Aquatic Environmental Analysis

5 credits

Syllabus, Bachelor's level, 1TV021

A revised version of the syllabus is available.
Code
1TV021
Education cycle
First cycle
Main field(s) of study and in-depth level
Biology G1F, Earth Science G1F, Technology G1F
Grading system
Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
Finalised by
The Faculty Board of Science and Technology, 18 March 2008
Responsible department
Department of Earth Sciences

Entry requirements

Biology, Ecology for engineers and Probability and Statistics.

Learning outcomes

After completion of the course the student should be able to:

- Apply an effect-load-sensitivity analysis to study effects from environmental problems in aquatic ecosystems

- Account for the most important environmental problems that affect society and aquatic ecosystems in Sweden and its immediate vicinity

- Rank these problems quantitatively

- Analyse environmental problems with a large areal distribution by means of geographical information systems

- Master basic principles for modelling expected results from measures against problems in the aquatic environment

Content

The part WATER POLLUTION treats the major chemical threats to mainly aquatic ecosystems, i. e., acidification (of mainly lakes, rivers and ground water), eutrophication (of mainly lakes and coastal areas) and toxic contamination (of metals, radionucleis and organic pollutants in mainly lakes, rivers and coastal areas). A system to rank chemical threats is also treated, as well as basic elements of ecosystem effect-load-senitivity analysis. The theoretical part of ECOSYSTEM MODELLING

focuses on basic structural components to mathematically describe the processes regulation spread, biouptake and effects of environmental toxins in ecosystems. The course focuses on basic principles for statistical/empirical models of environmental data (regression, transformations, etc.), basic different components of dynamical (i.e., time-dependent) models for environmental pollutants, and different methods to develop "mixed" statistical and dynamical models. An important aim of the course is to give insights into building and testing of predictive ecosystem models.

Instruction

Lectures and exercises.

Assessment

Written examination is held at the end of the course. Grading is on the scale 3, 4 or 5. A student who fails the examination can be examined again either at the beginning of the autumn or the spring term.

FOLLOW UPPSALA UNIVERSITY ON

facebook
instagram
twitter
youtube
linkedin