This work presents a flux inversion system which assesses the potential of new satellite imagery measurements of atmospheric CO2 for monitoring anthropogenic emissions at scales ranging from local intense point sources to regional and national scales. Such imagery measurements will be provided by the future Copernicus Anthropogenic Carbon Dioxide Monitoring Mission (CO2M). While the modeling framework retains the complexity of previous studies focused on individual and large cities, this system encompasses a wide range of sources to extend the scope of the analysis. This atmospheric inversion system uses a zoomed configuration of the CHIMERE regional transport model which covers most of western Europe with a 2 km resolution grid over northern France, western Germany and Benelux. For each day of March and May 2016, over the 6 h before a given satellite overpass, the inversion separately controls the hourly budgets of anthropogenic emissions in this area from ∼ 300 cities, power plants and regions. The inversion also controls hourly regional budgets of the natural fluxes. This enables the analysis of results at the local to regional scales for a wide range of sources in terms of emission budget and spatial extent while accounting for the uncertainties associated with natural fluxes and the overlapping of plumes from different sources. The potential of satellite data for monitoring CO2 fluxes is quantified with posterior uncertainties or uncertainty reductions (URs) from prior inventory-based statistical knowledge. A first analysis focuses on the hourly to 6 h budgets of the emissions of the Paris urban area and on the sensitivity of the results to different characteristics of the images of vertically integrated CO2 (XCO2) corresponding to the spaceborne instrument: the pixel spatial resolution, the precision of the XCO2 retrievals per pixel and the swath width. This sensitivity analysis provides a correspondence between these parameters and thresholds on the targeted precisions of emission estimates. However, the results indicate a large sensitivity to the wind speed and to the prior flux uncertainties. The analysis is then extended to the large ensemble of point sources, cities and regions in the study domain, with a focus on the inversion system's ability to separately monitor neighboring sources whose atmospheric signatures overlap and are also mixed with those produced by natural fluxes. Results highlight the strong dependence of uncertainty reductions on the emission budgets, on the wind speed and on whether the focus is on point or area sources. With the system hypothesis that the atmospheric transport is perfectly known, the results indicate that the atmospheric signal overlap is not a critical issue. All of the tests are conducted considering clear-sky conditions, and the limitations from cloud cover are ignored. Furthermore, in these tests, the inversion system is perfectly informed about the statistical properties of the various sources of errors that are accounted for, and systematic errors in the XCO2 retrievals are ignored; thus, the scores of URs are assumed to be optimistic. For the emissions within the 6 h before a satellite overpass, URs of more than 50 % can only be achieved for power plants and cities whose annual emissions are more than ∼ 2 MtC yr−1. For regional budgets encompassing more diffuse emissions, this threshold increases up to ∼ 10 MtC yr−1. The results therefore suggest an imbalance in the monitoring capabilities of the satellite XCO2 spectro-imagery towards high and dense sources.