Analysis of Volcanic CO₂ Emissions Using Next-Generation Satellite Hyperspectral Data

The present work investigates advanced methodologies for detecting and quantifying volcanic carbon dioxide (CO₂) emissions from degassing plumes and fumarole fields using hyperspectral data acquired by satellite and airborne sensors. Building upon well-established algorithms such as the Continuum Interpolated Band Ratio (CIBR), Matched Filter (MF) and Imaging Mapping Differential Optical Absorption Spectroscopy (IMAP-DOAS), this study introduces innovative approaches that exploit the high spectral resolution of modern hyperspectral satellite sensors. In particular, the analysis leverages data from the Italian Space Agency (ASI) satellite mission PRecursore IperSpettrale della Missione Applicativa (PRISMA) launched in 2019, and operating in the Visible and Near-InfraRed (VNIR) and Short-Wave InfraRed (SWIR) spectral ranges. The quantification of the CO₂ columnar content is achieved through the application of the Matched Filter algorithm to CO₂ absorption features in the 1900–2200 nm spectral interval. The MF approach is designed to maximize the detection of the CO₂ spectral signature while suppressing background variability associated with surface reflectance and atmospheric effects. We provide the first examples of high-resolution maps of CO₂ concentration and flux from two actively degassing, quiescent volcanoes (Campi Flegrei and Vulcano Island), hence contributing to volcanic monitoring efforts. Our results provide new insights into volcanic degassing processes and their potential implications for the regional and global carbon cycle and for the climate system.