The impact of binary water–CO2 isotherm models on the optimal performance of sorbent-based direct air capture processes

Abstract

Direct air capture (DAC) is an auspicious technology in pursuing negative CO₂ emissions. A promising process is temperature vacuum swing adsorption (TVSA) employing amine functionalised adsorbents such as Lewatit® VP OC 1065, which is selected as a benchmark sorbent in this study. To further improve process design, and critically lower costs, detailed modelling of DAC cycles is imperative. However, the multi-component adsorption on these materials, particularly the cooperative adsorption of CO₂ and H₂O, is crudely understood, and yet to be described in mathematical terms, prohibiting sound modelling efforts. Here, we commit in-depth understanding of the effect of humidity on CO₂ adsorption and demonstrate how this impacts modelling of DAC cycles. We present two novel mechanistic co-adsorption isotherm models to describe water's effect on CO₂ adsorption and find a good fit to original experimental co-adsorption data. We also show the considerable improvement in predictions of these models when compared to an empirical co-adsorption isotherm model from literature. A detailed TVSA DAC cycle process model is then used elucidating how different co-adsorption models affect the predicted process performance. It is found that the two novel isotherm models generate similar results and Pareto fronts, whilst the minimum work equivalent calculated using the more conservative of the two models is found to be 2.49 MJ kg⁻¹ for the case study considered. These mathematical descriptions laid out will lead to more accurate modelling and optimisation of cyclic DAC adsorption processes, prompting a greater understanding of the material-process combinations ideal for DAC and how costs can be driven down in the years to come. Importantly, they allowed us to independently benchmark a Climeworks type DAC process, providing key DAC performance data to the public domain.