Physical techniques to track and estimate volcanic emissions and their atmospheric dispersion

Volcanic areas represent an important source of risk for cities and populations. At the same time, these systems have significant impacts on atmospheric pollution, for both particles and gases released in the ecosystem. Among these, there are carbon dioxide and sulfur dioxide, that are one of the most important greenhouse gases and the main responsibile of the acid rain respectively. In addition, a small amount of methane, which has a greenhouse potential greater than carbon dioxide, is present in the hydrothermal volcanic emissions. Therefore, the development of innovative tools useful for estimating and tracking volcanic emissions assumes a crucial role. In this context, this PhD thesis deals with the study of volcanic emissions in Sicily (Southern Italy) by using pollutant dispersion modelling techniques and passive acoustic methods. Specifically, this path follows two main phases. The first one focuses on the ash and sulphur dioxide plume modelling due to paroxysmal activity at Mt. Etna by applying a customized configuration of the Weather Research and Forecasting model Chemistry (WRF-Chem) taking in input ground-based data. The second one deals with the study of gas emissions in shallow hydrothermal areas. In particular, a multimethodological modelling approach based on the coupling between passive acoustic methods, WRF (Weather Research and Forecasting) and Calpuff models will be proposed, to track gaseous pollutants that, after their emission from the seafloor reach the atmosphere where are thus dispersed by the prevailing winds. The research activities have been focused on the hydrothermal methane, which is estimated at the seafloor through the application of a customized algorithm of inverse modelling before ingesting the resultant flow rate in the modelling system which computes the atmospheric dispersion. Both approaches provided noteworthy results concerning the respective field of application, proposing themselves as powerful tools for also investigating other areas showing similar features.