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Earth Syst. Sci. Data, 14, 4811–4900, 2022

https://doi.org/10.5194/essd-14-4811-2022

the Creative Commons Attribution 4.0 License.

Global Carbon Budget 2022

Pierre Friedlingstein1,2, Michael O’Sullivan1, Matthew W. Jones3, Robbie M. Andrew4, Luke Gregor5,

Judith Hauck6, Corinne Le Quéré3, Ingrid T. Luijkx7, Are Olsen8,9, Glen P. Peters4, Wouter Peters7,10,

Julia Pongratz11,12, Clemens Schwingshackl11, Stephen Sitch1, Josep G. Canadell13, Philippe Ciais14,

Robert B. Jackson15, Simone R. Alin16, Ramdane Alkama17, Almut Arneth18, Vivek K. Arora19,

Nicholas R. Bates20,21, Meike Becker8,9, Nicolas Bellouin22, Henry C. Bittig23, Laurent Bopp2,

Frédéric Chevallier14, Louise P. Chini24, Margot Cronin25, Wiley Evans26, Stefanie Falk11,

Richard A. Feely16, Thomas Gasser27, Marion Gehlen14, Thanos Gkritzalis28, Lucas Gloege29,30,

Giacomo Grassi17, Nicolas Gruber5, Özgür Gürses6, Ian Harris31, Matthew Hefner32,33,

Richard A. Houghton34, George C. Hurtt24, Yosuke Iida35, Tatiana Ilyina12, Atul K. Jain36,

Annika Jersild12, Koji Kadono35, Etsushi Kato37, Daniel Kennedy38, Kees Klein Goldewijk39,

Jürgen Knauer40,41, Jan Ivar Korsbakken4, Peter Landschützer12,28, Nathalie Lefèvre42,

Keith Lindsay43, Junjie Liu44, Zhu Liu45, Gregg Marland32,33, Nicolas Mayot3, Matthew J. McGrath14,

Nicolas Metzl42, Natalie M. Monacci46, David R. Munro47,48, Shin-Ichiro Nakaoka49, Yosuke Niwa49,40,

Kevin O’Brien51,16, Tsuneo Ono52, Paul I. Palmer53,54, Naiqing Pan55,56, Denis Pierrot57, Katie Pocock26,

Benjamin Poulter58, Laure Resplandy59, Eddy Robertson60, Christian Rödenbeck61,

Carmen Rodriguez62, Thais M. Rosan1, Jörg Schwinger63,9, Roland Séférian64, Jamie D. Shutler1,

Ingunn Skjelvan63,9, Tobias Steinhoff65, Qing Sun66, Adrienne J. Sutton16, Colm Sweeney48,

Shintaro Takao49, Toste Tanhua65, Pieter P. Tans67,68, Xiangjun Tian69, Hanqin Tian56,

Bronte Tilbrook70,71, Hiroyuki Tsujino50, Francesco Tubiello72, Guido R. van der Werf73,

Anthony P. Walker74, Rik Wanninkhof57, Chris Whitehead75, Anna Willstrand Wranne76,

Rebecca Wright3, Wenping Yuan77, Chao Yue78, Xu Yue79, Sönke Zaehle61, Jiye Zeng49, and Bo Zheng80

1Faculty of Environment, Science and Economy, University of Exeter, Exeter EX4 4QF, UK

2Laboratoire de Météorologie Dynamique/Institut Pierre-Simon Laplace, CNRS, Ecole Normale

Supérieure/Université PSL, Sorbonne Université, Ecole Polytechnique, Paris, 75231, France

3Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia,

Norwich Research Park, Norwich NR4 7TJ, UK

4CICERO Center for International Climate Research, Oslo 0349, Norway

5Environmental Physics Group, Institute of Biogeochemistry and Pollutant Dynamics and Center for Climate

Systems Modeling (C2SM), ETH Zürich, Zurich, Switzerland

6Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung,

Postfach 120161, 27515 Bremerhaven, Germany

7Environmental Sciences Group, Wageningen University, P.O. Box 47, 6700AA, Wageningen, the Netherlands

8Geophysical Institute, University of Bergen, Bergen, Norway

9Bjerknes Centre for Climate Research, Bergen, Norway

10Centre for Isotope Research, University of Groningen, Groningen, the Netherlands

11Department für Geographie, Ludwig-Maximilians-Universität Munich,

Luisenstr. 37, 80333 München, Germany

12Max Planck Institute for Meteorology, 20146 Hamburg, Germany

13CSIRO Oceans and Atmosphere, Canberra, ACT 2101, Australia

14Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ,

Université Paris-Saclay, 91191 Gif-sur-Yvette, France

15Department of Earth System Science, Woods Institute for the Environment, and Precourt Institute for Energy,

Stanford University, Stanford, CA 94305–2210, USA

Published by Copernicus Publications.

4812 P. Friedlingstein et al.: Global Carbon Budget 2022

16National Oceanic & Atmospheric Administration, Paciﬁc Marine Environmental Laboratory (NOAA/PMEL),

7600 Sand Point Way NE, Seattle, WA 98115, USA

17Joint Research Centre, European Commission, 21027 Ispra (VA), Italy

18Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research/Atmospheric

Environmental Research, 82467 Garmisch-Partenkirchen, Germany

19Canadian Centre for Climate Modelling and Analysis, Climate Research Division,

Environment and Climate Change Canada, Victoria, BC, Canada

20Bermuda Institute of Ocean Sciences (BIOS), 17 Biological Lane, St. Georges, GE01, Bermuda

21Department of Ocean and Earth Science, University of Southampton,

European Way, Southampton SO14 3ZH, UK

22Department of Meteorology, University of Reading, Reading, RG6 6BB, UK

23Leibniz Institute for Baltic Sea Research Warnemuende (IOW), Seestrasse 15, 18119 Rostock, Germany

24Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA

25Marine Institute, Galway, Ireland

26Hakai Institute, Heriot Bay, BC, Canada

27International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, 2361 Laxenburg, Austria

28Flanders Marine Institute (VLIZ), InnovOceanSite, Jacobsenstraat 1, 8400, Ostend, Belgium

29Lamont-Doherty Earth Observatory and Department of Earth and Environmental Sciences,

Columbia University, New York, NY 10027, USA

30Open Earth Foundation, Marina del Rey, CA 90292, USA

31NCAS-Climate, Climatic Research Unit, School of Environmental Sciences, University of East Anglia,

Norwich Research Park, Norwich NR4 7TJ, UK

32Research Institute for Environment, Energy, and Economics,

Appalachian State University, Boone, NC 28608, USA

33Department of Geological and Environmental Sciences,

Appalachian State University, Boone, NC 28608, USA

34Woodwell Climate Research Center, Falmouth, MA 02540, USA

35Atmosphere and Ocean Department, Japan Meteorological Agency, Minato-Ku, Tokyo 105-8431, Japan

36Department of Atmospheric Sciences, University of Illinois, Urbana, IL 61821, USA

37Institute of Applied Energy (IAE), Minato-ku, Tokyo 105-0003, Japan

38National Center for Atmospheric Research, Climate and Global Dynamics,

Terrestrial Sciences Section, Boulder, CO 80305, USA

39Department IMEW, Faculty of Geosciences, Copernicus Institute of Sustainable Development, Utrecht

University, Heidelberglaan 2, P.O. Box 80115, 3508 TC, Utrecht, the Netherlands

40Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW 2751, Australia

41Climate Science Centre, CSIRO Oceans and Atmosphere, Canberra, ACT 2601, Australia

42LOCEAN/IPSL laboratory, Sorbonne Université, CNRS/IRD/MNHN, Paris, 75252, France

43National Center for Atmospheric Research, Climate and Global Dynamics,

Oceanography Section, Boulder, CO 80305, USA

44Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91125, USA

45Department of Earth System Science, Tsinghua University, Beijing, China

46University of Alaska Fairbanks, College of Fisheries and Ocean Sciences,

P.O. Box 757220, Fairbanks, AK 99775-7220, USA

47Cooperative Institute for Research in Environmental Sciences,

University of Colorado, Boulder, CO 80305, USA

48National Oceanic & Atmospheric Administration/Global Monitoring Laboratory (NOAA/GML),

Boulder, CO 80305, USA

49Earth System Division, National Institute for Environmental Studies (NIES),

16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan

50Meteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan

51Cooperative Institute for Climate, Ocean and Ecosystem Studies (CICOES),

University of Washington, Seattle, WA 98195, USA

52Japan Fisheries Research and Education Agency, 2-12-4 Fukuura, Kanazawa-Ku, Yokohama 236-8648, Japan

53National Centre for Earth Observation, University of Edinburgh, Edinburgh, EH9 3FE, UK

54School of Geosciences, University of Edinburgh, Edinburgh, EH9 3FE, UK

Earth Syst. Sci. Data, 14, 4811–4900, 2022 https://doi.org/10.5194/essd-14-4811-2022

P. Friedlingstein et al.: Global Carbon Budget 2022 4813

55College of Forestry, Wildlife and Environment, Auburn University, Auburn, AL 36849, USA

56Schiller Institute for Integrated Science and Society, Department of Earth and Environmental Sciences,

Boston College, Chestnut Hill, MA 02467, USA

57National Oceanic & Atmospheric Administration/Atlantic Oceanographic & Meteorological Laboratory

(NOAA/AOML), Miami, FL 33149, USA

58NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD 20771, USA

59Princeton University, Department of Geosciences and Princeton Environmental Institute,

Princeton, NJ 08544, USA

60Met Ofﬁce Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK

61Max Planck Institute for Biogeochemistry, P.O. Box 600164, Hans-Knöll-Str. 10, 07745 Jena, Germany

62University of Miami, RSMAS, 4600 Rickenbacker Causeway, Miami, FL 33149, USA

63NORCE Norwegian Research Centre, Jahnebakken 5, 5007 Bergen, Norway

64CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, 31057, France

65GEOMAR Helmholtz Centre for Ocean Research Kiel, Düsternbrooker Weg 20, 24105 Kiel, Germany

66Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research,

University of Bern, Bern, Switzerland

67National Oceanic & Atmospheric Administration, Global Monitoring Laboratory (NOAA GML),

Boulder, CO 80305, USA

68Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO 80309, USA

69State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER),

Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China

70CSIRO Oceans and Atmosphere, P.O. Box 1538, Hobart, TAS 7001, Australia

71Australian Antarctic Partnership Program, University of Tasmania, Hobart, TAS 7001, Australia

72Statistics Division, Food and Agriculture Organization of the United Nations,

Via Terme di Caracalla, Rome 00153, Italy

73Department of Earth Sciences, Faculty of Science, Vrije Universiteit, 1081 Amsterdam, the Netherlands

74Environmental Sciences Division and Climate Change Science Institute,

Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA

75Sitka Tribe of Alaska, 456 Katlian Street, Sitka, AK 99835, USA

76Swedish Meteorological and Hydrological Institute, Sven Källfeltsgata 15, 426 68 Västra Frölunda, Sweden

77School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, Guangdong 510245, China

78Institute of Soil and Water Conservation, Northwest A&F University, Yangling, Shaanxi 712100, China

79School of Environmental Science and Engineering, Nanjing University of Information Science and

Technology (NUIST), Nanjing 211544, China

80Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School,

Tsinghua University, Shenzhen 518055, China

Correspondence: Pierre Friedlingstein (p.friedlingstein@exeter.ac.uk)

Received: 26 September 2022 – Discussion started: 29 September 2022

Revised: 14 October 2022 – Accepted: 14 October 2022 – Published: 11 November 2022

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 CO2emissions (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 CO2concentration is measured directly, and its

growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2sink (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 ±0.5 GtC yr−1

(9.9 ±0.5 GtC yr−1when the cement carbonation sink is included), and ELUC was 1.1 ±0.7 GtC yr−1,

https://doi.org/10.5194/essd-14-4811-2022 Earth Syst. Sci. Data, 14, 4811–4900, 2022

