Abstract Title: | Introducing the 'local-scale Gaussian plume inversion' flux quantification technique |
Presenter Name: | Mr Adil Shah |
Co-authors: | Dr Grant Allen Dr Peter Hollingsworth Dr Mark Bourn |
Company/Organisation: | University of Manchester |
Country: | United Kingdom |
Abstract Information :
A local-scale Gaussian plume inversion (LGI) method was developed to quantify point source emission fluxes, on a facility scale. The LGI method is suitable for unmanned aerial vehicle (UAV) sampling of in-situ measurements on a plane perpendicular to mean wind direction, downwind of a well-defined source. The LGI method models a flux density in three dimensions, assuming Gaussian statistics, and optimises input parameters in order to reduce residuals between measured and modelled flux density. The minimisation of residuals allows the average plume morphology of a narrow instantaneous emission plume, being turbulently advected over a short (< 500 m) downwind distance, to be taken into account. The LGI method was developed using data from eight UAV flights ~90 m downwind of independent controlled methane releases in Cardington, Bedfordshire UK in November 2016. The method was subsequently tested in Little Plumpton, Lancashire, UK in August and September 2018 using two UAVs. One manually operated UAV carried an on-board prototype high-precision methane sensor. The other waypoint operated UAV carried an on-board low-precision methane sensor but was also connected to a high-precision sensor on the ground using 150 m of tubing. Random walk simulations were used to quantify residual bias due to limitations in the sampling strategy, resulting in increased upper uncertainty limits. The simulations were also used to successfully generate virtual LGI target fluxes, demonstrating the utility of the method for future use in the quantification of emissions from facility scale methane sources such as landfill sites, oil and gas infrastructure facilities or herds of cattle.