Assessment of Sensors and Methodology for Unmanned Aerial Vehicle Applications in Surveying Anthropogenic Methane Emissions

Abstract

Methane (CH₄) is the second most significant greenhouse gas driving climate change, with a much higher global warming potential than carbon dioxide over shorter timescales. Despite its rapid increase in atmospheric concentrations, significant uncertainties remain in accurately quantifying and attributing emissions. This thesis explores the use of unmanned aerial vehicle (UAV) platforms, sensors, and complementary datasets, to characterise and quantify methane emissions from anthropogenic sources, helping to constrain top-down methane estimates. A UAV-based methane emissions mapping survey at a landfill site using an open-path tunable diode laser (OP-TDL) methane sensor was studied. The analysis reconstructed UAV flight paths, filtered suboptimal data, and examined methane and wind measurements to identify and map emission hotspots. While this approach provided a rapid whole-site assessment, challenges such as distinguishing false positives, establishing reliable background levels, and pinpointing emission sources were identified. Laboratory experiments further evaluated the LaserMethane mini (LMm) OP-TDL sensor, highlighting notable inaccuracies and inconsistencies at ambient methane levels, though improved performance was observed at elevated concentrations. These findings underscore both the potential and limitations of UAV-based mapping surveys with OP-TDL sensors, emphasising the need for refined survey strategy, sensor calibration to improve accuracy and reliability in complex, dynamic environments. In a further case study, a UAV platform equipped with a high-precision Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS) methane sensor (the ABB GLA-133) and a 2D anemometer (wind sensor) was built to quantify emissions from the same landfill site. Methane emissions were estimated at 150.7 kg h⁻¹, with a standard deviation uncertainty range of 83.0 to 209.5 kg h⁻¹. This study provided valuable guidance on optimising sampling strategies, defining methane background concentrations, and performing geospatial interpolation. Additionally, it highlighted key remaining challenges associated with UAV wind measurements and the spatial characterisation of emission plumes. A third study in this thesis assessed urban methane emissions in Manchester, using data from the Manchester Air Quality Supersite (MAQS) and discussed the potential applications of UAVs for urban methane monitoring. Over a three-year period, methane mole fraction showed notable temporal variability, influenced by seasonal cycles, boundary layer dynamics, and meteorological conditions, with a clear upward trend consistent with global background observations. The analysis inferred the prominence of non-combustion related methane sources, such as natural gas leaks or waste treatment facilities. However, no strong spatial or temporal patterns emerged from the MAQS data to reliably inform the timing and location of potential UAV methane surveys. This suggests that the current common UAV applications, focused on point source or facility-level emissions, are not directly suited to complex and dynamic urban environments, notwithstanding challenges with UAV operation in urban settings. Alternative UAV applications, requiring future technological advancements, to better address the unique challenges of urban methane monitoring are also discussed in the thesis.

Date of Award	31 Mar 2025
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Hugo Ricketts (Supervisor) & Grant Allen (Supervisor)