Novembre 2022

PubAIV 2022
(aggiornamento di Novembre 2022)

1) Magmi e sistemi di alimentazione (1 articolo) 
2) Dinamiche eruttive e di messa in posto (3 articoli)
3) Geologia e struttura dei vulcani (0 articoli)
4) Monitoraggio, pericolosità e rischio vulcanico (1 articolo)

Tematica 1: Magmi e sistemi di alimentazione
Langhammer D., Di Genova D., Steinle-Neumann G. (2022)
Modelling viscosity of volcanic melts with artificial neural networks.
Geochemistry, Geophysics, Geosystems
Data di pubblicazione: 19/11/2022
PubAIV-ID-00089 - Articolo in Rivista (open access)

Viscosity is of great importance in governing the dynamics of volcanoes, including their eruptive style. The viscosity of a volcanic melt is dominated by temperature and chemical composition, both oxides and water content. The changes in melt structure resulting from the interactions between the various chemical components are complex, and the construction of a physical viscosity model that depends on composition has not yet been achieved. We therefore train an Artificial Neural Networks (ANN) on a large database of measured compositions, including water, and viscosities that spans virtually the entire chemical space of terrestrial magmas, as well as some technical and extra-terrestrial silicate melts. The ANN uses composition, temperature, a structural parameter reflecting melt polymerisation and the alkaline ratio as input parameters. It successfully reproduces and predicts measurements in the database with significantly higher accuracy than previous global models for volcanic melt viscosities. Viscosity measurements are restricted to low and high viscosity ranges, which exclude typical eruptive temperatures. Without training data at such conditions, the ANN cannot reliably predict viscosities for this important temperature range. To overcome this limitation, we use the ANN to create synthetic viscosity data in the high and low viscosity range and fit these points using a physically motivated, temperature-dependent viscosity model. Our study introduces a synthetic data approach for the creation of a physically motivated model predicting volcanic melt viscosities based on ANNs.

Tematica 2: Dinamiche eruttive e di messa in posto
Bonadonna C., Pistolesi M., Biass S., Voloschina M., Romero J., Coppola D., Folch A., Martin-Lorenzo A., Dominguez L., Pastore C., Reyes-Hardy M.P., Rodríguez F. (2022)
Physical Characterization of Long-Lasting Hybrid Eruptions: The 2021 Tajogaite Eruption of Cumbre Vieja (La Palma, Canary Islands).
Journal of Geophysical Research: Solid Earth, e2022JB025302.
Data di pubblicazione: 27/11/2022
PubAIV-ID-00092 - Articolo in Rivista (open access)

Long-lasting, hybrid eruptions can be of complex description and classification, especially when associated with multiple eruptive styles and multiple products. The 2021 Tajogaite eruption of La Palma, Canary Islands, was associated with a magma-gas decoupled system that resulted in the simultaneous emission of lava flows and tephra plumes from various vents. Even though the tephra blanket (∼2 × 107 m3) represents only 7%–16% of the total erupted volume, it provides fundamental insights into the overall eruptive dynamics. Tephra was mostly dispersed NE-SW due to a complex regional and local wind patterns and was subdivided into 3 units and 11 layers that well correlate at different distances from the vent and with both tremor data and lava emission rate. While plume height varied at the temporal scale of a few hours, the average mass eruption rate associated with the tephra blanket of the different units remained relatively constant (∼3–4 × 103 kg s−1). In contrast, the emission rate of lava largely increased after the first week and remained higher than the overall emission of tephra throughout the whole eruption (average value of ∼6 × 104 kg s−1). Based on a detailed characterization of the tephra blanket in combination with atmospheric wind, tremor, and lava emission trend, we demonstrate the need of (a) multidisciplinary strategies for the description of hybrid eruptions that account for both the duration of individual phases and the quantification of the mass of multiple products, and of (b) dedicated ash dispersal forecasting strategies that account for the frequent variations of eruptive and atmospheric conditions.
Risica G., Rosi M., Pistolesi M., Speranza F., Branney M. J. (2022)
Deposit-Derived Block-and-Ash Flows: The Hazard Posed by Perched Temporary Tephra Accumulations on Volcanoes; 2018 Fuego Disaster, Guatemala.
Journal of Geophysical Research Solid Earth, 127, e2021JB023699
Data di pubblicazione: 27/05/2022
PubAIV-ID-00091 - Articolo in Rivista (open access)

