The consolidated European synthesis of CH4and N2O emissions for the European Union and United Kingdom: 1990-2017

Ana Maria Roxana Petrescu*, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias KuhnertGabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, Albertus Johannes Dolman

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

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Abstract

Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27 + UK). We integrate recent emission inventory data, ecosystem process-based model results and inverse modeling estimates over the period 1990-2017. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported to the UN climate convention UNFCCC secretariat in 2019. For uncertainties, we used for NGHGIs the standard deviation obtained by varying parameters of inventory calculations, reported by the member states (MSs) following the recommendations of the IPCC Guidelines. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model-specific uncertainties when reported. In comparing NGHGIs with other approaches, a key source of bias is the activities included, e.g., anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011-2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr-1 (EDGAR v5.0) and 19.0 Tg CH4 yr-1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr-1. The estimates of TD total inversions give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher-resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr-1. Coarser-resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4 yr-1) and surface network (24.4 Tg CH4 yr-1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions, and geological sources together account for the gap between NGHGIs and inversions and account for 5.2 Tg CH4 yr-1. For N2O emissions, over the 2011-2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr-1, respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr-1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr-1, respectively. The TD and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at the EU+UK scale and at the national scale. The referenced datasets related to figures are visualized at. (Petrescu et al., 2020b).

Original languageEnglish
Pages (from-to)2307-2362
Number of pages56
JournalEarth System Science Data
Volume13
Issue number5
Early online date28 May 2021
DOIs
Publication statusPublished - 28 May 2021

Bibliographical note

Acknowledgements
FAOSTAT statistics are produced and disseminated with the support of its member countries to the FAO regular budget. The views expressed in this publication are those of the author(s) and do not necessarily reflect the views or policies of FAO. We acknowledge the work of the entire EDGAR group (Marilena Muntean, Diego Guizzardi, Edwin Schaaf and Jos Olivier).

Financial support
Philippe Ciais received support of the European Research Council Synergy project SyG-2013-610028 IMBALANCE-P and from the ANR CLAND Convergence Institute. Prabir Patra received support of the Environment Research and Technology Development Fund (JPMEERF20172001, JPMEERF20182002) of the Environmental Restoration and Conservation Agency of Japan. David Basviken received support of the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement no. 725546). David Bastviken was supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement no. 725546). Tuula Aalto received support from the Caroline Herschel Framework Partnership Agreement under the EU Horizon 2020 program (FPCUP, grant no. 809596) and Academy of Finland (SOMPA, grant no. 312932). Christine D. Groot Zwaaftink received support by the Norwegian Research Council (ICOS-Norway, project 245927). Joe McNorton received financial support from the Horizon2020 CHE project (776186).

Keywords

  • GREENHOUSE-GAS EMISSIONS
  • WETLAND METHANE EMISSIONS
  • TM 4D-VAR V1.0
  • ATMOSPHERIC METHANE
  • TERRESTRIAL ECOSYSTEMS
  • BIOGEOCHEMISTRY MODEL
  • DISPERSION MODEL
  • TRANSPORT MODEL
  • FLUXES
  • SOIL

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