Abstract
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1% relative to 2020, with fossil emissions at 10.1±0.5GtCyr-1 (9.9±0.5GtCyr-1 when the cement carbonation sink is included), and ELUC was 1.1±0.7GtCyr-1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9±0.8GtCyr-1 (40.0±2.9GtCO2). Also, for 2021, GATM was 5.2±0.2GtCyr-1 (2.5±0.1ppmyr-1), SOCEAN was 2.9 ±0.4GtCyr-1, and SLAND was 3.5±0.9GtCyr-1, with a BIM of -0.6GtCyr-1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71±0.1ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0% (0.1% to 1.9%) globally and atmospheric CO2 concentration reaching 417.2ppm, more than 50% above pre-industrial levels (around 278ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959-2021, but discrepancies of up to 1GtCyr-1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at 10.18160/GCP-2022 (Friedlingstein et al., 2022b).
Original language | English |
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Pages (from-to) | 4811-4900 |
Number of pages | 90 |
Journal | Earth System Science Data |
Volume | 14 |
Issue number | 11 |
Early online date | 11 Nov 2022 |
DOIs | |
Publication status | Published - 2022 |
Bibliographical note
Funding Information:We thank all people and institutions who provided the data used in this Global Carbon Budget 2022 and the Global Carbon Project members for their input throughout the development of this publication. We thank Nigel Hawtin for producing Figs. 2 and 14. We thank Thomas Hawes for technical support with the data management pipeline. We thank Ed Dlugokencky for providing atmospheric CO measurements. We thank Ian G. C. Ashton, Fatemeh Cheginig, Trang T. Chau, Sam Ditkovsky, Christian Ethé, Amanda R. Fay, Lonneke Goddijn-Murphy, Thomas Holding, Fabrice Lacroix, Enhui Liao, Galen A. McKinley, Shijie Shu, Richard Sims, Jade Skye, Andrew J. Watson, David Willis, and David K. Woolf for their involvement in the development, use, and analysis of the models and data products used here. Daniel Kennedy thanks all the scientists, software engineers, and administrators who contributed to the development of CESM2. We thank Joe Salisbury, Doug Vandemark, Christopher W. Hunt, and Peter Landschützer, who contributed to the provision of surface ocean CO observations for the year 2021 (see Table A5). We also thank Benjamin Pfeil, Rocío Castaño-Primo, and Stephen D. Jones of the Ocean Thematic Centre of the EU Integrated Carbon Observation System (ICOS) Research Infrastructure; Eugene Burger of NOAA's Pacific Marine Environmental Laboratory; and Alex Kozyr of NOAA's National Centers for Environmental Information for their contribution to surface ocean CO data and metadata management. This is PMEL contribution 5434. We thank the scientists, institutions, and funding agencies responsible for the collection and quality control of the data in SOCAT and the International Ocean Carbon Coordination Project (IOCCP), the Surface Ocean Lower Atmosphere Study (SOLAS), and the Integrated Marine Biosphere Research (IMBeR) program for their support. We thank data providers ObsPack GLOBALVIEWplus v7.0 and NRT v7.2 for atmospheric CO observations. We thank the individuals and institutions that provided the databases used for the model evaluations used here. We thank Fortunat Joos, Samar Khatiwala, and Timothy DeVries for providing historical data. Matthew J. McGrath thanks the whole ORCHIDEE group. Ian Harris thanks the Japan Meteorological Agency (JMA) for producing the Japanese 55-year Reanalysis (JRA-55). Anthony P. Walker thanks ORNL, which is managed by UT-Battelle, LLC, for the DOE under contract DE-AC05-1008 00OR22725. Yosuke Niwa thanks CSIRO, EC, EMPA, FMI, IPEN, JMA, LSCE, NCAR, NIES, NILU, NIWA, NOAA, SIO, and TU/NIPR for providing data for NISMON-CO. Xiangjun Tian thanks Zhe Jin, Yilong Wang, Tao Wang, and Shilong Piao for their contributions to the GONGGA inversion system. Bo Zheng thanks the comments and suggestions from Philippe Ciais and Frédéric Chevallier. Frédéric Chevallier thanks Marine Remaud, who maintained the atmospheric transport model for the CAMS inversion. Paul I. Palmer thanks Liang Feng and acknowledges ongoing support from the National Centre for Earth Observation. Junjie Liu thanks the Jet Propulsion Laboratory, California Institute of Technology. Wiley Evans thanks the Tula Foundation for funding support. Australian ocean CO data were sourced from Australia's Integrated Marine Observing System (IMOS); IMOS is enabled by the National Collaborative Research Infrastructure Strategy (NCRIS). Margot Cronin thanks Anthony English, Clynt Gregory, and Gordon Furey (P&O Maritime Services) for their support. Nathalie Lefèvre thanks the crew of the Cap San Lorenzo and the US IMAGO of IRD Brest for technical support. Henry C. Bittig is grateful for the skilful technical support of Michael Glockzin and Bernd Sadkowiak. Meike Becker and Are Olsen thank Sparebanken Vest/Agenda Vestlandet for their support for the observations on the Statsraad Lehmkuhl. Thanos Gkritzalis thanks the personnel and crew of Simon Stevin. Matthew W. Jones thanks Anthony J. De-Gol for his technical and conceptual assistance with the development of GCP-GridFED. FAOSTAT is funded by FAO member states through their contributions to the FAO Regular Programme; data contributions by national experts are gratefully acknowledged. The views expressed in this paper are the authors' only and do not necessarily reflect those of FAO. Finally, we thank all funders who have supported the individual and joint contributions to this work (see Table A9), the reviewers of this manuscript and previous versions, and the many researchers who have provided feedback.
Publisher Copyright:
© 2022 Pierre Friedlingstein et al.