Global Methane Budget 2016 The Global Methane budget

Global Methane Budget 2016 The Global Methane budget

Global Methane Budget 2016 The Global Methane budget for 2000-2012 Published on 12 December 2016 PowerPoint version 1.0 (released 12 December 2016) Acknowledgements The work presented here has been possible thanks to the enormous observational and modeling efforts of the institutions and networks below Atmospheric CH4 datasets NOAA/ESRL (Dlugokencky et al., 2011) AGAGE (Rigby et al., 2008) CSIRO (Francey et al., 1999) UCI (Simpson et al., 2012) Top-down atmospheric inversions TM5-4DVAR (Bergamaschi et al., 2009) LMDZ-MIOP (Pison et al., 2013) CarbonTracker-CH4 (Bruhwiler et al., 2014) TM5-4DVAR (Houweling et al., 2014) LMDZt-SACS (Locatelli et al., 2015) NIESTM (Saeki et al., 2013; Kim et al., 2011) ACTM (Patra et al., 2016) GELCA (Ishizawa et al., 2016; Zhuralev et al., 2013)

Bottom-up modeling Description of models contributing to the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP, Lamarque et al., 2013; Voulgarakis et al., 2013; Naik et al., 2013) Bottom-up studies data and modeling CLM 4.5 (Riley et al., 2011; Xu et al., 2016) CTEM (Melton and Arora, 2016) DLEM (Tian et al., 2010;2015) JULES (Hayman et al., 2014) LPJ-MPI (Kleinen et a., 2012) LPJ-wsl (Hodson et al, 2011) LPX-Bern (Spahni et al., 2011) ORCHIDEE (Ringeval et al., 2011) SDGVM (Woodward and Lomas, 2004) TRIPLEX-GHG (Zhu et al., 2104; 2015) VISIT (Ito ad Inatomi, 2012) GFEDv3 (Van der Werf et al., 2010) GFEDv4s (Giglio et al., 2013) GFASv1.0 (Kaiser et al., 2012) FINNv1 (Wiedinmyer et al., 2011) IIASA (Hglund-Isaksonn, 2012; Klimont et al., 2016) EPA, 2011; 2012 EDGARv4.2FT 2010 and FT2012 (EDGARv4.2, 2013;

2014) FAO (Tubiello et al., 2013) Full references provided in Saunois et al. 2016, ESSD Contributors: 81 people | 53 organisations | 15 countries Scientific contributors : Marielle Saunois France | Philippe Bousquet France | Ben Poulter USA | Anna Peregon France | Philippe Ciais France | Josep G. Canadell Australia| Edward J. Dlugokencky USA | Giuseppe Etiope Italy | David Bastviken Sweden | Sander Houweling The Netherlands | Greet JanssensMaenhout Italy | Francesco N. Tubiello Italy | Simona Castaldi Italy | Robert B. Jackson USA | Mihai Alexe Italy | Vivek K. Arora Canada| David J. Beerling UK | Peter Bergamaschi Italy | Donald R. Blake USA | Gordon Brailsford New Zealand| Victor Brovkin Germany | Lori Bruhwiler USA | Kristofer Covey USA | Cyril Crevoisier France | Patrick Crill Sweden | Kristofer Covey USA | Charles Curry Canada | Christian Frankenberg USA | Nicola Gedney UK | Lena Hglund-Isaksson Austria | Misa Ishizawa Japan | Akihiko Ito Japan | Fortunat Joos Switzerland| Heon-Sook Kim Japan | Thomas Kleinen Germany | Paul Krummel Australia| Jean-Franois Lamarque USA | Ray Langenfelds Australia | Robin Locatelli France | Toshinobu Machida Japan | Shamil Maksyutov Japan | Kyle C. McDonald USA | Julia Marshall Germany | Joe R. Melton Canada | Isamu Morino Japan | Vaishala Naik USA | Simon ODoherty UK | Frans-Jan W. Parmentier Sweden | Prabir K. Patra Japan | Changhui Peng Canada | Shushi Peng China | Glen P. Peters Norway | Isabelle Pison France | Catherine Prigent France | Ronald Prinn USA | Michel Ramonet France | William J. Riley USA | Makoto Saito Japan | Monia Santini Italy | Ronny Schroeder USA | Isobel J. Simpson USA | Renato Spahni Switzerland | Paul Steele Australia| Atsushi Takizawa Japan | Brett F. Thornton Sweden | Hanqin Tian USA | Yasunori Tohjima Japan | Nicolas Viovy France | Apostolos Voulgarakis UK | Michiel van Weele The Netherlands | Guido van der Werf The Netherlands | Ray Weiss USA | Christine Wiedinmyer USA | David J. Wilton UK | Andy Wiltshire UK | Doug Worthy Canada | Debra B. Wunch Canada | Xiyan Xu USA | Yukio Yoshida Japan | Bowen Zhang USA | Zhen Zhang USA |

