Publication date: February 2018
Source:Atmospheric Environment, Volume 174
Author(s): Aryeh I. Feinberg, Ancelin Coulon, Andrea Stenke, Stefan Schwietzke, Thomas Peter
The atmospheric methane growth rate has fluctuated over the past three decades, signifying variations in methane sources and sinks. Methane isotopic ratios (δ13CH4) differ between emission categories, and can therefore be used to distinguish which methane sources have changed. However, isotopic modelling studies have mainly focused on uncertainties in methane emissions rather than uncertainties in isotopic source signatures. We simulated atmospheric δ13CH4 for the period 1990–2010 using the global chemistry-climate model SOCOL. Empirically-derived regional variability in the isotopic signatures was introduced in a suite of sensitivity simulations. These simulations were compared to a baseline simulation with commonly used global mean isotopic signatures. We investigated coal, natural gas/oil, wetland, livestock, and biomass burning source signatures to determine whether regional variations impact the observed isotopic trend and spatial distribution. Based on recently published source signature datasets, our calculated global mean isotopic signatures are in general lighter than the commonly used values. Trends in several isotopic signatures were also apparent during the period 1990–2010. Tropical livestock emissions grew during the 2000s, introducing isotopically heavier livestock emissions since tropical livestock consume more C4 vegetation than midlatitude livestock. Chinese coal emissions, which are isotopically heavy compared to other coals, increase during the 2000s leading to higher global values of δ13CH4 for coal emissions. EDGAR v4.2 emissions disagree with the observed atmospheric isotopic trend for almost all simulations, confirming past doubts about this emissions inventory. The agreement between the modelled and observed δ13CH4 interhemispheric differences improves when regional source signatures are used. Even though the simulated results are highly dependent on the choice of methane emission inventories, they emphasize that the commonly used global mean signatures are inadequate. Regional isotopic signatures should be employed in modelling studies that try to constrain methane emission inventories.
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