Balancing Greenhouse Gas Budgets: Accounting for Natural and Anthropogenic Flows of CO2 and other Trace Gases

By Daniel Hayes

Balancing Greenhouse Gas Budgets: Accounting for Natural and Anthropogenic Flows of CO2 and other Trace Gases provides a synthesis of greenhouse gas budgeting activities across the world. Organized in four sections, including background, methods, case studies and opportunities, it is an interdisciplinary book covering both science and policy. All environments are covered, from terrestrial to ocean, along with atmospheric processes using models, inventories and observations to give a complete overview of greenhouse gas accounting. Perspectives presented give readers the tools necessary to understand budget activities, think critically, and use the framework to carry out initiatives.

• Written by a combination of experts across career stages, presenting an integrated perspective for graduate students and professionals alike
• Includes sections authored by those involved in both early and later IPCC assessments
• Provides an interdisciplinary resource that spans many topics and methodologies in oceanic, land and atmospheric processes

• Language: English
• Publisher: Elsevier Science
• Release date: May 5, 2022
• ISBN: 9780128149539

Book preview

9780128149539_FC

Balancing Greenhouse Gas Budgets

Accounting for Natural and Anthropogenic Flows of CO2 and other Trace Gases

First Edition

Benjamin Poulter

Josep G. Canadell

Daniel J. Hayes

Rona L. Thompson

Image 1

Table of Contents

Cover image

Title page

Copyright

Dedication

Contributors

Foreword

Preface

Acknowledgments

Section A: Background

Chapter 1: Balancing greenhouse gas sources and sinks: Inventories, budgets, and climate policy

Abstract

Acknowledgment

1: The human perturbation of the carbon cycle and other biogeochemical cycles

2: Inventories of anthropogenic GHG: The foundation of the Kyoto protocol and the Paris agreement

3: GHG budgets: Constraining GHG sources and sinks

4: Supporting the global stocktake and the net-zero emissions policy goals

5: A new generation of technologies and observations to constrain global and regional GHG budgets

6: Extending the carbon budget and accounting frameworks to meet broader policy information needs

References

Section B: Methods

Chapter 2: CO2 emissions from energy systems and industrial processes: Inventories from data- and proxy-driven approaches

Abstract

1: Introduction

2: Overview of inventory approaches

3: Uncertainty

4: Examples of emission estimates and products

5: Summary

References

Further reading

Chapter 3: Bottom-up approaches for estimating terrestrial GHG budgets: Bookkeeping, process-based modeling, and data-driven methods

Abstract

1: Introduction to bottom-up (BU) approaches

2: Bottom-up methodologies

3: Relevance to Stock-Change and flux-based accounting

4: Conclusions

References

Chapter 4: Top-down approaches

Abstract

Acknowledgments

1: Introduction

2: Measurements of greenhouse gases in the atmosphere

3: Atmospheric modeling

4: Inversion concepts

5: Application to land biosphere CO2 fluxes (NEE)

6: Application to fossil fuel emissions of CO2

7: Application to CH4 fluxes

8: Application to other GHG fluxes

9: Sources of error

10: Validation of flux estimates from inversions

11: Summary and conclusions

References

Section C: Case Studies

Chapter 5: Current knowledge and uncertainties associated with the Arctic greenhouse gas budget

Abstract

Acknowledgments

1: Introduction and background: Arctic ecosystems

2: Methodologies

3: Uncertainty and reducing uncertainty

4: Perspective and future opportunities

References

Chapter 6: Boreal forests

Abstract

Acknowledgments

1: Carbon in boreal forests

2: Estimating carbon stocks and fluxes in boreal forests

3: Carbon accounting in boreal forests

4: Regional-scale modeling

5: Synthesis

References

Chapter 7: State of science in carbon budget assessments for temperate forests and grasslands

Abstract

1: Introduction and background

2: Methodologies for flux estimations in temperate regions

3: Review of the carbon budget of temperate forests and grasslands

4: Uncertainties in carbon fluxes

5: Perspective and future opportunities for policy decision-making

References

Chapter 8: Tropical ecosystem greenhouse gas accounting

Abstract

Acknowledgments

1: Introduction and background: Tropical ecosystems

2: GHG budget in the tropics

3: Uncertainty and reducing uncertainty

4: Perspective and future opportunities

References

Chapter 9: Semiarid ecosystems

Abstract

Acknowledgment

1: Introduction and background: Global drylands and semiarid ecosystems

2: Methodologies

3: Future perspectives

References

Chapter 10: Urban environments and trans-boundary linkages

Abstract

1: From science to policy for urban carbon accounting

2: Four carbon accounting approaches for individual cities

3: Accounting biogenic carbon from land use and land-use change in individual cities

4: From individual cities to initiatives for all urban areas’ carbon accounting

References

Chapter 11: Agricultural systems

Abstract

Acknowledgments

1: Introduction

2: Carbon stocks, flows, and emissions in agricultural systems

3: Methodologies

4: Improving regional GHG inventories for agriculture

5: Conclusions

References

Chapter 12: Greenhouse gas balances in coastal ecosystems: Current challenges in blue carbon estimation and significance to national greenhouse gas inventories

Abstract

Acknowledgments

1: Background

2: What limits traditional AFOLU estimation approaches in coastal ecosystems?

3: IPCC guidelines for national-scale estimation of coastal wetland carbon

4: Improving application of the IPCC NGGI guidelines in the United States

5: Implications for the scale of GHG estimation

6: Implications for carbon cycle science on coastlines

7: Final thoughts

References

Chapter 13: Ocean systems

Abstract

1: Summary

2: The ocean as a sink/source of GHGs to the atmosphere

3: Preindustrial (or natural) carbon budget based on inverse estimates

4: Anthropogenic perturbations and the contemporary global carbon sink

5: Regional marine carbon sink

6: Storage of anthropogenic carbon

7: Variability of the ocean GHG uptake

8: Future outlook

References

Section D: Forward Looking

Chapter 14: Applications of top-down methods to anthropogenic GHG emission estimation

Abstract

1: Introduction

2: Using inverse estimates of non-CO2 GHG emissions in national reporting

3: Methane emissions detection at facility and basin scale

4: Large point source emission monitoring using satellite observations

5: Precision and sampling requirements for future satellite observations

6: Developing global high-resolution transport modeling capability for analysis of the satellite and ground-based observations of anthropogenic greenhouse gas emission

7: Developing high-resolution emission inventories for inverse modeling

8: Summary

References

Chapter 15: Earth system perspective

Abstract

1: Introduction and background: What is an earth system model?