Qiuan Zhu China Data visualisation support at LSCE : Patrick Brockmann France | Cathy Nangini France Papers http://www.earth-syst-sci-data.net/8/697/2016/ http://iopscience.iop.org/article/10.1088/1748-9326/11/12/120207 Contact: [email protected] Data access http://www.globalcarbonproject.org/methanebudget http://cdiac.ornl.gov/GCP/methanebudget/2016/ Contacts Global Methane Budget Website http://www.globalcarbonproject.org/methanebudget Activity Contacts Email

Philippe Bousquet [email protected] Marielle Saunois [email protected] Rob Jackson [email protected] Ben Poulter [email protected] Pep Canadell [email protected] All data are shown in teragrams CH4 (TgCH4) for emissions and sinks parts per billion (ppb) for atmospheric concentrations 1 teragram (Tg) = 1 million tonnes = 11012g

2.78 Tg CH4 per ppb Disclaimer The Global Methane Budget and the information presented here are intended for those interested in learning about the carbon cycle, and how human activities are changing it. The information contained herein is provided as a public service, with the understanding that the Global Carbon Project team make no warranties, either expressed or implied, concerning the accuracy, completeness, reliability, or suitability of the information. Context & Methods The methane context After carbon dioxide (CO2), methane (CH4) is the second most important greenhouse gas contributing to human-induced climate change. For a time horizon of 100 years, CH4 has a Global Warming Potential 28 times larger than CO2.

Methane is responsible for 20% of the global warming produced by all greenhouse gases so far. The concentration of CH4 in the atmosphere is 150% above pre-industrial levels (cf. 1750). The atmospheric life time of CH4 is 92 years, making it a good target for climate change mitigation Updated to 2012 Methane also contributes to tropospheric production of ozone, a pollutant that harms human health and ecosystems.

Methane also leads to production of water vapor in the stratosphere by chemical reactions, enhancing global warming. Sources : Saunois et al. 2016, ESDD; Kirschke et al. 2013, NatureGeo.; IPCC 2013 5AR; Voulgarakis et al., 2013 An ensemble of tools and data to estimate the global methane budget Bottom-up budget Atmospheric observations Emission inventories Biogeochemistry models & datadriven methods Methane sinks Inverse models Top-down budget

Ground-based data from observation networks (AGAGE, CSIRO, NOAA, UCI, LSCE, others). Satellite data (SCIAMACHY, GOSAT) Agriculture and waste related emissions, fossil fuel emissions (EDGARv4.2, USEPA, GAINS, FAO). Fire emissions (GFED3 & 4s, FINN, GFAS, FAO). Biofuel estimates Ensemble of 11 wetland models,

following the WETCHIMP intercomparison Model for Termites emissions Other sources from literature From Kirschke et al., (2013) Longterm trends and decadal variability of the OH sink. ACCMIP CTMs intercomparison. Soil uptake & chlorine sink taken from the literature Suite of eight atmospheric inversion models (TM5-4DVAR (JRC & SRON), LMDZMIOP, PYVARLMDz, C-TrackerCH4, GELCA, ACTM,

TM3, NIESTM). Ensemble of 30 inversions (diff. obs & setup) GATM (ppb yr-1) CH4 (ppb) CH4 Atmospheric Growth Rate, 1983-2012 Atmospheric observations 2000-2006: 0.60.1 ppb/yr 2007-2012: 5.50.6 ppb/yr Source: Saunois et al. 2016, ESSD (Fig. 1) Slowdown of atmospheric growth rate

before 2006 Resumed increase after 2006 Anthropogenic Methane Emissions & RCPs EDGARv4.2 infers an increase in emissions that is roughly twice as fast as EPA and GAINS-ECLIPSE5a before 2010 Bottom-up inventories are higher than any RCPs scenarios, except RCP8.5 Atmospheric observations Emission inventories 1850 Obs. RCP 4.5 1800

