METODOLOGIE CHIMICHE PER L'AMBIENTE
- Overview
- Assessment methods
- Learning objectives
- Contents
- Bibliography
- Delivery method
- Teaching methods
Basic knowledge of environmental chemistry and statistics. Basic knowledge of the software EXCEL.
Written examination with open questions and exercises. Duration 2 hours.
Aim of this course consists of the development of the following skills: 1) analysis and management of complex data systems through quantitative methodologies, 2) application of these knowledges in a multidisciplinary context, mainly to problems related to the impact of chemicals on the environment 3) formulation of a judgment based on the available information 4) results reporting and drawing conclusions.
Introduction to the course and Environmental Chemistry II : Survey of the main problems of environmental pollution by cheimicals. Chemical and biological reactivity in various environmental compartments. REACH legislation. Alternative energetic sources.Green Chemistry.
Introduction to Chemometrics: Elements of matrix algebra, data structure and pre-processing of data : Introduction to chemometrics, quantitative methods of analysis and modelling to extract useful information from the available data or to generate data using predictive methodologies.
Basic concepts of matrix algebra: unitary, identity, and diagonal matrix; sum and product of matrix; transposed matrix; norm of a vector.
Analysis of the data structure, and data pre-treatment procedures: trend analysis, dispersion analysis, scaling and transformation of variables, covariance and correlation.
Exploratory Data Analysis : Principal Component Analysis, Similarities, dissimilarities and Cluster analysis.
Data modelling techniques : introduction to data modeling for predictivity. Bias vs variance. Validation tecniques for fitting and robustness (Cross-validation) and predictivity (external).
Classification methods: parameters for quality assurance. k-NN as method based on minimal distance, CART as method of tree classification, discriminant analysis.
Linear regression using the ordinary least squares method: basic concepts, quality parameters, diagnostic procedures. Methods of variables selection stepwise and genetic algorithms. Classification examples on computer.
Methodologies based on quantitative (chemical) structure - (biological) activity relationships i.e. QSAR : introduction to QSAR, history, examples of regression and classification models. Application for prioritization of most hazardous chemicals for the environment and humans. The Software QSARINS: theory and application of the software for data analysis and exploration, and for the development of multiple linear regression models. (computer exercises using QSARINS)
Application of the quantitative tools presented in the course to themes of environmental interest.
Practical exercises (chemometrics and computational chemistry)
Suggested Textbook for Environmental Chemistry:
C. Baird M. Cann “Environmental Chemistry ”
Suggested Textbook for Chemometrics:
Roberto Todeschini, Introduzione alla chemiometria. 1998, Edises, Milano. Or other chemometric book.
Additional material: all the course slides are available for students of the course through the e-learning website.
Lessons in Varese, in videodicatics in Como.Use of chemometric software in Varese Lab.