Prestifilippo, Michele

Mt. Etna, in Italy, is one of the most active volcanoes in the world, producing several explosive events in recent years. Those eruptions form high eruption columns that often reach the top of the troposphere (and sometimes even the lower part of the stratosphere) and create several disruptions to air traffic, mainly to the Fontanarossa International Airport in Catania, which is about 20 NM (~ 37 km; NM = Nautical Miles) away from the summit craters and is located in the main wind direction. In Italy, the institution responsible for volcano monitoring is the Istituto Nazionale di Geofisica e Vulcanologia (INGV). In 2007, the INGV, Osservatorio Etneo (INGV-OE) in Catania was appointed as “State Volcano Observatory” (SVO) and, in 2014, sent the first Volcano Observatory Notice for Aviation (VONA) message. Since that moment, several VONA messages have been sent, mainly due to the high frequency of Etna activity. In order to facilitate and speed in the generation and the dispatch of the VONA messages, a computer-assisted procedure has been designed and built to help the work done by the volcanologist on duty and by the two shift workers of the 24/7 Control Room of INGV-OE. Consequently, information on the explosive activity can be quickly provided to the Volcanic Ash Advisory Center (VAAC) in Toulouse and national air traffic offices, reducing risks to aviation operations. In this work, we describe how the computer-assisted procedure works, addressing the main advantages and possible improvements. We retain that a similar approach could be easily applied to other volcano observatories worldwide.

Volcano-seismic signals can help for volcanic hazard estimation and eruption forecasting. However, the underlying mechanism for their low frequency components is still a matter of debate. Here, we show signatures of dynamic strain records from Distributed Acoustic Sensing in the low frequencies of volcanic signals at Vulcano Island, Italy. Signs of unrest have been observed since September 2021, with CO2 degassing and occurrence of long period and very long period events. We interrogated a fiber-optic telecommunication cable on-shore and off-shore linking Vulcano Island to Sicily. We explore various approaches to automatically detect seismo-volcanic events both adapting conventional algorithms and using machine learning techniques. During one month of acquisition, we found 1488 events with a great variety of waveforms composed of two main frequency bands (from 0.1 to 0.2 Hz and from 3 to 5 Hz) with various relative amplitudes. On the basis of spectral signature and family classification, we propose a model in which gas accumulates in the hydrothermal system and is released through a series of resonating fractures until the surface. Our findings demonstrate that fiber optic telecom cables in association with cutting-edge machine learning algorithms contribute to a better understanding and monitoring of volcanic hydrothermal systems.

This work presents the first results of the PANACEA project regarding the assessment of different volcano-related hazards at Mt. Etna (lava and pyroclastic flows, tephra fallout and earthquakes) by exploiting data deriving from the volcano’s history with accurate physical–mathematical models. Volcano-related hazards are distributed differently on Etna—from the deserted summit area down to the densely populated flanks—but must be considered together for long-term territorial planning.

Video cameras provide vital information on volcanic plumes from explosive eruptions, such as plume height, for monitoring and research. These images must be calibrated to get accurate quantitative data. However, the presence of wind complicates any calibration as the plume may no longer lie in the image plane, i.e. a plane perpendicular to the camera’s line-of-sight. Here, we present a simple new tool to correct for the effect of wind on the position and height of a volcanic plume as determined from imagery by rotating the image plane to be in the direction of the wind. We show the importance of accounting for the effect of wind on the maximum plume height determined from videos for two case-studies; a Vulcanian explosion from Sabancaya volcano, Peru, and a sustained plume from Mount Etna, Italy. This tool can improve the accuracy of quantitative information extracted from images of volcanic plumes, and should prove useful for both research and monitoring purposes.

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.

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.

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.

The Istituto Nazionale di Geofisica e Vulcanologia (INGV) is an Italian research institution with focus on earth sciences. Moreover, the INGV is the operational center for seismic surveillance and earthquake monitoring in Italy and is a part of the civil protection system as a center of expertise on seismic, volcanic, and tsunami risks.INGV operates the Italian National Seismic Network and other networks at national scale and is a primary node of the European Integrated Data Archive for archiving and distributing strong‐motion and weak‐motion seismic recordings. In the control room in Rome, INGV staff performs seismic surveillance and tsunami warning services; in Catania and Naples, the control rooms are devoted to volcanic surveillance. Volcano monitoring includes locating earthquakes in the regions around the Sicilian (Etna, Eolian Islands, and Pantelleria) and the Campanian (Vesuvius, Campi Fregrei, and Ischia) active volcanoes. The tsunami warning is based on earthquake location and magnitude (M) evaluation for moderate to large events in the Mediterranean region and also around the world. The technologists of the institute tuned the data acquisition system to accomplish, in near real time, automatic earthquake detection, hypocenter and magnitude determination, and evaluation of several seismological products (e.g., moment tensors and ShakeMaps). Database archiving of all parametric results is closely linked to the existing procedures of the INGV seismic surveillance environment and surveillance procedures. Earthquake information is routinely revised by the analysts of the Italian seismic bulletin. INGV provides earthquake information to the Department of Civil Protection (Dipartimento di Protezione Civile) to the scientific community and to the public through the web and social media. We aim at illustrating different aspects of earthquake monitoring at INGV: (1) network operations; (2) organizational structure and the hardware and software used; and (3) communication, including recent developments and planned improvements.

Mobile network routers in seismic and volcanic surveillance

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 e ective radius of about 7 m. 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.