Speaker
Description
The Leverhulme Centre for Climate Change Mitigation (LC3M) has been at the forefront of research into enhanced rock weathering (ERW) as a potential means of removing atmospheric CO2. Apart from laboratory studies and large-scale field trials, we undertake modelling studies aimed at assessing the feasibility, cost and CDR potential of ERW at national scales. These modelling efforts entail the use of a computationally intensive 1-D weathering model applied across a fine spatial grid, incorporating various climatic and economic drivers.
When addressing ERW on a national scales, numerous intricate factors come into play. These include the logistical challenges of transporting rock from its source to croplands, the variability in basalt minerology depending on its origin, and the demands on the electricity network required for rock grinding. Furthermore, the optimization routines we employ to determine the optimal pairings between rock sources and croplands, with the dual objectives of maximizing carbon capture and minimizing costs, present additional computational complexities. Finally, our research involves heavy-duty computing simulations to capture uncertainties associated with ERW and resulting CDR rates.
Here we will provide snippets into the technologies and methodologies we have developed to address these computational challenges. Our toolkit encompasses specialized optimization algorithms, Geographic Information Systems (GIS) to construct efficient transport networks, Life Cycle Analysis (LCA) to calculate the net Carbon Dioxide Removal (CDR), use of databases, and the utilization of machine learning techniques. We will also discuss our recent exploration of deep learning and its potential to enhance ERW modelling.
Through this presentation, we aim to illuminate the computational intricacies inherent in ERW modelling at a national scales and highlight the innovative solutions we have employed to surmount these challenges. Our research not only advances our understanding of ERW as a viable climate mitigation strategy but also contributes to the broader field of computational geoscience and climate modelling.
