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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]