Complementing XCO2 imagery with ground-based CO2 and 14CO2 measurements to monitor CO2 emissions from fossil fuels on a regional to local scale

Various satellite imagers of the vertically integrated column of carbon dioxide (XCO2) are under development to enhance the capabilities for the monitoring of fossil fuel (FF) CO2 emissions. XCO2 images can be used to detect plumes from cities and large industrial plants and to quantify the corresponding emission using atmospheric inversions techniques. However, this potential and the ability to catch the signal from more diffuse FF CO2 sources can be hampered by the mix between these FF signals and a background signal from other types of CO2 surface fluxes, and in particular of biogenic CO2 fluxes. The deployment of dense ground-based air-sampling networks for CO2 and radiocarbon (14CO2) could complement the spaceborne imagery by supporting the separation between the fossil fuel and biogenic or biofuel (BF) CO2 signals. We evaluate this potential complementarity with a high-resolution analytical inversion system focused on northern France, western Germany, Belgium, Luxembourg, and a part of the Netherlands and with pseudo-data experiments. The inversion system controls the FF and BF emissions from the large urban areas and plants, in addition to regional budgets of more diffuse emissions or of biogenic fluxes (NEE, net ecosystem exchange), at an hourly scale over a whole day. The system provides results corresponding to the assimilation of pseudo-data from a single track of a 300 km swath XCO2 imager at 2 km resolution and from surface ground-based CO2 and/or 14CO2 networks. It represents the diversity of 14CO2 sources and sinks and not just the dilution of radiocarbon-free FF CO2 emissions. The uncertainty in the resulting FF CO2 emissions at local (urban area/plant) to regional scales is directly derived and used to assess the potential of the different combinations of observation systems. The assimilation of satellite observations yields estimates of the morning regional emissions with an uncertainty down to 10 percent (1 sigma) in the satellite field of view, from an assumed uncertainty of 15 percent in the prior estimates. However, it does not provide direct information about emissions outside the satellite field of view or about afternoon or nighttime emissions. The co-assimilation of 14CO2 and CO2 surface observations leads to a further reduction of the uncertainty in the estimates of FF emissions. However, this further reduction is significant only in administrative regions with three or more 14CO2 and CO2 sampling sites. The uncertainty in the estimates of 1 d emission in North Rhine-Westphalia, a region with three sampling sites, decreases from 8 percent to 6.6 percent when assimilating the in situ 14CO2 and CO2 data in addition to the satellite data. Furthermore, this additional decrease appears to be larger when the ground stations are close to large FF emission areas, providing an additional direct constraint for the estimate of these sources rather than supporting the characterization of the background signal from the NEE and its separation from that of the FF emissions. More generally, the results indicate no amplification of the potential of each observation subsystem when they are combined into a large observation system with satellite and surface data