2: Carbon cycle modeling in the context of earth system models

3: Data assimilation in earth system models

4: Future direction for carbon cycle science, earth system modeling, and DA applications

References

Index

Copyright

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Dedication

The ideas and concepts presented in this book come from extensive years of research and collaboration carried out by colleagues around the world. We dedicate this book to two of these close colleagues, Dr. Vanessa Haverd and Dr. Bob Scholes. Vanessa was an exceptionally talented and engaging scientist at CSIRO, Australia, and a world leader in investigating the role of the biosphere in the carbon cycle and developing land-surface models. Bob was a dynamic and inspirational mentor to many scientists in Africa, leading South Africa’s first greenhouse gas inventory in 1995, and many global assessments on climate change and biodiversity. Vanessa and Bob both played key roles in the Global Carbon Project and their influence is found across many of the chapters of this book.

Contributors

Numbers in parentheses indicate the pages on which the authors’ contributions begin.

Anders Ahlström 311     Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden

Mariana Almeida 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Robbie Andrew 31     CICERO Center for International Climate Research, Oslo, Norway

Shawn Archibeque 375     Department of Animal Sciences, Colorado State University, Fort Collins, CO, United States

Luana Basso 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Ana Bastos 3, 59, 311     Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany

Francisco Gilney Bezerra 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Richard Birdsey 237     Woodwell Climate Research Center, Falmouth, MA, United States

Kevin Bowman 87     Jet Propulsion Laboratory, California Institute of Technology, CA, United States

Lori M. Bruhwiler 159     National Oceanic and Atmospheric Administration, Boulder, CO, United States

Dominik Brunner 455     Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland

Rostyslav Bun 31, 455

Department of Applied Mathematics, Lviv Polytechnic National University, Lviv, Ukraine

Department of Transport, WSB University, Dąbrowa Górnicza, Poland

David E. Butman203     Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States

Donovan Campbell 375     The University of the West Indies, Jamaica, West Indies

Josep G. Canadell 3, 59     Global Carbon Project, Climate Science Centre, CSIRO Oceans and Atmosphere, Canberra, ACT, Australia

Manoel Cardoso 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Abhishek Chatterjee 483

NASA Goddard Space Flight Center, Greenbelt

Universities Space Research Association, Columbia, MD, United States

Frédéric Chevallier 87     Laboratoire des Sciences du Climat et de l'Environnement, Gif sur Yvette, France

Philippe Ciais 3, 59     Laboratoire des Sciences du Climat et de l'Environnement LSCE CEA CNRS UVSQ, Gif sur Yvette Cedex, France

Róisín Commane 159     Department of Earth & Environmental Sciences, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, United States

Monica Crippa 31     European Commission, Joint Research Centre (JRC), Ispra, Italy

Gisleine Cunha-Zeri 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Grant M. Domke203     US Department of Agriculture, Forest Service Northern Research Station, St. Paul, MN, United States

Eugénie S. Euskirchen 159     Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK, United States

Joshua B. Fisher203     Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA, United States

Dennis Gilfillan 31     North Carolina School of Science and Mathematics, Durham, NC, United States

Daniel J. Hayes 3, 203     School of Forest Resources, University of Maine, Orono, ME, United States

James R. Holmquist403     Smithsonian Environmental Research Center, Edgewater, MD, United States

Richard A. Houghton 59     Woodwell Climate Research Center, Falmouth, MA, United States

Deborah Huntzinger 59     School of Earth and Sustainability, Northern Arizona University, Flagstaff, AZ, United States

Tatiana Ilyina 427     Max Planck Institute for Meteorology, Hamburg, Germany

Rajesh Janardanan 455     National Institute for Environmental Studies, Tsukuba, Japan

Greet Janssens-Maenhout 31     European Commission, Joint Research Centre (JRC), Ispra, Italy

Matthew W. Jones 31     Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom

Lydia Keppler 427

Max Planck Institute for Meteorology

International Max Planck Research School on Earth System Modelling (IMPRS-ESM), Hamburg, Germany

Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, United States

Masayuki Kondo 237

Institute for Space-Earth Environmental Research, Nagoya University, Nagoya

Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan

Kevin D. Kroeger403     Department of Earth and Environment/Institute of Environment, Florida International University, Miami, FL, United States

Werner Kurz 59     Natural Resources Canada, Canadian Forest Service, Victoria, British Columbia, Canada

Peter Landschützer 427     Max Planck Institute for Meteorology, Hamburg, Germany

Ronny Lauerwald 237     UMR Ecosys, Université Paris-Saclay, Paris, France

Sebastiaan Luyssaert 59     Department of Ecological Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

Natasha MacBean 311     Department of Geography, Indiana University, Bloomington, IN, United States

Shamil Maksyutov 87, 455     National Institute for Environmental Studies, Tsukuba, Japan

Eric Marland 31     Department of Mathematical Sciences, Appalachian State University, Boone, NC, United States

Gregg Marland 31     Research Institute for Environment, Energy, and Economics (RIEEE), Appalachian State University, Boone, NC, United States

Marcela Miranda 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Victoria Naipal 311

Departement of Geosciences, École Normale Supérieure, Paris

Laboratory for Climate and Environmental Sciences (LSCE), Gif-sur-Yvette, France

Kim Naudts 237     Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

Christopher S.R. Neigh203     Code 618, Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, United States

Eráclito Souza Neto 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Cynthia Nevison 375     Institute for Arctic and Alpine Research, University of Colorado, Boulder, CO, United States

Shuli Niu 237     Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, People’s Republic of China

Tomohiro Oda 455

The Earth From Space Institute, Universities Space Research Association, Columbia

Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, United States

Graduate School of Engineering, Osaka University, Suita, Osaka, Japan

Stephen M. Ogle 375     Natural Resource Ecology Laboratory and Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO, United States

Jean Pierre Ometto 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Lesley Ott 483     NASA Goddard Space Flight Center, Greenbelt, MD, United States

Felipe S. Pacheco 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Frans-Jan W. Parmentier 159

Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden

Centre for Biogeochemistry in the Anthropocene, Department of Geosciences, University of Oslo, Oslo, Norway

Prabir K. Patra 87, 455

Center for Environmental Remote Sensing, Chiba University, Chiba

Research Institute for Global Change, JAMSTEC, Yokohama, Japan

A.M. Roxana Petrescu 59     Department of Ecological Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

Julia Pongratz 59

Ludwig-Maximilians-Universität Munich, München

Max Planck Institute for Meteorology, Hamburg, Germany

Benjamin Poulter 3, 59, 311     Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, United States

Thomas A.M. Pugh 237

Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden

School of Geography Earth & Environmental Sciences and Birmingham Institute of Forest Research, University of Birmingham, Birmingham, United Kingdom

Anu Ramaswami 337

China-UK Low Carbon College, Shanghai Jiao Tong University, Pudong New District, Shanghai, China

High Meadows Environmental Institute

M.S. Chadha Center for Global India, Princeton University, Princeton, NJ, United States

Peter A. Raymond 237     Yale School of the Environment, Yale University, New Haven, CT, United States

Luiz Felipe Rezende 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Kelly Ribeiro 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Dustin Roten 31     Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT, United States

Christina Schädel 159     Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, United States

Edward A.G. Schuur 159     Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, United States

