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 (Massimo Pizzol)
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 (Bo Weidema)
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 (Jannick Schmidt).
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:

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

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.

The practicalities

When and where?:

Module 1: Online on 11, 18, 25 May and 1 June (four consecutive Tuesday mornings) – Online via Zoom platform
Modules 2-3: Physically on 7-10 June 2021 (four days in weeks 23) – Aalborg University, Rendsburggade 14, 9000 Aalborg (DK)

COVID note: We intend to run modules 2-3 physically at Aalborg University. However, in case of COVID restrictions we reserve the option to run these modules entirely online. We will refund expenses if a participant is prevented from joining physically due to travel restrictions but not if a participant doesn’t want to take the course online because the physical version is preferred. There will be no refund for participants who decide to withdraw from the course later than two weeks prior to the course start, no matter the reason.

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

Participant prerequisites:

The course requires basic knowledge of Life Cycle Assessment, i.e. the knowledge of the tool that one might get at bachelor or master level. This means that the students need to have either a strong theoretical understanding of LCA or practical experience (having done some LCA studies before, even if simple). We don’t teach the basics, and select the students based on their prior experience to make an homogeneous group and ensure a high starting level. In this way we can teach more advanced topics that are fit for a PhD level course.

Furthermore students should be able to organise themselves using online tools (skype, dropbox etc) to collaborate in groups remotely prior and after the course.

Teaching staff:

Bo Weidema, Professor
Jannick Schmidt, Associate Professor
Massimo Pizzol, Associate professor
Søren Løkke, Associate professor
Agneta Ghose, Postdoc

Price and course conditions:

18.000 DKK (2400 EUR) – for professionals (consultancy, industry)
9.000 DKK (1200 EUR) – for university personnel (postdocs, professors)
4.500 DKK (600 EUR) – for PhD students not affiliated to a Danish University
Free – PhD students affiliated to a Danish University
Prices do not include travel, accommodation and meals

Contact person and registration:

Please apply via mail to the course organiser Massimo Pizzol ( You must provide the following information in the email: Full name / Profession (PhD student, postdoc, consultant…) / Institution name / Address / email address / Phone nr / your research field or Phd topic / your experience with LCA

Registration deadline:
15 March 2021