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7 results on '"Doug Worthy"'

1. Enhanced North American carbon uptake associated with El Niño

Author

Kathryn McKain, Sébastien C. Biraud, Colm Sweeney, Doug Worthy, Lei Hu, S. E. Michel, Bruce H. Vaughn, Anna M. Michalak, M. E. Mountain, Edward J. Dlugokencky, Michael Trudeau, Y. P. Shiga, Stephen A. Montzka, Thomas Nehrkorn, Kirk Thoning, Arlyn E. Andrews, Vineet Yadav, James W. C. White, Marc Fischer, Ivar R. van der Velde, Sourish Basu, J. Kofler, Pieter P. Tans, John B. Miller, Economics, and Earth and Climate

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Atmospheric sciences, 01 natural sciences, chemistry.chemical_compound, Surface air temperature, Spring (hydrology), Research Articles, 0105 earth and related environmental sciences, Carbon flux, Climatology, geography, Multidisciplinary, geography.geographical_feature_category, 010604 marine biology & hydrobiology, Carbon uptake, SciAdv r-articles, La Niña, chemistry, El Niño, Net ecosystem exchange, Carbon dioxide, Environmental science, SDG 6 - Clean Water and Sanitation, Research Article
Abstract

North American ecosystems absorb more CO2 from the atmosphere during El Niño than during La Niña periods., Long-term atmospheric CO2 mole fraction and δ13CO2 observations over North America document persistent responses to the El Niño–Southern Oscillation. We estimate these responses corresponded to 0.61 (0.45 to 0.79) PgC year−1 more North American carbon uptake during El Niño than during La Niña between 2007 and 2015, partially offsetting increases of net tropical biosphere-to-atmosphere carbon flux around El Niño. Anomalies in derived North American net ecosystem exchange (NEE) display strong but opposite correlations with surface air temperature between seasons, while their correlation with water availability was more constant throughout the year, such that water availability is the dominant control on annual NEE variability over North America. These results suggest that increased water availability and favorable temperature conditions (warmer spring and cooler summer) caused enhanced carbon uptake over North America near and during El Niño.

Published
2019
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2. The Facility Level and Area Methane Emissions inventory for the Greater Toronto Area (FLAME-GTA)

Author

Elton Chan, Felix Vogel, Debra Wunch, Doug Worthy, Junhua Zhang, Sajjan Heerah, and Nasrin Mostafavi Pak

Subjects
Methane emissions, Atmospheric Science, 010504 meteorology & atmospheric sciences, Climate change, 010501 environmental sciences, Atmospheric sciences, 7. Clean energy, 01 natural sciences, Metropolitan area, Atmospheric research, Methane, symbols.namesake, chemistry.chemical_compound, chemistry, 13. Climate action, symbols, Environmental science, Emission inventory, Air quality index, Lagrangian, 0105 earth and related environmental sciences, General Environmental Science
Abstract

We present the Facility Level and Area Methane (CH4) Emissions inventory for the Greater Toronto Area (FLAME-GTA). We estimate that total emissions of CH4 in the GTA, the most populous metropolitan area in Canada, are about 86 ± 38 Gg/yr. The FLAME-GTA estimate is within uncertainty of, but lower in magnitude than the existing gridded inventories provided by the Emissions Database for Global Atmospheric Research (EDGAR v 5.0), and by Environment and Climate Change Canada's Air Quality Research Division (ECCC - AQRD) that estimate emissions of 96 ± 48 Gg/yr and 143 ± 71 Gg/yr in the GTA region, respectively. Using a Lagrangian transport model, we predict atmospheric mixing ratios based on different emission inventories and compare the predictions with in situ measurements available from an observatory within the GTA for January–March in both 2015 and 2016. Due to the strong influence of local sources on our observations only a subregion of our GTA inventory is evaluated. These results identify the need for a more extensive measurement network and an improved atmospheric transport modeling effort for further evaluation of the emission inventories.

