Upward revision of global fossil fuel methane emissions based on isotope database

Methane has the second-largest global radiative forcing impact of anthropogenic greenhouse gases after carbon dioxide, but our understanding of the global atmospheric methane budget is incomplete. The global fossil fuel industry (production and usage of natural gas, oil and coal) is thought to contribute 15 to 22 per cent of methane emissions to the total atmospheric methane budget. However, questions remain regarding methane emission trends as a result of fossil fuel industrial activity and the contribution to total methane emissions of sources from the fossil fuel industry and from natural geological seepage, which are often co-located. Here we re-evaluate the global methane budget and the contribution of the fossil fuel industry to methane emissions based on long-term global methane and methane carbon isotope records. We compile the largest isotopic methane source signature database so far, including fossil fuel, microbial and biomass-burning methane emission sources. We find that total fossil fuel methane emissions (fossil fuel industry plus natural geological seepage) are not increasing over time, but are 60 to 110 per cent greater than current estimates owing to large revisions in isotope source signatures. We show that this is consistent with the observed global latitudinal methane gradient. After accounting for natural geological methane seepage, we find that methane emissions from natural gas, oil and coal production and their usage are 20 to 60 per cent greater than inventories. Our findings imply a greater potential for the fossil fuel industry to mitigate anthropogenic climate forcing, but we also find that methane emissions from natural gas as a fraction of production have declined from approximately 8 per cent to approximately 2 per cent over the past three decades.Published88-916A. Geochimica per l'ambienteJCR Journa

Atmospheric Methane : Comparison Between Methane's Record in 2006–2022 and During Glacial Terminations

Atmospheric methane's rapid growth from late 2006 is unprecedented in the observational record. Assessment of atmospheric methane data attributes a large fraction of this atmospheric growth to increased natural emissions over the tropics, which appear to be responding to changes in anthropogenic climate forcing. Isotopically lighter measurements of (Figure presented.) are consistent with the recent atmospheric methane growth being mainly driven by an increase in emissions from microbial sources, particularly wetlands. The global methane budget is currently in disequilibrium and new inputs are as yet poorly quantified. Although microbial emissions from agriculture and waste sources have increased between 2006 and 2022 by perhaps 35 Tg/yr, with wide uncertainty, approximately another 35–45 Tg/yr of the recent net growth in methane emissions may have been driven by natural biogenic processes, especially wetland feedbacks to climate change. A model comparison shows that recent changes may be comparable or greater in scale and speed than methane's growth and isotopic shift during past glacial/interglacial termination events. It remains possible that methane's current growth is within the range of Holocene variability, but it is also possible that methane's recent growth and isotopic shift may indicate a large-scale reorganization of the natural climate and biosphere is under way

Atmospheric Methane: Comparison Between Methane's Record in 2006–2022 and During Glacial Terminations

Atmospheric methane's rapid growth from late 2006 is unprecedented in the observational record. Assessment of atmospheric methane data attributes a large fraction of this atmospheric growth to increased natural emissions over the tropics, which appear to be responding to changes in anthropogenic climate forcing. Isotopically lighter measurements of d13C-CH4 are consistent with the recent atmospheric methane growth being mainly driven by an increase in emissions from microbial sources, particularly wetlands. The global methane budget is currently in disequilibrium and new inputs are as yet poorly quantified. Although microbial emissions from agriculture and waste sources have increased between 2006 and 2022 by perhaps 35 Tg/yr, with wide uncertainty, approximately another 35–45 Tg/yr of the recent net growth in methane emissions may have been driven by natural biogenic processes, especially wetland feedbacks to climate change. A model comparison shows that recent changes may be comparable or greater in scale and speed than methane's growth and isotopic shift during past glacial/interglacial termination events. It remains possible that methane's current growth is within the range of Holocene variability, but it is also possible that methane's recent growth and isotopic shift may indicate a large-scale reorganization of the natural climate and biosphere is under way

Using ice core measurements from Taylor Glacier, Antarctica, to calibrate in situ cosmogenic 14 C production rates by muons

