Global limits on CO2 geological storage deployment using a coupled industry growth - pressure constrained model
Year: 2026
Type: preprint
Abstract: Geological storage of CO2 at scale is critical to meeting climate objectives, yet deployment targets often rely on top-down climate pathways that overlook the coupled constraints of subsurface pressure buildup and realistic industry drilling rates. Here we map global limits on CO2 storage deployment using CO2LOGIX 2.0, an improved model coupling subsurface pressure evolution with country-level deployment trajectories. We model nine scenarios, varying which countries participate and how quickly they scale, informed by volumes stored to date, historical drilling rates, project pipelines and storage readiness indicators. We find near-term global injection rates are significantly lower than previous estimates, reaching 2.71 GtCO2yr-1 by 2050 and peaking at 56.45 GtCO2yr-1 under central assumptions. Halving growth rates and extending start-up delays reduces the 2050 and peak rates to 0.35 and 32.7 GtCO2yr-1; increasing growth rates by half and shortening delays gives 16.6 and 70.7 GtCO2yr-1. Near-term expansion is driven by early adopters such as the USA and Brazil, while later expansion concentrates in China, Saudi Arabia, India and Southeast Asia. Cumulative storage by 2100 exceeds almost all 1.5 °C mitigation pathways, but near to mid-term projections appear overestimated – a mismatch that persists across every modelled scenario. Greater volumes could be achieved by targeting countries whose potential remains untapped even under the most aggressive scale-up assumptions, concentrated in sub-Saharan Africa, the Middle East and South America. This is the first study to constrain global injection rates with a coupled industry growth-pressure model, offering an adaptable framework for evaluating CO2 geological storage deployment.
DOI: 10.31223/x5zr46
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: green
OpenAlex ID: W7204837881