Published
2021
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3. Evaluation of wetland methane emissions across North America using atmospheric data and inverse modeling

Author

Edward J. Dlugokencky, Anna M. Michalak, Joe R. Melton, J. S. Benmergui, Doug Worthy, Colm Sweeney, Scot M. Miller, Greet Janssens-Maenhout, Roisin Commane, and Arlyn E. Andrews

Subjects
010504 meteorology & atmospheric sciences, lcsh:Life, Magnitude (mathematics), Wetland, Land cover, 010502 geochemistry & geophysics, Atmospheric sciences, Spatial distribution, 01 natural sciences, Methane, Synthetic data, chemistry.chemical_compound, lcsh:QH540-549.5, medicine, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences, Earth-Surface Processes, Hydrology, geography, geography.geographical_feature_category, lcsh:QE1-996.5, Seasonality, medicine.disease, lcsh:Geology, lcsh:QH501-531, chemistry, Environmental science, lcsh:Ecology, Wetland methane emissions
Abstract

Existing estimates of methane (CH4) fluxes from North American wetlands vary widely in both magnitude and distribution. In light of these differences, this study uses atmospheric CH4 observations from the US and Canada to analyze seven different bottom-up, wetland CH4 estimates reported in a recent model comparison project. We first use synthetic data to explore whether wetland CH4 fluxes are detectable at atmospheric observation sites. We find that the observation network can detect aggregate wetland fluxes from both eastern and western Canada but generally not from the US. Based upon these results, we then use real data and inverse modeling results to analyze the magnitude, seasonality, and spatial distribution of each model estimate. The magnitude of Canadian fluxes in many models is larger than indicated by atmospheric observations. Many models predict a seasonality that is narrower than implied by inverse modeling results, possibly indicating an oversensitivity to air or soil temperatures. The LPJ-Bern and SDGVM models have a geographic distribution that is most consistent with atmospheric observations, depending upon the region and season. These models utilize land cover maps or dynamic modeling to estimate wetland coverage while most other models rely primarily on remote sensing inundation data.

Published
2016

4. Analysis of atmospheric CH4 in Canadian Arctic and estimation of the regional CH4 fluxes

Author

Felix Vogel, Elton Chan, Doug Worthy, Misa Ishizawa, Douglas Chan, and Shamil Maksyutov

Subjects
Estimation, Atmospheric Science, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Range (biology), Wetland, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Methane, The arctic, Current (stream), chemistry.chemical_compound, Flux (metallurgy), Arctic, chemistry, Environmental science, 0105 earth and related environmental sciences
Abstract

The Canadian Arctic (> 60 ∘ N, 60–141 ∘ W) may undergo drastic changes if the Arctic warming trend continues. For methane ( CH4 ), Arctic reservoirs are large and widespread, and the climate feedbacks from such changes may be potentially substantial. Current bottom-up and top-down estimates of the regional CH4 flux range widely. This study analyzes the recent observations of atmospheric CH4 from five arctic monitoring sites and presents estimates of the regional CH4 fluxes for 2012–2015. The observational data reveal sizeable synoptic summertime enhancements in the atmospheric CH4 that are distinguishable from background variations, which indicate strong regional fluxes (primarily wetland and biomass burning CH4 emissions) around Behchoko and Inuvik in the western Canadian Arctic. Three regional Bayesian inversion modelling systems with two Lagrangian particle dispersion models and three meteorological datasets are applied to estimate fluxes for the Canadian Arctic and show relatively robust results in amplitude and temporal variations across different transport models, prior fluxes, and subregion masking. The estimated mean total CH4 flux for the entire Canadian Arctic is 1.8±0.6 Tg CH4 yr −1 . The flux estimate is partitioned into biomass burning of 0.3±0.1 Tg CH4 yr −1 and the remaining natural (wetland) flux of 1.5±0.5 Tg CH4 yr −1 . The summer natural CH4 flux estimates clearly show inter-annual variability that is positively correlated with surface temperature anomalies. The results indicate that years with warmer summer conditions result in more wetland CH4 emissions. More data and analysis are required to statistically characterize the dependence of regional CH4 fluxes on the climate in the Arctic. These Arctic measurement sites will aid in quantifying the inter-annual variations and long-term trends in CH4 emissions in the Canadian Arctic.

Published
2018
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5. Methane fluxes in the high northern latitudes for 2005–2013 estimated using a Bayesian atmospheric inversion

Author

Jost V. Lavric, Cathrine Lund Myhre, Toshinobu Machida, Motoki Sasakawa, Tuula Aalto, Rona Thompson, Doug Worthy, and Andreas Stohl

Subjects
Atmospheric Science, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Inversion (meteorology), Wetland, 010501 environmental sciences, 01 natural sciences, Methane, lcsh:QC1-999, Latitude, lcsh:Chemistry, chemistry.chemical_compound, Zeppelinobservatoriet, Flux (metallurgy), chemistry, lcsh:QD1-999, Temporal resolution, Climatology, Environmental science, Water content, Bay, lcsh:Physics, 0105 earth and related environmental sciences
Abstract