Stephen Sitch 59     University of Exeter, Exeter, United Kingdom

Pete Smith 375     Institute of Biological & Environmental Sciences, University of Aberdeen, Aberdeen, United Kingdom

William Kolby Smith 311     School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, United States

Miguel Taboada 375     National Agricultural Technology Institute (INTA), Natural Resources Research Center (CIRN), Institute of Soils, Ciudad Autónoma de Buenos Aires, Argentina

Rona L. Thompson 3, 87     NILU—Norsk Institutt for Luftforskning, Kjeller, Norway

Kangkang Tong 337     China-UK Low Carbon College, Shanghai Jiao Tong University, Pudong New District, Shanghai, China

Tiffany G. Troxler403     Department of Earth and Environment/Institute of Environment, Florida International University, Miami, FL, United States

Francesco N. Tubiello 375     Statistics Division, Food and Agriculture Organization of the United Nations, Rome, Italy

Alexander J. Turner 455     Department of Atmospheric Sciences, University of Washington, Seattle, WA, United States

Yohanna Villalobos 3     Global Carbon Project, Climate Science Centre, CSIRO Oceans and Atmosphere, Canberra, ACT, Australia

Celso von Randow 271     Earth System Science Centre/National Institute for Space Research, Sao Jose dos Campos, São Paulo, Brazil

Jennifer Watts 159     Woodwell Climate Research Center, Falmouth, MA, United States

Lisa R. Welp 203     Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, United States

Lisamarie Windham-Myers 403     US Geological Survey Water Mission Area, Menlo Park, CA, United States

Daniel Zavala-Araiza 455

Environmental Defense Fund, Amsterdam

Institute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, The Netherlands

Foreword

Corinne Le Quéré, Royal Society Professor of Climate Change Science, University of East Anglia, Norwich, United Kingdom

This book could not be more timely. The authors provide for the first time in one book the scientific foundations behind accounting for greenhouse gases. Political leaders around the world are now moving on from establishing their nation’s commitments on tackling climate change to designing policies for delivering actions on the ground. The design of climate policies needs to be based on clear scientific insights using the latest observations and understanding. After working with policymakers over the past decade, I realize the genuine desire to understand how their policies will work and how they will be monitored in the context of real-world implementation. Sound and detailed knowledge is more important than ever before because methodologies are being developed to deliver the global stocktake that forms the first opportunity to check the progress of the international Paris Climate Agreement. I am glad to see that this book takes on the challenge of providing the background needed to put human actions in perspective with the environment, which will benefit scientists and policy advisors alike.

Greenhouse gas accounting has so far been based on self-reporting of emissions at the country level. This book puts the self-reporting of emissions into the context of balancing greenhouse gases, by looking at how emissions propagate in the environment and how they interact and interfere with the natural world. It shows how observations can be used to provide independent constraints on greenhouse gas emissions and the effectiveness of climate policy, and where the limits are. The book helps put human interventions in the context of the real world so that the richness and complexities of the natural environment can be adequately considered as the world transitions away from carbon-intensive activities.

Attempts to balance greenhouse gases arose initially from the need to explain the rise in CO2 levels in the atmosphere, first measured directly at Mauna Loa Observatory in Hawaii. Emissions of CO2 from human activities minus their absorption in the land and ocean natural environment (the carbon ‘sinks’) account for the growth of CO2 in the atmosphere, constituting the global carbon balance (or budget). Global Carbon Budgets were reported in all six assessment reports of the Intergovernmental Panel on Climate Change (IPCC), with the first published in 1990. In 2004, the Global Carbon Project (GCP) operationalized the annual update of global carbon budgets. Alongside several other authors of this book, I was part of the pioneering international group of GCP scientists who took on this task and led the annual budget update for 13 years. Annual carbon budgets started as an attempt to increase the support of the carbon research community for the climate policy process. It quickly turned into a platform for scientific exchanges and innovation as well as a keystone event in the annual climate calendar. GCP has expanded its budget analysis to other CH4 and N2O to provide a more comprehensive view of the impact of humans on climate. The budget balance approach is now well recognized as one of the most powerful scientific constraints, and the approach has been adapted to other aspects of the climate system, namely, sea level and heat. Balancing budgets now sets the boundary for cutting-edge research in climate change.

Today we have a relatively clear view of the global emissions of greenhouse gases and their partitioning in the environment, even though uncertainties remain. The real challenge now is to break this down at the regional level. Regional breakdowns would both provide more relevant information for decision-makers locally and help reduce the remaining uncertainties globally. The GCP fostered an initial effort in the early 2010s to assess the evidence at the time, under the first REgional Carbon Cycle Assessment and Processes (RECCAP) umbrella published in the journal Biogeosciences. Since then, new methods have been developed based on advances in computing including machine learning, new data including from satellite-based CO2 sensors, and a further understanding of how the carbon cycle operates including in the built environment.

The authors of this book are at the forefront of our research field. Their book provides a comprehensive overview of the issues related to balancing greenhouse gases and how they can be resolved. There is a big need for the book. It brings together what we know about balancing greenhouse gases in one single place, and provides the background and support for the new generation of carbon cycle scientists and policy advisors who will implement the necessary actions to tackle climate change.

Preface

Since the adoption of the Paris Agreement in 2015, the science on climate change is clear; that CO2 emissions must reach net zero by 2050 or earlier, and that CH4, N2O, and halogenated greenhouse gas emissions must be reduced significantly to avoid 1.5°C or 2°C warming over preindustrial levels. Our book Balancing Greenhouse Gas Budgets: Accounting for Natural and Anthropogenic Flows of CO2and Other Trace Gases is written for students, practitioners, and experts who are interested in gaining a deeper understanding of the history, methodologies, and applications used for greenhouse gas accounting and its increasing relevance in informing climate policy.

The contributors to this book are scientists who work at universities, private organizations, and federal agencies around the world and have spent their careers developing methods to track and quantify greenhouse gas emissions and removals as well as the underlying processes that regulate changes in greenhouse gas concentrations over time. This global perspective has helped shape the breadth of individual chapters and the teams writing them, as well as the topics that they cover. The book’s scope encompasses the methods, regional cases, and the future outlook of greenhouse gas accounting. We address an increasing demand to better understand the synergies between policy-driven greenhouse gas inventories that aim to quantify anthropogenic influences on emissions and removals with science-based approaches that quantify fluxes from both natural and managed systems.

A variety of topics that are related to greenhouse gas accounting methodologies and their adaptation in different parts of the world are covered in the book. The diverse perspectives from the individual authors add to the comprehensiveness of the chapters, with authors representing each continent and bringing a range of experiences in local to national studies on climate change, including contributions to the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change.

