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Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000-2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000-2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000-2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008-2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16-32]Tg CH4yr-1 higher methane emissions over the period 2008-2012 compared to 2002-2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002-2006 and 2008-2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (g1/4 biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003-2012 decade, global methane emissions are estimated by top-down inversions at 558g Tgg CH4g yrg'1, range 540-568. About 60g % of global emissions are anthropogenic (range 50-65g %). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon-intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bottom-up approaches suggest larger global emissions (736g Tgg CH4g yrg'1, range 596-884) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the top-down budget, it is likely that some of the individual emissions reported by the bottom-up approaches are overestimated, leading to too large global emissions. Latitudinal data from top-down emissions indicate a predominance of tropical emissions (g1/4 64g % of the global budget, http://doi.org/10.3334/CDIAC/GLOBAL-METHANE-BUDGET-2016-V1.1) and the Global Carbon Project.

Stringent mobility restrictions across the world during the COVID 19 pandemic have impacted local economies and, consequently, city carbon budgets, offering a unique opportunity to evaluate the capability of scientific approaches to quantify emissions changes. Our study aims to quantify and map CO2 emissions from fossil fuel and biogenic CO2 fluxes over the Paris metropolitan area during the first lockdown period (March‐May 2020) in France, in comparison with the same period in 2019. Our inversion system relies on transport model simulations initiated with the Weather Research and Forecasting chemistry transport model combined with a high‐resolution fossil fuel CO2 emissions inventory, and biogenic CO2 fluxes from a vegetation model. The inversion with atmospheric observations from a network of six towers resulted in a positive re‐adjustment of fossil fuel CO2 emissions in 2019 and 2020 compared to prior. In 2020, the inversion resulted in a large emission reduction (43%) compared to 2019, while the reductions were estimated to be 37% based on the prior inventory itself. By assimilating CO mixing ratios in addition to CO2, the traffic emission estimates were reduced by 68% in 2020, compared to nontraffic (29%). Various sensitivity tests show that prior emission uncertainty and different background conditions significantly impacted the emissions estimates. We conclude that our current inversion system with atmospheric CO2 monitoring makes it possible to identify the emission decrease in 2020 partly over the urban region. However, additional information on prior emission errors and a dense network will be needed to map emissions precisely. Plain Language Summary: The study aims to quantify the Paris region's CO2 emissions using a Lagrangian‐based inversion system during the spring season (March‐May) of 2019–2020, using CO2 and co‐emitted CO observations from a network of six ground‐based stations. Our Inversion system tends to increase the emissions with respect to prior in 2019 and 2020. A significant increase (about 150 g CO2 m‐2 day‐1) in the fossil fuel emissions compared to prior was identified in the central Paris region across all our inversion experiments. Sectoral inversion shows an increase in the traffic emissions from the high‐resolution inventory by about 17% in 2019 and 10% in 2020. However, the impact of COVID 19 lockdown on the emissions were −37% to −46% (reduction) depending on the configuration of the inversion system. We also identified that the lack of information relative to inventory uncertainties remains a major limitation in quantifying the aggregated emissions. Precise mapping of fossil fuel emissions at the urban scale will require additional information to quantify both the high‐resolution inventory errors and their spatial structures. However, we confirmed the impact of lockdown restrictions on CO2 fossil fuel emissions to −12% ({plus minus}4%) over the Paris region through inversion. Key Points: Quantification and mapping of fossil fuel CO2 emissions over the Paris metropolitan area during the COVID‐19 pandemic lockdownLockdown has resulted in an emission decrease of about 43% in 2020, with a 37% contribution from the inventory itselfSpatial error correlations, different background conditions and prior uncertainty impact the posterior emission estimates [ABSTRACT FROM AUTHOR]

Author(s): P. Bousquet (corresponding author) [1, 2]; P. Ciais [1]; J. B. Miller [3, 4]; E. J. Dlugokencky [3]; D. A. Hauglustaine [1]; C. Prigent [5]; G. R. Van der [...]