Pollution and Environmental Control (online)

In this unit, you’ll build a foundation of general skills relating to measuring and predicting pollutant mobility and transformation.

Learn why measurement is meaningful – through statistical significance, sampling methods and analytical techniques – and appreciate when and why prediction is required.

Understand general techniques of prediction based on comparison of measurements, relationships and models, and develop an understanding of the processes and vocabulary surrounding models, using pollution case studies. 

A one-day virtual field trip and an introduction to the department’s analytical facilities will give you practical training and reinforce theoretical concepts.

 Learning outcomes: 

• Be able to recognise generic processes of research and categorise research into different types.
• Make your measurements meaningful and recognise the quality of those made by others.
• Design a sampling strategy by applying an understanding of variability. 
• Select appropriate techniques for the measurement and analysis of fluids and solids by applying knowledge of how instruments work.
• Apply a process of mathematical model developed to understand a simple environmental system.
• Evaluate whether arguments are logical in connecting objectives to aims.

In this unit, following on from Measuring and Predicting 1, you’ll focus on the use of models to make predictions and aid the interpretation of measurements.

Get an introduction to the use of models in the environmental sciences, drawing on examples from current scientific literature. Discuss the merits and limitations of various approaches.

A series of lectures and practical sessions will showcase different models, and a combination of baseline simulations and sensitivity tests will help explain relevant computational models. You’ll benefit from hands-on experience with different models, interpreting their output, and focusing on how they relate to the real world.

Learning outcomes: 

• Demonstrate knowledge of different modelling approaches.
• Investigate the kinds of problems that numerical models can help to solve and how they can augment measurements.
• Describe the assumptions of different modelling approaches in environmental sciences.
• Analyse environmental model output, from different data formats, and describe and present results in a useful way.
• Recognise model artefacts such as numerical diffusion and instabilities.
• Evaluate whether arguments are logical in connecting objectives to aims

In this unit you will examine and understand how human activities cause change and damage to the biosphere through key topics including the environmental impact of resource extraction and use, agriculture and air pollution from road transport, and the effect of urbanisation on water resources.

You will also assess mitigation and management strategies such as monitoring and remediation (including bioremediation) and start using methods and approaches – from molecular to community level – to assess and predict human impact on ecosystems.

This unit will be delivered through lectures videos and video seminar/practice sessions where more detailed case studies and data on the key topics will be provided and discussed through the use of research papers.

Learning outcomes: 

• Explain the impact of natural resource exploitation and pollution on populations and communities through the study of important human activities.
• Describe methods and approaches used in the assessment and prediction of anthropogenic impacts on key ecosystems and biomes.
• Explain the importance of connecting and integrating knowledge regarding human impacts, including on the whole biosphere.
• Evaluate the use of field and laboratory studies in understanding and solving environmental problems arising from human activities.
• Appraise and discuss research literature regarding contemporary and controversial issues related to human impacts on the environment. 

This unit uses urban environment theme case studies to develop environmental modelling skills and project management skills to work through a project life cycle for a simulated science/consultancy project using real world case studies. 

The emphasis of this unit is on helping you to develop advanced modelling skills and learn detailed knowledge about one of the following topics: flood prevention and mitigation in cities, and water resource planning for future urban and economic development. You will learn about how the models relate to the real world rather than computational details. 

Workshop sessions will focus on project planning, monitoring and reporting. Benefit from the opportunity to bring all your modelling knowledge together and present your solutions as a briefing note and video presentation.

Learning outcomes: 

• Be able to plan work from a project scope, develop a project programme, identify project risks, develop a project approach strategy, and use tools to share information and collaborate with team members.
• Be able to use industry-standard software for environmental modelling purposes to evaluate how urban development perturbs the natural environment, and how the natural environment impacts urban communities using real-world case studies.
• Apply environmental models to either evaluate future urban, and industrial development on natural lake environment or used to mitigate flood risk in UK cities, or to evaluate the impacts of nature dam failure on mountain settlements.
• Analyse model output to assess environmental impacts and use outcomes to make recommendations for mitigation and adaption in urban environments.
• Write individual short technical briefing documents which show an appreciation of the standards expected at the university graduate level.
• Make illustrated oral presentations to stakeholders (including animations, videos, and infographics) and demonstrate the ability to defend their position in a seminar environment. 

This unit will help you to understand the scope of pollution and its wider context, and the connections between natural processes and pollution. Get to grips with the concept of misplaced materials and misplaced people, and discuss particular types of pollution.

You will also learn about important concentration gradients that drive pollution, as well as methods to measure and predict their impact, quantified through consideration of organic and metal pollution.

Understand physical mobility as a result of diffusion and dispersion, and how to quantify it through water, sediment, groundwater, stream water and atmosphere.

In this unit you can apply your knowledge during a virtual field trip, with the opportunity to make measurements, predict outcomes and validate your predictions.

Learning outcomes: 

• Define pollution and thereby general approaches to its control.
• Use knowledge of the chemistry of natural waters to predict the distribution of organic and inorganic pollutants.
• Use knowledge of the chemistry/mineralogy of earth materials to predict the potential for certain environments to be pollution sources or sinks.
• Formulate knowledge of dispersion and diffusion into predictive models of pollutant mobility.

In this unit you will develop mathematical models to understand a simple environmental system, learn about data collection and examine environmental monitoring methods for water movement studies.

