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Petrescu, Ana Maria Roxana; McGrath, Matthew J.; Andrew, Robbie M.; Peylin, Philippe; Peters, Glen P.; Ciais, Philippe; Broquet, Gregoire; Tubiello, Francesco N.; Gerbig, Christoph; Pongratz, Julia ORCID logoORCID: https://orcid.org/0000-0003-0372-3960; Janssens-Maenhout, Greet; Grassi, Giacomo; Nabuurs, Gert-Jan; Regnier, Pierre; Lauerwald, Ronny; Kuhnert, Matthias; Balkovič, Juraj; Schelhaas, Mart-Jan; Denier van der Gon, Hugo A. C.; Solazzo, Efisio; Qiu, Chunjing; Pilli, Roberto; Konovalov, Igor B.; Houghton, Richard A.; Günther, Dirk; Perugini, Lucia; Crippa, Monica; Ganzenmüller, Raphael ORCID logoORCID: https://orcid.org/0000-0002-2337-0915; Luijkx, Ingrid T.; Smith, Pete; Munassar, Saqr; Thompson, Rona L.; Conchedda, Giulia; Monteil, Guillaume; Scholze, Marko; Karstens, Ute; Brockmann, Patrick and Dolman, Albertus Johannes (2021): The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2018. In: Earth System Science Data, Vol. 13, No. 5: pp. 2363-2406 [PDF, 3MB]


Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990–2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO2 emissions (including cement production) account for 2624 Tg CO2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGIs and report a mean of 2588 (± 463 Tg CO2). The inversion reports 2700 Tg CO2 (± 480 Tg CO2), which is well in line with the national inventories. Over 2011–2015, the CO2 land sources and sinks from NGHGI estimates report −90 Tg C yr−1 ±  30 Tg C yr−1 while all other BU approaches report a mean sink of −98 Tg C yr−1 (± 362 Tg of C from dynamic global vegetation models only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr−1 ± 400 Tg C yr−1). This concludes that (a) current independent approaches are consistent with NGHGIs and (b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of “CO2 flux” obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4626578 (Petrescu et al., 2020a).

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