Online monitoring of the solvent and absorbed acid gas concentration in a CO2 capture process using monoethanolamine

A method has been developed for online liquid analysis of the amine and absorbed CO2 concentrations in a postcombustion capture process using monoethanolamine (MEA) as a solvent. Online monitoring of the dynamic behavior of these parameters is important in process control and is currently achieved only using Fourier transform infrared spectroscopy. The developed method is based on cheap and easy measurable quantities. Inverse least-squares models were built at two temperature levels, based on a set of 29 calibration samples with different MEA and CO2 concentrations. Density, conductivity, refractive index, and sonic speed measurements were used as input data. The developed model has been validated during continuous operation of a CO2 capture pilot miniplant. Concentrations of MEA and CO2 in the liquid phase were predicted with an accuracy of 0.53 and 0.31 wt %, with MEA and CO2 concentrations ranging from 19.5 to 27.7 wt % and from 1.51 to 5.74 wt %, respectively. Process dynamics, like step changes in the CO2 flue gas concentration, were covered accurately, as well. The model showed good robustness to changes in temperature. Combining density, conductivity, refractive index, and sonic speed measurements with a multivariate chemometric method allows the real-time and accurate monitoring of the acid gas and MEA concentrations in CO2 absorption processes.Scopu

Online Monitoring of the Solvent and Absorbed Acid Gas Concentration in a CO₂ Capture Process Using Monoethanolamine

A method has been developed for online liquid analysis of the amine and absorbed CO₂ concentrations in a postcombustion capture process using monoethanolamine (MEA) as a solvent. Online monitoring of the dynamic behavior of these parameters is important in process control and is currently achieved only using Fourier transform infrared spectroscopy. The developed method is based on cheap and easy measurable quantities. Inverse least-squares models were built at two temperature levels, based on a set of 29 calibration samples with different MEA and CO₂ concentrations. Density, conductivity, refractive index, and sonic speed measurements were used as input data. The developed model has been validated during continuous operation of a CO₂ capture pilot miniplant. Concentrations of MEA and CO₂ in the liquid phase were predicted with an accuracy of 0.53 and 0.31 wt %, with MEA and CO₂ concentrations ranging from 19.5 to 27.7 wt % and from 1.51 to 5.74 wt %, respectively. Process dynamics, like step changes in the CO₂ flue gas concentration, were covered accurately, as well. The model showed good robustness to changes in temperature. Combining density, conductivity, refractive index, and sonic speed measurements with a multivariate chemometric method allows the real-time and accurate monitoring of the acid gas and MEA concentrations in CO₂ absorption processes