RCP 6 RCP 2.5 1750 400 2005 380 2008 USEPA 2011 EDGARv42FT2012 GAINS-ECLIPSE5a 2014 2017 2020 RCP 8.5 360 340 RCP 4.5

320 RCP 6 300 280 2005 RCP 2.5 2008 2011 2014 Years Source: based on Saunois et al. 2016, ERL; Meinshausen et al., 2011 2017 2020 41 40

39 38 37 1 CO2 emissions (Gt C.yr-1) Anthropogenic emissions (bottom plot): CH4 concentrations (ppb) The recent atmospheric increase is approaching the RCP8.5 scenario RCP 8.5 CH4 emissions (Tg CH4.yr-1) Methane concentrations rose even faster in 2014 and 2015, more than 10 ppb/yr. 42 CO2 concentrations (ppm)

1900 Atmospheric concentrations (top plot): 1 1 Observed Concentrations Compared to IPCC Projections Decadal emissions & sinks Global Methane Budget 2003-2012 http://www.globalcarbonatlas.org Mapping of the largest methane source categories Emission inventories Biogeochemistry models & datadriven methods

Source: Saunois et al. 2016, ESSD (Fig 3); Wetland methane emissions Wetlands are the largest natural global CH4 source Emission from an ensemble carbon-cycle models constrained with remote sensing surface water and inventory-based wetland area data. The resulting global flux range for natural wetland emissions is 153227 TgCH4/yr for the decade of 2003 2012, with an average of 185 TgCH4/yr. Biogeochemistry models & datadriven methods Source: Saunois et al. 2016, ESSD; Poulter et al, ERL in review Mapping other natural sources (a) Geological reservoirs based on a data-driven method

(b) Termites based on a Tprocess-based model e r m it e s 10 -3 m g (C H 4).m 4 0 .0 3 0 .0 2 0 .0 1 5 .0 1 2 .0 1 0 .0 5 .0 2 .0 1 .0 0 .5 0 .0

Other natural sources not mapped here are freshwater emissions, permafrost and hydrates Biogeochemistry models & datadriven methods Source: Saunois et al. 2016 (Fig 4); Etiope (2015), Kirschke et al., 2013) -2 .d a y -1 Methane Sinks (2000s) Tropospheric chlorine_x000d_15-40 Soil uptake_x000d_1045 Tg/yr Tg/yr Stratospheric chemistry_x000d_15- Tropospheric OH_x000d_450-620 85 Tg/yr Tg/yr

Source : Kirschke et al. 2013 Methane sinks Global methane emissions 2003-2012 Bottom-up budget Rice Enteric ferm & manure Landfills & waste Coal Gas & oil 185 [40%] 195 [15%] 30 [10%] 106 [20%] 59 [20%] 121 [20%] 42 [80%] 79 [10%] (TgCH4/yr) Top-down budget

Natural wetlands Agriculture & waste 167 [80%] 188 [65%] Fossil fuel use 105 [50%] 30 [30%] Biomass/biofuel burning 34 [55%] 199 [90%] Other natural emissions 64 [150%] Fresh waters 122 [100%] Mean [uncertainty= Wild animals 10 [100%] min-max range %] Wild fires 3 [100%] Termites 9 [120%] Geological 40 [50%]

Oceans 3 [100%] Permafrost 1 [100%] Mean [uncertainty= min-max range %] Bottom-up budget Bottom-up budget Process models, inventories, data driven methods 734 TgCH4/yr [596-884] Mean [min-max range %] Source : Saunois et al. 2016, ESSD Top-down budget Top-down budget Atmospheric inversions 559 TgCH4/yr [540-568] Global Methane Emissions 2003-2012

Global emissions: 559 TgCH4/yr [540-568] for TD 734 TgCH4/yr [596-884] for BU Top-down, left; Bottom-up, right TD and BU estimates generally agree for wetland and agricultural emissions Estimated fossil fuel emissions are lower for TD than for BU approaches Large discrepancy between TD and BU estimates for freshwaters Source: Saunois et al. 2016, ESSD (Fig 5) and natural geological sources (other natural sources) Biogeochemistry

