This paper is designed to provide the reader with some guidelines towards understanding the importance of the log-ratio approach in geochemistry. An application example is presented with an analysis of the water chemistry from the Arno river basin (Tuscany, central Italy). Simple graphical alternatives are proposed using ilr (isometric log-ratio) transformation on compositional data (constrained support), which are generally used to build up molar-ratio diagrams. If the variables are suitably chosen from a geochemical standpoint, relationships among samples in space and time, as well as compositional changes attributable to different natural or anthropogenic processes, can be analysed on a sound statistical basis. Classical statistics can be applied to ilr diagrams to evaluate differences among groups of data, presence of outliers, or significant changes in time (monitoring). The final aim is to demonstrate that through simple principles of univariate or bivariate statistics, valuable results can be obtained, both from a geochemical and a statistical point of view. The approach can be extended to the analysis of different geochemical data matrices.
Isometric log-ratio co-ordinates and their simple use in water geochemistry / A. Buccianti. - In: BOLETIN GEOLOGICO Y MINERO. - ISSN 0366-0176. - STAMPA. - 122(4):(2011), pp. 453-458.
Isometric log-ratio co-ordinates and their simple use in water geochemistry
BUCCIANTI, ANTONELLA
2011
Abstract
This paper is designed to provide the reader with some guidelines towards understanding the importance of the log-ratio approach in geochemistry. An application example is presented with an analysis of the water chemistry from the Arno river basin (Tuscany, central Italy). Simple graphical alternatives are proposed using ilr (isometric log-ratio) transformation on compositional data (constrained support), which are generally used to build up molar-ratio diagrams. If the variables are suitably chosen from a geochemical standpoint, relationships among samples in space and time, as well as compositional changes attributable to different natural or anthropogenic processes, can be analysed on a sound statistical basis. Classical statistics can be applied to ilr diagrams to evaluate differences among groups of data, presence of outliers, or significant changes in time (monitoring). The final aim is to demonstrate that through simple principles of univariate or bivariate statistics, valuable results can be obtained, both from a geochemical and a statistical point of view. The approach can be extended to the analysis of different geochemical data matrices.File | Dimensione | Formato | |
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