EGUsphere EGUsphere EGUsphere EGUsphere Copernicus Publications Göttingen, Germany 10.5194/egusphere-2025-6127 <em>HyperGas</em> 1.0: A Python package for analyzing hyperspectral data for greenhouse gases from retrieval to emission rate quantification Zhang Xin https://orcid.org/0000-0002-1756-6620 1 Maasakkers Joannes D. https://orcid.org/0000-0001-8118-0311 1 de Jong Tobias A. https://orcid.org/0000-0002-5211-8081 1 Tol Paul 1 Reuland Frances 2 Brandt Adam R. 2 Kort Eric A. 3 Adams Taylor J. https://orcid.org/0009-0008-0334-2977 3 Aben Ilse 1 4 SRON Space Research Organisation Netherlands, Leiden, 2333 CA, The Netherlands Department of Energy Science & Engineering, Stanford University, Stanford, California 94305, USA Department of Climate & Space Sciences & Engineering, University of Michigan, Ann Arbor, MI 48109, USA Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands 11 01 2026 2026 1 29 Copyright: © 2026 Xin Zhang et al. 2026 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2025-6127/ The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2025-6127/egusphere-2025-6127.pdf

We present HyperGas, an open-source Python package for the retrieval and estimation of atmospheric greenhouse gas concentration enhancements and plume emission rates using data from hyperspectral imagers such as the PRecursore IperSpettrale della Missione Applicativa (PRISMA), the Environmental Mapping and Analysis Program (EnMAP), and the Earth Surface Mineral Dust Source Investigation (EMIT). The software is designed for compatibility with any three-dimensional hyperspectral radiance dataset. HyperGas supports multiple retrieval algorithms, including matched filter and lognormal matched filter, and offers two emission rate estimation methods: the integrated mass enhancement and cross-sectional flux approaches. The software provides a scalable batch-processing framework that supports data workflows from radiances to emission rates and an interactive graphical user interface that enables visualization of gas plumes. Built on high-level data structures such as xarray and CSV, HyperGas simplifies metadata handling and facilitates robust analysis and visualization. The package provides a robust foundation for community use and expansion. This toolkit aims to advance atmospheric monitoring capabilities and support both research and operational applications of greenhouse gas monitoring.