METODOLOGIE CHIMICHE PER L'AMBIENTE - Mod. A Chimica ambientale applicata
Knowledge of environmental chemistry, in particular of the problems deriving from the presence of pollutants in the various environmental compartments. Basic elements of Statistics. Familiarity with the basic functions of the EXCEL software.
The course aims to provide students with the knowledge and skills necessary for the exploration and modeling of complex data using the main multivariate analysis techniques and modeling techniques (regression and classification).
At the end of the course the student will have the following knowledge:
• Quantitative methodologies for the study of chemical-environmental problems
• Complex data structure
• Main techniques of exploration and modeling of complex data through qualitative and quantitative methodologies
As a result, the student will develop the following skills:
• Exploration and management of complex data systems using quantitative qualitative methodologies
• Identification of the appropriate models based on the problem under investigation
• Development and validation of qualitative and quantitative predictive models
• Application of knowledge in a multidisciplinary context, with particular reference to the problems arising from the impact of chemicals to the environment
The student must develop adequate communication skills regarding the exposure of the identified problems, the methods used and the results achieved, using an appropriate language, as well as the ability to formulate a judgment and derive conclusions based on the information available or derived through the application of multivariate analysis and modeling.
Introduction to the course and basic elements of Environmental Chemistry II (4h): Verification of previous knowledge of the Environmental Chemistry of the student cohort. Summary of the main problems of environmental pollution, with particular reference to chemical and biological reactivity of chemical compounds in air, water, soil and sediments and environmental distribution. The REACH legislation.
Introduction to Chemometrics (4h): Introduction to chemiometry and its utility in its various fields of application. Basic concepts of matrix algebra. Analysis of the data structure and pre-treatment methods: trend and dispersion indices, transformations and scaling of variables, association between variables: covariance and correlation.
Methods of Exploratory Analysis (8h + 4h computational lab) Principal Component Analysis, similarity, dissimilarity and Cluster analysis
Data modeling methods (10h + 4h computational lab):General introduction to data modeling methods for predictive purposes. Fitting and predictivity. Validation techniques: cross-validation, external validation. Classification methods: distinction between clustering and classification. Evaluation parameters of the efficiency of the classification. k-NN as an example of methods based on minimum distance. CART as an example of tree classification methods. Discriminant analysis. Multivariate Regression Methods: Ordinary Squares Minimum Method (OLS). Diagnostic methods. Variable selection methods.
In silico alternatives to animal testing (front 4h +4h computational lab): Introduction to alternative methods to animal testing, 3R strategy, QSAR modeling with examples of application for prediction of properties and activities of organic environmental pollutants
Examples of application of the methodologies seen in class to environmental issues (10 h frontal + 4h computational lab) Application of chemometrics to problems related to the environmental context such as drugs in the environment, bioaccumulation and biotransformation of chemical substances, modeling of properties of nanoparticles.
C. Baird M. Cann “Chimica Ambientale” Zanichelli
Roberto Todeschini, Introduzione alla chemiometria. 1998, Edises, Milano.
Power Point slides and additional material will be made available on the e-learning website.