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.
- Teacher: Agneta Ghose
- Teacher: Søren Løkke
- Teacher: Massimo Pizzol
- Teacher: Jannick Schmidt
- Teacher: Bo Weidema