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Authors: Queißer, Manuel* 
Burton, Mike* 
Granieri, Domenico* 
Varnam, Matthew* 
Title: Ground-Based Remote Sensing of Volcanic CO2 Fluxes at Solfatara (Italy)—Direct Versus Inverse Bayesian Retrieval
Issue Date: 2018
Series/Report no.: /10 (2018)
DOI: 10.3390/rs10010125
Abstract: 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.
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