Potential of observables for global and regional atmospheric CH₄ budget estimation

Abstract

Methane (CH₄) is the second most important anthropogenic greenhouse gas (GHG) in terms of radiative forcing since 1750, and atmospheric mixing ratios are on the rise globally. However, our understanding of its fluxes is still poor, and our current and past observations including mixing ratios and bulk isotope ratios, δ¹³C and δ²H, do not provide sufficient constraints for an adequate understanding in source or sink estimates, or to verify our understanding of sectoral emissions at regional scales.

This thesis aims to find additional tools with which we can augment our knowledge on methane fluxes. For this purpose, there is a need to assess the impact of new and forthcoming measurements on our understanding of the global and regional CH₄ budget.

Firstly, the potential benefit of measuring ”clumped” isotopologues, specifically ¹³CH₃D and ¹²CH₂D₂, on the quantification of global fluxes is explored. Clumped isotopologues, referring to isotopologues with two or more of its constituents being the rarer isotopes, of CH₄ in the ambient atmosphere have not been measured before due to their low abundance. However the capability of instruments is improving and the recent decade has seen the measurements of high concentration natural samples, and experiments and improved calculations of kinetic isotope effects. We developed a 12-box model and an inverse method to thoroughly explore the added value of measuring clumped isotope ratios in the atmosphere rather than just the total amount fractions and the bulk stable isotope ratios. This work has shown and explained that mixing ratios and bulk isotope ratios (even if the measurement of δ²H was not discontinued), alone cannot sufficiently constrain global sources and sinks, while ¹³CH₃D is largely unresponsive to any changes in the atmospheric state, but ¹²CH₂D₂ has shown potential, even with a measurement frequency as low as annual, to differentiate a global high-emission/high-sink scenario from a low-emission/low sink-scenario.

Secondly, this study presents a novel method that combines measurement of radon (²²²Rn) and high-resolution Lagrangian particle dispersion model output to enhance the methods for regional CH₄ emissions estimation. The half-hourly estimates of ²²²Rn at the tall tower site in Heathfield, UK started in 2020, and back-trajectory footprints are created so that the decay of 222Rn during transport can be considered. This novel application firstly seeks to identify the bias introduced by errors in meteorology, which will help to minimise model-induced bias in top-down inversion methods. Within this study, for the first time, a unique radon dataset is derived from a standardized procedure, which is applicable to any similar 222Rn monitoring station. The obtained results showed that the 222Rn-based method can consistently identify the errors in back-trajectory sensitivity maps. In addition, this novel method suggests under which meteorological conditions the top-down methods need special care to be taken in order to accurately derive.

Lastly, a novel high-resolution hierarchical Bayesian inverse modelling technique based on NAME footprints that incorporates in-situ high frequency bulk isotopes, δ¹³C and δ²H, for regional emission estimation for different source categories is presented. This model is used to assess the impact high-frequency bulk isotope measurements at the tall tower site in Heathfield, UK, would bring to the regional source quantification and apportionments. Sensitivity tests have demonstrated that the inverse model is able to explain potential observations well, and have shown the new measurements improving the model’s performance in source apportionment, but also highlight the challenges in prior uncertainties as well as reduced usefulness of isotopic measurements in a future low CH₄ emission environment.