Advanced LCA – Consequential and IO‑based life cycle assessment

This course aims at strengthening skills in life cycle inventory analysis. The course introduces advanced inventory modelling using the techniques of consequential LCA and input-output (IO) LCA.

The course

Subject and programme:

The course targets the development of advanced competences in LCA by applying the problem based-learning (PBL) teaching method. Following the PBL model that focuses on learning by doing and reflection, the course activities will include intensive group work, problem defining and solving applied to real-word cases, practical exercises, and discussion sessions or workshops. The course content is organized in three modules (main teacher in parenthesis).

Module 1. Intro to advanced LCA. In this hands-on module participants will learn how to use the software Brightway2 that is specific for LCA research. Topics covered: Computational structure of LCA. Uncertainty analysis with stochastic error propagation (Monte Carlo) and statistical testing of LCA results. LCA reproducibility and data sharing. The module includes exercises.

Module 2. Consequential LCA. Participants will learn the fundamentals of Consequential LCA. Topics covered: Introduction to attributional and consequential models. Algorithms for performing consequential LCA in the definition of functional unit, consumption mix, and identification of determining and dependent co-products. Modelling of indirect Land Use Changes (iLUC). Communicating consequential models. The module includes
exercises.

Module 3. Input output LCA. Participants will learn the fundamentals of Input- Output modelling. Topics covered: supply-use tables, multi-regional models and trade linking. Integrating process LCA and IO-analysis via hybrid LCA, tiered and embedded. Expanding the IO-matrix to include the natural, social and economic environment. The module includes exercises.

Form and academic recognition:

When including readings and group work assignments, the total course workload corresponds to 5 ECTS (1 ETCS = 27,5 hours of work for the student).

Learning outcomes:

Activities include attending to the lectures and performing exercises in class. Readings include approx. 100 pages of scientific articles and reports, that are provided to the students. Participants work in groups (max 5 people), each group will work on a case study and apply the knowledge of the course on the case study.

A group might:

  • prior to the course: choice of product and data mining, getting base knowledge and data to describe the product system.
  • during the course (exercises in class): consequential inventory with matrix format, IO LCA inventory, inclusion of iLUC, inclusion of social impacts, etc.
  • after the course: organize the material and prepare a portfolio/article where all the techniques are presented for the case study.

Eventually, all portfolios are made available. Each participant will thus get the info on five different cases.

The practicalities

When and where?:

The course normally takes place every year in May at Aalborg University*, Rendsburggade 14, 9000 Aalborg (DK) – and new ‘editions are announced here at the ILCA homepage.

*This course is organized by The Technical Doctoral School of IT and Design, Aalborg University and Danish Centre for Environmental Assessment (DCEA) www.DCEA.dk, in collaboration with the International Life Cycle Academy (ILCA) www.ILCA.es

Participant prerequisites

The target audience of this course is academics (PhDs, postdoc, other) or professionals who already have basic experience with LCA and intend to bring their LCA competences to an advanced level. Basic experience means for example having carried out simple LCAs before or having elementary knowledge of LCA theory. Participants should be able to organize themselves using online tools (skype, dropbox etc) to collaborate in group remotely prior and after the course.