We present methane (CH4) flux estimates for 2005 to 2013 from a Bayesian inversion focusing on the high northern latitudes (north of 50° N). Our inversion is based on atmospheric transport modelled by the Lagrangian particle dispersion model FLEXPART and CH4 observations from 17 in situ and five discrete flask-sampling sites distributed over northern North America and Eurasia. CH4 fluxes are determined at monthly temporal resolution and on a variable grid with maximum resolution of 1° × 1°. Our inversion finds a CH4 source from the high northern latitudes of 82 to 84 Tg yr−1, constituting ∼ 15 % of the global total, compared to 64 to 68 Tg yr−1 (∼ 12 %) in the prior estimates. For northern North America, we estimate a mean source of 16.6 to 17.9 Tg yr−1, which is dominated by fluxes in the Hudson Bay Lowlands (HBL) and western Canada, specifically the province of Alberta. Our estimate for the HBL, of 2.7 to 3.4 Tg yr−1, is close to the prior estimate (which includes wetland fluxes from the land surface model, LPX-Bern) and to other independent inversion estimates. However, our estimate for Alberta, of 5.0 to 5.8 Tg yr−1, is significantly higher than the prior (which also includes anthropogenic sources from the EDGAR-4.2FT2010 inventory). Since the fluxes from this region persist throughout the winter, this may signify that the anthropogenic emissions are underestimated. For northern Eurasia, we find a mean source of 52.2 to 55.5 Tg yr−1, with a strong contribution from fluxes in the Western Siberian Lowlands (WSL) for which we estimate a source of 19.3 to 19.9 Tg yr−1. Over the 9-year inversion period, we find significant year-to-year variations in the fluxes, which in North America, and specifically in the HBL, appear to be driven at least in part by soil temperature, while in the WSL, the variability is more dependent on soil moisture. Moreover, we find significant positive trends in the CH4 fluxes in North America of 0.38 to 0.57 Tg yr−2, and northern Eurasia of 0.76 to 1.09 Tg yr−2. In North America, this could be due to an increase in soil temperature, while in North Eurasia, specifically Russia, the trend is likely due, at least in part, to an increase in anthropogenic sources.

