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Quantification of CO2 degassing and atmospheric dispersion at Caldeiras da Ribeira Grande (São Miguel Island, Azores)
No full textCaldeiras da Ribeira Grande is one of the degassing areas of Fogo, a trachytic central volcano located at Sa ̃o Miguel Island (Azores archipelago). Recently, new steam emissions, soil CO2 and temperature anomalies developed towards the inhabited area, causing high indoor CO2 values and affecting the vegetation and several small animals that were found dead in depressions and low-ventilated zones. During July–August 2021, a soil CO2 flux survey was carried out on the north flank of the volcano, estimating a soil gas release of at least 40 t d− 1 (excluding the contribution of the fumaroles) over an area of ~0.27 km2. Two populations for the CO2 released were found, highlighting the biogenic and volcanic-hydrothermal origins. General NW-SE diffuse degassing structures (DDS) were identified, in agreement with the tectonic lineaments previously recognized in the area. In this regard, we investigated the passive gas dispersion in the atmosphere at Caldeiras da Ribeira Grande per- forming a model validation aimed to estimate the fumarolic gas flux at source and the potential hazard for human and animal lives posed by CO2. Numerical simulations were carried out with the DISGAS-2.3, a 3D Eulerian advection-diffusion model, and the relative outputs processed through the VIGIL-1.3 workflow able to provide probabilistic long-term CO2 concentration maps, considering a meteorological variability over the last 30 years (1991–2020) taken from the ECMWF ERA5 reanalysis dataset. A best-fit between observed and simulated CO2 concentrations allowed us to estimate the total gas flux of the area (~209 t d− 1) obtained by scaling the soil CO2 gas flux by a factor 30. Such an estimate is composed of ~174 t d− 1 as unknown fumarolic and ~ 35 td− 1 as diffuse contribution, in a good agreement with measurements.
Although the present-day CO2 concentration at 0.3 m height cannot be considered to raise serious concerns for human health, we reasonably infer that the death of small animals may be due to local conditions of CO2 accumulation or to the presence of H2S. The current study highlights the relevance of coupling gas flux maps, concentration data, and gas dispersion modeling to obtain robust estimation of gas fluxes, including the fuma- rolic contribution, and identify zones potentially impacted by dangerous concentrations of volcanic gases, which are relevant for land-use planning and hazard assessment in case of renewed escalations of volcanic activity.Published1078076V. Pericolosità vulcanica e contributi alla stima del rischioJCR Journa
Timescale of Emplacement and Rheomorphism of the Green Tuff Ignimbrite (Pantelleria, Italy)
No full textWe present a multidisciplinary study based on Differential Scanning Calorimetry (DSC), paleomagnetic analysis, and numerical modeling to gain information on the timescales of syn- and post-depositional ductile deformation of the strongly welded and rheomorphic Green Tuff ignimbrite (GT; Pantelleria, Italy). DSC measurements allow the determination of glass fictive temperatures (Tf; i.e., the parameter accounting for the cooling dependence of glass structure and properties). Using a T -based f geospeedometry procedure, we infer the cooling rate (qc) experienced by the glassy phases in different lithofacies within the GT formation. Glass shards from the basal pumice fall deposit record a fast qc of ∼10°C/s. In contrast, the ignimbrite body returns slow qc values depending on the stratigraphic position and lithofacies (basal/upper vitrophyres, fiamme-rich and rheomorphic layers), ranging from ∼10−2 to ∼10−6 °C/s. Moreover,
paleomagnetic analyses of the natural remanent magnetization of ignimbrite matrix and embedded lithic clasts indicate an emplacement temperature higher than 550–600°C. By integrating calorimetric and paleomagnetic datasets, we constrain a conductive cooling model, describing the ignimbrite's temperature-time-viscosity (T–t–η) evolution from the eruptive temperature to below Tf. Outcomes suggest that the upper and basal vitrophyres deformed and quenched over hours, indicating that the entire GT underwent intense syn-depositional ductile deformation. Furthermore, the central body remained above T for a much longer timespan (>1 month), enabling post-emplacement rheomorphic flow. Lastly, we discuss the critical role of mechanisms such as shear heating and retrograde solubility of volatiles, in locally controlling the rheological behavior of the GT.Publishede2022JB0262571A. Geomagnetismo e PaleomagnetismoJCR Journa
Health impact of natural gas emission at Cava dei Selci residential zone (metropolitan city of Rome, Italy)
