Course content

This is an advanced course addressing life-cycle assessment, input-output analysis and the assessment of environmental consequences, with a focus on the former. The course introduces the state-of-the-art and scientific debates connected to both inventory modeling and impact assessment. The core of the course addresses the modeling of product systems and larger production-consumption networks. The course addresses recent advances related to the adaptation of input-output techniques and data for LCA. Allocation issues, attributional and consequential LCA, and the treatment of recycling will be discussed. The impact assessment with impact-category and damage-oriented approaches are reviewed using the new RECIPE method as an example. In addition to the presentation of an up-to-date overview of the LCA methodology, it will be discussed how to use LCA to illuminate critical issues relevant for environmental and technology policy. The planning and interpretation of LCA results will be highlighted using real-world case studies from industry and public policy.

Learning outcome

The aim is to improve the student's understanding of the methods of life cycle assessment and their ability to use these methods in their own research. The course aims to improve the general method competence and the ability to judge different research approaches and methods. Mathematical skills and software knowledge required to conduce environmental systems analysis are not focused on, and it is assumed that the student has the necessary technical-mathematical competence.

Learning methods and activities

The course will be taught as an intensive 2-week session in August, involving both lectures and exercises. The exercises are mostly in the computer lab and utilize the MatLab programming environment. There is an extensive reading list, and students are required to complete the reading before the session. This course is produced in collaboration with other universities in Europe and allows for networking among PhD students.

Compulsory assignments

• Exercises

Recommended previous knowledge

Life-cycle assessment, understanding of industrial ecology methods and topics; Linear algebra, basic understanding of programming. Some knowledge of MatLab is of advantage.

Required previous knowledge

Admission to the PhD Program

Course materials

Collection of articles