The impact of hazardous pyroclastic density currents (PDCs) increases with runout distance, which is strongly influenced by the mass flux. This article shows that the mass flux of a PDC may derive not only from vent discharge during the eruption, but also from partly hot, temporary stores (accumulations) of aerated pyroclastic material perched high on the volcano. The unforeseen PDC at Fuego volcano (Guatemala) on 3 June 2018 happened c.1.5 hr after the eruption climax. It overran the village of San Miguel Los Lotes causing an estimated 400+ fatalities. Analysis of the facies architecture of the deposit combined with video footage shows that a pulsatory block-and-ash flow flowed down the Las Lajas valley and rapidly waxed, the runout briefly increasing to 12.2 km as it filled and then spilled out of river channels, entered a second valley where it devastated the village and became increasingly erosive, prior to waning. Paleomagnetic analysis shows that the PDC contained only 6% very hot (>590°C) clasts, 39% moderately hot (∼200°C–500°C) clasts, and 51% cool (<200°C) clasts. This reveals that the block-and-ash flow mostly derived from collapse of loose and partly hot pyroclastic deposits, stored high on the volcano, gradually accumulated during the last 2–3 years. Progressive collapse of unstable deposits supplied the block-and-ash flow, causing a bulk-up process, waxing flow, channel overspill and unexpected runout. The study demonstrates that deposit-derived pyroclastic currents from perched temporary tephra stores pose a particular hazard that is easy to overlook and requires a new, different approach to hazard assessment and monitoring.
Scarani A., Zandonà A., Di Fiore F., Valdivia P., Putra R., Miyajima N., Bornhöft H., Vona A., Deubener J., Romano C., Di Genova D. (2022)
A chemical threshold controls nanocrystallization and degassing behaviour in basalt magmas.
Communications Earth & Environment, 3, 284
Data di pubblicazione: 18/11/2022
PubAIV-ID-00088 - Articolo in Rivista (open access)

An increasing number of studies are being presented demonstrating that volcanic glasses can be heterogeneous at the nanoscale. These nano-heterogeneities can develop both during viscosity measurements in the laboratory and during magma eruptions. Our multifaceted study identifies here total transition metal oxide content as a crucial compositional factor governing the tendency of basalt melts and glasses towards nanolitization: at both anhydrous and hydrous conditions, an undercooled trachybasalt melt from Mt. Etna readily develops nanocrystals whose formation also hampers viscosity measurements, while a similar but FeO- and TiO2-poorer basalt melt from Stromboli proves far more stable at similar conditions. We therefore outline a procedure to reliably derive pure liquid viscosity without the effect of nanocrystals, additionally discussing how subtle compositional differences may contribute to the different eruptive styles of Mt. Etna and Stromboli.
Tematica 3: Geologia e struttura dei vulcani
Tematica 4: Monitoraggio, pericolosità e rischio vulcanico
Dioguardi F., Massaro S., Chiodini G., Costa A., Folch A., Macedonio G., Sandri L., Selva J., Tamburello G. (2022)
VIGIL: A Python tool for automatized probabilistic VolcanIc Gas dIspersion modeLling.
Annals of Geophysics 65, 1, DM107
Data di pubblicazione: 03/06/2022
PubAIV-ID-00090 - Articolo in Rivista (open access)

Probabilistic volcanic hazard assessment is a standard methodology based on running a deter‐ ministic hazard quantification tool multiple times to explore the full range of uncertainty in the input parameters and boundary conditions, in order to probabilistically quantify the variability of outputs accounting for such uncertainties. Nowadays, different volcanic hazards are quantified by means of this approach. Among these, volcanic gas emission is particularly relevant given the threat posed to human health if concentrations and exposure times exceed certain thresholds. There are different types of gas emissions but two main scenarios can be recognized: hot buoyant gas emissions from fumaroles and the ground and dense gas emissions feeding density currents that can occur, e.g., in limnic eruptions.
Simulation tools are available to model the evolution of critical gas concentrations over an area of interest. Moreover, in order to perform probabilistic hazard assessments of volcanic gases, simulations should account for the natural variability associated to aspects such as seasonal and daily wind conditions, localized or diffuse source locations, and gas fluxes.
Here we present VIGIL (automatized probabilistic VolcanIc Gas dIspersion modeLling), a new Python tool designed for managing the entire simulation workflow involved in single and probabilistic applications of gas dispersion modelling. VIGIL is able to manage the whole process from meteorological data processing, needed to run gas dispersion in both the dilute and dense gas flow scenarios, to the post processing of models’ outputs. Two application examples are presented to show some of the modelling capabilities offered by VIGIL.
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