δ13C-CH4: source signatures from space.

Every methane source carries an isotopic fingerprint: biogenic sources (wetlands, cattle, landfills) are isotopically light, fossil sources heavier, fires heavier still. If you know the fingerprints, the atmosphere tells you the mixture.

A new global source-signature dataset [TN2 §3.3.2]

SMART-CH4 produced a gridded, sector-resolved global dataset of δ13C-CH4 source signatures for 1998–2022, built from a literature review plus recent sector-specific datasets, with time extrapolation where signatures are known to have drifted (US oil and gas, wetlands) and aggregation weighted by CH4 emission per grid cell.

Five gridded global maps of delta-13C-CH4 source signatures in per mil vs V-PDB, one per sector: Wetlands and Freshwaters (-75 to -40 per mil), Agriculture and Waste (-70 to -50 per mil), Biofuels and Biomass burning (-30 to -16 per mil), Fossil fuels and Geological (-55 to -35 per mil), and Other natural sources (-70 to -35 per mil). Each map shows spatial variation in isotopic signature across land areas, with each sector using its own colour scale.
The gridded, sector-resolved δ13C-CH4 source-signature dataset (1998–2022), one map per sector — wetlands & freshwaters, agriculture & waste, biofuels & biomass burning, fossil fuels & geological, and other natural sources. Colour scale is ‰ vs V-PDB and differs by panel, since each sector's isotopic range is different (fossil sources cluster far heavier than wetlands, for instance).

DOI: 10.57780/esa-6d202e9 · Tapin et al., ESSD, 2026. doi:10.5194/essd-18-4793-2026

Can we see it from space?

A Monte-Carlo signal-to-noise study (CIF–LMDz–SACS, synthetic GOSAT, TROPOMI and IASI observations, 2018–2024, 15 ensemble members) gives a clear and slightly deflating answer:

So δ13C-CH4 from space may support source attribution — but only in specific large-scale configurations, and only once systematic errors are controlled. (Which loops back to the spectroscopy work: that is precisely the constraint being attacked.)

What isotopes do to an inversion

A sensitivity analysis identified the kinetic isotope effect as the dominant source of spread — an ensemble approach is recommended — while the choice of aggregation method barely matters, meaning the new maps can be used directly. δ13C uncertainties must be propagated through the inversion, and agriculture/waste signatures should be optimised rather than fixed.

Preliminary joint CH4 + δ13C-CH4 inversions (surface network, 2002–2020) shift posterior wetland fluxes by 17 Tg/yr relative to a CH4-only inversion — a large change in one of the most uncertain terms in the global budget. Six inversions across three OH fields show where isotopes would help most: agriculture/waste and wetlands have the largest inter-inversion spread, and fossil-fuel disagreement concentrates over major producing regions. Satellite-based isotopic inversions have not yet converged; that work continues.

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