Experimental and modeling of CO2 capture by dry sodium hydroxide carbonation

In this work, CO2 capture from the air using dry NaOH sorbents has been studied. The influences of the main operating parameters such as temperature, air humidity, and NaOH loading on the CO2 removal rate have been experimentally investigated using Taguchi method. The results revealed that the appropriate value of the temperature to maximize the rate was in the range of 35–45 °C. A multilayer artificial neural network (ANN) was also used to model the process in order to find the optimal conditions. A procedure reported in the literature was modified and applied to design the ANN model. The model predictions were validated by conducting some more experiments. The experimental results proved the accuracy of the model to predict the optimal conditions. The effects of NaOH particle size and multiple carbonation cycles have also been investigated.