Analysis of Atmospheric Methane Across Different Spatial and Temporal Scales

Global trends of atmospheric methane are poorly understood due to uncertainties surrounding its sources and sinks. Atmospheric methane has a 20-year global warming potential 80 times greater than carbon dioxide, but a shorter lifetime of approximately 9 years. Therefore, it presents a good short-term opportunity to mitigate the human impact on climate change whilst carbon dioxide emissions are reduced. This research exploits observations and models across different spatial and temporal scales to address important knowledge gaps in atmospheric methane. Specifically, this thesis explores global changes in the seasonal cycle amplitude of methane, develops and demonstrates the capability of a new regional "nested grid'' 3-D chemical transport model, and quantifies emission estimates of a satellite-detected UK gas leak.

Long-term surface-based observations showed a decrease of 4ppb in the seasonal cycle amplitude (SCA) in the northern high latitudes (NHLs; 60N-90N) between 1995-2020. Global chemical transport modelling shows that the largest contributor to this SCA change was from well-mixed methane, as well as changes in emissions from Canada, Middle East and Europe. These results highlight that changes in the observed NHL seasonal cycle can indicate changes in emissions in local and non-local regions.

For studies on a finer spatial scale, a new high resolution regional model "nested'' in TOMCAT called ZOOMCAT was developed and tested. Two case studies were simulated in ZOOMCAT over Europe in 2020. One which simulated the Nord Stream pipeline gas leak, which provided much more spatial detail in plume transport compared to TOMCAT. The lack of improvement in ZOOMCAT when compared with TOMCAT and tall tower observations of methane in these case studies highlighted the importance of input meteorology.

On the metre-scale resolution, emissions from a 2023 gas leak near Cheltenham, UK were detected by tasking GHGSat. The satellite-derived emission estimates were evaluated using a surface-based mobile survey and were found to broadly agree. This work also demonstrated that the UK tall tower network in this case was too sparse to quantify fugitive emissions on this scale using inverse modelling techniques. The total methane leaked over the 11-week period is estimated to be 1,393,392 kg, equivalent to emissions from the average annual electricity consumption of 7,500 homes.