Search Results (20)

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. Full article

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. Full article

During explosive eruptions, tephra fallout represents one of the main volcanic hazards and can be extremely dangerous for air traffic, infrastructures, and human health. Here, we present a new technique aimed at identifying the area covered by tephra after an explosive event, based on processing PlanetScope imagery. We estimate the mean reflectance values of the visible (RGB) and near infrared (NIR) bands, analyzing pre- and post-eruptive data in specific areas and introducing a new index, which we call the ‘Tephra Fallout Index (TFI)’. We use the Google Earth Engine computing platform and define a threshold for the TFI of different eruptive events to distinguish the areas affected by the tephra fallout and quantify the surface coverage density. We apply our technique to the eruptive events occurring in 2021 at Mt. Etna (Italy), which mainly involved the eastern flank of the volcano, sometimes two or three times within a day, making field surveys difficult. Whenever possible, we compare our results with field data and find an optimal match. This work could have important implications for the identification and quantification of short-term volcanic hazard assessments in near real-time during a volcanic eruption, but also for the mapping of other hazardous events worldwide. Full article

Increasing the economic and environmental sustainability of irrigated agriculture is a vital challenge for the Mediterranean crop production sector. This study explores the effects of the adoption of reclaimed water (RW) as source of irrigation in conjunction with the application of deficit irrigation strategies in an olive orchard (different genotypes) located within the “Valle dei Margi” farmhouse (Eastern Sicily). Specifically, the RW was obtained in situ by treating the wastewater coming from the farmhouse throughout a nature-based treatment wetland system (TW). The effects of RW on crop water status (CWS) was assessed by conducting plant-based measurements (i.e., leaf water potential, Ψ; and leaves’ relative water content, RWC) and determining satellite-based biophysical indicators. An economic and environmental evaluation of the proposed sustainable irrigation practices was carried out using the life cycle assessment (LCA) approach. The RW quality showed high variability due to fluctuations in the number of customers at the farmhouse during the COVID-19 pandemic period. A strong impact on the variation in Ψ was observed among the olive orchard under the different water regimes, evidencing how CWS performances are conditioned by the genotype. However, no differences in leaves’ RWC and in satellite-based biophysical indicators were detected. Finally, the results of the LCA analysis underlined how the use of RW may permit us to obtain important economic and environmental gains, representing an added value for olive growing for operating in accordance to more sustainable development models. Full article

Forecasting volcanic ash transport is crucial for aviation, but its accuracy is subject to both the prevailing wind fields and the knowledge of the source term of the eruption, i.e., variation of emission rate and column height with time. In this study, we use data from the high spectral resolution lidar (HSRL) in space, Aeolus, to examine their impact on the estimation of the emission rates of volcanic particles through inversion techniques. For the inverse modelling, we couple the output of the FLEXPART Lagrangian particle dispersion model with lidar observations towards estimating the emission rates of volcanic particles released from an Etna eruption. The case study used here is the Etna eruption on the 12 March 2021, well captured by the ground-based lidar station of the PANGEA observatory located at the remote island of Antikythera in Greece, downwind of the Etna volcano. It is concluded that the inversion algorithm with Aeolus wind fields assimilation optimizes both the vertical emission distribution and the Etna emission rates. Full article

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 (H_TP). 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. Full article

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. Full article

Between 2020 and 2022, more than sixty lava fountains occurred at Mt. Etna (Italy), which formed high eruption columns rising up to 15 km above sea level (a.s.l.). During those events, several ballistics fell around the summit craters, sometimes reaching touristic areas. The rather frequent activity poses questions on how the impact associated with the fallout of those particles, can be estimated. In this work, we present field data collected soon after the lava fountain on 21 February 2022. This event produced a volcanic plume of about 10 km a.s.l. which was directed toward the southeast. Several ballistics fell in the area of the Barbagallo Craters (just southeast of the summit area at around 2900 m a.s.l.), which is one of the most popular touristic areas on Etna. Hence, we collected several samples and performed laboratory analyses in order to retrieve their size, shape and density. Those values together with a quantitative analysis of the lava fountain were compared with results obtained by a free-available calculator of ballistic trajectories named the ‘Eject!’. A similar approach was hence applied to other lava fountains of the 2020–2022 sequence for which the fallout of large clasts was reported. This work is a first step to identifying in near real-time the area affected by the fallout of ballistics during Etna lava fountains and quantifying their hazard. Full article

