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  • 1
    Publication Date: 2021-01-26
    Description: Hydrothermally-altered rocks collected at Solfatara volcano, Campi Flegrei caldera complex, Italy, are comparable to zones of steam-heated alterations found at low sulfidation epithermal deposits, and volcanic gases collected at Solfatara have temperatures and C-O-H isotopic compositions akin to those forming low sulfidation epithermal deposits. By contrast, hydrothermal alterations collected at La Fossa volcano, Vulcano island, Italy, are comparable to zones of residual vuggy silica formed in high sulfidation epithermal deposits, and volcanic gases collected at La Fossa have temperatures and C-O-H isotopic compositions comparable to those forming high sulfidation epithermal deposits. At Solfatara, amorphous and hydrous opal-A is responsible for shifts in δ7Li values, from +2.2‰ in fresher rocks, to −3.6‰ in most altered rocks, with increases in Au and Cu concentrations (up to 3 ppb and 96 ppm). The increase in Au and Cu concentrations in progressively-altered rocks resulted from the transport of Cu-Au in magmatic-hydrothermal fluids and their partitioning into pyrite, Fe oxides, phyllosilicates, sulfates, and/or opal-A. It is proposed that the combination of opal-A, decreases in δ7Li values, and increases in Cu and Au concentrations represent an exploration vector for low sulfidation epithermal veins. At La Fossa, α-cristobalite is responsible for shifts in δ7Li values, ranging from −0.9‰ in least-altered rocks, to +4.7‰ in most altered rocks, with decreases in Au-Cu concentrations. The decrease in Au and Cu concentrations in progressively-altered rocks may have resulted from the metasomatism of pyrite and Fe oxides, the dissolution of clinopyroxene and opal, and the invasion of the samples by α-cristobalite. The combination of α-cristobalite, increases in δ7Li values, and decreases in Cu and Au concentrations are proposed as proxies for potential high sulfidation epithermal disseminations. Alternating phases of high eruptive activity and quiescent degassing at volcanoes generally, and at Solfatara and La Fossa specifically, suggest that the physicochemical conditions of individual subvolcanic hydrothermal systems should also be alternating, between conditions that are characteristic of low- and high sulfidation epithermal ore-forming environments, and that the related zones of silicification should be alternating between low δ7Li and high Cu-Au values dominated by opal-A, and higher δ7Li and lower Cu-Au values dominated by α-cristobalite.
    Description: Published
    Description: 103934
    Description: 3V. Proprietà chimico-fisiche dei magmi e dei prodotti vulcanici
    Description: JCR Journal
    Keywords: Active ore-forming processes ; Opalization and cristobalization ; Lithium isotopes ; High and low sulfidation epithermal Au-Cu ore deposits ; La Fossa, Vulcano, Italy ; Solfatara, Campi Flegrei, Italy ; 04.08. Volcanology ; 05.04. Instrumentation and techniques of general interest ; Geochemistry
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
    Publication Date: 2024-02-07
    Description: Over the last decade, field investigations, laboratory experiments, geophysical exploration and petrological, geochemical and numerical modelling have provided insight into the mechanisms of phreatic and hydrothermal eruptions. These eruptions are driven by sudden flashing of ground- or hydrothermal water to steam and are strongly influenced by the interaction of host rock and hydrothermal system. Aquifers hosted in volcanic edifices, calderas and rift environments can be primed for instability by alteration processes affecting rock permeability and/or strength, while magmatic fluid injection(s), earthquakes or other subtle triggers can promote explosive failure. Gas emission, ground deformation and seismicity may provide short- to medium-term forerunner signals of these eruptions, yet a definition of universal precursors remains a key challenge. Looking forward in the next 10 years, improved warning and hazard assessment will require integration of field and experimental data with models combining case studies, as well as development of new monitoring methods integrated by machine learning approaches.
    Type: Article , PeerReviewed
    Format: text
    Format: text
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