Methane Flux Quantification Using Unmanned Aerial Vehicles

  • Adil Shah

Student thesis: Phd


Methane is a potent greenhouse gas. The global methane budget is poorly constrained, due in part to inaccurate flux quantification from facility scale anthropogenic sources. Accurate atmospheric measurement based (top-down) flux quantification is needed to help constrain inventory emission estimates. These top-down fluxes require in situ sampling of downwind methane mole fraction, near to source. An unmanned aerial vehicle (UAV) is an ideal platform to derive these measurements either by capturing samples for subsequent analysis, by pumping air through a tether to a sensor on the ground or with live on-board sampling. Methane flux density can be derived from two-dimensional downwind in situ sampling. When sampling a static plume, characterised by dispersive mixing, an emission flux can traditionally be derived treating the flux density plume as bell shaped or Gaussian. However, when sampling less than 500 m away from the emission source, the observed emission plume can move due to wind turbulence. It can appear episodically in space as it does not have time to diffusively mix, over short distances. The near-field Gaussian plume inversion (NGI) technique was therefore developed to model a moving plume. The NGI method assumes the spatial extent of the plume to increase linearly with distance from the source, allowing for sampling on a slightly offset plane. The NGI method also characterises the size of the plume using flux density measurements, rather than assumptions of atmospheric stability, otherwise valid for dispersive mixing. The NGI method was tested by flying a UAV downwind of a controlled methane release, resulting in 19 of 22 fluxes agreeing with the controlled emission flux, within uncertainty. Methane mole fraction was measured using precise infrared spectroscopy. A low precision sensor was also tested but was found to be unsuitable with the UAV NGI methodology. UAV sampling was then applied to detect and quantify emissions from a barn containing lactating cattle and the UK's first exploratory operation employing the horizontal hydraulic fracturing (fracking) of shale rock. Instantaneous fracking emissions were observed on one of five sampling days due to cold venting associated with liquid unloading, which was used to engage gas flow from the fracking well. Thus the NGI method with UAV sampling is suitable for low cost source identification and rough (order of magnitude level) flux estimation, with instrument quality being the largest limitation.
Date of Award1 Aug 2020
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorMartin Gallagher (Supervisor), Hugo Ricketts (Supervisor), Grant Allen (Supervisor) & Peter Hollingsworth (Supervisor)


  • Global Warming
  • Greenhouse Gas
  • Infrared Spectroscopy
  • Facility Scale
  • Lactating Cattle
  • Unmanned Aerial Vehicle
  • Flux
  • Methane
  • Hydraulic Fracturing

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