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Volume 17, issue 18
Atmos. Chem. Phys., 17, 11135-11161, 2017
https://doi.org/10.5194/acp-17-11135-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 17, 11135-11161, 2017
https://doi.org/10.5194/acp-17-11135-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 20 Sep 2017

Research article | 20 Sep 2017

Variability and quasi-decadal changes in the methane budget over the period 2000–2012

Marielle Saunois1, Philippe Bousquet1, Ben Poulter2, Anna Peregon1, Philippe Ciais1, Josep G. Canadell3, Edward J. Dlugokencky4, Giuseppe Etiope5,6, David Bastviken7, Sander Houweling8,9, Greet Janssens-Maenhout10, Francesco N. Tubiello11, Simona Castaldi12,13,14, Robert B. Jackson15, Mihai Alexe10, Vivek K. Arora16, David J. Beerling17, Peter Bergamaschi10, Donald R. Blake18, Gordon Brailsford19, Lori Bruhwiler4, Cyril Crevoisier20, Patrick Crill21, Kristofer Covey22, Christian Frankenberg23,24, Nicola Gedney25, Lena Höglund-Isaksson26, Misa Ishizawa27, Akihiko Ito27, Fortunat Joos28, Heon-Sook Kim27, Thomas Kleinen29, Paul Krummel30, Jean-François Lamarque31, Ray Langenfelds30, Robin Locatelli1, Toshinobu Machida27, Shamil Maksyutov27, Joe R. Melton32, Isamu Morino27, Vaishali Naik33, Simon O'Doherty34, Frans-Jan W. Parmentier35, Prabir K. Patra36, Changhui Peng37,38, Shushi Peng1,39, Glen P. Peters40, Isabelle Pison1, Ronald Prinn41, Michel Ramonet1, William J. Riley42, Makoto Saito27, Monia Santini13,14, Ronny Schroeder43, Isobel J. Simpson18, Renato Spahni28, Atsushi Takizawa44, Brett F. Thornton21, Hanqin Tian45, Yasunori Tohjima27, Nicolas Viovy1, Apostolos Voulgarakis46, Ray Weiss47, David J. Wilton17, Andy Wiltshire48, Doug Worthy49, Debra Wunch50, Xiyan Xu42,51, Yukio Yoshida27, Bowen Zhang45, Zhen Zhang2,52, and Qiuan Zhu38 Marielle Saunois et al.
  • 1Laboratoire des Sciences du Climat et de l'Environnement, LSCE-IPSL (CEA-CNRS-UVSQ), Université Paris-Saclay, 91191 Gif-sur-Yvette, France
  • 2NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD 20771, USA
  • 3Global Carbon Project, CSIRO Oceans and Atmosphere, Canberra, ACT 2601, Australia
  • 4NOAA ESRL, 325 Broadway, Boulder, CO 80305, USA
  • 5Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma 2, via V. Murata 605, Roma 00143 , Italy
  • 6Faculty of Environmental Science and Engineering, Babes Bolyai University, Cluj-Napoca, Romania
  • 7Department of Thematic Studies – Environmental Change, Linköping University, 581 83 Linköping, Sweden
  • 8Netherlands Institute for Space Research (SRON), Sorbonnelaan 2, 3584 CA, Utrecht, the Netherlands
  • 9Institute for Marine and Atmospheric Research Sorbonnelaan 2, 3584 CA, Utrecht, the Netherlands
  • 10European Commission Joint Research Centre, Ispra (Va), Italy
  • 11Statistics Division, Food and Agriculture Organization of the United Nations (FAO), Viale delle Terme di Caracalla, Rome 00153, Italy
  • 12Dipartimento di Scienze e Tecnologie Ambientali Biologiche e Farmaceutiche, Seconda Università di Napoli, via Vivaldi 43, 81100 Caserta, Italy
  • 13Far East Federal University (FEFU), Vladivostok, Russky Island, Russia
  • 14Euro-Mediterranean Center on Climate Change, Via Augusto Imperatore 16, 73100 Lecce, Italy
  • 15School of Earth, Energy and Environmental Sciences, Stanford University, Stanford, CA 94305-2210, USA
  • 16Canadian Centre for Climate Modelling and Analysis, Climate Research Division, Environment and Climate Change Canada, Victoria, BC, V8W 2Y2, Canada
  • 17Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK
  • 18University of California Irvine, 570 Rowland Hall, Irvine, CA 92697, USA
  • 19National Institute of Water and Atmospheric Research, 301 Evans Bay Parade, Wellington, New Zealand
  • 20Laboratoire de Météorologie Dynamique, LMD/IPSL, CNRS École polytechnique, Université Paris-Saclay, 91120 Palaiseau, France
  • 21Department of Geological Sciences and Bolin Centre for Climate Research, Svante Arrhenius väg 8, 106 91 Stockholm, Sweden
  • 22School of Forestry and Environmental Studies, Yale University, New Haven, CT 06511, USA
