Modelling of a fluidized bed carbonator reactor for post-combustion CO2 capture considering bed hydrodynamics and sorbent characteristics

This manuscript presents a general model for the fluidized bed carbonator reactor of the Calcium Looping (CaL) process based on bed hydrodynamics, kinetics and sorbent properties. The model proposed relies on the Kunii-Levenspiel theory for circulating fluidized beds in the fast fluidization regime and considers recent findings on the CO2 capture properties of CaO, including the effects of the diffusion-controlled carbonation stage and CaO modification by means of additives. By performing a sensitivity analysis, it is found that the solids inventory in the carbonator and superficial gas velocity are the main operational and hydrodynamic factors affecting the CO2 capture efficiency. Decay constant of the fraction of solids in the lean region and fraction of solids in the dense region are also identified as two important model parameters. Model predictions are shown to agree with experimental results retrieved from pilot-scale tests. The main novelty of the model is the consideration of a CaO/Al2O3 composite either as main CO2 sorbent used in the carbonator or as a make-up flow fed into the calciner. Using CaO/Al2O3 as the main CO2 sorbent leads to a 14.17% loss of capture efficiency after 100 cycles compared to 72.81% when using limestone derived CaO. It is demonstrated that feeding a very low ratio (similar to 0.1) of the CaO/Al2O3 composite or a rather high ratio (similar to 5) of limestone as makeup flow, leads to a significant improvement of the capture efficiency. The results obtained may be relevant for optimizing CaL operation conditions to be used in power plants.

Automated summary

The manuscript presents a general model for a fluidized bed carbonator reactor based on bed hydrodynamics, kinetics, and sorbent properties in the Calcium Looping (CaL) process. The study identifies key operational and hydrodynamic factors affecting CO2 capture efficiency, and highlights important model parameters. The model predictions are in agreement with experimental results and may be relevant for optimizing CaL operation conditions in power plants.