Ground-based remote sensing of volcanic CO2 fluxes at Solfatara (Italy)-Direct versus inverse Bayesian retrieval

Research output: Contribution to journalArticle

  • Authors:
  • Manuel Queißer
  • Mike Burton
  • Domenico Granieri
  • Matthew Varnam


CO2 is the second most abundant volatile species of degassing magma. CO2 fluxes carry information of incredible value, such as periods of volcanic unrest. Ground-based laser remote sensing is a powerful technique to measure CO2 fluxes in a spatially integrated manner, quickly and from a safe distance, but it needs accurate knowledge of the plume speed. The latter is often difficult to estimate, particularly for complex topographies. So, a supplementary or even alternative way of retrieving fluxes would be beneficial. Here, we assess Bayesian inversion as a potential technique for the case of the volcanic crater of Solfatara (Italy), a complex terrain hosting two major CO2 degassing fumarolic vents close to a steep slope. Direct integration of remotely sensed CO2 concentrations of these vents using plume speed derived from optical flow analysis yielded a flux of 717-121 t day-1, in agreement with independent measurements. The flux from Bayesian inversion based on a simple Gaussian plume model was in excellent agreement under certain conditions. In conclusion, Bayesian inversion is a promising retrieval tool for CO2 fluxes, especially in situations where plume speed estimation methods fail, e.g., optical flow for transparent plumes. The results have implications beyond volcanology, including ground-based remote sensing of greenhouse gases and verification of satellite soundings.

Bibliographical metadata

Original languageEnglish
Article number125
JournalRemote Sensing
Issue number1
Early online date18 Jan 2018
Publication statusPublished - 2018

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