Comprehensive evaluation of aircraft-based methane sensing for greenhouse gas mitigation

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Authors

Sahar Head El Abbadi, Zhenlin Chen, Philippine M. Burdeau, Jeffrey S. Rutherford, Yuanlei Chen , Zhan Zhang, Evan David Sherwin , Adam R Brandt 

Abstract

Methane is a major contributor to anthropogenic greenhouse gas emissions. Identifying large sources of methane, particularly from the oil and gas sector, will be essential for mitigating climate change. Aircraft-based methane sensing platforms can rapidly detect and quantify methane point-source emissions across large geographic regions, playing an increasingly important role in industrial methane management and greenhouse gas inventory. We independently evaluate the performance of five major methane-sensing aircraft platforms: Carbon Mapper, GHGSat-AV, Kairos Aerospace, MethaneAIR, and Scientific Aviation. Over a 6-week period, we released metered gas for over 700 single-blind measurements across all five platforms to evaluate their ability to detect and quantify emissions that range from 1  kg(CH4)/hr to over 1,500  kg(CH4)/hr. Aircraft consistently quantified releases above 10  kg(CH4)/hr, and GHGSat-AV and Kairos Aerospace detected emissions below 5 kg(CH4)/hr. Fully-blinded quantification estimates for platforms using spectroscopy-based measurements have parity slopes ranging from 0.76 to 1.13, with R2 values of 0.61 to 0.93; the platform using an in situ measurement approach has a parity slope of 0.5 (R2 = 0.93). Results demonstrate aircraft-based methane sensing has matured since previous studies and is ready for an increasingly important role in environmental policy and regulation.

DOI

https://doi.org/10.31223/X51D4C

Subjects

Engineering, Environmental Monitoring, Oil, Gas, and Energy

Keywords

methane, remote sensing, single-blind, controlled release

Dates

Published: 2023-06-22 05:43

License

CC BY Attribution 4.0 International

Additional Metadata

Data Availability (Reason not available):
All data and code required to reproduce the figures and analysis in this paper will be made available prior to publication. Due to ongoing analysis of other parts of the study, we are currently refraining from sharing raw data publicly as of June 2023.