A statistical analysis of the carbon dioxide capture process

Post combustion carbon dioxide (CO₂) capture is one of the most commonly adopted technologies for reducing industrial CO₂ emissions, which is now an important goal given the widespread concern over global warming. Research on amine-based CO₂ capture has mainly focused on improving effectiveness and efficiency of the CO₂ capture process. Our research work focuses on studying the relationships among the significant parameters influencing CO₂ production because an enhanced understanding of the intricate relationships among the parameters involved in the process is critical for improving efficiency of the CO₂ capture process. This paper presents a statistical study that explores the relationships among parameters involved in the amine-based post combustion CO₂ capture process at the International Centre for CO₂ Capture (ITC) located in Regina, Saskatchewan of Canada. A multiple regression technique has been applied for analysis of data collected at the CO₂ capture pilot plant at ITC. The parameters have been carefully selected to avoid issues of multicollinearity, and four mathematical models among the key parameters identified have been developed. The models have been tested, and accuracy of the models is found to be satisfactory. The models developed in this study describe part of the CO₂ capture process and can help to predict performance of the CO₂ capture process at ITC under different conditions. Some results from a preliminary validation process will also be presented.