Chapter 1 provides the context for greenhouse gas accounting, including a historical perspective on policy-driven versus scientific methodologies. Chapters 2, 3, and 4 provide a description of each of the main methodologies for greenhouse gas accounting, covering inventories, bottom-up process modeling, and top-down atmospheric inversion approaches. Chapters 5–11 provide examples of how these methodologies are applied to land regions with separate chapters for arctic, boreal, temperate, tropical, semiarid, urban, and agricultural systems. Chapters 12 and 13 address greenhouse gas accounting for aquatic systems, including the open ocean and nearshore coastal ecosystems. Chapters 14 and 15 cover forward-looking topics in greenhouse gas emissions estimation, including advances in atmospheric inversions and data assimilation.

We intend for this book to provide a foundation for greenhouse gas accounting that can be used in classes and coursework, and as a guide to informing local to national to global scale accounting frameworks, and as a reference for understanding the integration of policy and science-driven approaches. We also hope that the contributions within the book will help to advance the science needed to inform climate policies that require emission sources and sinks to be balanced in order to stabilize the Earth’s climate.

Acknowledgments

The editors acknowledge support from their home institutions: NASA Goddard Space Flight Center, Earth Sciences Division, Maryland, United States; Climate Science Centre, CSIRO Oceans and Atmosphere, Canberra, ACT, Australia, and the Australian National Environmental Science Program—Climate Systems Hub; School of Forest Resources at the University of Maine, United States; and NILU—Norsk Institutt for Luftforskning, Kjeller, Norway.

Section A

Background

Chapter 1: Balancing greenhouse gas sources and sinks: Inventories, budgets, and climate policy

Josep G. Canadella; Benjamin Poulterb; Ana Bastosc; Philippe Ciaisd; Daniel J. Hayese; Rona L. Thompsonf; Yohanna Villalobosa    a Global Carbon Project, Climate Science Centre, CSIRO Oceans and Atmosphere, Canberra, ACT, Australia

b Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, United States

c Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany

d Laboratoire des Sciences du Climat et de l’Environnement LSCE CEA CNRS UVSQ, Gif sur Yvette Cedex, France

e School of Forest Resources, University of Maine, Orono, ME, United States

f NILU—Norsk Institutt for Luftforskning, Kjeller, Norway

Abstract

Countries around the world are making ever stronger commitments to address human-induced climate change. The implementation of those commitments and their contributions to reach the Paris Agreement goal of balancing sources and removals of greenhouse gases (GHGs) are dependent on having comprehensive and reliable systems to monitor, report, and verify sources and sinks of GHGs. Both, emission inventories and comprehensive GHG budgets play a key role in characterizing and tracking the human perturbation of global biogeochemical cycles, and assessing the requirements to stabilize the climate system. The chapter covers GHG inventories within the Framework Convention on Climate Change, and shows how the development of comprehensive GHG budgets covering anthropogenic and natural fluxes provides additional and essential information to support climate policy and reach the goals of the Paris agreement.

Keywords

Global biogeochemical cycles; Human perturbation; Global and regional GHG budgets; Paris Agreement; Global Stocktake; GHG inventories

Acknowledgment

JGC acknowledges the support by the Australian National Environmental Science Program—Climate Systems hub. We thank Peter Briggs for preparing the figure files.

1: The human perturbation of the carbon cycle and other biogeochemical cycles

Human activities have increased emissions and atmospheric concentrations of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and halogenated gases, all of which are heat-trapping greenhouse gases (GHGs). Before the industrial revolution, the biospheric emissions of CO2, CH4, and N2O from the Earth’s land, ocean, and inland waters were roughly in a dynamic equilibrium with natural sinks. However, the combustion of fossil fuels, land clearing along with other agricultural and industrial activities have driven an imbalance in the global sources and sinks, with atmospheric CO2, CH4, and N2O concentrations now 47%, 156%, and 23% higher than that in 1750, respectively (Canadell et al., 2021). This imbalance is unprecedented in the Earth system in two ways. First, the atmospheric concentrations of the three main GHGs were higher in 2019 than at any time in the past 800,000 years, at 409.9 ppm for CO2, 1866.3 ppb for CH4, and 332.1 ppb for N2O, and current CO2 concentrations are also unprecedented in the last 2 million years. Second, the rate at which the CO2 concentration has been accumulating in the atmosphere during the Industrial Era is at least 10 times faster than any other 100-year period over the last 800,000 years, and 4–6 times faster than any other 1000-year period in the last 56 million years (Canadell et al., 2021). All these changes in GHG concentrations have led to the rapid warming of the planet, with impacts on almost all aspects of the Earth system (IPCC, 2021), including the rapid transformation of terrestrial and marine ecosystems (Canadell & Jackson, 2021), with direct consequences for human health, food security, and regional economies.

Unlike the halogenated gases, which are mostly synthetically produced by the chemical industry (and have thus appeared relatively recently in the atmosphere), CO2, CH4, and N2O have, in addition to anthropogenic emissions, large natural emissions and sinks from biogeochemical and chemical processes on land, in the ocean and in the atmosphere (Fig. 1). This makes the study of these three GHGs particularly complex as it requires the capability to separate anthropogenic emissions from natural sources and sinks. In addition, the natural sources and sinks are not stable but respond to human-driven environmental changes, including climate change as well as natural climate variability.

Fig. 1

Fig. 1 Global biogeochemical cycles with their natural and human perturbation fluxes. Top panel: mean annual global CO 2 budget, 2011–19 ( Global Carbon Atlas, 2021) based on ( Friedlingstein et al., 2020). Middle panel: mean annual global CH4 budget, 2008–17 ( Saunois et al., 2020). Bottom panel: mean annual global N2O budget, 2007–16 ( Tian et al., 2020).

2: Inventories of anthropogenic GHG: The foundation of the Kyoto protocol and the Paris agreement

The United Nations Framework Convention on Climate Change (UNFCCC) was established in 1992 to combat dangerous human interference with the climate system. At the first Conference of Parties (COP), the UNFCCC established a range of initiatives, including that all countries provide national-level inventories for all greenhouse gases, at annual intervals for developed countries (i.e., Annex 1) and every 2 years for non-Annex 1 countries (i.e., emerging economies and less developed countries). The least developed countries would choose their reporting years at their own discretion. The objective was to encourage the presentation of information and a national inventory of anthropogenic emissions by sources and removals by sinks of all GHG not already dealt with by the Montreal Protocol. The national communications are to be done in a consistent, transparent, and comparable manner, taking into account specific national circumstances. Fig. 2 shows an illustration of the attribution of the global anthropogenic GHG emission to activities and end-uses.

Fig. 2

Fig. 2 Global greenhouse gas emissions are attributed to the main end uses and activities for 2016. Source: World Resources Institute.

