Inverse modeling analysis demonstrates limited reduction in regional methane emission uncertainties using single-site dual-isotope data, highlighting the need for denser networks.
Methane is emitted from a range of anthropogenic and natural sources, and identifying these sources is important for emissions monitoring and mitigation. Different sources emit methane with different isotopic signatures. However, these signatures can vary spatially and temporally and are often not well understood. Top-down inverse methods can be used with measurements of methane mole fractions to estimate total emissions of methane from all sources. Here, we present an inverse system for concurrently estimating regional fossil-fuel (FF) and non-fossil-fuel (non-FF) emissions, using isotope ratio observations and considering uncertainty in the isotopic signatures. This method is highly adaptable and could be used to estimate emissions from any number of sources. Synthetic data tests with this method show that this inverse system can accurately estimate FF and non-FF methane emissions across the UK, when isotopic source signatures are fixed at known values. However, emissions estimation becomes less accurate when source signature uncertainties are increased to over approximately 50 % of their likely ranges. In a real-world test of this method, we estimated south-east UK FF and non-FF emissions using high-frequency δ13C-CH4 and δ2H-CH4 observations from one UK site, with source signature uncertainties reflecting our current understanding of these values. Results show only a limited impact on emissions uncertainty and magnitude, when compared with a methane-only inversion. This suggests that both an expansion of the UK network of isotope ratio observations and an improved understanding of isotopic signatures is required for this method to be effective in estimating UK FF and non-FF methane emissions with reduced uncertainty compared to traditional inverse methods.
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Ramsden et al. (2026) studied this question.
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