MSc Air Quality Solutions with Data Science(Not recruiting in 2024/25)

Year 1

(Award available for year: Master of Science)

Learning outcomes

1. Demonstrate an in-depth understanding of air quality fundamentals, informed by knowledge across all causally linked elements of emission sources, meteorology, atmospheric processes, pollution exposure indoors and outdoors, then associated health impacts;

2. Demonstrate an advanced understanding of UK/EU/International emission and air quality guidance and regulations, including appreciating the strengths and weaknesses of current practices, and forming own opinions of likely future developments in the field;

3. Exhibit a broad knowledge of environmental measurements and their strengths and weaknesses (uncertainties), by understanding: the fundamental principles of a wide range of sensors, data architectures used to store data, and quality assurance processes;

4. Articulate keys aspects of air pollution model design and be able to critically assess the strengths and limitations of different numerical model frameworks;

5. Converse with a wide range of sophisticated analytical and data visualisation techniques, whether handling measured or modelled information, to evaluate the performance of policies and models;

6. Evaluate solutions to mitigate poor air quality, using structured analysis frameworks, calling upon both qualitative and quantitative data;

7. Develop as an Environmental Sciences and Air Quality professional, building professional relationships with others and appreciate the contributions from industry, research and government organisations;

8.demonstrated through the production of an independent research dissertation, proactively formulate ideas, review literature and identify research gaps and hypotheses, then develop, implement and execute plans by which to critically and creatively evaluate current issues, research and advanced scholarship in the field of Environmental Sciences and Air Quality.


Skills Learning Outcomes
1. the broad skill set necessary to undertake a higher research degree and/or for employment in directly relevant and closely aligned fields of Environmental Sciences and management;

2. the skills to analyse and interpret complex, uncertain environmental data using a variety of data science tools;

3. the skills to design and use modelling concepts in a variety of contexts and applications areas, to test hypotheses and theories, and design mitigation solutions;

4. the judgement to select and effectively deploy sensors to evaluate policies and the performance of models;

5. relate own research and analyses to UK government and global policies, directives and wider social justice priorities;

6. work collaboratively and communicate with technical and non-expert audiences through a variety of media and presentation settings.

Assessment

The assessments will take a multidisciplinary approach, aimed at assessing fulfilment of the learning and skills outcomes.

Assessments will be authentic and include:

• practical field and modelling-based investigations;

• case study reports based on skills from observations, modelling and data analysis to support decision-making the design of air quality mitigations (solutions);

• group working, reporting and oral presentations based on real-life case studies, which will include an appreciation of societal contribution and context;

• independent research poster presentation and report, aimed at furthering understanding of air quality issues mitigation solutions.