Carbon capture and storage (CCS) is considered a critical part of climate change mitigation plans and reaching net zero. Aside from fossil fuel power plants, many industries have few or no carbon dioxide-free alternatives to manufacture the products. While some investigate novel production pathways for some industries, they are unlikely to be commercially ready to meet our climate mitigation goals. It has been deduced that achieving net-zero emissions in such industries is impossible and, at best, more expensive than CCS. Chemical absorption via amine solvents is currently the most mature post-combustion capture
process technology. Chemical absorption offers high capture efficiency and high selectivity;
however, it has significant solvent regeneration energy demand and, thus, high CO₂ capture costs. Research is being done for other solvents, including ionic liquids, phase change solvents, water lean solvents, and adsorption into solid sorbents, which use solvent promoters. All of the technologies mentioned vary in technology readiness level (TRL) from 3-7 and mostly still rely on amines in some form to enhance kinetics. There is a vast number of possibilities for amine blends, and the current research practice is to undergo screening experiments which are time consuming and not comparable due to different operating conditions. This research aimed to elucidate factors affecting CO₂ absorption in aqueous amine solvents, namely chemical kinetics and mass transfer affecting CO₂ absorption efficiency parameters,
specifically CO₂ loading, absorption rates, mass transfer coefficients and the speciation. The extent of chemical kinetics and mass transfer were influenced by changing operating conditions,including impeller speed, amine concentration, CO₂ flow rate, and temperature. The conditions
were the basis of a design of experiments to obtain high and low mass transfer regimes. The amines studied were monoethanolamine (MEA), N-methyldiethanolamine (MDEA), 2-amino-2-methyl1-propanol (AMP), and piperazine (PZ). The first set of experiments was carried out in the continuous stirred tank reactor (CSTR) under different regimes and conducted at three different temperatures 293, 313 and 333 K; two different CO₂ flow rates of 250 and 990 mL/min; two impeller speeds of 50 and 300 rpm; and two amine concentrations. Data-logging and 13C NMR spectroscopy were used to analyse results, where the CO₂ inlet and outlet and pH were measured and logged, and samples were taken for further 13C NMR analysis. Reaction mechanisms were deduced and discussed using this analysis. Furthermore, the overall mass transfer coefficient was determined using a modified CSTR and a wetted wall column (WWC), where the contact area was known. The final CO2 loadings achieved for the different amines and their blends ranged from 0.33 to 0.94
mol CO2/mol amine. The variation was due to the mass transfer regime, change in temperature or impeller speed. Results showed that experiments carried out at a higher mass transfer regime always achieved higher CO2 loadings but reached completion at a slower rate. The effect of the mass transfer regime was different depending on the amine, it had the most effect on MDEA and least on PZ. This relationship showed the importance of the interplay of chemical kinetics and mass transfer. The speciation under different conditions was also analysed using 13C NMR spectroscopy and several products were identified including amines, bicarbonate, amine carbonate, amine carbamate and amine dicarbamate. Moreover, mass transfer had an effect on speciation and determining the reaction mechanisms. Each result obtained in this work alone gives valuable information related to CO₂ absorption, whereas analysing the combined data significantly
enhances the fundamental understanding of the process. Results showed that reaction mechanisms have been oversimplified and reactions have been unaccounted for, all of which impact the performance of individual amine solvents. The analysis in this work goes beyond screening experiments at optimal operating conditions, which do not account for different industrial conditions. This understanding is crucial for industrial implementation to optimise the mature technology, hence decreasing costs and supporting the large number of plants required to reach net zero by 2050.