Published
2017

6. The global methane budget 2000-2012

Author

Akihiko Ito, Philippe Ciais, Peter Bergamaschi, Greet Janssens-Maenhout, David J. Beerling, Cyril Crevoisier, Philippe Bousquet, Julia Marshall, Simona Castaldi, Isabelle Pison, Heon Sook Kim, Yasunori Tohjima, Jean-Francois Lamarque, Atsushi Takizawa, Charles L. Curry, Debra Wunch, Kyle C. McDonald, Michel Ramonet, David Bastviken, Simon O'Doherty, Josep G. Canadell, Robin Locatelli, Francesco N. Tubiello, Prabir K. Patra, P. Steele, Brett F. Thornton, Catherine Prigent, Sander Houweling, Toshinobu Machida, David J. Wilton, Joe R. Melton, Ronald G. Prinn, William J. Riley, Edward J. Dlugokencky, Monia Santini, Giuseppe Etiope, Doug Worthy, Guido R. van der Werf, Christian Frankenberg, Shushi Peng, Vivek K. Arora, Patrick M. Crill, Ray F. Weiss, Nicolas Viovy, Michiel van Weele, Anna Peregon, Shamil Maksyutov, Vaishali Naik, Zhen Zhang, Thomas Kleinen, Lori Bruhwiler, Yukio Yoshida, Lena Höglund-Isaksson, Kristofer R. Covey, Fortunat Joos, Misa Ishizawa, Bowen Zhang, Christine Wiedinmyer, Ronny Schroeder, Nicola Gedney, Hanqin Tian, Changhui Peng, Apostolos Voulgarakis, Mihai Alexe, Victor Brovkin, Ray L. Langenfelds, Isamu Morino, Glen P. Peters, Xiyan Xu, Andy Wiltshire, Isobel J. Simpson, Ben Poulter, Marielle Saunois, Qiuan Zhu, Donald R. Blake, Paul B. Krummel, Frans-Jan W. Parmentier, Makoto Saito, Gordon Brailsford, Robert B. Jackson, Renato Spahni, Earth and Climate, Hydrology and Geo-environmental sciences, Faculty of Earth and Life Sciences, Saunois, Marielle, Bousquet, Philippe, Poulter, Ben, Peregon, Anna, Ciais, Philippe, Canadell Josep, G, Dlugokencky Edward, J., Etiope, Giuseppe, Bastviken, David, Houweling, Sander, Janssens Maenhout, Greet, Tubiello Francesco, N., Castaldi, Simona, Jackson Robert, B., Alexe, Mihai, Arora Vivek, K., Beerling David, J., Bergamaschi, Peter, Blake Donald, R., Brailsford, Gordon, Brovkin, Victor, Bruhwiler, Lori, Crevoisier, Cyril, Crill, Patrick, Covey, Kristofer, Curry, Charle, Frankenberg, Christian, Gedney, Nicola, Höglund Isaksson, Lena, Ishizawa, Misa, Ito, Akihiko, Joos, Fortunat, Kim Heon, Sook, Kleinen, Thoma, Krummel, Paul, Lamarque Jean, Françoi, Langenfelds, Ray, Locatelli, Robin, Machida, Toshinobu, Maksyutov, Shamil, McDonald Kyle, C., Marshall, Julia, Melton Joe, R., Morino, Isamu, Naik Vaishali, Oapo, Doherty, Simon, Parmentier Frans Jan, W., Patra Prabir, K., Peng, Changhui, Peng, Shushi, Peters Glen, P., Pison, Isabelle, Prigent, Catherine, Prinn, Ronald, Ramonet, Michel, Riley William, J., Saito, Makoto, Santini, Monia, Schroeder, Ronny, Simpson Isobel, J., Spahni, Renato, Steele, Paul, Takizawa, Atsushi, Thornton Brett, F., Tian, Hanqin, Tohjima, Yasunori, Viovy, Nicola, Voulgarakis, Apostolo, van Weele, Michiel, van der Werf Guido, R., Weiss, Ray, Wiedinmyer, Christine, Wilton David, J., Wiltshire, Andy, Worthy, Doug, Wunch, Debra, Xu, Xiyan, Yoshida, Yukio, Zhang, Bowen, Zhang, Zhen, Zhu, Qiuan, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), NASA Goddard Space Flight Center (GSFC), ICOS-ATC (ICOS-ATC), Istituto Nazionale di Geofisica e Vulcanologia, The Department of Thematic Studies - Water and Environmental Studies, Linköping University (LIU), SRON Netherlands Institute for Space Research (SRON), European Commission - Joint Research Centre [Ispra] (JRC), LM, Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Department of Animal and Plant Sciences, University of Sheffield [Sheffield], JRC Institute for Environment and Sustainability (IES), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Tropospheric sounding, assimilation, and modeling group [JPL], Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH)-NASA-California Institute of Technology (CALTECH), National Institute for Environmental Studies (NIES), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern] (UNIBE)-Universität Bern [Bern] (UNIBE), Atmospheric Chemistry Division [Boulder], National Center for Atmospheric Research [Boulder] (NCAR), Oceans and Atmosphere, CSIRO, Strathom Energie, Centre Européen de Réalité Virtuelle (CERV), École Nationale d'Ingénieurs de Brest (ENIB), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Université du Québec à Trois-Rivières (UQTR), ICOS-RAMCES (ICOS-RAMCES), Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique (LERMA), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université de Cergy Pontoise (UCP), Université Paris-Seine-Université Paris-Seine-Centre National de la Recherche Scientifique (CNRS), Shandong Agricultural University (SDAU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Department of Physics [Imperial College London], Imperial College London, Royal Netherlands Meteorological Institute (KNMI), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Scripps Institution of Oceanography (SIO - UC San Diego), University of California [San Diego] (UC San Diego), University of California (UC)-University of California (UC), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Climate Research Division [Toronto], California Institute of Technology (CALTECH), Laboratoire de Physique et d'Etude des Matériaux (UMR 8213) (LPEM), Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), USC Viterbi School of Engineering, University of Southern California (USC), Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences, Prinn, Ronald G, Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Universität Bern [Bern]-Universität Bern [Bern], Scripps Institution of Oceanography (SIO), and University of California-University of California

