About
Experimental research increasingly relies on computing to analyze data, model systems, and apply AI, expanding its role across all scientific disciplines. This shift has driven a surge in demand for computational power, alongside higher energy use and material consumption, compounding the already significant environmental footprint of experimental research.
To address this, a student-driven course was developed to assess research-related environmental impacts. Collaborating with a scientific computing team, students analyzed internal infrastructure and external computing use, including AI tools, to estimate carbon and material footprints and compare them with other research activities.
Results show computing is widespread but unevenly used: most researchers consume about 1,000 CPU hours annually, while a small group accounts for over 20% of total energy use. The computing footprint stems mainly from equipment production (57%), followed by services (25%) and storage (12%).
00:00:00 Slide 1
00:00:25 Slide 2
00:00:54 Slide 3
00:01:11 Slide 4
00:01:42 Slide 5
00:02:01 Slide 6
00:02:14 Slide 7
00:02:47 Slide 8
00:03:04 Slide 9
The talk
Credits and licence
- Institution
- CERN
- Speaker
- Jeroen Dobbelaere
- Year
- 2026
- Language
- English
- Subjects
- Mathematics
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed