Three decades of global methane sources and sinks
Centre national de la recherche scientifique1, Commonwealth Scientific and Industrial Research Organisation2, National Oceanic and Atmospheric Administration3, United States Department of Energy4, University of California, Irvine5, Seconda Università degli Studi di Napoli6, Central Maine Community College7, Max Planck Society8, Swiss Federal Institute for Forest, Snow and Landscape Research9, Utrecht University10, Carma11, National Center for Atmospheric Research12, University of East Anglia13, Massachusetts Institute of Technology14, VU University Amsterdam15, Goddard Space Flight Center16, University of Bern17, Nagoya University18, Imperial College London19, Royal Netherlands Meteorological Institute20, University of California, San Diego21, National Institute of Water and Atmospheric Research22
TL;DR: In this paper, the authors construct decadal budgets for methane sources and sinks between 1980 and 2010, using a combination of atmospheric measurements and results from chemical transport models, ecosystem models, climate chemistry models and inventories of anthropogenic emissions.
Abstract: Methane is an important greenhouse gas, responsible for about 20% of the warming induced by long-lived greenhouse gases since pre-industrial times. By reacting with hydroxyl radicals, methane reduces the oxidizing capacity of the atmosphere and generates ozone in the troposphere. Although most sources and sinks of methane have been identified, their relative contributions to atmospheric methane levels are highly uncertain. As such, the factors responsible for the observed stabilization of atmospheric methane levels in the early 2000s, and the renewed rise after 2006, remain unclear. Here, we construct decadal budgets for methane sources and sinks between 1980 and 2010, using a combination of atmospheric measurements and results from chemical transport models, ecosystem models, climate chemistry models and inventories of anthropogenic emissions. The resultant budgets suggest that data-driven approaches and ecosystem models overestimate total natural emissions. We build three contrasting emission scenarios-which differ in fossil fuel and microbial emissions-to explain the decadal variability in atmospheric methane levels detected, here and in previous studies, since 1985. Although uncertainties in emission trends do not allow definitive conclusions to be drawn, we show that the observed stabilization of methane levels between 1999 and 2006 can potentially be explained by decreasing-to-stable fossil fuel emissions, combined with stable-to-increasing microbial emissions. We show that a rise in natural wetland emissions and fossil fuel emissions probably accounts for the renewed increase in global methane levels after 2006, although the relative contribution of these two sources remains uncertain. © 2013 Macmillan Publishers Limited.
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Journal Article•
TL;DR: In this article, the authors present a document, redatto, voted and pubblicato by the Ipcc -Comitato intergovernativo sui cambiamenti climatici - illustra la sintesi delle ricerche svolte su questo tema rilevante.
Abstract: Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.
4,187 citations
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, Atlantic Oceanographic and Meteorological Laboratory8, Cooperative Institute for Marine and Atmospheric Studies9, 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, Hobart Corporation29, Cooperative Research Centre30, Japan Agency for Marine-Earth Science and Technology31, Wageningen University and Research Centre32, University of Groningen33, 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
TL;DR: In this article, the authors review various studies on resource potential of natural gas hydrate, the current research progress in laboratory settings, and several recent field trials, and discuss possible limitation in each production method and the challenges to be addressed for large scale production.
1,236 citations
Cites background from "Three decades of global methane sou..."
...Apart from methane as the major constituent, longer chain hydrocarbons such as ethane and propane also present in thermogenic natural gases (C1/C2+ < 100) [21,23]....
[...]
...Biogenic natural gases are formed from CH4-generating microbes (methanogens), which can be characterized by their high methane purity (C1/C2+ > 100) [20–22]....
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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, University of Bern23, Oeschger Centre for Climate Change Research24, 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
Université Paris-Saclay1, Commonwealth Scientific and Industrial Research Organisation2, Goddard Space Flight Center3, Stanford University4, Yale University5, National Oceanic and Atmospheric Administration6, Netherlands Institute for Space Research7, VU University Amsterdam8, Chiba University9, Japan Agency for Marine-Earth Science and Technology10, 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, Babeș-Bolyai University20, National Institute of Geophysics and Volcanology21, 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, Imperial College London45, Technical University of Crete46, 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
References
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European Centre for Medium-Range Weather Forecasts1, Lawrence Livermore National Laboratory2, Chinese Academy of Sciences3, Japan Meteorological Agency4, Met Office5, University of Reading6, Max Planck Society7, Royal Netherlands Meteorological Institute8, National Center for Atmospheric Research9, National Oceanic and Atmospheric Administration10
TL;DR: ERA-40 is a re-analysis of meteorological observations from September 1957 to August 2002 produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) in collaboration with many institutions as mentioned in this paper.
