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

Journal Article · · Atmospheric Chemistry and Physics (Online)
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  1. Univ. Paris-Saclay, Gif-sur-Yvette (France). Lab. des Sciences du Climat et de l'Environnement, LSCE-IPSL (CEA-CNRS-UVSQ)
  2. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States). Biospheric Sciences Lab.
  3. Commonwealth Scientific and Industrial Research Organization (CSIRO), Canberra, ACT (Australia). CSIRO Oceans and Atmosphere, Global Carbon Project
  4. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Earth System Research Lab.
  5. Istituto Nazionale di Geofisica e Vulcanologia, Roma (Italy); Babes Bolyai Univ., Cluj-Napoca (Romania)
  6. Linköping Univ., Linköping (Sweden)
  7. Netherlands Inst. for Space Research (SRON), Utrecht (Netherlands); Institute for Marine and Atmospheric Research, Utrecht (Netherlands)
  8. European Commission Joint Research Centre, Ispra, Italy
  9. Food and Agriculture Organization of the United Nations (FAO), Rome (Italy). Statistics Division
  10. Seconda Univ. di Napoli, Caserta (Italy); Far East Federal University (FEFU), Vladivostok, Russky Island (Russia); Euro-Mediterranean Center on Climate Change, Lecce (Italy)
  11. Stanford Univ., CA (United States)
  12. Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada)
  13. Univ. of Sheffield (United Kingdom)
  14. Univ. of California, Irvine, CA (United States)
  15. National Inst. of Water and Atmospheric Research, Wellington (New Zealand)
  16. Ecole Polytechnique, Palaiseau (France). Lab. de Météorologie Dynamique, LMD/IPSL
  17. Dept. of Geological Sciences and Bolin Centre for Climate Research, Stockholm (Sweden)
  18. Yale Univ., New Haven, CT (United States)
  19. California Inst. of Technology (CalTech), La Canada Flintridge, CA (United States). Jet Propulsion Lab.
  20. Met Office Hadley Centre, Joint Centre for Hydrometeorological Research, Wallingford (United Kingdom)
  21. International Inst. for Applied Systems Analysis (IIASA), Laxenburg (Austria)
  22. Center for Global Environmental Research, National Inst. for Environmental Studies (NIES), Tsukuba (Japan)
  23. National Inst. for Environmental Studies (NIES), Tsukuba (Japan)
  24. Univ. of Bern, Bern (Switzerland)
  25. Max Planck Inst. for Meteorology, Hamburg (Germany)
  26. Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, VIC (Australia). Oceans and Atmosphere
  27. NCAR, Boulder, CO (United States)
  28. Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, VIC (Australia). Oceans and Atmosphere
  29. Environment and Climate Change Canada, Victoria, BC (Canada). Climate Research Division
  30. National Oceanic and Atmospheric Administration (NOAA), Princeton, NJ (United States)
  31. Univ. of Bristol, Clifton, Bristol (United Kingdom)
  32. Arctic Univ. of Norway, Tromsø (Norway)
  33. Dept. of Environmental Geochemical Cycle Research and Inst. of Arctic Climate and Environment Research, JAMSTEC, Yokohama (Japan)
  34. Univ. of Quebec (Canada); Northwest A&F Univ., Yangling (China)
  35. Univ. Paris-Saclay, Gif-sur-Yvette (France). Lab. des Sciences du Climat et de l'Environnement, LSCE-IPSL (CEA-CNRS-UVSQ); Peking Univ., Beijing (China)
  36. CICERO Center for International Climate Research, Oslo, (Norway)
  37. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  38. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  39. Univ. of New Hampshire, Durham, NH (United States)
  40. Japan Meteorological Agency (JMA), Tokyo (Japan)
  41. Auburn Univ., AL (United States)
  42. Imperial College, London (United Kingdom)
  43. Univ. of California, San Diego, CA (United States). Scripps Inst. of Oceanography (SIO)
  44. Met Office Hadley Centre, Exeter (United Kingdom)
  45. Environment Canada,Toronto (Canada)
  46. Univ. of Toronto, ON (Canada)
  47. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chinese Academy of Sciences (CAS), Beijing (China)
  48. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Swiss Federal Research Institute WSL, Birmensdorf (Switzerland)
  49. Northwest A&F Univ., Yangling, Shaanxi (China). State Key Lab. of Soil Erosion and Dryland Farming on the Loess Plateau
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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.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1476543
Journal Information:
Atmospheric Chemistry and Physics (Online), Vol. 17, Issue 18; ISSN 1680-7324
Publisher:
European Geosciences UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 73 works
Citation information provided by
Web of Science

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The Fire INventory from NCAR (FINN) – a high resolution global model to estimate the emissions from open burning journal January 2010
Global wetland contribution to 2000–2012 atmospheric methane growth rate dynamics text January 2017
Effect of emission changes in Southeast Asia on global hydroxyl and methane lifetime journal September 2009
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WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia journal January 2015
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Inverse modelling of CH4 emissions for 2010-2011 using different satellite retrieval products from GOSAT and SCIAMACHY text January 2015
WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia text January 2015
Preindustrial to present-day changes in tropospheric hydroxyl radical and methane lifetime from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) text January 2013
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Cited By (23)

The role of environmental driving factors in historical and projected carbon dynamics of wetland ecosystems in Alaska journal December 2016
On the Causes and Consequences of Recent Trends in Atmospheric Methane journal August 2019
Changes in Global Tropospheric OH Expected as a Result of Climate Change Over the Last Several Decades journal September 2018
Space‐Based Observations for Understanding Changes in the Arctic‐Boreal Zone journal January 2020
Revisiting enteric methane emissions from domestic ruminants and their δ13CCH4 source signature journal July 2019
Interpreting contemporary trends in atmospheric methane journal February 2019
Methane production and emissions in trees and forests journal January 2019
Rising methane: A new climate challenge journal June 2019
Long-Term Trends of Atmospheric CH4 Concentration across China from 2002 to 2016 journal March 2019
Methane Emission Estimates by the Global High-Resolution Inverse Model Using National Inventories journal October 2019
Attribution of recent increases in atmospheric methane through 3-D inverse modelling journal January 2018
How a European network may help with estimating methane emissions on the French national scale journal January 2018
An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data journal January 2019
Investigation of the global methane budget over 1980–2017 using GFDL-AM4.1 journal January 2020
Atmospheric characterization through fused mobile airborne and surface in situ surveys: methane emissions quantification from a producing oil field journal January 2018
Disequilibrium of terrestrial ecosystem CO2 budget caused by disturbance-induced emissions and non-CO2 carbon export flows: a global model assessment journal January 2019
History of chemically and radiatively important atmospheric gases from the Advanced Global Atmospheric Gases Experiment (AGAGE) journal January 2018
Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations journal January 2019
EDGAR v4.3.2 Global Atlas of the three major greenhouse gas emissions for the period 1970–2012 journal January 2019
The cycle of nitrogen in river systems: sources, transformation, and flux journal January 2018
Assessment of the theoretical limit in instrumental detectability of northern high-latitude methane sources using δ13CCH4 atmospheric signals journal January 2019
Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations text January 2019
Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations text January 2019

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