Atmospheric chemistry and physics · 2022 · 21 citations · 49 references
Natural SciencesEarth SciencesEnvironmental SciencesAtmospheric ScienceBayesian Data AnalysisUncertainty QuantificationClimate ChangeEmission InventoriesGreenhouse Gas AccountingClimate Uncertainty QuantificationEmission UncertaintyEmissions Uncertainty AnalysisMethane Emission InventoriesMethane Emission ModelingMethane EmissionsMethane Emissions AccountingMethane Emissions Inventories
Abstract. 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.
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The Global Methane Budget 2000-2017
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