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MSc Pollution & Environmental Control

Year of entry: 2022

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Course unit details:
Measuring and Predicting 1

Unit code EART60061
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 1
Offered by Department of Earth and Environmental Sciences
Available as a free choice unit? No

Overview

The unit begins with a brief consideration of epistemology to put the subsequent content into a framework that can be delivered as a progression from measurement to prediction.  The initial challenge is to make measurement meaningful.  This is met by both explanation of statistical significance and of some commonly used and important methods of sampling and analytical techniques for pollutants.  Prediction is required when direct measurement is not possible.  General techniques of prediction are taught progressing from those based on comparison of measurements to comparison of relationships to comparison to models.  The models developed are simple but the process and vocabulary of development is emphasised and each technique is developed using a pollution related case study.

Students will be trained in techniques and have concepts reinforced by participating in a one day field trip and a day long introduction to Departmental analytical facilities.

This course unit detail provides the framework for delivery in 20/21 and may be subject to change due to any additional Covid-19 impact.  Please see Blackboard / course unit related emails for any further updates.

Aims

To prepare students to carry out an independent research project by defining a general process for research and teaching general skills related to measuring and predicting pollutant mobility and transformation.

 

Learning outcomes

 

On the successful completion of the course, students will be able to:

ILO 1

Recognise generic processes of research and categorise research into different types

ILO 2

Make their measurements meaningful and recognise the quality of those made by others – quantification and propagation of error

ILO 3

Design a sampling strategy by applying understanding of variability

ILO 4

Select appropriate techniques for measurement and analysis of fluids and solids by applying knowledge of how instruments work

 

ILO 5

Apply a process of mathematical model development to understanding a simple environmental system

 

ILO 6

Evaluate whether arguments are logical in connecting objectives to aims.

 

Syllabus

 

3 hour weekly + 2 hour sessions every 2 weeks or when requested

1 day field trip to UK Peak District – measuring and predicting aquatic carbon fluxes

1 day introduction to the analytical facilities in DEES.

 

Classroom content

1. What is knowledge, what is measurement, what is prediction, what is research?

2. Making meaningful measurements

  1. be able to explain why standard deviation is the most commonly used measure of variability
    1. Be able to calculate confidence limits on measurements
    2. be able to propagate these confidence limits (errors) when using measurements in calculations
  2. Use these statistics as a simple model of the environmental process of dispersion
  3. Recognise general problems and some solutions in making environmental measurements
  4. Measurement techniques commonly used and important to pollutant mobility
  5. Analytical techniques commonly used and important to pollutant mobility

3. Predicting

  1. predict one variable from another
  2. calculate the confidence in the prediction and propagate this in further calculation
  3. use concepts of discretising continuous variables to model environmental processes
  4. identify general procedures in modelling
  5. construct and use a compartmental model
  6. construct and use a finite difference model

 

Teaching and learning methods

 

  • The initial sessions teach general processes and techniques of research and give a framework into which the subsequent sessions on more specifically pollution / environment related content can be integrated.  The final sessions present an opportunity to synthesise the prior learning in a case study using data from the field trip.
  • Each section uses lectures and practical exercises.  The exercises are largely done as guided on-line video, with drop-in class room sessions when requested.
  • In addition to these exercises there are a full day field trip and introduction to laboratory analytical facilities.
  • Formative assessment through on-line BB tests with immediate feedback is given each week.
  • Summative assessment is by a single on-line open book examination using questions in the same style as the formative tests and with immediate feedback.
  • Synthesis – group work to prepare presentations and subsequent peer-review (marked by staff)

Assessment methods

Assessment type

% Weighting within unit

Hand out and hand in dates

Length

 

How, when and what feedback is provided

ILO tested

Formative tests

Weekly

0

 

5 – 30mins

On-line immediate

All

On-line test

100

 

2 hours

On-line within 3 days

2, 3, 5

 

Feedback methods

 

 

Recommended reading

 

Any basic statistics book – statistics for environmental science, statistics for biologists, statistics for geography

www.explorable.com

Study hours

Scheduled activity hours
Lectures 50
Independent study hours
Independent study 100

Teaching staff

Staff member Role
Stephen Boult Unit coordinator

Additional notes

Other Scheduled teaching and learning activities:
1 day field trip
1 day analytical facilities introduction
 

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