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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 >6 m 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 (%) 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.

Atmospheric 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).

Atmospheric methane’s rapid growth from 2006 to the present is unprecedented in the observational record. Isotopic evidence implies the growth is mainly driven by an increase in biogenically-sourced emissions, both from wetlands and ruminants, and waste. A significant part of methane’s current rise may come not from direct anthropogenic emissions and land use changes, but rather from a combination of natural biogenic feedback responses, occurring in response to the anthropogenic forcing. Although microbial emissions from agricultural and waste have increased between 2006-2020 by about 35 Tg/yr, perhaps 35-40 Tg/yr of the recent net growth in methane emissions may have been driven by natural biogenic processes, especially wetland feedbacks to climate change. Modelling comparison between the biogenic component of methane’s growth and isotopic shift in the 15 years from 2007-2022, and the global-scale climate reorganisations during the transitions from glacial to interglacial periods in the Pleistocene, shows that the modern growth event is comparable to or greater than the scale and speed of methane’s growth and isotopic shift during past glacial/interglacial termination events. It remains possible that current changes are related to decadal- or centennial-scale variability in precipitation and temperature and remain within the range of Holocene variability, or due to direct anthropogenic actions. But, though any current transition will differ greatly from the past glacial-interglacial changes, it is also possible methane’s remarkable growth and isotopic shift that began in 2006 may be a first indicator that a very large-scale reorganisation of the natural climate and biosphere system is under way.