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EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022©Author(s)2022.ThisworkisdistributedundertheCreativeCommonsAttribution4.0License.GlobalCarbonBudget2022PierreFriedlingstein1,2,MichaelO’Sullivan1,MatthewW.Jones3,RobbieM.Andrew4,LukeGregor5,JudithHauck6,CorinneLeQuéré3,IngridT.Luijkx7,AreOlsen8,9,GlenP.Peters4,WouterPeters7,10,JuliaPongratz11,12,ClemensSchwingshackl11,StephenSitch1,JosepG.Canadell13,PhilippeCiais14,RobertB.Jackson15,SimoneR.Alin16,RamdaneAlkama17,AlmutArneth18,VivekK.Arora19,NicholasR.Bates20,21,MeikeBecker8,9,NicolasBellouin22,HenryC.Bittig23,LaurentBopp2,FrédéricChevallier14,LouiseP.Chini24,MargotCronin25,WileyEvans26,StefanieFalk11,RichardA.Feely16,ThomasGasser27,MarionGehlen14,ThanosGkritzalis28,LucasGloege29,30,GiacomoGrassi17,NicolasGruber5,ÖzgürGürses6,IanHarris31,MatthewHefner32,33,RichardA.Houghton34,GeorgeC.Hurtt24,YosukeIida35,TatianaIlyina12,AtulK.Jain36,AnnikaJersild12,KojiKadono35,EtsushiKato37,DanielKennedy38,KeesKleinGoldewijk39,JürgenKnauer40,41,JanIvarKorsbakken4,PeterLandschützer12,28,NathalieLefèvre42,KeithLindsay43,JunjieLiu44,ZhuLiu45,GreggMarland32,33,NicolasMayot3,MatthewJ.McGrath14,NicolasMetzl42,NatalieM.Monacci46,DavidR.Munro47,48,Shin-IchiroNakaoka49,YosukeNiwa49,40,KevinO’Brien51,16,TsuneoOno52,PaulI.Palmer53,54,NaiqingPan55,56,DenisPierrot57,KatiePocock26,BenjaminPoulter58,LaureResplandy59,EddyRobertson60,ChristianRödenbeck61,CarmenRodriguez62,ThaisM.Rosan1,JörgSchwinger63,9,RolandSéférian64,JamieD.Shutler1,IngunnSkjelvan63,9,TobiasSteinhoff65,QingSun66,AdrienneJ.Sutton16,ColmSweeney48,ShintaroTakao49,TosteTanhua65,PieterP.Tans67,68,XiangjunTian69,HanqinTian56,BronteTilbrook70,71,HiroyukiTsujino50,FrancescoTubiello72,GuidoR.vanderWerf73,AnthonyP.Walker74,RikWanninkhof57,ChrisWhitehead75,AnnaWillstrandWranne76,RebeccaWright3,WenpingYuan77,ChaoYue78,XuYue79,SönkeZaehle61,JiyeZeng49,andBoZheng801FacultyofEnvironment,ScienceandEconomy,UniversityofExeter,ExeterEX44QF,UK2LaboratoiredeMétéorologieDynamique/InstitutPierre-SimonLaplace,CNRS,EcoleNormaleSupérieure/UniversitéPSL,SorbonneUniversité,EcolePolytechnique,Paris,75231,France3TyndallCentreforClimateChangeResearch,SchoolofEnvironmentalSciences,UniversityofEastAnglia,NorwichResearchPark,NorwichNR47TJ,UK4CICEROCenterforInternationalClimateResearch,Oslo0349,Norway5EnvironmentalPhysicsGroup,InstituteofBiogeochemistryandPollutantDynamicsandCenterforClimateSystemsModeling(C2SM),ETHZürich,Zurich,Switzerland6Alfred-Wegener-InstitutHelmholtz-ZentrumfürPolar-undMeeresforschung,Postfach120161,27515Bremerhaven,Germany7EnvironmentalSciencesGroup,WageningenUniversity,P.O.Box47,6700AA,Wageningen,theNetherlands8GeophysicalInstitute,UniversityofBergen,Bergen,Norway9BjerknesCentreforClimateResearch,Bergen,Norway10CentreforIsotopeResearch,UniversityofGroningen,Groningen,theNetherlands11DepartmentfürGeographie,Ludwig-Maximilians-UniversitätMunich,Luisenstr.37,80333München,Germany12MaxPlanckInstituteforMeteorology,20146Hamburg,Germany13CSIROOceansandAtmosphere,Canberra,ACT2101,Australia14LaboratoiredesSciencesduClimatetdel’Environnement,LSCE/IPSL,CEA-CNRS-UVSQ,UniversitéParis-Saclay,91191Gif-sur-Yvette,France15DepartmentofEarthSystemScience,WoodsInstitutefortheEnvironment,andPrecourtInstituteforEnergy,StanfordUniversity,Stanford,CA94305–2210,USAPublishedbyCopernicusPublications.4812P.Friedlingsteinetal.:GlobalCarbonBudget202216NationalOceanic&AtmosphericAdministration,PaciﬁcMarineEnvironmentalLaboratory(NOAA/PMEL),7600SandPointWayNE,Seattle,WA98115,USA17JointResearchCentre,EuropeanCommission,21027Ispra(VA),Italy18KarlsruheInstituteofTechnology,InstituteofMeteorologyandClimateResearch/AtmosphericEnvironmentalResearch,82467Garmisch-Partenkirchen,Germany19CanadianCentreforClimateModellingandAnalysis,ClimateResearchDivision,EnvironmentandClimateChangeCanada,Victoria,BC,Canada20BermudaInstituteofOceanSciences(BIOS),17BiologicalLane,St.Georges,GE01,Bermuda21DepartmentofOceanandEarthScience,UniversityofSouthampton,EuropeanWay,SouthamptonSO143ZH,UK22DepartmentofMeteorology,UniversityofReading,Reading,RG66BB,UK23LeibnizInstituteforBalticSeaResearchWarnemuende(IOW),Seestrasse15,18119Rostock,Germany24DepartmentofGeographicalSciences,UniversityofMaryland,CollegePark,MD20742,USA25MarineInstitute,Galway,Ireland26HakaiInstitute,HeriotBay,BC,Canada27InternationalInstituteforAppliedSystemsAnalysis(IIASA),Schlossplatz1,2361Laxenburg,Austria28FlandersMarineInstitute(VLIZ),InnovOceanSite,Jacobsenstraat1,8400,Ostend,Belgium29Lamont-DohertyEarthObservatoryandDepartmentofEarthandEnvironmentalSciences,ColumbiaUniversity,NewYork,NY10027,USA30OpenEarthFoundation,MarinadelRey,CA90292,USA31NCAS-Climate,ClimaticResearchUnit,SchoolofEnvironmentalSciences,UniversityofEastAnglia,NorwichResearchPark,NorwichNR47TJ,UK32ResearchInstituteforEnvironment,Energy,andEconomics,AppalachianStateUniversity,Boone,NC28608,USA33DepartmentofGeologicalandEnvironmentalSciences,AppalachianStateUniversity,Boone,NC28608,USA34WoodwellClimateResearchCenter,Falmouth,MA02540,USA35AtmosphereandOceanDepartment,JapanMeteorologicalAgency,Minato-Ku,Tokyo105-8431,Japan36DepartmentofAtmosphericSciences,UniversityofIllinois,Urbana,IL61821,USA37InstituteofAppliedEnergy(IAE),Minato-ku,Tokyo105-0003,Japan38NationalCenterforAtmosphericResearch,ClimateandGlobalDynamics,TerrestrialSciencesSection,Boulder,CO80305,USA39DepartmentIMEW,FacultyofGeosciences,CopernicusInstituteofSustainableDevelopment,UtrechtUniversity,Heidelberglaan2,P.O.Box80115,3508TC,Utrecht,theNetherlands40HawkesburyInstitutefortheEnvironment,WesternSydneyUniversity,Penrith,NSW2751,Australia41ClimateScienceCentre,CSIROOceansandAtmosphere,Canberra,ACT2601,Australia42LOCEAN/IPSLlaboratory,SorbonneUniversité,CNRS/IRD/MNHN,Paris,75252,France43NationalCenterforAtmosphericResearch,ClimateandGlobalDynamics,OceanographySection,Boulder,CO80305,USA44JetPropulsionLaboratory,CaliforniaInstituteofTechnology,Pasadena,CA91125,USA45DepartmentofEarthSystemScience,TsinghuaUniversity,Beijing,China46UniversityofAlaskaFairbanks,CollegeofFisheriesandOceanSciences,P.O.Box757220,Fairbanks,AK99775-7220,USA47CooperativeInstituteforResearchinEnvironmentalSciences,UniversityofColorado,Boulder,CO80305,USA48NationalOceanic&AtmosphericAdministration/GlobalMonitoringLaboratory(NOAA/GML),Boulder,CO80305,USA49EarthSystemDivision,NationalInstituteforEnvironmentalStudies(NIES),16-2Onogawa,Tsukuba,Ibaraki305-8506,Japan50MeteorologicalResearchInstitute,1-1Nagamine,Tsukuba,Ibaraki305-0052,Japan51CooperativeInstituteforClimate,OceanandEcosystemStudies(CICOES),UniversityofWashington,Seattle,WA98195,USA52JapanFisheriesResearchandEducationAgency,2-12-4Fukuura,Kanazawa-Ku,Yokohama236-8648,Japan53NationalCentreforEarthObservation,UniversityofEdinburgh,Edinburgh,EH93FE,UK54SchoolofGeosciences,UniversityofEdinburgh,Edinburgh,EH93FE,UKEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget2022481355CollegeofForestry,WildlifeandEnvironment,AuburnUniversity,Auburn,AL36849,USA56SchillerInstituteforIntegratedScienceandSociety,DepartmentofEarthandEnvironmentalSciences,BostonCollege,ChestnutHill,MA02467,USA57NationalOceanic&AtmosphericAdministration/AtlanticOceanographic&MeteorologicalLaboratory(NOAA/AOML),Miami,FL33149,USA58NASAGoddardSpaceFlightCenter,BiosphericSciencesLaboratory,Greenbelt,MD20771,USA59PrincetonUniversity,DepartmentofGeosciencesandPrincetonEnvironmentalInstitute,Princeton,NJ08544,USA60MetOfﬁceHadleyCentre,FitzRoyRoad,ExeterEX13PB,UK61MaxPlanckInstituteforBiogeochemistry,P.O.Box600164,Hans-Knöll-Str.10,07745Jena,Germany62UniversityofMiami,RSMAS,4600RickenbackerCauseway,Miami,FL33149,USA63NORCENorwegianResearchCentre,Jahnebakken5,5007Bergen,Norway64CNRM,UniversitédeToulouse,Météo-France,CNRS,Toulouse,31057,France65GEOMARHelmholtzCentreforOceanResearchKiel,DüsternbrookerWeg20,24105Kiel,Germany66ClimateandEnvironmentalPhysics,PhysicsInstituteandOeschgerCentreforClimateChangeResearch,UniversityofBern,Bern,Switzerland67NationalOceanic&AtmosphericAdministration,GlobalMonitoringLaboratory(NOAAGML),Boulder,CO80305,USA68InstituteofArcticandAlpineResearch,UniversityofColorado,Boulder,CO80309,USA69StateKeyLaboratoryofTibetanPlateauEarthSystem,EnvironmentandResources(TPESER),InstituteofTibetanPlateauResearch,ChineseAcademyofSciences,Beijing,100101,China70CSIROOceansandAtmosphere,P.O.Box1538,Hobart,TAS7001,Australia71AustralianAntarcticPartnershipProgram,UniversityofTasmania,Hobart,TAS7001,Australia72StatisticsDivision,FoodandAgricultureOrganizationoftheUnitedNations,ViaTermediCaracalla,Rome00153,Italy73DepartmentofEarthSciences,FacultyofScience,VrijeUniversiteit,1081Amsterdam,theNetherlands74EnvironmentalSciencesDivisionandClimateChangeScienceInstitute,OakRidgeNationalLaboratory,OakRidge,TN37831,USA75SitkaTribeofAlaska,456KatlianStreet,Sitka,AK99835,USA76SwedishMeteorologicalandHydrologicalInstitute,SvenKällfeltsgata15,42668VästraFrölunda,Sweden77SchoolofAtmosphericSciences,SunYat-senUniversity,Zhuhai,Guangdong510245,China78InstituteofSoilandWaterConservation,NorthwestA&FUniversity,Yangling,Shaanxi712100,China79SchoolofEnvironmentalScienceandEngineering,NanjingUniversityofInformationScienceandTechnology(NUIST),Nanjing211544,China80InstituteofEnvironmentandEcology,TsinghuaShenzhenInternationalGraduateSchool,TsinghuaUniversity,Shenzhen518055,ChinaCorrespondence:PierreFriedlingstein(p.friedlingstein@exeter.ac.uk)Received:26September2022–Discussionstarted:29September2022Revised:14October2022–Accepted:14October2022–Published:11November2022Abstract.Accurateassessmentofanthropogeniccarbondioxide(CO2)emissionsandtheirredistributionamongtheatmosphere,ocean,andterrestrialbiosphereinachangingclimateiscriticaltobetterunderstandtheglobalcarboncycle,supportthedevelopmentofclimatepolicies,andprojectfutureclimatechange.Herewedescribeandsynthesizedatasetsandmethodologiestoquantifytheﬁvemajorcomponentsoftheglobalcarbonbudgetandtheiruncertainties.FossilCO2emissions(EFOS)arebasedonenergystatisticsandcementproductiondata,whileemissionsfromland-usechange(ELUC),mainlydeforestation,arebasedonlanduseandland-usechangedataandbookkeepingmodels.AtmosphericCO2concentrationismeasureddirectly,anditsgrowthrate(GATM)iscomputedfromtheannualchangesinconcentration.TheoceanCO2sink(SOCEAN)isestimatedwithglobaloceanbiogeochemistrymodelsandobservation-baseddataproducts.TheterrestrialCO2sink(SLAND)isestimatedwithdynamicglobalvegetationmodels.Theresultingcarbonbudgetimbalance(BIM),thedifferencebetweentheestimatedtotalemissionsandtheestimatedchangesintheatmosphere,ocean,andterrestrialbiosphere,isameasureofimperfectdataandunderstandingofthecontemporarycarboncycle.Alluncertaintiesarereportedas±1σ.Fortheyear2021,EFOSincreasedby5.1%relativeto2020,withfossilemissionsat10.1±0.5GtCyr−1(9.9±0.5GtCyr−1whenthecementcarbonationsinkisincluded),andELUCwas1.1±0.7GtCyr−1,https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224814P.Friedlingsteinetal.:GlobalCarbonBudget2022foratotalanthropogenicCO2emission(includingthecementcarbonationsink)of10.9±0.8GtCyr−1(40.0±2.9GtCO2).Also,for2021,GATMwas5.2±0.2GtCyr−1(2.5±0.1ppmyr−1),SOCEANwas2.9±0.4GtCyr−1,andSLANDwas3.5±0.9GtCyr−1,withaBIMof−0.6GtCyr−1(i.e.thetotalestimatedsourcesweretooloworsinksweretoohigh).TheglobalatmosphericCO2concentrationaveragedover2021reached414.71±0.1ppm.Preliminarydatafor2022suggestanincreaseinEFOSrelativeto2021of+1.0%(0.1%to1.9%)globallyandatmosphericCO2concentrationreaching417.2ppm,morethan50%abovepre-industriallevels(around278ppm).Overall,themeanandtrendinthecomponentsoftheglobalcarbonbudgetareconsis-tentlyestimatedovertheperiod1959–2021,butdiscrepanciesofupto1GtCyr−1persistfortherepresentationofannualtosemi-decadalvariabilityinCO2ﬂuxes.Comparisonofestimatesfrommultipleapproachesandobservationsshows(1)apersistentlargeuncertaintyintheestimateofland-usechangeemissions,(2)alowagreementbetweenthedifferentmethodsonthemagnitudeofthelandCO2ﬂuxinthenorthernextratropics,and(3)adiscrepancybetweenthedifferentmethodsonthestrengthoftheoceansinkoverthelastdecade.Thislivingdataupdatedocumentschangesinthemethodsanddatasetsusedinthisnewglobalcarbonbudgetandtheprogressinunderstandingoftheglobalcarboncyclecomparedwithpreviouspublicationsofthisdataset.Thedatapresentedinthisworkareavailableathttps://doi.org/10.18160/GCP-2022(Friedlingsteinetal.,2022b).Executivesummary.GlobalfossilCO2emissions(includingce-mentcarbonation)furtherincreasedin2022,beingnowslightlyabovetheirpre-COVID-19pandemic2019level.The2021emis-sionincreasewas0.46GtCyr−1(1.7GtCO2yr−1),bringing2021emissionsto9.9±0.5GtCyr−1(36.3±1.8GtCO2yr−1),sameasthe2019emissionslevel.Preliminaryestimatesbasedondataavail-ablesuggestfossilCO2emissionscontinuedtoincreaseby1.0%in2022relativeto2021(0.1%to1.9%),bringingemissionsof10.0GtCyr−1(36.6GtCO2yr−1),slightlyabovethe2019level.Emissionsfromcoal,oil,andgasin2022areexpectedtobeabovetheir2021levels(by1.0%,2.2%and−0.2%respectively).Regionally,emissionsin2022areexpectedtohavedecreasedby0.9%inChina(3.1GtC,11.4GtCO2)and0.8%intheEuropeanUnion(0.8GtC,2.8GtCO2)butincreasedby1.5%intheUnitedStates(1.4GtC,5.1GtCO2),6%inIndia(0.8GtC,2.9GtCO2),and1.7%intherestoftheworld(4.2GtC,15.4GtCO2).FossilCO2emissionsdecreasedin24countriesduringthedecade2012–2021.Altogether,these24countriescontributedabout2.4GtCyr−1(8.8GtCO2)fossilfuelCO2emissionsoverthelastdecade,aboutaquarterofglobalCO2fossilemissions.GlobalCO2emissionsfromlanduse,land-usechange,andforestry(LUC)averagedat1.2±0.7GtCyr−1(4.5±2.6GtCO2yr−1)forthe2012–2021periodwithapreliminaryprojectionfor2022of1.1±0.7GtCyr−1(3.9±2.6GtCO2yr−1).Asmalldecreaseoverthepast2decadesisnotrobustgiventhelargemodeluncertainty.Emissionsfromdeforestation,themaindriverofglobalgrosssources,remainhighat1.8±0.4GtCyr−1overthe2012–2021period,highlightingthestrongpotentialforemissionsreductionswhenhaltingdefor-estation.Sequestrationof0.9±0.3GtCyr−1throughafforestationorreafforestationandforestryoffsetshalfofthedeforestationemissions.Emissionsfromotherland-usetransitionsandfrompeatdrainageandpeatﬁreaddfurthersmallcontributions.Thehighestemittersduring2012–2021indescendingorderwereBrazil,Indonesia,andtheDemocraticRepublicoftheCongo,withthesethreecountriescontributingmorethanhalfoftheglobaltotalland-useemissions.Theremainingcarbonbudgetfora50%likelihoodtolimitglobalwarmingto1.5,1.7,and2◦Chas,respectively,reducedto105GtC(380GtCO2),200GtC(730GtCO2),and335GtC(1230GtCO2)fromthebeginningof2023,equivalentto9,18,and30years,as-suming2022emissionslevels.Totalanthropogenicemissionswere11.0GtCyr−1(40.2GtCO2yr−1)in2021,withapreliminaryesti-mateof11.1GtCyr−1(40.5GtCO2yr−1)for2022.Theremainingcarbonbudgettokeepglobaltemperaturesbelowtheseclimatetar-getshasshrunkby32GtC(121GtCO2)sincetheIPCCAR6Work-ingGroup1assessmentbasedondataupto2019.ReachingzeroCO2emissionsby2050entailsatotalanthropogenicCO2emis-sionslineardecreasebyabout0.4GtC(1.4GtCO2)eachyear,com-parabletothedecreaseduring2020,highlightingthescaleoftheactionneeded.TheconcentrationofCO2intheatmosphereissettoreach417.2ppmin2022,51%abovepre-industriallevels.Theatmo-sphericCO2growthwas5.2±0.02GtCyr−1duringthedecade2012–2021(48%oftotalCO2emissions)withapreliminary2022growthrateestimateofaround5.3GtCyr−1(2.5ppm).TheoceanCO2sinkresumedamorerapidgrowthinthepast2decadesafterlowornogrowthduringthe1991–2002period.How-ever,thegrowthoftheoceanCO2sinkinthepastdecadehasanuncertaintyofafactorof3,withestimatesbasedondataprod-uctsandestimatesbasedonmodelsshowinganoceansinktrendof+0.7GtCyr−1perdecadeand+0.2GtCyr−1perdecadesince2010,respectively.ThediscrepancyinthetrendoriginatesfromalllatitudesbutislargestintheSouthernOcean.TheoceanCO2sinkwas2.9±0.4GtCyr−1duringthedecade2012–2021(26%oftotalCO2emissions),withasimilarpreliminaryestimateof2.9GtCyr−1for2022.ThelandCO2sinkcontinuedtoincreaseduringthe2012–2021periodprimarilyinresponsetoincreasedatmosphericCO2,al-beitwithlargeinterannualvariability.ThelandCO2sinkwas3.1±0.6GtCyr−1duringthedecade2012–2021(29%ofto-talCO2emissions),0.4GtCyr−1largerthanduringthepreviousdecade(2000–2009),withapreliminary2022estimateofaround3.4GtCyr−1.Year-to-yearvariabilityinthelandsinkisabout1GtCyr−1anddominatestheyear-to-yearchangesintheglobalat-mosphericCO2concentration,implyingthatsmallannualchangesinanthropogenicemissions(suchasthefossilfuelemissionde-EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224815Figure1.SurfaceaverageatmosphericCO2concentration(ppm).Since1980,monthlydataarefromNOAA/GML(DlugokenckyandTans,2022)andarebasedonanaverageofdirectatmosphericCO2measurementsfrommultiplestationsinthemarineboundarylayer(MasarieandTans,1995).The1958–1979monthlydataarefromtheScrippsInstitutionofOceanography,basedonanaverageofdirectatmosphericCO2measurementsfromtheMaunaLoaandSouthPolestations(Keelingetal.,1976).Toaccountforthediffer-enceinmeanCO2andseasonalitybetweentheNOAA/GMLandtheScrippsstationnetworksusedhere,theScrippssurfaceaver-age(fromtwostations)wasde-seasonalizedandadjustedtomatchtheNOAA/GMLsurfaceaverage(frommultiplestations)byaddingthemeandifferenceof0.667ppm,calculatedherefromoverlappingdataduring1980–2012.creasein2020)arehardtodetectintheatmosphericCO2obser-vations.1IntroductionTheconcentrationofcarbondioxide(CO2)intheatmo-spherehasincreasedfromapproximately278partspermil-lion(ppm)in1750(Gulevetal.,2021),thebeginningoftheIndustrialEra,to414.7±0.1ppmin2021(DlugokenckyandTans,2022;Fig.1).TheatmosphericCO2increaseabovepre-industriallevelswas,initially,primarilycausedbythereleaseofcarbontotheatmospherefromdeforestationandotherland-usechangeactivities(Canadelletal.,2021).WhileemissionsfromfossilfuelsstartedbeforetheIndus-trialEra,theybecamethedominantsourceofanthropogenicemissionstotheatmospherefromaround1950,andtheirrel-ativesharehascontinuedtoincreaseuntilpresent.Anthro-pogenicemissionsoccurontopofanactivenaturalcarboncyclethatcirculatescarbonbetweenthereservoirsoftheatmosphere,ocean,andterrestrialbiosphereontimescalesfromsub-dailytomillennia,whileexchangeswithgeologicreservoirsoccuratlongertimescales(Archeretal.,2009).Theglobalcarbonbudget(GCB)presentedherereferstothemean,variations,andtrendsintheperturbationofCO2intheenvironment,referencedtothebeginningoftheIn-dustrialEra(deﬁnedhereas1750).Thispaperdescribesthecomponentsoftheglobalcarboncycleoverthehistor-icalperiodwithastrongerfocusontherecentperiod(since1958,theonsetofatmosphericCO2measurements),thelastdecade(2012–2021),thelastyear(2021),andthecurrentyear(2022).Finally,itprovidescumulativeemissionsfromfossilfuelsandland-usechangesincetheyear1750(thepre-industrialperiod)andsincetheyear1850(thereferenceyearforhistoricalsimulationsinIPCCAR6)(Eyringetal.,2016).WequantifytheinputofCO2totheatmospherebyemis-sionsfromhumanactivities;thegrowthrateofatmosphericCO2concentration;andtheresultingchangesinthestorageofcarboninthelandandoceanreservoirsinresponsetoin-creasingatmosphericCO2levels,climatechangeandvari-ability,andotheranthropogenicandnaturalchanges(Fig.2).Anunderstandingofthisperturbationbudgetovertimeandtheunderlyingvariabilityandtrendsofthenaturalcarboncy-cleisnecessarytounderstandtheresponseofnaturalsinkstochangesinclimate,CO2,andland-usechangedriversandtoquantifyemissionscompatiblewithagivenclimatestabi-lizationtarget.ThecomponentsoftheCO2budgetthatarereportedannu-allyinthispaperincludeseparateandindependentestimatesfortheCO2emissionsfrom(1)fossilfuelcombustionandoxidationfromallenergyandindustrialprocesses,includingcementproductionandcarbonation(EFOS;GtCyr−1),and(2)theemissionsresultingfromdeliberatehumanactivitiesonland,includingthoseleadingtoland-usechange(ELUC;GtCyr−1)andtheirpartitioningamong(3)thegrowthrateofatmosphericCO2concentration(GATM;GtCyr−1)andtheuptakeofCO2(the“CO2sinks”)in(4)theocean(SOCEAN;GtCyr−1)and(5)onland(SLAND;GtCyr−1).TheCO2sinksasdeﬁnedhereconceptuallyincludetheresponseoftheland(includinginlandwatersandestuaries)andocean(includingcoastalandmarginalseas)toelevatedCO2andchangesinclimateandotherenvironmentalconditions,al-thoughinpracticenotallprocessesarefullyaccountedfor(seeSect.2.7).Globalemissionsandtheirpartitioningamongtheatmosphere,ocean,andlandareinbalanceintherealworld.Duetothecombinationofimperfectspatialand/ortemporaldatacoverage,errorsineachestimate,andsmallertermsnotincludedinourbudgetestimate(discussedinSect.2.7),theindependentestimates(1)to(5)abovedonotnecessarilyadduptozero.Wetherefore(i)additionallyassessasetofglobalatmosphericinversionsystemresultsthatbydesignclosetheglobalcarbonbalance(seeSect.2.6)and(i)estimateabudgetimbalance(BIM),whichisamea-sureofthemismatchbetweentheestimatedemissionsandtheestimatedchangesintheatmosphere,land,andocean,asfollows:BIM=EFOS+ELUC−(GATM+SOCEAN+SLAND).(1)GATMisusuallyreportedinppmyr−1,whichweconverttounitsofcarbonmassperyear,GtCyr−1,using1ppm=2.124GtC(Ballantyneetal.,2012;Table1).Allquantitiesarepresentedinunitsofgigatonnesofcarbon(GtC,1015gC),https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224816P.Friedlingsteinetal.:GlobalCarbonBudget2022Figure2.Schematicrepresentationoftheoverallperturbationoftheglobalcarboncyclecausedbyanthropogenicactivitiesaveragedgloballyforthedecade2012–2021.Seelegendsforthecorrespondingarrowsandunits.TheuncertaintyintheatmosphericCO2growthrateisverysmall(±0.02GtCyr−1)andisneglectedfortheﬁgure.Theanthropogenicperturbationoccursontopofanactivecarboncycle,withﬂuxesandstocksrepresentedinthebackgroundandtakenfromCanadelletal.(2021)forallnumbers,exceptforthecarbonstocksincoasts,whicharefromaliteraturereviewofcoastalmarinesediments(PriceandWarren,2016).whichisthesameaspetagramsofcarbon(PgC;Table1).UnitsofgigatonnesofCO2(orbilliontonnesofCO2)usedinpolicyareequalto3.664multipliedbythevalueinunitsofGtC.WealsoquantifyEFOSandELUCbycountry,includingbothterritorialandconsumption-basedaccountingforEFOS(seeSect.2),anddiscussmissingtermsfromsourcesotherthanthecombustionoffossilfuels(seeSect.2.7andAp-pendixD1andD2).TheglobalCO2budgethasbeenassessedbytheInter-governmentalPanelonClimateChange(IPCC)inallassess-mentreports(Prenticeetal.,2001;Schimeletal.,1995;Wat-sonetal.,1990;Denmanetal.,2007;Ciaisetal.,2013;Canadelletal.,2021)andbyothers(e.g.Ballantyneetal.,2012).TheGlobalCarbonProject(GCP,https://www.globalcarbonproject.org,lastaccess:25September2022)hascoordinatedthiscooperativecommunityeffortforthean-nualpublicationofglobalcarbonbudgetsfortheyear2005(Raupachetal.,2007;includingfossilemissionsonly),year2006(Canadelletal.,2007),year2007(GCP,2007),year2008(LeQuéréetal.,2009),year2009(Friedlingsteinetal.,2010),year2010(Petersetal.,2012b),year2012(LeQuéréetal.,2013;Petersetal.,2013),year2013(LeQuéréetal.,2014),year2014(LeQuéréetal.,2015a;Friedlingsteinetal.,2014),year2015(Jacksonetal.,2016;LeQuéréetal.,2015b),year2016(LeQuéréetal.,2016),year2017(LeQuéréetal.,2018a;Petersetal.,2017),year2018(LeQuéréetal.,2018b;Jacksonetal.,2018),year2019(Friedling-steinetal.,2019;Jacksonetal.,2019;Petersetal.,2020),year2020(Friedlingsteinetal.,2020;LeQuéréetal.,2021),andmorerecentlytheyear2021(Friedlingsteinetal.,2022a;Jacksonetal.,2022).Eachofthesepapersupdatedpreviousestimateswiththelatestavailableinformationfortheentiretimeseries.Weadoptarangeof±1standarddeviation(σ)toreporttheuncertaintiesinourestimates,representingalikelihoodof68%thatthetruevaluewillbewithintheprovidedrangeiftheerrorshaveaGaussiandistributionandnobiasisas-sumed.ThischoicereﬂectsthedifﬁcultyofcharacterizingtheuncertaintyintheCO2ﬂuxesbetweentheatmosphereandtheoceanandlandreservoirsindividually,particularlyonanannualbasis,aswellasthedifﬁcultyofupdatingtheCO2emissionsfromland-usechange.Alikelihoodof68%providesanindicationofourcurrentcapabilitytoquantifyeachtermanditsuncertaintygiventheavailableinforma-tion.Theuncertaintiesreportedherecombinestatisticalanal-ysisoftheunderlyingdata,assessmentsofuncertaintiesinthegenerationofthedatasets,andexpertjudgementofthelikelihoodofresultslyingoutsidethisrange.Thelimitationsofcurrentinformationarediscussedinthepaperandhavebeenexaminedindetailelsewhere(Ballantyneetal.,2015;Zscheischleretal.,2017).Wealsouseaqualitativeassess-EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224817Table1.Factorsusedtoconvertcarboninvariousunits(byconvention,Unit1=Unit2×conversion).Unit1Unit2ConversionSourceGtC(gigatonnesofcarbon)ppm(partspermillion)a2.124bBallantyneetal.(2012)GtC(gigatonnesofcarbon)PgC(petagramsofcarbon)1SIunitconversionGtCO2(gigatonnesofcarbondioxide)GtC(gigatonnesofcarbon)3.66444.01/12.011inmassequivalentGtC(gigatonnesofcarbon)MtC(megatonnesofcarbon)1000SIunitconversionaMeasurementsofatmosphericCO2concentrationhaveunitsofdry-airmolefraction.“ppm”isanabbreviationforµmolmol−1dryair.bTheuseofafactorof2.124assumesthatalloftheatmosphereiswellmixedwithin1year.Inreality,onlythetroposphereiswellmixed,andthegrowthrateofCO2concentrationinthelesswell-mixedstratosphereisnotmeasuredbysitesfromtheNOAAnetwork.Usingafactorof2.124makestheapproximationthatthegrowthrateofCO2concentrationinthestratosphereequalsthatofthetroposphereonayearlybasis.mentofconﬁdenceleveltocharacterizetheannualestimatesfromeachtermbasedonthetype,amount,quality,andcon-sistencyoftheevidenceasdeﬁnedbytheIPCC(Stockeretal.,2013).Thispaperprovidesadetaileddescriptionofthedatasetsandmethodologyusedtocomputetheglobalcarbonbud-getestimatesfortheindustrialperiod(from1750to2022)andinmoredetailfortheperiodsince1959.Thispaperisupdatedeveryyearusingtheformatof“livingdata”tokeeparecordofbudgetversionsandthechangesinnewdata,revisionsofdata,andchangesinmethodologythatleadtochangesinestimatesofthecarbonbudget.Addi-tionalmaterialsassociatedwiththereleaseofeachnewver-sionwillbepostedattheGlobalCarbonProject(GCP)website(http://www.globalcarbonproject.org/carbonbudget,lastaccess:25September2022),withfossilfuelemissionsalsoavailablethroughtheGlobalCarbonAtlas(http://www.globalcarbonatlas.org,lastaccess:25September2022).Allunderlyingdatausedtoproducethebudgetcanalsobefoundathttps://globalcarbonbudget.org/(lastaccess:25September2022).Withthisapproach,weaimtoprovidethehighesttransparencyandtraceabilityinthereportingofCO2,thekeydriverofclimatechange.2MethodsMultipleorganizationsandresearchgroupsaroundtheworldgeneratedtheoriginalmeasurementsanddatausedtocom-pletetheglobalcarbonbudget.Theeffortpresentedhereisthusmainlyoneofsynthesis,whereresultsfromindivid-ualgroupsarecollated,analysed,andevaluatedforconsis-tency.Wefacilitateaccesstooriginaldatawiththeunder-standingthatprimarydatasetswillbereferencedinfuturework(seeTable2forhowtocitethedatasets).Descrip-tionsofthemeasurements,models,andmethodologiesfol-lowbelow,anddetaileddescriptionsofeachcomponentareprovidedelsewhere.Thisisthe17thversionoftheglobalcarbonbudgetandthe11threvisedversionintheformatofalivingdataupdateinEarthSystemScienceData.ItbuildsonthelatestpublishedglobalcarbonbudgetofFriedlingsteinetal.(2022a).Themainchangesaretheinclusionof(1)datatoyear2021andaprojectionfortheglobalcarbonbudgetfortheyear2022,(2)theinclusionofcountry-levelestimatesofELUC,and(3)aprocess-baseddecompositionofELUCintoitsmaincompo-nents(deforestation;afforestation,reafforestation,andwoodharvest;emissionsfromorganicsoils;andnetﬂuxfromothertransitions).Themainmethodologicaldifferencesbetweenrecentan-nualcarbonbudgets(2018–2022)aresummarizedinTable3,andpreviouschangessince2006areprovidedinTableA7.2.1FossilCO2emissions(EFOS)2.1.1Historicalperiod1850–2021TheestimatesofglobalandnationalfossilCO2emissions(EFOS)includetheoxidationoffossilfuelsthroughbothcombustion(e.g.transport,heating)andchemicaloxidation(e.g.carbonanodedecompositioninaluminiumreﬁning)ac-tivities,andthedecompositionofcarbonatesinindustrialprocesses(e.g.theproductionofcement).WealsoincludeCO2uptakefromthecementcarbonationprocess.Severalemissionsourcesarenotestimatedornotfullycovered:cov-erageofemissionsfromlimeproductionisnotglobal,anddecompositionofcarbonatesinglassandceramicproductionareincludedonlyforthe“Annex1”countriesoftheUnitedNationsFrameworkConventiononClimateChange(UN-FCCC)forlackofactivitydata.Theseomissionsarecon-sideredtobeminor.Short-cyclecarbonemissions–forex-amplefromcombustionofbiomass–arenotincludedherebutareaccountedforintheCO2emissionsfromlanduse(seeSect.2.2).OurestimatesoffossilCO2emissionsarederivedusingthestandardapproachofactivitydataandemissionfactors,relyingondatacollectionbymanyotherparties.Ourgoalistoproducethebestestimateofthisﬂux,andwethere-foreuseaprioritizationframeworktocombinedatafromdifferentsourcesthathaveuseddifferentmethods,whilebe-ingcarefultoavoiddoublecountingandundercountingofemissionssources.TheCDIAC-FFemissionsdataset,de-rivedlargelyfromUNenergydata,formsthefoundation,andweextendemissionstoyearY-1usingenergygrowthratesreportedbytheBPenergycompany.Wethenproceedtore-placeestimatesusingdatafromwhatweconsidertobesupe-https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224818P.Friedlingsteinetal.:GlobalCarbonBudget2022Table2.Howtocitetheindividualcomponentsoftheglobalcarbonbudgetpresentedhere.ComponentPrimaryreferenceGlobalfossilCO2emissions(EFOS),totalandbyfueltypeUpdatedfromAndrewandPeters(2021)NationalterritorialfossilCO2emissions(EFOS)GilﬁllanandMarland(2021),UNFCCC(2022)Nationalconsumption-basedfossilCO2emissions(EFOS)bycountry(consumption)Petersetal.(2011b),updatedasdescribedinthispaperNetland-usechangeﬂux(ELUC)Thispaper(seeTable4forindividualmodelreferences)GrowthrateinatmosphericCO2concentration(GATM)DlugokenckyandTans(2022)OceanandlandCO2sinks(SOCEANandSLAND)Thispaper(seeTable4forindividualmodelanddataproductreferences)riorsources,forexampleAnnex1countries’ofﬁcialsubmis-sionstotheUNFCCC.Alldatapointsarepotentiallysubjecttorevision,notjustthelatestyear.Forthefulldetails,seeAndrewandPeters(2021).OtherestimatesofglobalfossilCO2emissionsexist,andthesearecomparedbyAndrew(2020a).ThemostcommonreasonfordifferencesinestimatesofglobalfossilCO2emis-sionsisadifferenceinwhichemissionssourcesareincludedinthedatasets.DatasetssuchasthosepublishedbytheenergycompanyBP,theUSEnergyInformationAdminis-tration,andtheInternationalEnergyAgency’s“CO2emis-sionsfromfuelcombustion”areallgenerallylimitedtoemis-sionsfromcombustionoffossilfuels.Incontrast,datasetssuchasPRIMAP-hist,CEDS,EDGAR,andGCP’sdatasetaimtoincludeallsourcesoffossilCO2emissions.SeeAn-drew(2020a)fordetailedcomparisonsanddiscussion.CementabsorbsCO2fromtheatmosphereoveritslife-time,aprocessknownas“cementcarbonation”.Weesti-matethisCO2sinkfrom1931onwardsastheaverageoftwostudiesintheliterature(Caoetal.,2020;Guoetal.,2021).Bothstudiesusethesamemodel,developedbyXietal.(2016),withdifferentparameterizationsandinputdata,withtheestimateofGuoandcolleaguesbeingarevisionofXietal.(2016).Thetrendsofthetwostudiesareverysim-ilar.Sincecarbonationisafunctionofbothcurrentandpre-viouscementproduction,weextendtheseestimatesto2022byusingthegrowthratederivedfromthesmoothedcementemissions(10-yearsmoothing)ﬁttedtothecarbonationdata.Inthepresentbudget,wealwaysincludethecementcar-bonationcarbonsinkinthefossilCO2emissioncomponent(EFOS).WeusetheKayaIdentityforasimpledecompositionofCO2emissionsintothekeydrivers(Raupachetal.,2007).Whiletherearevariations(Petersetal.,2017),wefocushereonadecompositionofCO2emissionsintopopulation,GDPperperson,energyuseperGDP,andCO2emissionsperen-ergy.Multiplyingtheseindividualcomponentstogetherre-turnstheCO2emissions.Usingthedecomposition,itispos-sibletoattributethechangeinCO2emissionstothechangeineachofthedrivers.Thismethodgivesaﬁrst-orderunder-standingofwhatcausesCO2emissionstochangeeachyear.2.1.2The2022projectionWeprovideaprojectionofglobalCO2emissionsin2022bycombiningseparateprojectionsforChina,USA,EU,India,andforallothercountriescombined.Themethodsaredif-ferentforeachofthese.ForChinawecombinemonthlyfos-silfuelproductiondatafromtheNationalBureauofStatis-tics,importandexportdatafromtheCustomsAdministra-tion,andmonthlycoalconsumptionestimatesfromSXCoal(2022),givinguspartialdataforthegrowthratestodateofnaturalgas,petroleum,andcement,andoftheconsump-tionitselfforrawcoal.Wethenusearegressionmodeltoprojectfull-yearemissionsbasedonhistoricalobserva-tions.FortheUSAourprojectionistakendirectlyfromtheEnergyInformationAdministration’s(EIA)Short-TermEn-ergyOutlook(EIA,2022),combinedwiththeyear-to-dategrowthrateofcementclinkerproduction.FortheEUweusemonthlyenergydatafromEurostattoderiveestimatesofmonthlyCO2emissionsthroughJuly,withcoalemissionsextendedthroughAugustusingastatisticalrelationshipwithreportedelectricitygenerationfromcoalandotherfactors.GiventheveryhighuncertaintyinEuropeanenergymar-ketsin2022,weforegoourusualhistory-basedprojectiontechniquesandinsteadusetheyear-to-dategrowthrateasthefull-yeargrowthrateforbothcoalandnaturalgas.EUemissionsfromoilarederivedusingtheEIA’sprojectionofoilconsumptionforEurope.EUcementemissionsarebasedonavailableyear-to-datedatafromthreeofthelargestpro-ducers,Germany,Poland,andSpain.India’sprojectedemis-sionsarederivedfromestimatesthroughJuly(Augustforoil)usingthemethodsofAndrew(2020b)andextrapolatedassumingnormalseasonalpatterns.EmissionsfortherestoftheworldarederivedusingprojectedgrowthineconomicproductionfromtheIMF(2022)combinedwithextrapo-latedchangesinemissionsintensityofeconomicproduction.EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224819Table3.Themainmethodologicalchangesintheglobalcarbonbudgetsince2018.Methodologicalchangesintroducedinanygivenyeararekeptforthefollowingyearsunlessotherwisenoted.Emptycellsmeantherewerenomethodologicalchangesintroducedthatyear.TableA7listsmethodologicalchangesfromtheﬁrstglobalcarbonbudgetpublicationupto2017.PublicationyearFossilfuelemissionsLUCemissionsReservoirsUncertaintyandotherchangesGlobalCountry(territorial)AtmosphereOceanLand2018Revisionincementemis-sionsandprojectionin-cludesEU-speciﬁcdataAggregationofoverseasterritoriesintogoverningnationsforatotalof213countries.Averageoftwobook-keepingmodelsanduseof16DGVMsUseoffouratmosphericinversionsBasedonsevenmodelsBasedon16models,withrevisedatmo-sphericforcingfromCRUNCEPtoCRUJRAIntroductionofmetricsforevaluationofindividualmodelsusingobservationsLeQuéréetal.(2018b)GCB20182019Globalemissionscalculatedassumofallcountriesplusbunkers,ratherthantakendirectlyfromCDIACAverageoftwobook-keepingmodelsanduseof15DGVMsUseofthreeatmosphericinversionsBasedonninemodelsBasedon16modelsFriedlingsteinetal.(2019)GCB20192020Cementcarbonationnowin-cludedintheEFOSesti-mate,reducingEFOSbyabout0.2GtCyr−1forthelastdecadeIndia’semissionsfromAndrew(2020a),cor-rectionstoNetherlandAntillesandArubaandSovietemissionsbefore1950asperAndrew(2020b),China’scoalemissionsin2019derivedfromofﬁcialstatistics,emissionsnowshownforEU27insteadofEU28,projectionfor2020isbasedonassessmentoffourapproachesAverageofthreebook-keepingmodels,useof17DGVMs,andestimateofgrossland-usesourcesandsinksprovidedUseofsixatmosphericinversionsBasedonninemodels;riverﬂuxrevisedandpartitionedNH,tropics,andSHBasedon17modelsFriedlingsteinetal.(2020)GCB20202021Projectionsarenolongeranassessmentoffourap-proachesOfﬁcialdataincludedforanumberofadditionalcoun-tries,newestimatesforSouthKorea,addedemis-sionsfromlimeproductioninChinaELUCestimatecom-paredtotheestimatesadoptedinnationalGHGinventories(NGHGI)Averageofmeansofeightmodelsandmeansofsevendataproducts;currentyearpredictionofSOCEANusingafeed-forwardneuralnetworkmethodCurrentyearpredictionofSLANDusingafeed-forwardneuralnetworkmethodFriedlingsteinetal.(2022a)GCB20212022ELUCprovidedatcoun-trylevel;decompositionintoﬂuxesfromdefor-estation,organicsoils,re/afforestationandwoodharvest,andothertransitions;changeinthemethodologytoderiveLUCmapsforBraziltocapturerecentupturnindeforestation;inclusionoftwonewdatasetsforpeatdrainage.UseofnineatmosphericinversionsAverageofmeansof10modelsandmeansofsevendataproductsBasedon16models,withachangeinthemethodologytoderiveLUCmapsforBraziltocapturerecentupturnindeforestationThisstudyhttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224820P.Friedlingsteinetal.:GlobalCarbonBudget2022MoredetailsontheEFOSmethodologyandits2022projec-tioncanbefoundinAppendixC1.2.2CO2emissionsfromlanduse,land-usechange,andforestry(ELUC)2.2.1Historicalperiod1850–2021ThenetCO2ﬂuxfromlanduse,land-usechange,andforestry(ELUC,calledland-usechangeemissionsintherestofthetext)includesCO2ﬂuxesfromdeforestation,afforesta-tion,loggingandforestdegradation(includingharvestactiv-ity),shiftingcultivation(cycleofcuttingforestforagricul-ture,thenabandoning),andregrowthofforests(followingwoodharvestoragricultureabandonment).Emissionsfrompeatburninganddrainageareaddedfromexternaldatasets,withpeatdrainagebeingaveragedfromthreespatiallyex-plicitindependentdatasets(seeAppendixC2.1).Threebookkeepingapproaches,updatedestimateseachofBLUE(Hansisetal.,2015),OSCAR(Gasseretal.,2020),andH&N2017(HoughtonandNassikas,2017),wereusedtoquantifygrosssourcesandsinksandtheresultingnetELUC.Uncertaintyestimateswerederivedfromthedynamicglobalvegetationmodels(DGVMs)ensembleforthetimeperiodpriorto1960,usingfortherecentdecadesanuncertaintyrangeof±0.7GtCyr−1,whichisasemi-quantitativemea-sureforannualanddecadalemissionsandreﬂectsourbestvaluejudgementthatthereisatleast68%chance(±1σ)thatthetrueland-usechangeemissionlieswithinthegivenrangefortherangeofprocessesconsideredhere.Thisuncertaintyrangehadbeenincreasedfrom0.5GtCyr−1afternewbook-keepingmodelswereincludedthatindicatedalargerspreadthanassumedbefore(LeQuéréetal.,2018a).Projectionsfor2021arebasedonﬁreactivityfromtropicaldeforestationanddegradationandemissionsfrompeatﬁresanddrainage.OurELUCestimatesfollowthedeﬁnitionofglobalcarboncyclemodelsofCO2ﬂuxesrelatedtoland-useandlandman-agementanddifferfromIPCCdeﬁnitionsadoptedinnationalgreenhousegas(GHG)inventories(NGHGI)forreportingundertheUNFCCC,whichadditionallygenerallyinclude,throughadoptionoftheIPCCso-calledmanagedlandproxyapproach,theterrestrialﬂuxesoccurringonlanddeﬁnedbycountriesasmanaged.Thispartlyincludesﬂuxesduetoen-vironmentalchange(e.g.atmosphericCO2increase),whicharepartofSLANDinourdeﬁnition.ThiscausestheglobalemissionestimatestobesmallerforNGHGIthanfortheglobalcarbonbudgetdeﬁnition(Grassietal.,2018).ThesameisthecasefortheFoodAgricultureOrganization(FAO)estimatesofcarbonﬂuxesonforestland,whichincludebothanthropogenicandnaturalsourcesonmanagedland(Tubielloetal.,2021).Wemapthetwodeﬁnitionstoeachother,toprovideacomparisonoftheanthropogeniccarbonbudgettotheofﬁcialcountryreportingtotheclimatecon-vention.2.2.2The2022projectionWeprojectthe2022land-useemissionsforBLUE,theup-datedH&N2017,andOSCAR,startingfromtheirestimatesfor2021assumingunalteredpeatdrainage,whichhaslowinterannualvariabilitybutadjustingthehighlyvariableemis-sionsfrompeatﬁres,tropicaldeforestation,anddegradationasestimatedusingactiveﬁredata(MCD14ML;Giglioetal.,2016).MoredetailsontheELUCmethodologycanbefoundinAppendixC2.2.3GrowthrateinatmosphericCO2concentration(GATM)2.3.1Historicalperiod1850–2021TherateofgrowthoftheatmosphericCO2concentrationisprovidedforyears1959–2021bytheUSNationalOceanicandAtmosphericAdministrationGlobalMonitoringLabo-ratory(NOAA/GML;DlugokenckyandTans,2022),whichisupdatedfromBallantyneetal.