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Global Methane Budget 2000–2020
Earth System Science Data ( IF 11.2 ) Pub Date : 2024-06-06 , DOI: 10.5194/essd-2024-115 Marielle Saunois , Adrien Martinez , Benjamin Poulter , Zhen Zhang , Peter Raymond , Pierre Regnier , Joseph G. Canadell , Robert B. Jackson , Prabir K. Patra , Philippe Bousquet , Philippe Ciais , Edward J. Dlugokencky , Xin Lan , George H. Allen , David Bastviken , David J. Beerling , Dmitry A. Belikov , Donald R. Blake , Simona Castaldi , Monica Crippa , Bridget R. Deemer , Fraser Dennison , Giuseppe Etiope , Nicola Gedney , Lena Höglund-Isaksson , Meredith A. Holgerson , Peter O. Hopcroft , Gustaf Hugelius , Akihito Ito , Atul K. Jain , Rajesh Janardanan , Matthew S. Johnson , Thomas Kleinen , Paul Krummel , Ronny Lauerwald , Tingting Li , Xiangyu Liu , Kyle C. McDonald , Joe R. Melton , Jens Mühle , Jurek Müller , Fabiola Murguia-Flores , Yosuke Niwa , Sergio Noce , Shufen Pan , Robert J. Parker , Changhui Peng , Michel Ramonet , William J. Riley , Gerard Rocher-Ros , Judith A. Rosentreter , Motoki Sasakawa , Arjo Segers , Steven J. Smith , Emily H. Stanley , Joel Thanwerdas , Hanquin Tian , Aki Tsuruta , Francesco N. Tubiello , Thomas S. Weber , Guido van der Werf , Doug E. Worthy , Yi Xi , Yukio Yoshida , Wenxin Zhang , Bo Zheng , Qing Zhu , Qiuan Zhu , Qianlai Zhuang
Earth System Science Data ( IF 11.2 ) Pub Date : 2024-06-06 , DOI: 10.5194/essd-2024-115 Marielle Saunois , Adrien Martinez , Benjamin Poulter , Zhen Zhang , Peter Raymond , Pierre Regnier , Joseph G. Canadell , Robert B. Jackson , Prabir K. Patra , Philippe Bousquet , Philippe Ciais , Edward J. Dlugokencky , Xin Lan , George H. Allen , David Bastviken , David J. Beerling , Dmitry A. Belikov , Donald R. Blake , Simona Castaldi , Monica Crippa , Bridget R. Deemer , Fraser Dennison , Giuseppe Etiope , Nicola Gedney , Lena Höglund-Isaksson , Meredith A. Holgerson , Peter O. Hopcroft , Gustaf Hugelius , Akihito Ito , Atul K. Jain , Rajesh Janardanan , Matthew S. Johnson , Thomas Kleinen , Paul Krummel , Ronny Lauerwald , Tingting Li , Xiangyu Liu , Kyle C. McDonald , Joe R. Melton , Jens Mühle , Jurek Müller , Fabiola Murguia-Flores , Yosuke Niwa , Sergio Noce , Shufen Pan , Robert J. Parker , Changhui Peng , Michel Ramonet , William J. Riley , Gerard Rocher-Ros , Judith A. Rosentreter , Motoki Sasakawa , Arjo Segers , Steven J. Smith , Emily H. Stanley , Joel Thanwerdas , Hanquin Tian , Aki Tsuruta , Francesco N. Tubiello , Thomas S. Weber , Guido van der Werf , Doug E. Worthy , Yi Xi , Yukio Yoshida , Wenxin Zhang , Bo Zheng , Qing Zhu , Qiuan Zhu , Qianlai Zhuang
Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Emissions and atmospheric concentrations of CH4 continue to increase, maintaining CH4 as 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 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the factors explaining the well-observed atmospheric growth rate arise from diverse, geographically overlapping CH4 sources and from the uncertain magnitude and temporal change in the destruction of CH4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise and update the global CH4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH4 budget, integrating results of top-down CH4 emission estimates (based on in-situ and greenhouse gas observing satellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land-surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full datasets are available), for the previous decade of 2000–2009 and for the year 2020. The revision of the bottom-up budget in this edition benefits from important progress in estimating inland freshwater emissions, with better accounting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double accounting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double accounting that still exists (average of 23 Tg CH4 yr-1). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH4 yr-1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches. For the 2010–2019 decade, global CH4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH4 yr-1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH4 yr-1 or ~65 % are attributed to direct anthropogenic sources in the fossil, agriculture and waste and anthropogenic biomass burning (range 350–391 Tg CH4 yr-1 or 63–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH4 yr-1 (range 9–40). Since 2012, global direct anthropogenic CH4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH4 yr-1) larger global emissions (669 Tg CH4 yr-1, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH4 yr-1 in Saunois et al. (2016, 2020), respectively), and for the first time uncertainty in bottom-up and top-down budgets overlap. The latitudinal distribution from atmospheric inversion-based emissions indicates a predominance of tropical and southern hemisphere emissions (~65 % of the global budget, <30° N) compared to mid (30° N–60° N, ~30 % of emissions) and high-northern latitudes (60° N–90° N, ~4 % of global emissions). This latitudinal distribution is similar in the bottom-up budget though the bottom-up budget estimates slightly larger contributions for the mid and high-northern latitudes, and slightly smaller contributions from the tropics and southern hemisphere than the inversions. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters. We identify five major priorities for improving the CH4 budget: i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH4 based on a robust classification of different types of emitting ecosystems; ii) further development of process-based models for inland-water emissions; iii) intensification of CH4 observations at local (e.g., FLUXNET-CH4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; iv) improvements of transport models and the representation of photochemical sinks in top-down inversions, and v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture and landfills) to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GKQ9-2RHT (Martinez et al., 2024).