Subjects
010504 meteorology & atmospheric sciences, Naturgeografi, TRACE GASES, 010501 environmental sciences, Atmospheric sciences, 7. Clean energy, 01 natural sciences, Physical Geography and Environmental Geoscience, Methane, chemistry.chemical_compound, Natural gas, 11. Sustainability, SDG 13 - Climate Action, Meteorology & Atmospheric Sciences, Geosciences, Multidisciplinary, Greenhouse effect, lcsh:Environmental sciences, ComputingMilieux_MISCELLANEOUS, lcsh:GE1-350, [PHYS]Physics [physics], GREENHOUSE-GAS EMISSIONS, methane, lcsh:QE1-996.5, Geology, PAST 2 DECADES, Carbon project, Atmospheric chemistry, Physical Sciences, hydroxyl, Earth and Related Environmental Sciences, Wetland methane emissions, BIOMASS BURNING EMISSIONS, NATURAL-GAS, PROCESS-BASED MODEL, TROPOSPHERIC METHANE, 530 Physics, methane sources, Climate change, Atmospheric Sciences, ATMOSPHERIC HYDROXYL RADICALS, SDG 14 - Life Below Water, ISOTOPIC COMPOSITION, 550 Earth sciences & geology, 0105 earth and related environmental sciences, global model, Science & Technology, business.industry, Environmental engineering, Geovetenskap och miljövetenskap, 15. Life on land, methane budget, lcsh:Geology, Climate Action, Geochemistry, chemistry, Physical Geography, 13. Climate action, Greenhouse gas, General Earth and Planetary Sciences, Environmental science, business, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], INTERCOMPARISON PROJECT ACCMIP
Abstract

The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (similar to biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003-2012 decade, global methane emissions are estimated by top-down inversions at 558 TgCH(4) yr(-1), range 540-568. About 60% of global emissions are anthropogenic (range 50-65 %). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon-intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bottom-up approaches suggest larger global emissions (736 TgCH(4) yr(-1), range 596-884) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the top-down budget, it is likely that some of the individual emissions reported by the bottom-up approaches are overestimated, leading to too large global emissions. Latitudinal data from top-down emissions indicate a predominance of tropical emissions (similar to 64% of the global budget, amp;lt;30 degrees N) as compared to mid (similar to 32 %, 30-60 degrees N) and high northern latitudes (similar to 4 %, 60-90 degrees N). Top-down inversions consistently infer lower emissions in China (similar to 58 TgCH(4) yr(-1), range 51-72, -14 %) and higher emissions in Africa (86 TgCH(4) yr(-1), range 73-108, + 19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models. The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30-40% on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions. The data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (http://doi.org/10.3334/CDIAC/GLOBAL_METHANE_BUDGET_2016_V1.1) and the Global Carbon Project. Funding Agencies|Swiss National Science Foundation; NASA [NNX14AF93G, NNX14AO73G]; National Environmental Science Program - Earth Systems and Climate Change Hub; European Commission [283576, 633080]; ESA Climate Change Initiative Greenhouse Gases Phase 2 project; US Department of Energy, BER [DE-AC02-05CH11231]; FAO member countries; Environment Research and Technology Development Fund of the Ministry of the Environment, Japan [2-1502]; ERC [322998]; NERC [NE/J00748X/1]; Swedish Research Council VR; Research Council of Norway [244074]; NSF [1243232, 1243220]; National Science and Engineering Research Council of Canada (NSERC); Chinas QianRen Program; CSIRO Australia; Australian Bureau of Meteorology; Australian Institute of Marine Science; Australian Antarctic Division; NOAA USA; Meteorological Service of Canada; National Aeronautic and Space Administration (NASA) [NAG5-12669, NNX07AE89G, NNX11AF17G, NNX07AE87G, NNX07AF09G, NNX11AF15G, NNX11AF16G]; Department of Energy and Climate Change (DECC, UK) [GA01081]; Commonwealth Scientific and Industrial Research Organization (CSIRO Australia); Bureau of Meteorology (Australia); Joint DECC/Defra Met Office Hadley Centre Climate Programme [GA01101]

Published
2016
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7. Regional trends and drivers of the global methane budget

