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.
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.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Mar 2020
Research article |
| 30 Mar 2020
| 30 Mar 2020
Testing the near-field Gaussian plume inversion flux quantification technique using unmanned aerial vehicle sampling
Centre for Atmospheric Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
Joseph R. Pitt
Centre for Atmospheric Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
Hugo Ricketts
Centre for Atmospheric Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
National Centre for Atmospheric Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
J. Brian Leen
ABB – Los Gatos Research, 3055 Orchard Drive, San Jose, CA 95134, USA
Paul I. Williams
Centre for Atmospheric Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
National Centre for Atmospheric Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
Khristopher Kabbabe
School of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
Martin W. Gallagher
Centre for Atmospheric Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
Grant Allen
Centre for Atmospheric Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
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- A Pilot Demonstration of Flaring Gas Recovery during Shale Gas Well Completion in Sichuan, China M. Xue et al. 10.2118/214665-PA
- Methane flux from flowback operations at a shale gas site J. Shaw et al. 10.1080/10962247.2020.1811800
- Methods for quantifying methane emissions using unmanned aerial vehicles: a review J. Shaw et al. 10.1098/rsta.2020.0450
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- Laser photo-acoustic methane sensor (7.7 µm) for use at unmanned aerial vehicles I. Sherstov et al. 10.1016/j.infrared.2023.104865
- Quantifying methane emissions from coal mining ventilation shafts using an unmanned aerial vehicle (UAV)-based active AirCore system T. Andersen et al. 10.1016/j.aeaoa.2021.100135
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- Advanced Leak Detection and Quantification of Methane Emissions Using sUAS D. Hollenbeck et al. 10.3390/drones5040117
- Unmanned aerial vehicle observations of cold venting from exploratory hydraulic fracturing in the United Kingdom A. Shah et al. 10.1088/2515-7620/ab716d
- Diurnal and Seasonal Variation of Area-Fugitive Methane Advective Flux from an Open-Pit Mining Facility in Northern Canada Using WRF M. Nambiar et al. 10.3390/atmos11111227
- Cavity Ring-Down Methane Sensor for Small Unmanned Aerial Systems B. Martinez et al. 10.3390/s20020454
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- Using Ground- and Drone-Based Surface Emission Monitoring (SEM) Data to Locate and Infer Landfill Methane Emissions T. Abichou et al. 10.3390/methane2040030
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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.
Methane is a potent greenhouse gas, with large flux uncertainties from facility-scale sources,...
