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2024/25 Taught Postgraduate Module Catalogue

SOEE5081M Air Quality Drivers and Processes

15 creditsClass Size: 30

Module manager: Jim McQuaid

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2024/25

This module is not approved as an Elective

Module summary

The impact on human life expectancy of air pollution is well documented and it is critical that we understand the processes controlling concentrations that communities are exposed to. This module will explore the sources and sinks of air pollutants, considering both urban and rural regions. The module will introduce both gas phase and particulate pollutants, considering the processes that control concentrations on various scalesThe interactions between air quality and climate change are explored alongside the details of pollutant monitoring strategies. Both surface monitoring and satellite observations are introduced as methods of tracking air pollutants.


To produce learners that have an appreciation of the complexity and interconnectedness of the topic, both on different timescales and spatial extent.
The module will provide students with:
- The need to consider air pollution at many scales
- The health implications of air pollution
- Measurement techniques for determining ambient concentrations
- The power of models to reinforce the value of measurements, to probe uncertainty and sensitivity.

Learning outcomes
On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:
1. Critically understand the sources with control levels of air pollutants;
2. Understand the transformation processes that occur following emission and the environmental factors controlling these processes;
3. Understand the relationship between Air Quality and Climate Change;
4. Be aware of the range of techniques and technologies to assess pollutant concentrations including the rapid growth of low-cost sensors;
5. Understand techniques used to combine observations to explore pollution landscapes.

Skills Learning Outcomes

On successful completion of the module students will have demonstrated the following skills learning outcomes:
1. Critically assess scientific evidence to draw conclusions regarding the effectiveness of interventions or policy changes;
2. Analyse and present complex geophysical data using computational data science tools;
3. Design model experiments to test hypotheses or theory;
4. Apply knowledge to novel situations to derive conclusions and predict system behaviour.

Competence Standards

On successful completion of the module students will have demonstrated the following competence standards:
1. Collate information from diverse sources, and analyse, and interpret data to reinforce understanding and develop solutions to problems.
2. Synthesise information and present it in an effective way to different audiences.
3. Apply knowledge to novel situations and tasks to demonstrate understanding of complex problems.
4. Apply data science and computational tools to processing and analysing complex datasets.


Details of the syllabus will be provided on the Minerva organisation (or equivalent) for the module

Teaching methods

Delivery typeNumberLength hoursStudent hours
Private study hours116.00
Total Contact hours34.00
Total hours (100hr per 10 credits)150.00

Opportunities for Formative Feedback

Students will have the opportunity to receive formative feedback on practical work via discussion and feedback from staff and demonstrators in computer sessions throughout the semester, and on their understanding of core material via in-class quizzes.

Methods of assessment

Assessment typeNotes% of formal assessment
Total percentage (Assessment Coursework)100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 24/04/2024


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