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We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004-April 2005) global inversion of CO sources at 4°×5° spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Global intercomparison of the different satellite datasets using GEOS-Chem as a common intercomparison platform shows consistency between the satellite datasets and with the in situ data. The majority of the differences between the datasets can be explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a-1, with an additional 217 Tg a-1 from oxidation of co-emitted VOCs. This is much higher than current bottom-up emission inventories. Consistent with both the satellite and in situ data, a large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. A posteriori emissions also indicate a general underestimation of biomass burning relative to the GFED2 inventory. However, the tropical biomass burning constraints are not consistent across the different datasets. Although the datasets reveal regional inconsistencies over tropical biomass burning regions, we find the global emission estimates to be a balance of information from all three instruments. [ABSTRACT FROM AUTHOR]

Carbon monoxide (CO) is an important atmospheric constituent affecting air quality and climate. SCIAMACHY on ENVISAT is currently the only satellite instrument that can measure the vertical column of CO with nearly equal sensitivity at all altitudes down to the Earth's surface because of its near-infrared nadir observations of reflected solar radiation. Here we present three years' (2003-2005) of SCIAMACHY CO columns consistently retrieved with the latest version of our retrieval algorithm (WFMDv0.6). We describe the retrieval method and discuss the multi-year global CO data set focusing on a comparison with the operational CO column data product of MOPITT. We found reasonable to good agreement (∼20%) with MOPITT, with the best agreement for 2004. We present detailed results for various regions (Europe, Middle East, India, China) and discuss to what extent enhanced levels of CO can be detected over populated areas including individual cities. The expected CO signal from cities is close to or even below the detection limit of individual measurements. We show however that cities can be identified when averaging long time series. [ABSTRACT FROM AUTHOR]