Toward a near real-time magma ascent monitoring by combined fluid inclusion barometry and ongoing seismicity

Abstract

Fluid inclusion microthermometry on olivines, clinopyroxenes, and amphiboles was used during a volcanic eruption, in combination with real-time seismic data and rapid petrographic observations, for petrological monitoring purposes. By applying this approach to the study of 18 volcanic samples collected during the eruption of Tajogaite volcano on La Palma Island (Canary Islands) in 2021, changes in the magma system were identified over time and space. Magma batches with distinct petrographic and geochemical characteristics emerged from source zones whose depth progressively increased from 27 to 31 kilometers. The rise of magma of deeper origin is attested by fluid inclusions made of N 2 and CO, markers of mantle outgassing. Magma accumulation occurred over different durations at depths of 22 to 27 and 4 to 16 kilometers. Time-integrated magma ascent velocities (including ponding times) were estimated at between 0.01 and 0.1 meters per second. This method is cost-effective and quickly identifies changes in the magma system during an eruption, enhancing petrological monitoring procedures.

DiadFit: An open-source Python3 tool for peak fitting of Raman data from silicate melts and CO2 fluids

“…Fitting these spectra took ∼8 hrs using Fityk, and ∼15 minutes using DiadFit on a typical laptop with 16 GB of RAM and an i7 processor. Given the potential for fluid inclusion analyses to provide rapid estimates of magma storage depths during volcanic crises [Dayton et al 2023;DeVitre and Wieser 2024;Zanon et al 2024], it is vital to speed up data processing as much as possible to reap the full benefits of this speedy technique. We anticipate that users who are not familiar with Python will simply use the provided Jupyter Notebooks and narrated YouTube videos, changing simple parameters like the path to their files and peak fit parameters to adjust for the different appearance of spectral peaks on different Raman instruments.…”

“…However, detecting the presence of H 2 O in fluid inclusions, let alone quantifying H 2 O mole proportions required to perform calculations using a H 2 O-CO 2 EOS, is very challenging for a number of reasons [Morgan et al 1993]. First, H 2 O may no longer be present in the inclusion, because of diffusive loss during stalling, ascent and syn-eruptive quenching, or because it reacted with the mineral host to form hydrous phases [Morgan et al 1993;Mavrogenes and Bodnar 1994;Zanon et al 2024]. If H 2 O is still present, H 2 O has a very low solubility in CO 2 fluids at temperatures typical of routine Raman analyses (∼0.5 mol%, [Spycher et al 2003;Frezzotti and Peccerillo 2007]).…”

“…However, perhaps because the H 2 O has been lost in many cases, and even with heating, quantification is challenging, the majority of fluid inclusion studies simply pick a fixed value of 𝑋 H 2 O (e.g. 0.1 for Forte et al [2023], Sandoval-Velasquez et al [2023], and Zanon et al [2024]). More recently, DeVitre and Wieser 2024 determine 𝑋 H 2 O as a function of pressure for the volcanic system of interest using melt inclusion measurements (many solubility models used to calculate saturation pressures also calculate 𝑋 H 2 O at the point of vapour saturation [e.g.…”

“…Since 2014, there has been a growing body of literature using Raman Spectroscopy to measure the density of CO 2 -rich fluids in melt inclusion vapour bubbles to more accurately obtain the total CO 2 content of the melt inclusion, and thus the magma storage depth [Hartley et al 2014;Moore et al 2015;Lamadrid et al 2017;Allison et al 2021;Wieser et al 2021;DeVitre et al 2023b]. Raman spectroscopy also shows enormous potential to quantify the densities of CO 2 -rich fluid inclusions [Wang et al 2011;Kobayashi et al 2012], allowing rapid and precise estimates of magma storage depths [Dayton et al 2023;DeVitre and Wieser 2024;Zanon et al 2024].…”