(2012)andincludesrecentrevisionstothecalibrationscaleofatmosphericCO2mea-surements(Halletal.,2021).Forthe1959–1979period,theglobalgrowthrateisbasedonmeasurementsofatmosphericCO2concentrationaveragedfromtheMaunaLoaandSouthPolestations,asobservedbytheCO2ProgramatScrippsInstitutionofOceanography(Keelingetal.,1976).Forthe1980–2020timeperiod,theglobalgrowthrateisbasedontheaverageofmultiplestationsselectedfromthemarineboundarylayersiteswithwell-mixedbackgroundair(Bal-lantyneetal.,2012),afterﬁttingasmoothcurvethroughthedataforeachstationasafunctionoftimeandaverag-ingbylatitudeband(MasarieandTans,1995).TheannualgrowthrateisestimatedbyDlugokenckyandTans(2022)fromatmosphericCO2concentrationbytakingtheaverageofthemostrecentDecember–Januarymonthscorrectedfortheaverageseasonalcycleandsubtractingthissameaver-ageoneyearearlier.Thegrowthrate(inunitsofppmyr−1)isconvertedtounitsofGtCyr−1bymultiplyingbyafactorof2.124GtCppm−1,assuminginstantaneousmixingofCO2throughouttheatmosphere(Ballantyneetal.,2012;Table1).Since2020,NOAA/GMLprovidesestimatesofatmo-sphericCO2concentrationswithrespecttoanewcalibra-tionscale,referredtoasWMO-CO2-X2019,inlinewiththerecommendationoftheWorldMeteorologicalOrganization(WMO)GlobalAtmosphereWatch(GAW)community(Halletal.,2021).The“X”inthescalenameindicatesthatitisamolefractionscale,howmanymicro-molesofCO2inasin-glemoleof(dry)air.Theword“concentration”onlylooselyreﬂectsthis.TheWMO-CO2-X2019scaleimprovesupontheearlierWMO-CO2-X2007scalebyincludingabroadersetofstandards,whichcontainCO2inawiderrangeofconcen-trationsthatspantherange250–800ppm(vs.250–520ppmforWMO-CO2-X2007).Inaddition,NOAA/GMLmadetwominorcorrectionstotheanalyticalprocedureusedtoquantifyCO2concentrations,ﬁxinganerrorinthesecondvirialcoef-EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224821ﬁcientofCO2andaccountingforlossofasmallamountofCO2tomaterialsinthemanometerduringthemeasurementprocess.ThedifferenceinconcentrationsmeasuredusingWMO-CO2-X2019vs.WMO-CO2-X2007is∼+0.18ppmat400ppmandtheobservationalrecordofatmosphericCO2concentrationshavebeenrevisedaccordingly.Therevisionshavebeenappliedretrospectivelyinallcaseswherethecal-ibrationswereperformedbyNOAA/GML,thusaffectingmeasurementsmadebymembersoftheWMO-GAWpro-grammeandotherregionallycoordinatedprogrammes(e.g.IntegratedCarbonObservingSystem,ICOS).ChangestotheCO2concentrationsmeasuredacrossthesenetworkspropa-gatetotheglobalmeanCO2concentrations.TherecalibrateddatawereﬁrstusedtoestimateGATMinthe2021editionoftheglobalcarbonbudget(Friedlingsteinetal.,2022a).Friedlingsteinetal.(2022a)veriﬁedthatthechangeofscalesfromWMO-CO2-X2007toWMO-CO2-X2019madeaneg-ligibledifferencetothevalueofGATM(−0.06GtCyr−1dur-ing2010–2019and−0.01GtCyr−1during1959–2019,wellwithintheuncertaintyrangereportedbelow).Theuncertaintyaroundtheatmosphericgrowthrateisduetofourmainfactors.First,thelong-termreproducibilityofreferencegasstandards(around0.03ppmfor1σfromthe1980s;DlugokenckyandTans,2022).Second,smallunex-plainedsystematicanalyticalerrorsthatmayhaveadurationofseveralmonthsto2yearscomeandgo.Theyhavebeensimulatedbyrandomizingboththedurationandthemag-nitude(determinedfromtheexistingevidence)inaMonteCarloprocedure.Third,thenetworkcompositionofthema-rineboundarylayerwithsomesitescomingorgoing,gapsinthetimeseriesateachsite,andsoon(DlugokenckyandTans,2022).ThelatteruncertaintywasestimatedbyNOAA/GMLwithaMonteCarlomethodbyconstructing100“alternative”networks(MasarieandTans,1995;NOAA/GML,2019).Thesecondandthirduncertainties,summedinquadrature,addupto0.085ppmonaverage(DlugokenckyandTans,2022).Fourth,theuncertaintyassociatedwithusingtheav-erageCO2concentrationfromasurfacenetworktoapproxi-matethetrueatmosphericaverageCO2concentration(mass-weighted,inthreedimensions)asneededtoassesstheto-talatmosphericCO2burden.Inreality,CO2variationsmea-suredatthestationswillnotexactlytrackchangesintotalatmosphericburden,withoffsetsinmagnitudeandphasingduetoverticalandhorizontalmixing.Thiseffectmustbeverysmallondecadalandlongertimescales,whentheatmo-spherecanbeconsideredwellmixed.TheCO2increaseinthestratospherelagstheincrease(meaninglowerconcentra-tions)thatweobserveinthemarineboundarylayer,whilethecontinentalboundarylayer(wheremostoftheemissionstakeplace)leadsthemarineboundarylayerwithhighercon-centrations.Theseeffectsnearlycanceleachother.Inad-dition,thegrowthrateisnearlythesameeverywhere(Bal-lantyneetal.,2012).Wethereforemaintainanuncertaintyaroundtheannualgrowthratebasedonthemultiplesta-tionsdatasetrangesbetween0.11and0.72GtCyr−1,withameanof0.61GtCyr−1for1959–1979and0.17GtCyr−1for1980–2020,whenalargersetofstationswereavail-ableasprovidedbyDlugokenckyandTans(2022).Wees-timatetheuncertaintyofthedecadalaveragedgrowthrateafter1980at0.02GtCyr−1basedonthecalibrationandtheannualgrowthrateuncertaintybutstretchedovera10-yearinterval.Foryearspriorto1980,weestimatethedecadalaverageduncertaintytobe0.07GtCyr−1basedonafactorproportionaltotheannualuncertaintypriorandafter1980(0.02×[0.61/0.17]GtCyr−1).WeassignahighconﬁdencetotheannualestimatesofGATMbecausetheyarebasedondirectmeasurementsfrommultipleandconsistentinstrumentsandstationsdistributedaroundtheworld(Ballantyneetal.,2012;Halletal.,2021).Toestimatethetotalcarbonaccumulatedintheatmo-spheresince1750or1850,weuseanatmosphericCO2con-centrationof278.3±3ppmor285.1±3ppm,respectively(Gulevetal.,2021).FortheconstructionofthecumulativebudgetshowninFig.3,weusetheﬁttedestimatesofCO2concentrationfromJoosandSpahni(2008)toestimatetheannualatmosphericgrowthrateusingtheconversionfac-torsshowninTable1.Theuncertaintyof±3ppm(convertedto±1σ)istakendirectlyfromtheIPCC’sAR5assessment(Ciaisetal.,2013).TypicaluncertaintiesinthegrowthrateinatmosphericCO2concentrationfromicecoredataareequivalentto±0.1–0.15GtCyr−1asevaluatedfromtheLawDomedata(Etheridgeetal.,1996)forindividual20-yearin-tervalsovertheperiodfrom1850to1960(BrunoandJoos,1997).2.3.2The2022projectionWeprovideanassessmentofGATMfor2022basedonthemonthlycalculatedglobalatmosphericCO2concentra-tion(GLO)throughAugust(DlugokenckyandTans,2022),andbias-adjustedHolt–Wintersexponentialsmoothingwithadditiveseasonality(Chatﬁeld,1978)toprojecttoJan-uary2023.Additionalanalysissuggeststhattheﬁrsthalfoftheyear(theborealwinter–spring–summertransition)showsmoreinterannualvariabilitythanthesecondhalfoftheyear(theborealsummer–autumn–wintertransition),sothattheexactprojectionmethodappliedtothesecondhalfoftheyearhasarelativelysmallerimpactontheprojectionofthefullyear.Uncertaintyisestimatedfrompastvariabilityusingthestandarddeviationofthelast5yearsofmonthlygrowthrates.2.4OceanCO2sink2.4.1Historicalperiod1850–2021ThereportedestimateoftheglobaloceananthropogenicCO2sinkSOCEANisderivedastheaverageoftwoestimates.Theﬁrstestimateisderivedasthemeanoveranensembleof10globaloceanbiogeochemistrymodels(GOBMs,Tables4andA2).Thesecondestimateisobtainedasthemeanoverhttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224822P.Friedlingsteinetal.:GlobalCarbonBudget2022Table4.Referencesfortheprocessmodels,bookkeepingmodels,oceandataproducts,andatmosphericinversions.Allmodelsandprod-uctsareupdatedwithnewdatatotheendofyear2021,andtheatmosphericforcingfortheDGVMshasbeenupdatedasdescribedinAppendixC2.2.ModelordatanameReferenceChangefromGlobalCarbonBudget2021(Friedlingsteinetal.,2022a)Bookkeepingmodelsforland-usechangeemissionsBLUEHansisetal.(2015)Nochangetomodel,butsimulationsareperformedwithupdatedLUH2forcing.Updateinaddedpeatdrainageemissions(basedonthreespa-tiallyexplicitdatasets).UpdatedH&N2017HoughtonandNassikas(2017)Minorbugﬁxinthefuelharvestestimatesthatwascausinganoveresti-mationoffuelsink.Updateinaddedpeatdrainageemissions(basedonthreespatiallyexplicitdatasets).OSCARGasseretal.(2020)Nochangetomodel,butland-useforcingischangedtoLUH2-GCB2022andFRA2020(asusedbyH&Nandextrapolatedto2021),withbothprescribedathigherspatialresolution(210insteadof96regions/countries).Constrainingbasedonlastyear’sbudgetdataforSLANDover1960–2021.Updateinaddedpeatdrainageemissions(basedonthreespatiallyexplicitdatasets).DynamicglobalvegetationmodelsCABLE-POPHaverdetal.(2018)Changesinparameterization.Diffusefractionofincomingradiationreadinasforcing.CLASSICMeltonetal.(2020)aMinorbugﬁxes.CLM5.0Lawrenceetal.(2019)Nochange.DLEMTianetal.(2015)bNochange.IBISYuanetal.(2014)cNochange.ISAMMeiyappanetal.(2015)dNochange.JSBACHReicketal.(2021)eNochange.JULES-ESWiltshireetal.(2021)fMinorbugﬁxes(usingJULESv6.3,suiteu-co002).LPJ-GUESSSmithetal.(2014)gNochange.LPJPoulteretal.(2011)hNochange.LPX-BernLienertandJoos(2018)FollowingtheresultsofJoosetal.(2020),weusemodiﬁedparametervaluesthatyieldamorereasonable(lower)biologicalnitrogenﬁxation(BNF),termedLPXv1.5.ThisparameterversionhasincreasedNim-mobilizationandastrongerNlimitationthanthepreviousversion.TheN2Oemissionswereadjustedaccordingly.Theparameterswereobtainedbyrunninganensemblesimulationandimposingvariousob-servationalconstraintsandsubsequentlyadjustingNimmobilization.Forthemethodology,seeJoosetal.(2020).OCNZaehleandFriend(2010)iNochange(usesr294).ORCHIDEEv3Vuichardetal.(2019)jNochange(ORCHIDEE–V3;revision7267).SDGVMWalkeretal.(2017)kNochange.VISITKatoetal.(2013)lNochange.YIBsYueandUnger(2015)Nochange.GlobaloceanbiogeochemistrymodelsNEMO-PlankTOM12Wrightetal.(2021)Minorbugﬁxes.MICOM-HAMOCC(NorESM-OCv1.2)Schwingeretal.(2016)Nochange.MPIOM-HAMOCC6Lacroixetal.(2021)Nochange.NEMO3.6-PISCESv2-gas(CNRM)Berthetetal.(2019)mNochange.FESOM-2.1-REcoM2Haucketal.(2020)nExtendedspin-up,minorbugﬁxes.MOM6-COBALT(Princeton)Liaoetal.(2020)Nochange.CESM-ETHZDoneyetal.(2009)Changedsalinityrestoringinthesurfaceoceanfrom700to300d,exceptfortheSouthernOceansouthof45◦S,wheretherestoringtimescalewassetto60d.NEMO-PISCES(IPSL)Aumontetal.(2015)Nochange.MRI-ESM2-1Nakanoetal.(2011),Urakawaetal.(2020)Newthisyear.CESM2Longetal.(2021)oNewthisyear.EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224823Table4.Continued.ModelordatanameReferenceChangefromGlobalCarbonBudget2021(Friedlingsteinetal.,2022a)OceandataproductsMPI-SOMFFNLandschützeretal.(2016)UpdatetoSOCATv2022measurementsandtimeperiod1982–2021.TheestimatenowcoversthefulloceandomainandtheArcticOceanextensiondescribedinLandschützeretal.(2020).Jena-MLSRödenbecketal.(2022)UpdatetoSOCATv2022measurements,timeperiodextendedto1957–2021.CMEMS-LSCE-FFNNv2Chauetal.(2022)UpdatetoSOCATv2022measurementsandtimeperiod1985–2021.TheCMEMS-LSCE-FFNNv2productnowcoversboththeopen-oceanandcoastalregions.LDEO-HPDGloegeetal.(2022)pNewthisyear.UOEx-WatsonWatsonetal.(2020)UpdatedtoSOCATv2022andOISSTv2.1.NIES-NNZengetal.(2014)UpdatedtoSOCATv2022.Smallchangesinmethod(gasexchangecoefﬁcienta=0.271;trendcalculation1990–2020,predictorsincludelongandlat).JMA-MLRIidaetal.(2021)UpdatedtoSOCATv2022,seasurfacetemperature(SST)ﬁelds(MGDSST)updated.OS-ETHZ-GRaCERGregorandGruber(2021)NochangeAtmosphericinversionsCAMSChevallieretal.(2005)qUpdatedtoWMOX2019scale.Extensiontoyear2021,revisionofthestationlist,updateofthepriorﬂuxesCarbonTrackerEurope(CTE)vanderLaan-Luijkxetal.(2017)UpdatedtoWMOX2019scale.BiospherepriorﬂuxesfromtheSiB4modelinsteadofSiBCASAmodel.Extensionto2021.JenaCarboScopeRödenbecketal.(2018)rUpdatedtoWMOX2019scale.Extensionto2021.UoEinsituFengetal.(2016)sUpdatedtoWMOX2019scale.Updatedstationlistandreﬁnedland–oceanmap.Extensionto2021.NISMON-CO2Niwaetal.(2022)tUpdatedtoWMOX2019scale.Positivedeﬁniteﬂuxparametersandup-datedstationlist.Extensionto2021.CMS-FluxLiuetal.(2021)UpdatedtoWMOX2019scale.Extensionto2021.GONGGAJinetal.(2022)uNewthisyear.THUKongetal.(2022)Newthisyear.CAMS-SatelliteChevallieretal.(2005)qNewthisyear.aSeealsoAsaadietal.(2018).bSeealsoTianetal.(2011).cThedynamiccarbonallocationschemewaspresentedbyXiaetal.(2015).dSeealsoJainetal.(2013).SoilbiogeochemistryisupdatedbasedonShuetal.(2020).eSeealsoMauritsenetal.(2019).fSeealsoSellaretal.(2019)andBurtonetal.(2019).JULES-ESistheEarthSystemconﬁgurationoftheJointUKLandEnvironmentSimulatorasusedintheUKEarthSystemModel(UKESM).gToaccountforthedifferencesbetweenthederivationofshort-waveradiationfromCRUcloudinessandDSWRFfromCRUJRA,thephotosynthesisscalingparameterαwasmodiﬁed(−15%)toyieldsimilarresults.hComparedtopublishedversion,decreasedLPJwoodharvestefﬁciencysothat50%ofbiomasswasremovedoff-sitecomparedto85%usedinthe2012budget.Residuemanagementofmanagedgrasslandsincreasedsothat100%ofharvestedgrassentersthelitterpool.iSeealsoZaehleetal.(2011).jSeealsoZaehleandFriend(2010)andKrinneretal.(2005)kSeealsoWoodwardandLomas(2004).lSeealsoItoandInatomi(2012).mSeealsoSéférianetal.(2019).nSeealsoSchourup-Kristensenetal.(2014).oSeealsoYeageretal.(2022).pSeealsoBenningtonetal.(2022).qSeealsoRemaud(2018).rSeealsoRödenbecketal.(2003).sSeealsoFengetal.(2009)andPalmeretal.(2019)tSeealsoNiwaetal.(2020)uSeealsoTianetal.(2014).anensembleofsevenobservation-baseddataproducts(Ta-bles4andA3).Aneighthproduct(Watsonetal.,2020)isshownbutisnotincludedintheensembleaverageasitdiffersfromtheotherproductsbyadjustingtheﬂuxtoacool,saltyoceansurfaceskin(seeAppendixC3.1foradiscussionoftheWatsonproduct).TheGOBMssimulateboththenaturalandanthropogenicCO2cyclesintheocean.Theyconstraintheanthropogenicair–seaCO2ﬂux(thedominantcomponentofSOCEAN)bythetransportofcarbonintotheoceaninterior,whichisalsothecontrollingfactorofpresent-dayoceancar-bonuptakeintherealworld.Theycoverthefullglobeandallseasonsandwererecentlyevaluatedagainstsurfaceoceancarbonobservations,suggestingtheyaresuitabletoestimatetheannualoceancarbonsink(Haucketal.,2020).ThedataproductsaretightlylinkedtoobservationsoffCO2(fugacityofCO2,whichequalspCO2correctedforthenon-idealbe-haviourofthegas;Pfeiletal.,2013),whichcarryimprintsoftemporalandspatialvariability,butarealsosensitivetoun-certaintiesingasexchangeparameterizationsanddataspar-sity.Theirassetistheassessmentofinterannualandspatialvariability(Haucketal.,2020).Weusetwofurtherdiagnos-ticoceanmodelstoestimateSOCEANovertheindustrialera(1781–1958).TheglobalfCO2-basedﬂuxestimateswereadjustedtoremovethepre-industrialoceansourceofCO2totheatmo-sphereof0.65GtCyr−1fromriverinputtotheocean(Reg-nieretal.,2022)tosatisfyourdeﬁnitionofSOCEAN(Haucketal.,2020).TheriverﬂuxadjustmentwasdistributedoverthelatitudinalbandsusingtheregionaldistributionofAumontetal.(2001;north:0.17GtCyr−1;tropics:0.16GtCyr−1;south:0.32GtCyr−1),acknowledgingthattheboundariesofAumontetal.(2001;namely20◦Sand20◦N)arenotcon-sistentwiththeboundariesotherwiseusedintheGCB(30◦Sand30◦N).Arecentstudybasedononeoceanbiogeochem-icalmodel(Lacroixetal.,2020)suggeststhatmoreoftheriverineoutgassingislocatedinthetropicsthanintheSouth-ernOcean,andhencethisregionaldistributionisassoci-atedwithamajoruncertainty.Anthropogenicperturbationshttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224824P.Friedlingsteinetal.:GlobalCarbonBudget2022ofrivercarbonandnutrienttransporttotheoceanarenotconsidered(seeSect.2.7andAppendixD3).WederiveSOCEANfromGOBMsbyusingasimulation(simA)withhistoricalforcingofclimateandatmosphericCO2,accountingformodelbiasesanddriftfromacon-trolsimulation(simB)withconstantatmosphericCO2andnormal-yearclimateforcing.Athirdsimulation(simC)withhistoricalatmosphericCO2increaseandnormal-yearclimateforcingisusedtoattributetheoceansinktoCO2(simCmi-nussimB)andclimate(simAminussimC)effects.Afourthsimulation(simD;historicalclimateforcingandconstantat-mosphericCO2)isusedtocomparethechangeinanthro-pogeniccarboninventoryintheinteriorocean(simAminussimD)totheobservationalestimateofGruberetal.(2019)withthesameﬂuxcomponents(steadystateandnon-steadystateanthropogeniccarbonﬂux).Dataproductsareadjustedtorepresentthefullice-freeoceanareabyasimplescalingapproachwhencoverageisbelow99%.GOBMsanddataproductsfallwithintheobservationalconstraintsoverthe1990s(2.2±0.7GtCyr−1,Ciaisetal.,2013)afterapplyingadjustments.SOCEANiscalculatedastheaverageoftheGOBMensem-blemeananddataproductensemblemeanfrom1990on-wards.Priorto1990,itiscalculatedastheGOBMensemblemeanplushalfoftheoffsetbetweenGOBMsanddataprod-uctensemblemeansover1990–2001.Weassignanuncertaintyof±0.4GtCyr−1totheoceansinkbasedonacombinationofrandom(ensemblestandarddeviation)andsystematicuncertainties(GOBMbiasinan-thropogeniccarbonaccumulation,previouslyreporteduncer-taintiesinfCO2-baseddataproducts;seeAppendixC3.3).WeassessamediumconﬁdenceleveltotheannualoceanCO2sinkanditsuncertaintybecauseitisbasedonmulti-plelinesofevidence,itisconsistentwithoceaninteriorcar-bonestimates(Gruberetal.,2019,seeSect.3.5.5)andtheinterannualvariabilityintheGOBMs,anddata-basedesti-matesarelargelyconsistentandcanbeexplainedbyclimatevariability.Werefrainfromassigningahighconﬁdencebe-causeofthesystematicdeviationbetweentheGOBManddataproducttrendssincearound2002.MoredetailsontheSOCEANmethodologycanbefoundinAppendixC3.2.4.2The2022projectionTheoceanCO2sinkforecastfortheyear2022isbasedontheannualhistoricalandestimated2022atmosphericCO2concentration(DlugokenckyandTans,2022),thehistoricalandestimated2022annualglobalfossilfuelemissionsfromthisyear’scarbonbudget,andthespring(March,April,May)OceanicNiñoIndex(ONI)(NCEP,2022).Usinganon-linearregressionapproach,i.e.afeed-forwardneuralnetwork,at-mosphericCO2,ONI,andfossilfuelemissionsareusedastrainingdatatobestmatchtheannualoceanCO2sink(i.e.combinedSOCEANestimatefromGOBMsanddataproducts)from1959through2021fromthisyear’scarbonbudget.Us-ingthisrelationship,the2022SOCEANcanthenbeestimatedfromtheprojected2021inputdatausingthenon-linearre-lationshipestablishedduringthenetworktraining.Toavoidoverﬁtting,theneuralnetworkwastrainedwithavariablenumberofhiddenneurons(varyingbetween2–5),and20%oftherandomlyselectedtrainingdatawerewithheldforin-dependentinternaltesting.Basedonthebestoutputperfor-mance(testedusingthe20%withheldinputdata),thebestperformingnumberofneuronswasselected.Inasecondstep,wetrainedthenetwork10timesusingthebestnumberofneuronsidentiﬁedinstep1anddifferentsetsofrandomlyselectedtrainingdata.Themeanofthe10trainingsequencesisconsideredourbestforecast,whereasthestandarddevia-tionofthe10ensemblesprovidesaﬁrst-orderestimateoftheforecastuncertainty.ThisuncertaintyisthencombinedwiththeSOCEANuncertainty(0.4GtCyr−1)toestimatetheoveralluncertaintyofthe2022projection.2.5LandCO2sink2.5.1HistoricalperiodTheterrestriallandsink(SLAND)isthoughttobeduetothecombinedeffectsoffertilizationbyrisingatmosphericCO2andNinputsonplantgrowth,aswellastheeffectsofcli-matechangesuchasthelengtheningofthegrowingseasoninnortherntemperateandborealareas.SLANDdoesnotin-cludelandsinksdirectlyresultingfromlanduseandland-usechange(e.g.regrowthofvegetation)asthesearepartoftheland-useﬂux(ELUC),althoughsystemboundariesmakeitdifﬁculttoexactlyattributeCO2ﬂuxesonlandbetweenSLANDandELUC(Erbetal.,2013).SLANDisestimatedfromthemulti-modelmeanof16DGVMs(TableA1).AsdescribedinAppendixC.4,DGVMsimulationsincludeallclimatevariabilityandCO2effectsoverland.InadditiontothecarboncyclerepresentedinallDGVMs,11modelsalsoaccountforthenitrogencycleandhencecanincludetheeffectofNinputsonSLAND.TheDGVMestimateofSLANDdoesnotincludetheexportofcar-bontoaquaticsystemsoritshistoricalperturbation,whichisdiscussedinAppendixD3.SeeAppendixC4forDGVMevaluationanduncertaintyassessmentforSLANDusingtheInternationalLandModelBenchmarkingsystem(ILAMB;Collieretal.,2018).MoredetailsontheSLANDmethodol-ogycanbefoundinAppendixC4.2.5.2The2022projectionLikefortheoceanforecast,thelandCO2sink(SLAND)fore-castisbasedontheannualhistoricalandestimated2022atmosphericCO2concentration(DlugokenckyandTans,2021),historicalandestimated2022annualglobalfossilfuelemissionsfromthisyear’scarbonbudget,andthesummer(June,July,August)ONI(NCEP,2022).AlltrainingdataareagainusedtobestmatchSLANDfrom1959through2021fromthisyear’scarbonbudgetusingafeed-forwardneuralEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224825network.Toavoidoverﬁtting,theneuralnetworkwastrainedwithavariablenumberofhiddenneurons(varyingbetween2–15),largerthanforSOCEANpredictionduetothestrongerlandcarboninterannualvariability.AsdoneforSOCEAN,apre-trainingselectstheoptimalnumberofhiddenneuronsbasedon20%withheldinputdata,andinasecondstep,anensembleof10forecastsisproducedtoprovidethemeanforecastplusuncertainty.ThisuncertaintyisthencombinedwiththeSLANDuncertaintyfor2021(0.9GtCyr−1)toesti-matetheoveralluncertaintyofthe2022projection.2.6TheatmosphericperspectiveTheworld-widenetworkofinsituatmosphericmeasure-mentsandsatellite-derivedatmosphericCO2column(xCO2)observationsputastrongconstraintonchangesintheatmo-sphericabundanceofCO2.Thisistrueglobally(henceourlargeconﬁdenceinGATM)butalsoregionallyinregionswithsufﬁcientobservationaldensityfoundmostlyintheextrat-ropics.Thisallowsatmosphericinversionmethodstocon-strainthemagnitudeandlocationofthecombinedtotalsur-faceCO2ﬂuxesfromallsources,includingfossilandland-usechangeemissionsandlandandoceanCO2ﬂuxes.TheinversionsassumeEFOStobewellknown,andtheysolveforthespatialandtemporaldistributionoflandandoceanﬂuxesfromtheresidualgradientsofCO2betweenstationsthatarenotexplainedbyfossilfuelemissions.Bydesign,suchsys-temsthusclosethecarbonbalance(BIM=0)andthuspro-videanadditionalperspectiveontheindependentestimatesoftheoceanandlandﬂuxes.Thisyear’sreleaseincludesnineinversionsystemsthataredescribedinTableA4.EachsystemisrootedinBayesianin-versionprinciplesbutusesdifferentmethodologies.ThesedifferencesconcerntheselectionofatmosphericCO2dataorxCO2,andthechoiceofaprioriﬂuxestoreﬁne.Theyalsodifferinspatialandtemporalresolution,assumedcorre-lationstructures,andmathematicalapproachofthemodels(seereferencesinTableA4fordetails).Importantly,thesys-temsuseavarietyoftransportmodels,whichwasdemon-stratedtobeadrivingfactorbehinddifferencesinatmo-sphericinversion-basedﬂuxestimatesandspeciﬁcallytheirdistributionacrosslatitudinalbands(Gaubertetal.,2019;Schuhetal.,2019).Fourinversionsystems(CAMS-FT21r2,CMS-ﬂux,GONGGA,THU)usedsatellitexCO2retrievalsfromGOSATand/orOCO-2,scaledtotheWMO2019cali-brationscale.Oneinversionthisyear(CMS-Flux)usedthesexCO2datasetsinadditiontotheinsituobservationalCO2molefractionrecords.Theoriginalproductsdeliveredbytheinversemodellersweremodiﬁedtofacilitatethecomparisontotheotherele-mentsofthebudget,speciﬁcallyontwoaccounts:(1)globaltotalfossilfuelemissions,includingcementcarbonationCO2uptake,and(2)riverineCO2transport.Detailsaregivenbelow.Wenotethatwiththeseadjustmentstheinverseresultsnolongerrepresentthenetatmosphere–surfaceexchangeoverlandandoceanareasassensedbyatmosphericobserva-tions.Instead,forland,theybecomethenetuptakeofCO2byvegetationandsoilsthatisnotexportedbyﬂuvialsystems,similartotheDGVMestimates.Foroceans,theybecomethenetuptakeofanthropogenicCO2,similartotheGOBMesti-mates.Theinversionsystemsprescribeglobalfossilfuelemis-sionsbasedontheGCP’sGriddedFossilEmissionsDatasetversions2022.1or2022.2(GCP-GridFED;Jonesetal.,2022),whichareupdatestoGCP-GridFEDv2021presentedbyJonesetal.(2021).GCP-GridFEDv2022scalesgriddedestimatesofCO2emissionsfromEDGARv4.3.2(Janssens-Maenhoutetal.,2019)withinnationalterritoriestomatchnationalemissionsestimatesprovidedbytheGCBfortheyears1959–2021,whichwerecompiledfollowingthemethodologydescribedinSect.2.1.Smalldifferencesbe-tweenthesystemsdueto,forinstance,regriddingtothetransportmodelresolutionoruseofdifferentGridFEDver-sionswithdifferentcementcarbonationsinks(whichwereonlypresentstartingwithGridFEDv2022.1)areadjustedinthelatitudinalpartitioningwepresenttoensureagreementwiththeestimateofEFOSinthisbudget.WealsonotethattheoceanﬂuxesusedaspriorbysixoutofthenineinversionsarepartofthesuiteoftheoceanprocessmodelsorfCO2dataproductslistedinSect.2.4.Althoughtheseﬂuxesarefurtheradjustedbytheatmosphericinversions,itmakestheinversionestimatesoftheoceanﬂuxesnotcompletelyinde-pendentofSOCEANassessedhere.TofacilitatecomparisonstotheindependentSOCEANandSLAND,weusedthesamecorrectionsfortransportandout-gassingofcarbontransportedfromlandtoocean,ashasbeendonefortheobservation-basedestimatesofSOCEAN(seeAp-pendixC3).TheatmosphericinversionsareevaluatedusingverticalproﬁlesofatmosphericCO2concentrations(Fig.B4).Morethan30aircraftprogrammesovertheglobe,eitherregularprogrammesorrepeatedsurveysoveratleast9months(ex-ceptforSouthernHemisphere,SH,programmes),havebeenusedtoassesssystemperformance(withspace–timeobser-vationalcoveragesparseintheSHandtropics,anddenserinNorthernHemisphere,NH,mid-latitudes;TableA6).TheninesystemsarecomparedtotheindependentaircraftCO2measurementsbetween2and7kmabovesealevelbetween2001and2021.ResultsareshowninFig.B4anddiscussedinAppendixC5.2Witharelativelysmallensemble(N=9)ofsystemsthatmoreoversharesomeaprioriﬂuxesusedwithoneanother,orwiththeprocess-basedmodels,itisdifﬁculttojustifyus-ingtheirmeanandstandarddeviationasametricforun-certaintyacrosstheensemble.Wethereforereporttheirfullrange(min–max)withouttheirmean.MoredetailsontheatmosphericinversionsmethodologycanbefoundinAp-pendixC5.https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224826P.Friedlingsteinetal.:GlobalCarbonBudget20222.7ProcessesnotincludedintheglobalcarbonbudgetThecontributionofanthropogenicCOandCH4totheglobalcarbonbudgetisnotfullyaccountedforinEq.(1)andisdescribedinAppendixD1.ThecontributionstoCO2emis-sionsofdecompositionofcarbonatesnotaccountedforisde-scribedinAppendixD2.ThecontributionofanthropogenicchangesinriverﬂuxesisconceptuallyincludedinEq.(1)inSOCEANandinSLAND,butitisnotrepresentedintheprocessmodelsusedtoquantifytheseﬂuxes.ThiseffectisdiscussedinAppendixD3.Similarly,thelossofadditionalsinkcapac-ityfromreducedforestcoverismissinginthecombinationofapproachesusedheretoestimatebothlandﬂuxes(ELUCandSLAND)anditspotentialeffectisdiscussedandquanti-ﬁedinAppendixD4.3ResultsForeachcomponentoftheglobalcarbonbudget,wepresentresultsforthreedifferenttimeperiods:thefullhistoricalpe-riod,from1850to2021,the6decadesinwhichwehaveatmosphericconcentrationrecordsfromMaunaLoa(1960–2021);aspeciﬁcfocusonthelastyear(2021);andthepro-jectionforthecurrentyear(2022).Subsequently,weassessthecombinedconstraintsfromthebudgetcomponents(oftenreferredtoasabottom-upbudget)againstthetop-downcon-straintsfrominversemodellingofatmosphericobservations.Wedothisfortheglobalbalanceofthelastdecade,aswellasforaregionalbreakdownoflandandoceansinksbybroadlatitudebands.3.1FossilCO2emissions3.1.1Historicalperiod1850–2021CumulativefossilCO2emissionsfor1850–2021were465±25GtC,includingthecementcarbonationsink(Fig.3,Table8,allcumulativenumbersareroundedtothenearest5GtC).Inthisperiod,46%offossilCO2emissionscamefromcoal,35%fromoil,15%fromnaturalgas,3%fromdecom-positionofcarbonates,and1%fromﬂaring.In1850,theUKcontributed62%ofglobalfossilCO2emissions.In1891thecombinedcumulativeemissionsofthecurrentmembersoftheEuropeanUnionreachedandsubse-quentlysurpassedtheleveloftheUK.Since1917,UScumu-lativeemissionshavebeenthelargest.Overtheentireperiod1850–2021,UScumulativeemissionsamountedto115GtC(24%ofworldtotal),theEU’sto80GtC(17%),andChina’sto70GtC(14%).InadditiontotheestimatesoffossilCO2emissionsthatweprovidehere(seeSect.2),therearethreeadditionalglobaldatasetswithlongtimeseriesthatincludeallsourcesoffossilCO2emissions:CDIAC-FF(GilﬁllanandMar-land,2021),CEDSversionv_2021_04_21(Hoeslyetal.,2018;O’Rourkeetal.,2021),andPRIMAP-histversion2.3.1(Gütschowetal.,2016,2021),althoughthesedatasetsarenotentirelyindependentofeachother(Andrew,2020a).CDIAC-FFhasthelowestcumulativeemissionsover1750–2018at437GtC,GCPhas443GtC,CEDS445GtC,PRIMAP-histTP453GtC,andPRIMAP-histCR455GtC.CDIAC-FFexcludesemissionsfromlimeproduction,whileneitherCDIAC-FFnorGCPexplicitlyincludeemissionsfrominternationalbunkerfuelspriorto1950.CEDShashigheremissionsfrominternationalshippinginrecentyears,whilePRIMAP-histhashigherfugitiveemissionsthantheotherdatasets.However,ingeneralthesefourdatasetsareinrelativeagreementastototalhistoricalglobalemissionsoffossilCO2.3.1.2Recentperiod1960–2021GlobalfossilCO2emissions,EFOS(includingthecementcarbonationsink),haveincreasedeverydecadefromanav-erageof3.0±0.2GtCyr−1forthedecadeofthe1960stoanaverageof9.6±0.5GtCyr−1during2012–2021(Ta-ble6,Figs.2and5).Thegrowthrateintheseemissionsdecreasedbetweenthe1960sandthe1990s,from4.3%peryearinthe1960s(1960–1969),3.2%peryearinthe1970s(1970–1979),1.6%peryearinthe1980s(1980–1989),and0.9%peryearinthe1990s(1990–1999).Af-terthisperiod,thegrowthratebeganincreasingagaininthe2000satanaveragegrowthrateof3.0%peryear,de-creasingto0.5%peryearforthelastdecade(2012–2021).China’semissionsincreasedby+1.5%peryearonaverageoverthelast10years,dominatingtheglobaltrend,andIn-dia’semissionsincreasedby+3.8%peryear,whileemis-sionsdecreasedinEU27by−1.8%peryearandintheUSAby−1.1%peryear.Figure6illustratesthespatialdistribu-tionoffossilfuelemissionsforthe2012–2021period.EFOSincludestheuptakeofCO2bycementviacarbon-ation,whichhasincreasedwithincreasingstocksofcementproductsfromanaverageof20MtCyr−1(0.02GtCyr−1)inthe1960stoanaverageof200MtCyr−1(0.2GtCyr−1)dur-ing2012–2021(Fig.5).3.1.3Finalyear2021GlobalfossilCO2emissionswere5.1%higherin2021thanin2020becauseoftheglobalreboundfromtheworstoftheCOVID-19pandemic,withanincreaseof0.5GtCtoreach9.9±0.5GtC(includingthecementcarbonationsink)in2021(Fig.5),distributedamongcoal(41%),oil(32%),naturalgas(22%),cement(5%),andothers(1%).Com-paredtothepreviousyear,2021emissionsfromcoal,oil,andgasincreasedby5.7%,5.8%,and4.8%,respectively,whileemissionsfromcementincreasedby2.1%.Allgrowthratespresentedareadjustedfortheleapyearunlessstatedotherwise.In2021,thelargestabsolutecontributionstoglobalfos-silCO2emissionswerefromChina(31%),theUSA(14%),EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224827Figure3.CombinedcomponentsoftheglobalcarbonbudgetillustratedinFig.2asafunctionoftimeforfossilCO2emissions(EFOS,includingasmallsinkfromcementcarbonation;grey)andemissionsfromland-usechange(ELUC;brown),aswellastheirpartitioningamongtheatmosphere(GATM;cyan),ocean(SOCEAN;blue),andland(SLAND;green).Panel(a)showsannualestimatesofeachﬂux,andpanel(b)showsthecumulativeﬂux(thesumofallpriorannualﬂuxes)sincetheyear1850.Thepartitioningisbasedonnearlyindependentestimatesfromobservations(forGATM)andfromprocessmodelensemblesconstrainedbydata(forSOCEANandSLAND)anddoesnotexactlyadduptothesumoftheemissions,resultinginabudgetimbalance(BIM),whichisrepresentedbythedifferencebetweenthebottomredline(mirroringtotalemissions)andthesumofcarbonﬂuxesintheocean,land,andatmospherereservoirs.AlldataareinGtCyr−1(a)andGtC(b).TheEFOSestimateisbasedonamosaicofdifferentdatasets,andhasanuncertaintyof±5%(±1σ).TheELUCestimateisfromthreebookkeepingmodels(Table4)withuncertaintyof±0.7GtCyr−1.TheGATMestimatespriorto1959arefromJoosandSpahni(2008)withuncertaintiesequivalenttoabout±0.1–0.15GtCyr−1andfromDlugokenckyandTans(2022)since1959withuncertaintiesofabout+-0.07GtCyr−1during1959–1979and±0.02GtCyr−1since1980.TheSOCEANestimateistheaveragefromKhatiwalaetal.(2013)andDeVries(2014)withuncertaintyofabout±30%priorto1959,andtheaverageofanensembleofmodelsandanensembleoffCO2dataproducts(Table4)withuncertaintiesofabout±0.4GtCyr−1since1959.TheSLANDestimateistheaverageofanensembleofmodels(Table4)withuncertaintiesofabout±1GtCyr−1.Seethetextformoredetailsofeachcomponentandtheiruncertainties.theEU27(8%),andIndia(7%).Thesefourregionsaccountfor59%ofglobalCO2emissions,whiletherestoftheworldcontributed41%,includinginternationalaviationandmarinebunkerfuels(2.8%ofthetotal).Growthratesforthesecoun-triesfrom2020to2021were3.5%(China),6.2%(USA),6.8%(EU27),and11.1%(India),with+4.5%fortherestoftheworld.ThepercapitafossilCO2emissionsin2021were1.3tCperpersonperyearfortheglobeandwere4.0(USA),2.2(China),1.7(EU27),and0.5(India)tCperper-sonperyearforthefourhighest-emittingcountries(Fig.5).Thepost-COVID-19reboundinemissionsof5.1%in2021isclosetotheprojectedincreaseof4.8%publishedinFriedlingsteinetal.(2022a)(Table7).Oftheregions,theprojectionforthe“restofworld”regionwasleastaccurate(offby−1.3%),largelybecauseofpoorlyprojectedemis-sionsfrominternationaltransport(bunkerfuels),whichweresubjecttoverylargechangesduringthisperiod.3.1.4Year2022projectionGlobally,weestimatethatglobalfossilCO2emissions(in-cludingcementcarbonation)willgrowby1.0%in2022(0.1%to1.9%)to10.0GtC(36.6GtCO2),exceedingtheir2019emissionlevelsof9.9GtC(36.3GtCO2).Globalin-creasein2022emissionsperfueltypesareprojectedtobe+1%(range0.2%to1.8%)forcoal,+2.2%(range1.1%to3.3%)foroil,−0.2%(range−1.1%to0.7%)fornaturalgas,and−1.6%(range−3.7%to−0.5%)forcement.ForChina,projectedfossilemissionsin2022areexpectedtodeclineby0.9%(range−2.3%to+0.4%)comparedwith2021emissions,bringing2022emissionsforChinatoaround3.1GtCyr−1(11.4GtCO2yr−1).Changesinfuel-speciﬁcprojectionsforChinaare+0.1%forcoal,−2.8%foroil,−1.1%fornaturalgas,and−7.0%forcement.FortheUSA,theEnergyInformationAdministration(EIA)emissionsprojectionfor2022combinedwithcementclinkerdatafromUSGSgivesanincreaseof1.5%(range−1%to+4%)comparedto2021,bringing2022USAemis-https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224828P.Friedlingsteinetal.:GlobalCarbonBudget2022Figure4.Componentsoftheglobalcarbonbudgetandtheiruncertaintiesasafunctionoftime,presentedindividuallyfor(a)fossilCO2andcementcarbonationemissions(EFOS),(b)growthrateinatmosphericCO2concentration(GATM),(c)emissionsfromland-usechange(ELUC),(d)thelandCO2sink(SLAND),(e)theoceanCO2sink(SOCEAN),and(f)thebudgetimbalancethatisnotaccountedforbytheotherterms.PositivevaluesofSLANDandSOCEANrepresentaﬂuxfromtheatmospheretolandortheocean.AlldataareinGtCyr−1withtheuncertaintyboundsrepresenting±1standarddeviationinshadedcolour.DatasourcesareasinFig.3.Thereddotsindicateourprojectionsfortheyear2022,andtherederrorbarstheuncertaintyintheprojections(seeSect.2).sionstoaround1.4GtCyr−1(5.1GtCO2yr−1).Thisisbasedonseparateprojectionsforcoalof−4.6%,oilof+2%,nat-uralgasof+4.7%,andcementof+1.2%.FortheEuropeanUnion,ourprojectionfor2022isforadeclineof0.8%(range−2.8%to+1.2%)over2021,with2022emissionsaround0.8GtCyr−1(2.8GtCO2yr−1).Thisisbasedonseparateprojectionsforcoalof+6.7%,oilof+0.9%,andnaturalgasof−10.0%,whilecementremainsunchanged.ForIndia,ourprojectionfor2022isanincreaseof6%(rangeof3.9%to8%)over2021,with2022emissionsaround0.8GtCyr−1(2.9GtCO2yr−1).Thisisbasedonsep-arateprojectionsforcoalof+5.0%,oilof+10.0%,naturalgasof−4.0%,andcementof+10.0%.Fortherestoftheworld,theexpectedgrowthratefor2022is1.7%(range0.1%to3.3%).Thefuel-speciﬁcprojected2022growthratesfortherestoftheworldare:+1.6%forEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224829Figure5.FossilCO2emissionsfor(a)theglobe,includinganuncertaintyof±5%(greyshading)andaprojectionthroughtheyear2022(reddotanduncertaintyrange);(b)territorial(solidlines)andconsumption(dashedlines)emissionsforthetopthreecountryemitters(USA,China,India)andfortheEuropeanUnion(EU27);(c)globalemissionsbyfueltype,includingcoal,oil,gas,cement,andcementminuscementcarbonation(dashed);and(d)percapitaemissionsfortheworldandforthelargeemitters,asinpanel(b).TerritorialemissionsareprimarilyfromadraftupdateofGilﬁllanandMarland(2021),withtheexceptionofthenationaldataforAnnexIcountriesfor1990–2020,whicharereportedtotheUNFCCCasdetailedinthetext,aswellassomeimprovementsinindividualcountries,andareextrapolatedforwardto2021usingBPEnergyStatistics.Consumption-basedemissionsareupdatedfromPetersetal.