  • 23California Institute of Technology, Geological and Planetary Sciences, Pasadena, CA, USA
  • 24Jet Propulsion Laboratory, M/S 183-601, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
  • 25Met Office Hadley Centre, Joint Centre for Hydrometeorological Research, Maclean Building, Wallingford OX10 8BB, UK
  • 26Air Quality and Greenhouse Gases program (AIR), International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, Austria
  • 27Center for Global Environmental Research, National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, Japan
  • 28Climate and Environmental Physics, Physics Institute and Oeschger Center for Climate Change Research, University of Bern, Sidlerstr. 5, 3012 Bern, Switzerland
  • 29Max Planck Institute for Meteorology, Bundesstrasse 53, 20146 Hamburg, Germany
  • 30CSIRO Oceans and Atmosphere, Aspendale, Victoria 3195, Australia
  • 31NCAR, P.O. Box 3000, Boulder, CO 80307-3000, USA
  • 32Climate Research Division, Environment and Climate Change Canada, Victoria, BC, V8W 2Y2, Canada
  • 33NOAA, GFDL, 201 Forrestal Rd., Princeton, NJ 08540, USA
  • 34School of Chemistry, University of Bristol, Cantock's Close, Clifton, Bristol BS8 1TS, UK
  • 35Department of Arctic and Marine Biology, Faculty of Biosciences, Fisheries and Economics, UiT: The Arctic University of Norway, 9037 Tromsø, Norway
  • 36Department of Environmental Geochemical Cycle Research and Institute of Arctic Climate and Environment Research, JAMSTEC, 3173-25 Showa-machi, Kanazawa-ku, Yokohama, 236-0001, Japan
  • 37Department of Biological Sciences, Institute of Environmental Sciences, University of Quebec at Montreal, Montreal, QC H3C 3P8, Canada
  • 38State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling, Shaanxi 712100, China
  • 39Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
  • 40CICERO Center for International Climate Research, Pb. 1129 Blindern, 0318 Oslo, Norway
  • 41Massachusetts Institute of Technology (MIT), Building 54-1312, Cambridge, MA 02139, USA
  • 42Climate and Ecosystem Sciences Division, Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA 94720, USA
  • 43Department of Civil and Environmental Engineering, University of New Hampshire, Durham, NH 03824, USA
  • 44Japan Meteorological Agency (JMA), 1-3-4 Otemachi, Chiyoda-ku, Tokyo 100-8122, Japan
  • 45International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, 602 Duncan Drive, Auburn, AL 36849, USA
  • 46Space and Atmospheric Physics, Blackett Laboratory, Imperial College London, London SW7 2AZ, UK
  • 47Scripps Institution of Oceanography (SIO), University of California San Diego, La Jolla, CA 92093, USA
  • 48Met Office Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK
  • 49Environment Canada, 4905, rue Dufferin, Toronto, Canada
  • 50Department of Physics, University of Toronto, 60 St. George Street, Toronto, Ontario, Canada
  • 51CAS Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • 52Swiss Federal Research Institute WSL, Birmensdorf 8059, Switzerland

Abstract. Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches.

The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32]Tg CH4yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions.

The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained.

The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations.

In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

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Following the Global Methane Budget 2000–2012 published in Saunois et al. (2016), we use the same dataset of bottom-up and top-down approaches to discuss the variations in methane emissions over the period 2000–2012. The changes in emissions are discussed both in terms of trends and quasi-decadal changes. The ensemble gathered here allows us to synthesise the robust changes in terms of regional and sectorial contributions to the increasing methane emissions.
Following the Global Methane Budget 2000–2012 published in Saunois et al. (2016), we use the...
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