Cosmic rays entering the Earth’s atmosphere produce showers of secondary particles such as protons, neutrons, and muons. The interaction of these particles with oxygen-16 (16O) in minerals such as ice and quartz can produce carbon-14 (14C). In glacial ice, 14C is also incorporated through trapping of 14C-containing atmospheric gases (14CO2, 14CO, and 14CH4). Understanding the production rates of in situ cosmogenic 14C is important to deconvolve the in situ cosmogenic and atmospheric 14C signals in ice, both of which contain valuable paleoenvironmental information. Unfortunately, the in situ 14C production rates by muons (which are the dominant production mechanism at depths of > 6m solid ice equivalent) are uncertain. In this study, we use measurements of in situ 14C in ancient ice (> 50 ka) from the Taylor Glacier, an ablation site in Antarctica, in combination with a 2D ice flow model to better constrain the compound-specific rates of 14C production by muons and the partitioning of in situ 14C between CO2, CO, and CH4. Our measurements show that 33.7% (11.4%; 95% confidence interval) of the produced cosmogenic 14C forms 14CO and 66.1% (11.5%; 95% confidence interval) of the produced cosmogenic 14C forms 14CO2. 14CH4 represents a very small fraction (< 0.3%) of the total. Assuming that the majority of in situ muogenic 14C in ice forms 14CO2, 14CO, and 14CH4, we also calculated muogenic 14C production rates that are lower by factors of 5.7 (3.6–13.9; 95% confidence interval) and 3.7 (2.0–11.9; 95% confidence interval) for negative muon capture and fast muon interactions, respectively, when compared to values determined in quartz from laboratory studies (Heisinger et al., 2002a, b) and in a natural setting (Lupker et al., 2015). This apparent discrepancy in muogenic 14C production rates in ice and quartz currently lacks a good explanation and requires further investigation

Variational inverse modeling within the Community Inversion Framework v1.1 to assimilate δ<SUP>13</SUP>C(CH<SUB>4</SUB>) and CH<SUB>4</SUB>: a case study with model LMDz-SACS

International audienceAtmospheric CH4 mole fractions resumed their increase in 2007 after a plateau during the 1999-2006 period, indicating relative changes in the sources and sinks. Estimating sources by exploiting observations within an inverse modeling framework (top-down approaches) is a powerful approach. It is, nevertheless, challenging to efficiently differentiate co-located emission categories and sinks by using CH4 observations alone. As a result, top-down approaches are limited when it comes to fully understanding CH4 burden changes and attributing these changes to specific source variations. δ13C(CH4)source isotopic signatures of CH4 sources differ between emission categories (biogenic, thermogenic, and pyrogenic) and can therefore be used to address this limitation. Here, a new 3-D variational inverse modeling framework designed to assimilate δ13C(CH4) observations together with CH4 observations is presented. This system is capable of optimizing both the emissions and the associated source signatures of multiple emission categories at the pixel scale. To our knowledge, this represents the first attempt to carry out variational inversion assimilating δ13C(CH4) with a 3-D chemistry transport model (CTM) and to independently optimize isotopic source signatures of multiple emission categories. We present the technical implementation of joint CH4 and δ13C(CH4) constraints in a variational system and analyze how sensitive the system is to the setup controlling the optimization using the LMDz-SACS 3-D CTM. We find that assimilating δ13C(CH4) observations and allowing the system to adjust isotopic source signatures provide relatively large differences in global flux estimates for wetlands (-5.7 Tg CH4 yr-1), agriculture and waste (-6.4 Tg CH4 yr-1), fossil fuels (+8.6 Tg CH4 yr-1) and biofuels-biomass burning (+3.2 Tg CH4 yr-1) categories compared to the results inferred without assimilating δ13C(CH4) observations. More importantly, when assimilating both CH4 and δ13C(CH4) observations, but assuming that the source signatures are perfectly known, these differences increase by a factor of 3-4, strengthening the importance of having as accurate signature estimates as possible. Initial conditions, uncertainties in δ13C(CH4) observations, or the number of optimized categories have a much smaller impact (less than 2 Tg CH4 yr-1)