Driving down the cost of direct air capture with intelligent policy design and technology deployment

Abstract

Direct air capture and storage (DACS) is a technology that can provide vital negative emissions in pursuing the net-zero target and a net-negative future. However, huge uncertainties remain over the cost of DACS today and how we can drive down the cost of DACS in the future. In this study, we aim to help clarify these issues by calculating the cost of a first-of-a-kind DACS plant across four DACS technologies. Here, we apply contingencies and cost-adders for a first-of-a-kind plant that are often neglected in academic techno-economic studies. Then we show how we can reduce the future cost of DACS through technological learning, siting, and smart policy selection. We show that the cost of DACS may be thousands of dollars per tonne of CO2 today, but in the future, this can come down to somewhere between $80-600 per tonne of CO2. Intelligent siting and selection of energy sources have the potential to save up to a few thousand dollars per tonne of CO2. Finally, we analyse policies that can create a market for carbon removal, accelerate technology scale-up, and reduce long-term costs. We hope policymakers and academics can use these results to design pathways to enable this potential new industry and limit the planet's warming to 1.5°C.

Keywords: Direct air capture; carbon dioxide removal; negative emission technologies; techno-economics; policy; learning curves; technological learning; regional analysis