An Optimization Framework for a Temperature-Vacuum Swing Adsorption Direct Air Capture Process

Abstract

The extraction of CO2 from the atmosphere via adsorption with supported-amine sorbents is being demonstrated on increasingly larger scale. Adsorption via temperature-vacuum swing adsorption is one of the major Direct Air Capture technologies. Optimization of such a process is complex, since many operational parameters are involved. This requires a multi-dimensional optimization approach aiming for a minimal total cost of capture. Process performance depends heavily on the ambient conditions, which makes the estimation of the cost of capture even more challenging. This study provides an optimization approach using an accurate, validated numerical model of the process as basis. Essential is that the optimization approach is performed for a single set of ambient conditions. Each simulation then resulted in a productivity and energy duty associated with a unique set of operational parameters. A trade-off between both performance indicators arose, where the points on the pareto front were selected for further optimization via an economic assessment. The optimization framework is demonstrated for a single set of ambient conditions, namely 20°C and 50% RH. This resulted in a minimum cost of capture of €560 per ton CO2. However, this is only valid for the given set of ambient conditions. To determine the total cost of direct air capture, the optimization procedure must be performed for multiple combinations of ambient conditions that correspond to the climate at the DAC location of interest.