The inventories account for anthropogenic emissions of GHGs only, including those from agriculture and land-use change, using 1990 as the first year, or baseline. In 1997, the Kyoto Protocol (2005–20) provided a legally binding mandate for emission reductions, with the inventories providing the basis for determining whether countries met their targets to reduce emissions over two commitment periods. The IPCC provides the scientific basis for the methodologies used in the national inventories, first described in the 1994 IPCC Guidelines for National Greenhouse Gas Inventories, and later revised and refined in 1996, 2006, and 2019, with supplements for land use in 2003 and wetlands in 2013. The methodologies combine activity data and emission factors using either stock-change or gain/loss approaches to estimate emissions and removals, and are designed to use detailed information where available and more generalized information in cases where little or no data exist. A Tier system based on different levels of analytical complexity and data richness was developed, which is associated with a level of uncertainty. Tier 1 methods have higher uncertainty and use global average emission factors, Tier 2 methods have medium uncertainty, using regional emission factors, and Tier 3 methods have the lowest uncertainties and use local data and more sophisticated modeling approaches. The type of approach used affects the estimates and their uncertainties, with higher uncertainties for data-poor countries and lower uncertainties for data-rich countries.

While the inventories aim to provide estimates of direct anthropogenic emissions and removals, for some GHGs and sectors they inadvertently include indirect and natural processes. For example, inventories of CO2 emissions from the land use, land-use change, and forestry (LULUCF) sector include the effects of climate change and CO2 on ecosystems, and may also implicitly include (or not) natural disturbances (Canadell et al., 2007; Grassi et al., 2018). In addition, different countries use the proxy of managed lands for the emissions that they are responsible to cover with their inventories. The use of different definitions for what is designated as managed land has a large effect on what processes are included in the inventories and on the extent of land upon which the reporting is based (Grassi et al., 2018). For instance, the definition of managed lands includes almost the entire land area in the United States and European inventories, whereas, for Canada, Russia, and Brazil, large areas of land are considered unmanaged and excluded from the GHG inventory reporting. In tropical countries, the distinction between managed and unmanaged land is often unclear, and illegal logging along with forest degradation may occur on what is reported as unmanaged land and thus omitted from inventories, thereby contributing to uncertainty in the reporting.

These differences in definitions, methodology, and reporting make the inventories less comparable among countries and also lead to uncertainties on how genuine, additive, and effective GHG national mitigation targets are. For instance, errors occur in estimating GHG emissions from the agriculture and LULUCF sectors for not correcting indirect and natural processes, and because land ecosystems and management are unique to each country so too are the errors (Cui et al., 2021). This is in contrast to, for example, the calculation of CO2 emissions from the combustion of fossil fuels, which depend on the type and quantity of fuel combusted with a narrower spread of potential uncertainties, albeit also requiring a regional/national focus (Liu et al., 2015).

The national GHG inventories for UNFCCC reporting are prepared by government bodies or other institutions in each country. For instance, in the United States, the Environmental Protection Agency (EPA) develops the national GHG inventory, with the development cycle beginning a year before submission to the UNFCCC. EPA scientists and experts contribute to the inventory, which then goes through an external review process. Atmospheric measurements are used to help refine emission factors and act as independent benchmarks for inventory uncertainty assessment. In Australia, the government updates the GHG inventories four times a year, with a 25-m resolution satellite-based system that is used to estimate emissions from land clearing and revegetation due to human activities. However, the frequency and quality of reporting are much reduced in developing and less developed countries, limiting the capacity of global analyses to track progress toward the objectives of the Paris Agreement (Fig. 3). All signatory countries to the Paris Agreement will be required to report on a regular basis from 2024 onwards.

Fig. 3

Fig. 3 The last period for which GHG emissions inventories submitted to the UNFCCC are available. The figure includes all types of inventories, from the very detailed and annually updated GHG inventories from Annex I countries (developed countries), to biennial reporting for some non-Annex I countries with a wide range in the quality of reporting and detail provided. Least developed countries submit inventories at frequencies chosen at their own discretion and often provide very limited detail. Source Minx, J., Lamb, W., Andrew, R., Canadell, J., Crippa, M., Döbbeling, N., et al. (2021). A comprehensive dataset for global, regional and national greenhouse gas emissions by sector 1970–2019. Earth System Science Data Discussions, 1–63. https://doi.org/10.5194/essd-2021-228.

The limitations of GHG inventories in many regions of the world limit the value of global estimates from the sum of national inventories and their use to constrain studies of the anthropogenic perturbation of the carbon cycle. Moreover, major disparities in flux estimates have been identified when comparing inventory data with other estimates using independent or partially independent approaches. For instance, the global anthropogenic net land-use CO2 emissions reported by global biospheric models, as presented in the annual Global Carbon Project-Global Carbon Budget (Friedlingstein et al., 2020) and the IPCC Assessment reports (Canadell et al., 2021; Ciais et al., 2013), have a discrepancy of about 4 Gigatons of CO2 per year when compared to the aggregate national estimates reported to the UNFCCC (Grassi et al., 2018). Inventory-based emissions estimates show that CH4 emissions from coal mining in China declined between 2012 and 2016 (Gao, Guan, & Zhang, 2020; Sheng, Song, Zhang, Prinn, & Janssens-Maenhout, 2019), whereas atmospheric inversion estimates showed an increase in CH4 emissions albeit at a slower rate for 2015 (Miller et al., 2019) and 2016 (Chandra et al., 2021). Deng et al. (2021) also suggest that GHG inventories grossly underestimate CH4 emissions from oil and gas extracting countries in the Gulf region and Central Asia (Deng et al., 2021). Thompson et al. (2019) reported a faster rate of global N2O emissions using atmospheric inversions than that estimated based on IPCC emission factors utilized in national reporting.

3: GHG budgets: Constraining GHG sources and sinks

GHG budgets are the compilation of estimates of all GHG sources and sinks constrained by mass balance, i.e., globally the change in atmospheric abundance is balanced by the sum of all sources and sinks. Regionally, there is also a mass balance constraint, but there are larger uncertainties due to the exchange of mass between the regional domain and the rest of the world. The mass balance constraint provides a means to help assess the magnitude of the net emissions reported to the UNFCCC and how uncertain they might be. In addition, research-driven GHG budgeting efforts, which are separate from the UNFCCC national greenhouse gas inventory reporting, can help assess inconsistencies and gaps in current emissions reporting, and support model development and benchmarking to assess the future evolution of GHG sources and sinks.

The scientific budget framework relies on the use of multiple flux estimates, fully or partially independent that are derived from the use of bottom-up and top-down approaches. The incorporation of multiple constraints from these different estimates also enables some level of redundancy to assess uncertainties in the budget calculations (Fig. 4). Bottom-up estimates are typically based on some combination of global and national GHG inventory-based fluxes, process-based biogeochemical models for land and ocean, bookkeeping models, upscaled flux products from observations, and remote sensing-based flux estimates including carbon stock changes over time. Top-down flux methods are based on inverse methods that use atmospheric GHG concentrations and transport models to optimize land-atmosphere and ocean-atmosphere flux estimates. In some cases, top-down methods can attribute net fluxes to major source categories, such as biogenic and fossil sources, based on prior knowledge of the spatial distribution of sources or by the classification of unique isotopic signatures (Chandra et al., 2021; Saunois et al., 2020; Zhang et al., 2021). With such an integrative framework, the construction of GHG budgets is the ultimate test of our knowledge on the magnitude and uncertainties of GHG sources and sinks.