Emission inventories models & datadriven methods Inverse models Regional Methane Sources (2003-2012) Top-down budget 60% of global methane emissions come from tropical sources Anthropogenic sources are responsible for 60% of global emissions. Source: Saunois et al. 2016 ERL (Fig 2) Inverse models An interactive view of the methane budget LINK : http://lsce-datavisgroup.github.io/MethaneBudget/ Top-down budget Bottom-up budget Source: Saunois et al. 2016 ESSD; Dataviz group of LSCE

Emission inventories Biogeochemistry models & datadriven methods Inverse models Regional Methane Sources (2003-2012) Source: Saunois et al. 2016 ESSD (Fig 7) Largest emissions in Tropical South America, South-East Asia and China (50% of global emissions) Dominance of wetland emissions in the tropics and boreal regions

Dominance of agriculture & waste in India and China Balance between agriculture & waste and fossil fuels at mid- latitudes Uncertain magnitude of wetland emissions in boreal regions between TD and BU Chinese emissions lower in TD than in BU, African emissions larger in TD than in BU Emission inventories Biogeochemistry models & datadriven methods Inverse models

Sink changes Impact of OH change in the methane sink ? Sustained OH increase can contribute to explain the the stagnation of atmospheric methane (before 2007) Stagnation or decrease in OH radicals can contribute to explain : the renewed increase of atmospheric methane since 2007 The lighter atmosphere in 13 C isotope since 2007 Source : Dalsoren et al., 2016 Key point: OH changes could have limited the emission changes necessary to explain the atmospheric methane variations An accelerated atmospheric increase since 2014

1830 ppb reached in 2015 +12.5 ppb/yr in 2014 +10.0 ppb/yr in 2015 Challenging signal to analyse Courtesy, Ed Dlugokencky, NOAA Highlights Unlike CO2, atmospheric CH4 concentrations are rising faster than at any time in the past two decades and, since 2014, are now above all but the most greenhouse-gas-intensive scenarios. A likely major driver of the recent rapid rise in global CH4 concentrations is increased biogenic emissions mostly from agriculture. Tropical regions play the most significant role as contributors to the atmospheric growth. Other sources including emissions from the use of fossil fuels have also increased. The role of methane sinks has to be further explored as a slower destruction of methane by OH radicals in the atmosphere could have also contributed to the observed atmospheric changes of the past decade. Methane global emissions were 559 TgCH4/yr [540-570] for 2003-2012 as inferred by an ensemble of atmospheric inversions (top-down approach). Methane mitigation offers rapid climate benefits and economic, health and agricultural cobenefits that are highly complementary to CO2 mitigation. Emission estimates from inventories/models (bottom-up approach) show larger global totals because of larger natural emissions. Improved emission inventories and estimates from

Global Carbon Atlas Explore GHG emissions at the global and country levels, compare among countries, visualize, and download data and illustrations (Emissions application). Also explore Outreach and Research. Methane section to come. www.globalcarbonatlas.org Acknowledgements The work presented in the Global Carbon Budget 2015 has been possible thanks to the contributions of hundreds of people involved in observational networks, modeling, and synthesis efforts. Not all of them are individually acknowledged in this presentation for reasons of space (see slide 2 for those individuals directly involved). Additional acknowledgement is owed to those institutions and agencies that provide support for individuals and funding that enable the collaborative effort of bringing all components together in the carbon budget effort. Swiss National Science Foundation, GOSAT Research Computation Facility, National Aeronautic and Space Administration (NASA), National Environmental Science Program Earth Sciences and Climate Change Hub, LSCE computing support and data analyses, French national facility for high performance computing, European Commission Seventh Framework, Horizon2020, and ERC programme, ESA Climate Change Initiative Greenhouse Gases Phase 2 project, US Department of Energy, Ministry of the Environment, All FAO member countries, Swedish Research Council, Ministry of the Environment (Japan), Research Council of Norway, National Science Engineering Research Council of Canada, Chinas QianRen program, Commonwealth Scientific and Industrial Research Organization (CSIRO Australia), Australian Government Bureau of Meteorology, Australian Institute of Marine Science, Australian Antarctic Division, NOAA USA, Meteorological Service of Canada, Department of Energy and Climate Change (DECC, UK), Met Office Hadley Centre Climate Programme We also thank the sponsors of the GCP and GCP support/liaison offices