Abstract: ERA-40 is a re-analysis of meteorological observations from September 1957 to August 2002 produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) in collaboration with many institutions. The observing system changed considerably over this re-analysis period, with assimilable data provided by a succession of satellite-borne instruments from the 1970s onwards, supplemented by increasing numbers of observations from aircraft, ocean-buoys and other surface platforms, but with a declining number of radiosonde ascents since the late 1980s. The observations used in ERA-40 were accumulated from many sources. The first part of this paper describes the data acquisition and the principal changes in data type and coverage over the period. It also describes the data assimilation system used for ERA-40. This benefited from many of the changes introduced into operational forecasting since the mid-1990s, when the systems used for the 15-year ECMWF re-analysis (ERA-15) and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis were implemented. Several of the improvements are discussed. General aspects of the production of the analyses are also summarized.
A number of results indicative of the overall performance of the data assimilation system, and implicitly of the observing system, are presented and discussed. The comparison of background (short-range) forecasts and analyses with observations, the consistency of the global mass budget, the magnitude of differences between analysis and background fields and the accuracy of medium-range forecasts run from the ERA-40 analyses are illustrated. Several results demonstrate the marked improvement that was made to the observing system for the southern hemisphere in the 1970s, particularly towards the end of the decade. In contrast, the synoptic quality of the analysis for the northern hemisphere is sufficient to provide forecasts that remain skilful well into the medium range for all years. Two particular problems are also examined: excessive precipitation over tropical oceans and a too strong Brewer-Dobson circulation, both of which are pronounced in later years. Several other aspects of the quality of the re-analyses revealed by monitoring and validation studies are summarized. Expectations that the ‘second-generation’ ERA-40 re-analysis would provide products that are better than those from the firstgeneration ERA-15 and NCEP/NCAR re-analyses are found to have been met in most cases. © Royal Meteorological Society, 2005. The contributions of N. A. Rayner and R. W. Saunders are Crown copyright.
7,110 citations
Journal Article•
TL;DR: In this article, the authors present a document, redatto, voted and pubblicato by the Ipcc -Comitato intergovernativo sui cambiamenti climatici - illustra la sintesi delle ricerche svolte su questo tema rilevante.
Abstract: Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.
4,187 citations
"Three decades of global methane sou..." refers background in this paper
...Experiment - AGAGE 14 , Commonwealth Scientific and Industrial Research Organisation 62 CSIRO 5 , University of California Irvine - UCI 15 ) show consistent changes in the global 63 annual CH4 growth rate since 1980 (Fig. 1 and ST1 in SI text). The agreement between these 64 networks has improved with increasing coverage. The standard deviation for the global annual 65 growth rate decreased from ±3.3 ppb.yr -1 (1980s) to ±1.3 ppb.yr -1 (2000s). These data reveal a 66 sustained increase of atmospheric CH4 in the 1980s (by an average of 12±6 ppb....
[...]
...Experiment - AGAGE 14 , Commonwealth Scientific and Industrial Research Organisation 62 CSIRO 5 , University of California Irvine - UCI 15 ) show consistent changes in the global 63 annual CH4 growth rate since 1980 (Fig. 1 and ST1 in SI text). The agreement between these 64 networks has improved with increasing coverage. The standard deviation for the global annual 65 growth rate decreased from ±3.3 ppb.yr -1 (1980s) to ±1....
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...…studies concluded that a recent surge in natural wetland emissions is one main cause of increasing CH4 levels, in response to abnormally high temperatures in northern high latitudes in 2007, and increased rainfall over tropical wetlands during 2008–2009 and 2010–201113,53,60, two La Niña periods4....
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Book•
17 Jul 2000
TL;DR: This book treats the inverse problem of remote sounding comprehensively, and discusses a wide range of retrieval methods for extracting atmospheric parameters of interest from the quantities such as thermal emission that can be measured remotely.
Abstract: Remote sounding of the atmosphere has proved to be a fruitful method of obtaining global information about the atmospheres of the earth and planets. This book treats the inverse problem of remote sounding comprehensively, and discusses a wide range of retrieval methods for extracting atmospheric parameters of interest from the quantities such as thermal emission that can be measured remotely. Inverse theory is treated in depth from an estimation-theory point of view, but practical questions are also emphasized, for example designing observing systems to obtain the maximum quantity of information, efficient numerical implementation of algorithms for processing of large quantities of data, error analysis and approaches to the validation of the resulting retrievals, The book is targeted at both graduate students and working scientists.
4,052 citations
Additional excerpts
...Other sources 36 [35–36]19,21,76 130 [61–200] 32 [23–37]21,74,77 130 [61–200] 43 [37–65]46,53,73,75,77 130 [61–200]...
