Testing the near-field Gaussian plume inversion flux quantification technique using unmanned aerial vehicle sampling

Shah, Adil; Pitt, Joseph R.; Ricketts, Hugo; Leen, J. Brian; Williams, Paul I.; Kabbabe, Khristopher; Gallagher, Martin W.; Allen, Grant

doi:https://doi.org/10.5194/amt-13-1467-2020

Articles | Volume 13, issue 3

https://doi.org/10.5194/amt-13-1467-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-13-1467-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 3

Research article

|

30 Mar 2020

Research article |

| 30 Mar 2020

Testing the near-field Gaussian plume inversion flux quantification technique using unmanned aerial vehicle sampling

Adil Shah, Joseph R. Pitt, Hugo Ricketts, J. Brian Leen, Paul I. Williams, Khristopher Kabbabe, Martin W. Gallagher, and Grant Allen

Supplement

https://doi.org/10.5194/amt-13-1467-2020-supplement

Data sets

MGGA and pMGGA sensor characterisation data A. Shah and J. R. Pitt https://doi.org/10.5281/zenodo.3706383

Data from the Blackpool testing controlled methane release field campaign of 2018 A. Shah, H. Ricketts, P. I. Williams, J. B. Leen, J. R. Pitt, and G. Allen https://doi.org/10.5281/zenodo.3708518

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Short summary

Methane is a potent greenhouse gas, with large flux uncertainties from facility-scale sources, such as natural gas extraction infrastructure. A recently developed flux quantification method was successfully tested by flying an unmanned aerial vehicle (UAV) downwind of 22 controlled atmospheric methane releases. The UAVs were used to derive high-precision atmospheric methane measurements. The UAV methodology was successful in both detecting the release and providing a rough flux estimate.