Impact of direct air capture process flexibility and response to ambient conditions in net-zero transition of the power grid

Erick O. Arwa and Kristen R. Schell

Applied Energy, 2025, vol. 386, issue C, No S030626192500279X

Abstract: Recent studies show that the cost of transitioning the power grid to a net-zero system could be reduced with the integration of direct air capture (DAC) of carbon dioxide as part of the portfolio of technologies. However, existing capacity expansion studies that model DAC assume that it has a constant capture rate, ignoring the ambient environmental conditions that are known to affect the DAC capture rate as well as geographical location. Furthermore, there are currently no studies that endogenously model DAC flexibility, especially the value of load-shifting in such a large-scale industrial process in capacity expansion optimization. This study develops a capacity expansion optimization model that integrates more realistic data on DAC’s response to ambient environmental conditions as well as DAC process flexibility. Results show that ignoring the impact of ambient environmental conditions leads to underestimation of the required cost, DAC capacity and renewable energy capacity to meet the net-zero goal. It is shown that when DAC capture rate data that has been computed as a function of ambient conditions is used, about 22.2%, 2.5% and 1.9% more DAC, wind and solar capacity, respectively, is required to meet net-zero requirements, relative to the often assumed 90% capture rate. Moreover, increasing the operational flexibility of DAC using material storage in silos was found to lower the cost of generation capacity expansion by lowering the DAC and renewable energy capacity needed to meet the net-zero target. These findings will be useful in improving the accuracy of net-zero transition plans that are focused on climate change mitigation.

Keywords: Direct air capture; Renewable energy; Generation capacity expansion; Load shifting; Negative emission technologies; Industrial decarbonization; Mixed-integer linear program (MILP) (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2025.125549

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