Tackling climate change will require a rapid transition to a net-zero economy. There remains considerable uncertainty about the best path by which to achieve this transformational goal. Integrated assessment models (IAMs) have been used to explore the diversity of decarbonisation pathways and provide evidence on their relative strengths and weaknesses. A consistent message from IAM modelling has been the value of large-scale deployment of carbon capture and storage (CCS) and carbon dioxide removal (CDR). IAMs have represented these interrelated decarbonisation options as critical to least-cost decarbonisation. At the
same time, low-carbon scenarios produced by IAMs have been heavily criticised, in part due to their reliance on CCS and CDR. There is a nexus between widespread scepticism about CCS and CDR, and criticism of the models which foreground them as key solutions.
This thesis situates itself in this nexus. It conducts a model-based investigation and critique of the representation of CCS and CDR in IAMs. Using a detailed-process IAM, it explores how the predominant representation of CCS and CDR can be challenged, and therefore how the narrative that IAMs provide about CCS and CDR can be transformed.
The thesis conducts a first-of-a-kind analysis into how the value of CCS is eroded by cost reductions in wind and solar photovoltaics. It finds that the role of CCS in IAMs may have been overestimated due to pessimistic assumptions around renewables costs and the use of high discount rates. Accounting for competition from alternative technologies is essential to accurately representing CCS in IAMs. The thesis also critiques the representation of CO2 storage as globally ubiquitous and low-cost. It argues that due to the central importance of CO2 injection rates, and the contractual, financial and institutional barriers to appraising geological reservoirs, storage may in fact be a scarce resource. The thesis explores the implications of limited CO2 storage for decarbonisation pathways, including the concept of a merit order for CCS applications and the potential role of inter-regional trade in captured CO2.
The thesis then critiques the representation of CDR in IAMs. It conducts an in-depth
investigation into the concept of mitigation deterrence in low-carbon scenarios, where the anticipated availability of CDR deters or delays actions to reduce emissions. It provides a systematic and model-based quantification of the risks of mitigation deterrence. Continual mitigation deterrence coupled with CDR deployment failure could lead to temperature overshoot of 0.3 °C by the end of the century. It also explores how CDR could contribute to decarbonisation pathways as additional to, rather than a substitute for, mitigation. Building on these results, the thesis assesses the implications of uncertainty in CDR availability for near-
term climate policy. It uses stochastic optimisation to demonstrate that uncertainty in CDR availability provides a strong rationale to substantially increase near-term mitigation rates and hedge against the potential of limited CDR deployment. While CDR will be critical to achieving the Paris Agreement goals, it cannot serve as a substitute for ambitious emissions reductions. This critique of the representation of CCS and CDR in IAMs provides a range of insights into how the narrative that IAMs provide could be challenged and therefore transformed. Additional insights are also provided around best practice in the production and communication of IAM scenarios. The results can help improve our understanding of the appropriate role for these contested and controversial strategies and models in achieving the goals of the Paris Agreement.