The project, which builds on a decade of expertise at the Leverhulme Centre for Climate Change Mitigation (LC3M), aims to move beyond expensive, manual soil testing to provide a more transparent and cost-effective digital understanding of carbon capture.
For the global climate effort, meeting net-zero goals requires more than emissions reductions alone. The United Nations IPCC has highlighted the need for a portfolio of carbon dioxide removal (CDR) solutions. The aim is to remove billions of tonnes of CO2 from the atmosphere annually with Enhanced Weathering - the process of spreading crushed rock on farmland - being key to this strategy. However, current standard monitoring approaches are too complex and costly for commercial use, leaving the technology struggling to reach the scale required to make a significant impact.
Funded by the Leverhulme Trust and led by Professor David Beerling, the team will now move to the implementation of an open-source, AI-driven monitoring, reporting, and verification (MRV) framework. Co-produced with Noah Planavsky at Yale and Chris Reinhard at Georgia Institute of Technology, this digital toolkit is designed to bridge the data gap by capturing the geochemical changes that signify permanent carbon storage.
Professor David Beerling (University of Sheffield), project lead, said, “Building on the work of our world-class Leverhulme Centre for Climate Change Mitigation in Sheffield, this project will advance the use of state-of-the-art numerical models integrated with ‘big data’ and AI to allow carbon dioxide removal by enhanced weathering to scale cost-effectively”
The team plans to integrate global field data into AI models, to accurately predict how much carbon is being removed during enhanced weathering deployments. The end goal is to replace the need for costly soil tests while providing more accurate estimates of carbon removal rates. Hybrid modeling efforts–jointly mechanistic and AI driven modeling approaches are transforming a range of fields. This effort will build on advances to develop a robust and practical solution for tracking carbon removals.
Early findings suggest that this data-led approach can provide a vital tool for the agricultural sector - not only removing carbon but also providing the evidence needed to rehabilitate acidified soils and increase crop yields. By comparing data from diverse farming systems across both sides of the Atlantic, the researchers will determine how to optimise rock application for different climates, ensuring interventions are precisely targeted.
The aim is that this digital framework will eventually be adopted as a standard for enhanced weathering, shifting the culture of carbon removal from high-cost empirical measurements to a transparent, global necessity.