Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/6264
AuthorsCorsaro, Rosa Anna* 
Falsaperla, Susanna* 
Langer, Horst* 
TitleNew Insights into Composition of Volcanic Products at Mt. Etna, Italy, from Geochemical Pattern Classification
Issue Date31-May-2010
URIhttp://hdl.handle.net/2122/6264
KeywordsVolcanic Products
Mt. Etna
Geochemical pattern classification
Subject Classification04. Solid Earth::04.08. Volcanology::04.08.05. Volcanic rocks 
AbstractGeochemical analyses of volcanic products erupted by Mt. Etna, Italy, have been carried out by INGV-CT (formerly CNR-IIV) staff since three decades. The need to realize a near-real time monitoring of the basic compositional features of a magma compelled since the 1990s an organization of personnel engaged for sampling and analyzing the collected rocks in laboratories. Geochemical monitoring has been outstandingly improved with the application of sophisticated, but quick, analytical techniques which take into account both oxides as well as trace elements of lavas. The geochemical monitoring offers up-to-date information on processes and dynamics of magma, and allows documenting the evolution of different eruptive styles throughout an eruptive event. Accordingly, changes in chemical parameters have become a key information for the Italian Civil Defence to highlight any hazardous evolution of volcanic activity at Etna, and promptly warn potential endangered populations. Compared to traditional classification methods, where compositional patterns are defined by selecting oxides and/or elements in binary and ternary petrologic systems, we can handle a statistics with many components, in our specific case thirteen (SiO2, K2O, CaO/ Al2O3, Mg, Th, La, Nb, Nd, Sr, Tb, Cr, Ni, Rb/Nb). The statistical treatment of geochemical patterns exploits Kohonen Maps and Fuzzy Clustering, which are applied to samples collected at Etna between 1995 and 2005. We present a comprehensive picture of the evolution of these products in time and space with a convenient visualization of the results. The application of multivariate classification allows us to identify a signature in the compositional characteristics of magma erupted from the four summit craters and/or flank eruptive vents, even in the time spans in which volcanic activity was concurrent. Dubious compositional changes are also considered in the light of earthquakes and volcanic tremor characteristics, which offer independent evidence of the significance of the results.
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