MCA: Incorporating Stream Biogeochemistry into Carbon Assessment of Enhanced Rock Weathering: A Machine Learning and Dynamic River Network Modelling Approach

University Of Washington, Seattle WA

Investigators

Abstract

Enhanced rock weathering (ERW) within agricultural fields is a promising carbon dioxide removal approach. It already has commercial investment and pilot-scale deployment. Weathering occurs when silicate or carbonate rocks are crushed and spread on fields where the rock reacts with carbon dioxide and water to generate a dissolved form of inorganic carbon called bicarbonate. Successful carbon dioxide removal requires generated bicarbonate to travel from agricultural fields through rivers into the ocean. Once in the ocean, bicarbonate will stay dissolved in water and out of the atmosphere for a period of >100,000 years. However, in rivers, on the way to the ocean, it is possible for bicarbonate to convert back to carbon dioxide and to re-enter the atmosphere. Currently, the ERW community has overlooked the ability of biological processes in rivers to convert bicarbonate back to carbon dioxide. Quantification and consideration of biological processes in rivers is needed to correctly estimate the amount of carbon dioxide removed via ERW. This information will help ensure that carbon emitted with the technology does not exceed the amount sequestered. This mid-career advancement project will create protected time and establish resources needed to add biological processes into a leading model that tracks transport and reaction of carbon in rivers. Adding biological processes into this model holds potential to substantially alter the carbon balance and carbon credits that can be sold for ERW deployments. This project will add photosynthesis and respiration of aquatic plants and algae into the Dynamic River Network model. The model incorporates machine learning techniques to predict key water quality parameters and implements numerical carbon tracking to simulate changes in river chemistry and carbon degassing following ERW. With photosynthesis and respiration added, it will be possible to identify river conditions that promote biological uptake and subsequent release of ERW-derived carbon back to the atmosphere. It is hypothesized that rivers with high light availability, intermediate flow stability, and ample nutrients promote biological processing and release of ERW-derived carbon. Results will help to identify rivers and watersheds that promote carbon dioxide removal by ERW versus promote carbon loss, and to determine if it is possible to manage rivers and watersheds in a way that maximizes carbon dioxide removal by ERW. The modified model will be open source and thus available to directly inform ERW deployments. This award is co-funded by the Hydrologic Sciences and Geobiology & Low-temperature Geochemistry programs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.