MSc Pollution & Environmental Control / Course details

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 virtual field trip and a day long introduction to Departmental analytical facilities.

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.

3 hour weekly 0.5 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

· 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 test using questions in the same style as the formative tests and with immediate feedback (taken after Week 12).

· Synthesis – group work to prepare presentations and subsequent peer-review (marked by staff)

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

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