No full textNatural gas hazard was assessed at Cava dei Selci, a residential neighbourhood of Marino (Rome) by a joint study of gas emissions and related health problems. Here a densely urbanized zone with 4000 residents surrounds a dangerous natural gas discharge where, along the years, dozens of animals were killed by the gas. Gas originates from Colli Albani volcano and consists mostly of CO2 with ~1 vol.% of H2S. In recent years, several gas-related accidents occurred in the urbanized zone (gas blowouts and road collapses). Some houses were evacuated because of hazardous indoor air gas concentration. Gas hazard was assessed by soil CO2 flux and concentration surveys and indoor and outdoor air CO2 and H2S concentration measurements. Open fields and house gardens release a high quantity of CO2 (32.23 tonnes*day-1). Inside most houses, CO2 air concentration exceeds 0.1 vol.%, the acceptable long-term exposure range. In several houses both CO2 and H2S exceed the IDLH level (Immediately Dangerous to Life and Health). An epidemiological cohort study was carried out on the residents of two Cava dei Selci zones with high (ZoneA) and medium (ZoneB) gas hazard exposure, using the rest of Marino as reference zone. We found excess mortality and Emergency Room Visits (ERV) related to high exposure to CO2 and H2S; in particular , an increased risk of mortality and ERV for diseases of central nervous system (HR 1.57, 95% CI 0.76-3.25 and HR 5.82, 95% CI 1.27-26.56 respectively) was found among men living in Zone A.Published707–7296A. Geochimica per l'ambiente e geologia medicaJCR Journa
Tracking of the huge Antarctic iceberg A-76
No full textThis paper presents a processing scheme whose aim is to provide the basis for a fast time-series analysis of iceberg drifting patterns. The study focuses on the drifting of iceberg A-76 and makes use of SAR images which were collected by the Sentinel-1 satellites, from May 2021 to June 2022. The processing scheme is composed of the following steps: a) image pre-processing by morphological theory; b) contextual analysis for performing the segmentation task; and c) regularization of the derived label field. The implemented processing scheme incorporates a further step for measuring the drift trajectory and a geometric characterization of the iceberg’s shape.Published10-205A. Ricerche polari e paleoclimaJCR Journa
Distribution of the invasive alien species Cotula coronopifolia L. (Asteraceae) relating to water halinity and sodicity in the Variconi wetland (Campania, southern Italy)
No full textInvasive alien species represent one of the main environmental threats to native biodiversity and can also strongly alter the biogeochemical cycles within an ecosystem. This study aims to define the distribution of the invasive alien species Cotula cor-onopifolia L. within the protected wetland "Variconi" (Campania region, southern Italy) and evaluate the potential role of water geochemical features as interpretation tools for pattern distribution. The presence of C. coronopifolia was assessed in the field, and a distribution map was drawn; concomitantly thirty-nine water samples were collected from groundwater and surface water bodies for chemical analyses. The results showed that C. coronopifolia preferentially colonized the sector of the wetland characterized by high halinity, while it is totally absent in retrodunal and sandy coastal area with very high halinity. The cartography presented can be used as a tool to help target future management interventions. Through our multidisciplinary approach, new evidence has been provided on the ecology of this invasive alien plant that occupies several wetlands worldwide. The replicability of this method may be useful to assess the level of invasion of an alien species but also to predict its evolution as a function of environmental parameters.Published1653–1668JCR Journa
The EU Center of Excellence for Exascale in Solid Earth (ChEESE): Implementation, results, and roadmap for the second phase
No full textThe EU Center of Excellence for Exascale in Solid Earth (ChEESE) develops exascale transition capabilities in the domain of Solid Earth, an area of geophysics rich in computational challenges embracing different approaches to exascale (capability, capacity, and urgent computing). The first implementation phase of the project (ChEESE-1P; 2018–2022) addressed scientific and technical computational challenges in seismology, tsunami science, volcanology, and magnetohydrodynamics, in order to understand the phenomena, anticipate the impact of natural disasters, and contribute to risk management. The project initiated the optimisation of 10 community flagship codes for the upcoming exascale systems and implemented 12 Pilot Demonstrators that combine the flagship codes with dedicated workflows in order to address the underlying capability and capacity computational challenges. Pilot Demonstrators reaching more mature Technology Readiness Levels (TRLs) were further enabled in operational service environments on critical aspects of geohazards such as long-term and short-term probabilistic hazard assessment, urgent computing, and early warning and probabilistic forecasting. Partnership and service co-design with members of the project Industry and User Board (IUB) leveraged the uptake of results across multiple research institutions, academia, industry, and public governance bodies (e.g. civil protection agencies). This article summarises the implementation strategy and the results from ChEESE-1P, outlining also the underpinning concepts and the roadmap for the on-going second project implementation phase (ChEESE-2P; 2023–2026).EUPublished47-61OSV1: Verso la previsione dei fenomeni vulcanici pericolosiJCR Journa
