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The consolidated European synthesis of CO2 emissions and removals for EU27 and UK: 1990-2018.

Authors :
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
Janssens-Maenhout, Greet
Grassi, Giacomo
Nabuurs, Gert-Jan
Regnier, Pierre
Lauerwald, Ronny
Kuhnert, Matthias
Balcovič, Juraj
Schelhaas, Mart-Jan
van der Gon, Hugo A. C. Denier
Solazzo, Efisio
Source :
Earth System Science Data Discussions; 12/18/2020, p1-73, 73p
Publication Year :
2020

Abstract

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO<subscript>2</subscript>), 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 CO<subscript>2</subscript> 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 modelling estimates, over the period 1990-2018. BU and TD products are compared with European national GHG inventories (NGHGI) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGI, 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), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGI with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO<subscript>2</subscript> fossil) and the use of different land use definitions for reporting emissions from Land Use, Land Use Change and Forestry (LULUCF) activities (CO<subscript>2</subscript> land). At the EU27 + UK level, the NGHGI (2019) fossil CO<subscript>2</subscript> emissions (including cement production) account for 2624 Tg CO<subscript>2</subscript> in 2014 while all the other seven bottom-up sources are consistent with the NGHGI and report a mean of 2588 (± 463 Tg CO<subscript>2</subscript>). The inversion reports 2700 Tg CO<subscript>2</subscript> (± 480 Tg CO<subscript>2</subscript>), well in line with the national inventories. Over 2011-2015, the CO<subscript>2</subscript> land sources/sinks from NGHGI estimates report -90 Tg C yr<superscript>-1</superscript> ± 30 Tg C while all other BU approaches report a mean sink of -98 Tg yr<superscript>-1</superscript> (± 362 Tg C from DGVMs only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr<superscript>-1</superscript> ± 400 T g C yr<superscript>-1</superscript>). This concludes that a) current independent approaches are consistent with NGHGI b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of CO<subscript>2</subscript> flux obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288883 (Petrescu et al., 2020). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18663591
Database :
Complementary Index
Journal :
Earth System Science Data Discussions
Publication Type :
Academic Journal
Accession number :
147671648
Full Text :
https://doi.org/10.5194/essd-2020-376