Characterizing the effects of policy instruments on cost and deployment trajectories of Direct Air Capture in the U.S. energy system

Capturing and sequestering carbon dioxide (CO2) from the atmosphere via large-scale direct air capture (DAC) deployment is critical for achieving net-zero emissions. Large-scale DAC deployment, though, will require significant cost reductions in part through policy and investment support. This study evaluates the impact of policy interventions on DAC cost reduction trajectories by integrating energy system optimization, learning curve, and policy instrument models. We examine how three policy instruments - incremental deployment, accelerated deployment, and R&D-driven innovation - impact DAC learning investment, which is the total investment required until the technology achieves cost parity with conventional alternatives or a target cost.