The molecular gas mass of M33
P. Gratier, J. Braine, K. Schuster, E. Rosolowsky, M. Boquien, D., Calzetti, F. Combes, C. Kramer, C. Henkel, F. Herpin, F. Israel., B.S., Koribalski, B. Mookerjea, F.S. Tabatabaei, M. R\"ollig, F.F.S. van der Tak,, P. van der Werf, M. Wiedner

TL;DR
This study uses Herschel FIR data and Bayesian analysis to estimate the molecular gas mass in M33, revealing the distribution of dark gas and variations in the CO-to-H2 conversion factor across the galaxy.
Contribution
It introduces a Bayesian method to derive molecular gas parameters from dust and CO data, accounting for CO-dark gas, in a low metallicity galaxy.
Findings
Dark gas fraction is radially decreasing and correlates with CO emission.
The average XCO is twice the galactic standard, with 55% of H2 traced by CO.
No significant radial trend in XCO was observed in M33.
Abstract
[Abridged] Do some environments favor efficient conversion of molecular gas into stars? To answer this, we need to be able to estimate the H2 mass. Traditionally, this is done using CO and a few assumptions but the Herschel observations in the FIR make it possible to estimate the molecular gas mass independently of CO. Previous attempts to derive gas masses from dust emission suffered from biases. Generally, dust surface densities, HI column densities, and CO intensities are used to derive a gas-to-dust ratio (GDR) and the local CO intensity to H2 column density ratio (XCO), sometimes allowing for an additional CO-dark gas component (Kdark). We tested earlier methods, revealing degeneracies among the parameters, and then used a Bayesian formalism to derive the most likely values for each of the parameters mentioned above as a function of position in the nearby low metallicity spiral…
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