CARDELLINI, C., CHIODINI, G., FRIGERI, A., BAGNATO, E., AIUPPA, A., WERNER, C., FISCHER, T., FRONDINI, F., IONESCU, A., VIVEIROS, F., D’ALESSANDRO, W. (2021) – The MAGA database: state of the art and preliminary data elaboration toward an estimation of the contribution of diffuse CO2 degassing to the global carbon emissions, 1^st CCVG Virtual Workshop, 24-26 de maio.

​Understanding the complex process of gas release from the Earth’s interior by volcanoes and tectonically active areas, and improving the current estimates of global carbon emissions requires access to data collections and tools to explore and analyse these data. MaGa is an online database that was developed to collect data on gas compositions and fluxes from volcanic and tectonic gas emissions and make them available in the web. MaGa allows to insert data interactively and dynamically into a spatially referenced relational database system. Data can be accessed from a web interface and data-driven web services, where software clients can request data directly from the database. This way, GIS and Virtual Globes can access the database, and data can be exchanged with other database. MaGa currently contains the location of about 1000 gas emission sites (volcanic plumes, fumaroles, vents and diffuse degassing areas) and about 2000 records including gas flux and gas composition data from about 158 volcanoes. Data of diffuse CO₂ degassing archived in MaGa have been elaborated in order to attempt an estimate of the total volcanic diffuse emission of CO₂. Data analysis has been focussed on characterising the typical CO₂ emission from a diffuse degassing structure that coupled with a reasonable number for degassing volcanoes hosting diffuse emissions was used to estimate the total CO₂ emission. Preliminary results showed that diffuse degassing processes significantly contribute to the global volcanic CO₂ emissions. However, data analysis pointed out also that ad-hoc and reliable investigations of diffuse degassing at a larger number of volcanoes are necessary to improve the estimate.