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Atmosphere 2018, 9(9), 333; https://doi.org/10.3390/atmos9090333

Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Localization and Quantification of Emission Rate

1
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08540, USA
2
Physical Sciences Inc., Andover, MA 01810, USA
3
Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX 77004, USA
4
Heath Consultants Inc., Houston, TX 77061, USA
*
Author to whom correspondence should be addressed.
Received: 1 March 2018 / Revised: 7 July 2018 / Accepted: 16 July 2018 / Published: 23 August 2018
(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))
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Abstract

We describe a set of methods for locating and quantifying natural gas leaks using a small unmanned aerial system equipped with a path-integrated methane sensor. The algorithms are developed as part of a system to enable the continuous monitoring of methane, supported by a series of over 200 methane release trials covering 51 release location and flow rate combinations. The system was found throughout the trials to reliably distinguish between cases with and without a methane release down to 2 standard cubic feet per hour (0.011 g/s). Among several methods evaluated for horizontal localization, the location corresponding to the maximum path-integrated methane reading performed best with a mean absolute error of 1.2 m if the results from several flights are spatially averaged. Additionally, a method of rotating the data around the estimated leak location according to the wind is developed, with the leak magnitude calculated from the average crosswind integrated flux in the region near the source location. The system is initially applied at the well pad scale (100–1000 m2 area). Validation of these methods is presented including tests with unknown leak locations. Sources of error, including GPS uncertainty, meteorological variables, data averaging, and flight pattern coverage, are discussed. The techniques described here are important for surveys of small facilities where the scales for dispersion-based approaches are not readily applicable. View Full-Text
Keywords: source estimation; methane emissions; natural gas; leak surveys; inverse emissions; MONITOR; UAV; LDAR source estimation; methane emissions; natural gas; leak surveys; inverse emissions; MONITOR; UAV; LDAR
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Golston, L.M.; Aubut, N.F.; Frish, M.B.; Yang, S.; Talbot, R.W.; Gretencord, C.; McSpiritt, J.; Zondlo, M.A. Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Localization and Quantification of Emission Rate. Atmosphere 2018, 9, 333.

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