Assimilation of atmospheric CO2 observations from space can support national CO2 emission inventories. (4th January 2022)

• Record Type: Journal Article
• Authors: Kaminski, Thomas; Scholze, Marko; Rayner, Peter; Voßbeck, Michael; Buchwitz, Michael; Reuter, Maximilian; Knorr, Wolfgang; Chen, Hans; Agustí-Panareda, Anna; Löscher, Armin; Meijer, Yasjka
• Is Part Of: Environmental research letters. Volume 17:Number 1(2022)
• Publication Date: 2022-01-04
• Subjects: CO2 Monitoring Mission -- fossil fuel emissions -- Monitoring and Verification System -- Paris Agreement -- inverse modelling; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/ac3cea
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: The Paris Agreement establishes a transparency framework for anthropogenic carbon dioxide (CO2 ) emissions. It's core component are inventory-based national greenhouse gas emission reports, which are complemented by independent estimates derived from atmospheric CO2 measurements combined with inverse modelling. It is, however, not known whether such a Monitoring and Verification Support (MVS) capacity is capable of constraining estimates of fossil-fuel emissions to an extent that is sufficient to provide valuable additional information. The CO2 Monitoring Mission (CO2M), planned as a constellation of satellites measuring column-integrated atmospheric CO2 concentration (XCO2 ), is expected to become a key component of such an MVS capacity. Here we provide a novel assessment of the potential of a comprehensive data assimilation system using simulated XCO2 and other observations to constrain fossil fuel CO2 emission estimates for an exemplary 1-week period in 2008. We find that CO2M enables useful weekly estimates of country-scale fossil fuel emissions independent of national inventories. When extrapolated from the weekly to the annual scale, uncertainties in emissions are comparable to uncertainties in inventories, so that estimates from inventories and from the MVS capacity can be used for mutual verification. We further demonstrate an alternative, synergistic mode of operation, with the purpose of delivering a best fossil fuel emission estimate. In this mode, the assimilation system uses not only XCO2 and the other data streams of the previous (verification) mode, but also the inventory information. Finally, we identify further steps towards an operational MVS capacity.