Single-Course English 5 ECTS

Advanced life cycle assessment methods

Overall Course Objectives

Building on the students´ fundamental knowledge and skills in life cycle assessment, the course objective is to enable students to solve complex problems using three advanced life cycle assessment methods: prospective life cycle inventory modelling, environmentally extended input-output analysis and absolute environmental sustainability assessment.

The course intends to broaden the students´ capacities in life cycle assessment preparing them for real-world applications in a career in life cycle-based sustainability assessment and related fields in industry or academia.

Learning Objectives

  • Evaluate the environmental impacts of complex systems using advanced life cycle assessment methods integrated in specialized software tools
  • Explain how generic and current process life cycle data can be transformed to represent future changes in technology.
  • Predict the environmental impacts of future systems by modelling prospective life cycle inventories for domain-specific cases involving the quantification of learning and scaling effects for foreground and background processes.
  • Explain how an environmentally extended input-output model can be created.
  • Estimate the environmental impacts of large-scale systems using environmentally extended input-output analysis.
  • Describe the main components of an absolute environmental sustainability assessment.
  • Perform absolute environmental sustainability assessment of systems at different scales.
  • Discuss and interpret results from the applications of the advanced life cycle assessment methods, considering assessment context, uncertainties and other limitations.

Course Content

The course covers three main parts: prospective life cycle inventory modelling, environmentally extended input-output analysis and absolute environmental sustainability assessment. The students will be introduced to the theory behind these advanced methods and will apply the methods to solve specific problems using software, such as SimaPro, Python and MATLAB. The students will also learn to critically reflect on the limitations of using advanced assessment results for decision-support, considering the application context and uncertainties.

Recommended prerequisites

12772, Or other equivalent LCA course. Experience working with Python and rudimentary knowledge of MATLAB

Teaching Method

Lectures and exercises

Limited number of seats

Minimum: 15.

Please be aware that this course will only be held if the required minimum number of participants is met. You will be informed 8 days before the start of the course, whether the course will be held.

See course in the course database.

Registration

Language

English

Duration

13 weeks

Institute

Sustain

Place

DTU Lyngby Campus

Course code 12773
Course type Candidate
Semester start Week 5
Semester end Week 19
Days Tues 8-12
Price

7.500,00 DKK

Please note that this course has participants limitation. Read more

Registration