from the crater rim lasting a few hours. In this paper, we use remote sensing data from the ground and satellite, integrated with ground deformation data recorded by a high precision borehole strainmeter to characterize the 12 March 2021 eruptive episode, which was one of the most powerful (and best recorded) among that occurred since 13 December 2020. We describe the formation and growth of the lava fountains, and the way they feed the eruptive column and the ash plume, using data gathered from the INGV visible and thermal camera monitoring network, compared with satellite images. We show the growth of the lava flow field associated with the explosive phase obtained from a fixed thermal monitoring camera. We estimate the erupted volume of pyroclasts from the heights of the lava fountains measured by the cameras, and the erupted lava flow volume from the satellite-derived radiant heat flux. We compare all erupted volumes (pyroclasts plus lava flows) with the total erupted volume inferred from the volcano deflation recorded by the borehole strainmeter, obtaining a total erupted volume of ~3 × 106 m3 of magma constrained by the strainmeter. This volume comprises ~1.6 × 106 m3 of pyroclasts erupted during the lava fountain and 2.4 × 106 m3 of lava flow, with ~30% of the erupted pyroclasts being remobilized as rootless lava to feed the lava flows. The episode lasted 130 min and resulted in an eruption rate of ~385 m3 s−1 and caused the formation of an ash plume rising from the margins of the lava fountain that rose up to 12.6 km a.s.l. in ~1 h. The maximum elevation of the ash plume was well constrained by an empirical formula that can be used for prompt hazard assessment. [ABSTRACT FROM AUTHOR]

Satellite data provide crucial information to better understand volcanic processes and mitigate associated risks. In recent years, exploiting the growing number of spaceborne polar platforms, several automated volcanic monitoring systems have been developed. These, however, rely on good geometrical and meteorological conditions, as well as on the occurrence of thermally detectable activity at the time of acquisition. A multiplatform approach can thus increase the number of volcanological-suitable scenes, minimise the temporal gap between acquisitions, and provide crucial information on the onset, evolution, and conclusion of both transient and long-lasting volcanic episodes. In this work, we assessed the capabilities of the MEdium Resolution Spectral Imager-II (MERSI-II) sensor aboard the Fengyun-3D (FY-3D) platform to detect and quantify heat flux sourced from volcanic activity. Using the Middle Infrared Observation of Volcanic Activity (MIROVA) algorithm, we processed 3117 MERSI-II scenes of Mount Etna acquired between January 2020 and February 2023. We then compared the Volcanic Radiative Power (VRP, in Watt) timeseries against those obtained by MODIS and VIIRS sensors. The remarkable agreement between the timeseries, both in trends and magnitudes, was corroborated by correlation coefficients (ρ) between 0.93 and 0.95 and coefficients of determination (R2) ranging from 0.79 to 0.84. Integrating the datasets of the three sensors, we examined the effusive eruption of Mount Etna started on 27 November 2022, and estimated a total volume of erupted lava of 8.15 ± 2.44 × 106 m3 with a Mean Output Rate (MOR) of 1.35 ± 0.40 m3 s−1. The reduced temporal gaps between acquisitions revealed that rapid variations in cloud coverage as well as geometrically unfavourable conditions play a major role in thermal volcano monitoring. Evaluating the capabilities of MERSI-II, we also highlight how a multiplatform approach is essential to enhance the efficiency of satellite-based systems for volcanic surveillance. [ABSTRACT FROM AUTHOR]

The survey and structural analysis of surface coseismic ruptures are essential tools for characterizing seismogenic structures. In this work, a procedure to survey coseismic ruptures using satellite interferometric synthetic aperture radar (InSAR) data, directing the survey using Unmanned Aerial Vehicles (UAV), is proposed together with a field validation of the results. The Sentinel-1 A/B Interferometric Wide (IW) Swath TOPSAR mode offers the possibility of acquiring images with a short revisit time. This huge amount of open data is extremely useful for geohazards monitoring, such as for earthquakes. Interferograms show the deformation field associated with earthquakes. Phase discontinuities appearing on wrapped interferograms or loss-of-coherence areas could represent small ground displacements associated with the fault's ruptures. Low-altitude flight platforms such as UAV permit the acquisition of high resolution images and generate 3D spatial geolocalized clouds of data with centimeter-level accuracy. The generated topography maps and orthomosaic images are the direct products of this technology, allowing the possibility of analyzing geological structures from many viewpoints. We present two case studies. The first one is relative to the 2016 central Italian earthquakes, astride which the InSAR outcomes highlighted quite accurately the field displacement of extensional faults in the Mt. Vettore–M. Bove area. Here, the geological effect of the earthquake is represented by more than 35 km of ground ruptures with a complex pattern composed by subparallel and overlapping synthetic and antithetic fault splays. The second case is relative to the Mt. Etna earthquake of 26 December 2018, following which several ground ruptures were detected. The analysis of the unwrapped phase and the application of edge detector filtering and other discontinuity enhancers allowed the identification of a complex pattern of ground ruptures. In the Pennisi and Fiandaca areas different generation of ruptures can be distinguished, while previously unknown ruptures pertaining to the Acireale and Ragalna faults can be identify and analyzed. [ABSTRACT FROM AUTHOR]

