PyIRoGlass: An Open-Source, Bayesian MCMC Algorithm for Fitting Baselines to FTIR Spectra of Basaltic-Andesitic Glasses

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.30909/vol.07.02.471501. This is version 3 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Authors

Sarah Christine Shi , William Henry Towbin, Terry Plank, Anna Barth, Daniel Rasmussen, Yves Moussallam, Hyun Joo Lee, William Menke

Abstract

Quantifying volatile concentrations in magmas is critical for understanding magma storage, phase equilibria, and eruption processes. We present PyIRoGlass, an open-source Python package for quantifying H2O and CO2 species concentrations in the transmission FTIR spectra of basaltic to andesitic glasses. We leverage a database of naturally degassed melt inclusions and back-arc basin basalts to delineate the fundamental shape and variability of the baseline underlying the CO32- and H2Om,1635 peaks, in the mid-infrared region. All Beer-Lambert Law parameters are examined to quantify associated uncertainties. PyIRoGlass employs Bayesian inference and Markov Chain Monte Carlo sampling to fit all probable baselines and peaks, solving for best-fit parameters and capturing covariance to offer robust uncertainty estimates. Results from PyIRoGlass agree with independent analysis of experimental devolatilized glasses (within 6%) and interlaboratory standards (13% for H2O, 9% for CO2). We determine new molar absorptivities for basalts, εH2Ot,3550=63.03±4.47 L/mol·cm and εCO32-1515, 1430=303.44±9.20 L/mol·cm; we additionally update the composition-dependent parameterizations of molar absorptivities, with their uncertainties, for all H2O and CO2 species peaks. The open-source nature of PyIRoGlass ensures its adaptability and evolution as more data become available.

DOI

https://doi.org/10.31223/X55H4N

Subjects

Earth Sciences, Geochemistry, Other Earth Sciences, Physical Sciences and Mathematics, Volcanology

Keywords

volatiles, FTIR, Open-source, python, Bayesian, Markov chain Monte Carlo

Dates

Published: 2023-11-02 08:42

Last Updated: 2024-07-26 15:40

Older Versions
License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data Availability (Reason not available):
https://github.com/sarahshi/PyIRoGlass