Focused on understanding the strengths, limitations, and potential pitfalls of Life Cycle Assessment methods, this course provides state-of-the-art insights in both inventory modelling and impact assessment.

This course focuses on understanding the strengths, limitations, and potential pitfalls of Life Cycle Assessment (LCA) methods. The course provides state-of-the-art insights in both inventory modelling and impact assessment. The core of the course addresses the modelling of product systems and larger production-consumption networks. For the inventory modelling, it includes recent advances related to the adaptation of input-output techniques and data, allocation issues, attributional and consequential LCA, and the treatment of recycling.

The impact assessment covers new insights in impact category and damage-oriented approaches. At least one impact category is investigated in depth. The importance of spatial differentiation in a number of impact categories is discussed by using the spatially differentiated, global impact assessment method LC-IMPACT as an example. Finally, dealing with different types of uncertainties in LCA modelling is part of the course.

Education forms used are in the form of lectures and working group assignments, where you will model inventory and impact assessment processes with, a.o. matlab and excel on your own laptop. This will be done with the guidance of the experienced course lecturers.

Before the start of the course you are asked to prepare and read through the material. You are asked to fill out a questionnaire and a simple modelling exercise to have a head start during the scheduled course weeks. Finally, you are asked to write a reflection afterwards.

Learning Outcomes

After this course you are able to:

1. Compile life cycle inventory matrix calculations
2. Understand the scientific background for life cycle inventory and impact assessment models
3. Execute complex life cycle impact assessment calculations and interpret their outcomes

Level of participant

• PhD
• Post-doc
• Professional

For whom is the course designed

Everyone who is qualified for a doctoral programme can apply, which means that you must have completed a master degree.

Admission Requirements

A basic knowledge of university-level mathematics/statistics

Admission Documents

• Motivation letter
• CV

Date

Monday 6 – Friday 17 August 2018 (two weeks)

Course Leader

Dr. Rosalie van Zelm
Assistant Professor
Environmental Science
Radboud University

Course Fee

€1030
The fee includes the registration fees, course materials, access to library and IT facilities, coffee/tea, lunch, and a number of social activities.

Number of ECTS credits

7,5 EC

Register here