Assessments of carbon monoxide emissions through inverse modeling are dependent on the modeled abundance of the hydroxyl radical (OH) which controls both the primary sink of CO and its photochemical source through hydrocarbon oxidation. However, most chemistry transport models (CTMs) fall short of reproducing constraints on hemispherically averaged OH levels derived from methylchloroform (MCF) observations. Here we construct five different OH fields compatible with MCF-based analyses, and we

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... scribe those fields in a global CTM to infer CO fluxes based on Infrared Atmospheric Sounding Interferometer (IASI) CO columns. Each OH field leads to a different set of optimized emissions. Comparisons with independent data (surface, ground-based remotely sensed, aircraft) indicate that the inversion adopting the lowest average OH level in the Northern Hemisphere (7.8 × 10 5 molec cm −3 , ∼18% lower than the best estimate based on MCF measurements) provides the best overall agreement with all tested observation data sets. Plain Language Summary Satellite measurements of a pollutant can be used to deduce the emissions of this pollutant to the atmosphere. But often, such estimates have errors due to our uncertain knowledge of the chemical lifetime of pollutants. Here we assess the importance of specifying the correct lifetime for deducing the sources of carbon monoxide. We also show that the measurements can provide new constraints on the lifetime of pollutants. More precisely, we provide constraints on the abundance of OH radicals, often considered to be the main detergent of the atmosphere. Indeed, OH radical is the main oxidant of carbon monoxide, but also methane, which is a potent greenhouse gas. Key Points: • The global CO sources were inferred based on IASI CO columns, using a global CTM and prescribed OH fields • Varying hemispheric mean OH levels within their uncertainties estimated from methylchloroform analyses has a strong impact on derived fluxes • The inversion adopting the lowest OH in NH provides the best match with satellite, in situ, and FTIR data Supporting Information: • Supporting Information S1