Fig. 4

Fig. 4 Net carbon fluxes, storage changes, and lateral fluxes from trade and riverine carbon export to the ocean for the decade 2000s, based on the REgional Carbon Cycle Assessment and Processes-1 ( Ciais, Bastos, et al., 2020; Ciais, Yao, et al., 2020). NEE, net ecosystem exchange; ΔX, carbon stock change; PgC, petagrams of carbon.

The global carbon budget has been assessed by the IPCC Assessment Reports, while the Global Carbon Project has taken a leading role in the construction and further development of the science underpinning the global and regional assessments, and extending the budgeting work to cover the three most important GHGs: CO2, annually from 2009 (Friedlingstein et al., 2020); CH4 (2007, 2016, 2020; Saunois et al., 2020); and N2O 2020 (Tian et al., 2020). The latter efforts have led to the full incorporation of the three budgets in the last two assessment cycles of the IPCC (Canadell et al., 2021; Ciais, Sabine, et al., 2013).

The GCP-REgional Carbon Cycle and Processes study (RECCAP; Canadell, Ciais, Sabine, & Joos, 2012; Ciais, Yao, et al., 2020; Stavert et al., 2022) was established to support the development of budgets for regions and large nations, building from the initial efforts of the EU-project, CarboEurope, in the early 2000s. CarboEurope developed the first comprehensive GHG regional budgets for Europe (Schulze et al., 2009, 2010). Similar efforts were followed with the USA-State of the Carbon Cycle Report (USCCSP, 2007) and others in Australia (Haverd et al., 2013), China (Piao et al., 2009), among others.

Budgeting activities can vary widely in their approach, and different studies have developed their own methodology and workflow, using a range of datasets to estimate emissions and sources. The flexibility in these approaches means that data derived from multiple sources such as direct observations of emissions from flux towers and soil chambers, aircraft campaigns, satellites, process-based models, atmospheric inversions, and GHG inventories—can be combined to provide comprehensive assessments that contribute to the next-level research users and policymakers. A limitation of the current GHG budget approaches is the spatial resolution at which budgets can be developed, which is determined by data availability and model resolution, particularly for atmospheric inversions. This limits their current use in directly supporting the development of national GHG inventories, except for larger countries such as Australia, Brazil, China, Russia, and the United States. Likewise, atmospheric components of the budget have limits on their ability to partition anthropogenic from natural fluxes. However, new data platforms and model development will fundamentally change this premise in the years ahead making GHG budgets more central to national GHG assessments (see the section on New generation of technologies and observations).

RECCAP1 was the first global effort to develop a set of regional (10) and ocean basins (5) carbon budgets covering the entire globe over the decades of 1990–2009. The regionalization allows for the incorporation of regional knowledge on unique processes such as a detailed land-use change in South America and Southeast Asia, dust transport in Australia, and permafrost thawing in Russia while using regionally specific datasets and modeling capabilities. This effort led to the first global carbon budget constructed from the bottom-up (Ciais, Yao, et al., 2020), and provided new insights into the dynamics of the carbon cycle, including an estimate of the global soil heterotrophic respiration smaller than all previous estimates. This work highlighted the large effects of lateral carbon fluxes from crop and wood trade along with riverine-carbon export to the ocean. Building from the results in RECCAP1, a new carbon accounting framework has been developed (Fig. 5; Ciais, Bastos, et al., 2020), which is guiding the second phase of RECCAP. In addition to the CO2 flux estimates in the previous effort, RECCAP2 also includes estimates of CH4 and N2O fluxes along with stock change estimates based on new satellite products and observation-based data, and extends the assessment to 2010–19.

Fig. 5

Fig. 5 Carbon budget framework and individual flux components as developed for the REgional Carbon Cycle Assessment and Processes-2 ( Ciais, Bastos, et al., 2020 ).

The process of reconciling top-down and bottom-up estimates is key to constraining uncertainties in the overall budget by way of identifying inconsistencies and methodological problems, missing fluxes, and/or overlapping estimates (double counting). Wider use of atmospheric constraints has shown to be of great value in detecting major gaps between reported emissions and what is being observed in the atmosphere (Shen et al., 2021), identifying hotspot regions (Zhang et al., 2020), and supporting the development of improved emission factors (Thompson et al., 2019). Together, the benefits of the scientific budgeting approach underpin the set of best practices in monitoring, reporting, and verification (MRV), which are central to compliance under the UNFCCC.

4: Supporting the global stocktake and the net-zero emissions policy goals

In 2015, the Paris Agreement was adopted at the 21st COP of the United Nations Framework Convention on Climate Change (UNFCCC). The goal of the Agreement is to limit global warming to well below 2.0°C and pursue efforts to limit the temperature increase to 1.5°C compared to preindustrial temperatures. Article 4 stipulates that in order to achieve the long-term temperature goals, parties aim to reach global peaking of greenhouse gas emissions as soon as possible,… and to undertake rapid reductions thereafter in accordance with the best available science, so as to achieve a balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases in the second half of this century.

The Paris Agreement is different from the Kyoto Protocol because it is the first agreement to establish a specific global mean temperature goal at which global warming should be limited. Importantly, the Paris Agreement, via IPCC, also established a tangible link to the underlying biogeochemical requirements to stabilize the climate system. These requirements can be directly linked to emissions targets that nations, regions, and their global aggregate need to achieve: i.e., a balance between GHG sources and removals, otherwise known as net-zero emissions. This was achieved by better understanding the linear relationship between cumulative GHG emissions and global temperature change. Although the Agreement specifies anthropogenic fluxes, from an Earth perspective, the climate will stop warming only when at least all CO2 emissions (regardless of whether they are from human activities or natural sources) reach net-zero (emissions equal to sources), and other GHGs emissions decrease very significantly (IPCC, 2021). Reaching net-zero GHG emissions, that is for all non-CO2 GHG in addition to CO2 emissions, would stop further global warming and lead to the slow decline in global mean temperature (IPCC, 2021).

This GHG balance also requires tracking any emerging biogeochemical-climate feedbacks, which might lead to the need to adjust the size and speed of mitigation efforts. Global net-zero CO2 emissions need to be reached by 2050 for the 1.5°C goals and by halfway through the second half of this century for the well below 2°C goals (Arias et al., 2021).