(2011b).SeeSect.2.1andAppendixC1fordetailsaboutthecalculationsanddatasources.coal,+3.1%foroil,−0.1%fornaturalgas,+3%force-ment.3.2Emissionsfromland-usechanges3.2.1Historicalperiod1850–2021CumulativeCO2emissionsfromland-usechanges(ELUC)for1850–2021were205±60GtC(Table8;Fig.3;Fig.14).ThecumulativeemissionsfromELUCshowalargespreadamongindividualestimatesof140GtC(updatedH&N2017),280GtC(BLUE),and190GtC(OSCAR)forthethreebook-keepingmodelsandasimilarwideestimateof185±60GtCfortheDGVMs(allcumulativenumbersareroundedtothenearest5GtC).Theseestimatesarebroadlyconsistentwithindirectconstraintsfromvegetationbiomassobserva-tions,givingacumulativesourceof155±50GtCoverthe1901–2012period(Lietal.,2017).However,giventhelargespread,abestestimateisdifﬁculttoascertain.3.2.2Recentperiod1960–2021Incontrasttogrowingfossilemissions,CO2emissionsfromlanduse,land-usechange,andforestryhaveremainedrela-tivelyconstantoverthe1960–1999periodbutshowaslightdecreaseofabout0.1GtCperdecadesincethe1990s,reach-ing1.2±0.7GtCyr−1forthe2012–2021period(Table6)butwithlargespreadacrossestimates(Table5,Fig.7).Dif-ferentfromthebookkeepingaverage,theDGVMmodelav-eragegrowsslightlylargeroverthe1970–2021periodandshowsnosignofdecreasingemissionsintherecentdecades(Table5,Fig.7).Thisis,however,expectedasDGVM-basedestimatesincludethelossofadditionalsinkcapacity,whichgrowswithtime,whilethebookkeepingestimatesdonot(AppendixD4).https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224830P.Friedlingsteinetal.:GlobalCarbonBudget2022Table5.ComparisonofresultsfromthebookkeepingmethodandbudgetresidualswithresultsfromtheDGVMsandinverseestimatesfordifferentperiods,thelastdecade,andthelastyearavailable.AllvaluesareinGtCyr−1.SeeFig.7foranexplanationofthebookkeepingcomponentﬂuxes.TheDGVMuncertaintiesrepresent±1σofthedecadalorannual(for2021)estimatesfromtheindividualDGVMs;fortheinversesystemstherangeofavailableresultsisgiven.Allvaluesareroundedtothenearest0.1GtCandthereforecolumnsdonotnecessarilyaddtozero.Mean(GtCyr−1)1960s1970s1980s1990s2000s2012–20212021Land-usechangeemis-sions(ELUC)Bookkeeping(BK)Netﬂux(1a)1.5±0.71.2±0.71.3±0.71.5±0.71.4±0.71.2±0.71.1±0.7BK–deforestation1.6±0.41.5±0.41.6±0.41.8±0.31.9±0.41.8±0.41.8±0.4BK–organicsoils0.1±0.10.1±0.10.2±0.10.2±0.10.2±0.10.2±0.10.2±0.1BK–re/afforestationandwoodharvest−0.6±0.1−0.6±0.1−0.6±0.2−0.7±0.1−0.8±0.2−0.9±0.3−1.0±0.3BK–othertransitions0.4±0.10.2±0.10.2±0.10.1±0.10.1±0.10.2±0.10.1±0.2DGVMnetﬂux(1b)1.4±0.51.3±0.51.5±0.51.5±0.61.6±0.61.6±0.51.6±0.5Terrestrialsink(SLAND)Residualsinkfromglobalbudget(EFOS+ELUC(1a)−GATM−SOCEAN)(2a)1.7±0.81.8±0.81.6±0.92.6±0.92.8±0.92.8±0.92.8±1DGVMs(2b)1.2±0.42.2±0.51.9±0.72.5±0.42.7±0.53.1±0.63.5±0.9Totallandﬂuxes(SLAND−ELUC)GCB2022budget(2b–1a)−0.2±0.81±0.90.5±11±0.81.4±0.91.9±0.92.4±1.1Budgetconstraint(2a–1a)0.2±0.40.6±0.50.3±0.51.1±0.51.5±0.61.5±0.61.7±0.7DGVMsnet(2b–1b)−0.1±0.40.9±0.50.4±0.50.9±0.41.2±0.31.5±0.51.9±0.7Inversions∗––0.3–0.6(2)0.7–1.1(3)1.2–1.6(3)1.1–1.7(7)1.5–2.1(9)∗Estimatesareadjustedforthepre-industrialinﬂuenceofriverﬂuxesandthecementcarbonationsinkandarealsoadjustedtocommonEFOS(Sect.2.6).Therangesgivenincludevaryingnumbers(inparentheses)ofinversionsineachdecade(TableA4).ELUCisanettermofvariousgrossﬂuxes,whichcom-priseemissionsandremovals.Grossemissionsonaverageoverthe1850–2021periodare2(BLUE,OSCAR)to3(up-datedH&N2017)timeslargerthanthenetELUCemissions.Grossemissionsshowamoderateincreasefromanaverageof3.2±0.9GtCyr−1forthedecadeofthe1960stoanav-erageof3.8±0.7GtCyr−1during2012–2021(Fig.7).In-creasesingrossremovals,from1.8±0.4GtCyr−1forthe1960sto2.6±0.4GtCyr−1for2012–2021,wereslightlylargerthantheincreaseingrossemissions.Sincethepro-cessesbehindgrossremovals,foremostforestregrowthandsoilrecovery,areallslow,whilegrossemissionsincludealargeinstantaneouscomponent,short-termchangesinland-usedynamics,suchasatemporarydecreaseindeforesta-tion,inﬂuencesgrossemissionsdynamicsmorethangrossremovaldynamics.ItistheserelativechangestoeachotherthatexplainthesmalldecreaseinnetELUCemissionsoverthelast2decadesandthelastfewyears.Grossﬂuxesoftendiffermoreacrossthethreebookkeepingestimatesthannetﬂuxes,whichisexpectedduetodifferentprocessrepresen-tation;inparticular,treatmentofshiftingcultivation,whichincreasesbothgrossemissionsandremovals,differsacrossmodels.ThereisasmallerdecreaseinnetCO2emissionsfromland-usechangeinthelastfewyears(Fig.7)thaninlastyear’sestimate(Friedlingsteinetal.,2021),whichplacesourupdatedestimatesbetweenlastyear’sestimateandtheesti-matefromtheGCB2020(Friedlingsteinetal.,2020).ThischangeisprincipallyattributabletochangesinELUCesti-matesfromBLUEandOSCAR,whichrelatetoimprove-mentsintheunderlyingland-useforcing(seeAppendixC2.2fordetails).Thesechangesaddressissuesidentiﬁedwithlastyear’sland-useforcing(seeFriedlingsteinetal.,2022a)andremoveorattenuateseveralemissionpeaksinBrazilandtheDemocraticRepublicoftheCongoandleadtohighernetemissionsinBrazilinthelastdecadescomparedtolastyear’sglobalcarbonbudget(theemissionsaveragedoverthethreebookkeepingmodelsforBrazilforthe2011–2020periodwere168MtCyr−1inGCB2021ascomparedto289MtCyr−1inGCB2022).Aremainingcaveatisthatgloballand-usechangedataformodelinputdoesnotcap-tureforestdegradation,whichoftenoccursonsmallscaleorwithoutforestcoverchangeseasilydetectablefromremotesensingandposesagrowingthreattoforestareaandcarbonstocksthatmaysurpassdeforestationeffects(e.g.Matricardietal.,2020;Qinetal.,2021).Whileindependentpan-tropicalorglobalestimatesofvegetationcoverdynamicsorcarbonstockchangesbasedonsatelliteremotesensinghavebecomeavailableinrecentyears,adirectcomparisontoourestimatesisnotpossible,mostimportantlybecausesatellite-basedes-timatesusuallydonotdistinguishbetweenanthropogenicEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224831Figure6.The2012–2021decadalmeancomponentsoftheglobalcarbonbudget,presentedfor(a)fossilCO2emissions(EFOS),(b)land-usechangeemissions(ELUC),(c)theoceanCO2sink(SOCEAN),and(d)thelandCO2sink(SLAND).PositivevaluesforEFOSandELUCrepresentaﬂuxtotheatmosphere,whereaspositivevaluesofSOCEANandSLANDrepresentaﬂuxfromtheatmospheretotheoceanortheland.Inallpanels,yellowandred(greenandblue)coloursrepresentaﬂuxfrom(into)thelandandoceanto(from)theatmosphere.AllunitsareinkgCm−2yr−1.Notethedifferentscalesineachpanel.EFOSdatashownisfromGCP-GridFEDv2022.2.ELUCdatashownareonlyfromBLUEastheupdatedH&N2017andOSCARdonotresolvegriddedﬂuxes.SOCEANdatashownaretheaverageofGOBMsanddataproductmeansusingGOBMsimulationAwithnoadjustmentforbiasordriftappliedtothegriddedﬁelds(seeSect.2.4).SLANDdatashownaretheaverageofDGVMsforsimulationS2(seeSect.2.5).driversandnaturalforestcoverlosses(e.g.fromdroughtornaturalwildﬁres)(Pongratzetal.,2021).WeadditionallyseparatethenetELUCintofourcompo-nentﬂuxestogainfurtherinsightintothedriversofemis-sions:deforestation,afforestation,reafforestation,andwoodharvest(i.e.allﬂuxesonforestlands);emissionsfromor-ganicsoils(i.e.peatdrainageandpeatﬁres);andﬂuxesassociatedwithallothertransitions(Fig.7;Sect.C2.1).Onaverageoverthe2012–2021periodandoverthethreebookkeepingestimates,ﬂuxesfromdeforestationamountto1.8±0.4GtCyr−1,andfromafforestation,reafforestation,andwoodharvestﬂuxesamountto−0.9±0.3GtCyr−1(Ta-ble5).Emissionsfromorganicsoils(0.2±0.1GtCyr−1)andthenetﬂuxfromothertransitions(0.2±0.1GtCyr−1)aresubstantiallylessimportantglobally.Deforestationisthusthemaindriverofglobalgrosssources.Therelativelysmalldeforestationﬂux(1.8±0.4GtCyr−1)incomparisontothegrossemissionestimateabove(3.8±0.7GtCyr−1)isex-plainedbythefactthatemissionsassociatedwithwoodhar-vestingdonotcountasdeforestationastheydonotchangethelandcover.Thissplitintocomponentﬂuxesclariﬁesthepotentialforemissionreductionandcarbondioxidere-moval:theemissionsfromdeforestationcouldbehalted(largely)withoutcompromisingcarbonuptakebyforestsandwouldcontributetoemissionsreduction.Bycontrast,reduc-ingwoodharvestingwouldhavelimitedpotentialtoreduceemissionsasitwouldbeassociatedwithlessforestregrowth;sinksandsourcescannotbedecoupledhere.Carbondioxideremovalinforestscouldinsteadbeincreasedbyafforestationandreafforestation.Overall,thehighestland-useemissionsoccurinthetrop-icalregionsofallthreecontinents.Thetopthreeemitters(bothcumulatively1959–2021andonaverageover2012–2021)areBrazil(inparticulartheAmazonArcofDeforesta-https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224832P.Friedlingsteinetal.:GlobalCarbonBudget2022Figure7.NetCO2exchangesbetweentheatmosphereandtheterrestrialbiosphererelatedtoland-usechange.(a)NetCO2emissionsfromland-usechange(ELUC)withestimatesfromthethreebookkeepingmodels(yellowlines)andthebudgetestimate(blackwith±1σuncertainty),whichistheaverageofthethreebookkeepingmodels.EstimatesfromindividualDGVMs(narrowgreenlines)andtheDGVMensemblemean(thickgreenline)arealsoshown.(b)NetCO2emissionsfromland-usechangefromthefourcountrieswithlargestcumula-tiveemissionssince1959.Valuesshownaretheaverageofthethreebookkeepingmodels,withshadedregionsas±1σuncertainty.(c)CO2grosssinks(negative,fromregrowthafteragriculturalabandonmentandwoodharvesting)andgrosssources(positive,fromdecayingma-terialleftdeadonsite,productsafterclearingofnaturalvegetationforagriculturalpurposes,woodharvesting,and,forBLUE,degradationfromprimarytosecondarylandthroughusageofnaturalvegetationasrangelandandfromemissionsfrompeatdrainageandpeatburning).Valuesareshownforthethreebookkeepingmodels(yellowlines)andfortheiraverage(blackwith±1σuncertainty).ThesumofthegrosssinksandsourcesisELUCshowninpanel(a).(d)SourcesandsinksaggregatedintofourcomponentsthatcontributetothenetﬂuxesofCO2,including(i)grosssourcesfromdeforestation;(ii)afforestation,reafforestation,andwoodharvest(i.e.thenetﬂuxonforestlandscomprisingslashandproductdecayfollowingwoodharvestandsinksduetoregrowthafterwoodharvestorafterabandonment,includingreforestationandabandonmentaspartsofshiftingcultivationcycles);(iii)emissionsfromorganicsoils(peatdrainageandpeatﬁre);and(iv)sourcesandsinksrelatedtootherland-usetransitions.Thescaleoftheﬂuxesshownissmallerthaninpanel(c)becausethesubstantialgrosssourcesandsinksfromwoodharvestingareaccountedforasnetﬂuxunder(ii).ThesumofthecomponentﬂuxesisELUCshowninpanel(a).tion),Indonesia,andtheDemocraticRepublicoftheCongo,withthesethreecountriescontributing0.7GtCyr−1or58%oftheglobaltotalland-useemissions(averageover2012–2021)(Fig.6b).Thisisrelatedtomassiveexpansionofcrop-land,particularlyinthelastfewdecadesinLatinAmerica,SoutheastAsia,andsub-SaharanAfrica(Hongetal.,2021),asubstantialpartofwhichhasbeenforexportofagriculturalproducts(Pendrilletal.,2019).Emissionintensityishighinmanytropicalcountries,particularlyinSoutheastAsia,duetohighratesoflandconversioninregionsofcarbon-denseandoftenstillpristineundegradednaturalforests(Hongetal.,2021).EmissionsarefurtherincreasedbypeatﬁresinequatorialAsia(GFED4s,vanderWerfetal.,2017).Uptakeduetoland-usechangeoccurspartlyduetoexpandingforestareaasaconsequenceoftheforesttransitioninthe19thand20thcenturiesandthesubsequentregrowthofforest,par-ticularlyinEurope(Fig.6b)(Mather,2001;McGrathetal.,2015).EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224833Whilethementionedpatternsaresupportedbyindepen-dentliteratureandrobust,weacknowledgethatmodelspreadissubstantiallylargeratregionalratherthangloballevels,ashasbeenshownforbookkeepingmodels(Bastosetal.,2021)andDGVMs(Obermeieretal.,2021).Assessmentsforindi-vidualregionswillbeperformedaspartofREgionalCarbonCycleAssessmentandProcesses(RECCAP2;Ciaisetal.,2022)oralreadyexistforselectedregions(e.g.forEuropebyPetrescuetal.,2020;forBrazilbyRosanetal.,2021;andforeightselectedcountriesandregionsincomparisontoinventorydatabySchwingshackletal.,2022).NationalGHGinventorydata(NGHGI)undertheLU-LUCFsectorordatasubmittedbycountriestoFAOSTATdif-ferfromtheglobalmodels’deﬁnitionofELUCthatweadopthereinthatthenaturalﬂuxes(SLAND)arecountedtowardsELUCwhentheyoccuronmanagedlandintheNGHGIre-porting(Grassietal.,2018).InordertocompareourresultstotheNGHGIapproach,weperformare-mappingofourELUCestimatesbyaddingSLANDinmanagedforestfromtheDGVMsimulations(followingGrassietal.,2021)tothebookkeepingELUCestimate(seeAppendixC2.3).Forthe2012–2021period,weestimatethat1.8GtCyr−1ofSLANDoccurredinmanagedforestsandisthenreallocatedtoELUChere,ashasbeendoneintheNGHGImethod.Bydoingso,ourmeanestimateofELUCisreducedfromasourceof1.2GtCtoasinkof0.6GtC,whichisverysimilartotheNGHGIestimateofa0.5GtCsink(Table9).There-mappingapproachhasbeenshowntoalsobegenerallyappli-cableforcountry-leveldata(Grassietal.,2022b;Schwing-shackletal.,2022).Country-levelanalysissuggests,e.g.thatthebookkeepingmeanestimateshigherdeforestationemissionsthanthenationalreportinIndonesiabutestimateslessCO2removalbyafforestationthanthenationalreportinChina.ThefractionofthenaturalCO2sinksthattheNGHGIestimatesincludedifferssubstantiallyacrosscoun-tries,relatedtovaryingproportionsofmanagedvs.allfor-estareas(Schwingshackletal.,2022).ComparingELUCandNGHGIonthebasisofthefourcomponentﬂuxes(Grassietal.,2022b),weﬁndthatNGHGIdeforestationemissionsarereportedtobesmallerthanthebookkeepingestimate(1.1GtCyr−1averagedover2012–2021).Areasonforthisliesinthefactthatcountryreportsdonot(fully)capturethecarbonﬂuxconsequencesofshiftingcultivation.Con-versely,carbonuptakeinforests(afforestation,reafforesta-tion,andforestry)issubstantiallylargerthanthebookkeep-ingestimate(1.75GtCyr−1averagedover2012–2021),ow-ingtotheinclusionofnaturalCO2ﬂuxesonmanagedlandintheNGHGI.Emissionsfromorganicsoilsandthenetﬂuxfromothertransitionsaresimilartotheestimatesbasedonthebookkeepingapproachandtheexternalpeatdrainageandburningdatasets.ThoughestimatesbetweenNGHGI,FAOSTAT,individualprocess-basedmodels,andthemappedbudgetstilldifferinvalueandneedfurtheranalysis,theap-proachtakenhereprovidesapossibilitytorelatetheglobalmodels’andNGHGIapproachtoeachotherroutinelyandthuslinktheanthropogeniccarbonbudgetestimatesoflandCO2ﬂuxesdirectlytotheGlobalStocktakeaspartofUN-FCCCParisAgreement.3.2.3Finalyear2021TheglobalCO2emissionsfromland-usechangeareesti-matedas1.1±0.7GtCin2021,similartothe2020estimate.However,conﬁdenceintheannualchangeremainslow.Land-usechangeandrelatedemissionsmayhavebeenaf-fectedbytheCOVID-19pandemic(e.g.Poulteretal.,2021).Duringtheperiodofthepandemic,environmentalprotectionpoliciesandtheirimplementationmayhavebeenweakenedinBrazil(Valeetal.,2021).Inothercountriesmonitoringcapacitiesandlegalenforcementofmeasurestoreducetrop-icaldeforestationhavealsobeenreducedduetobudgetre-strictionsofenvironmentalagenciesortheimpairmentsofground-basedmonitoringintendedtopreventlandgrabsandtenureconﬂicts(Brancalionetal.,2020;Amador-Jiménezetal.,2020).Effectsofthepandemicontrendsinﬁreactivityorforestcoverchangesarehardtoseparatefromthoseofgeneralpoliticaldevelopmentsandenvironmentalchanges,andthelong-termconsequencesofdisruptionsinagriculturalandforestryeconomicactivities(e.g.GruèreandBrooks,2021;Golaretal.,2020;BeckmanandCountryman,2021)remaintobeseen.Overall,thereislimitedevidencesofarthatCOVID-19wasakeydriverofchangesinLULUCFemissionsataglobalscale.Impactsvaryacrosscountriesanddeforestation-curbingandenhancingfactorsmaypartlycompensateeachother(Wunderetal.,2021).3.2.4Year2022projectionInIndonesia,peatﬁreemissionsareverylow,potentiallyre-latedtoarelativelywetdryseason(GFED4.1s,vanderWerfetal.,2017).InSouthAmerica,thetrajectoryoftropicaldeforestationanddegradationﬁresresemblesthelong-termaverage;globalemissionsfromtropicaldeforestationanddegradationﬁreswereestimatedtobe206TgCby14Octo-ber2020.(GFED4.1s,vanderWerfetal.,2017).Ourprelim-inaryestimateofELUCfor2022issubstantiallylowerthanthe2012–2021average,whichsawyearsofanomalouslydryconditionsinIndonesiaandhighdeforestationﬁresinSouthAmerica(Friedlingsteinetal.,2022a).Basedontheﬁreemissionsuntil14October,weexpectELUCemissionsofaround1.1GtCin2022.Notethatalthoughourextrapola-tionisbasedontropicaldeforestationanddegradationﬁres,degradationattributabletoselectivelogging,edgeeffects,orfragmentationwillnotbecaptured.Further,deforestationandﬁresindeforestationzonesmaybecomemorediscon-nected,partlyduechangesinlegislationinsomeregions.Forexample,VanWeesetal.(2021)foundthatthecontributionfromﬁrestoforestlossdecreasedintheAmazonandinIn-donesiaovertheperiodof2003–2018.Morerecentyears,however,sawanuptickintheAmazonagain(Tyukavinaethttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224834P.Friedlingsteinetal.:GlobalCarbonBudget2022al.,2022withupdate),andmoreworkisneededtounder-standﬁre–deforestationrelations.TheﬁresinMediterraneanEuropeinsummer2022andintheUSinspring2022,thoughaboveaverageforthosere-gions,onlycontributeasmallamounttoglobalemissions.However,theywereunrelatedtoland-usechangeandarethusnotattributedtoELUCbutwouldbepartofthenaturallandsink.Land-usedynamicsmaybeinﬂuencedbythedisruptiontotheglobalfoodmarketassociatedwiththewarinUkraine,butscientiﬁcevidencesofarisverylimited.Highfoodprices,whichpreceded(butwereexacerbatedby)thewar(ToreroandFAO,2022),aregenerallylinkedtohigherdefor-estation(AngelsenandKaimowitz,1999),whilehighpricesonagriculturalinputssuchasfertilizersandfuel,whicharealsounderpressurefromembargoes,mayimpairyields.3.3TotalanthropogenicemissionsCumulativeanthropogenicCO2emissionsfor1850–2021totalled670±65GtC(2455±240GtCO2),ofwhich70%(470GtC)occurredsince1960and33%(220GtC)since2000(Tables6and8).Totalanthropogenicemis-sionsmorethandoubledoverthelast60years,from4.5±0.7GtCyr−1forthedecadeofthe1960stoanaver-ageof10.8±0.8GtCyr−1during2012–2021,andreach-ing10.9±0.9GtC(40.0±3.3GtCO2)in2021.For2022,weprojectglobaltotalanthropogenicCO2emissionsfromfossilandland-usechangestobealsoaround11.1GtC(40.5GtCO2).Allvalueshereincludethecementcarbona-tionsink(currentlyabout0.2GtCyr−1).Duringthehistoricalperiod1850–2021,30%ofhistor-icalemissionswerefromland-usechangeand70%fromfossilemissions.However,fossilemissionshavegrownsig-niﬁcantlysince1960whileland-usechangeshavenot,andconsequentlythecontributionsofland-usechangetototalanthropogenicemissionsweresmallerduringrecentperiods(18%duringtheperiod1960–2021and11%during2012–2021).3.4AtmosphericCO23.4.1Historicalperiod1850–2021AtmosphericCO2concentrationwasapproximately278ppmin1750,300ppminthe1910s,350ppminthelate1980s,and414.71±0.1ppmin2021(DlugokenckyandTans,2022);Fig.1).Themassofcarbonintheatmosphereincreasedby48%from590GtCin1750to879GtCin2021.CurrentCO2concentrationsintheatmosphereareunprecedentedinthelast2millionyears,andthecurrentrateofatmosphericCO2increaseisatleast10timesfasterthanatanyothertimedur-ingthelast800000years(Canadelletal.,2021).3.4.2Recentperiod1960–2021ThegrowthrateinatmosphericCO2levelincreasedfrom1.7±0.07GtCyr−1inthe1960sto5.2±0.02GtCyr−1dur-ing2012–2022withimportantdecadalvariations(Table6,Figs.3and4).Duringthelastdecade(2012–2021),thegrowthrateinatmosphericCO2concentrationcontinuedtoincrease,albeitwithlargeinterannualvariability(Fig.4).Theairbornefraction(AF),deﬁnedastheratioofatmo-sphericCO2growthratetototalanthropogenicemissions,i.e.AF=GATM/(EFOS+ELUC),(2)providesadiagnosticoftherelativestrengthofthelandandoceancarbonsinksinremovingpartoftheanthropogenicCO2perturbation.TheevolutionofAFoverthelast60yearsshowsnosigniﬁcanttrend,remainingataround44%,albeitshowingalargeinterannualanddecadalvariabilitydrivenbytheyear-to-yearvariabilityinGATM(Fig.9).Theobservedstabilityoftheairbornefractionoverthe1960–2020periodindicatesthattheoceanandlandCO2sinkshaveonaveragebeenremovingabout55%oftheanthropogenicemissions(seeSect.3.5and3.6).3.4.3Finalyear2021ThegrowthrateinatmosphericCO2concentrationwas5.2±0.2GtC(2.46±0.08ppm)in2021(Fig.4;Dlugo-kenckyandTans,2022),slightlyabovethe2020growthrate(5.0GtC)butsimilartothe2011–2020average(5.2GtC).3.4.4Year2022projectionThe2022growthinatmosphericCO2concentration(GATM)isprojectedtobeabout5.3GtC(2.5ppm)basedonglobalobservationsuntilOctober2022,bringingtheatmosphericCO2concentrationtoanexpectedlevelof417.2ppmaver-agedovertheyear,51%overthepreindustriallevel.3.5Oceansink3.5.1Historicalperiod1850–2021Cumulatedsince1850,theoceansinkaddsupto175±35GtC,withmorethantwo-thirdsofthisamount(120GtC)beingtakenupbytheglobaloceansince1960.Overthehistoricalperiod,theoceansinkincreasedinpacewiththeexponentialanthropogenicemissionsincrease(Fig.3b).Since1850,theoceanhasremoved26%oftotalanthropogenicemissions.3.5.2Recentperiod1960–2021TheoceanCO2sinkincreasedfrom1.1±0.4GtCyr−1inthe1960sto2.9±0.4GtCyr−1during2012–2021(Table6),withinterannualvariationsoftheorderofafewtenthsofaEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224835Table6.DecadalmeanintheﬁvecomponentsoftheanthropogenicCO2budgetfordifferentperiodsandthelastyearavailable.AllvaluesareinGtCyr−1,anduncertaintiesarereportedas±1σ.FossilCO2emissionsincludecementcarbonation.Thebudgetimbalance(BIM)isalsoshown,whichprovidesameasureofthediscrepanciesamongthenearlyindependentestimates.Apositiveimbalancemeanstheemissionsareoverestimatedand/orthesinksaretoosmall.Allvaluesareroundedtothenearest0.1GtC,andthereforecolumnsdonotnecessarilyaddtozero.Mean(GtCyr−1)1960s1970s1980s1990s2000s2012–202120212022(Projection)Totalemissions(EFOS+ELUC)FossilCO2emissions(EFOS)∗3±0.24.7±0.25.5±0.36.3±0.37.7±0.49.6±0.59.9±0.510±0.5Land-usechangeemis-sions(ELUC)1.5±0.71.2±0.71.3±0.71.5±0.71.4±0.71.2±0.71.1±0.71.1±0.7Totalemissions4.5±0.75.9±0.76.8±0.87.8±0.89.1±0.810.8±0.810.9±0.911.1±0.9PartitioningGrowthrateinatmosCO2(GATM)1.7±0.072.8±0.073.4±0.023.1±0.024±0.025.2±0.025.2±0.25.3±0.4Oceansink(SOCEAN)1.1±0.41.4±0.41.8±0.42.1±0.42.3±0.42.9±0.42.9±0.42.9±0.4Terrestrialsink(SLAND)1.2±0.42.2±0.51.9±0.72.5±0.42.7±0.53.1±0.63.5±0.93.4±0.9BudgetimbalanceBIM=EFOS+ELUC−(GATM+SOCEAN+SLAND)0.4−0.4−0.30.10.1−0.3−0.6−0.5∗Fossilemissionsexcludingthecementcarbonationsinkamountto3.1±0.2,4.7±0.2,5.5±0.3,6.4±0.3,7.9±0.4,and9.8±0.5GtCyr−1forthedecadesofthe1960sto2010s,respectively,10.1±0.5GtCyr−1for2021,and10.2±0.5GtCyr−1for2022.Figure8.(a)ThelandCO2sink(SLAND)estimatedbyindividualDGVMestimates(green),aswellasthebudgetestimate(blackwith±1σuncertainty),whichistheaverageofallDGVMs.(b)Totalatmosphere–landCO2ﬂuxes(SLAND−ELUC).Thebudgetestimateofthetotallandﬂux(blackwith±1σuncertainty)combinestheDGVMestimateofSLANDfrompanel(a)withthebookkeepingestimateofELUCfromFig.7a.UncertaintiesaresimilarlypropagatedinquadraturefromthebudgetestimatesofSLANDfrompanel(a)andELUCfromFig.7a.DGVMsalsoprovideestimatesofELUC(seeFig.7a),whichcanbecombinedwiththeirownestimatesofthelandsink.Hence,panel(b)alsoincludesanestimateforthetotallandﬂuxforindividualDGVMs(thingreenlines)andtheirmulti-modelmean(thickgreenline).gigatonneofcarbonperyear(Fig.10).Theocean-bornefrac-tion(SOCEAN/(EFOS+ELUC)hasbeenremarkablyconstantataround25%onaverage(Fig.9).Variationsaroundthismeanillustratedecadalvariabilityoftheoceancarbonsink.Sofarthereisnoindicationofadecreaseintheocean-bornefractionfrom1960to2021.TheincreaseintheoceansinkisprimarilydrivenbytheincreasedatmosphericCO2concen-tration,withthestrongestCO2-inducedsignalintheNorthAtlanticOceanandtheSouthernOcean(Fig.11a).Theeffectofclimatechangeismuchweaker,reducingtheoceansinkgloballyby0.11±0.09GtCyr−1(−4.2%)during2012–2021(ninemodelssimulateaweakeningoftheoceansinkbyclimatechangewitharangeof−3.2to−8.9%,andonlyonemodelsimulatesastrengtheningby4.8%),anditdoeshttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224836P.Friedlingsteinetal.:GlobalCarbonBudget2022Table7.ComparisonoftheprojectionwithrealizedfossilCO2emissions(EFOS).The“actual”valuesaretheﬁrstestimateavailableusingactualdata,andthe“projected”valuesrefertoestimatesmadebeforetheendoftheyearforeachpublication.Projectionsbasedonadifferentmethodfromthatdescribedhereduring2008–2014areavailableinLeQuéréetal.(2016).Allvaluesareadjustedforleapyears.WorldChinaUSAEU28/EU27iIndiaRestofworldProjectedActualProjectedActualProjectedActualProjectedActualProjectedActualProjectedActual2015a−0.6%0.06%−3.9%−0.7%−1.5%−2.5%––––1.2%1.2%(−1.6to0.5)(−4.6to−1.1)(−5.5to0.3)(−0.2to2.6)2016b−0.2%0.20%−0.5%−0.3%−1.7%−2.1%––––1.0%1.3%(−1.0to+1.8)(−3.8to+1.3)(−4.0to+0.6)(−0.4to+2.5)2017c2.0%1.6%3.5%1.5%−0.4%−0.5%––2.00%3.9%1.6%1.9%(+0.8to+3.0)(+0.7to+5.4)(−2.7to+1.0)(+0.2to+3.8)(0.0to+3.2)2018d2.7%2.1%4.7%2.3%2.5%2.8%−0.7%−2.1%6.3%8.0%1.8%1.7%(+1.8to+3.7)(+2.0to+7.4)(+0.5to+4.5)(−2.6to+1.3)(+4.3to+8.3)(+0.5to+3.0)2019e0.5%0.1%2.6%2.2%−2.4%−2.6%−1.7%−4.3%1.8%1.0%0.5%0.5%(−0.3to+1.4)(+0.7to+4.4)(−4.7to−0.1)(−5.1%to+1.8%)(−0.7to+3.7)(−0.8to+1.8)2020f−6.7%−5.4%−1.7%1.4%−12.2%−10.6%−11.3%(EU27)−10.9%−9.1%−7.3%−7.4%−7.0%2021g4.8%5.1%4.3%3.5%6.8%6.2%6.3%6.8%11.2%11.1%3.2%4.5%(4.2%to5.4%)(3.0%to5.4%)(6.6%to7.0%)(4.3%to8.3%)(10.7%to11.7%)(2.0%to4.3%)2022h1.0%−0.9%1.5%−0.8%6%1.7%(0.1%to1.9%)(−2.3%to0.4%)(−1%to4%)(−2.8%to1.2%)(3.9%to8%)(0.1%to3.3%)aJacksonetal.(2016)andLeQuéréetal.(2015a).bLeQuéréetal.(2016).cLeQuéréetal.(2018a).dLeQuéréetal.(2018b).eFriedlingsteinetal.(2019),fFriedlingsteinetal.(2020),gFriedlingsteinetal.(2022a),hThisstudy.iEU28upto2019andEU27from2020.EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224837Table8.CumulativeCO2fordifferenttimeperiodsingigatonnesofcarbon(GtC).FossilCO2emissionsincludecementcarbonation.Thebudgetimbalance(BIM)providesameasureofthediscrepanciesamongthenearlyindependentestimates.Allvaluesareroundedtothenearest5GtC,andthereforecolumnsdonotnecessarilyaddtozero.Uncertaintiesarereportedasfollows:EFOSis5%ofcumulativeemissions,ELUCpriorto1959is1σspreadfromtheDGVMs,ELUCpost-1959is0.7timesthenumberofyears(where0.7GtCyr−1istheuncertaintyontheannualELUCﬂuxestimate),GATMuncertaintyisheldconstantat5GtCforalltimeperiods,SOCEANuncertaintyis20%ofthecumulativesink(20%relatestotheannualuncertaintyof0.4GtCyr−1,whichis∼20%ofthecurrentoceansink),andSLANDisthe1σspreadfromtheDGVMestimates.1750–20211850–20141850–20211960–20211850–2022EmissionsFossilCO2emissions(EFOS)470±25400±20465±25390±20475±25Land-usechangeemissions(ELUC)235±70195±60205±6085±45205±60Totalemissions700±75595±60670±65470±50680±65PartitioningGrowthrateinatmosCO2(GATM)295±5235±5275±5210±5280±5Oceansink(SOCEAN)185±35155±30175±35120±25180±35Terrestrialsink(SLAND)230±50185±40210±45145±30210±45BudgetimbalanceBIM=EFOS+ELUC−(GATM+SOCEAN+SLAND)−51515−515notshowclearspatialpatternsacrosstheGOBMensemble(Fig.11b).Thisisthecombinedeffectofchangeandvari-abilityinallatmosphericforcingﬁelds,previouslyattributedtowindandtemperaturechangesinonemodel(LeQuéréetal.,2010).Theglobalnetair–seaCO2ﬂuxisaresidualoflargenat-uralandanthropogenicCO2ﬂuxesintoandoutoftheoceanwithdistinctregionalandseasonalvariations(Figs.6andB1).Naturalﬂuxesdominateonregionalscalesbutlargelycanceloutwhenintegratedglobally(Gruberetal.,2009).Mid-latitudesinallbasinsandthehigh-latitudeNorthAt-lanticdominatetheoceanCO2uptakewherelowtempera-turesandhighwindspeedsfacilitateCO2uptakeatthesur-face(Takahashietal.,2009).Intheseregions,formationofmode,intermediate,anddeep-watermassestransportanthro-pogeniccarbonintotheoceaninterior,thusallowingforcon-tinuedCO2uptakeatthesurface.OutgassingofnaturalCO2occursmostlyinthetropics,especiallyintheequatorialup-wellingregion,andtoalesserextentintheNorthPaciﬁcandpolarSouthernOcean,mirroringawell-establishedunder-standingofregionalpatternsofair–seaCO2exchange(e.g.Takahashietal.,2009;Gruberetal.,2009).ThesepatternsarealsonoticeableintheSurfaceOceanCO2Atlas(SOCAT)dataset,whereanoceanfCO2valueabovetheatmosphericlevelindicatesoutgassing(Fig.B1).Thismapfurtherillus-tratesthedatasparsityintheIndianOceanandtheSouthernHemisphereingeneral.Interannualvariabilityoftheoceancarbonsinkisdrivenbyclimatevariabilitywithaﬁrst-ordereffectfromastrongeroceansinkduringlargeElNiñoevents(e.g.1997–1998)(Fig.10;Rödenbecketal.,2014;Haucketal.,2020).TheGOBMsshowthesamepatternsofdecadalvariabilityasthemeanofthefCO2-baseddataproducts,withastag-nationoftheoceansinkinthe1990sandastrengtheningsincetheearly2000s(Fig.10,LeQuéréetal.,2007;Land-schützeretal.,2015,2016;DeVriesetal.,2017;Haucketal.,2020;McKinleyetal.,2020).Differentexplanationshavebeenproposedforthisdecadalvariability,rangingfromtheocean’sresponsetochangesinatmosphericwindandpres-suresystems(e.g.LeQuéréetal.,2007;KepplerandLand-schützer,2019),includingvariationsinupper-oceanover-turningcirculation(DeVriesetal.,2017),totheeruptionofMountPinatuboanditseffectsonseasurfacetempera-tureandslowedatmosphericCO2growthrateinthe1990s(McKinleyetal.,2020).Themainoriginofthedecadalvari-abilityisamatterofdebate,withanumberofstudiesini-tiallypointingtotheSouthernOcean(seereviewinCanadelletal.,2021),butcontributionsfromtheNorthAtlanticandNorthPaciﬁcoceans(Landschützeretal.,2016;DeVriesetal.,2019)oraglobalsignal(McKinleyetal.,2020)werealsoproposed.AlthoughallindividualGOBMsanddataproductsfallwithintheobservationalconstraint,theensemblemeansofGOBMsanddataproductsadjustedfortheriverineﬂuxdivergeovertimewithameanoffsetincreasingfrom0.28GtCyr−1inthe1990sto0.61GtCyr−1inthedecade2012–2021andreaching0.79GtCyr−1in2021.TheSOCEANpositivetrendovertimehasdivergedbyafac-torof2since2002(GOBMs:0.28±0.07GtCyr−1perdecade;dataproducts:0.61±0.17GtCyr−1perdecade;SOCEAN:0.45GtCyr−1perdecade)andbyafactorof3since2010(GOBMs:0.21±0.14GtCyr−1perdecade;dataproducts:0.66±0.38GtCyr−1perdecade;SOCEAN:0.44GtCyr−1perdecade).TheGOBMestimateisslightlyhigher(<0.1GtCyr−1)thaninthepreviousglobalcarbonbudget(Friedlingsteinetal.,2022a)becausetwonewmod-elsareincluded(CESM2,MRI)andfourmodelsrevisedtheirestimatesupwards(CESM-ETHZ,CNRM,FESOM2-REcoM,PlankTOM).Thedataproductestimateishigherbyabout0.1GtCyr−1comparedtoFriedlingsteinetal.(2022a)https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224838P.Friedlingsteinetal.:GlobalCarbonBudget2022Table9.MappingofglobalcarboncyclemodellandﬂuxdeﬁnitionstothedeﬁnitionoftheLULUCFnetﬂuxusedinnationalGreenhouseGasInventoriesreportedtoUNFCCC.SeeSect.C2.3andTableA8fordetailsonthemethodologyandacomparisontootherdatasets.2002–20112012–2021ELUCfrombookkeepingestimates(fromTable5)1.41.2SLANDonnon-intactforestfromDGVMs−1.7−1.8ELUCplusSLANDonnon-intactforests−0.3−0.6NationalGreenhouseGasInventories−0.4−0.5asaresultofanupwardcorrectioninthreeproducts(Jena-MLS,MPI-SOMFFN,OS-ETHZ-Gracer),thesubmissionofLDEO-HPD(whichisaboveaverage),thenon-availabilityoftheCSIRproduct,andthesmallupwardcorrectionoftheriverﬂuxadjustment.ThediscrepancybetweenthetwotypesofestimatesstemsmostlyfromalargerSouthernOceansinkinthedataprod-uctspriorto2001andfromalargerSOCEANtrendinthenorthernandsouthernextratropicssincethen(Fig.13).Notethatthelocationofthemeanoffset(butnotitstrend)dependsstronglyonthechoiceofregionalriverﬂuxadjustmentandwouldoccurinthetropicsratherthanintheSouthernOceanwhenusingthedatasetofLacroixetal.(2020)insteadofAumontetal.(2001).OtherpossibleexplanationsforthediscrepancyintheSouthernOceancouldbemissingwinterobservationsanddatasparsityingeneral(Bushinskyetal.,2019,Gloegeetal.,2021)ormodelbiases(asindicatedbythelargemodelspreadintheSouthernHemisphere,asshowninFig.13,andthelargermodel–datamismatch,asshowninFig.B2).InGCBreleasesuntil2021,theoceansink1959–1989wasonlyestimatedbyGOBMsduetotheabsenceoffCO2observations.Now,theﬁrstdata-basedestimatesextendingbackto1957/58arebecomingavailable(Jena-MLS,Rö-denbecketal.,2022,LDEO-HPD,Benningtonetal.,2022;Gloegeetal.,2022).Thesearebasedonamulti-linearre-gressionofpCO2withenvironmentalpredictors(Rödenbecketal.,2022,includedhere)oronmodel–datapCO2misﬁtsandtheirrelationtoenvironmentalpredictors(Benningtonetal.,2022).TheJena-MLSestimatefallswellwithintherangeofGOBMestimatesandhasacorrelationof0.98withSOCEAN(1959–2021and1959–1989).ItagreeswellonthemeanSOCEANestimatesince1977withaslightlyhigheram-plitudeofvariability(Fig.10).Until1976,Jena-MLSis0.2–0.3GtCyr−1belowthecentralSOCEANestimate.Theagree-ment,especiallyonphasingofvariability,isimpressive,andthediscrepanciesinthemeanﬂux1959–1976couldbeex-plainedbyanoverestimatedtrendofJena-MLS(Rödenbecketal.,2022).Benningtonetal.(2022)reportalargerﬂuxintothepre-1990oceanthaninJena-MLS.ThereportedSOCEANestimatefromGOBMsanddataproductsis2.1±0.4GtCyr−1overtheperiod1994to2007,whichisinagreementwiththeoceaninteriorestimateof2.2±0.4GtCyr−1,whichaccountsfortheclimateeffectonthenaturalCO2ﬂuxof−0.4±0.24GtCyr−1(Gruberetal.,2019)tomatchthedeﬁnitionofSOCEANusedhere(Haucketal.,2020).Thiscomparisondependscriticallyonthees-timateoftheclimateeffectonthenaturalCO2ﬂux,whichissmallerfromtheGOBMs(−0.1GtCyr−1)thaninGruberetal.(2019).UncertaintiesinthesetwoestimateswouldalsooverlapwhenusingtheGOBMestimateoftheclimateeffectonthenaturalCO2ﬂux.During2010–2016,theoceanCO2sinkappearstohavein-tensiﬁedinlinewiththeexpectedincreasefromatmosphericCO2(McKinleyetal.,2020).ThiseffectisstrongerinthefCO2-baseddataproducts(Fig.10,oceansink2016mi-nus2010,GOBMs:+0.42±0.09GtCyr−1;dataproducts:+0.52±0.22GtCyr−1).Thereductionof−0.09GtCyr−1(range:−0.39to+0.01GtCyr−1)intheoceanCO2sinkin2017isconsistentwiththereturntonormalcondi-tionsaftertheElNiñoin2015/16,whichcausedanen-hancedsinkinpreviousyears.After2017,theGOBMen-semblemeansuggeststheoceansinklevellingoffatabout2.6GtCyr−1,whereasthedataproductestimateincreasesby0.24±0.17GtCyr−1overthesameperiod.3.5.3Finalyear2021TheestimatedoceanCO2sinkwas2.9±0.4GtCin2021.Thisisadecreaseof0.12GtCcomparedto2020,inlinewiththeexpectedsinkweakeningfrompersistentLaNiñacon-ditions.GOBManddataproductestimatesconsistentlyre-sultinastagnationofSOCEAN(GOBMs:−0.09±0.15GtC;dataproducts:−0.15±0.24GtC).SevenmodelsandsixdataproductsshowadecreaseinSOCEAN(GOBMsdownto−0.31GtC,dataproductsdownto−0.58GtC),whilethreemodelsandtwodataproductsshowanincreaseinSOCEAN(GOBMsupto0.15GtC,dataproductsupto0.12GtC;Fig.10).Thedataproductshavealargeruncertaintyatthetailsofthereconstructedtimeseries(e.g.Watsonetal.,2020).Speciﬁcally,thedataproducts’estimateofthelastyearisregularlyadjustedinthefollowingreleaseowingtothetaileffectandanincrementallyincreasingdataavailabil-itywitha1–5-yearlag(Fig.10inset).EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget202248393.5.4Year2022projectionUsingafeed-forwardneuralnetworkmethod(seeSect.2.4)weprojectanoceansinkof2.9GtCfor2022.Thisissimilartotheyear2021astheLaNiñaconditionspersistin2022.3.5.5ModelevaluationTheadditionalsimulationDallowsustoseparatethean-thropogeniccarboncomponent(steadystateandnon-steadystate,simD−simA)andcomparethemodelﬂuxanddis-solvedinorganiccarbon(DIC)inventorychangedirectlytotheinterioroceanestimateofGruberetal.(2019)withoutfurtherassumptions.TheGOBMensembleaverageofan-thropogeniccarboninventorychanges1994–2007amountsto2.2GtCyr−1andisthuslowerthanthe2.6±0.3GtCyr−1estimatedbyGruberetal.(2019).OnlyfourmodelswiththehighestsinkestimatefallwithintherangereportedbyGruberetal.(2019).ThissuggeststhatthemajorityoftheGOBMsunderestimateanthropogeniccarbonuptakeby10%–20%.AnalysisofEarthsystemmodelsindicatethatanunderes-timationbyabout10%maybeduetobiasesinoceancar-bontransportandmixingfromthesurfacemixedlayertotheoceaninterior(Gorisetal.,2018;Terhaaretal.,2021;Bour-geoisetal.,2022;Terhaaretal.,2022),biasesinthechemicalbuffercapacity(Revellefactor)oftheocean(VaittinadaAyaretal.,2022;Terhaaretal.,2022),andpartlyduetothelatestartingdateofthesimulations(mirroredinatmosphericCO2chosenforthepre-industrialcontrolsimulation,TableA2,Bronselaeretal.,2017;Terhaaretal.,2022).Interestingly,andincontrasttotheuncertaintiesinthesurfaceCO2ﬂux,weﬁndthelargestmismatchininterioroceancarbonaccu-mulationinthetropics(93%ofthemismatch),withminorcontributionfromthenorth(1%)andthesouth(6%).Thishighlightstheroleofinterioroceancarbonredistributionforthoseinventories(Khatiwalaetal.,2009).Theevaluationoftheoceanestimates(Fig.B2)showsaroot-mean-squarederror(RMSE)fromannuallydetrendeddataof0.4to2.6µatmforthesevenfCO2-baseddataprod-uctsovertheglobe,relativetothefCO2observationsfromtheSOCATv2022datasetfortheperiod1990–2021.TheGOBMRMSEsarelargerandrangefrom3.0to4.8µatm.TheRMSEsaregenerallylargerathighlatitudescomparedtothetropics,forboththedataproductsandtheGOBMs.ThedataproductshaveRMSEsof0.4to3.2µatminthetrop-ics,0.8to2.8µatminthenorthernextratropics(>30◦N),and0.8to3.6µatminthesouthernextratropics(<30◦S).NotethatthedataproductsarebasedontheSOCATv2022database;hence,theSOCATisnotanindependentdatasetfortheevaluationofthedataproducts.TheGOBMRM-SEsaremorespreadacrossregions,rangingfrom2.5to3.9µatminthetropics,3.1to6.5µatminthenorth,and5.4to7.9µatminthesouth.ThehigherRMSEsoccurinregionswithstrongerclimatevariability,suchasthenorthernandsouthernhighlatitudes(polewardofthesubtropicalgyres).Figure9.ThepartitioningoftotalanthropogenicCO2emis-sions(EFOS+ELUC)across(a)theatmosphere(airbornefraction),(b)land(land-bornefraction),and(c)ocean(ocean-bornefraction).Blacklinesrepresentthecentralestimate,andthecolouredshad-ingrepresentstheuncertainty.Thedashedgreylinesrepresentthelong-termaverageoftheairborne(44%),land-borne(30%),andocean-borne(25%)fractionsduring1960–2021.https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224840P.Friedlingsteinetal.:GlobalCarbonBudget2022Figure10.Comparisonoftheanthropogenicatmosphere–oceanCO2ﬂuxshowingthebudgetvaluesofSOCEAN(black;withtheuncertaintyingreyshading),individualoceanmodels(royalblue),andtheoceanfCO2-baseddataproducts(cyan;withWatsonetal.,2020,shownasadashedlineasitisnotusedfortheensemblemean).Onlyonedataproduct(Jena-MLS)extendsbackto1959(Rödenbecketal.,2022).ThefCO2-baseddataproductsweread-justedforthepre-industrialoceansourceofCO2fromriverinputtotheoceanbysubtractingasourceof0.65GtCyr−1tomakethemcomparabletoSOCEAN(seeSect.2.4).ThebarplotinthelowerrightillustratesthenumberoffCO2observationsintheSOCATv2022database(Bakkeretal.,2022).Greybarsindicatethenum-berofdatapointsinSOCATv2021,andcolouredbarsshowthenewlyaddedobservationsinv2022.TheupperrangesofthemodelRMSEshavedecreasedsome-whatrelativetoFriedlingsteinetal.