Description:
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 organized in three modules (main teacher in parenthesis). The course includes a mix of online and physical lectures. Part of each module is delivered using a flipped-classroom approach and pre-recorded videos that are provided to the students in advance. The physical lectures instead focus on hands-on exercises targeted to the completion of a portfolio and in discussion as well as Q&A rounds.

Module 1. 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, consumptions 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-analyses via hybrid LCA, tiered and embedded. The module includes exercises.

Prices:

Attendee / Price*
PhD students affiliated to a Danish University / Free
PhD students not affiliated to a Danish University / 4.500 DKK (600 EUR)
Academics (e.g. postdoc and professors) / 9.000 DKK (1.200 EUR)
Professionals (consultancy, industry, etc.) / 18.000 DKK (2.400 EUR)
*Prices do not cover meals or accommodation

Organizer:
The 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

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

Registration and info:
Please apply via mail to the course organizer Massimo Pizzol (massimo@plan.aau.dk). 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 of PhD topic / your experience with LCA.

ECTS: 5.0

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

Activity

Hours

ECTS

Lectures and group work in class

50

1.8

Readings

35

1.3

Group work prior to course

20

0.7

Group work after course

35

1.3

Total

140

5.0

*One ECTS credit is equivalent to 28 hours of work

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 and videos.

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 products 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 student will thus get the info on five different cases. Students should be able to organize themselves using online tools (skype, dropbox etc) to collaborate in group remotely prior and after the course.

Time: The equivalent of 6 full-days distributed between weeks 19-22

Place: TBA

Number of seats: 25

Deadline: 15 March 2022

Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year.
We look forward to your registrations.