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Quantifying fossil fuel methane emissions using observations of atmospheric ethane and an uncertain emission ratio

Ramsden, A E; Ganesan, A L; Wastern, L M; Rigby, M; Manning, A J; Foulds, A; France, J L; Barker, P; Levy, P; Say, D; Wisher, A; Arnold, T; Rennick, C; Stanley, K M; Young, D; O'Doherty, S (2022) Quantifying fossil fuel methane emissions using observations of atmospheric ethane and an uncertain emission ratio. Atmospheric Chemistry and Physics, 22 (6). pp. 3911-3929.

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We present a method for estimating fossil fuel methane emissions using observations of methane and ethane, accounting for uncertainty in their emission ratio. The ethane:methane emission ratio is incorporated as a spatially and temporally variable parameter in a Bayesian model, with its own prior distribution and uncertainty. We find that using an emission ratio distribution mitigates bias from using a fixed, potentially incorrect emission ratio and that uncertainty in this ratio is propagated into posterior estimates of emissions. A synthetic data test is used to show the impact of assuming an incorrect ethane:methane emission ratio and demonstrate how our variable parameter model can better quantify overall uncertainty. We also use this method to estimate UK methane emissions from high-frequency observations of methane and ethane from the UK Deriving Emissions linked to Climate Change (DECC) network. Using the joint methane–ethane inverse model, we estimate annual mean UK methane emissions of approximately 0.27 (95 % uncertainty interval 0.26–0.29) Tg yr−1 from fossil fuel sources and 2.06 (1.99–2.15) Tg yr−1 from non-fossil fuel sources, during the period 2015–2019. Uncertainties in UK fossil fuel emissions estimates are reduced on average by 15 % and up to 35 % when incorporating ethane into the inverse model, in comparison to results from the methane-only inversion.

Item Type: Article
Subjects: Environmental Measurement > Atmospheric Science, Emission and Security
Divisions: Atmospheric Environmental Sciences
Identification number/DOI: 10.5194/acp-22-3911-2022
Last Modified: 07 Nov 2022 14:30
URI: http://eprintspublications.npl.co.uk/id/eprint/9574

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