The Summary for Policymakers of the IPCC Working Group III report, Climate Change 2022 was approved on April 4 2022, by 195 member governments of the IPCC. One of the main conclusions extracted from the report is the needed to use carbon capture and storage (CCS) as a route to decarbonize the energy and industrial sectors in the short to medium term. Among the different options for CCS, post-combustion CO2 capture (PCC) is the most mature methodology nowadays. However, the conventional chemical absorption-based PCC process by using aqueous alkanolamines (e.g., monoethanolamine (MEA)) implies high regeneration energy requirements, as well as losses due to degradation and evaporation . Changing the solvent or improving the process flowsheet are the two main methodologies to achieve higher energy efficiency and lower exergy losses. Subsequently, the development of new chemical/physical solvents and process designs are in progress to enhance the performance or mitigate issues associated with the established process with aqueous MEA . Nevertheless, evaluating these emerging solvents/processes remains limited to overall characteristics such as the net power for regeneration, and constrained to conditions far from typical process operating conditions with non-standardized measurements. Considering the vast amount of research in this area, a rapid and reliable procedure to screen emerging solvents/processes for CO2 capture and rank them against processes currently in use is needed.
After a brief introduction of the activities of the Research and Innovation Center on CO2 and Hydrogen (RICH Center) at Khalifa University related to carbon capture, utilization and storage, we will showcase the capabilities and results obtained from a robust decision-matrix tool  developed in our team, devoted to the evaluation and identification of top-performer prime candidates for the next generation of PCC plants, comparing them to the traditional MEA aqueous solution at relevant gas separation process conditions (i.e., T, P, CO2 concentration). The equilibrium-based process model includes 50+ different amine co-solvents (including water-free and water-lean systems) and different process configurations allowing extracting conclusions in terms of technical and economic performance of the solvents and processes, as well as performing sensitivity analysis in terms of economic parameters. Furthermore, the soft-SAFT equation of state [4,5] is used when needed to generate missing thermophysical data from the literature, especially for novel solvents, and feed into the process modelOnce all needed solvent data is in place, the evaluation of candidate solvents and process modifications is performed based on key performance indicators such as the net power of regeneration, capture cost per tonne of CO2, CAPEX, and OPEX (see figure). The model confirms that the column sizing and reboiler duty represent the two most important process parameters to be used for fast comparative performance, while also showing that the two solvent properties that have more influence on the capital cost, altogether with the absorption capacity, are the absorption enthalpy (heat of absorption) and the liquid phase viscosity. Moreover, the CO2 gas concentration is a stronger determinant of the cost of capture than the degree of capture, confirming that for the same investment, it is economically preferable to capture CO2 from higher concentration sources. The cost of capture is nearly constant for capture rates ~85%, but the marginal cost increases exponentially if rates above >95% are desired. Following this procedure and standardized metrics allowed to prioritize 10 amines and the best performer process.
This works is financially supported by Khalifa University of Science and Technology through project RC2-2019-007. Additional financial support was provided by IAEGHG (project IEA/CON/20/265).
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Professor and Director of the Research and Innovation Center on CO2 and H2 (RICH Center)