scispace - formally typeset
Search or ask a question
JournalISSN: 1866-3508

Earth System Science Data 

Copernicus Publications
About: Earth System Science Data is an academic journal published by Copernicus Publications. The journal publishes majorly in the area(s): Environmental science & Geology. It has an ISSN identifier of 1866-3508. It is also open access. Over the lifetime, 1249 publications have been published receiving 51614 citations. The journal is also known as: ESSD (Internet) & ESSD (Print).


Papers
More filters
Journal ArticleDOI
Pierre Friedlingstein1, Pierre Friedlingstein2, Michael O'Sullivan1, Matthew W. Jones3, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters4, Wouter Peters5, Julia Pongratz6, Julia Pongratz7, Stephen Sitch2, Corinne Le Quéré3, Josep G. Canadell8, Philippe Ciais9, Robert B. Jackson10, Simone R. Alin11, Luiz E. O. C. Aragão12, Luiz E. O. C. Aragão2, Almut Arneth, Vivek K. Arora, Nicholas R. Bates13, Nicholas R. Bates14, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp15, Selma Bultan6, Naveen Chandra16, Naveen Chandra17, Frédéric Chevallier9, Louise Chini18, Wiley Evans, Liesbeth Florentie5, Piers M. Forster19, Thomas Gasser20, Marion Gehlen9, Dennis Gilfillan, Thanos Gkritzalis21, Luke Gregor22, Nicolas Gruber22, Ian Harris23, Kerstin Hartung24, Kerstin Hartung6, Vanessa Haverd8, Richard A. Houghton25, Tatiana Ilyina7, Atul K. Jain26, Emilie Joetzjer27, Koji Kadono28, Etsushi Kato, Vassilis Kitidis29, Jan Ivar Korsbakken, Peter Landschützer7, Nathalie Lefèvre30, Andrew Lenton31, Sebastian Lienert32, Zhu Liu33, Danica Lombardozzi34, Gregg Marland35, Nicolas Metzl30, David R. Munro11, David R. Munro36, Julia E. M. S. Nabel7, S. Nakaoka16, Yosuke Niwa16, Kevin D. O'Brien11, Kevin D. O'Brien37, Tsuneo Ono, Paul I. Palmer, Denis Pierrot38, Benjamin Poulter, Laure Resplandy39, Eddy Robertson40, Christian Rödenbeck7, Jörg Schwinger, Roland Séférian27, Ingunn Skjelvan, Adam J. P. Smith3, Adrienne J. Sutton11, Toste Tanhua41, Pieter P. Tans11, Hanqin Tian42, Bronte Tilbrook31, Bronte Tilbrook43, Guido R. van der Werf44, N. Vuichard9, Anthony P. Walker45, Rik Wanninkhof38, Andrew J. Watson2, David R. Willis23, Andy Wiltshire40, Wenping Yuan46, Xu Yue47, Sönke Zaehle7 
École Normale Supérieure1, University of Exeter2, Norwich Research Park3, University of Groningen4, Wageningen University and Research Centre5, Ludwig Maximilian University of Munich6, Max Planck Society7, Commonwealth Scientific and Industrial Research Organisation8, Université Paris-Saclay9, Stanford University10, National Oceanic and Atmospheric Administration11, National Institute for Space Research12, University of Southampton13, Bermuda Institute of Ocean Sciences14, PSL Research University15, National Institute for Environmental Studies16, Japan Agency for Marine-Earth Science and Technology17, University of Maryland, College Park18, University of Leeds19, International Institute of Minnesota20, Flanders Marine Institute21, ETH Zurich22, University of East Anglia23, German Aerospace Center24, Woods Hole Research Center25, University of Illinois at Urbana–Champaign26, University of Toulouse27, Japan Meteorological Agency28, Plymouth Marine Laboratory29, University of Paris30, Hobart Corporation31, Oeschger Centre for Climate Change Research32, Tsinghua University33, National Center for Atmospheric Research34, Appalachian State University35, University of Colorado Boulder36, University of Washington37, Atlantic Oceanographic and Meteorological Laboratory38, Princeton University39, Met Office40, Leibniz Institute of Marine Sciences41, Auburn University42, University of Tasmania43, VU University Amsterdam44, Oak Ridge National Laboratory45, Sun Yat-sen University46, Nanjing University47
TL;DR: In this paper, the authors describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties, including emissions from land use and land-use change data and bookkeeping models.
Abstract: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important 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 methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. 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 last decade available (2010–2019), EFOS was 9.6 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.6 ± 0.7 GtC yr−1. For the same decade, GATM was 5.1 ± 0.02 GtC yr−1 (2.4 ± 0.01 ppm yr−1), SOCEAN 2.5 ± 0.6 GtC yr−1, and SLAND 3.4 ± 0.9 GtC yr−1, with a budget imbalance BIM of −0.1 GtC yr−1 indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in EFOS was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.7 ± 0.5 GtC yr−1 when cement carbonation sink is included), and ELUC was 1.8 ± 0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5 ± 0.9 GtC yr−1 (42.2 ± 3.3 GtCO2). Also for 2019, GATM was 5.4 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.6 ± 0.6 GtC yr−1, and SLAND was 3.1 ± 1.2 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in EFOS relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019; Le Quere et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020).

