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 aims at strengthening skills in life cycle inventory analysis. The course targets the development of advanced competences in LCA by applying the problem based-learning (PBL) teaching 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 target audience of the 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. The course content is organised in three modules (main teacher in parenthesis).

Module 1 (online). Intro to advanced LCA 
In this hands-on module students will learn how to use the software Brightway2 for LCA research. Topics covered: Computational structure of LCA. Computer simulation and statistical approaches for uncertainty and sensitivity analysis in LCA. LCA reproducibility and data sharing. The module includes exercises.

Module 2. Consequential LCA
Students 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. Communicating consequential models. The module includes exercises.

Module 3. Input output LCA
Students 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. The module includes exercises.

Form and academic recognition:

When including readings and group work assignments, the total course workload corresponds to 5 ECTS (One ECTS credit is equivalent to 28 hours of work).

The five ECTS credits of the course are divided roughly in this way:

ActivityHoursECTS
Lectures and group work in class501.8
Readings351.3
Group work prior to course200.7
Group work after course351.3
Total1405.0

This course is organised yearly 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 and takes place at Aalborg University.

Learning outcomes and teaching methods:

Activities: Includes attending to the lectures and performing exercises in class.

Readings: Approx. 100 pages of scientific articles and reports, that are provided to the students, plus python tutorials.

Group work: students 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.

EXAMPLE, a group works on an LCA of a product and does:

  • 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: organise the material and prepare a portfolio/article where all the techniques are presented for the case study.

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