Author

Naveen Chandra, Akihiko Ito, Philippe Ciais, Peter A. Raymond, Jurek Müller, Ann R. Stavert, Joe R. Melton, Marielle Saunois, Phillipe Bousquet, Adrian Gustafson, Yosuke Niwa, Robert B. Jackson, Shushi Peng, Qianlai Zhuang, Hanqin Tian, Aki Tsuruta, George H. Allen, Benjamin Poulter, Joe McNorton, Bo Zheng, Yi Yin, Prabir K. Patra, Thomas Kleinen, Pierre Regnier, Peter Bergamaschi, Ronny Lauerwald, Shamil Maksyutov, Misa Ishizawa, Arjo Segers, William J. Riley, Josep G. Canadell, Zhen Zhang, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université libre de Bruxelles (ULB), This paper is the result of a collaborative international effort under the umbrella of the Global Carbon Project, a Global Research Project of Future Earth and a research partner of the World Climate Research Programme. We acknowledge primary support for the methane budget from the Gordon and Betty Moore Foundation through Grant GBMF5439 'Advancing Understanding of the Global Methane Cycle' to Stanford University (P.I. Rob Jackson, co- P.I.s Philippe Bousquet, Marielle Saunois, Josep Canadell, Gustaf Hugelius, and Ben Poulter). Josep Canadell acknowledges the support of the Australian National Environmental Science Program – Earth Systems and Climate Change. Prabir K Patra and Neveen Chandra acknowledge support from Environment Research and Technology Development Funds of the Environmental Restoration and Conservation Agency of Japan (JPMEERF20182002, JPMEERF20172001). Jurek Müller thanks for support by the Swiss National Science Foundation (#200020_172476). Peter Bergamaschi acknowledges the support of ECMWF providing computing resources under the special project 'Improve European and global CH4 and N2O flux inversions (2018-2020)'. Pierre Regnier acknowledges the support from the VERIFY project under European Union's Horizon 2020 research and innovation program grant agree-ment no. 776810. The TM5-CAMS inversions are available from https://atmos phere.copernicus.eu, Arjo Segers acknowledges the support from the Copernicus Atmosphere Monitoring Service, implemented by the European Centre for Medium-Range Weather Forecasts on be-half of the European Commission (grant no. CAMS73). William Riley acknowledges support by the US Department of Energy, Office of Science, Biological and Environmental Research, Regional and Global Climate Modeling Program through the RUBISCO Scientific Focus Area under contract DE-AC02- 05CH11231 to Lawrence Berkeley National Laboratory. The authors gratefully acknowledge those re-sponsible for the global network of atmospheric observations used in this study including Donald R Blake and Isobel Simpson, University of California Irvine, USA, Gordon Brailsford, NIWA, Cyril Crevosier, LMD, France, New Zealand, Paul Krummel and Ray Langenfelds, CSIRO, Australia, Toshinobu Machida, Yasunori Tohjima and Yukio Yoshida, NIES, Japan, Ronald Prinn, MIT, USA, Simon O’Doherty, University of Bristol, UK, Michel Ramonet, LSCE-IPSL, France, Atsushi Takizawa, JMA, Japan, Ray Weiss, Scripps Institute of Oceanography, USA and Doug Worthy, Environment Canada, Canada. We would also like to thank Lena Höglund-Isaksson, IIASA, Austria, Greet Janssens- Maenhout EC-JRC, Italy and Steven Smith, PNNL-JGCR, USA for their assistance with the anthropogenic inventory data. The authors also acknowledge the significant contribution of Goulven G. Laruelle, Department Geoscience, Environment & Society, Université Libre de Bruxelles, Brussels, Belgium who, with P. Regnier, developed the re-gionally distributed estuarine flux data set., and European Project: 776810,H2020,H2020-SC5-2017-OneStageB,VERIFY(2018)

Subjects
China, Municipal solid waste, Livestock, 010504 meteorology & atmospheric sciences, methane emissions, Oceans and Seas, 010501 environmental sciences, 7. Clean energy, 01 natural sciences, Methane, 12. Responsible consumption, bottom-up, Atmosphere, chemistry.chemical_compound, Enteric fermentation, Environmental protection, source sectors, Environmental Chemistry, Animals, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Global and Planetary Change, regional, Ecology, business.industry, Coal mining, Biological Sciences, Climate Action, natural emissions, Carbon project, chemistry, 13. Climate action, Greenhouse gas, top-down, Environmental science, anthropogenic emissions, business, Environmental Sciences
Abstract

The ongoing development of the Global Carbon Project (GCP) global methane (CH4 ) budget shows a continuation of increasing CH4 emissions and CH4 accumulation in the atmosphere during 2000-2017. Here, we decompose the global budget into 19 regions (18land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top-down (TD) (atmospheric and transport model-based) and bottom-up (BU) (inventory- and process model-based) CH4 emission estimates demonstrates robust temporal trends with CH4 emissions increasing in 16 of the 19 regions. Five regions-China, Southeast Asia, USA, South Asia, and Brazil-account for >40% of the global total emissions (their anthropogenic and natural sources together totaling >270Tg CH4 yr-1 in 2008-2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (>75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by >20%. In contrast, Europe and Korea and Japan show a steady decline in CH4 emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH4 burden and the greatest opportunities for greenhouse gas abatement.

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