1,764 citations

Journal ArticleDOI
Corinne Le Quéré1, Robbie M. Andrew, Pierre Friedlingstein2, Stephen Sitch2, Judith Hauck3, Julia Pongratz4, Julia Pongratz5, Penelope A. Pickers1, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell6, Almut Arneth7, Vivek K. Arora, Leticia Barbero8, Leticia Barbero9, Ana Bastos4, Laurent Bopp10, Frédéric Chevallier11, Louise Chini12, Philippe Ciais11, Scott C. Doney13, Thanos Gkritzalis14, Daniel S. Goll11, Ian Harris1, Vanessa Haverd6, Forrest M. Hoffman15, Mario Hoppema3, Richard A. Houghton16, George C. Hurtt12, Tatiana Ilyina5, Atul K. Jain17, Truls Johannessen18, Chris D. Jones19, Etsushi Kato, Ralph F. Keeling20, Kees Klein Goldewijk21, Kees Klein Goldewijk22, Peter Landschützer5, Nathalie Lefèvre23, Sebastian Lienert24, Zhu Liu1, Zhu Liu25, Danica Lombardozzi26, Nicolas Metzl23, David R. Munro27, Julia E. M. S. Nabel5, Shin-Ichiro Nakaoka28, Craig Neill29, Craig Neill30, Are Olsen18, T. Ono, Prabir K. Patra31, Anna Peregon11, Wouter Peters32, Wouter Peters33, Philippe Peylin11, Benjamin Pfeil18, Benjamin Pfeil34, Denis Pierrot9, Denis Pierrot8, Benjamin Poulter35, Gregor Rehder36, Laure Resplandy37, Eddy Robertson19, Matthias Rocher11, Christian Rödenbeck5, Ute Schuster2, Jörg Schwinger34, Roland Séférian11, Ingunn Skjelvan34, Tobias Steinhoff38, Adrienne J. Sutton39, Pieter P. Tans39, Hanqin Tian40, Bronte Tilbrook29, Bronte Tilbrook30, Francesco N. Tubiello41, Ingrid T. van der Laan-Luijkx33, Guido R. van der Werf42, Nicolas Viovy11, Anthony P. Walker15, Andy Wiltshire19, Rebecca Wright1, Sönke Zaehle5, Bo Zheng11 
University of East Anglia1, University of Exeter2, Alfred Wegener Institute for Polar and Marine Research3, Ludwig Maximilian University of Munich4, Max Planck Society5, Commonwealth Scientific and Industrial Research Organisation6, Karlsruhe Institute of Technology7, Cooperative Institute for Marine and Atmospheric Studies8, Atlantic Oceanographic and Meteorological Laboratory9, École Normale Supérieure10, Centre national de la recherche scientifique11, University of Maryland, College Park12, University of Virginia13, Flanders Marine Institute14, Oak Ridge National Laboratory15, Woods Hole Research Center16, University of Illinois at Urbana–Champaign17, Geophysical Institute, University of Bergen18, Met Office19, University of California, San Diego20, Netherlands Environmental Assessment Agency21, Utrecht University22, University of Paris23, Oeschger Centre for Climate Change Research24, Tsinghua University25, National Center for Atmospheric Research26, Institute of Arctic and Alpine Research27, National Institute for Environmental Studies28, Cooperative Research Centre29, Hobart Corporation30, Japan Agency for Marine-Earth Science and Technology31, University of Groningen32, Wageningen University and Research Centre33, Bjerknes Centre for Climate Research34, Goddard Space Flight Center35, Leibniz Institute for Baltic Sea Research36, Princeton University37, Leibniz Institute of Marine Sciences38, National Oceanic and Atmospheric Administration39, Auburn University40, Food and Agriculture Organization41, VU University Amsterdam42
TL;DR: In this article, the authors describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties, including emissions from land use and land-use change data and bookkeeping models.
Abstract: . Accurate assessment of anthropogenic carbon dioxide ( CO2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions ( EFF ) are based on energy statistics and cement production data, while emissions from land use and land-use change ( ELUC ), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate ( GATM ) is computed from the annual changes in concentration. The ocean CO2 sink ( SOCEAN ) and terrestrial CO2 sink ( SLAND ) are estimated with global process models constrained by observations. 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 last decade available (2008–2017), EFF was 9.4±0.5 GtC yr −1 , ELUC 1.5±0.7 GtC yr −1 , GATM 4.7±0.02 GtC yr −1 , SOCEAN 2.4±0.5 GtC yr −1 , and SLAND 3.2±0.8 GtC yr −1 , with a budget imbalance BIM of 0.5 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr −1 . Also for 2017, ELUC was 1.4±0.7 GtC yr −1 , GATM was 4.6±0.2 GtC yr −1 , SOCEAN was 2.5±0.5 GtC yr −1 , and SLAND was 3.8±0.8 GtC yr −1 , with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of + 2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr −1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quere et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018 .