(2022a).3.6Landsink3.6.1Historicalperiod1850–2021Cumulatedsince1850,theterrestrialCO2sinkamountsto210±45GtC,31%oftotalanthropogenicemissions.Overthehistoricalperiod,thesinkincreasedinpacewiththeex-ponentialanthropogenicemissionsincrease(Fig.3b).3.6.2Recentperiod1960–2021TheterrestrialCO2sinkincreasedfrom1.2±0.4GtCyr−1inthe1960sto3.1±0.6GtCyr−1during2012–2021,withimportantinterannualvariationsofupto2GtCyr−1gener-allyshowingadecreasedlandsinkduringElNiñoevents(Fig.8),responsibleforthecorrespondingenhancedgrowthrateinatmosphericCO2concentration.ThelargerlandCO2sinkduring2012–2021comparedtothe1960sisreproducedbyalltheDGVMsinresponsetotheincreaseinbothatmo-sphericCO2andnitrogendepositionandthechangesincli-mateandisconsistentwithconstraintsfromtheotherbudgetterms(Table5).Overtheperiod1960topresenttheincreaseintheglobalterrestrialCO2sinkislargelyattributedtotheCO2fertil-izationeffect(Prenticeetal.,2001;Piaoetal.,2009),di-rectlystimulatingplantphotosynthesisandincreasedplantwateruseinwater-limitedsystems,withasmallnegativecontributionofclimatechange(Fig.11).ThereisarangeofevidencetosupportapositiveterrestrialcarbonsinkinresponsetoincreasingatmosphericCO2,albeitwithuncer-tainmagnitude(Walkeretal.,2021).Asexpectedfromthe-ory,thegreatestCO2effectissimulatedinthetropicalforestregions,associatedwithwarmtemperaturesandlonggrow-ingseasons(Hickleretal.,2008)(Fig.11a).However,ev-idencefromtropicalintactforestplotsindicateanoveralldeclineinthelandsinkacrossAmazonia(1985–2011),at-tributedtoenhancedmortalityoffsettingproductivitygains(Brienenetal.,2005,Hubauetal.,2020).During2012–2021thelandsinkispositiveinallregions(Fig.6)withtheexceptionofeasternBrazil,thesouthwesternUS,south-easternEurope,centralAsia,northernandsouthernAfrica,andeasternAustralia,wherethenegativeeffectsofclimatevariabilityandchange(i.e.reducedrainfall)counterbalanceCO2effects.ThisisclearlyvisibleinFig.11wheretheef-fectsofCO2(Fig.11a)andclimate(Fig.11b)assimulatedbytheDGVMsareisolated.ThenegativeeffectofclimateisthestrongestinmostofSouthAmerica,CentralAmerica,thesouthwesternUS,centralEurope,westernSahel,south-ernAfrica,SoutheastAsiaandsouthernChina,andeasternAustralia(Fig.11b).Globally,climatechangereducesthelandsinkby0.63±0.52GtCyr−1or17%(2012–2021).Since2020theglobehasexperiencedLaNiñaconditions,whichwouldbeexpectedtoleadtoanincreasedlandcar-bonsink.Aclearpeakinthegloballandsinkisnotevi-dentinSLAND,andweﬁndthataLaNiña-drivenincreaseintropicallandsinkisoffsetbyareducedhighlatitudeextrat-ropicallandsink,whichmaybelinkedtothelandresponsetorecentclimateextremes.Inthepastyearsseveralregionsexperiencedrecord-settingﬁreevents.Whileglobalburnedareahasdeclinedoverthepastdecades,mostlyduetode-cliningﬁreactivityinsavannas(Andelaetal.,2017),forestﬁreemissionsarerisingandhavethepotentialtocounterthenegativeﬁretrendinsavannas(Zhengetal.,2021).Notewor-thyeventsincludetheBlackSummereventinAustraliain2019–2020(emissionsofroughly0.2GtC;vanderVeldeetal.,2021)andeventsinSiberiain2021whereemissionsap-proached0.4GtCor3timesthe1997–2020averageaccord-ingtoGFED4s.Whileotherregions,includingthewesternUSandMediterraneanEurope,alsoexperiencedintenseﬁreseasonsin2021,theiremissionsaresubstantiallylower.DespitetheseregionalnegativeeffectsofclimatechangeonSLAND,theefﬁciencyoflandtoremoveanthropogenicCO2emissionshasremainedbroadlyconstantoverthelast6decades,withaland-bornefraction(SLAND/(EFOS+ELUC))of∼30%(Fig.9).EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224841Figure11.Attributionoftheatmosphere–ocean(SOCEAN)andatmosphere–land(SLAND)CO2ﬂuxesto(a)increasingatmosphericCO2concentrationsand(b)changesinclimate,averagedoverthepreviousdecade2012–2021.Alldatashownarefromtheprocessed-basedGOBMsandDGVMs.ThesumofoceanCO2andclimateeffectswillnotequaltheoceansinkshowninFig.6,whichincludesthefCO2-baseddataproducts.SeeAppendicesC3.2andC4.1forattributionmethodology.UnitsareinkgCm−2yr−1(notethenon-linearcolourscale).3.6.3Finalyear2021TheterrestrialCO2sinkfromtheDGVMsensemblewas3.5±0.9GtCin2021,slightlyabovethedecadalaverageof3.1±0.6GtCyr−1(Fig.4,Table6).WenotethattheDGVMestimatefor2021islargerthan,butwithintheuncertaintyof,the2.8±0.9GtCyr−1estimatefromtheresidualsinkfromtheglobalbudget(EFOS+ELUC−GATM−SOCEAN)(Table5).3.6.4Year2022projectionUsingafeed-forwardneuralnetworkmethodweprojectalandsinkof3.4GtCfor2022,verysimilartothe2021esti-mate.Asfortheoceansink,weattributethistothepersis-tenceofLaNiñaconditionsin2022.3.6.5ModelevaluationTheevaluationoftheDGVMs(Fig.B3)showsgenerallyhighskillscoresacrossmodelsforrunoffandtoalesserextentforvegetationbiomass,grossprimaryproduction(orproductivity;GPP),andecosystemrespiration(Fig.B3,leftpanel).Skillscorewaslowestforleafareaindexandnetecosystemexchange,withthewidestdisparityamongmod-elsforsoilcarbon.TheseconclusionsaresupportedbyamorecomprehensiveanalysisofDGVMperformanceincomparisonwithbenchmarkdata(Seileretal.,2022).Fur-thermore,resultsshowhowDGVMdifferencesareoftenofsimilarmagnitudecomparedwiththerangeacrossobserva-tionaldatasets.https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224842P.Friedlingsteinetal.:GlobalCarbonBudget2022Figure12.The2012–2021decadalmeannetatmosphere–oceanandatmosphere–landﬂuxesderivedfromtheoceanmodelsandfCO2products(yaxis,right-andleft-pointingbluetriangles,re-spectively)andfromtheDGVMs(xaxis,greensymbols)andthesameﬂuxesestimatedfromtheinversions(purplesymbolsonsec-ondaryxandyaxes).Thegreycentralpointisthemean(±1σ)ofSOCEANand(SLAND−ELUC)asassessedinthisbudget.Theshadeddistributionsshowthedensityoftheensembleofindivid-ualestimates.Thegreydiagonalbandrepresentsthefossilfuelemissionsminustheatmosphericgrowthratefromthisbudget(EFOS−GATM).NotethatpositivevaluesareCO2sinks.3.7Partitioningthecarbonsinks3.7.1GlobalsinksandspreadofestimatesIntheperiod2012–2021,thebottom-upviewoftotalglobalcarbonsinksprovidedbytheGCB,SOCEANfortheoceanandSLAND–ELUCfortheland(tobecomparabletoinver-sions),agreescloselywiththetop-downglobalcarbonsinksdeliveredbytheatmosphericinversions.Figure12showsbothtotalsinkestimatesofthelastdecadesplitbyoceanandland(includingELUC),whichmatchthedifferencebe-tweenGATMandEFOStowithin0.01–0.12GtCyr−1forin-versesystems,andto0.34GtCyr−1fortheGCBmean.ThelatterrepresentstheBIMdiscussedinSect.3.8,whichbyde-signisminimalfortheinversesystems.ThedistributionsbasedontheindividualmodelsanddataproductsrevealsubstantialspreadbutconvergenearthedecadalmeansquotedinTables5and6.SinkestimatesforSOCEANandfrominversesystemsaremostlynon-Gaussian,whiletheensembleofDGVMsappearsmorenormallydis-tributed,justifyingtheuseofamulti-modelmeanandstan-darddeviationfortheirerrorsinthebudget.Noteworthyisthatthetailsofthedistributionsprovidedbythelandandoceanbottom-upestimateswouldnotagreewiththeglobalconstraintprovidedbythefossilfuelemissionsandtheob-servedatmosphericCO2growthrate(EFOS−GATM).ThisillustratesthepoweroftheatmosphericjointconstraintfromGATMandtheglobalCO2observationnetworkitderivesfrom.3.7.2Totalatmosphere-to-landﬂuxesThetotalatmosphere-to-landﬂuxes(SLAND−ELUC),cal-culatedhereasthedifferencebetweenSLANDfromtheDGVMsandELUCfromthebookkeepingmodels,amountstoa1.9±0.9GtCyr−1sinkduring2012–2021(Table5).Es-timatesoftotalatmosphere-to-landﬂuxes(SLAND−ELUC)fromtheDGVMsalone(1.5±0.5GtCyr−1)areconsistentwiththisestimateandalsowiththeglobalcarbonbudgetconstraint(EFOS−GATM−SOCEAN,1.5±0.6GtCyr−1Ta-ble5).Forthelastdecade(2012–2021),theinversionsesti-matethenetatmosphere-to-landuptaketoliewithinarangeof1.1to1.7GtCyr−1,consistentwiththeGCBandDGVMestimatesofSLAND−ELUC(Fig.13toprow).3.7.3Totalatmosphere-to-oceanﬂuxesForthe2012–2021period,theGOBMs(2.6±0.5GtCyr−1)producealowerestimatefortheoceansinkthanthefCO2-baseddataproducts(3.2±0.6GtCyr−1),whichshowsupinFig.12asaseparatepeakinthedistributionfromtheGOBMs(trianglesymbolspointingright)andfromthefCO2-basedproducts(trianglesymbolspointingleft).Atmosphericinversions(2.7to3.3GtCyr−1)alsosuggesthigheroceanuptakeinthelastdecade(Fig.13toprow).Ininterpretingthesedifferences,wecautionthattheriverinetransportofcarbontakenuponlandandoutgassingfromtheoceanisasubstantial(0.65GtCyr−1)anduncertaintermthatseparatesthevariousmethods.ArecentestimateofdecadaloceanuptakefromobservedO2/N2ratios(Tohjimaetal.,2019)alsopointstowardsalargeroceansink,albeitwithlargeuncertainty(2012–2016:3.1±1.5GtCyr−1).3.7.4RegionalbreakdownandinterannualvariabilityFigure13alsoshowsthelatitudinalpartitioningofthetotalatmosphere-to-surfaceﬂuxesexcludingfossilCO2emissions(SOCEAN+SLAND−ELUC)accordingtothemulti-modelav-erageestimatesfromGOBMsandoceanfCO2-basedprod-ucts(SOCEAN)andDGVMs(SLAND−ELUC)andfromatmo-sphericinversions(SOCEANandSLAND−ELUC).NorthDespitebeingoneofthemostdenselyobservedandstud-iedregionsofourglobe,annualmeancarbonsinkesti-matesinthenorthernextratropics(northof30◦N)con-EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224843Figure13.CO2ﬂuxesbetweentheatmosphereandtheEarth’ssurfaceseparatedbetweenlandandoceansgloballyandinthreelatitudebands.TheoceanﬂuxisSOCEAN,andthelandﬂuxisthenetofatmosphere–landﬂuxesfromtheDGVMs.Thelatitudebandsare(toprow)global,(secondrow)north(>30◦N),(thirdrow)tropics(30◦S–30◦N),and(bottomrow)south(<30◦S),showingvaluesoverocean(leftcolumn)andland(middlecolumn)andintotal(rightcolumn).Estimatesareshownforprocess-basedmodels(DGVMsforland,GOBMsforoceans),inversionsystems(landandocean),andfCO2-baseddataproducts(oceanonly).Positivevaluesindicateaﬂuxfromtheatmospheretothelandortheocean.Meanestimatesfromthecombinationoftheprocessmodelsforthelandandoceansareshown(blackline)with±1standarddeviation(1σ)ofthemodelensemble(greyshading).Forthetotaluncertaintyintheprocess-basedestimateofthetotalsink,uncertaintiesaresummedinquadrature.Meanestimatesfromtheatmosphericinversionsareshown(purplelines)withtheirfullspread(purpleshading).MeanestimatesfromthefCO2-baseddataproductsareshownfortheoceandomain(lightbluelines)withtheir±1σspread(lightblueshading).TheglobalSOCEAN(upperleft)andthesumofSOCEANinallthreeregionsrepresentstheanthropogenicatmosphere-to-oceanﬂuxbasedontheassumptionthatthepre-industrialoceansinkwas0GtCyr−1whenriverineﬂuxesarenotconsidered.Thisassumptiondoesnotholdattheregionallevel,wherepre-industrialﬂuxescanbesigniﬁcantlydifferentfromzero.Hence,theregionalpanelsforSOCEANrepresentacombinationofnaturalandanthropogenicﬂuxes.BiascorrectionandareaweightingwereonlyappliedtoglobalSOCEAN;hence,thesumoftheregionsisslightlydifferentfromtheglobalestimate(<0.05GtCyr−1).https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224844P.Friedlingsteinetal.:GlobalCarbonBudget2022tinuetodiffer.Theatmosphericinversionssuggestanatmosphere-to-surfacesink(SOCEAN+SLAND−ELUC)for2012–2021of2.0to3.2GtCyr−1,whichishigherthantheprocessmodels’estimateof2.2±0.4GtCyr−1(Fig.13).TheGOBMs(1.2±0.2GtCyr−1),fCO2-baseddataprod-ucts(1.4±0.1GtCyr−1),andinversionsystems(0.9to1.4GtCyr−1)produceconsistentestimatesoftheoceansink.Thus,thedifferencemainlyarisesfromthetotallandﬂux(SLAND−ELUC)estimate,whichis1.0±0.4GtCyr−1intheDGVMscomparedto0.6to2.0GtCyr−1intheatmosphericinversions(Fig.13,secondrow).DiscrepanciesinthenorthernlandﬂuxesconformwithpersistentissuessurroundingthequantiﬁcationofthedriversoftheglobalnetlandCO2ﬂux(Arnethetal.,2017;Huntzingeretal.,2017;O’Sullivanetal.,2022)andthedis-tributionofatmosphere-to-landﬂuxesbetweenthetropicsandhighnorthernlatitudes(Baccinietal.,2017;Schimeletal.,2015;Stephensetal.,2007;Ciaisetal.,2019;Gaubertetal.,2019).Inthenorthernextratropics,theprocessmodels,inver-sions,andfCO2-baseddataproductsconsistentlysug-gestthatmostofthevariabilitystemsfromtheland(Fig.13).Inversionsgenerallyestimatesimilarinterannualvariations(IAVs)overlandtoDGVMs(0.30–0.37vs.0.17–0.69GtCyr−1,averagedover1990–2021),andtheyhavehigherIAVinoceanﬂuxes(0.05–0.09GtCyr−1)relativetoGOBMs(0.02–0.06GtCyr−1,Fig.B2)andfCO2-baseddataproducts(0.03–0.09GtCyr−1).TropicsInthetropics(30◦S–30◦N),boththeatmosphericinver-sionsandprocessmodelsestimateatotalcarbonbalance(SOCEAN+SLAND−ELUC)thatisclosetoneutraloverthepastdecade.TheGOBMs(0.06±0.34GtCyr−1),fCO2-baseddataproducts(0.00±0.06GtCyr−1),andinversionsystems(−0.2to0.5GtCyr−1)allindicateanapproximatelyneutraltropicaloceanﬂux(seeFig.B1forspatialpat-terns).DGVMsindicateanetlandsink(SLAND−ELUC)of0.5±0.3GtCyr−1,whereastheinversionsystemsindicateanetlandﬂuxbetween−0.9and0.7GtCyr−1,albeitwithhighuncertainty(Fig.13,thirdrow).Thetropicallandsaretheoriginofmostoftheatmo-sphericCO2interannualvariability(Ahlströmetal.,2015),andthisisconsistentamongtheprocessmodelsandinver-sions(Fig.13).Theinterannualvariabilityinthetropicsissimilaramongtheoceandataproducts(0.07–0.16GtCyr−1)andtheGOBMs(0.07–0.16GtCyr−1,Fig.B2),whichisthehighestoceansinkvariabilityofallregions.TheDGVMsandinversionsindicatethatatmosphere-to-landCO2ﬂuxesaremorevariablethanatmosphere-to-oceanCO2ﬂuxesinthetropics,withinterannualvariabilityof0.5to1.1and0.8to1.0GtCyr−1forDGVMsandinversions,respectively.SouthInthesouthernextratropics(southof30◦S),theatmo-sphericinversionssuggestatotalatmosphere-to-surfacesink(SOCEAN+SLAND−ELUC)for2012–2021of1.6to1.9GtCyr−1,slightlyhigherthantheprocessmodels’esti-mateof1.4±0.3GtCyr−1(Fig.13).Anapproximatelyneu-traltotallandﬂux(SLAND−ELUC)forthesouthernextratrop-icsisestimatedbyboththeDGVMs(0.02±0.06GtCyr−1)andtheinversionsystems(sinkof−0.2to0.2GtCyr−1).Thismeansnearlyallcarbonuptakeisduetooceanicsinkssouthof30◦S.TheSouthernOceanﬂuxinthefCO2-baseddataproducts(1.8±0.1GtCyr−1)andinversiones-timates(1.6to1.9GtCyr−1)ishigherthanintheGOBMs(1.4±0.3GtCyr−1)(Fig.13,bottomrow).Thisdiscrepancyinthemeanﬂuxislikelyexplainedbytheuncertaintyintheregionaldistributionoftheriverﬂuxadjustment(Aumontetal.,2001;Lacroixetal.,2020)appliedtofCO2-baseddataproductsandinversesystemstoisolatetheanthropogenicSOCEANﬂux.OtherpossiblycontributingfactorsarethatthedataproductspotentiallyunderestimatethewinterCO2out-gassingsouthofthePolarFront(Bushinskyetal.,2019)andpotentialmodelbiases.CO2ﬂuxesfromthisregionaremoresparselysampledbyallmethods,especiallyinwintertime(Fig.B1).DominantbiasesinEarthsystemmodelsarere-latedtomodewaterformation,stratiﬁcation,andthechem-icalbuffercapacity(Terhaaretal.,2021;Bourgeoisetal.,2022;Terhaaretal.,2022).Theinterannualvariabilityinthesouthernextratropicsislowbecauseofthedominanceofoceanareaswithlowvariabilitycomparedtolandareas.Thesplitbetweenland(SLAND−ELUC)andocean(SOCEAN)showsasubstantialcontributiontovariabilityinthesouthcomingfromtheland,withnoconsistencybetweentheDGVMsandtheinversionsoramonginversions.Thisisexpectedduetothedifﬁcultyofexactlyseparatingthelandandoceanicﬂuxeswhenviewedfromatmosphericobservationsalone.TheSOCEANinteran-nualvariabilitywasfoundtobehigherinthefCO2-baseddataproducts(0.09to0.19GtCyr−1)comparedtoGOBMs(0.03to0.06GtCyr−1)in1990–2021(Fig.B2).Modelsub-samplingexperimentsrecentlyillustratedthatobservation-basedproductsmayoverestimatedecadalvariabilityintheSouthernOceancarbonsinkby30%duetodatasparsity,basedononedataproductwiththehighestdecadalvariabil-ity(Gloegeetal.,2021).Tropicalvs.northernlanduptakeAcontinuingconundrumisthepartitioningoftheglobalatmosphere–landﬂuxbetweentheNorthernHemispherelandandthetropicalland(Stephensetal.,2017;Panetal.,2011;Gaubertetal.,2019).Itisofimportancebecauseeachregionhasitsownhistoryofland-usechange,climatedrivers,andtheimpactofincreasingatmosphericCO2andnitrogendeposition.QuantifyingthemagnitudeofeachsinkEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224845isaprerequisitetounderstandinghoweachindividualdriverimpactsthetropicalandmid-andhigh-latitudecarbonbal-ance.Wedeﬁnethenorth–south(N–S)differenceasnetatmosphere–landﬂuxnorthof30◦Nminusthenetatmosphere–landﬂuxsouthof30◦N.Fortheinversions,theN–Sdifferencerangesfrom0.1to2.9GtCyr−1acrossthisyear’sinversionensemblewithapreferenceacrossmodelsforeitherasmallernorthernlandsinkwithanear-neutraltropicallandﬂux(mediumN–Sdifference)oralargenorth-ernlandsinkandatropicallandsource(largeN–Sdiffer-ence).IntheensembleofDGVMstheN–Sdifferenceis0.6±0.5GtCyr−1,amuchnarrowerrangethantheonefrominversions.OnlytwoDGVMshaveaN–Sdifferencelargerthan1.0GtCyr−1.ThelargeragreementacrossDGVMsthanacrossinversionsistobeexpectedasthereisnocorrelationbetweennorthernandtropicallandsinksintheDGVMs,asopposedtotheinversionswherethesumofthetworegionsbeingwell-constrainedleadstoananti-correlationbetweenthesetworegions.ThemuchsmallerspreadintheN–Sdif-ferencebetweentheDGVMscouldhelptoscrutinizetheinversesystemsfurther.Forexample,alargenorthernlandsinkandatropicallandsourceinaninversionwouldsuggestalargesensitivitytoCO2fertilization(thedominantfactordrivingthelandsinks)fornorthernecosystems,whichwouldbenotmirroredbytropicalecosystems.SuchacombinationcouldbehardtoreconcilewiththeprocessunderstandinggainedfromtheDGVMensemblesandindependentmea-surements(e.g.free-airCO2enrichmentexperiments).Suchinvestigationswillbefurtherpursuedintheupcomingas-sessmentfromREgionalCarbonCycleAssessmentandPro-cesses(RECCAP2;Ciaisetal.,2022).3.8Closingtheglobalcarboncycle3.8.1PartitioningofcumulativeemissionsandsinkﬂuxesTheglobalcarbonbudgetoverthehistoricalperiod(1850–2021)isshowninFig.3.Emissionsduringtheperiod1850–2021amountedto670±65GtCandwerepartitionedamongtheatmosphere(275±5GtC;41%),ocean(175±35GtC;26%),andland(210±45GtC;31%).Thecumulativelandsinkisalmostequaltothecumulativeland-useemissions(200±60GtC),makingthegloballandnearlyneutraloverthewhole1850–2021period.Theuseofnearlyindependentestimatesfortheindividualtermsoftheglobalcarbonbudgetshowsacumulativebudgetimbalanceof15GtC(2%oftotalemissions)during1850–2021(Fig.3,Table8),which,ifcorrect,suggeststhatemis-sionscouldbeslightlytoohighbythesameproportion(2%)orthatthecombinedlandandoceansinksareslightlyunder-estimated(byabout3%),althoughthesearewellwithintheuncertaintyrangeofeachcomponentofthebudget.Never-theless,partoftheimbalancecouldoriginatefromtheesti-mationofsigniﬁcantincreaseinEFOSandELUCbetweenthemid-1920sandthemid-1960sthatisunmatchedbyasim-ilargrowthinatmosphericCO2concentrationasrecordedinicecores(Fig.3).However,theknownlossofadditionalsinkcapacityof30–40GtC(overthe1850–2020period)duetoreducedforestcoverhasnotbeenaccountedforinourmethodandwouldexacerbatethebudgetimbalance(seeAp-pendixD4).Forthemorerecent1960–2021periodwheredirectat-mosphericCO2measurementsareavailable,totalemis-sions(EFOS+ELUC)amountedto470±50GtC,ofwhich390±20GtC(82%)werecausedbyfossilCO2emis-sionsand85±45GtC(18%)byland-usechange(Ta-ble8).Thetotalemissionswerepartitionedamongtheat-mosphere(210±5GtC;45%),ocean(120±25GtC;26%),andland(145±30GtC;30%),withanear-zero(−5GtC)unattributedbudgetimbalance.Allcomponentsexceptland-usechangeemissionshavesigniﬁcantlygrownsince1960,withimportantinterannualvariabilityinthegrowthrateinatmosphericCO2concentrationandinthelandCO2sink(Fig.4)andsomedecadalvariabilityinallterms(Table6).DifferenceswithpreviousbudgetreleasesaredocumentedinFig.B5.Theglobalcarbonbudgetaveragedoverthelastdecade(2012–2021)isshowninFigs.2and14(rightpanel)andTa-ble6.Forthisperiod,89%ofthetotalemissions(EFOS+ELUC)werefromfossilCO2emissions(EFOS),and11%werefromland-usechange(ELUC).Thetotalemissionswerepartitionedamongtheatmosphere(48%),ocean(26%),andland(29%),withanear-zerounattributedbudgetimbalance(∼3%).Forsingleyears,thebudgetimbalancecanbelarger(Fig.4).For2021,thecombinationofourestimatedsources(10.9±0.9GtCyr−1)andsinks(11.6±1.0GtCyr−1)leadstoaBIMof−0.6GtC,suggestingaslightunderestimationoftheanthropogenicsourcesand/oranoverestimationofthecombinedlandandoceansinks.3.8.2CarbonbudgetimbalancetrendandvariabilityThecarbonbudgetimbalance(BIM;Eq.1,Fig.4)quantiﬁesthemismatchbetweentheestimatedtotalemissionsandtheestimatedchangesintheatmosphere,land,andoceanreser-voirs.Themeanbudgetimbalancefrom1960to2021isverysmall(4.6GtCovertheperiod,i.e.averageof0.07GtCyr−1)andshowsnotrendoverthefulltimeseries(Fig.4).Theprocessmodels(GOBMsandDGVMs)anddataproductshavebeenselectedtomatchobservationalconstraintsinthe1990s,butnofurtherconstraintshavebeenappliedtotheirrepresentationoftrendandvariability.Therefore,thenear-zeromeanandtrendinthebudgetimbalanceisseenasevi-denceofacoherentcommunityunderstandingoftheemis-sionsandtheirpartitioningonthosetimescales(Fig.4).However,thebudgetimbalanceshowssubstantialvariabilityhttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224846P.Friedlingsteinetal.:GlobalCarbonBudget2022Figure14.Cumulativechangesoverthe1850–2021period(left)andaverageﬂuxesoverthe2012–2021period(right)fortheanthro-pogenicperturbationoftheglobalcarboncycle.SeethecaptionofFig.3forkeyinformationandSect.2forfulldetails.ontheorderof±1GtCyr−1,particularlyoversemi-decadaltimescales,althoughmostofthevariabilityiswithintheun-certaintyoftheestimates.Thepositivecarbonimbalanceduringthe1960sandearly1990sindicatesthateithertheemissionswereoverestimatedorthesinkswereunderesti-matedduringtheseperiods.Thereverseistrueforthe1970sandtoalesserextentforthe1980sandthe2012–2021period(Fig.4,Table6).Wecannotattributethecauseofthevariabilityinthebud-getimbalancewithouranalysis,weonlynotethatthebudgetimbalanceisunlikelytobeexplainedbyerrorsorbiasesintheemissionsalonebecauseofitslargesemi-decadalvari-abilitycomponent,avariabilitythatisuntypicalofemissionsandwhichhasnotchangedinthepast60yearsdespiteaneartriplingofemissions(Fig.4).ErrorsinSLANDandSOCEANaremorelikelytobethemaincauseforthebudgetimbal-ance,especiallyoninterannualtosemi-decadaltimescales.Forexample,underestimationoftheSLANDbyDGVMshasbeenreportedfollowingtheeruptionofMountPinatuboin1991,possiblyduetomissingresponsestochangesindiffuseradiation(Mercadoetal.,2009).AlthoughsinceGCB2021weaccountedforaerosoleffectsonsolarradiationquan-tityandquality(diffusevs.direct),mostDGVMsonlyusedtheformerasinput(i.e.totalsolarradiation)(TableA1).Thus,theensemblemeanmaynotcapturethefulleffectsofvolcaniceruptions,i.e.associatedwithhighlight-scatteringsulfateaerosols,onthelandcarbonsink(O’Sullivanetal.,2021).DGVMsaresuspectedtooverestimatethelandsinkinresponsetothewetdecadeofthe1970s(Sitchetal.,2008).Quasi-decadalvariabilityintheoceansinkhasalsobeenre-ported,withallmethodsagreeingonasmallerthanexpectedoceanCO2sinkinthe1990sandalargerthanexpectedsinkinthe2000s(Fig.10;Landschützeretal.,2016;DeVriesetal.,2019;Haucketal.,2020;McKinleyetal.,2020).Errorsinsinkestimatescouldalsobedrivenbyerrorsinthecli-maticforcingdata,particularlyprecipitationforSLANDandwindforSOCEAN.Also,theBIMshowssubstantialdeparturefromzeroonyearlytimescales(Fig.4e),highlightingunre-solvedvariabilityofthecarboncycle,likelyinthelandsink(SLAND),givenitslargeyear-to-yearvariability(Figs.4dand8).Boththebudgetimbalance(BIM,Table6)andtheresiduallandsinkfromtheglobalbudget(EFOS+ELUC−GATM−SOCEAN,Table5)includeanerrortermduetotheinconsis-tenciesthatarisefromusingELUCfrombookkeepingmodelsandSLANDfromDGVMs,mostnotablythelossofadditionalsinkcapacity(seeSect.2.7andAppendixD4).Otherdiffer-encesincludeabetteraccountingofland-usechangeprac-ticesandprocessesinbookkeepingmodelsthaninDGVMsortheerrorinbookkeepingmodelsofhavingpresent-dayobservedcarbondensitiesﬁxedinthepast.ThatthebudgetimbalanceshowsnocleartrendtowardslargervaluesovertimeisanindicationthattheseinconsistenciesprobablyplayaminorrolecomparedtoothererrorsinSLANDorSOCEAN.Althoughthebudgetimbalanceisnearzeroforthere-centdecades,itcouldbeduetocompensationoferrors.WecannotexcludeanoverestimationofCO2emissions,partic-ularlyfromland-usechange,giventheirlargeuncertainty,ashasbeensuggestedelsewhere(Piaoetal.,2018),com-binedwithanunderestimateofthesinks.AlargerDGVM(SLAND−ELUC)overtheextratropicswouldreconcilemodelresultswithinversionestimatesforﬂuxesinthetotallandduringthepastdecade(Fig.13;Table5).Likewise,alargerSOCEANisalsopossiblegiventhehigherestimatesfromthedataproducts(seeSect.3.1.2,Figs.10and13),theunderesti-mationofinterioroceananthropogeniccarbonaccumulationintheGOBMs(Sect.3.5.5),andtherecentlysuggestedup-wardadjustmentsoftheoceancarbonsinkinEarthsystemmodels(Terhaaretal.,2022)andindataproducts,herere-latedtoapotentialtemperaturebiasandskineffects(Watsonetal.,2020;Dongetal.,2022,Fig.10).IfSOCEANweretobebasedondataproductsalone,withalldataproductsinclud-ingthisadjustment,thiswouldresultina2012–2021SOCEANof3.8GtCyr−1(Dongetal.,2022)or>4GtCyr−1(Watsonetal.,2020),i.e.outsideoftherangesupportedbytheatmo-sphericinversionsandwithanimpliednegativeBIMofmorethan−1GtCyr−1,indicatingthataclosureofthebudgetcouldonlybeachievedwitheitheranthropogenicemissionsbeingsigniﬁcantlylargerand/orthenetlandsinkbeingsub-stantiallysmallerthanestimatedhere.Moreintegrateduseofobservationsintheglobalcarbonbudget,eitherontheirownEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224847orforfurtherconstrainingmodelresults,shouldhelpresolvesomeofthebudgetimbalance(Petersetal.,2017).4TrackingprogresstowardsmitigationtargetsTheaveragegrowthinglobalfossilCO2emissionspeakedat+3%peryearduringthe2000s,drivenbytherapidgrowthinemissionsinChina.Inthelastdecade,however,theglobalgrowthratehasslowlydeclined,reachingalow+0.5%peryearover2012–2021(includingthe2020globaldeclineandthe2021emissionsrebound).Whilethisslow-downinglobalfossilCO2emissionsgrowthiswelcome,itisfarfromtheemissiondecreaseneededtobeconsistentwiththetemperaturegoalsoftheParisAgreement.Sincethe1990s,theaveragegrowthrateoffossilCO2emissionshascontinuouslydeclinedacrossthegroupofde-velopedcountriesoftheOrganizationforEconomicCo-operationandDevelopment(OECD),withemissionspeak-inginaround2005andnowdecliningataround1%peryear(LeQuéréetal.,2021).Inthedecade2012–2021,territo-rialfossilCO2emissionsdecreasedsigniﬁcantly(atthe95%conﬁdencelevel)in24countrieswhoseeconomiesgrewsig-niﬁcantly(alsoatthe95%conﬁdencelevel):Belgium,Croa-tia,CzechRepublic,Denmark,Estonia,Finland,France,Germany,HongKong,Israel,Italy,Japan,Luxembourg,Malta,Mexico,Netherlands,Norway,Singapore,Slovenia,Sweden,Switzerland,theUnitedKingdom,theUSA,andUruguay(updatedfromLeQuéréetal.,2019).Altogether,these24countriesemitted2.4GtCyr−1(8.8GtCO2yr−1)onaverageoverthelastdecade,aboutaquarterofworldfos-silCO2emissions.Consumption-basedemissionsalsofellsigniﬁcantlyduringtheﬁnaldecadeforwhichestimatesareavailable(2011–2020)in15ofthesecountries:Belgium,Denmark,Estonia,Finland,France,Germany,HongKong,Israel,Japan,Luxembourg,Mexico,Netherlands,Singapore,Sweden,theUnitedKingdom,andUruguay.Figure15showsthattheemissiondeclinesintheUSAandtheEU27arepri-marilydrivenbyincreaseddecarbonization(CO2emissionsperunitenergy)inthelastdecadecomparedtotheprevious,withsmallercontributionsintheEU27fromslightlyweakereconomicgrowthandslightlylargerdeclinesinenergyperGDP.Thesecountrieshavestableordecliningenergyuseandthusdecarbonizationpoliciesreplaceexistingfossilfuelinfrastructure(LeQuéréetal.,2019).Incontrast,fossilCO2emissionscontinuetogrowinnon-OECDcountries,althoughthegrowthratehasslowedfromalmost6%peryearduringthe2000stolessthan2%peryearinthelastdecade.Representing47%ofnon-OECDemissionsin2021,alargepartofthisslowdownisduetoChina,whichhasseenemissionsgrowthdeclinefromnearly10%peryearinthe2000sto1.5%peryearinthelastdecade.ExcludingChina,non-OECDemissionsgrewat3.3%peryearinthe2000scomparedto1.6%peryearinthelastdecade.Figure15showsthat,comparedtothepreviousdecade,Chinahashadweakereconomicgrowthinthelastdecadeandahigherdecarbonizationrate,withmorerapiddeclinesinenergyperGDPthatarenowbacktolevelsseenduringthe1990s.Indiaandtherestoftheworldhavestrongeconomicgrowththatisnotoffsetbydecarbonizationorde-clinesinenergyperGDP,drivingupfossilCO2emissions.Despitethehighdeploymentofrenewablesinsomecountries(e.g.India),fossilenergysourcescontinuetogrowtomeetgrowingenergydemand(LeQuéréetal.,2019).Globally,fossilCO2emissionsgrowthisslowing,andthisisduetotheemergenceofclimatepolicy(EskanderandFankhauser,2020;LeQuereetal.,2019)andtechnologicalchange,whichisleadingtoashiftfromcoaltogas,growthinrenewableenergies,andreducedexpansionofcoalcapac-ity.Attheaggregatedgloballevel,decarbonizationshowsastrongandgrowingsignalinthelastdecade,withsmallercontributionsfromlowereconomicgrowthanddeclinesinenergyperGDP.Despitetheslowinggrowthinglobalfos-silCO2emissions,emissionsarestillgrowing,butthesearefarfromthereductionsneededtomeettheambitiousclimategoalsoftheUNFCCCParisAgreement.WeupdatetheremainingcarbonbudgetassessedbytheIPCCAR6(Canadelletal.,2021),accountingfortheesti-mated2020to2022emissionsfromfossilfuelcombustion(EFOS)andland-usechanges(ELUC).FromJanuary2023,theremainingcarbon(50%likelihood)forlimitingglobalwarmingto1.5,1.7,and2◦Cisestimatedtoamountto105,200,and335GtC(380,730,1230GtCO2).Thesenumbersincludeanuncertaintybasedonmodelspread(asinIPCCAR6),whichisreﬂectedthroughthepercentlikelihoodofexceedingthegiventemperaturethreshold.Theseremainingamountscorrespondrespectivelytoabout9,18,and30yearsfromthebeginningof2023atthe2022leveloftotalCO2emissions.ReachingnetzeroCO2emissionsby2050entailscuttingtotalanthropogenicCO2emissionsbyabout0.4GtC(1.4GtCO2)eachyearonaverage,comparabletothede-creaseobservedin2020duringtheCOVID-19pandemic.5DiscussionEachyearwhentheglobalcarbonbudgetispublished,eachﬂuxcomponentisupdatedforallpreviousyearstoconsidercorrectionsthataretheresultoffurtherscrutinyandveriﬁ-cationoftheunderlyingdataintheprimaryinputdatasets.Annualestimatesmaybeupdatedwithimprovementsindataqualityandtimeliness(e.g.toeliminatetheneedforextrap-olationofforcingdatasuchaslanduse).Ofalltermsintheglobalbudget,onlythefossilCO2emissionsandthegrowthrateinatmosphericCO2concentrationsarebasedprimarilyonempiricalinputssupportingannualestimatesinthiscar-bonbudget.Thecarbonbudgetimbalance,whileanimper-fectmeasure,providesastrongindicationofthelimitationsinobservationsinunderstandingandrepresentingprocesseshttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224848P.Friedlingsteinetal.:GlobalCarbonBudget2022Figure15.KayadecompositionofthemaindriversoffossilCO2emissions,consideringpopulation,GDPperperson,energyperGDP,andCO2emissionsperenergy,forChina(a),theUSA(b),theEU27(c),India(d),therestoftheworld(e),andtheworld(f).BlackdotsaretheannualfossilCO2emissionsgrowthrate,colouredbarsarethecontributionsfromthedifferentdrivers.AgeneraltrendisthatpopulationandGDPgrowthputupwardpressureonemissions,whileenergyperGDPandmorerecentlyCO2emissionsperenergyputdownwardpressureonemissions.BoththeCOVID-19-inducedchangesduring2020andtherecoveryin2021ledtoastarkcontrasttopreviousyears,withdifferentdriversineachregion.inmodelsand/orintheintegrationofthecarbonbudgetcom-ponents.Thepersistentunexplainedvariabilityinthecarbonbudgetimbalancelimitsourabilitytoverifyreportedemissions(Pe-tersetal.,2017)andsuggestswedonotyethaveacompleteunderstandingoftheunderlyingcarboncycledynamicsonannualtodecadaltimescales.Resolvingmostofthisunex-plainedvariabilityshouldbepossiblethroughdifferentandcomplementaryapproaches.First,asintendedwithouran-nualupdates,theimbalanceasanerrortermisreducedbyimprovementsofindividualcomponentsoftheglobalcar-bonbudgetthatfollowfromimprovingtheunderlyingdataandstatisticsandbyimprovingthemodelsthroughthereso-lutionofsomeofthekeyuncertaintiesdetailedinTable10.Second,additionalcluestotheoriginandprocessesrespon-sibleforthevariabilityinthebudgetimbalancecouldbeob-tainedthroughacloserscrutinyofcarbonvariabilityinlightofotherEarthsystemdata(e.g.heatbalance,waterbalance)andtheuseofawiderrangeofbiogeochemicalobservationstobetterunderstandtheland–oceanpartitioningofthecarbonEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224849Table10.Majorknownsourcesofuncertaintiesineachcomponentoftheglobalcarbonbudget,deﬁnedasinputdataorprocessesthathaveademonstratedeffectofatleast±0.3GtCyr−1.SourceofuncertaintyTimescale(years)LocationStatusEvidenceFossilCO2emissions(EFOS;Sect.2.1)Energystatisticsannualtodecadalglobal,butmainlyChinaandmajordevelopingcountriesseeSect.2.1Korsbakkenetal.(2016),Guanetal.(2012)Carboncontentofcoalannualtodecadalglobal,butmainlyChinaandmajordevelopingcountriesseeSect.2.1Liuetal.(2015)SystemboundaryannualtodecadalallcountriesseeSect.2.1Andrew(2020b)Netland-usechangeﬂux(ELUC;Sect.2.2)Landcoverandland-usechangestatisticscontinuousglobal,inparticularthetrop-icsseeSect.2.4Houghtonetal.(2012),Gasseretal.(2020),Ganzenmülleretal.(2022),Yuetal.(2022)Sub-grid-scaletransitionsannualtodecadalglobalseeSect.2.4,TableA1Wilkenskjeldetal.(2014)Vegetationbiomassannualtodecadalglobal,inparticularthetrop-icsseeSect.2.4Houghtonetal.(2012),Bastosetal.(2021)Forestdegradation(ﬁre,selectivelogging)annualtodecadaltropicsseeSect.3.2.2,TableA1Aragãoetal.(2018),Qinetal.(2021)Woodandcropharvestannualtodecadalglobal,particularlySEAsiaseeTableA1Arnethetal.(2017),Erbetal.(2018)Peatburningamulti-decadaltrendglobalseeTableA1vanderWerfetal.(2010,2017)Lossofadditionalsinkcapacitymulti-decadaltrendglobalnotincluded;seeAppendixD4Pongratzetal.(2014),Gasseretal.(2020);Obermeieretal.(2021)Atmosphericgrowthrate(GATM;Sect.2.3):nodemonstrateduncertaintieslargerthan±0.3GtCyr−1bOceansink(SOCEAN;Sect.2.4)SparsityinsurfacefCO2ob-servationsmean,decadalvariabilityandtrendglobal,inparticularSouth-ernHemisphereseeSect.3.5.2Gloegeetal.(2021),Denvil-Sommeretal.(2021),Bushinskyetal.(2019)Riverinecarbonoutgassinganditsanthropogenicperturbationannualtodecadalglobal,inparticularparti-tioningbetweenthetropicsandsouthernextratropicsseeSect.2.4(anthro-pogenicperturbationsnotincluded)Aumontetal.(2001),Resplandyetal.(2018),Lacroixetal.(2020)UnderestimationofinterioroceananthropogeniccarbonstorageannualtodecadalglobalseeSect.3.5.5Friedlingsteinetal.(2021),thisstudy,seealsoTerhaaretal.(2022)Near-surfacetemperatureandsalinitygradientsmeanonalltimescalesglobalseeSect.3.8.2Watsonetal.(2020),Dongetal.(2022)Landsink(SLAND;Sect.2.5)StrengthofCO2fertilizationmulti-decadaltrendglobalseeSect.2.5Wenzeletal.(2016),Walkeretal.(2021)Responsetovariabilityintem-peratureandrainfallannualtodecadalglobal,inparticularthetrop-icsseeSect.2.5Coxetal.(2013);Jungetal.(2017);Humphreyetal.(2018,2021)NutrientlimitationandsupplyannualtodecadalglobalZaehleetal.(2014)CarbonallocationandtissueturnoverratesannualtodecadalglobalDeKauweetal.(2014),O’Sullivanetal.(2022)Treemortalityannualglobal,inparticularthetrop-icsseeSect.2.5Hubauetal.(2020);Brienenetal.(2020)ResponsetodiffuseradiationannualglobalseeSect.2.5Mercadoetal.(2009);O’Sullivanetal.(2021)aAsaresultofinteractionsbetweenlanduseandclimate.bTheuncertaintiesinGATMhavebeenestimatedas±0.2GtCyr−1,althoughtheconversionofthegrowthrateintoaglobalannualﬂuxassuminginstantaneousmixingthroughouttheatmosphereintroducesadditionalerrorsthathavenotyetbeenquantiﬁed.imbalance(e.g.oxygen,carbonisotopes).Finally,additionalinformationcouldalsobeobtainedthroughhigherresolutionandprocessknowledgeattheregionallevelandthroughtheintroductionofinferredﬂuxessuchasthosebasedonsatelliteCO2retrievals.Thelimitoftheresolutionofthecarbonbud-getimbalanceisyetunclear,buthasmostcertainlynotyetbeenreachedgiventhepossibilitiesforimprovementsthatlieahead.EstimatesofglobalfossilCO2emissionsfromdifferentdatasetsareinrelativelygoodagreementwhenthediffer-entsystemboundariesofthesedatasetsareconsidered(An-drew,2020a).ButwhileestimatesofEFOSarederivedfromreportedactivitydatarequiringmuchfewercomplextrans-formationsthansomeothercomponentsofthebudget,uncer-taintiesremain,andonereasonfortheapparentlylowvari-ationbetweendatasetsispreciselytherelianceonthesamehttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224850P.Friedlingsteinetal.:GlobalCarbonBudget2022underlyingreportedenergydata.ThebudgetexcludessomesourcesoffossilCO2emissions,whichavailableevidencesuggestsarerelativelysmall(<1%).Wehaveaddedemis-sionsfromlimeproductioninChinaandtheUS,butthesearestillabsentinmostothernon-AnnexIcountriesandbefore1990inotherAnnexIcountries.EstimatesofELUCsufferfromarangeofintertwinedissues,includingthepoorqualityofhistoricallandcoverandland-usechangemaps,therudimentaryrepresentationofmanagementprocessesinmostmodels,andtheconfusioninmethodologiesandboundaryconditionsusedacrossmeth-ods(e.g.Arnethetal.,2017;Pongratzetal.,2014;Bastosetal.,2021;seealsoAppendixD4onthelossofsinkcapacity).UncertaintiesincurrentandhistoricalcarbonstocksinsoilsandvegetationalsoadduncertaintyintheELUCestimates.Unlessamajorefforttoresolvetheseissuesismade,littleprogressisexpectedintheresolutionofELUC.Thisispar-ticularlyconcerninggiventhegrowingimportanceofELUCforclimatemitigationstrategiesandthelargeissuesinthequantiﬁcationofthecumulativeemissionsoverthehistoricalperiodthatarisefromlargeuncertaintiesinELUC.ByaddingtheDGVMestimatesofCO2ﬂuxesduetoenvi-ronmentalchangefromcountries’managedforestareas(partofSLANDinthisbudget)tothebudgetELUCestimate,wesuccessfullyreconciledthelargegapbetweenourELUCesti-mateandtheland-useﬂuxfromNGHGIsusingtheapproachdescribedinGrassietal.(2021)forafuturescenarioandinGrassietal.(2022b)usingdatafromtheGlobalCarbonBudget2021.Theupdateddatapresentedherecanbeusedaspotentialadjustmentinthepolicycontext,e.g.tohelpas-sessingthecollectivecountries’progresstowardsthegoaloftheParisAgreementandavoidingdoubleaccountingofthesinkinmanagedforests.Intheabsenceofthisadjust-ment,collectiveprogresswouldhenceappearbetterthanitis(Grassietal.,2021).TheneedofsuchadjustmentwheneveracomparisonbetweenLULUCFﬂuxesreportedbycountriesandtheglobalemissionestimatesoftheIPCCisattemptedisrecommendedalsointherecentUNFCCCSynthesisreportfortheﬁrstGlobalStocktake(UNFCCC,2022).However,thisadjustmentshouldbeseenasashort-termandpragmaticﬁxbasedonexistingdata,ratherthanadeﬁnitivesolutiontobridgethedifferencesbetweenglobalmodelsandnationalinventories.Additionalstepsareneededtounderstandandreconciletheremainingdifferences,someofwhicharerele-vantatthecountrylevel(Grassietal.,2022b;Schwingshackletal.,2022).ThecomparisonofGOBMs,dataproducts,andinversionshighlightsasubstantialdiscrepancyintheSouthernOcean(Fig.13,Haucketal.,2020).Alargepartoftheuncertaintyinthemeanﬂuxesstemsfromtheregionaldistributionoftheriverﬂuxadjustmentterm.Thecurrentdistribution(Au-montetal.,2001)isbasedononemodelstudyyieldingthelargestriverineoutgassingﬂuxsouthof20◦S,whereasare-centstudy,alsobasedononemodel,simulatesthelargestshareoftheoutgassingtooccurinthetropics(Lacroixetal.,2020).Thelong-standingsparsedatacoverageoffCO2observationsintheSouthernHemispherecomparedtotheNorthernHemisphere(e.g.Takahashietal.,2009)contin-uestoexist(Bakkeretal.,2016,2022,Fig.B1)andtoleadtosubstantiallyhigheruncertaintyintheSOCEANestimatefortheSouthernHemisphere(Watsonetal.,2020;Gloegeetal.,2021).Thisdiscrepancy,whichalsohampersmodelimprovement,pointstotheneedforincreasedhigh-qualityfCO2observations,especiallyintheSouthernOcean.Atthesametime,modeluncertaintyisillustratedbythelargespreadofindividualGOBMestimates(indicatedbyshadinginFig.13)andhighlightstheneedformodelimprovement.ThedivergingtrendsinSOCEANfromdifferentmethodsisamatterofconcern,whichisunresolved.Theassessmentofthenetland–atmosphereexchangefromDGVMsandatmo-sphericinversionsalsoshowssubstantialdiscrepancy,partic-ularlyfortheestimateofthetotallandﬂuxoverthenorth-ernextratropics.Thisdiscrepancyhighlightsthedifﬁcultytoquantifycomplexprocesses(CO2fertilization,nitrogende-positionandfertilizers,climatechangeandvariability,landmanagement,etc.)thatcollectivelydeterminethenetlandCO2ﬂux.ResolvingthedifferencesintheNorthernHemi-spherelandsinkwillrequiretheconsiderationandinclusionoflargervolumesofobservations.Weprovidemetricsfortheevaluationoftheoceanandlandmodelsandtheatmosphericinversions(Figs.B2toB4).Thesemetricsexpandtheuseofobservationsintheglobalcarbonbudget,helping(1)tosupportimprovementsintheoceanandlandcarbonmodelsthatproducethesinkestimatesand(2)toconstraintherepresentationofkeyunderlyingpro-cessesinthemodelsandallocatetheregionalpartitioningoftheCO2ﬂuxes.However,GOBMsskillshavechangedlit-tlesincetheintroductionoftheoceanmodelevaluation.Theadditionalsimulationallowsfordirectcomparisonwithinte-rioroceananthropogeniccarbonestimatesandsuggeststhatthemodelsunderestimateanthropogeniccarbonuptakeandstorage.Thisisaninitialsteptowardstheintroductionofabroaderrangeofobservationsthatwehopewillsupportcon-tinuedimprovementsintheannualestimatesoftheglobalcarbonbudget.Weassessedbeforethatasustaineddecreaseof−1%inglobalemissionscouldbedetectedatthe66%likelihoodlevelafteradecadeonly(Petersetal.,2017).Similarly,achangeinbehaviourofthelandand/oroceancarbonsinkwouldtakeaslongtodetectandmuchlongerifitemergesmoreslowly.Continuingwithreducingthecarbonimbal-anceonannualtodecadaltimescales,regionalizingthecar-bonbudget,andintegratingmultiplevariablesarepowerfulwaystoshortenthedetectionlimitandensuretheresearchcommunitycanrapidlyidentifyissuesofconcernintheevo-lutionoftheglobalcarboncycleunderthecurrentrapidandunprecedentedchangingenvironmentalconditions.EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget202248516ConclusionsTheestimationofglobalCO2emissionsandsinksisamajoreffortbythecarboncycleresearchcommunitythatrequiresacarefulcompilationandsynthesisofmeasurements,statis-ticalestimates,andmodelresults.Thedeliveryofanannualcarbonbudgetservestwopurposes.First,thereisalargede-mandforup-to-dateinformationonthestateoftheanthro-pogenicperturbationoftheclimatesystemanditsunderpin-ningcauses.Abroadstakeholdercommunityreliesonthedatasetsassociatedwiththeannualcarbonbudgetincludingscientists,policymakers,businesses,journalists,andnon-governmentalorganizationsengagedinadaptingtoandmit-igatinghuman-drivenclimatechange.Second,overthelastdecadeswehaveseenunprecedentedchangesinthehumanandbiophysicalenvironments(e.g.changesinthegrowthoffossilfuelemissions,impactsoftheCOVID-19pandemic,Earth’swarming,andstrengthofthecarbonsinks),whichcallforfrequentassessmentsofthestateoftheplanet,abet-terquantiﬁcationofthecausesofchangesinthecontempo-raryglobalcarboncycle,andanimprovedcapacitytoan-ticipateitsevolutioninthefuture.Buildingthisscientiﬁcunderstandingtomeettheextraordinaryclimatemitigationchallengerequiresfrequent,robust,transparent,andtrace-abledatasetsandmethodsthatcanbescrutinizedandrepli-cated.Thispaper,via“livingdata”,helpstokeeptrackofnewbudgetupdates.7DataavailabilityThedatapresentedherearemadeavailableinthebeliefthattheirwidedisseminationwillleadtogreaterunderstandingandnewscientiﬁcinsightsofhowthecarboncycleworks,howhumansarealteringit,andhowwecanmitigatetheresultinghuman-drivenclimatechange.FullcontactdetailsandinformationonhowtocitethedatashownherearegivenatthetopofeachpageintheaccompanyingdatabaseandsummarizedinTable2.TheaccompanyingdatabaseincludesthreeExcelﬁlesor-ganizedintothefollowingspreadsheets.TheﬁleGlobal_Carbon_Budget_2022v0.1.xlsxincludesthefollowingitems:1.summary;2.theglobalcarbonbudget(1959–2021);3.thehistoricalglobalcarbonbudget(1750–2021);4.globalCO2emissionsfromfossilfuelsandcementpro-ductionbyfueltypeandthepercapitaemissions(1850–2021);5.CO2emissionsfromland-usechangefromtheindivid-ualbookkeepingmodels(1959–2021);6.oceanCO2sinkfromtheindividualoceanmodelsandfCO2-basedproducts(1959–2021);7.terrestrialCO2sinkfromtheindividualDGVMs(1959–2021);8.cementcarbonationCO2sink(1959–2021).TheﬁleNational_Fossil_Carbon_Emissions_2022v0.1.xlsxincludesthefollowingitems:1.summary;2.territorialcountryCO2emissionsfromfossilfuelsandcementproduction(1850–2021);3.consumptioncountryCO2emissionsfromfossilfuelsandcementproductionandemissionstransferfromtheinternationaltradeofgoodsandservices(1990–2020)usingCDIAC/UNFCCCdataasreference;4.emissionstransfers(consumptionminusterritorialemissions;1990–2020);5.countrydeﬁnitions.TheﬁleNational_LandUseChange_Carbon_Emissions_2022v0.1xlsxincludesthefollowingitems:1.summary2.territorialcountryCO2emissionsfromland-usechange(1850–2021)fromthreebookkeepingmodels;AllthreespreadsheetsarepublishedbytheIntegratedCar-bonObservationSystem(ICOS)CarbonPortalandareavail-ableathttps://doi.org/10.18160/GCP-2022(Friedlingsteinetal.,2022b).NationalemissionsdataarealsoavailablefromtheGlobalCarbonAtlas(http://www.globalcarbonatlas.org/,lastaccess:25September2022)andfromOurWorldinData(https://ourworldindata.org/co2-emissions,lastaccess:25September2022).https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224852P.Friedlingsteinetal.:GlobalCarbonBudget2022AppendixA:SupplementarytablesTableA1.ComparisonoftheprocessesincludedinthebookkeepingmethodandDGVMsintheirestimatesofELUCandSLAND.SeeTable4formodelreferences.Allmodelsincludedeforestationandforestregrowthafterabandonmentofagriculture(orfromafforestationactivitiesonagriculturalland).ProcessesrelevantforELUCareonlydescribedfortheDGVMsusedwithland-coverchangeinthisstudy.Hereweusetheterm“DGVM”inthebroadestsenseintermsofglobalvegetationmodelswhichareabletodynamicallyadjusttoimposedlanduseandland-usechange(LULCC).BookkeepingmodelsDGVMsH&NBLUEOSCARCABLE-POPCLASSICCLM5.0DLEMIBISISAMJSBACHJULES-ESLPJ-GUESSLPJLPX-BernOCNv2ORCHIDEEv3SDGVMVISITYIBsProcessesrelevantforELUCWoodharvestandforestdegradationayesyesyesyesnoyesyesyesyesyesnoyesyesnodyesyesnoyesnoShiftingcultivation/subgridscaletransitionsyesbyesyesyesnoyesnoyesnoyesnoyesyesnodnononoyesnoCroplandharvest(re-moved,R,oraddedtolitter,L)yes(R)jyes(R)jyes(R)yes(R)yes(L)yes(R)yesyes(R)yesyes(R+L)yes(R)yes(R)yes(L)yes(R)yes(R+L)yes(R)yes(R)yes(R)yes(L)PeatﬁresyesyesyesnonoyesnononononononononononononoFireasamanagementtoolyesjyesjyeshnonononononononononononononononoNfertilizationyesjyesjyeshnonoyesyesnoyesnoyesiyesnoyesyesyesnononoTillageyesjyesjyeshnoyesgnonononononoyesnononoyesgnononoIrrigationyesjyesjyeshnonoyesyesnoyesnonoyesnononononononoWetlanddrainageyesjyesjyeshnononononoyesnonononononononononoErosionyesjyesjyeshnononoyesnonononononononononoyesnoPeatdrainageyesyesyesnonononononononononononononononoGrazingandmowingHarvest(removed,r,oraddedtolitter,l)yes(r)jyes(r)jyes(r)yes(r)nonononoyes(r,l)yes(l)noyes(r)yes(l)noyes(r+l)nonononoProcessesalsorelevantforSLAND(inadditiontoCO2fertilizationandclimate)Firesimulationand/orsuppressionn/an/an/anoyesyesnoyesnoyesyesyesyesyesnonoyesyesnoCarbon–nitrogenin-teractions,includingNdepositionn/an/an/ayesnofyesyesnoyesyesyesyesnoyesyesyesyescnonofSeparatetreatmentofdirectanddiffuseso-larradiationn/an/an/ayesnoyesnonononoyesnononononononoyesEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224853TableA2.Comparisonoftheprocessesandmodelset-upfortheGlobalOceanBiogeochemistryModelsfortheirestimatesofSOCEAN.SeeTable4formodelreferences.NEMO-PlankTOM12NEMO-PISCES(IPSL)MICOM-HAMOCC(NorESM1-OCv1.2)MPIOM-HAMOCC6FESOM-2.1-REcoM2NEMO3.6-PISCESv2-gas(CNRM)MOM6-COBALT(Princeton)CESM-ETHZMRI-ESM2-1CESM2ModelspeciﬁcsPhysicaloceanmodelNEMOv3.6-ORCA2NEMOv3.6-eORCA1L75MICOM(NorESM1-OCv1.2)MPIOMFESOM-2.1NEMOv3.6-GELATOv6-eORCA1L75MOM6-SIS2CESMv1.3(oceanmodelbasedonPOP2)MRI.COMv4CESM2-POP2BiogeochemistrymodelPlankTOM12PISCESv2HAMOCC(NorESM1-OCv1.2)HAMOCC6REcoM-2-MPISCESv2-gasCOBALTv2BEC(modiﬁed&extended)NPZDMARBLHorizontalresolution2◦long,0.3to1.5◦lat1◦long,0.3to1◦lat1◦long,0.17to0.25lat1.5◦unstructuredmesh,20–120kmresolution(COREmesh)1◦long,0.3to1◦lat0.5◦long,0.25to0.5◦lat1.125◦long,0.53◦to0.27◦lat1◦long,0.3to0.5◦lat1.125◦long,0.53◦to0.27◦latVerticalresolution31levels75levels,1matthesur-face51isopycniclayers+2layersrepresentingabulkmixedlayer40levels46levels,10mspacinginthetop100m75levels,1matsurface75levelshybridcoordi-nates,2matsurface60levels60levelswith1levelofbottomboundarylayer60levelsTotaloceanareaonna-tivegrid(km2)3.6080E+083.6270E+083.6006E+083.6598E+083.6435E+083.6270E+143.6111E+083.5926E+083.6141E+083.61E+08Gasexchangeparame-terizationWanninkhof(1992)Orretal.