Lava fountains at the Etna volcano are spectacular eruptive events characterized by powerful jets that expel hot mixtures of solid particles and volcanic gases, easily reaching stratospheric heights. Ash dispersal and fallout of solid particles affect the inhabited areas, often causing hazards both to infrastructure and to air and vehicular traffic. We focus on the extraordinary intense and frequent eruptive activity at Etna in the period of December 2020–February 2022, when more than 60 lava fountain events occurred with various ejected magma volume and lava fountain height and duration. Differences among the events are also imprinted in tiny ground deformations caught by strain signals recorded concurrently with the lava fountain events, reflecting a strict relationship with their evolution. To characterize this variability, which denotes changes in the eruption style, we clustered the lava fountain events using the k -means algorithm applied on the strain signal. A novel procedure was developed to ensure a high-quality clustering process and obtain robust results. The analysis identified four groups of strain variations which stand out for their amplitude, duration and time derivative of the signal. The temporal distribution of the clusters highlighted a transition in different types of eruptions, thus revealing the importance of clustering the strain variations for monitoring the volcano activity and evaluating the associated hazards. [ABSTRACT FROM AUTHOR]

The South-East Crater (SEC) at Mt. Etna started a period of lava fountaining in December 2020, producing over 60 paroxysms until February 2022. The activity had an intense sequence from February 16 to April 1, 2021, totaling 17 paroxysmal events separated by repose times varying from 1 to 7 days. The eruptive sequence was extensively monitored, providing a unique opportunity to relate the chemistry and texture of the erupted products to eruption dynamics. We investigate the temporal evolution of the magmatic system through this eruptive sequence by quantifying variations in the composition and texture of clinopyroxene. Clinopyroxene major element transects across crystals from five representative lava fountains allow us to determine the relative proportions of deep versus shallow-stored magmas that fed these events. We use hierarchical clustering (HC), an unsupervised machine learning technique, to objectively identify clinopyroxene compositional clusters and their variations during this intense eruptive phase. Our results show that variations of monitoring parameters and eruption intensity are expressed in the mineral record both as changes in cluster proportions and the chemical complexity of single crystals. We also apply random forest thermobarometry to relate each cluster to P-T conditions of formation. We suggest that the February–April 2021 eruptive sequence was sustained by the injection of a hotter and deeper magma into a storage area at 1–3 kbar, where it mixed with a slightly more evolved magma. The February 28 episode emitted the most mafic magma, in association with the highest mean lava fountain height and highest time–averaged discharge rate, which make it the peak of the analyzed eruptive interval. Our results show that after this episode, the deep magma supply decreased and the erupted magma become gradually more chemically evolved, with a lower time–average discharge rate and fountain height. We propose this approach as a means to rapidly, objectively, and effectively link petrological and geophysical/geochemical monitoring during ongoing eruptions. We anticipate that the systematic application of this approach will serve to shed light on the magmatic processes controlling the evolution of ongoing eruptions. [ABSTRACT FROM AUTHOR]

Accurate forecasting of volcanic particle (tephra) dispersal and fallout requires a reliable estimation of key Eruption Source Parameters (ESPs) such as the Mass Eruption Rate (QM). QM is usually estimated from the Top Plume Height (HTP) using empirical and analytical models. For the first time, we combine estimates of HTP and QM derived from the same sensor (radar) with mean wind velocity values (vW) for lava‐fountain fed tephra plumes associated with 32 paroxysms of Mt. Etna (Italy) to develop a new statistical model based on a Markov Chain Monte Carlo approach for model parameter estimation. This model is especially designed for application to radar data to quickly infer QM from observed HTP and vW, and estimate the associated uncertainty. It can be easily applied and adjusted to data retrieved by radars worldwide, improving our capacity to quickly estimate QM and related uncertainties required for the tephra dispersal hazard. Plain Language Summary: New radar‐based statistical model useful to quickly infer the mass eruption rate, usually the key parameter to initialize the tephra dispersion model, from the volcanic plume height during the eruptions. Key Points: X‐band radar observations of explosive eruptions can be used to estimate the eruption source parameters and associated uncertaintiesUsing the Markov Chain Monte Carlo model can be performed the statistical analysis of time seriesStatistical parametric model to infer the mass eruption rate from the measured top plume height [ABSTRACT FROM AUTHOR]