Global geologic carbon storage requirements of climate change mitigation scenarios

Abstract:

Carbon capture and storage (CCS) has been identified as an important technology for limiting climate change in integrated assessment models. To achieve the climate targets outlined by the Intergovernmental Panel on Climate Change (IPCC) 2C climate targets, many scenarios require tens of gigatons of CO₂ stored per year by mid-century. These scenarios are often unconstrained by growth rates or historical data, and uncertainty in global geologic storage assessments limits storage resource-based constraints. Here we show how logistic growth models, a common tool in resource assessment, provide a mathematical framework to monitor short-term CCS deployment progress and long-term resource requirements in the context of climate change mitigation targets. Growth rate analysis, constrained by historic commercial CO₂ storage rates, indicates sufficient growth to achieve several of the 2100 storage targets identified by the Intergovernmental Panel on Climate Change. Specifically, the logistic growth model results indicate that the current growth rate trajectory of 8.6%, which is constrained by 20 years of commercial-scale CO₂ storage data, could lead to as much as 441 Gt of CO₂ stored by 2100. This would be sufficient to achieve many of the climate change mitigation trajectories with less than 2C of warming. These growth-based models significantly diverge from the integrated assessment model year-on-year trajectories. For example, deployment under the median IPCC scenario requiring an unprecedentedly high exponential growth of over 28% between 2020 and 2050. The identification of a maximum storage resource need of 2700 Gt is less than the highly uncertain estimates of the potential resource available, of 10,000 Gt or more. We will also present results that highlight the tradeoffs between storage rate, duration, and required storage resource. These results indicate that the 2700 GT ceiling decreases if CCS deployment rates are increased. These findings, and the associated modeling framework, are anticipated to provide a tool for policy makers, industrial developers, non-governmental organizations, and scientific institutions to monitor short term emission reductions and long-term resource needs for the deployment of large-scale carbon capture and storage.