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<p>In support of the global stocktake of the Paris Agreement on climate change, this study presents a comprehensive framework to process the results of an ensemble of atmospheric inversions in order to make their net ecosystem exchange (NEE) carbon dioxide (CO<span class="inline-formula">₂</span>) flux suitable for evaluating national greenhouse gas inventories (NGHGIs) submitted by countries to the United Nations Framework Convention on Climate Change (UNFCCC). From inversions we also deduced anthropogenic methane (CH<span class="inline-formula">₄</span>) emissions regrouped into fossil and agriculture and waste emissions, as well as anthropogenic nitrous oxide (N<span class="inline-formula">₂</span>O) emissions. To compare inversion results with national reports, we compiled a new global harmonized database of emissions and removals from periodical UNFCCC inventories by Annex I countries, and from sporadic and less detailed emissions reports by non-Annex I countries, given by national communications and biennial update reports. No gap filling was applied. The method to reconcile inversions with inventories is applied to selected large countries covering <span class="inline-formula">∼90</span> % of the global land carbon uptake for CO<span class="inline-formula">₂</span> and top emitters of CH<span class="inline-formula">₄</span> and N<span class="inline-formula">₂</span>O. Our method uses results from an ensemble of global inversions produced by the Global Carbon Project for the three greenhouse gases, with ancillary data. We examine the role of CO<span class="inline-formula">₂</span> fluxes caused by lateral transfer processes from rivers and from trade in crop and wood products and the role of carbon uptake in unmanaged lands, both not accounted for by NGHGIs. Here we show that, despite a large spread across the inversions, the median of available inversion models points to a larger terrestrial carbon sink than inventories over temperate countries or groups of countries of the Northern Hemisphere like Russia, Canada and the European Union. For CH<span class="inline-formula">₄</span>, we find good consistency between the inversions assimilating only data from the global in situ network and those using satellite CH<span class="inline-formula">₄</span> retrievals and a tendency for inversions to diagnose higher CH<span class="inline-formula">₄</span> emission estimates than reported by NGHGIs. In particular, oil- and gas-extracting countries in central Asia and the Persian Gulf region tend to systematically report lower emissions compared to those estimated by inversions. For N<span class="inline-formula">₂</span>O, inversions tend to produce higher anthropogenic emissions than inventories for tropical countries, even when attempting to consider only managed land emissions. In the inventories of many non-Annex I countries, this can be tentatively attributed to a lack of reporting indirect N<span class="inline-formula">₂</span>O emissions from atmospheric deposition and from leaching to rivers, to the existence of natural sources intertwined with managed lands, or to an underestimation of N<span class="inline-formula">₂</span>O emission factors for direct agricultural soil emissions. Inversions provide insights into seasonal and interannual greenhouse gas fluxes anomalies, e.g., during extreme events such as drought or abnormal fire episodes, whereas inventory methods are established to estimate trends and multi-annual changes. As a much denser sampling of atmospheric CO<span class="inline-formula">₂</span> and CH<span class="inline-formula">₄</span> concentrations by different satellites coordinated into a global constellation is expected in the coming years, the methodology proposed here to compare inversion results with inventory reports (e.g., NGHGIs) could be applied regularly for monitoring the effectiveness of mitigation policy and progress by countries to meet the objective of their pledges. The dataset constructed by this study is publicly available at <a href="https://doi.org/10.5281/zenodo.5089799">https://doi.org/10.5281/zenodo.5089799</a> (Deng et al., 2021).</p>