Energy-efficiency analysis of industrial CO2 removal system using nanoabsorbents. (20th March 2021) - Kim, Seonggon; Xu, Ronghuan; Lee, Wonhyeok; Lim, Hwan Suk; Kang, Yong Tae
Abstract: CO2 physical absorption process is typically operated at a low temperature as low as −40 °C and high pressure. In this study, nanoabsorbents are applied to increase the operating temperature by improving the absorption performance. Herein, CO2 absorption performance is analyzed in a column absorber based on the Eulerian-Eulerian and population balance models. The computational results are verified experimentally under the same conditions and flow regimes can be classified into two regions in terms of the Reynolds numbers of the CO2 gas and absorbent. Dimensionless correlations are developed to predict the CO2 mass transfer coefficient for each region, which can be scaled up for industrial applications of the nanoabsorbents. The input power of the CO2 absorption system is calculated by considering each component. Finally, an operational map of the CO2 absorption and regeneration system, including both CO2 mass transfer coefficient and the input power, is presented. The operational map will be a guideline to optimize operating conditions. Specifically, when the CO2 absorption/regeneration industrial system is optimally designed, energy consumption can be reduced by approximately 40.5% with the CO2 mass transfer coefficient of 0.475 m/s. When SiO2 /MeOH nanoabsorbents are used as a working fluid of CO2 absorption system, the operational energy can be additionally saved by 23.2%. In addition, CO2 mass transfer coefficient can be improved by 11.9% using nanoabsorbents for same Reynolds number. It is expected that the energy consumption in the industrial MeOH-based CO2 absorption system will be greatly reduced by using the nanoabsorbents and the present optimization methods. Graphical abstract: Methodology of scale up analysis considering input power and CO2 mass transfer coefficient, and energy saving of the industrial CO2 absorption system using nanoabsorbents. Image 1 Highlights: CO2 absorption patterns are divided into two regions in terms of dimensionless correlation using nanoabsorbents. CO2 absorption can be controlled based on Sherwood number correlations of each regime. Operational map is presented to optimize industrial system considering input power and performance. Energy consumption can be reduced by 40.5% by optimizing nanoabsorbents system.