Course content

The course is taugt 1 week intensively in the late summer.

This is an advanced course addressing the use of programmatic approaches to improve the workflows, methods, and possibilities of environmental systems analyses. The course introduces and gives practical examples of the state-of-the-art and scientific debates connected to life cycle assessment.

The core of the course is an introduction to python-based programming and the Brightway open source framework. The course will introduce the basics of Brightway, such as the data ontology, data storage and format, importing external data, calculation possibilities, and interpretation of results. Advanced topics will also be discussed, such as the consumption of dynamic data, uncertainty analysis and global sensitivity, dealing with classical LCA problems (multifunctionality, allocation), as well as regionalization aspects. In addition to the introduction to this cutting-edge research platform, students will carry out their own projects by conducting and interpreting LCAs, using real-world case studies from industry and public policy.

Learning outcome

After having completed the course, the students should

1. have acquired Python coding knowledge for environmental systems analyses

2. understand the structure and functionality of the Brightway framework

3. be able to conduct LCA studies through Brightway

Learning methods and activities

The course will be taught as an intensive 1-week session, involving both lectures and exercises (both group exercises and individual ones). The exercises are all conducted on the students’ own computers. There is an extensive set of preparatory tasks (both literature and practical knowledge), and students are required to complete these tasks before the session.

There will be two online sessions prior to the intensive week to ensure students have installed Brightway correctly.

The course is planned to take place every 2 years. Next time in summer 2026.

Further on evaluation

To pass the course a score of at least 70 percent is required

Recommended previous knowledge

Life Cycle Assessment, Python coding

Required previous knowledge

Basics of LCA, e.g. through TEP4223

Basic Python programming

Course materials

Brightway software (download: https://brightway.dev/ ), and reading materials & tasks (introduction to Python and Brightway specific) that are distributed before the intensive week.