(2017)Orretal.(2017),butwitha=0.337Orretal.(2017)Orretal.(2017)Orretal.(2017)Orretal.(2017)Wanninkhof(1992,co-efﬁcientascaleddownto0.31)Orretal.(2017)Orretal.(2017)CO2chemistryroutinesfollowingBroecker(1982)mocsyfollowingDicksonetal.(2007)Ilyinaetal.(2013)adaptedtocomplywithOMIPprotocol(Orretal.,2017)mocsymocsymocsyOCMIP2(Orretal.,2017)mocsyOCMIP2(Orretal.,2017)Riverinput(PgCyr−1)(organic/inorganicDIC)0.723/–0.61/–00.77/–0/0∼0.611/–∼0.07/∼0.150.33/–0/00.173/0.263Netﬂuxtosediment(PgCyr−1)(organic/other)0.723/–0.59/–around0.54/––/0.440/0∼0.656/–∼0.11/∼0.07(CaCO3)0.21/–0/00.345/0.110(CaCO3)Spin-upprocedureInitializationofcarbonchemistryGLODAPv1(pre-industrialDIC)GLODAPv2(pre-industrialDIC)GLODAPv1(pre-industrialDIC)initializationfrompre-vioussimulationGLODAPv2(pre-industrialDIC)GLODAPv2GLODAPv2(alka-linity,DIC).DICcorrectedto1959level(simulationAandC)andtopre-industriallevel(simulationBandD)usingKhatiwalaetal.(2009)GLODAPv2(pre-industrialDIC)GLODAPv2(pre-industrialDIC)GLODAPv2(pre-industrialDIC)Pre-industrialspin-uppriorto1850spin-up1750–1947spin-upstartingin1836with3loopsofJRA551000yearspin-up∼2000years189yearslongspin-up(>1000years)OtherbiogeochemicaltracersinitializedfromaGFDL-ESM2Mspin-up(>1000years)spin-up1655–18491661yearswithxCO2=284.32spin-up1653–1850,xCO2=278AtmosphericforcingﬁeldsandCO2Atmosphericforcingfor(i)pre-industrialspin-up,(ii)spin-up1850–1958forsimula-tionB,(iii)simulationBloopingNCEPyear1990(i,ii,iii)loopingfullJRA55re-analysisCORE-I(normal-year)forcing(i,ii,iii)OMIPclimatology(i),NCEPyear1957(ii,iii)JRA55-dov.1.5.0repeated-year1961(i,ii,iii)JRA55-do-v1.5.0fullreanalysis(i)cycling-year1958(ii,iii)GFDL-ESM2Min-ternalforcing(i),JRA55-do-v1.5.0repeat-year1959(ii,iii)COREv2until1835,from1835-1850:JRA(i),normal-yearforcingcreatedfromJRA55-doversion1.3(ii,iii)JRA55-dov1.5.0repeat-year1990/91(i,ii,iii)(i)repeatingJRA1958–2018forspin-upforA&D,repeat-ingJRA1990/1991repeat-yearforcingforspin-upforB&C,(ii)&(iii)JRA1990/1991repeat-yearforcingAtmosphericCO2forcontrolspin-up1850–1958forsimulationB,andforsimulationBconstant278ppm,convertedtopCO2temperatureformula-tion(Sarmientoetal.,1992)xCO2of286.46ppm,convertedtopCO2withconstantsea-levelpressureandwater-vapourpressurexCO2of278ppm,con-vertedtopCO2withsea-levelpressureandwater-vapourpressurexCO2of278ppm,noconversiontopCO2xCO2of278ppm,con-vertedtopCO2withsea-levelpressureandwater-vapourpressurexCO2of286.46ppm,convertedtopCO2withconstantsea-levelpressureandwater-vapourpressurexCO2of278ppm,con-vertedtopCO2withsea-levelpressureandwater-vapourpressurexCO2of287.4ppm,convertedtopCO2withatmosphericpres-sure,andwater-vapourpressurexCO2of284.32ppm(CMIP6piControl),convertedtopCO2withwater-vapourandsea-levelpressure(JRA55-dorepeat-year1990/91)xCO2of278ppmAtmosphericforcingforhistoricalspin-up1850–1958forsim-ulationA(i)andforsimulationA(ii)1750–1947:loopingNCEPyear1990;1948–2021:NCEP1836–1958:loopingfullJRA55reanalysis(i),JRA55-do-v1.4then1.5for2020–2021(ii)CORE-I(normal-year)forcing;from1948on-wards:NCEP-R1withCORE-IIcorrectionsNCEP6-hourlycyclicforcing(10yearsstartingfrom1948,i);1948–2021:transientNCEPforcingJRA55-do-v1.5.0repeated-year1961(i),transientJRA55-do-v1.5.0(ii)JRA55-docycling-year1958(i),JRA55-do-v1.5.0(ii)JRA55-do-v1.5repeat-year1959(i),v1.5.0(1959-2019),v1.5.0.1b(2020),v1.5.0.1(2021;ii)JRA55version1.3,repeatcyclebetween1958and2018(i),v1.3(1959–2018),v.1.5.0.1(2020–2021)1653-1957:repeatedcycleJRA55-dov1.5.01958–2018(i),v1.5.0(1958–2018),v1.5.0.1(2019–2021;ii)(i)repeatingJRA1958–2018,(ii)JRA1958–2021AtmosphericCO2forhistoricalspin-up1850–1958forsimulationA(i)andsimulationA(ii)xCO2providedbytheGCB;convertedtopCO2temperatureformulation(Sarmientoetal.,1992),monthlyresolution(i,ii)xCO2asprovidedbytheGCB,globalmean,annualresolution,con-vertedtopCO2withsea-levelpressureandwater-vapourpressure(i,ii)xCO2asprovidedbytheGCB,convertedtopCO2withsea-levelpressure(takenfromtheatmosphericforc-ing)andwater-vapourcorrection(i,ii)transientmonthlyxCO2providedbyGCB,noconversion(i,ii)xCO2asprovidedbytheGCB,convertedtopCO2withsea-levelpressureandwater-vapourpressure,globalmean,andmonthlyresolution(i,ii)xCO2asprovidedbytheGCB,convertedtopCO2withconstantsea-levelpressureandwater-vapourpressure,globalmean,andyearlyresolution(i,ii)xCO2atyear1959level(315ppm,i)andasprovidedbyGCB(ii),bothconvertedtopCO2withsea-levelpressureandwater-vapourpressure,globalmean,andyearlyresolutionxCO2asprovidedbytheGCB,convertedtopCO2withlocallyde-terminedatm.pressureandwater-vapourpres-sure(i,ii)xCO2asprovidedforCMIP6historicalsimulations,froman-nualresolution(i)andasprovidedbyGCB(ii),bothconvertedtopCO2withwater-vapourandsea-levelpressureannualglobalxCO2providedbyGCB,convertedtoequi-libriumCO2usingatmosphericpressureandWeissandPrice(1980)https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224854P.Friedlingsteinetal.:GlobalCarbonBudget2022TableA3.DescriptionofoceandataproductsusedforassessmentofSOCEAN.SeeTable4forreferences.Jena-MLSMPI-SOMFFNCMEMS-LSCE-FFNNWatsonetalNIES-NNJMA-MLROS-ETHZ-GRaCERLDEOHPDMethodSpatio-temporalin-terpolation(versionoc_v2022).Spatio-temporalﬁeldofocean-internalcarbonsourcesandsinksisﬁttotheSOCATv2022pCO2data.Includesamulti-linearregressionagainstenvironmentaldriverstobridgedatagaps.Afeed-forwardneuralnetwork(FFN)deter-minesthenon-linearrelationshipbetweenSOCATpCO2measure-mentsandenvironmentalpredictordatafor16biogeochemicalprovinces(deﬁnedthroughaself-organizingmap,SOM)andisusedtoﬁlltheexistingdatagaps.Anensembleofneuralnetworkmodelstrainedon100subsampleddatasetsfromSOCATandenvironmentalpredictors.ThemodelsareusedtoreconstructseasurfacefugacityofCO2andconverttoair–seaCO2ﬂuxes.ModiﬁedMPI-SOMFFNwithSOCATv2022pCO2database.Correctedtothesub-skintemperatureoftheoceanasmeasuredbysatellite(Goddijn-Murphyetal.,2015).Fluxcalculationcorrectedforthecoolandsaltysurfaceskin.MonthlyclimatologyforskintemperaturecorrectionderivedfromESACCIproductfortheperiod2003to2011(Merchantetal.,2019).Afeed-forwardneuralnetworkmodeltrainedonSOCAT2021fCO2andenvironmentalpre-dictordata.ThefCO2wasnormalizedtothereferenceyear2000byaglobalfCO2trend.WeﬁttedthedependenceoffCO2onyearbylinearregression.WesubtractedthetrendfromfCO2andusedtheneuralnetworktomodelthenon-lineardependenceoftheresid-ualonpredictors.ThetrendwasaddedtomodelpredictionstoreconstructfCO2.Fieldsoftotalalkalinity(TA)wereestimatedbyusingamultiplelin-earregression(MLR)methodbasedonGLO-DAPv2.2021andsatelliteobservationdata.SOCATv2022fCO2datawereconvertedtodis-solvedinorganiccarbon(DIC)withtheTA.FieldsofDICwereestimatedbyusingaMLRmethodbasedontheDICandsatelliteobservationdata.Geospatialrandomclus-terensembleregressionisatwo-stepcluster-regressionapproach,wheremultipleclusteringinstanceswithslightvari-ationsareruntocreateanensembleofestimates.WeuseK-meanscluster-ingandacombinationofgradient-boostedtreesandfeed-forwardneuralnetworkstoestimateSOCATv2022fCO2.BasedonfCO2misﬁtbetweenobservedfCO2andeightoftheoceanbio-geochemicalmodelsusedinthisassessment.Theextremegradientboost-ingmethodlinksthismis-ﬁttoenvironmentalob-servationstoreconstructthemodelmisﬁtacrossallspaceandtime,whichisthenaddedbacktomodel-basedfCO2esti-mate.Theﬁnalrecon-structionofsurfacefCO2istheaverageacrosstheeightreconstructions.Gasexchangepa-rameterizationWanninkhof(1992);transfercoefﬁcientkscaledtomatchaglobalmeantransferrateof16.5cmh−1byNae-gler(2009)Wanninkhof(1992);transfercoefﬁcientkscaledtomatchaglobalmeantransferrateof16.5cmh−1Wanninkhof(2014);transfercoefﬁcientkscaledtomatchaglobalmeantransferrateof16.5cmh−1(Naegler,2009)Nightingaleetal.(2000)Wanninkhof(2014);transfercoefﬁcientkscaledtomatchaglobalmeantransferrateof16.5cmh−1(Naegler,2009)Wanninkhof(2014);transfercoefﬁcientkscaledtomatchaglobalmeantransferrateof16.5cmh−1(Naegler,2009).Wanninkhof(1992);averagedandscaledforthreereanalysiswinddatasetstoaglobalmean16.5cmh−1(afterNae-gler,2009;Fayetal.,2021)Wanninkhof(1992);averagedandscaledforthreereanalysiswinddatasetstoaglobalmean16.5cmh−1(afterNae-gler,2009;Fayetal.,2021)WindproductJMA55-doreanalysisERA5ERA5Meanandmeansquarewindmonthlyat1×1◦fromCCMP,0.25×0.25◦×6-hourlydata,ERA5JRA55JRA55,ERA5,NCEP1JRA55,ERA5,CCMP2Spatialresolution2.5◦longitude×2◦latitude1×1◦1×1◦1×1◦1×1◦1×1◦1×1◦1×1◦TemporalresolutiondailymonthlymonthlymonthlymonthlymonthlymonthlymonthlyAtmosphericCO2Spatiallyandtemporallyvaryingﬁeldbasedonat-mosphericCO2datafrom169stations(JenaCarbo-Scopeatmosphericinver-sionsEXTALL_v2021).Spatiallyvarying1×1◦atmosphericpCO2_wetcalculatedfromtheNOAAGMDmarineboundarylayerxCO2andNCEPsea-levelpres-surewiththemoisturecorrectionbyDicksonetal.(2007).Spatiallyandmonthlyvaryingﬁeldsofatmo-sphericpCO2computedfromCO2molefraction(CO2atmosphericinver-sionfromtheCopernicusAtmosphereMonitoringService)andatmosphericdry-airpressure,whichisderivedfrommonthlysurfacepressure(ERA5)andwater-vapourpres-sureﬁttedbyWeissandPrice(1980).AtmosphericpCO2(wet)calculatedfromNOAAmarineboundarylayerXCO2andNCEPsea-levelpressure,withpH2OcalculatedfromCooperetal.(1998).The2021XCO2marineboundaryvalueswerenotavailableatsubmissionsoweusedpreliminaryvalues,esti-matedfrom2020valuesandtheincreaseatMaunaLoa.NOAAGreenhouseGasMarineBound-aryLayerReference,whichcanbeaccessedathttps://gml.noaa.gov/ccgg/mbl/mbl.html(lastaccess:25September2022).AtmosphericxCO2ﬁeldsoftheJMA-GSAMinver-sionmodel(Makietal.,2010;Nakamuraetal.,2015)wereused.TheywereconvertedtopCO2byusingJRA55sea-levelpressure.The2021xCO2ﬁeldswerenotavailableatthisstage,andweusedglobalxCO2incrementsfrom2020to2021.NOAA’smarineboundarylayerproductforxCO2islinearlyinterpolatedontoa1×1◦gridandre-sampledfromweeklytomonthly.xCO2ismul-tipliedbyERA5meansea-levelpressure,wherethelattercorrectedforwater-vapourpressureus-ingDicksonetal.(2007).Thisresultsaregiveninmonthly1×1◦pCO2atm.NOAA’smarineboundarylayerproductforxCO2islinearlyinterpolatedontoa1×1◦gridandre-sampledfromweeklytomonthly.xCO2ismul-tipliedbyERA5meansea-levelpressure,wherethelattercorrectedforwater-vapourpressureus-ingDicksonetal.(2007).Thisresultsaregiveninmonthly1×1◦pCO2atm.Totaloceanareaonnativegrid(km2)3.63E+083.63E+083.50E+083.52E+083.49E+083.10E+08(2.98E+08to3.16E+08,dependingonicecover)3.55E+083.61E+08methodtoextendproducttofullglobaloceancoverageArcticandmarginalseasaddedfollowingLand-schützeretal.(2020).Nocoastalcut.Fayetal.(2021)Methodhasnear-fullcov-erage.Fayetal.(2021)wasused,andgapswereﬁlledwithmonthlyclimatology.In-terannualvariabilitywasaddedtotheclimatologybasedonthetemporalevolutionofﬁveproductsfortheyears1985through2020andthenonlyusingthisproductfortheyear2021.EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224855TableA4.Comparisonoftheinversionset-upandinputﬁeldsfortheatmosphericinversions.AtmosphericinversionsseethefullCO2ﬂuxes,includingtheanthropogenicandpre-industrialﬂuxes.Hence,theyneedtobeadjustedforthepre-industrialﬂuxofCO2fromthelandtotheoceanthatispartofthenaturalcarboncyclebeforetheycanbecomparedwithSOCEANandSLANDfromprocessmodels.SeeTable4forreferences.CopernicusAtmosphereMonitor-ingService(CAMS)Carbon-TrackerEurope(CTE)JenaCarboScopeUoENISMON-CO2CMS-FluxGONGGATHUCopernicusAtmosphereMonitor-ingService(CAMS)SatelliteVersionnumberv21r1v2022v2022UoEv6.1bv2022.1v2022v2022v2022FT21r2ObservationsAtmosphericobservationsHourlyresolution(well-mixedconditions)obspackGLOBALVIEWplusv7.0aandNRT_v7.2b,WDCGG,RAMCES,andICOSATCHourlyresolution(well-mixedconditions)obspackGLOBALVIEWplusv7.0aandNRT_v7.2bFlasksandhourlyresolutionfromvariousinstitutions(outliersremovedby2σcriterion)Hourlyresolution(well-mixedconditions)obspackGLOBALVIEWplusv7.0aandNRT_v7.2bHourlyresolution(well-mixedconditions)obspackGLOBALVIEWplusv7.0aandNRT_v7.2bACOS-GOSATv9r;OCO-2v10scaledtoWMO2019standard;andremoteﬂaskobservationsfromObsPack,GLOB-ALVIEWplus,v7.0a,andNRT_v7.2bOCO-2v10rdatascaledtotheWMO2019standardOCO-2v10rdatascaledtotheWMO2019standardBias-correctedACOSGOSATv9overlanduntilAugust2024plusbias-correctedACOSOCO-2v10overland,withbothrescaledtoX2019Periodcovered1979–20212001–20211957–20212001–20211990–20212010–20212015–20212015–20212010–2021PriorﬂuxesBiosphereandﬁresORCHIDEE,GFEDv4.1sSiB4andGFASZeroCASAv1.0,climatol-ogyafter2016andGFED4.0VISITandGFEDv4.1sCARDAMOMCASAandGFEDv4.1sSiB4.2andGFEDv4.1sORCHIDEE,GFEDv4.1sOceanCMEMS-LSCE-FFNN2021CarboScopev2021CarboScopev2022TakahashiclimatologyJMAglobaloceanmapping(Iidaetal.,2015)MOM6TakahashiclimatologyTakahashiclimatologyCMEMS-LSCE-FFNN2021FossilfuelsGridFED2021.2cwithanextrapolationto2021basedonCar-bonmonitorandNO2GridFED2021.3+GridFED2022.2for2021cGridFEDv2022.2cGridFED2022.1cGridFEDv2022.2cGridFED2022.2cGridFED2021.3cwithanextrapolationto2021basedonCarbon-monitorGridFEDv2022.1cGridFED2021.2cwithanextrapolationto2021basedonCar-bonmonitorandNO2TransportandoptimizationTransportmodelLMDZv6TM5TM3GEOS-CHEMNICAM-TMGEOS-CHEMGEOS-Chemv12.9.3GEOS-CHEMLMDZv6WeatherforcingECMWFECMWFNCEPMERRAJRA55MERRAMERRA2GEOS-FPECMWFHorizontalresolutionGlobal3.75◦×1.875◦Global3◦×2◦,Eu-rope1◦×1◦,NorthAmerica1◦×1◦Global3.83◦×5◦Global4◦×5◦Isosahedralgrid∼225kmGlobal4◦×5◦Global2◦×2.5◦Global4◦×5◦Global3.75◦×1.875◦OptimizationVariationalEnsembleKalmanﬁl-terConjugategradient(re-ortho-normalization)dEnsembleKalmanﬁl-terVariationalVariationalNon-linearleastsquaresfour-dimensionalvariation(NLS-4DVar)EnsembleKalmanﬁlterVariationalahttps://doi.org/10.25925/20210801(Schuldtetal.,2021).bhttps://doi.org/10.25925/20220624(Schuldtetal.,2022).cGCP-GridFEDv2021.2,v2021.3,v2022.1,andv2022.2(Jonesetal.,2022)areupdatesthroughtheyear2021oftheGCP-GridFEDdatasetpresentedbyJonesetal.(2021).dOceanpriorisnotoptimized.https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224856P.Friedlingsteinetal.:GlobalCarbonBudget2022TableA5.AttributionoffCO2measurementsfortheyear2021includedinSOCATv2022(Bakkeretal.,2016,2022)toinformoceanfCO2-baseddataproducts.PlatformnameRegionsNo.ofPrincipalinvestigatorsNo.ofPlatformmeasurementsdatasetstype1degreeNorthAtlantic,coastal71863Tanhua,T.1ShipAlawai_158W_21NTropicalPaciﬁc387Sutton,A.;DeCarlo,E.H.;Sabine,C.1MooringAtlanticExplorerNorthAtlantic,tropicalAtlantic,coastal34399Bates,N.R.16ShipAtlanticSailNorthAtlantic,coastal27496Steinhoff,T.;Körtzinger,A.7ShipBlueFinTropicalPaciﬁc60606Alin,S.R.;Feely,R.A.11ShipCapSanLorenzoNorthAtlantic,tropicalAtlantic,coastal44281Lefèvre,N.7ShipCCE2_121W_34NCoastal1333Sutton,A.;Send,U.;Ohman,M.1MooringCelticExplorerNorthAtlantic,coastal61118Cronin,M.10ShipF.G.WaltonSmithCoastal38375Rodriguez,C.;Millero,F.J.;Pierrot,D.;Wanninkhof,R.14ShipFinnmaidCoastal223438Rehder,G.;Bittig,H.C.;Glockzin,M.1ShipFRA56Coastal5652Tanhua,T.1ShipG.O.SarsArctic,NorthAtlantic,coastal82607Skjelvan,I.9ShipGAKOA_149W_60NCoastal402Monacci,N.;Cross,J.;Musielewicz,S.;Sutton,A.1MooringGordonGunterNorthAtlantic,coastal36058Wanninkhof,R.;Pierrot,D.6ShipGulfChallengerCoastal6375Salisbury,J.;Vandemark,D.;Hunt,C.W.6ShipHealyArctic,NorthAtlantic,coastal28998Sweeney,C.;Newberger,T.;Sutherland,S.C.;Munro,D.R.5ShipHenryB.BigelowNorthAtlantic,coastal67399Wanninkhof,R.;Pierrot,D.8ShipHeronIslandCoastal989Tilbrook,B.;Neill,C.;vanOo-jen,E.;Passmore,A.;Black,J.1MooringInvestigatorSouthernOcean,coastal,tropicalPaciﬁc,In-dianOcean120782Tilbrook,B.;Akl,J.;Neill,C.6ShipKC_BUOYCoastal2860Evans,W.;Pocock,K.1MooringKeifuMaruIINorthPaciﬁc,tropicalPaciﬁc,coastal10053Kadono,K.8ShipLaurenceM.GouldSouthernOcean2604Sweeney,C.;Newberger,T.;Sutherland,S.C.;Munro,D.R.1ShipMarionDufresneIndianOcean,SouthernOcean,coastal9911LoMonaco,C.;Metzl,N.1ShipNathanielB.PalmerSouthernOcean2376Sweeney,C.;Newberger,T.;Sutherland,S.C.;Munro,D.R.1ShipNewCentury2NorthPaciﬁc,tropicalPaciﬁc,NorthAtlantic,coastal198293Nakaoka,S.-I.;Takao,S.10ShipNewrest–ArtandFenetresNorthAtlantic,tropicalAtlantic,SouthAt-lantic,coastal17699Tanhua,T.2ShipQuadraIslandFieldStationCoastal81201Evans,W.;Pocock,K.1MooringRonaldH.BrownNorthAtlantic,coastal31661Wanninkhof,R.;Pierrot,D.3ShipRyofuMaruIIINorthPaciﬁc,tropicalPaciﬁc,coastal10464Kadono,K.8ShipSeaExplorerSouthernOcean,NorthAtlantic,coastal,trop-icalAtlantic37027Landshützer,P.;Tanhua,T.2ShipSikuliaqArctic,NorthPaciﬁc,coastal60549Sweeney,C.;Newberger,T.;Sutherland,S.C.;Munro,D.R.13ShipSimonStevinCoastal57055Gkritzalis,T.;Theetaert,H.;Cat-trijsse,A.;T’Jampens,M.11ShipSitkaTribeofAlaskaEnvironmentalResearchLaboratoryCoastal19086Whitehead,C.;Evans,W.;Lan-phier,K.;Peterson,W.;Kennedy,E.;Hales,B.1MooringSOFS_142E_46SSouthernOcean894Sutton,A.;Trull,T.;Shadwick,E.1MooringSoyoMaruTropicalPaciﬁc,coastal33234Ono,T.3ShipStationMNorthAtlantic447Skjelvan,I.1MooringStatsraadLehmkuhlNorthAtlantic,tropicalAtlantic,coastal47,881Becker,M.;Olsen,A.3ShipTAO125W_0NTropicalPaciﬁc241Sutton,A.1MooringTavastlandCoastal48421WillstrandWranne,A.;Stein-hoff,T.17ShipThomasG.ThompsonNorthAtlantic,tropicalAtlantic,NorthPa-ciﬁc,tropicalPaciﬁc,coastal47073Alin,S.R.;Feely,R.A.5ShipTransFuture5SouthernOcean,NorthPaciﬁc,tropicalPa-ciﬁc,coastal257424Nakaoka,S.-I.;Takao,S.22ShipTukumaArcticaNorthAtlantic,coastal70033Becker,M.;Olsen,A.23ShipWakatakaMaruNorthPaciﬁc,coastal13392Tadokoro,K.2ShipEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224857TableA6.AircraftmeasurementprogrammesarchivedbyCooperativeGlobalAtmosphericDataIntegrationProject(CGADIP;Schuldtetal.,2021,2022)thatcontributetotheevaluationoftheatmosphericinversions(Fig.B4).SitecodeMeasurementprogrammenameinObspackSpeciﬁcDOIDataprovidersAAOAirborneAerosolObservatory,Bondville,Illi-noisSweeney,C.;Dlugokencky,E.J.ABOVECarboninArcticReservoirsVulnerabilityEx-periment(CARVE)https://doi.org/10.3334/ORNLDAAC/1404Sweeney,C.,J.B.Miller,A.Kar-ion,S.J.Dinardo,andC.E.Miller.2016.CARVE:L2AtmosphericGasConcentra-tions,AirborneFlasks,Alaska,2012-2015.ORNLDAAC,OakRidge,Tennessee,USA.ACGAlaskaCoastGuardSweeney,C.;McKain,K.;Karion,A.;Dlugokencky,E.J.ACTAtmosphericCarbonandTransport–AmericaSweeney,C.;Dlugokencky,E.J.;Baier,B;Montzka,S.;Davis,K.AIRCORENOAANOAAAirCoreColmSweeney(NOAA)ANDBiancaBaier(NOAA)ALFAltaFlorestaGatti,L.V.;Gloor,E.;Miller,J.B.;AOAAircraftObservationofAtmospherictracegasesbyJMAghg_obs@met.kishou.go.jpBGIBradgate,IowaSweeney,C.;Dlugokencky,E.J.BNEBeaverCrossing,NebraskaSweeney,C.;Dlugokencky,E.J.BRZBerezorechka,RussiaSasakama,N.;Machida,T.CARBriggsdale,ColoradoSweeney,C.;Dlugokencky,E.J.CMACapeMay,NewJerseySweeney,C.;Dlugokencky,E.J.CONCONTRAIL(ComprehensiveObservationNetworkforTRacegasesbyAIrLiner)https://doi.org/10.17595/20180208.001Machida,T.;Matsueda,H.;Sawa,Y.;Niwa,Y.CRVCarboninArcticReservoirsVulnerabilityEx-periment(CARVE)Sweeney,C.;Karion,A.;Miller,J.B.;Miller,C.E.;Dlugokencky,E.J.DNDDahlen,NorthDakotaSweeney,C.;Dlugokencky,E.J.ECOEastCoastOutﬂowSweeney,C.;McKain,K.ESPEstevanPoint,BritishColumbiaSweeney,C.;Dlugokencky,E.J.ETLEastTroutLake,SaskatchewanSweeney,C.;Dlugokencky,E.J.FWIFairchild,WisconsinSweeney,C.;Dlugokencky,E.J.GSFCNASAGoddardSpaceFlightCenterAircraftCampaignKawa,S.R.;Abshire,J.B.;Riris,H.HAAMolokaiIsland,HawaiiSweeney,C.;Dlugokencky,E.J.HFMHarvardUniversityAircraftCampaignWofsy,S.C.HILHomer,IllinoisSweeney,C.;Dlugokencky,E.J.HIPHIPPO(HIAPERPole-to-PoleObservations)https://doi.org/10.3334/CDIAC/HIPPO_010Wofsy,S.C.;Stephens,B.B.;Elkins,J.W.;Hintsa,E.J.;Moore,F.IAGOS-CARIBICIn-serviceAircraftforaGlobalObservingSystemObersteiner,F.;Boenisch,H;Gehrlein,T.;Zahn,A.;Schuck,T.INXINFLUX(IndianapolisFluxExperiment)Sweeney,C.;Dlugokencky,E.J.;Shepson,P.B.;Turnbull,J.LEFParkFalls,WisconsinSweeney,C.;Dlugokencky,E.J.NHAOffshorePortsmouth,NewHampshire(IslesofShoals)Sweeney,C.;Dlugokencky,E.J.OILOglesby,IllinoisSweeney,C.;Dlugokencky,E.J.ORCORCAS(O2/N2RatioandCO2AirborneSouthernOceanStudy)https://doi.org/10.5065/D6SB445XStephens,B.B,Sweeney,C.,McKain,K.,Kort,E.PFAPokerFlat,AlaskaSweeney,C.;Dlugokencky,E.J.RBA-BRioBrancoGatti,L.V.;Gloor,E.;Miller,J.B.RTARarotongaSweeney,C.;Dlugokencky,E.J.SCACharleston,SouthCarolinaSweeney,C.;Dlugokencky,E.J.SGPSouthernGreatPlains,OklahomaSweeney,C.;Dlugokencky,E.J.;Biraud,S.TABTabatingaGatti,L.V.;Gloor,E.;Miller,J.B.TGCOffshoreCorpusChristi,TexasSweeney,C.;Dlugokencky,E.J.THDTrinidadHead,CaliforniaSweeney,C.;Dlugokencky,E.J.WBIWestBranch,IowaSweeney,C.;Dlugokencky,E.J.https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224858P.Friedlingsteinetal.:GlobalCarbonBudget2022TableA7.Mainmethodologicalchangesintheglobalcarbonbudgetsinceﬁrstpublication.Methodologicalchangesintroducedinoneyeararekeptforthefollowingyearsunlessnoted.Emptycellsmeantherewerenomethodologicalchangesintroducedthatyear.PublicationyearFossilfuelemissionsLUCemissionsReservoirsUncertainty&otherchangesGlobalCountry(territorial)Country(consumption)AtmosphereOceanLand2006aSplitinregions2007bELUCbasedonFAO-FRA2005andcon-stantELUCfor20061959–1979datafromMaunaLoa,dataaf-ter1980arefromtheglobalaverageBasedononeoceanmodeltunedtorepro-ducedobserved1990ssink±1σprovidedforallcomponents2008cConstantELUCfor20072009dSplitbetweenAnnexBandnon-AnnexBResultsfromanindependentstudydiscussedFire-basedemissionanomaliesusedfor2006–2008Basedonfouroceanmodelsnormalizedtoobservationswithcon-stantdeltaFirstuseofﬁveDGVMstocomparewithbudgetresidual2010eProjectionforcurrentyearbasedonGDPEmissionsfortopemit-tersELUCupdatedwithFAO-FRA20102011fSplitbetweenAnnexBandnon-AnnexB2012g129countriesfrom1959129countriesandre-gionsfrom1990–2010basedonGTAP8.0ELUCfor1997–2011includesinteran-nualanomaliesfromﬁre-basedemissionsAllyearsfromglobalaverageBasedonﬁveoceanmodelsnormalizedtoobservationswithratio10DGVMsavailableforSLAND.FirstuseoffourmodelstocomparewithELUC2013h250countries134countriesandregions1990–2011basedonGTAP8.1,withdetailedestimatesforyears1997,2001,2004,and2007ELUCfor2012es-timatedfrom2001–2010averageBasedonsixmodelscomparedwithtwodataproductstoyear2011CoordinatedDGVMex-perimentsforSLANDandELUCConﬁdencelevels,cumu-lativeemissions,andbud-getfrom17502014i3yearsofBPdata3yearsofBPdataExtendedto2012withupdatedGDPdataELUCfor1997–2013includesinteran-nualanomaliesfromﬁre-basedemissionsBasedonsevenmodelsBasedon10modelsInclusionofbreakdownofthesinksinthreelat-itudebandsandcom-parisonwiththreeatmo-sphericinversions2015jProjectionforcurrent-year-basedJanuary–AugustdataNationalemissionsfromUNFCCCextendedto2014alsoprovidedDetailedestimatesintroducedfor2011basedonGTAP9BasedoneightmodelsBasedon10modelswithassessmentofminimumrealismThedecadaluncertaintyfortheDGVMensemblemeannowuses±1σofthedecadalspreadacrossmodels2016k2yearsofBPdataAddedthreesmallcoun-triesandChina’semis-sionsfrom1990fromBPdata(thisreleaseonly)PreliminaryELUCus-ingFRA-2015shownforcomparisonanduseofﬁveDGVMsBasedonsevenmodelsBasedon14modelsDiscussionofprojectionforfullbudgetforcurrentyear2017lProjectionincludesIndia-speciﬁcdataAverageoftwobook-keepingmodelsanduseof12DGVMsBasedoneightmodelsthatmatchtheobservedsinkforthe1990sandisnolongernormalizedBasedon15modelsthatmeetobservation-basedcriteria(seeSect.2.5)Landmulti-modelaver-agenowusedinmaincar-bonbudget,withthecar-bonimbalancepresentedseparatelyandanewtableofkeyuncertaintiesaRaupachetal.(2007).bCanadelletal.(2007).cGCP(2007).dLeQuéréetal.(2009).eFriedlingsteinetal.(2010).fPetersetal.(2012b).gLeQuéréetal.(2013);Petersetal.(2013).hLeQuéréetal.(2014).iLeQuéréetal.(2015a);jLeQuéréetal.(2015b).kLeQuéréetal.(2016).lLeQuéréetal.(2018a).EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224859TableA8.MappingofglobalcarboncyclemodelslandﬂuxdeﬁnitionstothedeﬁnitionoftheLULUCFnetﬂuxusedinnationalreportingtoUNFCCC.Non-intactlandsareusedhereasproxyfor“managedlands”inthecountryreporting;nationalgreenhousegasinventories(NGHGI)aregapﬁlled(seeSect.C2.3fordetails).Whereavailable,weprovideindependentestimatesofcertainﬂuxesforcomparison(valuesareinGtCyr−1).2002–20112012–2021ELUCfrombookkeepingestimates(fromTable5)1.361.24SLANDtotal(fromTable5)fromDGVMs−2.85−3.10innon-forestlandsfromDGVMs−0.74−0.83innon-intactforestfromDGVMs−1.67−1.81inintactforestsfromDGVMs−0.44−0.47inintactlandfromORCHIDEE-MICT−1.34−1.38ELUCplusSLANDonnon-intactlandsconsideringnon-intactforestsonlyfrombookkeepingELUCandDGVMs−0.31−0.56consideringallnon-intactlandfromORCHIDEE-MICT0.900.60Nationalgreenhousegasinventories(LULUCF)−0.37−0.54FAOSTAT(LULUCF)0.390.24https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224860P.Friedlingsteinetal.:GlobalCarbonBudget2022TableA9.Fundingsupportingtheproductionofthevariouscomponentsoftheglobalcarbonbudgetinadditiontotheauthors’supportinginstitutions(seetheAcknowledgementsforfurtherdetails).Funderandgrantnumber(whererelevant)AuthorinitialsAustralia,IntegratedMarineObservingSystem(IMOS)BTAustralianNationalEnvironmentScienceProgram(NESP)JGCBelgium,FWO(FlandersResearchFoundation,contractgrantno.I001821N)ThaGBNPParibasFoundationthroughClimate&Biodiversityinitiative,philanthropicgrantfordevelopmentsoftheGlobalCarbonAtlasPCCanada,TulaFoundationWE,KPChina,NationalNaturalScienceFoundation(grantno.41975155)XYChina,NationalNaturalScienceFoundation(grantno.42141020)WYChina,NationalNaturalScienceFoundationofChina(grantno.41921005)BZChina,ScientiﬁcResearchStart-upFunds(grantno.QD2021024C)fromTsinghuaShenzhenInternationalGraduateSchoolBZChina,SecondTibetanPlateauScientiﬁcExpeditionandResearchProgram(2022QZKK0101)TXChina,YoungEliteScientistsSponsorshipProgrambyCAST(grantno.YESS20200135)BZECCopernicusAtmosphereMonitoringServiceimplementedbyECMWFFCECCopernicusMarineEnvironmentMonitoringServiceimplementedbyMercatorOceanMGECH2020(4C;grantno.821003)PF,MOS,RMA,SS,GPP,PC,JIK,TI,LB,AJ,PL,LukG,NG,NMa,SZECH2020(CoCO2:grantno.958927)RMA,GPP,JIKECH2020(COMFORT:grantno.820989)LukG,MG,NGECH2020(CONSTRAIN:grantno.820829)RS,ThoGECH2020(ESM2025–EarthSystemModelsfortheFuture;grantagreementno.101003536).RS,ThoG,TI,LB,BDECH2020(JERICO-S3:grantno.871153)HCBECH2020(VERIFY:grantno.776810)MWJ,RMA,GPP,PC,JIK,MJMEfgInternationalTT,MGEuropeanSpaceAgencyClimateChangeInitiativeESA-CCIRECCAP2project655(ESRIN/4000123002/18/I-NB)SS,PCEuropeanSpaceAgencyOceanSODAproject(grantno.4000137603/22/I-DT)LukG,NGFrance,FrenchOceanographicFleet(FOF)NMeFrance,ICOS(IntegratedCarbonObservationSystem)FranceNLFrance,InstitutNationaldesSciencesdel’Univers(INSU)NMeFrance,InstitutpolairefrançaisPaul-EmileVictor(IPEV)NMeFrance,Institutderecherchefrançaissurlesressourcesmarines(IFREMER)NMeFrance,InstitutdeRecherchepourleDéveloppement(IRD)NLFrance,Observatoiredessciencesdel’universEcce-Terra(OSUatSorbonneUniversité)NMeGermany,DeutscheForschungsgemeinschaft(DFG)underGermany’sExcellenceStrategy–EXC2037“Climate,ClimaticChange,andSociety”–projectno.390683824TIGermany,FederalMinistryforEducationandResearch(BMBF)HCBGermany,FederalMinistryforEducationandResearch(BMBF)underproject“CDRSynTra”(01LS2101A)JPGermany,GermanFederalMinistryofEducationandResearchunderproject”DArgo2025”(03F0857C)TSGermany,HelmholtzAssociationATMOprogramAAGermany,HelmholtzYoungInvestigatorGroupMarineCarbonandEcosystemFeedbacksintheEarthSystem(MarESys),grantno.VH-NG-1301JH,OGGermany,ICOS(IntegratedCarbonObservationSystem)GermanyHCBHapag-LloydTT,MGIreland,MarineInstituteMCJapan,EnvironmentResearchandTechnologyDevelopmentFundoftheMinistryoftheEnvironment(JPMEERF21S20810)YNJapan,GlobalEnvironmentalResearchCoordinationSystem,MinistryoftheEnvironment(grantno.E1751)SN,ST,TOJapan,EnvironmentResearchandTechnologyDevelopmentFundoftheMinistryoftheEnvironment(JPMEERF21S20800)HTJapan,JapanMeteorologicalAgencyKKKuehne+NagelInternationalAGTT,MGMediterraneanShippingCompany(MSc)TT,MGMonaco,FondationPrinceAlbertIIdeMonacoTT,MGMonaco,YachtClubdeMonacoTT,MGNetherlands,ICOS(IntegratedCarbonObservationSystem)WPEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224861TableA9.Continued.Funderandgrantnumber(whererelevant)AuthorinitialsNorway,ResearchCouncilofNorway(N-ICOS-2,grantno.296012)AO,MB,ISNorway,NorwegianResearchCouncil(grantno.270061)JSSweden,ICOS(IntegratedCarbonObservationSystem)AWSweden,SwedishMeteorologicalandHydrologicalInstituteAWSweden,TheSwedishResearchCouncilAWSwissNationalScienceFoundation(grantno.200020-200511)QSTibet,SecondTibetanPlateauScientiﬁcExpeditionandResearchProgram(SQ2022QZKK0101)TXUKRoyalSociety(grantno.RP\R1\191063)CLQUK,NaturalEnvironmentResearchCouncil(SONATA:grantno.NE/P021417/1)RWUK,NaturalEnvironmentalResearchCouncil(NE/R016518/1)PIPUK,NaturalEnvironmentResearchCouncil(NE/V01417X/1)MWJUK,RoyalSociety:TheEuropeanSpaceAgencyOCEANFLUXprojectsJDSUKRoyalSociety(grantno.RP\R1\191063)CLQUSA,BIATribalResilienceCWUSA,CooperativeInstituteforModelingtheEarthSystembetweentheNationalOceanicandAtmosphericAdministrationGeophysicalFluidDynamicsLaboratoryandPrincetonUniversityandtheHighMeadowsEnvironmentalInstituteLRUSA,CooperativeInstituteforClimate,Ocean,andEcosystemStudies(CIOCES)underNOAACooperativeAgreementno.NA20OAR4320271KOUSA,DepartmentofEnergy,BiologicalandEnvironmentalResearchAPWUSA,DepartmentofEnergy,SciDac(DESC0012972)GCH,LPCUSA,EnergyExascaleEarthSystemModel(E3SM)project,DepartmentofEnergy,OfﬁceofScience,OfﬁceofBiologicalandEnvironmentalResearchGCH,LPCUSA,EPAIndianGeneralAssistanceProgramCWUSA,NASACarbonMonitoringSystemprogramandOCOScienceteamprogram(80NM0018F0583).JLUSA,NASAInterdisciplinaryResearchinEarthScience(IDS)(80NSSC17K0348)GCH,LPC,BPUSA,NationalCenterforAtmosphericResearch(NSFCooperativeAgreementno.1852977)DKUSA,NationalOceanicandAtmosphericAdministration,OceanAcidiﬁcationProgramDP,RW,SRA,RAF,AJS,NMMUSA,NationalOceanicandAtmosphericAdministration,GlobalOceanMonitoringandObservingProgramDRM,CSw,NRB,CRodr,DP,RW,SRA,RAF,AJSUSA,NationalScienceFoundation(grantno.1903722)HTUSA,StateofAlaskaNMMComputingresourcesADAHPCclusterattheUniversityofEastAngliaMWJCAMSinversionwasgrantedaccesstotheHPCresourcesofTGCCundertheallocationA0110102201FCCheyennesupercomputerdatawereprovidedbytheComputationalandInformationSystemsLaboratory(CISL)atNCARDKHPCclusterAetherattheUniversityofBremen,ﬁnancedbyDFGwithinthescopeoftheExcellenceInitiativeITLMRI(FUJITSUServerPRIMERGYCX2550M5)YNNIES(SX-Aurora)YNNIESsupercomputersystemEKhttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224862P.Friedlingsteinetal.:GlobalCarbonBudget2022AppendixB:SupplementaryﬁguresFigureB1.Ensemblemeanair–seaCO2ﬂuxfrom(a)globaloceanbiogeochemistrymodelsand(b)fCO2-baseddataproducts,averagedoverthe2012–2021period(kgCm−2yr−1).Positivenumbersindicateaﬂuxintotheocean.