Dynamic Process Simulation and Assessment of CO₂ Removal from Confined Spaces Using Pressure Swing Adsorption

Pressure swing adsorption (PSA) is an attractive technology for low-concentration CO₂ removal from confined spaces. In this study, the dynamic process simulation of PSA with four adsorbents (e.g., Zeolite 13X, carbon molecular sieve (CMS), silica gel, and MOF-508b), the sensitivity analysis, and the minimum energy optimization of the PSA process were employed. The adsorption isotherm Langmuir models of CO₂ and N₂ with four absorbents were built, and the estimated values agreed well with the experimental data of the literature. Considering the sensitivity analysis, the minimization of energy consumption of PSA process was conducted to obtain the optimal adsorption pressure, desorption pressure, and purge/feed ratio. The results indicated that Zeolite 13X is the best candidate that meets the separation goals (CO₂ concentration below 500 ppm) with the lowest specific energy consumption (108.8 kJ·Nm^–3 N₂). The results provide a novel strategy and guidance for low-concentration CO₂ removal.