Articles | Volume 26, issue 14
https://doi.org/10.5194/acp-26-10661-2026
https://doi.org/10.5194/acp-26-10661-2026
Research article
 | 
30 Jul 2026
Research article |  | 30 Jul 2026

Detection and quantification of agricultural methane plumes using MethaneAIR through targeted scene selection, wavelet denoising, and divergence-integral analysis

Penelope Smale, Alexander Geddes, Sara Mikaloff-Fletcher, Zhan Zhang, Apisada Chulakadabba, MaryAnn Sargent, Christopher C. Miller, Sébastien Roche, Joseph Rudek, Jonathan Franklin, Jack Warren, and Steven Wofsy

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Cited articles

CDPHE: Feedlot registration and compliance data, Colorado Department of Public Health Environment – Environmental Agriculture Program, 2017. 
Chan Miller, C., Roche, S., Wilzewski, J. S., Liu, X., Chance, K., Souri, A. H., Conway, E., Luo, B., Samra, J., Hawthorne, J., Sun, K., Staebell, C., Chulakadabba, A., Sargent, M., Benmergui, J. S., Franklin, J. E., Daube, B. C., Li, Y., Laughner, J. L., Baier, B. C., Gautam, R., Omara, M., and Wofsy, S. C.: Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission, Atmos. Meas. Tech., 17, 5429–5454, https://doi.org/10.5194/amt-17-5429-2024, 2024. 
Chang, J., Peng, S., Yin, Y., Ciais, P., Havlik, P., and Herrero, M.: The Key Role of Production Efficiency Changes in Livestock Methane Emission Mitigation, AGU Advances, 2, e2021AV000391, https://doi.org/10.1029/2021AV000391, 2021. 
Chen, Y., Sherwin, E. D., Berman, E. S. F., Jones, B. B., Gordon, M. P., Wetherley, E. B., Kort, E. A., and Brandt, A. R.: Quantifying Regional Methane Emissions in the New Mexico Permian Basin with a Comprehensive Aerial Survey, Environ. Sci. Technol. 56, 4317–4323, 10.1021/acs.est.1c06458, 2022. 
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MethaneAIR was used to quantify methane emissions from concentrated animal feeding operations (CAFOs) using a targeted scene‑based approach with wavelet denoising. Emissions show substantial variability and are often elevated relative to inventory estimates under detectable conditions, reflecting variability, detection bias, and activity data uncertainty. Results highlight MethaneAIR capability and the potential of future satellite platforms.
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