Earth-System Digital Twins for Verifiable Gigaton-Scale Carbon Removal through Enhanced Weathering

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a comprehensive digital-twin architecture for CDR verification, useful for advancing carbon accounting and MRV research.

🏢実務担当者:Offers a framework for developing auditable MRV systems for enhanced weathering projects, relevant for carbon credit developers and sustainability teams.

🏛政策担当者:Highlights the need for standardized verification protocols for CDR, informing policy on carbon markets and climate targets.

Abstract Gigaton-scale carbon dioxide removal will be required alongside rapid emissions reduction, yet enhanced rock weathering remains difficult to verify because carbon moves through heterogeneous soils, groundwater, rivers and oceans while operational emissions and environmental effects occur across the supply chain. This paper develops an Earth-system digital-twin framework for persistent, uncertainty-aware verification of enhanced weathering from feedstock production to durable storage. The study adopts a design-science methodology that integrates process-based geochemistry, agricultural and hydrological modelling, multisource observation, Bayesian data assimilation, life-cycle assessment and auditable monitoring, reporting and verification. The proposed twin is organized across plot, catchment, regional and global scales. It assimilates mineralogical passports, soil mass balances, pore-water alkalinity, isotopic tracers, sensor streams, remote sensing, logistics data and downstream carbon measurements. A cradle-to-grave accounting model distinguishes gross mineral reaction from net atmospheric removal by deducting non-carbonic-acid weathering, secondary mineral formation, riverine carbon loss and life-cycle emissions. The paper specifies testable propositions, a scenario matrix, validation criteria and adaptive-sampling logic rather than inventing numerical results. The framework is expected to improve source attribution, quantify uncertainty, reveal time lags, optimize monitoring expenditure and impose environmental and equity safeguards before deployment expands. Its principal contribution is to recast enhanced-weathering assessment as continuous Earth-system inference rather than periodic project accounting. The architecture offers a research pathway for transforming modelled removal potential into conservative, reproducible and independently auditable evidence suitable for scientific assessment, public policy and high-integrity carbon markets. Keywords: adaptive sampling; Bayesian data assimilation; carbon dioxide removal; carbon accounting; digital twin; enhanced rock weathering; Earth-system modelling; environmental safeguards; life-cycle assessment; monitoring, reporting and verification; multiproxy geochemistry; uncertainty quantification

• semanticscholar https://doi.org/10.62311/nesx/rp8jy-30072026first seen 2026-08-09 05:29:23