To track progress toward these objectives of the Paris Agreement, the global stocktake was established to assess progress toward the multiple objectives on mitigation, adaptation, and finance flows every 5 years, with the first assessment due in 2023. Of particular relevance to the work on GHG budgets is the monitoring and tracking of the emissions reduction efforts encapsulated in the Nationally Determined Contributions (NDCs, or short-term mitigation goals) and the progress toward net-zero emissions (the long-term goal). Scientific budget assessments can support the quantification of mitigation activities both regionally and globally, but except for a small number of large countries such as Australia, China, the United States, and the European Union as a region, they are not currently conducted at the national level which is what would be required to support meeting the NDCs and net-zero emission targets. The work on GHG budgets includes assessing the combined effectiveness of the NDCs, improving national inventories, and contributing to the setting of more stringent NDCs over time. Globally, budgets over time will be able to detect changes in the strength of the natural sinks, currently removing 56% of all anthropogenic emissions, and emerging biogeochemical-climate feedback (Canadell et al., 2021; Friedlingstein et al., 2020).

Nature-based solutions to achieve mitigation targets and net-zero emissions goals (Griscom et al., 2017; Smith et al., 2016) are becoming ever more important, particularly those activities removing CO2 from the atmosphere (CDR, carbon dioxide removal). Their growing importance comes from the large requirements for negative emissions in decarbonization pathways consistent with the Paris agreement (Fuss et al., 2014; IPCC, 2018). A thorough assessment of the potential for nature-based solutions is required as well as tracking the effects of rapidly changing climate and atmospheric CO2 on the sink capacity of CDR activities and the natural biospheric sink are required (Canadell & Schulze, 2014; Roe et al., 2021; Walker et al., 2020).

A comprehensive and transparent approach to all sources and sinks of GHGs is also central to the development of carbon markets, certification schemes, green bonds, standards of carbon credits, and voluntary markets. They are all growing quickly as nations increase their mitigation commitments, pledges to net-zero emissions, and a broader spectrum of corporate and civil actors become involved.

5: A new generation of technologies and observations to constrain global and regional GHG budgets

Remote sensing is playing a growing role in supporting the monitoring, reporting, and verification of GHGs sources and sinks. Satellite systems are critical for filling in the gaps among in situ measurements (in both time and space), especially over large, remote, and inaccessible regions with otherwise sparse monitoring networks on the ground. The public opening of the Landsat archive (Wulder, Masek, Cohen, Loveland, & Woodcock, 2012) and its availability for analysis on cloud platforms (Gorelick et al., 2017) is allowing for unprecedented access to high resolution and up-to-date information on land cover and land-use change everywhere on Earth (Kennedy et al., 2018).

For regions and nations with vast land to cover or without a comprehensive inventory program, repeated satellite analysis of land-use change and aboveground biomass can be combined in a simple book-keeping model to track carbon stocks and fluxes for the purposes of GHG budgets (Tang et al., 2020). For instance, when Australia began to estimate emissions from land-clearing in the early 1990s, it relied on a number of disparate observations and reports from different states with no common methodologies, including analyzing the sales of Tordon, a chemical used to kill trees, to indirectly estimate the annual amount of land clearing (personal communication Prof. Graham Farquar, head of the National Greenhouse Gas Inventory in early 1990s). Since then, Australia has developed a tier-3 modeling approach to estimate GHG emissions and removals from land use, land-use change, and forestry with continent-wide information, and land-use transitions at 25 m resolution based on the NASA-USGS Landsat retrievals (Lehmann, Wallace, Caccetta, Furby, & Zdunic, 2013). Many other countries, particularly in more advanced and emerging economies have developed equally sophisticated systems to track the anthropogenic GHG sources, including the combustion of fossil fuels and land use including agriculture, land-use change (Dutra et al., 2012), and forestry.

Compared to the use of optical imagery to detect changes in land cover, active remote-sensing systems such as synthetic aperture radar are used to more directly measure above-ground C stocks from airborne and spaceborne platforms (Berninger, Lohberger, Stängel, & Siegert, 2018). Airborne laser scanning, or LiDAR, is capable of high-resolution biomass carbon mapping (Montesano et al., 2014) and is increasingly being used operationally in national forest inventories (Naesset, 2007; White et al., 2013). New products related to solar-induced fluorescence (SIF) and vegetation optical depth (VOD) are providing unique insights into productivity and biomass that previous multispectral and coarse-spatial resolution radar missions were unable to provide (Fan et al., 2019; Liu et al., 2015; Qin et al., 2021).

Advances in ground-based networks, space-based monitoring, modeling, and data assimilation techniques can contribute substantially toward reducing uncertainties and providing lower-latency information on emissions and removals. For example, the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (Gitarskiy, 2019) now includes guidelines on how atmospheric inversions can be used in emissions estimation. Specifically, atmospheric GHG inversions can be compared with national GHG inventories to provide quality assurance of the inventory by verifying total emissions for particular categories and gases, helping countries to target areas of uncertainty.

Ground-based networks have expanded and become more coordinated with one another over the past decade. These include observing networks such as NEON, GLEON, SAEON, Fluxnet, Euroflux, Ameriflux, Ozflux, and Asiaflux. Trace gas measurements provided by these networks are the basis of training datasets for machine learning or artificial intelligence algorithms used to develop data-driven, gridded time series of greenhouse gas emissions. Gaps in measurements still exist, particularly in the tropics and high latitudes, where logistics are challenged by remote access and difficult weather conditions. Measurements of methane are sparse globally, making uncertainty for wetland emissions relatively high.

Over the past few years, a new satellite constellation of space-based remote-sensing platforms has emerged to provide insight into plant function (Stavros et al., 2017) and other important measurements such as forest canopy height, canopy vertical structure, and GHGs column retrievals. National space agencies (e.g., NASA, ESA, ASI, JAXA) and private companies (Maxar, Planet, DLR) have launched a range of optical, lidar, and radar instruments as free-flyers or as hosted payloads using the International Space Station. These missions include NASA’s Ice, Cloud, and land elevation satellite (ICESat-2) (Markus et al., 2017), the Global Ecosystem Dynamics Investigation (GEDI) (Dubayah et al., 2020), the Orbiting Carbon Observatory-2 OCO-2 and OCO-3 (Crisp et al., 2017; Eldering, Taylor, O’Dell, & Pavlick, 2019), ESA’s Sentinel 1, 2, and 5, the TROPOspheric Measuring Instrument (TROPOMI) (Veefkind et al., 2012), and JAXA’s GOSAT (Greenhouse gases Observing SATellite) series (Kuze et al., 2016). Commercial spacecraft include MAXAR’s Worldview high-resolution instruments, which can be used for mapping individual shrubs and trees in open-canopy forests, and Planet’s ‘Doves’ providing daily 3-m resolution observations of land cover and land cover change. On the horizons are the joint NASA-ESA Biomass mission and NASA’s NISAR mission, which combined with GEDI and ICEsat-2, will provide full global coverage of biomass and ~ 30 m resolution, and ESA’s FLEX mission, which will provide improved estimates of photosynthesis activity and plant health and stress conditions.