1,458 citations

Journal ArticleDOI
University of East Anglia1, University of Oslo2, Commonwealth Scientific and Industrial Research Organisation3, University of Exeter4, Oak Ridge National Laboratory5, National Oceanic and Atmospheric Administration6, Woods Hole Research Center7, University of California, San Diego8, Karlsruhe Institute of Technology9, Cooperative Institute for Marine and Atmospheric Studies10, Centre national de la recherche scientifique11, University of Maryland, College Park12, National Institute of Water and Atmospheric Research13, Woods Hole Oceanographic Institution14, Flanders Marine Institute15, Alfred Wegener Institute for Polar and Marine Research16, Netherlands Environmental Assessment Agency17, University of Illinois at Urbana–Champaign18, Leibniz Institute of Marine Sciences19, Max Planck Society20, University of Paris21, Hobart Corporation22, Oeschger Centre for Climate Change Research23, University of Bern24, National Center for Atmospheric Research25, University of Miami26, Council of Scientific and Industrial Research27, University of Colorado Boulder28, National Institute for Environmental Studies29, Joint Institute for the Study of the Atmosphere and Ocean30, Geophysical Institute, University of Bergen31, Goddard Space Flight Center32, Montana State University33, University of New Hampshire34, Bjerknes Centre for Climate Research35, Imperial College London36, Lamont–Doherty Earth Observatory37, Auburn University38, Wageningen University and Research Centre39, VU University Amsterdam40, Met Office41
TL;DR: In this article, the authors quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community.
Abstract: . Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr−1 that took place during 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Nino conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quere et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center ( doi:10.3334/CDIAC/GCP_2016 ).

1,224 citations

Journal ArticleDOI
TL;DR: The Global Fire Emissions Database (GFED) as mentioned in this paper has been used to quantify global fire emissions patterns during 1997-2016, with the largest impact on emissions in temperate North America, Central America, Europe, and temperate Asia.
Abstract: . Climate, land use, and other anthropogenic and natural drivers have the potential to influence fire dynamics in many regions. To develop a mechanistic understanding of the changing role of these drivers and their impact on atmospheric composition, long-term fire records are needed that fuse information from different satellite and in situ data streams. Here we describe the fourth version of the Global Fire Emissions Database (GFED) and quantify global fire emissions patterns during 1997–2016. The modeling system, based on the Carnegie–Ames–Stanford Approach (CASA) biogeochemical model, has several modifications from the previous version and uses higher quality input datasets. Significant upgrades include (1) new burned area estimates with contributions from small fires, (2) a revised fuel consumption parameterization optimized using field observations, (3) modifications that improve the representation of fuel consumption in frequently burning landscapes, and (4) fire severity estimates that better represent continental differences in burning processes across boreal regions of North America and Eurasia. The new version has a higher spatial resolution (0.25°) and uses a different set of emission factors that separately resolves trace gas and aerosol emissions from temperate and boreal forest ecosystems. Global mean carbon emissions using the burned area dataset with small fires (GFED4s) were 2.2 × 1015 grams of carbon per year (Pg C yr−1) during 1997–2016, with a maximum in 1997 (3.0 Pg C yr−1) and minimum in 2013 (1.8 Pg C yr−1). These estimates were 11 % higher than our previous estimates (GFED3) during 1997–2011, when the two datasets overlapped. This net increase was the result of a substantial increase in burned area (37 %), mostly due to the inclusion of small fires, and a modest decrease in mean fuel consumption (−19 %) to better match estimates from field studies, primarily in savannas and grasslands. For trace gas and aerosol emissions, differences between GFED4s and GFED3 were often larger due to the use of revised emission factors. If small fire burned area was excluded (GFED4 without the s for small fires), average emissions were 1.5 Pg C yr−1. The addition of small fires had the largest impact on emissions in temperate North America, Central America, Europe, and temperate Asia. This small fire layer carries substantial uncertainties; improving these estimates will require use of new burned area products derived from high-resolution satellite imagery. Our revised dataset provides an internally consistent set of burned area and emissions that may contribute to a better understanding of multi-decadal changes in fire dynamics and their impact on the Earth system. GFED data are available from http://www.globalfiredata.org .

