RSS04.15 Technology and Sustainability modelling for net-zero industries

Energy-intensive industry is core to the European and global economy, being a substantive contributor to the GDPs of many developed and emerging economies and employing millions. Yet it is also a sector that is under immense pressure and needs to be transformed: It is responsible for around a third of global greenhouse gas emissions, while needing to be close to net-zero by 2050.

If Europe and the and the rest of the world are to meet their net-zero targets, a fast transition to a climate-neutral industry must take place. This is an interdisciplinary challenge par excellence, and the need for expertise to address it will only continue to grow. To be able to steer future innovations in a sustainable direction, quantitative prospective assessments are needed. Therefore, after an overview is given of new technologies, this course will provide a robust and in-depth understanding of economic and environmental assessment methods to address industrial innovations, such as carbon capture and utilization and carbon capture and storage technologies. This will take place over five days and will consist of in-depth lectures by modelling experts, and presentations by industry experts, as well as workgroup assignments in which participants will get hands - on modelling assignments and discussion questions.

By the end of the course, participants will be equipped with the necessary insight and expertise to understand and apply the multi-disciplinary approach, which is needed to effectively reduce emissions in industry.

The course is co-organized by Radboud University, Politecnico di Milano, and CO2 Value Europe, in the context of the Horizon 2020 INITIATE project.

Detailed program (pdf, 200 kB)


10 July 2023 - 14 July 2023
Course Fee

Regular: €400

Early Bird: €360 (application deadline* April 1st)

Scholarships and discounts Find more information here
Application deadline

May 1st

*Your application is only completed when the course fee has been paid

Course leader
Level of participant
  • Master
  • PhD
  • Postdoc
  • Professional
Admission requirements A basic knowledge of university-level mathematics/statistics and basic knowledge on energy systems are required, as well as an interest in modelling.
Admission documents
  • CV
Mode of Study On Campus
Location to be determined