Aims and objectives
To provide an overview of the techniques used for predicting impacts and collecting data for monitoring purposes in EIA.

Content
The series of lectures deals with the main facets of the environment which are generally considered in EIA. These are grouped into a series of media-related or impact-related topics. The initial series of lectures is concerned with a general overview of data collection, storage and analysis within the context of EIA. This is followed by a consideration of predicting the impact of development on air quality, water quality, traffic and transport, noise, visual and landscape resources and ecological resources.

External seminars are given on a weekly basis and their contributions are an integral part of the lecture component of this course. Two case studies will be presented, looking at a range of computer-based prediction models.

For the purposes of continuous assessment, students will be required to prepare a critical appraisal of key issues presented by external speakers in their presentations with respect to the objectives of environmental management, not to exceed 3,000 words.

Learning outcomes
On completion of the course students should understand the role of data collection and analysis in EIA. They should also be aware of the strengths and weaknesses associated with a range of data collection, storage and analysis techniques frequently employed in impact assessment and be able to identify i) the informational needs of an EIA, ii) the most appropriate technique to employ, and iii) the required precision for prediction and monitoring.