A Near-Field Gaussian Plume Inversion Flux Quantification Method, Applied to Unmanned Aerial Vehicle Sampling

Autor: Adil Shah, Grant Allen, Joseph R. Pitt, Hugo Ricketts, Paul I. Williams, Jonathan Helmore, Andrew Finlayson, Rod Robinson, Khristopher Kabbabe, Peter Hollingsworth, Tristan C. Rees-White, Richard Beaven, Charlotte Scheutz, Mark Bourn
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Atmosphere, Vol 10, Iss 7, p 396 (2019)
Druh dokumentu: article
ISSN: 2073-4433
DOI: 10.3390/atmos10070396
Popis: The accurate quantification of methane emissions from point sources is required to better quantify emissions for sector-specific reporting and inventory validation. An unmanned aerial vehicle (UAV) serves as a platform to sample plumes near to source. This paper describes a near-field Gaussian plume inversion (NGI) flux technique, adapted for downwind sampling of turbulent plumes, by fitting a plume model to measured flux density in three spatial dimensions. The method was refined and tested using sample data acquired from eight UAV flights, which measured a controlled release of methane gas. Sampling was conducted to a maximum height of 31 m (i.e. above the maximum height of the emission plumes). The method applies a flux inversion to plumes sampled near point sources. To test the method, a series of random walk sampling simulations were used to derive an NGI upper uncertainty bound by quantifying systematic flux bias due to a limited spatial sampling extent typical for short-duration small UAV flights (less than 30 min). The development of the NGI method enables its future use to quantify methane emissions for point sources, facilitating future assessments of emissions from specific source-types and source areas. This allows for atmospheric measurement-based fluxes to be derived using downwind UAV sampling for relatively rapid flux analysis, without the need for access to difficult-to-reach areas.
Databáze: Directory of Open Access Journals