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) This deed highlights only some of the key features and terms of the actual license. It is not a license and has no legal value. You should carefully review all of the terms and conditions of the actual license before using the licensed material. Creative Commons is not a law firm and does not provide legal services. Distributing, displaying, or linking to this deed or the license that it summarizes does not create a lawyer-client or any other relationship. This is a human-readable summary of (and not a substitute for) the license. You are free to: Share copy and redistribute the material in any medium or format Adapt remix, transform, and build upon the material The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. What does "Attribute this work" mean? The page you came from contained embedded licensing metadata, including how the creator wishes to be attributed for re-use. You can use the HTML here to cite the work. Doing so will also include metadata on your page so that others can find the original work as well. No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation. No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material. References used in this presentation Global Methane Budget 2000-2012, data sources and data files at http://www.globalcarbonproject.org/methanebudget/ Saunois, M., Bousquet, P., Poulter, B., Peregon, A., Ciais, P., Canadell, J. G., Dlugokencky, E. J., Etiope, G., Bastviken, D., Houweling, S., JanssensMaenhout, G., Tubiello, F. N., Castaldi, S., Jackson, R. B., Alexe, M., Arora, V. K., Beerling, D. J., Bergamaschi, P., Blake, D. R., Brailsford, G.,

Brovkin, V., Bruhwiler, L., Crevoisier, C., Crill, P., Kovey, K., Curry, C., Frankenberg, C., Gedney, N., Hglund-Isaksson, L., Ishizawa, M., Ito, A., Joos, F., Kim, H.-S., Kleinen, T., Krummel, P., Lamarque, J.-F., Langenfelds, R., Locatelli, R., Machida, T., Maksyutov, S., McDonald, K. C., Marshall, J., Melton, J. R., Morino, I., Naik, V., O'Doherty, S., Parmentier, F.-J. W., Patra, P. K., Peng, C., Peng, S., Peters, G. P., Pison, I., Prigent, C., Prinn, R., Ramonet, M., Riley, W. J., Saito, M., Sanyini, M., Schroeder, R., Simpson, I. J., Spahni, R., Steele, P., Takizawa, A., Thornton, B. F., Tian, H., Tohjima, Y., Viovy, N., Voulgarakis, A., van Weele, M., van der Werf, G., Weiss, R., Wiedinmyer, C., Wilton, D. J., Wiltshire, A., Worthy, D., Wunch, D. B., Xu, X., Yoshida, Y., Zhang, B., Zhang, Z., and Zhu, Q. (2016): The Global Methane Budget 2000-2012, Earth System Science Data, 8, 1-54, http://dx.doi.org/10.5194/essd-8-1-2016 Saunois M, R B Jackson, P Bousquet, B Poulter, and J G Canadell (2016) The growing role of methane in anthropogenic climate change. Environmental Research Letters, vol. 11, 120207, DOI: 10.1088/1748-9326/11/12/120207. http://iopscience.iop.org/article/10.1088/1748-9326/11/12/120207 Dalsoren et al. (2016): Atmospheric methane evolution the last 40 years, Atmos. Chem. Phys., 16,3099-3126, http://dx.doi.org/10.5094 acp16-3099-2016 Etiope G. (2015): Natural gas seepage. The earths Hydrocarbon Degassing, Springer International Publishing, 199 pp., 2015 IPCC (2013) WGI. 5th Assessment Report. Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Kirschke, S. et al. (2013): Three decades of global methane sources and sinks. Nature Climate Change, 6, 813-823, http://dx.doi.org/10.1038ngeo1955 Meinshausen, M. et al. (2011): The RCP Greenhouse Gas Concentrations and their Extension from 1765 to 2300." Climatic Change (Special Issue), http://dx.doi.org/10.1007/s10584-011-0156-z Poulter B et al 2016 Global wetland contribution to increasing atmospheric methane concentrations (20002012) , submitted Voulgarakis A. et al. (2013): Analysis of present day and future OH and methane lifetime in the ACCMIP simulations, Atm. Chem. Phys., 13, 2563-2587, http://dx.doi.org/10.5194/acp-13-2563-2013

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