中文翻译:
2000-2020 年全球甲烷预算
摘要。了解和量化全球甲烷 (CH 4 ) 预算对于评估缓解气候变化的现实途径非常重要。 CH 4 的排放量和大气浓度持续增加,使 CH 4 成为继二氧化碳 (CO 2 相对于 CO 2 对温度变化的相对重要性与其大气寿命较短、辐射效应较强以及过去十年大气生长速度加快有关,其原因是其中仍有争议。减少解释观测到的大气增长率的因素的不确定性的两个主要挑战来自不同的、地理上重叠的 CH 4 来源以及 CH 4 预算,并促进有关甲烷循环的新研究。继 Saunois 等人之后。 (2016 年,2020 年),我们在此介绍专门针对十年 CH 4 预算的实时回顾论文的第三版,整合了自上而下的 CH 4 排放估算结果(基于现场和温室气体观测卫星(GOSAT)大气观测和大气反演模型结果的集合)和自下而上的估计(基于用于估计地表排放和大气化学的基于过程的模型、人为排放清单、和数据驱动的推断)。我们提出了最近 2010-2019 年日历十年(可获得完整数据集的最新时期)、2000-2009 年前十年以及 2020 年的预算。本版自下而上预算的修订受益于估算内陆淡水排放量方面的重大进展,更好地核算湖泊、池塘、水库、溪流和河流的排放量。该预算还减少了淡水和湿地排放的双重核算,并首次包括对仍然存在的潜在双重核算的估计(平均 23 Tg CH 4 年 -1 )。自下而上的方法表明,2010-2019 年十年间,湿地和内陆淡水的综合排放量平均为 248 [159-369] Tg CH 4 年 -1 。自然通量受到气候、富营养化和土地利用等人类活动的干扰。在本预算中,我们还首次估计了造成湿地和内陆淡水排放的人为因素。新推出的网格产品还使我们能够基于自下而上的方法得出几乎完整的纬度和区域预算。 2010-2019 十年间,通过大气反演(自上而下)估计全球 CH 4 排放量为 575 Tg CH 4 年 -1 (范围 553 –586,对应于模型集合的最小和最大估计)。其中,369 Tg CH 4 年 -1 或约 65% 归因于化石、农业和废物以及人为生物质燃烧中的直接人为来源(范围 350–391 Tg CH 4 年 -1 或 63–68 %)。 2000-2009 年期间,大气逆温的总排放量比 2010-2019 年略低,减少了 32 Tg CH 4 年 -1 (范围 9-40)。自 2012 年以来,全球直接人为 CH 4 排放趋势一直在跟踪政府间气候变化专门委员会提出的不采取或采取最低限度气候缓解政策的情景(共享社会经济路径 SSP5 和 SSP3)。自下而上的方法建议全球排放量增加 16%(94 Tg CH 4 年 -1 )(669 Tg CH 4 年 -1 ,范围 512-849)比 2010-2019 年期间自上而下的反演方法要好。与 Saunois 等人 (2016 ,2020),并且自下而上和自上而下预算的不确定性首次重叠。基于大气逆温的排放的纬度分布表明,与中半球(30° N–60° N,约 30% 的排放)相比,热带和南半球的排放占主导地位(约占全球预算的 65%,<30° N)和北高纬度地区(60° N–90° N,约占全球排放量的 4%)。 这种纬度分布与自下而上的预算类似,尽管自下而上的预算估计中北纬度和高北纬度的贡献略大,而热带地区和南半球的贡献略小于反演。尽管反演和自下而上之间的差异已经缩小,但全球 CH 4 预算中最重要的不确定性来源仍然可归因于自然排放,特别是来自湿地和内陆淡水的排放。我们确定了改善 CH 4 预算的五个主要优先事项: i) 基于可靠的分类,制作水饱和土壤和排放 CH 4 的淹没区域的全球高分辨率地图不同类型的排放生态系统; ii) 进一步开发基于过程的内陆水域排放模型; iii) 将 CH 4 局部观测(例如 FLUXNET-CH 4 测量、城市规模监测、具有指向能力的卫星图像)加强到区域规模(地面网络和全球远程来自卫星的传感测量)以约束自下而上的模型和大气反演; iv) 输运模型的改进和自上而下反演中光化学汇的表示,以及 v) 使用同位素和/或共发射物质(例如乙烷)以及自下而上清单中的信息集成 3D 变分反演系统通过遥感检测人为超级排放源(主要是石油和天然气部门,但也包括煤炭、农业和垃圾填埋场),以改善源分区。此处提供的数据可以从 https://doi.org/10.18160/GKQ9-2RHT 下载(Martinez 等人,2024)。
