Articles | Volume 19, issue 13
https://doi.org/10.5194/gmd-19-5979-2026
https://doi.org/10.5194/gmd-19-5979-2026
Development and technical paper
 | 
13 Jul 2026
Development and technical paper |  | 13 Jul 2026

HyperGas 1.0: a python package for analyzing hyperspectral data for greenhouse gases from retrieval to emission rate quantification

Xin Zhang, Joannes D. Maasakkers, Tobias A. de Jong, Paul Tol, Frances Reuland, Adam R. Brandt, Eric A. Kort, Taylor J. Adams, and Ilse Aben

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Cited articles

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Borger, C., Beirle, S., Butz, A., Scheidweiler, L. O., and Wagner, T.: High-Resolution Observations of NO2 and CO2 Emission Plumes from EnMAP Satellite Measurements, Environ. Res. Lett., 20, 044034, https://doi.org/10.1088/1748-9326/adc0b1, 2025. a, b
Brandt, A., Reuland, F., Adams, T., Sherwin, E., Abbadi, S. E., and Kort, E.: Unlocking Credible Space-Based Methane Sensing through a Year-Long Single-Blind Test, Research Square, https://doi.org/10.21203/rs.3.rs-9110475/v1, 2026. a
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Short summary
Reducing emissions of greenhouse gases such as methane and carbon dioxide is essential for addressing climate change. We developed HyperGas, an open tool that uses hyperspectral satellite images to retrieve and detect greenhouse gas plumes. It helps scientists locate emission sources, estimate their strength, and examine uncertainties through an easy workflow and visual app. Our goal is to make tracking human-made emissions more accurate and accessible, supporting better climate monitoring.
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