Satellite microwave (MW) and millimetre-wave (MMW) passive sensors can be used to detect volcanic clouds because of their sensitivity to larger volcanic particles (i.e., size bigger than 20 µm). In this work, we combine the MW-MMW observations with thermal-infrared (TIR) radiometric data from the Low Earth Orbit (LEO) spectroradiometer to have a complete characterisation of volcanic plumes. We describe new physical-statistical methods, which combine machine learning techniques, aimed at detecting and retrieving volcanic clouds of two highly explosive eruptions: the 2014 Kelud and 2015 Calbuco test cases. For the detection procedure, we compare the well-known split-window methods with a machine learning algorithm named random forest (RF). Our work highlights how the machine learning method is suitable to detect volcanic clouds using different spectral signatures without fixing a threshold. Moreover, the RF model allows images to be automatically processed with promising results (90% of the area correctly identified). For the retrieval procedure of the mass of volcanic particles, we consider two methods, one based on the maximum likelihood estimation (MLE) and one using the neural network (NN) architecture. Results show a good comparison of the mass obtained using the MLE and NN methods for all the analysed bands. Summing the MW-MMW and TIR estimates, we obtain the following masses: 1.11 ± 0.40 × 10¹¹ kg (MLE method) and 1.32 ± 0.47 × 10¹¹ kg (NN method) for Kelud; 4.48 ± 1.61 × 10¹⁰ kg (MLE method) and 4.32 ± 1.56 × 10¹⁰ kg (NN method) for Calbuco. This work shows how machine learning techniques can be an effective tool for volcanic cloud detection and how the synergic use of the TIR and MW-MMW observations can give more accurate estimates of the near-source volcanic clouds. Full article

Between 13 December 2020 and 21 February 2022, Etna volcano produced a sequence of 66 paroxysmal explosive eruptions, with Strombolian activity at the summit craters climaxing in lava fountains and eruption columns extending several kilometers above the craters, accompanied by minor and short-lasting lava flows from the crater rim. We selected three of these episodes that occurred within a short space of time, between 13 December 2020 and 12 March 2021, of different magnitude (i.e., erupted volume) and intensity (i.e., mass eruption rate or instantaneous eruption rate), and analyzed them from a multidisciplinary perspective. The aim was to gain insights into those parameters that mostly reveal the eruptive process for hazard assessment purposes. The multidisciplinary data consist of calibrated visible images, thermal images, seismic and infrasound data, ground deformation detected from the strainmeters, as well as satellite SEVIRI images. From these data, we obtained the timing of each paroxysmal event, the erupted volume in terms of tephra and lava flows, and the corresponding deflation of the source region, together with the development of the lava fountains and eruption columns with time. The results enabled determining that the smallest episode was that of 13 December 2020, which comprised three distinctive pulses but did not produce an eruptive column detectable from either monitoring cameras or satellites. The 28 February 2021 episode was remarkable for the short amount of time required to reach the climax, and was the most intense, whereas the 12 March 2021 event showed the longest duration but with an intensity between that of the previous two. Our results show that these three paroxysmal events display a typical trend, with the first event also being the smallest in terms of both erupted volume and intensity, the second being the most intense, and the third the one of greatest magnitude but less intense than the second. This is coherent with the end of the first paroxysmal phase on 1 April 2021, which was followed by 48 days of eruptive pause before starting again. In this context, the end of the paroxysmal phase was anticipated by a more effusive episode, thus heralding a temporary decline in the gas content within the feeding magma batch. Full article

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. Full article

Multi-sensor strategies are key to the real-time determination of eruptive source parameters (ESPs) of explosive eruptions necessary to forecast accurately both tephra dispersal and deposition. To explore the capacity of these strategies in various eruptive conditions, we analyze data acquired by two Doppler radars, ground- and satellite-based infrared sensors, one infrasound array, visible video-monitoring cameras as well as data from tephra-fallout deposits associated with a weak and a strong paroxysmal event at Mount Etna (Italy). We find that the different sensors provide complementary observations that should be critically analyzed and combined to provide comprehensive estimates of ESPs. First, all measurements of plume height agree during the strong paroxysmal activity considered, whereas some discrepancies are found for the weak paroxysm due to rapid plume and cloud dilution. Second, the event duration, key to convert the total erupted mass (TEM) in the mass eruption rate (MER) and vice versa, varies depending on the sensor used, providing information on different phases of the paroxysm (i.e., unsteady lava fountaining, lava fountain-fed tephra plume, waning phase associated with plume and cloud expansion in the atmosphere). As a result, TEM and MER derived from different sensors also correspond to the different phases of the paroxysms. Finally, satellite retrievals for grain-size can be combined with radar data to provide a first approximation of total grain-size distribution (TGSD) in near real-time. Such a TGSD shows a promising agreement with the TGSD derived from the combination of satellite data and whole deposit grain-size distribution (WDGSD). Full article

