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

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 CO₃^2- and H₂O_m,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, εH₂O_t,3550=63.03±4.47 L/mol·cm and εCO₃^2-_{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.