You will learn how to use different techniques to analyse the natural processes of surface water runoff and groundwater, as well as the movement of water in rivers and on floodplains. Understand the importance of reservoirs and water transport, release and movement in urban areas

You will also be able to apply models using industry-standard software, learn to interpret output, and evaluate performance and parameters through sensitivity analysis to solve real-world problems.

You will apply models to design dams and evaluate their impacts on water movement downstream. The unit finishes by exploring future trends and challenges in water movement and how technology such as remote sensing, Big Data, the Internet of Things (IoT) and Artificial Intelligence (AI) may provide solutions.

Learning outcomes: 

• Apply a process of mathematical model development to understanding a simple environmental system using the theme of water movement.
  
• Assess data collection and environmental monitoring for water movement studies.
• Select appropriate techniques for analysis of the natural processes of surface water runoff and groundwater, the movement of water in rivers and on floodplains, the storage of water in reservoirs, the release of water from dams, water transport and supply for food and energy production, water releases for the environment, the water movement in urban areas and its impact on water quality and pollution.
• Demonstrate knowledge of different modelling approaches including catchment and groundwater modelling, river modelling, forecasting modelling, dam breach modelling, reservoir operation, water resource modelling, modelling urban drainage systems, and modelling water quality and pollution, using real-world case studies.
• Be able to use industry-standard software for environmental modelling of the movement of water and recognise their application to real-world problems.
• Be able to use models for water movement studies and to interpret model output, evaluate model performance and evaluate model parameters through sensitivity analysis and provide solutions to real-world problems.

In this unit, you will learn how to select appropriate techniques for measuring environmental data and apply industry-standard software for hydraulic, river, water resource and glacier runoff modelling in a range of climatic zones.

Examine various measurement and modelling approaches and get hands-on experience with data analysis using GIS, applying models and interpreting model output.

Use different models to explore flood hydrology and the mechanism of flooding, including techniques to collect and analyse hydrometric data. Examine catchment flow dynamics using 1D and 2D numerical modelling.

Become familiar with climate change models, predicted impacts and global future megatrends, including population growth, urbanisation, climate change and the effect of these on society.

This unit complements ‘Measuring and Predicting’ Part 1 and Part 2 by exploring processes but also with an emphasis on using models used in industry to examine real-world problems rather than focusing on the computational detail. 

This unit will also introduce climate change models and some of the predicted impacts around the world with a focus on East Africa.

Learning outcomes: 

• Apply flood hydrology and be able to estimate design flows used to resolve flooding problems.
• Recognise the appropriate hydrometeorological data collection and environmental monitoring methods.
• Demonstrate knowledge of different modelling approaches including hydrological and hydraulic (1D 2D and 3D) modelling, water resource modelling, glacier modelling, and climate models using case studies.
• Use industry-standard software for environmental modelling purposes and recognise their application to real-world problems.
• Assess the importance of the water-food-energy nexus, global water insecurity, causes of water conflicts, and the economics of water scarcity, and how water resources modelling can assist policymakers for food security and poverty reduction purpose.
• Use a glacier runoff model and interpret model output, to evaluate model performance and evaluate model parameters through sensitivity analysis.

This unit consists of weekly sessions to help guide you in the planning and proposal of your final research project. In this unit you will look at issues to consider when preparing for a research project, and how to apply these to your individual project.

This unit will be taught through a series of video lectures in addition to guidance for individual projects via weekly videos and a series of small group tutorials.

In this unit you will create a draft research proposal presentation and report to prepare you for your official research proposal presentation and research project report at the end of your course.

Learning outcomes: 

• Describe and structure the key requirements of a strong research proposal.
• Synthesise literature and data to identify potentially viable research projects and the critical data required to be obtained to achieve the research project aims and objectives.
• Subdivide the requirements of a research project to identify relevant tractable methods and sampling strategies to achieve them and develop a plausible viable research project plan.
• Defend a research proposal or research proposition against reasonable criticism.
• Apply relevant literature review, computer modelling, and field and/or laboratory protocols relevant to obtaining preliminary data for the purposes of preparing a research proposal.
• Apply key skills and attributes of those seeking employment in the environment sector by planning and presenting a professional research proposal.

• Choose to focus on a water or air pollution project.
• The skills you will learn will be relevant to all areas of environmental science, whether within the industry or if you decide to pursue a higher research degree afterwards.
• Research projects include training themed around fieldwork, lab work and advanced computing.
• The water project will feature virtual labs and fieldwork conducted in an upper peat catchment in the Peak District.
• The air project will feature virtual fieldwork in Manchester using our new, state-of-the-art 'air quality supersite' facility in Fallowfield, Manchester.
• Water project computer training is in predictive numerical modelling tools.
• Air project computing training is in machine learning applications for advanced data analysis.

Learning outcomes: 

• Review literature or otherwise, describe the key theories and concepts relevant to a specified research area and compare and contrast data outputs that would be consistent with different theoretical models or hypotheses.
• Identify a research question and clearly summarise the relevant and key points of context as well as the aims and objectives arising.
• Devise and justify a project design demonstrably appropriate to meet the research requirements.
• Apply relevant literature review, computer modelling, field and/or laboratory protocols relevant to obtaining data for the purposes of preparing an environmental research thesis.
• Present data and other outputs in a clear manner with determination and reporting of quality parameters and application of appropriate and justified statistical tests.
• Appraise data sets, assessing their quality.