Articles | Volume 26, issue 21
https://doi.org/10.5194/acp-26-15915-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-15915-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Probabilities of detection of methane plumes by remote sensing and implications for inferred emissions distributions
Ethan Manninen
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Apisada Chulakadabba
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
School of Computation, Information and Technology, Technischen Universität München, Munich, Germany
Maryann Sargent
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Zhan Zhang
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Harshil Kamdar
Insight M, Sunnyvale, CA 94085, USA
Jack Warren
Environmental Defense Fund, Washington DC, USA
Sébastien Roche
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Environmental Defense Fund, Washington DC, USA
Center for Astrophysics, Harvard and Smithsonian, Cambridge, MA, USA
Christopher Chan Miller
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Environmental Defense Fund, Washington DC, USA
Center for Astrophysics, Harvard and Smithsonian, Cambridge, MA, USA
Ethan Kyzivat
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Joshua Benmergui
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Environmental Defense Fund, Washington DC, USA
Jasna Pittman
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Eleanor Walker
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Jacob Bushey
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Jenna Samra
Center for Astrophysics, Harvard and Smithsonian, Cambridge, MA, USA
Jacob Hawthorne
Center for Astrophysics, Harvard and Smithsonian, Cambridge, MA, USA
Bingkun Luo
Center for Astrophysics, Harvard and Smithsonian, Cambridge, MA, USA
Maya Nasr
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Center for Astrophysics, Harvard and Smithsonian, Cambridge, MA, USA
Research and Education in Energy, Environment, and Water Institute, University at Buffalo, Buffalo, NY, USA
Jonathan Franklin
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
Xiong Liu
Center for Astrophysics, Harvard and Smithsonian, Cambridge, MA, USA
School of Computation, Information and Technology, Technischen Universität München, Munich, Germany
Steven Wofsy
CORRESPONDING AUTHOR
Harvard University School of Engineering and Applied Sciences, Cambridge, MA, USA
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Cumulative views and downloads
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Cited
3 citations as recorded by crossref.
- Detection and quantification of agricultural methane plumes using MethaneAIR through targeted scene selection, wavelet denoising, and divergence-integral analysis P. Smale et al. https://doi.org/10.5194/acp-26-10661-2026
- Performance validation of the GHGSat methane constellation via controlled releases A. Ramier et al. https://doi.org/10.5194/amt-19-6643-2026
- Automatic methane plume masking based on wavelet transform image processing: application to MethaneAIR and MethaneSAT data Z. Zhang et al. https://doi.org/10.5194/amt-19-4637-2026
3 citations as recorded by crossref.
- Detection and quantification of agricultural methane plumes using MethaneAIR through targeted scene selection, wavelet denoising, and divergence-integral analysis P. Smale et al. https://doi.org/10.5194/acp-26-10661-2026
- Performance validation of the GHGSat methane constellation via controlled releases A. Ramier et al. https://doi.org/10.5194/amt-19-6643-2026
- Automatic methane plume masking based on wavelet transform image processing: application to MethaneAIR and MethaneSAT data Z. Zhang et al. https://doi.org/10.5194/amt-19-4637-2026
Latest update: 11 Nov 2026
Short summary
In this work, my coauthors and I interpret methane emissions observed by remote sensing systems as plumes, or point sources. We model the probability that a general imaging spectrometer will detect a plume, and apply this framework to multiple remote sensing systems. We show how two recent systems- MethanAIR and MethaneSAT- provide enough sensitivity to facility scale point sources to effectively characterize most plume emissions in the Permian Basin.
In this work, my coauthors and I interpret methane emissions observed by remote sensing systems...
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