81758 - Atmospheric Chemistry

Learning outcomes

At the end of the course, students will get an appropriate understanding of the chemical and physico-chemical processes occurring in the atmosphere, with special focus on problems related to ozone layer, greenhouse effect and tropospheric pollution both in the gaseous and in the heterogeneous phases (aerosol). In particular, students will gain the basic knowledge necessary to set up experimental design in the various compositional atmospheric problems (monitoring, trend and time series analysis, processes related to aerosol, outdoor and indoor environments); will possess the mathematical and informatic tools used in investigation methods; will get chemical and physical concepts needed to carry out qualitative and quantitative evaluations of the impact of processes induced by anthropic activity on the atmosphere by means of receptor-models and source-apportionment techniques.

Course contents

This course provides an advanced overview of atmospheric composition and of the chemical and physico-chemical processes controlling air quality and climate. Particular emphasis is placed on trace species responsible for atmospheric pollution and climate forcing, and on the methods used to investigate their sources, transformations, transport, and impacts.

The course is organized into two modules.

Module 1 – Atmospheric Chemistry and Atmospheric Composition

• Structure and composition of the atmosphere under natural and polluted conditions.
• Major and trace atmospheric constituents.
• Spatial and temporal variability of atmospheric composition from local to global scales.
• Monitoring, detection, and measurement techniques for atmospheric species.
• Atmospheric transport processes and atmospheric lifetimes.
• Primary and secondary pollutants.
• Atmospheric photochemistry and chemical transformation processes.
• Formation of photochemical smog.
• Stratospheric ozone depletion and recovery.
• Oxidation chemistry of the troposphere.
• Sources, sinks, and atmospheric budgets of greenhouse gases and other climate forcers.
• Environmental, climatic, and health impacts of atmospheric pollutants.

Module 2 – Aerosol Chemistry and Source Apportionment

• Chemical composition of atmospheric particulate matter and the use of chemical species as source markers and tracers.
  
• Primary emissions, atmospheric processing, and the formation of secondary aerosol.
• Principles of source apportionment and the complementary perspectives of source-oriented and receptor-oriented models.
• Mathematical formulation, assumptions, data requirements, and limitations of receptor models.
• Design of a receptor-modelling study: sampling strategy, chemical characterisation, uncertainty assessment, data validation, and preliminary exploratory analyses.
• Chemical Mass Balance modelling: source profiles, model assumptions, source collinearity, model diagnostics, and interpretation of source contributions.
• Multivariate methods for atmospheric datasets and introduction to factor analysis.
• Positive Matrix Factorization: uncertainty-weighted fitting, selection of the number of factors, residual analysis, rotational ambiguity, and factor interpretation.
• Comparison of Chemical Mass Balance and Positive Matrix Factorization approaches.
• Representation and attribution of secondary aerosol in receptor-oriented and source-oriented models.
• Use of meteorological information, wind analysis, polar plots, and back trajectories to support the interpretation of sources, atmospheric processes, and transport pathways.
• Practical applications and case studies based on atmospheric aerosol datasets.
• Computer exercises using Chemical Mass Balance and Positive Matrix Factorization software.
  
  The module combines theoretical lectures, examples from current atmospheric research, and computer exercises. Particular attention is devoted to evaluating model assumptions, uncertainties, diagnostic results, and the strength of the evidence supporting source interpretation.

Readings/Bibliography

Required Learning Material

• Lecture notes, slides, datasets, and supplementary material provided by the instructors through the University e-learning platform.

Recommended Textbooks

• Jeremy Colls and Abhishek Tiwary, Air Pollution: Measurement, Modelling and Mitigation, Third Edition, CRC Press, 2009.
• John H. Seinfeld and Spyros N. Pandis, Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, 2nd Edition, Wiley, 2012.

Further Reading

• Mircea, M., Calori, G., Pirovano, G., and Belis, C., European Guide on Air Pollution Source Apportionment for Particulate Matter with Source-Oriented Models and their Combined Use with Receptor Models, EUR 30082 EN, Publications Office of the European Union, Luxembourg, 2020.

Additional scientific papers, technical reports, and recent publications will be provided during the course to complement the topics discussed in class.

Teaching methods

Teaching activities consist of lectures, guided discussions, numerical exercises, and problem-solving sessions.

Lectures are supported by slides, blackboard explanations, scientific literature, technical reports, and examples derived from current atmospheric research. Particular attention is devoted to linking theoretical concepts with real-world environmental applications.

The source apportionment module includes practical exercises and case studies designed to develop students’ ability to analyse atmospheric datasets, critically evaluate model assumptions, and interpret modelling results.

These activities are intended to foster both theoretical understanding and the quantitative skills required for atmospheric composition analysis and air quality assessment.

Assessment methods

Student learning is assessed through an oral examination covering the entire course syllabus.

The examination consists of three questions:

• two questions addressing topics covered in Module 1;
• one question addressing topics covered in Module 2.

The examination is designed to assess:

• knowledge and understanding of atmospheric chemical and physico-chemical processes;
• ability to explain atmospheric composition dynamics from local to global scales;
• understanding of aerosol processes and source apportionment methodologies;
• ability to critically discuss monitoring approaches, modelling techniques, and environmental impacts;
• appropriate use of scientific terminology.

Assessment Criteria

• 18–19/30: basic knowledge of the main topics and limited ability to discuss processes and methodologies.
• 20–24/30: satisfactory understanding of the course contents and ability to explain standard concepts and applications.
• 25–29/30: good command of the subject, ability to establish connections among different topics, and appropriate use of technical terminology.
• 30–30 cum laude: comprehensive and critical understanding of atmospheric chemistry processes, strong analytical skills, excellent command of scientific terminology, and ability to discuss complex environmental issues independently.

Regarding assessment, the use of generative Artificial Intelligence tools is not permitted during examination activities. Any unauthorized use constitutes a violation of academic integrity. (PQA 2026 – Scenario 1).

Students with learning disorders and\or temporary or permanent disabilities: please, contact the office responsible (https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students ) as soon as possible so that they can propose acceptable adjustments. The request for adaptation must be submitted in advance (15 days before the exam date) to the lecturers, who will assess the appropriateness of the adjustments, taking into account the teaching objectives

Teaching tools

The following resources will be made available to students:

• Lecture notes and slides in PDF format.
• Scientific articles, technical reports, and additional references supporting the topics discussed during lectures.
• Datasets for data analysis exercises.
• Specific software and computational tools used for source apportionment applications and practical exercises.
• Additional material distributed through the University e-learning platform.

Generative AI tools may be used as support for individual study activities, such as literature exploration, summarization of concepts, and self-assessment exercises. However, they do not replace independent study of the course materials and may not be used during examinations.

Office hours

See the website of Erika Brattich

See the website of Alessandro Zappi