Carbon atoms have the exceptional ability to form stable chemical bonds with each other and therefore participate in all living organisms on Earth. Their ubiquity, the ability of living organisms to reduce carbon dioxide and to oxidize carbon to carbon dioxide through photosynthesis and respiration and the carbonate-chemistry system in water, translates into diverse individual processes that contribute to the carbon balance at the Earth-atmosphere interface. With the growing contribution of human activities in the carbon cycle, the quantification of this carbon balance at regional scales has become a major scientific challenge that is being tackled by experimentalists and modelers. At present, direct carbon flux measurements lack the spatial coverage needed to map the fluxes accurately. Numerical models of the carbon cycle, informed by process studies and specific inventories, lack the sophistication to pin down the variability of the carbon surface sources and sinks. In this context, atmospheric CO2 mixing ratio measurements form a complementary source of information about the fluxes, because atmospheric mixing integrates the individual contributions from the fluxes at large spatial and temporal scales. However, the transformation of the CO2 mixing ratio gradients into carbon fluxes involves sophisticated statistical inversion schemes and atmospheric transport models that are still a topic of active research [e.g., Rödenbeck et al., 2003; Peters et al., 2007].
 This paper reports on a collective effort to analyze the CO2 surface fluxes over two decades, from 1988 to 2008, based on CO2 mixing ratio records from three large databases: the NOAA Earth System Research Laboratory (ESRL) archive, the CarboEurope IP project, and the World Data Centre for Greenhouse Gases (WDCGG) of the World Meteorological Organization (WMO) Global Atmosphere Watch Programme. The three databases include both in situ measurements made by automated quasicontinuous analyzers and air samples collected in flasks and later analyzed at central facilities. The flux inversion builds on the variational Bayesian inversion system of Chevallier et al. , which allows the fluxes to be estimated at a relatively high resolution over the globe: 8 days and 3.75° × 2.5° (longitude-latitude). The period of analysis covers 21 years, from 1988 to 2008. Fluxes and mixing ratios are linked in the system by the global atmospheric transport model of the Laboratoire de Météorologie Dynamique (LMDZ [Hourdin et al., 2006]). A series of flux inventories, flux climatologies, flux models, and flux error models regularizes the solution to the flux inference problem. The uncertainty of the inverted fluxes is quantified from the Bayesian theory by the Monte Carlo method of Chevallier et al. . Independent validation data are provided by 34 aircraft measurement campaigns gathered in the GEOMON database (http://geomon-wg.ipsl.jussieu.fr/sections/aircraftcampaigns) and by the commercial-aircraft-based observations in the Comprehensive Observation Network for Trace gases by Airliner (CONTRAIL) database [Machida et al., 2008]. As a benchmark to evaluate the quality of the fluxes resulting from our inversion, we use a simpler inversion called the “poor man’s inversion,” based only on the global annual CO2 growth rate information.
 The paper is structured as follows. Section 2 describes the inversion method. The validation strategy is described in section 3. The results are presented in section 4. Section 5 concludes the paper.