更新日期:2024-06-06
中文翻译:
2000-2020 年全球甲烷预算
摘要。了解和量化全球甲烷 (CH 4 ) 预算对于评估缓解气候变化的现实途径非常重要。 CH 4 的排放量和大气浓度持续增加,使 CH 4 成为继二氧化碳 (CO 2 相对于 CO 2 对温度变化的相对重要性与其大气寿命较短、辐射效应较强以及过去十年大气生长速度加快有关,其原因是其中仍有争议。减少解释观测到的大气增长率的因素的不确定性的两个主要挑战来自不同的、地理上重叠的 CH 4 来源以及 CH 4 预算,并促进有关甲烷循环的新研究。继 Saunois 等人之后。 (2016 年,2020 年),我们在此介绍专门针对十年 CH 4 预算的实时回顾论文的第三版,整合了自上而下的 CH 4 排放估算结果(基于现场和温室气体观测卫星(GOSAT)大气观测和大气反演模型结果的集合)和自下而上的估计(基于用于估计地表排放和大气化学的基于过程的模型、人为排放清单、和数据驱动的推断)。我们提出了最近 2010-2019 年日历十年(可获得完整数据集的最新时期)、2000-2009 年前十年以及 2020 年的预算。本版自下而上预算的修订受益于估算内陆淡水排放量方面的重大进展,更好地核算湖泊、池塘、水库、溪流和河流的排放量。该预算还减少了淡水和湿地排放的双重核算,并首次包括对仍然存在的潜在双重核算的估计(平均 23 Tg CH 4 年 -1 )。自下而上的方法表明,2010-2019 年十年间,湿地和内陆淡水的综合排放量平均为 248 [159-369] Tg CH 4 年 -1 。自然通量受到气候、富营养化和土地利用等人类活动的干扰。在本预算中,我们还首次估计了造成湿地和内陆淡水排放的人为因素。新推出的网格产品还使我们能够基于自下而上的方法得出几乎完整的纬度和区域预算。 2010-2019 十年间,通过大气反演(自上而下)估计全球 CH 4 排放量为 575 Tg CH 4 年 -1 (范围 553 –586,对应于模型集合的最小和最大估计)。其中,369 Tg CH 4 年 -1 或约 65% 归因于化石、农业和废物以及人为生物质燃烧中的直接人为来源(范围 350–391 Tg CH 4 年 -1 或 63–68 %)。 2000-2009 年期间,大气逆温的总排放量比 2010-2019 年略低,减少了 32 Tg CH 4 年 -1 (范围 9-40)。自 2012 年以来,全球直接人为 CH 4 排放趋势一直在跟踪政府间气候变化专门委员会提出的不采取或采取最低限度气候缓解政策的情景(共享社会经济路径 SSP5 和 SSP3)。自下而上的方法建议全球排放量增加 16%(94 Tg CH 4 年 -1 )(669 Tg CH 4 年 -1 ,范围 512-849)比 2010-2019 年期间自上而下的反演方法要好。与 Saunois 等人 (2016 ,2020),并且自下而上和自上而下预算的不确定性首次重叠。基于大气逆温的排放的纬度分布表明,与中半球(30° N–60° N,约 30% 的排放)相比,热带和南半球的排放占主导地位(约占全球预算的 65%,<30° N)和北高纬度地区(60° N–90° N,约占全球排放量的 4%)。 这种纬度分布与自下而上的预算类似,尽管自下而上的预算估计中北纬度和高北纬度的贡献略大,而热带地区和南半球的贡献略小于反演。尽管反演和自下而上之间的差异已经缩小,但全球 CH 4 预算中最重要的不确定性来源仍然可归因于自然排放,特别是来自湿地和内陆淡水的排放。我们确定了改善 CH 4 预算的五个主要优先事项: i) 基于可靠的分类,制作水饱和土壤和排放 CH 4 的淹没区域的全球高分辨率地图不同类型的排放生态系统; ii) 进一步开发基于过程的内陆水域排放模型; iii) 将 CH 4 局部观测(例如 FLUXNET-CH 4 测量、城市规模监测、具有指向能力的卫星图像)加强到区域规模(地面网络和全球远程来自卫星的传感测量)以约束自下而上的模型和大气反演; iv) 输运模型的改进和自上而下反演中光化学汇的表示,以及 v) 使用同位素和/或共发射物质(例如乙烷)以及自下而上清单中的信息集成 3D 变分反演系统通过遥感检测人为超级排放源(主要是石油和天然气部门,但也包括煤炭、农业和垃圾填埋场),以改善源分区。此处提供的数据可以从 https://doi.org/10.18160/GKQ9-2RHT 下载(Martinez 等人,2024)。