Improving adsorption-based direct air capture performance through operating parameter optimization

Abstract

Direct air capture (DAC) of CO2 through adsorption is a promising technology for mitigating climate change, but its high cost presents a significant challenge to large-scale implementation. To address this issue, this study presents a dynamic fixed-bed model of the closed-inlet temperature-vacuum swing adsorption (TVSA) process and investigates the impact of various operating and model parameters on DAC performance via dynamic simulation. The results indicate that optimizing the durations of the adsorption and regeneration phases is crucial for improving cyclic DAC performance. Maximizing the working capacity by driving both phases towards near-equilibrium conditions generally leads to the lowest specific energy requirement (SER), while cutting the adsorption phase earlier increases the CO2 productivity. Additionally, appropriate choices of operating parameters, such as feed gas velocity and vacuum pressure, can significantly improve DAC process performance. Furthermore, placing the DAC unit in a location with favourable temperature and humidity conditions, affordable heat source, and elevated CO2 concentration can greatly enhance the process and its cost-effectiveness. These individual approaches have the potential to multiply productivity and decrease SER by increasing the working capacity, shortening the cycle duration, and minimizing the absolute energy consumption. However, optimizing the DAC process necessitates careful consideration of trade-offs between productivity, SER, and various constraints. These insights, along with the developed model, can provide a valuable basis for further advancement of DAC technology.