A framework for modeling carbon loss from rivers following terrestrial enhanced weathering

Abstract Enhanced weathering (EW) has garnered increasing interest as a promising technique for durable carbon dioxide removal, with a range of potential co-benefits including increased soil pH and nutrient availability. However, the potential loss of initially captured CO 2 during river transport remains poorly constrained, undermining the use of this practice as a carbon mitigation strategy. Here, we present results from a first-of-its-kind dynamic river network (DRN) model designed to quantify the impact of EW on river carbonate chemistry in North American watersheds. We map key water quality parameters using machine learning and use a DRN model to simulate changes in carbon degassing during EW. Our model predicts low carbon loss (<5%) from river networks for many of the river pathways explored here, but significantly higher (>15%) carbon degassing is also observed, indicating that riverine carbon storage and the impacts of EW on river chemistry must be evaluated in a deployment-specific or regional context.