The new technologies for satellite measurements of GHGs such as CO2 and CH4 provide new opportunities to study the global carbon cycle, particularly in regions that have been historically poorly covered by ground-based carbon observations. For instance, the Greenhouse gases Observing SATellite (GOSAT) (CO2, CH4) (Kuze et al., 2016), the Orbiting Carbon Observatory-2 (OCO-2) (CO2) (Crisp et al., 2017), and the global carbon dioxide monitoring satellite (TanSat) (CO2) (Yang et al., 2021) now provide column GHG retrievals across the world that can be used to quantify carbon flux exchanges (Fig. 6A). The NASA OCO-3 launched to space in 2019 (Eldering et al., 2019; Taylor et al., 2020) offers more dense information than OCO-2 at northern and southern mid-latitudes, while the upcoming NASA Geostationary Carbon Cycle Observatory (GeoCarb) (Moore et al., 2018) will focus on the Americas’ carbon cycle with the total concentration of CO2 and carbon monoxide at a 5–10-km horizontal resolution. The CO2MVS constellation will track CH4 and CO2 and is under development by ESA and the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT).

Fig. 6

Fig. 6 (A) CO 2 column-averaged dry air mole fraction (ppm) June–July 2018, OCO-2 Lite (version 9). (B) Net carbon exchange for Australia in 2015 estimated by the Community Atmosphere Biosphere Land Exchange (CABLE) model, used as a prior flux estimate for the inversion in (C). It includes fire emissions but excludes emissions from the combustion of fossil fuels and land-use change. (C) Net carbon exchange for Australia in 2015 based on an inversion of column CO 2 from the Orbiting Carbon Observatory-2, including all CO 2 fluxes except fossil fuel emissions. (A) Source: OCO-2 Science Team, Michael Gunson, A. E. (2018). OCO-2 level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files, retrospective processing V9r. Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC). (C) Based on Villalobos, Y., Rayner, P., Silver, J., Thomas, S., Haverd, V., Knauer, J., et al. (2021). Was Australia a sink or source of CO2 in 2015? Data assimilation using OCO-2 satellite measurements. Atmospheric Chemistry and Physics, 21, 17453–17494. https://doi.org/10.5194/acp-21-17453-2021.

Although satellite-based column GHG estimates are no replacement for precise and accurate atmospheric observations (Masarie, Peters, Jacobson, & Tans, 2014), their continuous improvement and broad coverage can provide new insights on regions such as the tropics and the Southern Hemisphere where atmospheric observations are too sparse (Peylin et al., 2013).

The value of the new GHG satellite data to develop regional carbon budgets is evident, as an example, for the Australian continent (Fig. 6). Atmospheric inversions rely on one GHG monitoring station (Cape Grim), located at a coastal site with onshore winds intended to provide global baseline measurements of atmospheric GHGs and pollutants (Pearman, Fraser, & Garratt, 2017). It is, therefore, free, by design, of continental influences, limiting its capability to constrain the fluxes across the continent in global atmospheric inversions (Haverd et al., 2013). Observations from the OCO-2 satellite retrievals have enabled to perform a first-of-its-kind regional atmospheric inversion (Fig. 6B, C; Villalobos, Rayner, Thomas, & Silver, 2020) informed (as a prior) by the land-atmosphere fluxes from a highly parameterized biospheric model for Australian conditions (CABLE; Haverd et al., 2018) (Fig. 6); the use of both bottom-up and top-down constraints has highlighted the importance of savanna ecosystems of the north and semiarid regions of the southeast as strong carbons sinks.

As a much denser and higher resolution sampling of GHG concentrations, biomass, vegetation structural characteristics, and flux measurements are becoming more widely available; the comparison between national inventories and comprehensive scientific GHG budgets can be done on a regular basis. More spatially and temporally explicit modeling is an important extension from current GHG inventories to address the needs for mitigation and adaptation.

Modeling approaches have advanced to take advantage of increased computational capacity, available at lower cost, and open-science mandates that provide faster access, transparency, and data equity. Collaborative tools such as Slack, Github, and others now provide instantaneous sharing of ideas and code, leading to less delay in the availability of data. Governmental coordination, such as the European Copernicus Program, the European Space Agency’s Climate Change Initiative, and NASA’s Carbon Monitoring System has enabled greater collaboration and data access for advancing greenhouse gas science.

6: Extending the carbon budget and accounting frameworks to meet broader policy information needs

The history of greenhouse gas accounting is explained by the information needs of a wide range of stakeholders. The stakeholders include scientists, policymakers, and regulators at the city, state, national, and global scales. Corporations and nonprofit organizations have also been interested in determining their own carbon footprints and budgets, while the GHG budget framework has been important in higher education. Accounting approaches have evolved to inform policy, provide monitoring and enforcement, and develop a better understanding of ecosystems and the Earth system while contributing to theory and benchmarking used in model development and applications.

In addition to global and regional carbon and GHG budgets described in the preceding sections (Global: Friedlingstein et al., 2020; Saunois et al., 2020; Tian et al., 2020; Regional: Canadell et al., 2012; Petrescu et al., 2021; Petrescu et al., 2021; Saunois et al., 2020), the carbon budget and accounting frameworks have been extended to fulfill other information needs leading to the development of cumulative carbon budgets (Friedlingstein et al., 2020; Quéré et al., 2016); Fig. 7, and remaining carbon budgets (Matthews et al., 2020; Rogelj et al., 2016); Fig. 8.

Fig. 7

Fig. 7 Global cumulative carbon budget for all major CO 2 sources and sinks for the period 1850–2020 ( Friedlingstein et al., 2021).

Fig. 8

Fig. 8 Total carbon budget to 1.5°C, 1.7°C, and 2°C global surface mean temperature starting from 1850 to 2021, with the partition of the historical carbon budget and the remaining carbon budget. The remaining carbon budget since January 2022. Total CO 2 emissions include emissions from the combustion of fossil fuels, land-use change, and cement production. Budgets based on IPCC methods ( Canadell et al., 2021 ) and updated data from Friedlingstein et al. (2021) . Source: Global Carbon Project.

Cumulative carbon budgets refer to the total amount of carbon emitted over a period and their partition between the atmosphere and the CO2 sinks on land and in the ocean (Fig. 7). The cumulative carbon budget provides information on the historical role or responsibility of the various components of the budget leading to or avoiding climate change. The cumulative component of emissions has also been used to assign the responsibility to individual countries for their historical cumulative emissions (and contribution to global warming), as opposed to assessments based on their current emissions. This approach was initially discussed in the FCCC and is known as the Brazilian proposal, which did not succeed in being adopted. The inclusion of both cumulative CO2 emissions and sinks has also been used to determine the net effect of individual regions and countries on the observed anthropogenic radiative forcing and climate change to date (Ciais et al., 2013; Fu et al., 2021).

The remaining carbon budget (Allen et al., 2009; Matthews et al., 2020; Rogelj et al., 2016) is the total amount of net CO2 emissions that human activities can still release into the atmosphere while keeping the global mean surface temperature to a specific level, for instance, to 1.5°C or well below 2°C relative to preindustrial temperatures as pursued by the Paris Agreement (Fig.