Modern Geochemistry utilizes three powerful tools: (major and trace) elements, isotopes and equations, to study various Earth and environmental processes. A combination of the experimental tools (elements and isotopes) with theoretical tools (equations) provides penetrating insights into the variability of natural processes.
1) Modern thermodynamics. From Heat Engines to Dissipative Structures. D. Kondepudi, I. Prigogine, Wiley, 1999.
2) Environmental Applications of Geochemical Modeling. C. Zhu, G. Anderson, Cambridge, 2002.
3) Geochemical and Biogeochemical Reaction Modeling. C. M. Bethke, Cambridge, 2008 (II edition).
4) An introduction to Applied Geostatistics. E.H. Isaaks, R.M.
5) Metodi matematici e statistici nelle Scienze della Terra vol. III, Tecniche statistiche. A. Buccianti, F. Rosso, F. Vlacci, Liguori Editore, 2003.
The student learns how to analyze experimental data obtained by geochemical surveys with the aim to model (from a thermodynamic and or statistical and geostatistical point of view) the variability characterizing natural processes.
Fundaments of Mathematics, Chemistry, MIneralogy and Geochemistry
Lectures, exercises in computer room or by using own laptop
Use of Matlab and R software.
Type of Assessment
Final oral exam. Presentation of a technical report with statistical and geostatistical analysis on database given by the teacher. Questions on the developed program.
Environmental problems and the need for geochemical modeling. Real Systems and their modeling. Fluctuations and stability. Linear and non linear processes. Order through fluctuations. Dissipative structures. Computer programs (Matlab, R) for geochemical modeling.
Statistical and geostatistical analysis. Exploratory univariate and bivariate analysis. Deterministic and probabilistic models. Modeling regionalized and coregionalized phenomena. Mapping of spatial data, problems and perspectives. Defining background and threshold values, identification of data outliers and element sources.
Self-organized geochemical systems for different scales, presence of fractals and multifractals structures.
Problems of compositional data analysis and nature (geometry) of the sample space.