MULTIVARIATED DATA ANALYSIS IN ENVIRONMENTAL MATRICES

The course aims to introduce students to chemometrics tools that can be useful in studying and interpreting complex systems.
The course will start with the description of the multivariate structure of data for the characterization of a chemical/environmental system. The main methods covered in the course will be: Pattern Recognition, with particular reference to Cluster Analysis, Principal Component Analysis (PCA) and the development of predictive multivariate models (PCR and PLS) by means of QSAR (Quantitative Structure-Activity Relationship) strategy and Experimental Design.
Particular emphasis will be given to the development and the validation of multivariate calibration models, and to the study and the understanding of practical problems concerning environmental systems. Different cases of study will be discussed in-depth.
These knowledge are extremely important inside the Degree’s program, because the students will acquire the necessary skills for interpreting environmental data and understanding the mechanisms and the dynamics of environmental processes in chemical, ecological, geological, hydrogeological and biological field. That is the starting point for implementing strategies of remediation, monitoring and evaluation of environmental biodiversity, as well as defense of natural resources.
The course has a predominant experimental approach and is focused on the understanding and the practical use of the main methods of Pattern Recognition.
In this course, limited emphasis will be placed on mathematical and statistical details, in order to devote more attention to a variety of applications and case studies specifically aimed at developing problem-solving skills in both environmental monitoring and remediation, as well as in addressing issues related to the improvement of ecosystem service quality — the two main focuses of the master’s degree program.

The student will be able to acquire:
1) the appropriate skills for using chemometrics methods of multivariate analysis, such as Pattern Recognition methods and Experimental Design;
2) the ability to apply these methods for solving new environmental problems, by being able to interpret new data related to environmental systems. These skills will be given by the presentation of specific cases of study in which chemometrics methods are applied;
3) a sufficient critical approach on choosing the right chemometrics methods for solving environmental problems and on extrapolating from the results useful information, which can lead him to implement a decisional strategy of action on an environmental system.
The student will have to learn a consistent and correct use of the language and terminology, so he will be able to propose and communicate this methodological approach even to people who don’t have these skills and with whom he will have to collaborate in a professional future.

High school basic knowledge of mathematics and General Chemistry

Pattern Recognition.
Preliminary data processing, classification methods and clustering methods based on metrics and adherence to mathematical models. K-NN, LDA.
Cluster Analysis: general principles, numerical examples of agglomerative hierarchical clusters, interpretation of a dendrogram, supported by case studies: water quality, analysis of the profile of a marine sediment core, temporal study of metals present in atmospheric particulate matter in the city of Turin.
Non-hierarchical methods (K-means).
Principal Component Analysis (PCA): theory, use and applications, supported by case studies: water quality, analysis of the composition of volatile organic pollutants and of a vertical soil profile in a contaminated site, Study of chemical contamination in the Venice Lagoon, study and characterization of fecal sterols (as biomarkers) of large mammals in soil samples from North America.
The SIMCA method.
Multivariate correlation models: MRA, PCR, PLS methods and validation criteria. Selection of the optimal model dimensionality and its optimization. Strategies to obtain the best dimensionality (cross-validation criteria). Practical applications: multivariate models of tropospheric persistence of HCFCs, modeling to predict physicochemical properties in gasoline samples in a refinery.
Experimental Design.
Factorial designs, D-efficiency and D-optimal designs. Practical use of chemometric software. A large part of the course will be dedicated to the study of real cases found in the literature, tailored to the two specific tracks of the Degree Programme: Natural Capital / ecosystem services and monitoring / remediation.

Didactic material and presentations provided by the professor.
Roberto Todeschini: "Introduzione Alla Chemiometria". EDiSES, Napoli.
D.L. Massart et al: "Chemometrics:a Textbook", Data Handling in Science and Technology, 2, ELSEVIER, Amsterdam.

The final mark will be given after an oral examination concerning the topics discussed during the course. The student will be asked to discuss cases of study and show the ability to apply the chemometrics approach to real environmental problems.

oral

1. scores in the 18-22 range will be awarded in the presence of:
- sufficient knowledge and ability to understand applied in reference to the program;
- limited ability to collect and/or interpret data, formulating independent judgments;
- sufficient communication skills;
2. scores in the 23-26 range will be awarded in the presence of:
- fair knowledge and ability to understand applied in reference to the program;
- fair ability to collect and/or interpret data, formulating independent judgments;
- fair communication skills;
3. scores in the 27-30 range will be awarded in the presence of:
- good or excellent knowledge and ability to understand applied in reference to the program;
- good or excellent ability to collect and/or interpret data, formulating independent judgments;
- fully appropriate communication skills.
4. honors will be awarded in the presence of knowledge and understanding applied in reference to the program, judgment and communication skills, excellent.

Classroom lessons. The lessons will have the main goal of explaining the “philosophy” of the chemometrics approach, which is completely different from the one commonly used in the traditional scientific method.

This subject deals with topics related to the macro-area "Natural capital and environmental quality" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development