1,135 citations

Journal ArticleDOI
Marielle Saunois1, Ann R. Stavert2, Ben Poulter3, Philippe Bousquet1, Josep G. Canadell2, Robert B. Jackson4, Peter A. Raymond5, Edward J. Dlugokencky6, Sander Houweling7, Sander Houweling8, Prabir K. Patra9, Prabir K. Patra10, Philippe Ciais1, Vivek K. Arora, David Bastviken11, Peter Bergamaschi, Donald R. Blake12, Gordon Brailsford13, Lori Bruhwiler6, Kimberly M. Carlson14, Mark Carrol3, Simona Castaldi15, Naveen Chandra9, Cyril Crevoisier16, Patrick M. Crill17, Kristofer R. Covey18, Charles L. Curry19, Giuseppe Etiope20, Giuseppe Etiope21, Christian Frankenberg22, Nicola Gedney23, Michaela I. Hegglin24, Lena Höglund-Isaksson25, Gustaf Hugelius17, Misa Ishizawa26, Akihiko Ito26, Greet Janssens-Maenhout, Katherine M. Jensen27, Fortunat Joos28, Thomas Kleinen29, Paul B. Krummel2, Ray L. Langenfelds2, Goulven Gildas Laruelle, Licheng Liu30, Toshinobu Machida26, Shamil Maksyutov26, Kyle C. McDonald27, Joe McNorton31, Paul A. Miller32, Joe R. Melton, Isamu Morino26, Jurek Müller28, Fabiola Murguia-Flores33, Vaishali Naik34, Yosuke Niwa26, Sergio Noce, Simon O'Doherty33, Robert J. Parker35, Changhui Peng36, Shushi Peng37, Glen P. Peters, Catherine Prigent, Ronald G. Prinn38, Michel Ramonet1, Pierre Regnier, William J. Riley39, Judith A. Rosentreter40, Arjo Segers, Isobel J. Simpson12, Hao Shi41, Steven J. Smith42, L. Paul Steele2, Brett F. Thornton17, Hanqin Tian41, Yasunori Tohjima26, Francesco N. Tubiello43, Aki Tsuruta44, Nicolas Viovy1, Apostolos Voulgarakis45, Apostolos Voulgarakis46, Thomas Weber47, Michiel van Weele48, Guido R. van der Werf7, Ray F. Weiss49, Doug Worthy, Debra Wunch50, Yi Yin22, Yi Yin1, Yukio Yoshida26, Weiya Zhang32, Zhen Zhang51, Yuanhong Zhao1, Bo Zheng1, Qing Zhu39, Qiuan Zhu52, Qianlai Zhuang30 
Université Paris-Saclay1, Commonwealth Scientific and Industrial Research Organisation2, Goddard Space Flight Center3, Stanford University4, Yale University5, National Oceanic and Atmospheric Administration6, VU University Amsterdam7, Netherlands Institute for Space Research8, Japan Agency for Marine-Earth Science and Technology9, Chiba University10, Linköping University11, University of California, Irvine12, National Institute of Water and Atmospheric Research13, New York University14, Seconda Università degli Studi di Napoli15, École Polytechnique16, Stockholm University17, Skidmore College18, University of Victoria19, National Institute of Geophysics and Volcanology20, Babeș-Bolyai University21, California Institute of Technology22, Met Office23, University of Reading24, International Institute for Applied Systems Analysis25, National Institute for Environmental Studies26, City University of New York27, University of Bern28, Max Planck Society29, Purdue University30, European Centre for Medium-Range Weather Forecasts31, Lund University32, University of Bristol33, Geophysical Fluid Dynamics Laboratory34, University of Leicester35, Université du Québec à Montréal36, Peking University37, Massachusetts Institute of Technology38, Lawrence Berkeley National Laboratory39, Southern Cross University40, Auburn University41, Joint Global Change Research Institute42, Food and Agriculture Organization43, Finnish Meteorological Institute44, Technical University of Crete45, Imperial College London46, University of Rochester47, Royal Netherlands Meteorological Institute48, Scripps Institution of Oceanography49, University of Toronto50, University of Maryland, College Park51, Hohai University52
TL;DR: The second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modeling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations) as discussed by the authors.
Abstract: Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.

1,047 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
2023144
2022298
2021269
2020191
2019102
201876