Lidar observations are very useful to analyse dispersed volcanic clouds in the troposphere mainly because of their high range resolution, providing morphological as well as microphysical (size and mass) properties. In this work, we analyse the volcanic cloud of 18 May 2016 at Mt. Etna, in Italy, retrieved by polarimetric dual-wavelength Lidar measurements. We use the AMPLE (Aerosol Multi-Wavelength Polarization Lidar Experiment) system, located in Catania, about 25 km from the Etna summit craters, pointing at a thin volcanic cloud layer, clearly visible and dispersed from the summit craters at the altitude between 2 and 4 km and 6 and 7 km above the sea level. Both the backscattering and linear depolarization profiles at 355 nm (UV, ultraviolet) and 532 nm (VIS, visible) wavelengths, respectively, were obtained using different angles at 20°, 30°, 40° and 90°. The proposed approach inverts the Lidar measurements with a physically based inversion methodology named Volcanic Ash Lidar Retrieval (VALR), based on Maximum-Likelihood (ML). VALRML can provide estimates of volcanic ash mean size and mass concentration at a resolution of few tens of meters. We also compared those results with two methods: Single-variate Regression (SR) and Multi-variate Regression (MR). SR uses the backscattering coefficient or backscattering and depolarization coefficients of one wavelength (UV or VIS in our cases). The MR method uses the backscattering coefficient of both wavelengths (UV and VIS). In absence of in situ airborne validation data, the discrepancy among the different retrieval techniques is estimated with respect to the VALR ML algorithm. The VALR ML analysis provides ash concentrations between about 0.1 μg/m³ and 1 mg/m³ and particle mean sizes of 0.1 μm and 6 μm, respectively. Results show that, for the SR method differences are less than <10%, using the backscattering coefficient only and backscattering and depolarization coefficients. Moreover, we find differences of 20–30% respect to VALR ML, considering well-known parametric retrieval methods. VALR algorithms show how a physics-based inversion approaches can effectively exploit the spectral-polarimetric Lidar AMPLE capability. Full article

Between 30 May and 6 June 2019 a series of new flanks eruptions interested the south-east flanks of Mt. Etna, Italy, forming lava flows and explosive activity that was most intense during the first day of the eruption; as a result, volcanic particles were dispersed towards Greece. Lidar measurements performed at the PANhellenic GEophysical observatory of Antikythera (PANGEA) of the National Observatory of Athens (NOA), in Greece, reveal the presence of particles of volcanic origin above the area the days following the eruption. FLEXible PARTicle dispersion model (FLEXPART) simulations and satellite-based SO₂ observations from the TROPOspheric Monitoring Instrument onboard the Sentinel-5 Precursor (TROPOMI/S5P), confirm the volcanic plume transport from Etna towards PANGEA and possible mixing with co-existing desert dust particles. Lidar and modeled values are in agreement and the derived sulfate mass concentration is approximately 15 μg/m³. This is the first time that Etna volcanic products are monitored at Antikythera station, in Greece with implications for the investigation of their role in the Mediterranean weather and climate. Full article

Volcanic emissions are a well-known hazard that can have serious impacts on local populations and aviation operations. Whereas several remote sensing observations detect high-intensity explosive eruptions, few studies focus on low intensity and long-lasting volcanic emissions. In this work, we have managed to fully characterize those events by analyzing the volcanic plume produced on the last day of the 2018 Christmas eruption at Mt. Etna, in Italy. We combined data from a visible calibrated camera, a multi-wavelength elastic/Raman Lidar system, from SEVIRI (EUMETSAT-MSG) and MODIS (NASA-Terra/Aqua) satellites and, for the first time, data from an automatic sun-photometer of the aerosol robotic network (AERONET). Results show that the volcanic plume height, ranging between 4.5 and 6 km at the source, decreased by about 0.5 km after 25 km. Moreover, the volcanic plume was detectable by the satellites up to a distance of about 400 km and contained very fine particles with a mean effective radius of about 7 µm. In some time intervals, volcanic ash mass concentration values were around the aviation safety thresholds of 2 × 10⁻³ g m⁻³. Of note, Lidar observations show two main stratifications of about 0.25 km, which were not observed at the volcanic source. The presence of the double stratification could have important implications on satellite retrievals, which usually consider only one plume layer. This work gives new details on the main features of volcanic plumes produced during low intensity and long-lasting volcanic plume emissions. Full article