Near Real-Time Petrologic Monitoring on Volcanic Glass to Infer Magmatic Processes During the February-April 2021 Paroxysms of the South-East Crater, Etna

FRONTIERS IN EARTH SCIENCE(2022)

引用 8|浏览0
暂无评分
摘要
The South-East crater of Etna (SEC) is the most active summit crater over the last 20 years, producing lava fountains in 2000, 2007-08, and 2011-14. It has been monitored by the INGV Etna Observatory by instrumental networks, field surveys and petrologic monitoring. The syn-eruptive petrologic monitoring consists of an articulated work chain which is generally carried out within 24 h from the moment the sample was emplaced to detect possible changes of magma composition episode by episode, as well as over a longer period. The findings of petrologic monitoring are integrated with the results provided by geophysical networks and gas geochemistry to check the volcano's behavior during the eruption and to communicate potentially dangerous variations in eruptive features to the local authorities. This paper presents the variation of volcanic glass compositions during the paroxysmal activity of the SEC, which began in December 2020 and climaxed with 17 episodes from 16 February to 1 April 2021. We infer pre-eruptive magmatic processes (e.g., fractional crystallization and mixing) based on temporal trends of some key compositional parameters (i.e., CaO/Al2O3; FeOtot/MgO). Correlation between magma dynamics and volcanological characteristics of the paroxysms requires future studies. We demonstrated that petrologic monitoring carried out during a volcanic crisis at Etna, as well as in other volcanoes worldwide, may be crucial to acquire preliminary insights into the structure of the plumbing system and the pre-eruptive processes governing the eruptive activity. Interestingly, this goal has been achieved also thanks to the collaboration with local citizens, who kindly contributed to collecting samples.
更多
查看译文
关键词
Etna summit eruptions, lava fountains, petrologic monitoring, glass compositions, mixing, fractional crystallization
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要