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...Fossil fuels 94 [75–108]19,21,76 89 [89–89]56 95 [84–107]21,74,77 84 [66–96]55,56,81 96 [77–123]46,53,73,75,77 96 [85–105]55,56,81...
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TL;DR: In this paper, the authors used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997-2009 period on a 0.5° spatial resolution with a monthly time step.
Abstract: . New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used maps of burned area derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and estimates of plant productivity derived from Advanced Very High Resolution Radiometer (AVHRR) observations during the same period. Average global fire carbon emissions according to this version 3 of the Global Fire Emissions Database (GFED3) were 2.0 Pg C year−1 with significant interannual variability during 1997–2001 (2.8 Pg C year−1 in 1998 and 1.6 Pg C year−1 in 2001). Globally, emissions during 2002–2007 were relatively constant (around 2.1 Pg C year−1) before declining in 2008 (1.7 Pg C year−1) and 2009 (1.5 Pg C year−1) partly due to lower deforestation fire emissions in South America and tropical Asia. On a regional basis, emissions were highly variable during 2002–2007 (e.g., boreal Asia, South America, and Indonesia), but these regional differences canceled out at a global level. During the MODIS era (2001–2009), most carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. Total carbon emissions were on average 13% lower than in our previous (GFED2) work. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C year−1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series.
2,494 citations
Journal Article•
TL;DR: Denman et al. as discussed by the authors presented the Couplings between changes in the climate system and biogeochemistry Coordinating Lead Authors: Kenneth L. Denman (Canada), Guy Brasseur (USA, Germany), Amnat Chidthaisong (Thailand), Philippe Ciais (France), Peter M. Cox (UK), Robert E. Austin (USA), D.B. Wofsy (USA) and Xiaoye Zhang (China).
Abstract: Couplings Between Changes in the Climate System and Biogeochemistry Coordinating Lead Authors: Kenneth L. Denman (Canada), Guy Brasseur (USA, Germany) Lead Authors: Amnat Chidthaisong (Thailand), Philippe Ciais (France), Peter M. Cox (UK), Robert E. Dickinson (USA), Didier Hauglustaine (France), Christoph Heinze (Norway, Germany), Elisabeth Holland (USA), Daniel Jacob (USA, France), Ulrike Lohmann (Switzerland), Srikanthan Ramachandran (India), Pedro Leite da Silva Dias (Brazil), Steven C. Wofsy (USA), Xiaoye Zhang (China) Contributing Authors: D. Archer (USA), V. Arora (Canada), J. Austin (USA), D. Baker (USA), J.A. Berry (USA), R. Betts (UK), G. Bonan (USA), P. Bousquet (France), J. Canadell (Australia), J. Christian (Canada), D.A. Clark (USA), M. Dameris (Germany), F. Dentener (EU), D. Easterling (USA), V. Eyring (Germany), J. Feichter (Germany), P. Friedlingstein (France, Belgium), I. Fung (USA), S. Fuzzi (Italy), S. Gong (Canada), N. Gruber (USA, Switzerland), A. Guenther (USA), K. Gurney (USA), A. Henderson-Sellers (Switzerland), J. House (UK), A. Jones (UK), C. Jones (UK), B. Karcher (Germany), M. Kawamiya (Japan), K. Lassey (New Zealand), C. Le Quere (UK, France, Canada), C. Leck (Sweden), J. Lee-Taylor (USA, UK), Y. Malhi (UK), K. Masarie (USA), G. McFiggans (UK), S. Menon (USA), J.B. Miller (USA), P. Peylin (France), A. Pitman (Australia), J. Quaas (Germany), M. Raupach (Australia), P. Rayner (France), G. Rehder (Germany), U. Riebesell (Germany), C. Rodenbeck (Germany), L. Rotstayn (Australia), N. Roulet (Canada), C. Sabine (USA), M.G. Schultz (Germany), M. Schulz (France, Germany), S.E. Schwartz (USA), W. Steffen (Australia), D. Stevenson (UK), Y. Tian (USA, China), K.E. Trenberth (USA), T. Van Noije (Netherlands), O. Wild (Japan, UK), T. Zhang (USA, China), L. Zhou (USA, China) Review Editors: Kansri Boonpragob (Thailand), Martin Heimann (Germany, Switzerland), Mario Molina (USA, Mexico) This chapter should be cited as: Denman, K.L., G. Brasseur, A. Chidthaisong, P. Ciais, P.M. Cox, R.E. Dickinson, D. Hauglustaine, C. Heinze, E. Holland, D. Jacob, U. Lohmann, S Ramachandran, P.L. da Silva Dias, S.C. Wofsy and X. Zhang, 2007: Couplings Between Changes in the Climate System and Biogeochemistry. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
2,208 citations