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A global dataset of <i>δ</i><sup>13</sup>C-CH<sub>4</sub> source signatures and associated uncertainties (1998–2022); with a sensitivity analysis to support isotopic inversions
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DOI：10.5194/essd-18-4793-2026.png)
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Abstract
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Abstract. The isotopic composition of atmospheric methane (δ13C-CH4) provides critical constraints for attributing methane emissions to specific sources. In this study; we present updated global maps of δ13C-CH4 source signatures across five major methane-emitting sectors (fossil fuels and geological; agriculture and waste; biomass and biofuel burning; wetlands; and other natural sources) for the period 1998–2022. These maps integrate recent spatially explicit datasets and literature-derived observations; and include explicit quantification of both intrinsic (within-sector) and aggregation-related uncertainties. Building upon previous global compilations; our dataset extends the temporal coverage to 2022; harmonizes sectoral definitions with the Global Methane Budget framework; and provides a consistent and traceable quantification of uncertainties suitable for atmospheric inversions. We assess the influence of these updated source signatures on the modeled atmospheric δ13C-CH4 using forward simulations within the Community Inversion Framework (CIF) coupled to the LMDz transport model. A comprehensive sensitivity analysis quantifies the impacts of key drivers of uncertainty; including emission flux datasets; OH sinks; kinetic isotope effects; and isotopic source signatures. We show that uncertainties in methane oxidation chemistry and source signatures; particularly from agriculture and waste; dominate the variability in the modeled δ13C-CH4 signal; while the impact of flux aggregation choices is comparatively minor. The updated isotopic dataset is provided on a global 1°×1° grid; supporting future atmospheric inversions and improved methane budget assessments at global and regional scales. Practical guidelines for configuring isotopic inversions; including recommended uncertainty specifications and key parameters to optimize; are also provided; offering a framework for next-generation δ13C-CH4 inversion studies. The final version of the gridded δ13C-CH4 source signature dataset is available under CC BY 4.0 (Tapin et al.; 2025; https://doi.org/10.57780/ESA-6D202E9).
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