Using Big Data Simulation Models for Real-world Scenarios for CO2 Removal
We discuss the use of large-scale simulation and optimisation models to predict how ERW could be deployed and scaled in practical, real-world contexts.
In this episode, Professor David Beerling is joined by Dr Euripides Kantzas to explore how big data, simulation and optimisation modelling are used to understand how Enhanced Rock Weathering (ERW) could be deployed at scale with agriculture for carbon dioxide removal.
They discuss how combining data from field trials, crop systems, transport networks, geological resources and climate datasets enables researchers to simulate real-world deployment scenarios and assess where ERW could deliver the greatest climate benefits.
The conversation also explores the challenges of scaling carbon dioxide removal technologies, including practical, environmental and economic considerations, and how modelling helps inform these trade-offs.
Together, they reflect on how advances in computational modelling are helping to transform ERW from a promising scientific concept into a credible, scalable climate mitigation strategy.
Credits
- Podcast Host: Professor David Beerling (Director of The Leverhulme Centre for Climate Change Mitigation at the University of Sheffield)
- Podcast Guest: Dr Euripides Kantzas (Researcher, The Leverhulme Centre for Climate Change Mitigation at the University of Sheffield)
- Podcast Production: Victoria Giordano-Bibby (Marketing and Communications Manager, The Leverhulme Centre for Climate Change Mitigation at the University of Sheffield)
- This work was funded by The Leverhulme Trust (Leverhulme Research Centre grant RC-2015-029)