(c)GriddedSOCATv2022fCO2measure-ments,averagedoverthe2012–2021period(µatm).In(a),modelsimulationAisshown.Thedataproductsrepresentthecontemporaryﬂux,i.e.includingoutgassingofriverinecarbon,whichisestimatedtoamountto0.65GtCyr−1globally.EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224863FigureB2.EvaluationoftheGOBMsanddataproductsusingtheroot-mean-squarederror(RMSE)fortheperiod1990to2021betweentheindividualsurfaceoceanfCO2mappingschemesandtheSOCATv2022database.Theyaxisshowstheamplitudeoftheinterannualvariabilityoftheair–seaCO2ﬂux(A-IAV),takenasthestandarddeviationofthedetrendedannualtimeseries.Resultsarepresentedfortheglobe,northernextratropics(>30◦N),tropics(30◦S–30◦N),andsouthernextratropics(<30◦S)fortheGOBMs(seelegend,circles)andforthefCO2-baseddataproducts(starsymbols).ThefCO2-baseddataproductsusetheSOCATdatabaseandarethereforenotindependentofthedata(seeSect.2.4.1).https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224864P.Friedlingsteinetal.:GlobalCarbonBudget2022FigureB3.EvaluationoftheDGVMsusingtheInternationalLandModelBenchmarkingsystem(ILAMB;Collieretal.,2018)(left)absoluteskillscoresand(right)skillscoresrelativetoothermodels.Thebenchmarkingisdonewithobservationsforvegetationbiomass(Saatchietal.,2011;andglobalcarbonunpublisheddata;Avitabileetal.,2016),GPP(Jungetal.,2010;Lasslopetal.,2010),leafareaindex(DeKauweetal.,2011;Mynenietal.,1997),ecosystemrespiration(Jungetal.,2010;Lasslopetal.,2010),soilcarbon(Hugeliusetal.,2013;Todd-Brownetal.,2013),evapotranspiration(DeKauweetal.,2011),andrunoff(DaiandTrenberth,2002).Foreachmodel–observationcomparisonaseriesoferrormetricsarecalculated.Scoresarethencalculatedasanexponentialfunctionofeacherrormetric.Finally,foreachvariablethemultiplescoresfromdifferentmetricsandobservationaldatasetsarecombinedtogivetheoverallvariablescoresshownintheleftpanel.Overallvariablescoresincreasefrom0to1withimprovementsinmodelperformance.Thesetoferrormetricsvarywithdatasetandcanincludemetricsbasedontheperiodmean,bias,root-mean-squarederror,spatialdistribution,interannualvariabilityandseasonalcycle.TherelativeskillscoreshownintherightpanelisaZscore,whichindicatesinunitsofstandarddeviationthemodelscoresrelativetothemulti-modelmeanscoreforagivenvariable.Greyboxesrepresentmissingmodeldata.FigureB4.Evaluationoftheatmosphericinversionproducts.Themeanofthemodelminusobservationsisshownforfourlatitudebandsinfourperiods:(ﬁrstpanel)2001–2021,(secondpanel)2001–2010,(thirdpanel)2011–2021,and(fourthpanel)2015–2021.TheninesystemsarecomparedtoindependentCO2measurementsmadeaboardaircraftovermanyareasoftheworldbetween2and7kmabovesealevel.AircraftmeasurementsarchivedintheCooperativeGlobalAtmosphericDataIntegrationProject(Schuldtetal.,2021,2022)fromsites,campaigns,orprogrammesthathavenotbeenassimilatedandcoveratleast9months(exceptforSHprogrammes)between2001and2021havebeenusedtocomputethebiasesofthedifferencesinfour45◦latitudebins.Landandoceandataareusedwithoutdistinction,andobservationdensityvariesstronglywithlatitudeandtime,asseeninthelowerpanels.EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224865FigureB5.Comparisonoftheestimatesofeachcomponentoftheglobalcarbonbudgetinthisstudy(blackline)withtheestimatesreleasedannuallybytheGCPsince2006.Greyshadingshowstheuncertaintyboundsrepresenting±1standarddeviationofthecurrentglobalcarbonbudgetbasedontheuncertaintyassessmentsdescribedinAppendixC.CO2emissionsfrom(a)fossilCO2emissions(EFOS)and(b)land-usechange(ELUC)andtheirpartitioningamong(c)theatmosphere(GATM),(d)land(SLAND),and(e)ocean(SOCEAN).SeethelegendforthecorrespondingyearsandTables3andA7forreferences.Thebudgetyearcorrespondstotheyearwhenthebudgetwasﬁrstreleased(allvaluesareinGtCyr−1).https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224866P.Friedlingsteinetal.:GlobalCarbonBudget2022FigureB6.DifferencesintheHYDE/LUH2land-useforcingusedfortheglobalcarbonbudgetsGCB2020(Friedlingsteinetal.,2021),GCB2021(Friedlingsteinetal.,2022a),andGCB2022(Friedlingsteinetal.,2022b).Shownareyear-to-yearchangesincroplandarea(b)andpasturearea(c).Toillustratetherelevanceoftheupdateintheland-useforcingtotherecenttrendsinELUC,thetoppanelshowstheland-useemissionestimatefromthebookkeepingmodelBLUE(originalmodeloutput,i.e.excludingpeatﬁreanddrainageemissions).EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224867AppendixC:ExtendedmethodologyC1Methodology:fossilfuelCO2emissions(EFOS)C1.1CementcarbonationFromthemomentitiscreated,cementbeginstoabsorbCO2fromtheatmosphere,aprocessknownas“cementcarbona-tion”.WeestimatethisCO2sink,from1931onwardsastheaverageoftwostudiesintheliterature(Caoetal.,2020;Guoetal.,2021).TheGlobalCementandConcreteAssociationreportsamuchlowercarbonationrate,butthisisbasedonthehighlyconservativeassumptionof0%mortar(GCCA,2021).Modellingcementcarbonationrequiresestimationofalargenumberofparameters,includingthedifferenttypesofcementmaterialindifferentcountries,thelifetimeofthestructuresbeforedemolition,thelifetimeofcementwasteafterdemolition,andthevolumetricpropertiesofstructures(Xietal.,2016).Lifetimeisanimportantparameterbecausedemolitionresultsintheexposureofnewsurfacestothecar-bonationprocess.Themainreasonsfordifferencesbetweenthetwostudiesappeartobetheassumedlifetimesofcementstructuresandthegeographicresolution,buttheuncertaintyboundsofthetwostudiesoverlap.C1.2EmissionsembodiedingoodsandservicesCDIAC,UNFCCC,andBPnationalemissionstatistics“in-cludegreenhousegasemissionsandremovalstakingplacewithinnationalterritoryandoffshoreareasoverwhichthecountryhasjurisdiction”(Rypdaletal.,2006)andarecalledterritorialemissioninventories.Consumption-basedemis-sioninventoriesallocateemissionstoproductsthatarecon-sumedwithinacountryandareconceptuallycalculatedastheterritorialemissionsminusthe“embodied”territo-rialemissionstoproduceexportedproductsplustheemis-sionsinothercountriestoproduceimportedproducts(con-sumptionisequaltoterritorialminusexportsplusim-ports).Consumption-basedemissionattributionresults(e.g.DavisandCaldeira,2010)provideadditionalinformationtoterritorial-basedemissionsthatcanbeusedtounderstandemissiondrivers(HertwichandPeters,2009)andquantifyemissiontransfersbythetradeofproductsbetweencoun-tries(Petersetal.,2011b).Theconsumption-basedemissionshavethesameglobaltotalbutreﬂectthetrade-drivenmove-mentofemissionsacrosstheEarth’ssurfaceinresponsetohumanactivities.Weestimateconsumption-basedemissionsfrom1990–2020byenumeratingtheglobalsupplychainus-ingaglobalmodeloftheeconomicrelationshipsbetweeneconomicsectorswithinandbetweeneverycountry(An-drewandPeters,2013;Petersetal.,2011a).OuranalysisisbasedontheeconomicandtradedatafromtheGlobalTradeandAnalysisProject(GTAP;Narayananetal.,2015),andwemakedetailedestimatesfortheyears1997(GTAPversion5);2001(GTAP6);and2004,2007,2011,and2014(GTAP10.0a),covering57sectorsand141countriesandre-gions.Thedetailedresultsarethenextendedintoanannualtimeseriesfrom1990tothelatestyearofthegrossdomes-ticproduct(GDP)data(2020inthisbudget)usingGDPdatabyexpenditureincurrentexchangerateofUSdollars(USD;fromtheUNNationalAccountsmainaggregatesdatabase;UN,2021)andtimeseriesoftradedatafromGTAP(basedonthemethodologyinPetersetal.,2011a).Weestimatethesector-levelCO2emissionsusingtheGTAPdataandmethodology,addtheﬂaringandcementemissionsfromourfossilCO2dataset,andthenscalethenationaltotals(exclud-ingbunkerfuels)tomatchtheemissionestimatesfromthecarbonbudget.Wedonotprovideaseparateuncertaintyes-timatefortheconsumption-basedemissions;however,basedonmodelcomparisonsandsensitivityanalysis,theyareun-likelytobesigniﬁcantlydifferentthanfortheterritorialemis-sionestimates(Petersetal.,2012a).C1.3UncertaintyassessmentforEFOSWeestimatetheuncertaintyoftheglobalfossilCO2emis-sionsat±5%(scaleddownfromthepublished±10%at±2σtotheuseof±1σboundsreportedhere;Andresetal.,2012).Thisisconsistentwithamoredetailedanaly-sisofuncertaintyof±8.4%at±2σ(Andresetal.,2014)andatthehighendoftherangeof±5%–10%at±2σreportedby(Ballantyneetal.,2015).Thisincludesanas-sessmentofuncertaintiesintheamountsoffuelconsumed,thecarbonandheatcontentsoffuels,andthecombustionefﬁciency.Whileweconsideraﬁxeduncertaintyof±5%forallyears,theuncertaintyasapercentageofemissionsisgrowingwithtimebecauseofthelargershareofglobalemissionsfromemergingeconomiesanddevelopingcoun-tries(Marlandetal.,2009).Generally,emissionsfromma-tureeconomieswithgoodstatisticalprocesseshaveanuncer-taintyofonlyafewpercent(Marland,2008),whileemissionsfromstronglydevelopingeconomiessuchasChinahaveun-certaintiesofaround±10%(for±1σ;Greggetal.,2008;Andresetal.,2014).Uncertaintiesinemissionsarelikelytobemainlysystematicerrorsrelatedtounderlyingbiasesofenergystatisticsandtotheaccountingmethodusedbyeachcountry.C1.4GrowthrateinemissionsWereporttheannualgrowthrateinemissionsforadjacentyears(inpercentperyear)bycalculatingthedifferencebe-tweenthe2yearsandthennormalizingtotheemissionsintheﬁrstyear:(EFOS(t0+1)−EFOS(t0))/EFOS(t0)×100%.Weapplyaleap-yearadjustmentwhererelevanttoensurevalidinterpretationsofannualgrowthrates.Thisaffectsthegrowthratebyabout0.3%peryear(1/366)andcausescal-culatedgrowthratestogoupapproximately0.3%iftheﬁrstyearisaleapyearanddown0.3%ifthesecondyearisaleapyear.https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224868P.Friedlingsteinetal.:GlobalCarbonBudget2022TherelativegrowthrateofEFOSovertimeperiodsofgreaterthan1yearcanberewrittenusingitslogarithmequiv-alentasfollows:1EFOSdEFOSdt=d(lnEFOS)dt.(C1)Herewecalculaterelativegrowthratesinemissionsformulti-yearperiods(e.g.adecade)byﬁttingalineartrendtoln(EFOS)inEq.(2),reportedinpercentperyear.C1.5Emissionsprojectionfor2022Togaininsightintoemissiontrendsfor2022,weprovideanassessmentofglobalfossilCO2emissions,EFOS,bycom-biningindividualassessmentsofemissionsforChina,USA,theEU,andIndia(thefourcountries/regionswiththelargestemissions)andtherestoftheworld.Themethodsarespeciﬁctoeachcountryorregion,asde-scribedindetailbelow.ChinaWeusearegressionbetweenmonthlydataforeachfossilfuelandcementandannualdataforconsumptionoffossilfuelsorproductionofcementtoprojectfull-yeargrowthinfossilfuelconsumptionandcementproduction.Themonthlydataforeachproductconsistsofthefollowingelements.–Coal.ThisproductusesaproprietaryestimateformonthlyconsumptionofmaincoaltypesfromSXCoal.–Oil.TheproductusesproductiondatafromtheNationalBureauofStatistics(NBS),plusnetimportsfromtheChinaCustomsAdministration(i.e.grosssupplyofoil,notincludinginventorychanges).–Naturalgas.Thisproductusesthesamesourceasforoil.–Cement.ThisproductusesproductiondatafromNBS.Foroil,weusedataforproductionandnetimportsofreﬁnedoilproductsratherthancrudeoil.Thischoiceismadebe-causereﬁnedproductsareonestepclosertoactualconsump-tionandbecausecrudeoilcanbesubjecttolargemarket-drivenandstrategicinventorychangesthatarenotcapturedbyavailablemonthlydata.Foreachfuelandcement,wemakeaBayesianlinearre-gressionbetweenyear-on-yearcumulativegrowthinsupply(productionforcement)andfull-yeargrowthinconsumption(productionforcement)fromannualconsumptiondata.Intheregressionmodel,thegrowthrateinannualconsumption(productionforcement)ismodelledasaregressionparam-etermultipliedbythecumulativeyear-on-yeargrowthratefromthemonthlydatathroughJulyofeachyearforpastyears(through2021).WeusebroadGaussiandistributionscentredaround1aspriorsfortheratiosbetweenannualandthrough-Julygrowthrates.Wethenusetheposteriorsforthegrowthratestogetherwithcumulativemonthlysupplyorpro-ductiondatathroughJulyof2022toproduceaposteriorpre-dictivedistributionforthefull-yeargrowthrateforfossilfuelconsumptionandcementproductionin2022.IfthegrowthinsupplyorproductionthroughJulywereanunbiasedestimateofthefull-yeargrowthinconsump-tionorproduction,theposteriordistributionfortheratiobe-tweenthemonthlyandannualgrowthrateswouldbecen-tredaround1.However,inpracticetheratiosaredifferentfrom1(inmostcasesbelow1).Thisisaresultofvariousbiassingfactorssuchasunevenevolutionintheﬁrstandsec-ondhalfofeachyear,inventorychangesthataresomewhatanti-correlatedwithproductionandnetimports,differencesinstatisticalcoverage,andotherfactorsthatarenotcapturedinthemonthlydata.Forfossilfuels,themeanoftheposteriordistributionisusedasthecentralestimateforthegrowthratein2022,whiletheedgesofa68%credibleinterval(analogoustoa1σcon-ﬁdenceinterval)areusedfortheupperandlowerbounds.Forcement,theevolutionfromJanuarytoJulyhasbeenhighlyatypicalowingtotheongoingturmoilinthecon-structionsector,andtheresultsoftheregressionanalysisareheavilybiasedbyequallyatypicalbutdifferentdynamicsin2021.Forthisreason,weuseanaverageoftheresultsoftheregressionanalysisandtheplaingrowthincementproduc-tionthroughJuly2022,sincethisresultsinagrowthratethatseemsmoreplausibleandinlinewithwherethecumulativecementproductionappearstobeheadedatthetimeofwrit-ing.USAWeuseemissionsestimatedbytheU.S.EnergyInforma-tionAdministration(EIA)intheirShort-TermEnergyOut-look(STEO)foremissionsfromfossilfuelstogetbothyear-to-date(YTD)informationandafull-yearprojection(EIA,2022).TheSTEOalsoincludesanear-termforecastbasedonanenergyforecastingmodelthatisupdatedmonthly(lastupdatewithpreliminarydatathroughAugust2022)andtakesintoaccountexpectedtemperatures,householdexpendituresbyfueltype,energymarkets,policies,andothereffects.WecombinethiswithourestimateofemissionsfromcementproductionusingthemonthlyUScementclinkerproductiondatafromUSGSforJanuary–June2022,assumingchangesincementproductionovertheﬁrstpartoftheyearapplythroughouttheyear.IndiaWeusemonthlyemissionsestimatesforIndiaupdatedfromAndrew(2020b)throughJuly2022.Theseestimatesarede-rivedfrommanyofﬁcialmonthlyenergyandotheractiv-itydatasourcestoproducedirectestimatesofnationalCO2emissionswithouttheuseofproxies.EmissionsfromcoalEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224869arethenextendedtoAugustusingaregressionrelationshipbasedonpowergeneratedfromcoal,coaldispatchesbyCoalIndiaLtd.,thecompositePurchasingManagers’Index,time,anddayspermonth.Forthelast3–5monthsoftheyear,eachseriesisextrapolatedassumingtypicaltrends.EUWeuseareﬁnementtothemethodspresentedbyAndrew(2021),derivingemissionsfrommonthlyenergydatare-portedbyEurostat.SomedatagapsareﬁlledusingdatafromtheJointOrganizationsDataInitiative(JODI,2022).Sub-annualcementproductiondataarelimited,butdataforGer-manyandPoland,thetwolargestproducers,suggestasmalldecline.ForfossilfuelsthisprovidesestimatesthroughJuly.WeextendcoalemissionsthroughAugustusingaregressionmodelbuiltfromgenerationofpowerfromhardcoal,powerfrombrowncoal,totalpowergeneration,andthenumberofworkingdaysinGermanyandPoland,thetwobiggestcoalconsumersintheEU.Thesearethenextendedthroughtheendoftheyearassumingtypicaltrends.Weextendoilemis-sionsbybuildingaregressionmodelbetweenourmonthlyCO2estimatesandoilconsumptionreportedbytheEIAforEuropeinitsShort-TermEnergyOutlook(Septemberedi-tion)andthenusingthismodelwithEIA’smonthlyfore-casts.Fornaturalgas,thestrongseasonalsignalallowstheuseofthebias-adjustedHolt–Wintersexponentialsmooth-ingmethod(Chatﬁeld,1978).RestoftheworldWeusethecloserelationshipbetweenthegrowthinGDPandthegrowthinemissions(Raupachetal.,2007)toprojectemissionsforthecurrentyear.ThisisbasedonasimpliﬁedKayaIdentity,wherebyEFOS(GtCyr−1)isdecomposedbytheproductofGDP(USDyr−1)andthefossilfuelcarbonintensityoftheeconomy(IFOS;GtCUSD−1)asfollows:EFOS=GDP×IFOS.(C2)TakingatimederivativeofEq.(3)andrearranginggives1EFOSdEFOSdt=1GDPdGDPdt+1IFOSdIFOSdt,(C3)wheretheleft-handtermistherelativegrowthrateofEFOS,andtheright-handtermsaretherelativegrowthratesofGDPandIFOS,respectively,whichcansimplybeaddedlinearlytogivetheoverallgrowthrate.TheIFOSisbasedonGDPinconstantPPP(purchasingpowerparity)fromtheInternationalEnergyAgency(IEA)upto2017(IEA/OECD,2019)andextendedusingtheInter-nationalMonetaryFund(IMF)growthratesthrough2021(IMF,2022).InterannualvariabilityinIFOSisthelargestsourceofuncertaintyintheGDP-basedemissionsprojec-tions.WethususethestandarddeviationoftheannualIFOSfortheperiod2012–2021asameasureofuncertainty,re-ﬂectinga±1σasintherestofthecarbonbudget.Forrest-of-worldoilemissionsgrowth,weusetheglobaloildemandforecastpublishedbytheEIAlessourprojectionsfortheotherfourregionsandestimateuncertaintyasthemaximumabsolutedifferenceovertheperiodavailableforsuchfore-castsusingthespeciﬁcmonthlyedition(e.g.August)com-paredtotheﬁrstestimatebasedonmoresoliddatainthefollowingyear(April).WorldTheglobaltotalisthesumofeachofthecountriesandre-gions.C2Methodology:CO2emissionsfromland-use,land-usechange,andforestry(ELUC)ThenetCO2ﬂuxfromland-use,land-usechange,andforestry(ELUC,calledland-usechangeemissionsintherestofthetext)includesCO2ﬂuxesfromdeforestation,afforesta-tion,logging,andforestdegradation(includingharvestac-tivity);shiftingcultivation(cycleofcuttingforestforagri-culture,thenabandoning);andregrowthofforestsfollowingwoodharvestorabandonmentofagriculture.Emissionsfrompeatburninganddrainageareaddedfromexternaldatasets(seeAppendixC2.1below).Onlysomeland-managementactivitiesareincludedinourland-usechangeemissionses-timates(TableA1).Someoftheseactivitiesleadtoemis-sionsofCO2totheatmosphere,whileothersleadtoCO2sinks.ELUCisthenetsumofemissionsandremovalsduetoallanthropogenicactivitiesconsidered.Ourannualesti-matefor1960–2021isprovidedastheaverageofresultsfromthreebookkeepingapproaches(AppendixC2.1below):anestimateusingtheBookkeepingofLandUseEmissionsmodel(Hansisetal.,2015;hereafterBLUE),oneusingthecompactEarthsystemmodelOSCAR(Gasseretal.,2020),withbothBLUEandOSCARbeingupdatedheretonewland-useforcingcoveringthetimeperioduntil2021,andanupdatedversionoftheestimatepublishedbyHoughtonandNassikas(2017)(hereafterupdatedH&N2017).Allthreedatasetsarethenextrapolatedtoprovideaprojectionfor2022(AppendixC2.5below).Inaddition,weuseresultsfromdynamicglobalvegetationmodels(DGVMs;seeAp-pendixC2.2andTable4)tohelpquantifytheuncertaintyinELUC(AppendixC2.4)andthusbettercharacterizeourunderstanding.Notethatinthisbudget,weusethescien-tiﬁcELUCdeﬁnition,whichcountsﬂuxesduetoenvironmen-talchangesonmanagedlandtowardsSLAND,asopposedtothenationalgreenhousegasinventoriesundertheUNFCCC,whichincludetheminELUCandthusoftenreportsmallerland-useemissions(Grassietal.,2018;Petrescuetal.,2020).However,weprovideamethodologyofmappingofthetwoapproachestoeachotherfurtherbelow(AppendixC2.3).https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224870P.Friedlingsteinetal.:GlobalCarbonBudget2022C2.1BookkeepingmodelsLand-usechangeCO2emissionsanduptakeﬂuxesarecal-culatedbythreebookkeepingmodels.ThesearebasedontheoriginalbookkeepingapproachofHoughton(2003)thatkeepstrackofthecarbonstoredinvegetationandsoilsbe-foreandafteraland-usechange(transitionsbetweenvariousnaturalvegetationtypes,croplands,andpastures).Literature-basedresponsecurvesdescribedecayofvegetationandsoilcarbon,includingtransfertoproductpoolsofdifferentlife-times,aswellascarbonuptakeduetoregrowth.Inaddition,thebookkeepingmodelsrepresentlong-termdegradationofprimaryforestasloweredstandingvegetationandsoilcarbonstocksinsecondaryforestsandincludeforestmanagementpracticessuchaswoodharvests.BLUEandtheupdatedH&N2017excludelandecosys-tems’transientresponsetochangesinclimate,atmosphericCO2,andotherenvironmentalfactorsandbasethecarbondensitiesoncontemporarydatafromliteratureandinven-torydata.Sincecarbondensitiesthusremainﬁxedovertime,theadditionalsinkcapacitythatecosystemsprovideinre-sponsetoCO2fertilizationandsomeotherenvironmentalchangesisnotcapturedbythesemodels(Pongratzetal.,2014).Onthecontrary,OSCARincludesthistransientre-sponse,anditfollowsatheoreticalframework(GasserandCiais,2013)thatallowsseparatingbookkeepingland-useemissionsandthelossofadditionalsinkcapacity.Onlytheformerisincludedhere,whilethelatterisdiscussedinAp-pendixD4.Thebookkeepingmodelsdifferin(1)computa-tionalunits(spatiallyexplicittreatmentofland-usechangeforBLUE,country-levelfortheupdatedH&N2017andOS-CAR),(2)processesrepresented(seeTableA1),and(3)car-bondensitiesassignedtovegetationandsoilofeachvege-tationtype(basedonliteratureforBLUEandtheupdatedH&N2017,calibratedtoDGVMsforOSCAR).Anotabledifferencebetweenmodelsexistswithrespecttothetreat-mentofshiftingcultivation.TheupdateofH&N2017,in-troducedfortheGCB2021(Friedlingsteinetal.,2022a),changedtheapproachovertheearlierH&N2017version:H&N2017hadassumedthe“excessloss”oftropicalforests,i.e.whentheGlobalForestResourcesAssessment(FRA;FAO2020)indicatedthataforestlosslargerthanthein-creaseinagriculturalareasfromFAO(FAOSTAT2021)re-sultedfromconvertingforeststocroplandsatthesametimeoldercroplandswereabandoned.Thoseabandonedcrop-landsbegantorecovertoforestsafter15years.TheupdatedH&N2017nowassumesthatforestlossinexcessofincreasesincroplandandpasturesrepresentedanincreaseinshiftingcultivation.Whentheexcesslossofforestswasnegative,itwasassumedthatshiftingcultivationwasreturnedtoforest.Historicalareasinshiftingcultivationwereextrapolatedtak-ingintoaccountcountry-basedestimatesofareasinfallowin1980(FAO/UNEP,1981)andexpertopinion(fromHeini-mannetal.,2017).Incontrast,theBLUEandOSCARmod-elsincludesub-grid-scaletransitionsbetweenallvegetationtypes.Furthermore,theupdatedH&N2017assumesconver-sionofnaturalgrasslandstopasture,whileBLUEandOS-CARallocatepasturetransitionsproportionallyonallnat-uralvegetationthatexistsinagridcell.Thisisonerea-sonforgenerallyhigheremissionsinBLUEandOSCAR.Bookkeepingmodelsdonotdirectlycapturecarbonemis-sionsfrompeatﬁres,whichcancreatelargeemissionsandinterannualvariabilityduetosynergiesofland-useandcli-matevariabilityinSoutheastAsia,particularlyduringEl-Niñoevents,nordotheycaptureemissionsfromtheorganiclayersofdrainedpeatsoils.Tocorrectforthis,weaddpeatﬁreemissionsbasedontheGlobalFireEmissionDatabase(GFED4s;vanderWerfetal.,2017)tothebookkeepingmodels’output.EmissionsarecalculatedbymultiplyingthemassofdrymatteremittedbypeatﬁreswiththeCemissionfactorforpeatﬁresindicatedintheGFED4sdatabase.Emis-sionsfromdeforestationﬁresusedtoderiveELUCprojec-tionsfor2022arecalculatedanalogously.Asthesesatellite-derivedestimatesofpeatﬁreemissionsstartin1997only,wefollowtheapproachbyHoughtonandNassikas(2017)forearlieryears,whichrampsupfromzeroemissionsin1980to0.04PgCyr−1in1996,reﬂectingtheonsetofma-jorclearingofpeatlandsinequatorialSoutheastAsiainthe1980s.Similarly,weaddestimatesofpeatdrainageemis-sions.Inrecentyears,morepeatdrainageestimatesthatpro-videspatiallyexplicitdatahavebecomeavailable,andwethusextendedthenumberofpeatdrainagedatasetsconsid-ered.WeemployFAOpeatdrainageemissions1990–2019fromcroplandsandgrasslands(ConcheddaandTubiello,2020),peatdrainageemissions1700–2010fromsimulationswiththeDGVMORCHIDEE-PEAT(Qiuetal.,2021),andpeatdrainageemissions1701–2021fromsimulationswiththeDGVMLPX-Bern(LienertandJoos,2018;MüllerandJoos,2021),applyingtheupdatedLUH2forcingasalsousedbyBLUE,OSCAR,andtheDGVMs.WeextrapolatetheFAOdatato1850–2021bykeepingthepost-2019emis-sionsconstantat2019levels,bylinearlyincreasingtropi-caldrainageemissionsbetween1980and1990startingfrom0GtCyr−1in1980,consistentwithH&N2017’sassumption(HoughtonandNassikas,2017),andbykeepingpre-1990emissionsfromtheoftenolddrainedareasoftheextratropicsconstantat1990emissionlevels.ORCHIDEE-PEATdataareextrapolatedto2011–2021byreplicatingtheaverageemis-sionsin2000–2010(ChunjingQiu„personalcommunica-tion,2022).Further,ORCHIDEE-PEATonlyprovidespeatdrainageemissionsnorthof30◦N,andthusweﬁllthere-gionssouthof30◦Nusingtheaveragepeatdrainageemis-sionsfromFAOandLPX-Bern.Theaverageofthecar-bonemissionestimatesbythethreedifferentpeatdrainagedatasetsisaddedtothebookkeepingmodelstoobtainnetELUCandgrosssources.Thethreebookkeepingestimatesusedinthisstudydifferwithrespecttotheland-usechangedatausedtodrivethemodels.TheupdatedH&N2017basesitsestimatesdirectlyontheForestResourceAssessmentoftheFAO,whichpro-EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224871videsstatisticsonforestareachangeandmanagementatin-tervalsof5yearsandiscurrentlyupdateduntil2020(FAO,2020).ThedataarebasedoncountryreportingtoFAOandmayincluderemote-sensinginformationinmorerecentas-sessments.Changesinland-useotherthanforestsarebasedonannual,nationalchangesincroplandandpastureareasre-portedbyFAO(FAOSTAT,2021).Ontheotherhand,BLUEusestheharmonizedland-usechangedataLUH2-GCB2022coveringtheentire850–2021period(anupdatetothepre-viouslyreleasedLUH2v2hdataset;Hurttetal.,2017;Hurttetal.,2020),whichwasalsousedasinputtotheDGVMs(AppendixC2.2).Itdescribesland-usechange,alsobasedontheFAOdataasdescribedinAppendixC2.2andtheHYDE3.3dataset(KleinGoldewijketal.,2017a,b),butpro-videdataquarter-degreespatialresolution,consideringsub-grid-scaletransitionsbetweenprimaryforest,secondaryfor-est,primarynon-forest,secondarynon-forest,cropland,pas-ture,rangeland,andurbanland(Hurttetal.,2020;Chinietal.,2021).LUH2-GCB2022providesadistinctionbetweenrangelandsandpasture,basedoninputsfromHYDE.Toconstrainthemodels’interpretationonwhetherrangelandimpliestheoriginalnaturalvegetationtobetransformedtograsslandornot(e.g.browsingonshrubland),aforestmaskwasprovidedwithLUH2-GCB2021;forestisassumedtobetransformedtograsslands,whileothernaturalvegetationremains(incaseofsecondaryvegetation)orisdegradedfromprimarytosecondaryvegetation(Maetal.,2020).ThisisimplementedinBLUE.OSCARwasrunwithbothLUH2-GCB2022andFAO/FRA(asusedwiththeupdatedH&N2017),wherethedriversofthelatterwerelinearlyex-trapolatedto2021usingtheir2015–2020trends.Thebest-guessOSCARestimateusedinourstudyisacombinationofresultsforLUH2-GCB2022andFAO/FRAland-usedataandalargenumberofperturbedparametersimulationsweightedagainstaconstraint(thecumulativeSLANDover1960–2020oflastyear’sGCB).AstherecordoftheupdatedH&N2017endsin2020,weextenditto2021byaddingthedifferenceoftheemissionsfromtropicaldeforestationanddegradation,peatdrainage,andpeatﬁrebetween2020and2021tothemodel’sestimatefor2020(i.e.consideringtheyearlyanoma-liesoftheemissionsfromtropicaldeforestationanddegra-dation,peatdrainage,andpeatﬁre).Thesamemethodisap-pliedtoallthreebookkeepingestimatestoprovideaprojec-tionfor2022.ForELUCfrom1850onwardsweaveragetheestimatesfromBLUE,theupdatedH&N2017,andOSCAR.Forthecumulativenumbersstarting1750,anaverageoffourearlierpublicationsisadded(30±20PgC1750–1850,roundedtothenearest5;LeQuéréetal.,2016).Weprovideestimatesofthegrossland-usechangeﬂuxesfromwhichthereportednetland-usechangeﬂux,ELUC,isderivedasasum.Grossﬂuxesarederivedinternallybythethreebookkeepingmodels.Grossemissionsstemfromdecayingmaterialleftdeadonsiteandfromproductsaf-terclearingofnaturalvegetationforagriculturalpurposesorwoodharvesting,emissionsfrompeatdrainageandpeatburning,and,forBLUE,additionallyfromdegradationfromprimarytosecondarylandthroughusageofnaturalvegeta-tionasrangeland.Grossremovalsstemfromregrowthafteragriculturalabandonmentandwoodharvesting.GrossﬂuxesfortheupdatedH&N2017for2020andforthe2022pro-jectionofallthreemodelswerecalculatedbythechangeinemissionsfromtropicaldeforestationanddegradationandpeatburninganddrainageasdescribedforthenetELUCabove.Astropicaldeforestationanddegradationandpeatburninganddrainageallonlyleadtogrossemissionstotheatmosphere,onlygross(andnet)emissionsareadjustedthisway,whilegrosssinksareassumedtoremainconstantoverthepreviousyear..Thisyear,weprovideanadditionalsplitofthenetELUCintocomponentﬂuxestobetteridentifyreasonsfordiver-gencebetweenbookkeepingestimatesandtogivemorein-sightintothedriversofsourcesandsinks.Thissplitdis-tinguishesbetweenﬂuxesfromdeforestation(includingduetoshiftingcultivation);ﬂuxesfromorganicsoils(i.e.peatdrainageandﬁres);afforestation,reafforestation,andwoodharvest(i.e.ﬂuxesinforestsfromslashandproductdecayfollowingwoodharvesting,regrowthassociatedwithwoodharvestingorafterabandonment,includingreforestationandinshiftingcultivationcycles,andafforestation);andﬂuxesassociatedwithallothertransitions.C2.2Dynamicglobalvegetationmodels(DGVMs)Land-usechangeCO2emissionshavealsobeenestimatedusinganensembleof16DGVMsimulations.TheDGVMsaccountfordeforestationandregrowth,themostimportantcomponentsofELUC,buttheydonotrepresentallprocessesresultingdirectlyfromhumanactivitiesonland(TableA1).AllDGVMsrepresentprocessesofvegetationgrowthandmortality,aswellasdecompositionofdeadorganicmatterassociatedwithnaturalcycles,andincludethevegetationandsoilcarbonresponsetoincreasingatmosphericCO2concen-trationandtoclimatevariabilityandchange.Mostmodelsexplicitlysimulatethecouplingofcarbonandnitrogency-clesandaccountforatmosphericNdepositionandNfertil-izers(TableA1).TheDGVMsareindependentoftheotherbudgettermsexceptfortheiruseofatmosphericCO2con-centrationtocalculatethefertilizationeffectofCO2onplantphotosynthesis.AllDGVMsusetheLUH2-GCB2022datasetasinput,whichincludestheHYDEcropland/grazinglanddataset(KleinGoldewijketal.,2017a,b),andadditionalinformationonland-covertransitionsandwoodharvest.DGVMsusean-nual,half-degree(regriddedfrom5minresolution)fractionaldataoncroplandandpasturefromHYDE3.3.DGVMsthatdonotsimulatesubgrid-scaletransitions(i.e.netland-useemissions;seeTableA1)usedtheHYDEinfor-mationonagriculturalareachange.Forallcountries,withtheexceptionofBrazilandtheDemocraticRepublicofthehttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224872P.Friedlingsteinetal.:GlobalCarbonBudget2022Congo,thesedataarebasedontheavailableannualFAOstatisticsofchangeinagriculturallandareaavailablefrom1961uptoandincluding2017.TheFAOretrospectivelyrevisedtheirreportingfortheDemocraticRepublicoftheCongo,whichwasnewlyavailableuntil2020.InadditiontoFAOcountry-levelstatistics,theHYDE3.3cropland/graz-inglanddatasetisconstrainedspatiallybasedonmulti-yearsatellitelandcovermapsfromESACCILC(seebelow).Af-tertheyear2017,LUH2extrapolates,onagridcellbasis,thecropland,pasture,andurbandatalinearlybasedonthetrendovertheprevious5yearstogeneratedatauntiltheyear2021.Thisextrapolationmethodologyisnotappropriateforcoun-triesthathaveexperiencedrecentrapidchangesintherateofland-usechange,e.g.Brazil,whichhasexperiencedarecentupturnindeforestation.Hence,forBrazilwereplaceFAOstate-leveldataforcroplandandgrazinglandinHYDEbythosefromin-countrylandcoverdatasetMapBiomas(col-lection6)for1985–2020(Souzaetal.,2020).ESA-CCIisusedtospatiallydisaggregateasdescribedbelow.Similarly,anestimatefortheyear2021isbasedontheMapBiomastrend2015–2020.Thepre-1985periodisscaledwiththepercapitanumbersfrom1985fromMapBiomas,andthusthistransitionissmooth.HYDEusessatelliteimageryfromESA-CCIfrom1992–2018formoredetailedyearlyallocationofcroplandandgrazingland,withtheESAareadatascaledtomatchtheFAOannualtotalsatcountrylevel.Theoriginal300mspatialresolutiondatafromESAwereaggregatedtoa5arcminres-olutionaccordingtotheclassiﬁcationschemeasdescribedinKleinGoldewijketal.(2017a).DGVMsthatsimulatesubgridscaletransitions(i.e.grossland-useemissions;seeTableA1)usemoredetailedland-usetransitionandwoodharvestinformationfromtheLUH2-GCB2022dataset.LUH2-GCB2022isanupdateofthemorecomprehensiveharmonizedland-usedataset(Hurttetal.,2020)thatfurtherincludesfractionaldataonprimaryandsecondaryforestvegetation,aswellasallunderlyingtransi-tionsbetweenland-usestates(850-2020;Hurttetal.,2011,2017,2020;Chinietal.,2021;TableA1).Thisdatasetisofquarter-degreefractionalareasofland-usestatesandalltransitionsbetweenthosestates,includinganewwoodhar-vestreconstruction,newrepresentationofshiftingcultiva-tion,croprotations,andmanagementinformation,includingirrigationandfertilizerapplication.Theland-usestatesin-cludeﬁvedifferentcroptypesinadditiontosplittinggrazinglandintomanagedpastureandrangeland.Woodharvestpat-ternsareconstrainedwithLandsat-basedtreecoverlossdata(Hansenetal.,2013).UpdatesofLUH2-GCB2022overlastyear’sversion(LUH2-GCB2021)areusingthemostrecentHYDErelease(coveringthetimeperiodupto2017,revi-siontoBrazilandtheDemocraticRepublicoftheCongoasdescribedabove).WeusethesameFAOwoodharvestdataaslastyearforalldatasetyearsfrom1961to2019andextrapolatetotheyear2022.TheHYDE3.3popula-tiondataarealsousedtoextendthewoodharvesttimese-riesbackintime.Otherwoodharvestinputs(foryearspriorto1961)remainthesameinLUH2.Theseupdatesintheland-useforcingareshownincomparisontothemorepro-nouncedversionchangefromtheGCB2020(Friedlingsteinetal.,2020)toGCB2021,whichwasdiscussedinFriedling-steinetal.(2022a)inFig.B6,andtheirrelevanceforland-useemissionsisdiscussedinSect.3.2.2.DGVMsimplementland-usechangedifferently(e.g.anincreasedcroplandfrac-tioninagridcellcaneitherbeattheexpenseofgrassland,shrubs,orforest,thelatterresultingindeforestation;landcoverfractionsofthenon-agriculturallanddifferbetweenmodels).Similarly,model-speciﬁcassumptionsareappliedtoconvertdeforestedbiomassordeforestedareaandotherforestproductpoolsintocarbon,anddifferentchoicesaremaderegardingtheallocationofrangelandsasnaturalvege-tationorpastures.ThedifferencebetweentwoDGVMsimulations(seeAp-pendixC4.1below),oneforcedwithhistoricalchangesinlanduseandasecondwithtime-invariantpre-industriallandcoverandpre-industrialwoodharvestrates,allowsquan-tiﬁcationofthedynamicevolutionofvegetationbiomassandsoilcarbonpoolsinresponsetoland-usechangeineachmodel(ELUC).UsingthedifferencebetweenthesetwoDGVMssimulationstodiagnoseELUCmeanstheDGVMsaccountforthelossofadditionalsinkcapacity(around0.4±0.3GtCyr−1;seeSect.2.7andAppendixD4),whereasthebookkeepingmodelsdonot.Asacriterionforinclusioninthiscarbonbudget,weonlyretainmodelsthatsimulateapositiveELUCduringthe1990s,asassessedintheIPCCAR4(Denmanetal.,2007)andAR5(Ciaisetal.,2013).AllDGVMsmetthiscriterion,al-thoughonemodelwasnotincludedintheELUCestimatefromDGVMsasitexhibitedaspuriousresponsetothetran-sientlandcoverchangeforcingafteritsinitialspin-up.C2.3MappingofnationalGHGinventorydatatoELUCAnapproachwasimplementedtoreconcilethelargegapbe-tweenland-useemissionsestimatesfrombookkeepingmod-elsandfromnationalGHGinventories(NGHGI)(seeTa-bleA8).Thisgapisduetodifferentapproachestocalculat-ing“anthropogenic”CO2ﬂuxesrelatedtoland-usechangeandlandmanagement(Grassietal.,2018).Inparticular,thelandsinksduetoenvironmentalchangeonmanagedlandsaretreatedasnon-anthropogenicintheglobalcarbonbud-get,whiletheyaregenerallyconsideredanthropogenicinNGHGIs(“indirectanthropogenicﬂuxes”;Egglestonetal.,2006).Buildingonpreviousstudies(Grassietal.,2021),theapproachimplementedhereaddstheDGVMestimatesofCO2ﬂuxesduetoenvironmentalchangefromcountries’managedforestarea(partofSLAND)totheELUCﬂux.ThissumisexpectedtobeconceptuallymorecomparabletoLU-LUCFthanELUC.ELUCdataaretakenfrombookkeepingmodels,inlinewiththeglobalcarbonbudgetapproach.TodetermineSLANDEarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224873onmanagedforest,thefollowingstepsweretaken:spa-tiallygriddeddataof“natural”forestnetbiomeproductiv-ity(NBP)(SLAND,i.e.duetoenvironmentalchangeandex-cludingland-usechangeﬂuxes)wereobtainedwithS2runsfromDGVMsupto2021fromtheTRENDYv11dataset.ResultswereﬁrstmaskedwithaforestmapthatisbasedonHansen(Hansenetal.,2013)treecoverdata.Todothiscon-version(“tree”coverto“forest”cover),weexcludegridcellswithlessthan20%treecoverandisolatedpixelswithmaxi-mumconnectivitylessthan0.5hafollowingtheFAOdeﬁni-tionofforest.ForestNBPsarethenfurthermaskedwiththe“intact”forestmapfortheyear2013,i.e.forestareaschar-acterizedbynoremotelydetectedsignsofhumanactivity(Potapovetal.,2017).Thisway,weobtainedtheSLANDin“intact”and“non-intact”forestarea,whichpreviousstudies(Grassietal.,2021)indicatedtobeagoodproxy,respec-tively,for“unmanaged”and“managed”forestareaintheNGHGI.Notethatonlyfourmodels(CABLE-POP,CLAS-SIC,JSBACHandYIBs)hadforestNBPatgrid-celllevel.FortheotherDGVMs,whenagridcellhadforest,alltheNBPwasallocatedtoforest.However,sinceS2simulationsusepre-industrialforestcovermasksthatareatleast20%largerthantoday’sforest(Hurttetal.,2020),wecorrectedthisNBPusingaratiobetweenobserved(basedonHansenetal.,2013)andprescribed(fromDGVMs)forestcover.ThisratioiscalculatedforeachindividualDGVMthatprovidesinformationonprescribedforestcover(LPX-Bern,OCN,JULES,VISIT,VISIT-NIES,SDGVM).Fortheothers(IBIS,CLM5.0,ORCHIDEE,ISAM,DLEM,LPJ-GUESS),acom-monratio(medianratioofallthe10modelsthatprovidein-formationonprescribedforestcover)isused.ThedetailsofthemethodusedareexplainedinAlkama(2022).LULUCFdatafromNGHGIsarefromGrassietal.(2022a).WhileAnnexIcountriesreportacompletetimeseries1990–2020,fornon-AnnexIcountriesgap-ﬁllingmea-sureswereappliedthroughlinearinterpolationbetweentwopointsand/orthroughextrapolationbackward(till1990)andforward(till2020)usingthesingleclosestavailabledatapoint.Forallcountries,theestimatesoftheyear2021areassumedtobeequaltothoseof2020.ThesedataincludeallCO2ﬂuxesfromlandconsideredmanaged,whichinprinci-pleencompassesalllanduses(forestland,cropland,grass-land,wetlands,settlements,andotherland),changesamongthem,andemissionsfromorganicsoilsandﬁres.Inprac-tice,althoughalmostallAnnexIcountriesreportalllanduses,manynon-AnnexIcountriesreportonlyondeforesta-tionandforestland,andonlyfewcountriesreportonotherlanduses.Inmostcases,NGHGIsincludemostofthenat-uralresponsetorecentenvironmentalchangebecausetheyusedirectobservations(e.g.nationalforestinventories)thatdonotallowforseparatingdirectandindirectanthropogeniceffects(Egglestonetal.,2006).Toprovideadditional,largelyindependentassessmentsofﬂuxesonunmanagedvs.managedlands,weincludeaDGVMthatallowsdiagnosingﬂuxesfromunmanagedvs.managedlandsbytrackingvegetationcohortsofdifferentagesseparately.Thismodel,ORCHIDEE-MICT(Yueetal.,2018),wasrunusingthesameLUH2forcingastheDGVMsusedinthisbudget(Sect.2.5)andthebookkeepingmodelsBLUEandOSCAR(Sect.2.2).Old-agedforestwasclassi-ﬁedasprimaryforestafteracertainthresholdofcarbonden-sitywasreachedagain,andthemodel-internaldistinctionbe-tweenprimaryandsecondaryforestwasusedaproxyforun-managedvs.managedforests;agriculturallandsareaddedtothelattertoarriveattotalmanagedland.TableA8showstheresultingmappingofglobalcarboncyclemodels’landﬂuxdeﬁnitionstothatoftheNGHGI(discussedinSect.3.2.2).ORCHIDEE-MICTestimatesforSLANDonintactforestsareexpectedtobehigherthanbasedonDGVMsincombinationwiththeNGHGImanagedandunmanagedforestdatabecausetheunmanagedforestarea,withabout27×106km2,isestimatedtobesubstantiallylargerbyORCHIDEE-MICTthanbytheNGHGI(lessthan10×106km2),whilemanagedforestareaisestimatedtobesmaller(22comparedto32×106km2).Relatedtothis,ELUCplusSLANDonnon-intactlandsisalargersourceesti-matedbyORCHIDEE-MICTcomparedtoNGHGI.WealsoshowFAOSTATemissionstotals(FAO,2021)asacompari-son,whichincludeemissionsfromnetforestconversionandﬂuxesonforestland(Tubielloetal.,2021)andCO2emis-sionsfrompeatdrainageandpeatﬁres.The2021datawereestimatedbyincludingactual2021estimatesforpeatlanddrainageandﬁreandacarryforwardfrom2020to2021fortheforestlandstockchange.TheFAOdatashowsaglobalsourceof0.24GtCyr−1averagedover2012–2021,incontrasttothesinkof−0.54GtCyr−1ofthegap-ﬁlledNGHGIdata.Mostofthisdifferenceisattributabletodif-ferentscopes:afocusoncarbonﬂuxesfortheNGHGIandafocusonareaandbiomassforFAO.Inparticular,theNGHGIdataincludesalargerforestsinkfornon-Annex1countriesresultingfromamorecompletecoverageofnon-biomasscarbonpoolsandnon-forestlanduses.NGHGIandFAOdataalsodifferintermsofunderlyingdataonforestland(Grassietal.,2022a).C2.4UncertaintyassessmentforELUCDifferencesbetweenthebookkeepingmodelsandDGVMsmodelsoriginatefromthreemainsources:thedifferentmethodologies,whichamongothersleadtoinclusionofthelossofadditionalsinkcapacityinDGVMs(seeAp-pendixD1.4),theunderlyingland-useorland-coverdataset,andthedifferentprocessesrepresented(TableA1).Weex-aminetheresultsfromtheDGVMsmodelsandofthebook-keepingmethodandusetheresultingvariationsasawaytocharacterizetheuncertaintyinELUC.Despitethesedifferences,theELUCestimatefromtheDGVMsmulti-modelmeanisconsistentwiththeaverageoftheemissionsfromthebookkeepingmodels(Table5).How-ever,therearelargedifferencesamongindividualDGVMshttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224874P.Friedlingsteinetal.:GlobalCarbonBudget2022(standarddeviationataround0.5GtCyr−1;Table5),be-tweenthebookkeepingestimates(averagedifference1850–2020BLUE-updatedH&N2017of0.8GtCyr−1,BLUE-OSCARof0.4GtCyr−1,OSCAR-updatedH&N2017of0.3GtCyr−1),andbetweentheupdatedestimateofH&N2017anditspreviousmodelversion(Houghtonetal.,2012).AfactorialanalysisofdifferencesbetweenBLUEandH&N2017attributedthemparticularlytodifferencesincar-bondensitiesbetweennaturalandmanagedvegetationorpri-maryandsecondaryvegetation(Bastosetal.,2021).Ear-lierstudiesadditionallyshowedtherelevanceofthediffer-entland-useforcingasapplied(inupdatedversions)alsointhecurrentstudy(Gasseretal.,2020).Ganzenmülleretal.