Ground-Based Remote Sensing of Volcanic CO2 Fluxes at Solfatara (Italy)—Direct Versus Inverse Bayesian Retrieval

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.