Experimental Modeling and Optimization of CO₂ Absorption into Piperazine Solutions Using RSM-CCD Methodology

Area of Science:

• Chemical Engineering
• Environmental Science
• Process Optimization

Background:

• Carbon dioxide (CO2) absorption is crucial for mitigating greenhouse gas emissions.
• Bubble column reactors are widely used for gas-liquid mass transfer processes.
• Optimizing operating conditions is essential for enhancing CO2 absorption efficiency.

Purpose of the Study:

• To evaluate and optimize CO2 absorption in a bubble column using a piperazine (Pz)-water system.
• To analyze the impact of operating parameters on hydrodynamic and mass-transfer performance.
• To determine optimal conditions for maximizing CO2 removal efficiency and absorption rate.

Main Methods:

• Utilized response surface methodology (RSM) with a central composite design (CCD) for process optimization.
• Applied multivariate statistical methods, including multiple regression and analysis of variance (ANOVA).
• Conducted validation experiments to confirm the optimized parameters and model accuracy.

Main Results:

• Achieved a maximum CO2 removal efficiency of 97.9% under optimized conditions.
• Determined optimal operating parameters: Pz concentration (0.162 M), solution flow rate (0.502 l/h), CO2 flow rate (2.199 l/min), and stirrer speed (68.89 rpm).
• Obtained high model fit with R² values ranging from 0.944 to 0.999, indicating satisfactory agreement between experimental and model data.

Conclusions:

• The RSM approach effectively optimized the CO2 absorption process in the bubble column.
• The identified optimal conditions significantly enhance CO2 capture performance.
• The developed models accurately predict CO2 absorption, providing a reliable framework for industrial application.