(2022)recentlyshowedthatELUCestimateswithBLUEaresubstantiallysmallerwhenthemodelisdrivenbyanewhigh-resolutionland-usedataset(HILDA+).TheyidentiﬁedshiftingcultivationandthewayitisimplementedinLUH2asamainreasonforthisdivergence.Theyfurthershowedthatahigherspatialresolutionreducestheestimatesofbothsourcesandsinksbecausesuccessivetransitionsarenotade-quatelyrepresentedatcoarserresolution,whichhastheeffectthat–despitecapturingthesameextentoftransitionareas–overalllessarearemainspristineatthecoarsercomparedtothehigherresolution.TheuncertaintyinELUCof±0.7GtCyr−1reﬂectsourbestvaluejudgementthatthereisatleast68%chance(±1σ)thatthetrueland-usechangeemissionlieswithinthegivenrangefortherangeofprocessesconsideredhere.Priortotheyear1959,theuncertaintyinELUCwastakenfromthestan-darddeviationoftheDGVMs.WeassignlowconﬁdencetotheannualestimatesofELUCbecauseoftheinconsistenciesamongestimatesandofthedifﬁcultiesinquantifyingsomeoftheprocessesinDGVMs.C2.5EmissionsprojectionsforELUCWeprojectthe2022land-useemissionsforBLUE,theup-datedH&N2017,andOSCAR,startingfromtheirestimatesfor2021assumingunalteredpeatdrainage,whichhaslowin-terannualvariability,andthehighlyvariableemissionsfrompeatﬁres,tropicaldeforestationanddegradationasestimatedusingactiveﬁredata(MCD14ML;Giglioetal.,2016).TheselattervariablesscalealmostlinearlywithGFEDoverlargeareas(vanderWerfetal.,2017),andthustheyallowfortrackingﬁreemissionsindeforestationandtropicalpeatzonesinnear-realtime.C3Methodology:oceanCO2sinkC3.1Observation-basedestimatesWeprimarilyusetheobservationalconstraintsassessedbyIPCCofameanoceanCO2sinkof2.2±0.7GtCyr−1forthe1990s(90%conﬁdenceinterval;Ciaisetal.,2013)toverifythattheGOBMsprovidearealisticassessmentofSOCEAN.Thisisbasedonindirectobservationswithsevendifferentmethodologiesandtheiruncertaintiesandfurtheruseofthethreeofthesemethodsthataredeemedmostre-liablefortheassessmentofthisquantity(Denmanetal.,2007;Ciaisetal.,2013).Theobservation-basedestimatesusetheocean–landCO2sinkpartitioningfromobservedatmosphericCO2andO2/N2concentrationtrends(Man-ningandKeeling,2006;KeelingandManning,2014),anoceanicinversionmethodconstrainedbyoceanbiogeochem-istrydata(MikaloffFletcheretal.,2006),andamethodbasedonpenetrationtimescaleforchloroﬂuorocarbons(Mc-Neil,2003).TheIPCCestimateof2.2GtCyr−1forthe1990sisconsistentwitharangeofmethods(Wanninkhofetal.,2013).WerefrainfromusingtheIPCCestimatesforthe2000s(2.3±0.7GtCyr−1)andtheperiod2002–2011(2.4±0.7GtCyr−1,Ciaisetal.,2013),asthesearebasedontrendsderivedmainlyfrommodelsandonedataprod-uct(Ciaisetal.,2013).AdditionalconstraintssummarizedinAR6(Canadelletal.,2021)aretheinterioroceananthro-pogeniccarbonchange(Gruberetal.,2019)andoceansinkestimatesfromatmosphericCO2andO2/N2(Tohjimaetal.,2019),whichareusedformodelevaluationanddiscussion,respectively.WealsouseeightestimatesoftheoceanCO2sinkanditsvariabilitybasedonsurfaceoceanfCO2mapsobtainedbytheinterpolationofsurfaceoceanfCO2measurementsfrom1990onwardsduetosevererestrictionsondataavailabilitypriorto1990(Fig.10).Theseestimatesdifferinmanyre-spects:theyusedifferentmapsofsurfacefCO2,atmosphericCO2concentrations,windproducts,andgasexchangefor-mulationsasspeciﬁedinTableA3.WerefertothemasfCO2-basedﬂuxestimates.ThemeasurementsunderlyingthesurfacefCO2mapsarefromtheSurfaceOceanCO2At-lasversion2022(SOCATv2022;Bakkeretal.,2022),whichisanupdateofversion3(Bakkeretal.,2016)andcontainsquality-controlleddatathrough2021(seedataattributionTa-bleA5).EachoftheestimatesusesadifferentmethodtothenmaptheSOCATv2022datatotheglobalocean.Themethodsincludeadata-drivendiagnosticmethodcombinedwithamulti-linearregressionapproachtoextendbackto1957(Rödenbecketal.,2022;referredtohereasJena-MLS),threeneuralnetworkmodels(Landschützeretal.,2014;re-ferredtoasMPI-SOMFFN;Chauetal.,2022;CopernicusMarineEnvironmentMonitoringService,referredtohereasCMEMS-LSCE-FFNN;andZengetal.,2014;referredtoasNIES-NN),aclusterregressionapproach(GregorandGru-ber,2021,referredtoasOS-ETHZ-GRaCER),amulti-linearregressionmethod(Iidaetal.,2021;referredtoasJMA-MLR),andamethodthatrelatesthefCO2misﬁtbetweenGOBMsandSOCATtoenvironmentalpredictorsusingtheextremegradient-boostingmethod(Gloegeetal.,2022).TheensemblemeanofthefCO2-basedﬂuxestimatesiscalcu-latedfromthesesevenmappingmethods.Further,weshowtheﬂuxestimateofWatsonetal.(2020),whoalsousetheMPI-SOMFFNmethodtomaptheadjustedfCO2datatotheglobe,resultinginasubstantiallylargeroceansinkesti-EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224875mateowingtoanumberofadjustmentstheyappliedtothesurfaceoceanfCO2data.Concretely,theseauthorsadjustedtheSOCATfCO2downwardtoaccountfordifferencesintemperaturebetweenthedepthoftheshipintakeandtherel-evantdepthrightnearthesurface,andtheyincludedafurtheradjustmenttoaccountforthecoolsurfaceskintemperatureeffect.TheWatsonetal.(2020)ﬂuxestimatehencediffersfromtheothersbytheirchoiceofadjustingtheﬂuxtoacool,saltyoceansurfaceskin.Watsonetal.(2020)showedthatthistemperatureadjustmentleadstoanupwardcorrectionoftheoceancarbonsink,upto0.9GtCyr−1,that,ifcorrect,shouldbeappliedtoallfCO2-basedﬂuxestimates.Are-ductionofthisadjustmentto0.6GtCyr−1wasproposedbyDongetal.(2022).Theimpactofthecoolskineffectonair–seaCO2ﬂuxisbasedonestablishedunderstandingoftemperaturegradients(asdiscussedbyGoddijn-Murphyetal2015)andlaboratoryobservations(JähneandHaußecker,1998;Jähne,2019),butinsituﬁeldobservationalevidenceislacking(Dongetal.,2022).TheWatsonetal.(2020)ﬂuxestimatepresentedhereisthereforenotincludedintheen-semblemeanofthefCO2-basedﬂuxestimates.Thischoicewillbere-evaluatedinupcomingbudgetsbasedonfurtherlinesofevidence.Typically,dataproductsdonotcovertheentireoceanduetomissingcoastaloceansandseaicecover.TheCO2ﬂuxfromeachfCO2-basedproductisalreadyatorabove99%coverageoftheice-freeoceansurfaceareaintwoprod-ucts(Jena-MLS,OS-ETHZ-GRaCER)andﬁlledbythedataproviderinthreeproducts(usingtheFayetal.,2021,methodforJMA-MLRandLDEO-HPDandtheLandschützeretal.,2020,methodologyforMPI-SOMFFN).Theproductsthatremainedbelow99%coverageoftheice-freeocean(CMEMS-LSCE-FFNN,MPI-SOMFFN,NIES-NN,UOx-Watson)werescaledbythefollowingprocedure.InpreviousversionsoftheGCB,themissingareaswereaccountedforbyscalingthegloballyintegratedﬂuxesbythefractionoftheglobaloceancoverage(361.9×106km2basedonETOPO1,AmanteandEakins,2009;EakinsandShar-man,2010)withtheareacoveredbytheCO2ﬂuxpredic-tions.Thisapproachmayleadtounnecessaryscalingwhenthemajorityofthemissingdataareintheice-coveredregion(asisoftenthecase),whereﬂuxisalreadyassumedtobezero.Toavoidthisunnecessaryscaling,wenowscaleﬂuxesregionally(north,tropics,south)tomatchtheice-freearea(usingNOAA’sOISSTv2;Reynoldsetal.,2002):FCOreg-scaled2=Aregion(1−ice)AregionFCO2·FCOregion2.(C4)InEq.(C4),Arepresentsarea,(1−ice)representstheice-freeocean,AregionFCO2representsthecoverageofthedataproductforaregion,andFCOregion2istheintegratedﬂuxforaregion.Wefurtheruseresultsfromtwodiagnosticoceanmod-els,Khatiwalaetal.(2013)andDeVries(2014),toestimatetheanthropogeniccarbonaccumulatedintheoceanpriorto1959.Thetwoapproachesassumeconstantoceancircula-tionandbiologicalﬂuxes,withSOCEANestimatedasare-sponseinthechangeinatmosphericCO2concentrationcali-bratedtoobservations.Theuncertaintyincumulativeuptakeof±20GtC(convertedto±1σ)istakendirectlyfromtheIPCC’sreviewoftheliterature(Rheinetal.,2013)orabout±30%fortheannualvalues(Khatiwalaetal.,2009).C3.2Globaloceanbiogeochemistrymodels(GOBMs)TheoceanCO2sinkfor1959–20121isestimatedusing10GOBMs(TableA2).TheGOBMsrepresentthephysical,chemical,andbiologicalprocessesthatinﬂuencethesur-faceoceanconcentrationofCO2andthustheair–seaCO2ﬂux.TheGOBMsareforcedbymeteorologicalreanalysisandatmosphericCO2concentrationdataavailablefortheen-tiretimeperiod.Theymostlydifferinthesourceoftheat-mosphericforcingdata(meteorologicalreanalysis),spin-upstrategies,andhorizontalandverticalresolutions(TableA2).AllGOBMsexcepttwo(CESM-ETHZ,CESM2)donotin-cludetheeffectsofanthropogenicchangesinnutrientsupply(Duceetal.,2008).Theyalsodonotincludetheperturba-tionassociatedwithchangesinriverineorganiccarbon(seeSect.2.7andAppendixD3).FoursetsofsimulationswereperformedwitheachoftheGOBMs.SimulationAappliedhistoricalchangesinclimateandatmosphericCO2concentration.SimulationBisacon-trolsimulationwithconstantatmosphericforcing(normal-yearorrepeated-yearforcing)andconstantpre-industrialat-mosphericCO2concentration.SimulationCisforcedwithhistoricalchangesinatmosphericCO2concentrationbutrepeated-yearornormal-yearatmosphericclimateforcing.SimulationDisforcedbyhistoricalchangesinclimateandconstantpre-industrialatmosphericCO2concentration.ToderiveSOCEANfromthemodelsimulations,wesubtractedtheslopeofalinearﬁttotheannualtimeseriesofthecontrolsimulationBfromtheannualtimeseriesofsimulationA.As-sumingthatdriftandbiasarethesameinsimulationsAandB,wetherebycorrectforanymodeldrift.Further,thisdiffer-encealsoremovesthenaturalsteady-stateﬂux(assumedtobe0GtCyr−1globallywithoutrivers),whichisoftenamajorsourceofbiases.Thisapproachworksforallmodelset-ups,includingIPSL,wheresimulationBwasforcedwithconstantatmosphericCO2butobservedhistoricalchangesinclimate(equivalenttosimulationD).ThisapproachassuresthattheinterannualvariabilityisnotremovedfromIPSLsimulationA.Theabsolutecorrectionforbiasanddriftpermodelinthe1990svariedbetween<0.01and0.41GtCyr−1,withsevenmodelshavingpositivebiases,twohavingnegativebiases,andonehavingessentiallynobias(NorESM).TheMPImodelusesriverineinputandthereforesimulatesout-gassinginsimulationB.BysubtractingsimulationB,theoceancarbonsinkoftheMPImodelalsofollowsthedeﬁ-https://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224876P.Friedlingsteinetal.:GlobalCarbonBudget2022nitionofSOCEAN.Thiscorrectionreducesthemodelmeanoceancarbonsinkby0.04GtCyr−1inthe1990s.Theoceanmodelscover99%to101%ofthetotaloceanareasothatareascalingisnotnecessary.C3.3GOBMevaluationanduncertaintyassessmentforSOCEANTheoceanCO2sinkforallGOBMsandtheensemblemeanfallswithin90%conﬁdenceoftheobservedrange,or1.5to2.9GtCyr−1,forthe1990s(Ciaisetal.,2013)beforeandafterapplyingadjustments.AnexceptionistheMPImodel,whichsimulatesalowoceancarbonsinkof1.38GtCyr−1forthe1990sinsimulationAowingtothein-clusionofriverinecarbonﬂux.AfteradjustingtotheGCB’sdeﬁnitionofSOCEANbysubtractingsimulationB,theMPImodelfallsintotheobservedrangewithanestimatedsinkof1.69GtCyr−1.TheGOBMsanddataproductshavebeenfurthereval-uatedusingthefugacityofseasurfaceCO2(fCO2)fromtheSOCATv2022database(Bakkeretal.,2016,2022).Wefocusedthisevaluationontheroot-mean-squarederror(RMSE)betweenobservedandmodelledfCO2andonameasureoftheamplitudeoftheinterannualvariabilityoftheﬂux(modiﬁedafterRödenbecketal.,2015).TheRMSEiscalculatedfromdetrended,annuallyandregionallyaveragedtimeseriescalculatedfromGOBMsanddataproductfCO2subsampledtoSOCATsamplingpointstomeasurethemisﬁtbetweenlarge-scalesignals(Haucketal.,2020).Tothisend,weapplythefollowingsteps:(i)subsampledatapointsforwhichthereareobservations(GOBMsordataproductsandSOCAT),(ii)averagespatially,(iii)calculateannualmean,(iv)detrendbothtimeseries(GOBMsordataproductsandSOCAT),and(v)calculateRMSE.Thisyear,wedonotap-plyanopen-oceanmaskof400mbutinsteadamaskbasedontheminimumareacoverageofthedat-products.Thisen-suresafaircomparisonoverequalareas.TheamplitudeoftheSOCEANinterannualvariability(A-IAV)iscalculatedasthetemporalstandarddeviationofthedetrendedannualCO2ﬂuxtimeseriesafterareascaling(Rödenbecketal.,2015;Haucketal.,2020).ThesemetricsarechosenbecauseRMSEisthemostdirectmeasureofdata–modelmismatch,andtheA-IAVisadirectmeasureofthevariabilityofSOCEANonin-terannualtimescales.Weapplythesemetricsgloballyandbylatitudebands.ResultsareshowninFig.B2anddiscussedinSect.3.5.5.Wequantifythe1σuncertaintyaroundthemeanoceansinkofanthropogenicCO2byassessingrandomandsys-tematicuncertaintiesfortheGOBMsanddata-products.Therandomuncertaintiesaretakenfromtheensemblestan-darddeviation(0.3GtCyr−1forGOBMs,0.3GtCyr−1fordata-products).WederivetheGOBMssystematicuncer-taintybythedeviationoftheDICinventorychange1994–2007fromtheGruberetal.(2019)estimate(0.4GtCyr−1)andsuggestthesearerelatedtophysicaltransport(mix-ing,advection)intotheoceaninterior.Forthedataprod-ucts,weconsidersystematicuncertaintiesstemmingfromuncertaintyinfCO2observations(0.2GtCyr−1,Takahashietal.,2009;Wanninkhofetal.,2013),gastransferve-locity(0.2GtCyr−1,Hoetal.,2011;Wanninkhofetal.,2013;Roobaertetal.,2018),windproduct(0.1GtCyr−1,Fayetal.,2021),riverﬂuxadjustment(0.3GtCyr−1,Reg-nieretal.,2022,formally2σuncertainty),andfCO2map-ping(0.2GtCyr−1,Landschützeretal.,2014).Combin-ingtheseuncertaintiesastheirsquaredsums,weassignanuncertaintyof±0.5GtCyr−1totheGOBMensemblemeanandanuncertaintyof±0.6GtCyr−1tothedataprod-uctensemblemean.Theseuncertaintiesarepropagatedasσ(SOCEAN)=(1/22×0.52+1/22×0.62)1/2GtCyr−1andre-sultinan±0.4GtCyr−1uncertaintyaroundthebestestimateofSOCEAN.Weexaminetheconsistencybetweenthevariabilityofthemodel-basedandthefCO2-baseddataproductstoas-sessconﬁdenceinSOCEAN.Theinterannualvariabilityoftheoceanﬂuxes(quantiﬁedasA-IAV,thestandarddeviationaf-terdetrending,Fig.B2)ofthesevenfCO2-baseddataprod-uctsplustheWatsonetal.(2020)productfor1990–2021rangesfrom0.12to0.32GtCyr−1,withthelowerestimatescomingfromthetwoensemblemethods(CMEMS-LSCE-FFNN,OS-ETHZ-GRaCER).TheinterannualvariabilityintheGOBMsrangesbetween0.09and0.20GtCyr−1;hence,thereisoverlapwiththelowerA-IAVestimatesoftwodataproducts.Individualestimates(bothGOBMsanddataproducts)generallyproduceahigheroceanCO2sinkduringstrongElNiñoevents.ThereisemergingagreementbetweenGOBMsanddataproductsonthepatternsofdecadalvariabilityofSOCEAN,withaglobalstagnationinthe1990sandanextra-tropicalstrengtheninginthe2000s(McKinleyetal.,2020;Haucketal.,2020).ThecentralestimatesoftheannualﬂuxfromtheGOBMsandthefCO2-baseddataproductshaveacorrelationrof0.94(1990–2021).Theagreementbetweenthemodelsandthedataproductsreﬂectssomeconsistencyintheirrepresentationofunderlyingvariabilitysincethereislittleoverlapintheirmethodologyoruseofobservations.C4Methodology:landCO2sinkC4.1DGVMsimulationsTheDGVMsmodelrunswereforcedbyeitherthemergedmonthlyClimateResearchUnit(CRU)and6-hourlyJapanese55-yearReanalysis(JRA-55)datasetorbythemonthlyCRUdataset,withbothprovidingobservation-basedtemperature,precipitation,andincomingsurfacera-diationdataona0.5◦×0.5◦gridupdatedto2021(Harrisetal.,2014,2020).ThecombinationofCRUmonthlydatawith6-hourlyforcingfromJRA-55(Kobayashietal.,2015)isperformedwithmethodologyusedinpreviousyears(Viovy,2016)adaptedtothespeciﬁcsoftheJRA-55data.EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224877IntroducedinGCB2021(Friedlingsteinetal.,2022a),in-comingshort-waveradiationﬁeldsareusedtotakeintoac-countaerosolimpactsandthedivisionoftotalradiationintodirectanddiffusecomponentsassummarizedbelow.Thediffusefractiondatasetoffers6-hourlydistributionsofthediffusefractionofsurfaceshort-waveﬂuxesovertheperiod1901–2021.Radiativetransfercalculationsarebasedonmonthlyaverageddistributionsoftroposphericandstrato-sphericaerosolopticaldepthand6-hourlydistributionsofcloudfraction.MethodsfollowthosedescribedintheMeth-odssectionofMercadoetal.(2009)butwithupdatedinputdatasets.ThetimeseriesofspeciatedtroposphericaerosolopticaldepthistakenfromthehistoricalandRCP8.5simulationsbytheHadGEM2-ESclimatemodel(Bellouinetal.,2011).TocorrectforbiasesinHadGEM2-ES,troposphericaerosolopticaldepthsarescaledoverthewholeperiodtomatchtheglobalandmonthlyaveragesobtainedovertheperiod2003–2020bytheCAMSreanalysisofatmosphericcomposition(Innessetal.,2019),whichassimilatessatelliteretrievalsofaerosolopticaldepth.ThetimeseriesofstratosphericaerosolopticaldepthistakenfromtheclimatologyofSatoetal.(1993),whichhasbeenupdatedto2012.Theyears2013–2020areassumedtobebackgroundyearsandthusreplicatethebackgroundyear2010.ThatassumptionissupportedbytheGlobalSpace-basedStratosphericAerosolClimatologytimeseries(1979–2016;Thomasonetal.,2018).Thetimeseriesofcloudfrac-tionisobtainedbyscalingthe6-hourlydistributionssim-ulatedintheJapaneseReanalysis(Kobayashietal.,2015)tomatchthemonthlyaveragedcloudcoverintheCRUTSv4.06dataset(Harrisetal.,2020).Surfaceradiativeﬂuxesaccountforaerosol–radiationinteractionsfrombothtropo-sphericandstratosphericaerosolsandforaerosol–cloudin-teractionsfromtroposphericaerosols(exceptmineraldust).Troposphericaerosolsarealsoassumedtoexertinteractionswithclouds.Theradiativeeffectsofthoseaerosol–cloudinteractionsareassumedtoscalewiththeradiativeeffectsofaerosol–radiationinteractionsoftroposphericaerosolsusingregionalscalingfactorsderivedfromHadGEM2-ES.Diffusefractionisassumedtobe1incloudysky.Atmosphericconstituentsotherthanaerosolsandcloudsaresettoaconstantstandardmid-latitudesummeratmosphere,buttheirvariationsdonotaffectthediffusefractionofsurfaceshort-waveﬂuxes.Insummary,theDGVMsforcingdataincludetime-dependentgriddedclimateforcing,globalatmosphericCO2(DlugokenckyandTans,2022),griddedlandcoverchanges(seeAppendixC2.2),andgriddednitrogendepositionandfertilizers(seeTableA1forspeciﬁcmodelsdetails).FoursimulationswereperformedwitheachoftheDGVMs.Simulation0(S0)isacontrolsimulationthatusesﬁxedpre-industrial(year1700)atmosphericCO2con-centrations,cyclesearly20thcentury(1901–1920)climate,andappliesatime-invariantpre-industriallandcoverdistri-butionandpre-industrialwoodharvestrates.Simulation1(S1)differsfromS0byapplyinghistoricalchangesinat-mosphericCO2concentrationandNinputs.Simulation2(S2)applieshistoricalchangesinatmosphericCO2concen-tration,Ninputs,andclimate,whileapplyingtime-invariantpre-industriallandcoverdistributionandpre-industrialwoodharvestrates.Simulation3(S3)applieshistoricalchangesinatmosphericCO2concentration,Ninputs,climate,landcoverdistribution,andwoodharvestrates.S2isusedtoestimatethelandsinkcomponentoftheglobalcarbonbudget(SLAND).S3isusedtoestimatethetotallandﬂuxbutisnotusedintheglobalcarbonbudget.Wefur-therseparateSLANDintocontributionsfromCO2(=S1–S0)andclimate(=S2−S1+S0).C4.2DGVMevaluationanduncertaintyassessmentforSLANDWeapplythreecriteriaforminimumDGVMrealismbyincludingonlythoseDGVMswith(1)steadystateafterspinup,(2)globalnetlandﬂux(SLAND−ELUC),i.e.anatmosphere-to-landcarbonﬂuxoverthe1990srangingbe-tween−0.3and2.3GtCyr−1within90%conﬁdenceofconstraintsbyglobalatmosphericandoceanicobservations(KeelingandManning,2014;Wanninkhofetal.,2013),and(3)globalELUCthatisacarbonsourcetotheatmosphereoverthe1990s,asalreadymentionedinAppendixC2.2.AllDGVMsmeetthesethreecriteria.Inaddition,theDGVMsresultsarealsoevaluatedus-ingtheInternationalLandModelBenchmarkingsystem(IL-AMB;Collieretal.,2018).Thisevaluationisprovidedheretodocument,encourage,andsupportmodelimprove-mentsthroughtime.ILAMBvariablescoverkeyprocessesthatarerelevantforthequantiﬁcationofSLANDandresult-ingaggregatedoutcomes.Theselectedvariablesarevege-tationbiomass,grossprimaryproductivity,leafareaindex,netecosystemexchange,ecosystemrespiration,evapotran-spiration,soilcarbon,andrunoff(seeFig.B3fortheresultsandforthelistofobserveddatabases).ResultsareshowninFig.B3anddiscussedinSect.3.6.5.FortheuncertaintyforSLAND,weusethestandarddevia-tionoftheannualCO2sinkacrosstheDGVMs,averagingtoabout±0.6GtCyr−1fortheperiod1959to2021.WeattachamediumconﬁdenceleveltotheannuallandCO2sinkanditsuncertaintybecausetheestimatesfromtheresidualbud-getandaveragedDGVMsmatchwellwithintheirrespectiveuncertainties(Table5).C5Methodology:atmosphericinversionsC5.1InversionsystemsimulationsNineatmosphericinversions(detailsofeacharegiveninTa-bleA4)wereusedtoinferthespatio-temporaldistributionoftheCO2ﬂuxexchangedbetweentheatmosphereandthehttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224878P.Friedlingsteinetal.:GlobalCarbonBudget2022landoroceans.TheseinversionsarebasedonBayesianin-versionprincipleswithpriorinformationonﬂuxesandtheiruncertainties.Theyuseverysimilarsetsofsurfacemeasure-mentsofCO2timeseries(orsubsetsthereof)fromvariousﬂaskandinsitunetworks.OneinversionsystemalsousedsatellitexCO2retrievalsfromGOSATandOCO-2.EachinversionsystemusesdifferentmethodologiesandinputdatabutisrootedinBayesianinversionprinciples.Thesedifferencesmainlyconcerntheselectionoftheatmo-sphericCO2data,priorﬂuxes,spatialresolution,assumedcorrelationstructures,andmathematicalapproachesofthemodels.Eachsystemusesadifferenttransportmodel,whichwasdemonstratedtobeadrivingfactorbehinddifferencesinatmosphericinversion-basedﬂuxestimatesandspeciﬁ-callytheirdistributionacrosslatitudinalbands(Gaubertetal.,2019;Schuhetal.,2019).Theinversionsystemsallprescribesimilarglobalfos-silfuelemissionsforEFOS;speciﬁcally,theGCP’sGriddedFossilEmissionsDatasetversion2022(GCP-GridFEDv2022.2;Jonesetal.,2022),whichisanupdatethrough2021oftheﬁrstversionofGCP-GridFEDpre-sentedbyJonesetal.(2021),oranotherrecentversionofGCP-GridFED(TableA4).AllGCP-GridFEDversionsscalegriddedestimatesofCO2emissionsfromEDGARv4.3.2(Janssens-Maenhoutetal.,2019)withinnationalterrito-riestomatchnationalemissionsestimatesprovidedbytheGCPfortheyears1959–2021,whicharecompiledfol-lowingthemethodologydescribedinAppendixC1.GCP-GridFEDv2022.2adoptstheseasonalityofemissions(themonthlydistributionofannualemissions)fromtheCarbonMonitor(Liuetal.,2020a,b;Douetal.,2022)forBrazil,China,allEU27countries,theUnitedKingdom,theUSA,andshippingandaviationbunkeremissions.TheseasonalitypresentinCarbonMonitorisuseddirectlyforyears2019–2021,whileforyears1959–2018theaverageseasonalityof2019and2021areapplied(avoidingtheyear2020duringwhichemissionsweremostimpactedbytheCOVID-19pan-demic).Forallothercountries,seasonalityofemissionsistakenfromEDGAR(Janssens-Maenhoutetal.,2019;Jonesetal.,2022),withasmallannualcorrectiontotheseasonalitypresentinyear2010basedonheatingorcoolingdegreedaystoaccountfortheeffectsofinterannualclimatevariabilityontheseasonalityofemissions(Jonesetal.,2021).EarlierversionsofGridFEDusedCarbonMonitor-basedseasonal-ityonlyfrom2019onwards.Inaddition,wenotethatGCP-GridFEDv2022.1andv2022.2includeemissionsfromce-mentproductionandthecementcarbonationCO2sink(Ap-pendixC1.1),whereasearlierversionsofGCP-GridFEDdidnotincludethecementcarbonationCO2sink.TheconsistentuseofrecentversionsofGCP-GridFEDforEFOSensuresaclosealignmentwiththeestimateofEFOSusedinthisbudgetassessment,enhancingthecomparabilityoftheinversion-basedestimatewiththeﬂuxestimatesde-rivingfromDGVMs,GOBMs,andfCO2-basedmethods.ToensurethattheestimateduptakeofatmosphericCO2bythelandandoceanswasfullyconsistentwiththesumofthefossilemissionsﬂuxfromGCP-GridFEDv2022.2andtheat-mosphericgrowthrateofCO2,smallcorrectionstothefossilfuelemissionsﬂuxwereappliedtoinversionssystemsusingotherversionsofGCP-GridFED.ThelandandoceanCO2ﬂuxesfromatmosphericinver-sionscontainanthropogenicperturbationandnaturalpre-industrialCO2ﬂuxes.Onannualtimescales,naturalpre-industrialﬂuxesareprimarilylandCO2sinksandoceanCO2sourcescorrespondingtocarbontakenuponland,trans-portedbyriversfromlandtoocean,andoutgassedbytheocean.Thesepre-industriallandCO2sinksarethuscompen-satedovertheglobebyoceanCO2sourcescorrespondingtotheoutgassingofriverinecarboninputstotheocean,usingtheexactsamenumbersanddistributionsasdescribedfortheoceansinSect.2.4.Tofacilitatethecomparison,weadjustedtheinverseestimatesofthelandandoceanﬂuxesperlatitudebandwiththesenumberstoproducehistoricalperturbationCO2ﬂuxesfrominversions.C5.2InversionsystemevaluationAllparticipatingatmosphericinversionsarecheckedforcon-sistencywiththeannualglobalgrowthrate,asbotharede-rivedfromtheglobalsurfacenetworkofatmosphericCO2observations.Inthisexercise,weusetheconversionfactorof2.086GtCppm−1toconverttheinvertedcarbonﬂuxestomolefractions,assuggestedbyPrather(2012).Thisnumberisspeciﬁcallysuitedforthecomparisontosurfaceobserva-tionsthatdonotresponduniformly(orimmediately)toeachyear’ssummedsourcesandsinks.ThisfactoristhereforeslightlysmallerthantheGCBconversionfactorinTable1(2.142GtCppm−1,Ballantyneetal.,2012).Overall,thein-versionsagreewiththegrowthrate,withbiasesbetween0.03and0.08ppm(0.06–0.17GtCyr−1)onthedecadalaverage.Theatmosphericinversionsarealsoevaluatedusingver-ticalproﬁlesofatmosphericCO2concentrations(Fig.B4).Morethan30aircraftprogrammesovertheglobe,eitherreg-ularprogrammesorrepeatedsurveysoveratleast9months,havebeenusedinordertodrawarobustpictureofthesys-temperformance(withspace–timedatacoveragethatisir-regularanddenserinthe0–45◦Nlatitudeband;TableA6).TheninesystemsarecomparedtotheindependentaircraftCO2measurementsbetween2and7kmabovesealevelbe-tween2001and2021.ResultsareshowninFig.B4,wheretheinversionsgenerallymatchtheatmosphericmolefrac-tionstowithin0.7ppmatalllatitudes,exceptforCTEu-ropein2011–2021overthemoresparselysampledSouthernHemisphere.EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224879AppendixD:ProcessesnotincludedintheglobalcarbonbudgetD1ContributionofanthropogenicCOandCH4totheglobalcarbonbudgetEquation(1)onlypartlyincludesthenetinputofCO2totheatmospherefromthechemicaloxidationofreactivecarbon-containinggasesfromsourcesotherthanthecombustionoffossilfuels,suchas(1)cementprocessemissions,sincethesedonotcomefromcombustionoffossilfuels,(2)theoxi-dationoffossilfuels,and(3)theassumptionofimmediateoxidationofventedmethaneinoilproduction.However,itomitsanyotheranthropogeniccarbon-containinggasesthatareeventuallyoxidizedintheatmosphere,formingadiffusesourceofCO2,suchasanthropogenicemissionsofCOandCH4.Anattemptismadeheretoestimatetheirmagnitudeandidentifythesourcesofuncertainty.AnthropogenicCOemissionsarefromincompletefossilfuelandbiofuelburninganddeforestationﬁres.ThemainanthropogenicemissionsoffossilCH4thatmatterfortheglobal(anthropogenic)carbonbudgetarethefugitiveemissionsofcoal,oil,andgassectors(seebelow).TheseemissionsofCOandCH4contributeanetadditionoffossilcarbontotheatmosphere.InourestimateofEFOS,weassumed(Sect.2.1.1)thatallthefuelburnedisemittedasCO2,andthusCOan-thropogenicemissionsassociatedwithincompletefossilfuelcombustionanditsatmosphericoxidationintoCO2withinafewmonthsarealreadycountedimplicitlyinEFOSandshouldnotbecountedtwice(sameforELUCandanthro-pogenicCOemissionsbydeforestationﬁres).Thediffuseat-mosphericsourceofCO2derivingfromanthropogenicemis-sionsoffossilCH4isnotincludedinEFOS.Inreality,thediffusesourceofCO2fromCH4oxidationcontributestotheannualCO2growth.EmissionsoffossilCH4represent30%oftotalanthropogenicCH4emissions(Saunoisetal.,2020;theirtop-downestimateisusedbecauseitisconsistentwiththeobservedCH4growthrate),i.e.0.083GtCyr−1forthedecade2008–2017.Assumingsteadystate,anamountequaltothisfossilCH4emissionisallconvertedtoCO2byOHoxidation,andthisthereforeexplains0.083GtCyr−1oftheglobalCO2growthrate,withanuncertaintyrangeof0.061to0.098GtCyr−1takenfromthemin–maxoftop-downes-timatesinSaunoisetal.(2020).Ifthismin–maxrangeisassumedtobe2σbecauseSaunoisetal.(2020)didnotac-countfortheinternaluncertaintyoftheirminimumandmax-imumtop-downestimates,ittranslatesintoa1σuncertaintyof0.019GtCyr−1.OtheranthropogenicchangesinthesourcesofCOandCH4fromwildﬁres,vegetationbiomass,wetlands,rumi-nants,orpermafrostchangesaresimilarlyassumedtohaveasmalleffectontheCO2growthrate.TheCH4andCOemissionsandsinksarepublishedandanalysedseparatelyintheglobalmethanebudgetandglobalcarbonmonoxidebudgetpublications,whichfollowasimilarapproachtothatpresentedhere(Saunoisetal.,2020;Zhengetal.,2019).D2ContributionofothercarbonatestoCO2emissionsAlthoughwedoaccountforcementcarbonation(acarbonsink),thecontributionofemissionsoffossilcarbonates(car-bonsources)otherthancementproductionisnotsystem-aticallyincludedinestimatesofEFOS,exceptforAnnexIcountriesandlimeproductioninChina(AndrewandPeters,2021).ThemissingprocessesincludeCO2emissionsasso-ciatedwiththecalcinationoflimeandlimestoneoutsideofcementproduction.Carbonatesarealsousedinvariousin-dustries,includinginironandsteelmanufactureandinagri-culture.Theyarefoundnaturallyinsomecoals.CO2emis-sionsfromfossilcarbonatesotherthancementnotincludedinourdatasetareestimatedtoamounttoabout0.3%ofEFOS(estimatedbasedonCrippaetal.,2019).D3Anthropogeniccarbonﬂuxesintheland-to-oceanaquaticcontinuumTheapproachusedtodeterminetheglobalcarbonbudgetreferstothemean,variations,andtrendsintheperturbationofCO2intheatmosphere,referencedtothepre-industrialera.Carboniscontinuouslydisplacedfromthelandtotheoceanthroughtheland–oceanaquaticcontinuum(LOAC)comprisingfreshwaters,estuaries,andcoastalareas(Baueretal.,2013;Regnieretal.,2013).Asubstantialfractionofthislateralcarbonﬂuxisentirely“natural”andisthusasteady-statecomponentofthepre-industrialcarboncycle.Weac-countforthispre-industrialﬂuxwhereappropriateinourstudy(seeAppendixC3).However,changesinenvironmen-talconditionsandland-usechangehavecausedanincreaseinthelateraltransportofcarbonintotheLOAC–apertur-bationthatisrelevantfortheglobalcarbonbudgetpresentedhere.TheresultsoftheanalysisofRegnieretal.(2013)canbesummarizedintwopointsofrelevancefortheanthro-pogenicCO2budget.First,theanthropogenicperturbationoftheLOAChasincreasedtheorganiccarbonexportfromterrestrialecosystemstothehydrospherebyasmuchas1.0±0.5GtCyr−1sincepre-industrialtimes,mainlyow-ingtoenhancedcarbonexportfromsoils.Second,thisex-portedanthropogeniccarbonispartlyrespiredthroughtheLOAC,partlysequesteredinsedimentsalongtheLOAC,andtoalesserextenttransferredtotheopenoceanwhereitmayaccumulateorbeoutgassed.Theincreaseinstorageofland-derivedorganiccarbonintheLOACcarbonreser-voirs(burial)andintheopenoceancombinedisestimatedbyRegnieretal.(2013)at0.65±0.35GtCyr−1.Theinclu-sionofLOAC-relatedanthropogenicCO2ﬂuxesshouldaf-fectestimatesofSLANDandSOCEANinEq.(1)butdoesnotaffecttheotherterms.RepresentationoftheanthropogenicperturbationofLOACCO2ﬂuxesis,however,notincludedhttps://doi.org/10.5194/essd-14-4811-2022EarthSyst.Sci.Data,14,4811–4900,20224880P.Friedlingsteinetal.:GlobalCarbonBudget2022intheGOBMsandDGVMsusedinourglobalcarbonbudgetanalysispresentedhere.D4LossofadditionallandsinkcapacityHistoricalland-coverchangewasdominatedbytransitionsfromvegetationtypesthatcanprovidealargecarbonsinkperareaunit(typically,forests)tootherslessefﬁcientinremovingCO2fromtheatmosphere(typically,croplands).Theresultantdecreaseinlandsink,calledthe“lossofad-ditionalsinkcapacity”,canbecalculatedasthedifferencebetweentheactuallandsinkunderchanginglandcoverandthecounterfactuallandsinkunderpre-industriallandcover.Thistermisnotaccountedforinourglobalcarbonbudgetes-timate.Here,weprovideaquantitativeestimateofthistermtobeusedinthediscussion.SevenoftheDGVMsusedinFriedlingsteinetal.(2019)performedadditionalsimulationswithandwithoutland-usechangeundercycledpre-industrialenvironmentalconditions.Theresultinglossofadditionalsinkcapacityamountsto0.9±0.3GtCyr−1onaverageover2009–2018and42±16GtCaccumulatedbetween1850and2018(Obermeieretal.,2021).OSCAR,emulatingthebe-haviourof11DGVMs,ﬁndsvaluesofthelossofadditionalsinkcapacityof0.7±0.6GtCyr−1and31±23GtCforthesametimeperiod(Gasseretal.,2020).SincetheDGVM-basedELUCestimatesareonlyusedtoquantifytheuncer-taintyaroundthebookkeepingmodels’ELUC,wedonotaddthelossofadditionalsinkcapacitytothebookkeepingesti-mate.Authorcontributions.PF,MOS,MWJ,RMA,LukG,JH,CLQ,ITL,AO,GPP,WP,JP,ClS,andSSdesignedthestudy,conductedtheanalysis,andwrotethepaperwithinputfromJGC,PC,andRBJ.RMA,GPPandJIKproducedthefossilfuelemissionsandtheirun-certaintiesandanalysedtheemissionsdata.MHandGMprovidedfossilfuelemissiondata.JP,ThoG,ClS,andRAHprovidedthebookkeepingland-usechangeemissionswithsynthesisbyJPandClS.JH,LB,ÖG,NG,TI,KL,NMa,LR,JS,RS,HiT,andReWprovidedanupdateoftheglobaloceanbiogeochemicalmodels.MG,LucG,LukG,YI,AJ,ChR,JDS,andJZprovidedanupdateoftheoceanfCO2dataproducts,withsynthesisonbothstreamsbyJH,LukG,andNMa.SRA,NRB,MB,HCB,MC,WE,RAF,ThaG,KK,NL,NMe,NMM,DRM,SN,TO,DP,KP,ChR,IS,TS,AJS,CoS,ST,TT,BT,RiW,CW,andAWprovidedoceanfCO2measurementsfortheyear2021,withsynthesisbyAOandKO.AA,VKA,SF,AKJ,EK,DK,JK,MJM,MOS,BP,QS,HaT,APW,WY,XY,andSZprovidedanupdateofthedynamicglobalvegeta-tionmodels,withsynthesisbySSandMOS.WP,ITL,FC,JL,YN,PIP,ChR,XT,andBZprovidedanupdatedatmosphericinversion.WP,FC,andITLdevelopedtheprotocolandproducedtheevalu-ation.RMAprovidedpredictionsofthe2022emissionsandatmo-sphericCO2growthrate.PLprovidedthepredictionsofthe2022oceanandlandsinks.LPC,GCH,KKG,TMR,andGRvdWpro-videdforcingdataforland-usechange.RA,GG,FT,andCYpro-videddatafortheland-usechangeNGHGImapping.PPTprovidedkeyatmosphericCO2data.MWJproducedthemodelatmosphericCO2forcingandtheatmosphericCO2growthrate.MOSandNBproducedtheaerosoldiffuseradiativeforcingfortheDGVMs.IHprovidedtheclimateforcingdatafortheDGVMs.ERprovidedtheevaluationoftheDGVMs.MWJprovidedtheemissionpriorsforuseintheinversionsystems.ZLprovidedseasonalemissionsdataformostrecentyearsfortheemissionprior.MWJandMOSde-velopedthenewdatamanagementpipeline,whichautomatesmanyaspectsofthedatacollation,analysis,plotting,andsynthesis.PF,MOS,andMMJcoordinatedtheeffortandrevisedallﬁgures,ta-bles,text,and/ornumberstoensuretheupdatewasclearfromthe2021editionandinlinewiththehttp://globalcarbonatlas.org(lastaccess:25September2022).Competinginterests.Atleastoneofthe(co-)authorsisamem-beroftheeditorialboardofEarthSystemScienceData.Thepeer-reviewprocesswasguidedbyanindependenteditor,andtheauthorsalsohavenoothercompetingintereststodeclare.Disclaimer.Publisher’snote:CopernicusPublicationsremainsneutralwithregardtojurisdictionalclaimsinpublishedmapsandinstitutionalafﬁliations.Acknowledgements.WethankallpeopleandinstitutionswhoprovidedthedatausedinthisGlobalCarbonBudget2022andtheGlobalCarbonProjectmembersfortheirinputthroughoutthede-velopmentofthispublication.WethankNigelHawtinforproducingFigs.2and14.WethankThomasHawesfortechnicalsupportwiththedatamanagementpipeline.WethankEdDlugokenckyforpro-vidingatmosphericCO2measurements.WethankIanG.C.Ash-ton,FatemehCheginig,TrangT.Chau,SamDitkovsky,ChristianEthé,AmandaR.Fay,LonnekeGoddijn-Murphy,ThomasHold-ing,FabriceLacroix,EnhuiLiao,GalenA.McKinley,ShijieShu,RichardSims,JadeSkye,AndrewJ.Watson,DavidWillis,andDavidK.Woolffortheirinvolvementinthedevelopment,use,andanalysisofthemodelsanddataproductsusedhere.DanielKennedythanksallthescientists,softwareengineers,andadmin-istratorswhocontributedtothedevelopmentofCESM2.WethankJoeSalisbury,DougVandemark,ChristopherW.Hunt,andPeterLandschützer,whocontributedtotheprovisionofsurfaceoceanCO2observationsfortheyear2021(seeTableA5).WealsothankBenjaminPfeil,RocíoCastaño-Primo,andStephenD.JonesoftheOceanThematicCentreoftheEUIntegratedCarbonObser-vationSystem(ICOS)ResearchInfrastructure;EugeneBurgerofNOAA’sPaciﬁcMarineEnvironmentalLaboratory;andAlexKozyrofNOAA’sNationalCentersforEnvironmentalInformationfortheircontributiontosurfaceoceanCO2dataandmetadataman-agement.ThisisPMELcontribution5434.Wethankthescien-tists,institutions,andfundingagenciesresponsibleforthecollec-tionandqualitycontrolofthedatainSOCATandtheInterna-tionalOceanCarbonCoordinationProject(IOCCP),theSurfaceOceanLowerAtmosphereStudy(SOLAS),andtheIntegratedMa-rineBiosphereResearch(IMBeR)programfortheirsupport.WethankdataprovidersObsPackGLOBALVIEWplusv7.0andNRTv7.2foratmosphericCO2observations.Wethanktheindividu-alsandinstitutionsthatprovidedthedatabasesusedforthemodelevaluationsusedhere.WethankFortunatJoos,SamarKhatiwala,EarthSyst.Sci.Data,14,4811–4900,2022https://doi.org/10.5194/essd-14-4811-2022P.Friedlingsteinetal.:GlobalCarbonBudget20224881andTimothyDeVriesforprovidinghistoricaldata.MatthewJ.Mc-GraththanksthewholeORCHIDEEgroup.IanHarristhankstheJapanMeteorologicalAgency(JMA)forproducingtheJapanese55-yearReanalysis(JRA-55).AnthonyP.WalkerthanksORNL,whichismanagedbyUT-Battelle,LLC,fortheDOEundercon-tractDE-AC05-100800OR22725.YosukeNiwathanksCSIRO,EC,EMPA,FMI,IPEN,JMA,LSCE,NCAR,NIES,NILU,NIWA,NOAA,SIO,andTU/NIPRforprovidingdataforNISMON-CO2.XiangjunTianthanksZheJin,YilongWang,TaoWang,andShi-longPiaofortheircontributionstotheGONGGAinversionsys-tem.BoZhengthanksthecommentsandsuggestionsfromPhilippeCiaisandFrédéricChevallier.FrédéricChevallierthanksMarineRemaud,whomaintainedtheatmospherictransportmodelfortheCAMSinversion.PaulI.PalmerthanksLiangFengandacknowl-edgesongoingsupportfromtheNationalCentreforEarthObser-vation.JunjieLiuthankstheJetPropulsionLaboratory,CaliforniaInstituteofTechnology.WileyEvansthankstheTulaFoundationforfundingsupport.AustralianoceanCO2dataweresourcedfromAustralia’sIntegratedMarineObservingSystem(IMOS);IMOSisenabledbytheNationalCollaborativeResearchInfrastructureStrat-egy(NCRIS).MargotCroninthanksAnthonyEnglish,ClyntGre-gory,andGordonFurey(P&OMaritimeServices)fortheirsupport.NathalieLefèvrethanksthecrewoftheCapSanLorenzoandtheUSIMAGOofIRDBrestfortechnicalsupport.HenryC.BittigisgratefulfortheskilfultechnicalsupportofMichaelGlockzinandBerndSadkowiak.MeikeBeckerandAreOlsenthankSparebankenVest/AgendaVestlandetfortheirsupportfortheobservationsontheStatsraadLehmkuhl.ThanosGkritzalisthanksthepersonnelandcrewofSimonStevin.MatthewW.JonesthanksAnthonyJ.De-GolforhistechnicalandconceptualassistancewiththedevelopmentofGCP-GridFED.FAOSTATisfundedbyFAOmemberstatesthroughtheircontributionstotheFAORegularProgramme;datacontribu-tionsbynationalexpertsaregratefullyacknowledged.Theviewsexpressedinthispaperaretheauthors’onlyanddonotnecessar-ilyreﬂectthoseofFAO.Finally,wethankallfunderswhohavesupportedtheindividualandjointcontributionstothiswork(seeTableA9),thereviewersofthismanuscriptandpreviousversions,andthemanyresearcherswhohaveprovidedfeedback.Financialsupport.Foralistofallfundersthathavesupportedthisresearch,pleaserefertoTableA9.Reviewstatement.ThispaperwaseditedbyDavidCarlsonandreviewedbyH.DamonMatthews,HélènePeiro,AnaMariaRoxanaPetrescu,MichioKawamiya,andoneanonymousreferee.ReferencesAhlström,A.,Raupach,M.R.,Schurgers,G.,Smith,B.,Arneth,A.,Jung,M.,Reichstein,M.,Canadell,J.G.,Friedlingstein,P.,Jain,A.K.,Kato,E.,Poulter,B.,Sitch,S.,Stocker,B.D.,Viovy,N.,Wang,Y.P.,Wiltshire,A.,Zaehle,S.,andZeng,N.:Thedominantroleofsemi-aridecosystemsinthetrendandvariabilityofthelandCO2sink,Science,348,895–899,https://doi.org/10.1126/science.aaa1668,2015.Alkama,R.:LandCarbonBudget:IntactandNon-IntactForestNBPfromTRENDYv11S2simulations[code],https://github.com/RamAlkama/LandCarbonBudget_IntactAndNonIntactForest,lastaccess:25September2022.Amador-Jiménez,M.,Millner,N.,Palmer,C.,Pennington,R.T.,andSileci,L.:TheUnintendedImpactofColombia’sCovid-19LockdownonForestFires,Environ.ResourceEcon.,76,1081–1105,https://doi.org/10.1007/s10640-020-00501-5,2020.Amante,C.andEakins,B.W.:ETOPO1GlobalReliefModelconvertedtoPanMaplayerformat,PANGAEA[dataset],https://doi.org/10.1594/PANGAEA.769615,2009.Andela,N.,Morton,D.C.,Giglio,L.,Chen,Y.,vanderWerf,G.R.,Kasibhatla,P.S.,DeFries,R.S.,Collatz,G.J.,Hantson,S.,Kloster,S.,Bachelet,D.,Forrest,M.,Lasslop,G.,Li,F.,Man-geon,S.,Melton,J.R.,Yue,C.,andRanderson,J.T.:Ahuman-drivendeclineinglobalburnedarea,Science,356,1356–1362,https://doi.org/10.1126/science.aal4108,2017.Andres,R.J.,Boden,T.A.,Bréon,F.-M.,Ciais,P.,Davis,S.,Erickson,D.,Gregg,J.S.,Jacobson,A.,Marland,G.,Miller,J.,Oda,T.,Olivier,J.G.J.,Raupach,M.R.,Rayner,P.,andTreanton,K.:Asynthesisofcarbondioxideemissionsfromfossil-fuelcombustion,Biogeosciences,9,1845–1871,https://doi.org/10.5194/bg-9-1845-2012,2012.Andres,R.J.,Boden,T.A.,andHigdon,D.:Aneweval-uationoftheuncertaintyassociatedwithCDIACestimatesoffossilfuelcarbondioxideemission,TellusB,66,23616,https://doi.org/10.3402/tellusb.v66.23616,2014.Andrew,R.M.:Acomparisonofestimatesofglobalcarbondioxideemissionsfromfossilcarbonsources,EarthSyst.Sci.Data,12,1437–1465,https://doi.org/10.5194/essd-12-1437-2020,2020a.Andrew,R.M.:TimelyestimatesofIndia’sannualandmonthlyfossilCO2emissions,EarthSyst.Sci.Data,12,2411–2421,https://doi.org/10.5194/essd-12-2411-2020,2020b.Andrew,R.M.:Towardsnearreal-time,monthlyfossilCO2emissionsestimatesfortheEuropeanUnionwithcurrent-yearprojections,Atmos.Pollut.Res.,12,101229,https://doi.org/10.1016/j.apr.2021.101229,2021.Andrew,R.M.andPeters,G.P.:Amulti-regioninput–outputtablebasedontheglobaltradeanalysisprojectdatabase(GTAP-MRIO),Econ.Syst.Res.,25,99–121,https://doi.org/10.1080/09535314.2012.761953,2013.Andrew,R.M.andPeters,G.P.:TheGlobalCarbonProject’sfossilCO2emissionsdataset(2021v34),Zenodo[dataset],https://doi.org/10.5281/ZENODO.5569235,2021.Angelsen,A.andKaimowitz,D.:RethinkingtheCausesofDe-forestation:LessonsfromEconomicModels,WorldBankRes.Obs.,14,73–98,https://doi.org/10.1093/wbro/14.1.73,1999.Aragão,L.E.O.C.,Anderson,L.O.,Fonseca,M.G.,Rosan,T.M.,Vedovato,L.B.,Wagner,F.H.,Silva,C.V.J.,SilvaJu-nior,C.H.L.,Arai,E.,Aguiar,A.P.,Barlow,J.,Berenguer,E.,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