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从矿物化学角度看2021年2月至4月埃特纳火山东南火山口岩浆喷泉喷发序列期间的岩浆演化。

The magmatic evolution of South-East Crater (Mt. Etna) during the February-April 2021 sequence of lava fountains from a mineral chemistry perspective.

作者信息

Musu Alessandro, Corsaro Rosa Anna, Higgins Oliver, Jorgenson Corin, Petrelli Maurizio, Caricchi Luca

机构信息

Department of Earth Sciences, University of Geneva, Rue des Maraîchers 13, CH-1205 Geneva, Switzerland.

Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo-Sezione di Catania, Piazza Roma 2, 95123 Catania, Italy.

出版信息

Bull Volcanol. 2023;85(5):33. doi: 10.1007/s00445-023-01643-2. Epub 2023 Apr 26.

DOI:10.1007/s00445-023-01643-2
PMID:37124166
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10133385/
Abstract

UNLABELLED

The South-East Crater (SEC) at Mt. Etna started a period of lava fountaining in December 2020, producing over 60 paroxysms until February 2022. The activity had an intense sequence from February 16 to April 1, 2021, totaling 17 paroxysmal events separated by repose times varying from 1 to 7 days. The eruptive sequence was extensively monitored, providing a unique opportunity to relate the chemistry and texture of the erupted products to eruption dynamics. We investigate the temporal evolution of the magmatic system through this eruptive sequence by quantifying variations in the composition and texture of clinopyroxene. Clinopyroxene major element transects across crystals from five representative lava fountains allow us to determine the relative proportions of deep versus shallow-stored magmas that fed these events. We use hierarchical clustering (HC), an unsupervised machine learning technique, to objectively identify clinopyroxene compositional clusters and their variations during this intense eruptive phase. Our results show that variations of monitoring parameters and eruption intensity are expressed in the mineral record both as changes in cluster proportions and the chemical complexity of single crystals. We also apply random forest thermobarometry to relate each cluster to P-T conditions of formation. We suggest that the February-April 2021 eruptive sequence was sustained by the injection of a hotter and deeper magma into a storage area at 1-3 kbar, where it mixed with a slightly more evolved magma. The February 28 episode emitted the most mafic magma, in association with the highest mean lava fountain height and highest time-averaged discharge rate, which make it the peak of the analyzed eruptive interval. Our results show that after this episode, the deep magma supply decreased and the erupted magma become gradually more chemically evolved, with a lower time-average discharge rate and fountain height. We propose this approach as a means to rapidly, objectively, and effectively link petrological and geophysical/geochemical monitoring during ongoing eruptions. We anticipate that the systematic application of this approach will serve to shed light on the magmatic processes controlling the evolution of ongoing eruptions.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00445-023-01643-2.

摘要

未标注

埃特纳火山的东南火山口于2020年12月开始了一段熔岩喷发期,直至2022年2月产生了60多次阵发性喷发。2021年2月16日至4月1日期间活动剧烈,共有17次阵发性事件,间歇时间从1天到7天不等。对喷发序列进行了广泛监测,为将喷发产物的化学性质和结构与喷发动力学联系起来提供了独特机会。我们通过量化单斜辉石的成分和结构变化,研究了通过这一喷发序列的岩浆系统的时间演化。对来自五个代表性熔岩喷泉的晶体进行的单斜辉石主要元素剖面分析,使我们能够确定为这些事件提供岩浆的深部与浅部储存岩浆的相对比例。我们使用分层聚类(HC)这一无监督机器学习技术,客观地识别单斜辉石成分簇及其在这一强烈喷发阶段的变化。我们的结果表明,监测参数和喷发强度的变化在矿物记录中表现为簇比例的变化和单晶的化学复杂性。我们还应用随机森林热压法将每个簇与形成的P-T条件联系起来。我们认为,2021年2月至4月的喷发序列是由注入到1-3千巴储存区域的更热、更深部的岩浆维持的,在那里它与稍为演化程度更高的岩浆混合。2月28日的喷发事件喷出了最基性的岩浆,伴随着最高的平均熔岩喷泉高度和最高的时间平均排放率,使其成为分析喷发间隔的峰值。我们的结果表明,在这一事件之后,深部岩浆供应减少,喷出的岩浆化学演化程度逐渐增加,时间平均排放率和喷泉高度降低。我们提出这种方法作为在正在进行的喷发期间快速、客观和有效地将岩石学与地球物理/地球化学监测联系起来的一种手段。我们预计,系统应用这种方法将有助于阐明控制正在进行的喷发演化的岩浆过程。

补充信息

在线版本包含可在10.1007/s00445-023-01643-2获取的补充材料。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc94/10133385/1cf4a81ecec2/445_2023_1643_Fig8_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc94/10133385/23cebe807198/445_2023_1643_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc94/10133385/8d45c4284e27/445_2023_1643_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc94/10133385/ed4c29d042eb/445_2023_1643_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc94/10133385/0f7d121c0c3f/445_2023_1643_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc94/10133385/1cf4a81ecec2/445_2023_1643_Fig8_HTML.jpg

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