Volcanic Cloud Detection and Retrieval Using Satellite Multisensor Observations
No full textSatellite 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 10 11 kg (MLE method) and 1.32 ± 0.47 10 11 kg (NN method) for Kelud; 4.48 ± 1.61 10 10 kg (MLE method) and 4.32 ± 1.56 10 10 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.Published8885V. Processi eruttivi e post-eruttiviJCR Journa
Complex Systems Methods Characterizing Nonlinear Processes in the Near-Earth Electromagnetic Environment: Recent Advances and Open Challenges
No full textLearning from successful applications of methods originating in statistical mechanics, com- plex systems science, or information theory in one scientific field (e.g., atmospheric physics or climatology) can provide important insights or conceptual ideas for other areas (e.g., space sciences) or even stimulate new research questions and approaches. For instance, quantification and attribution of dynamical complexity in output time series of nonlinear dynamical systems is a key challenge across scientific disciplines. Especially in the field of space physics, an early and accurate detection of characteristic dissimilarity between nor- mal and abnormal states (e.g., pre-storm activity vs. magnetic storms) has the potential to vastly improve space weather diagnosis and, consequently, the mitigation of space weather hazards.
This review provides a systematic overview on existing nonlinear dynamical systems- based methodologies along with key results of their previous applications in a space physics context, which particularly illustrates how complementary modern complex systems ap- proaches have recently shaped our understanding of nonlinear magnetospheric variability. The rising number of corresponding studies demonstrates that the multiplicity of nonlin- ear time series analysis methods developed during the last decades offers great potentials for uncovering relevant yet complex processes interlinking different geospace subsystems, variables and spatiotemporal scales.Published381A. Geomagnetismo e PaleomagnetismoJCR Journa
A Seismo-Stratigraphic Analysis of the Relict Deposits of the Cilento Continental Shelf (Southern Italy)
No full textThe relict (palimpsest and lowstand) deposits of the Cilento continental shelf were analyzed based on the geological interpretation of Sub-Bottom Chirp sections, calibrated with core data. A progradational unit, which is overlying the acoustic basement, is interpreted as the beach deposits of the isotopic stages 4 and 5. This unit is overlain by a seismo-stratigraphic unit, which is composed of coarse-grained organogenic sands and interpreted as relict sands. This unit consists of sandy ridges, occurring at water depths ranging between 130 and 140 m, and was interpreted as an example of submerged beach deposits, genetically related to the marine isotopic stage 2 (Last Glacial Maximum; starting date 29 ky B.P.).Published87Virtual conference1T. Struttura della TerraN/A or not JC
Graph neural networks for multivariate time series regression with application to seismic data
No full textMachine learning, with its advances in deep learning has shown great potential in analyzing time series. In many scenarios, however, additional information that can potentially improve the predictions is available. This is crucial for data that arise from e. g., sensor networks that contain information about sensor locations. Then, such spatial information can be exploited by modeling it via graph structures, along with the sequential (time series) information. Recent advances in adapting deep learning to graphs have shown potential in various tasks. However, these methods have not been adapted for time series tasks to a great extent. Most attempts have essentially consolidated around time series forecasting with small sequence lengths. Generally, these architectures are not well suited for regression or classification tasks where the value to be predicted is not strictly depending on the most recent values, but rather on the whole length of the time series. We propose TISER-GCN, a novel graph neural network architecture for processing, in particular, these long time series in a multivariate regression task. Our proposed model is tested on two seismic datasets containing earthquake waveforms, where the goal is to predict maximum intensity measurements of ground shaking at each seismic station. Our findings demonstrate promising results of our approach—with an average MSE reduction of 16.3%—compared to the best performing baselines. In addition, our approach matches the baseline scores by needing only half the input size. The results are discussed in depth with an additional ablation study.Interreg North-West Europe program (Interreg NWE), project Di-Plast - Digital Circular Economy for the Plastics Industry (NWE729).
INGV Pianeta Dinamico 2021 Tema 8 SOME (CUP D53J1900017001) funded by Italian Ministry of University and Research “Fondo finalizzato al rilancio degli investimenti delle amministrazioni centrali dello Stato e allo sviluppo del Paese, legge 145/2018.Published317–3328T. Sismologia in tempo reale e Early Warning Sismico e da TsunamiJCR Journa