Abstract View
Aerosol Emissions Control from Water-lean Solvents for Post-combustion CO2 Capture
Vijay Gupta, Paul Mobley, JONATHAN THORNBURG, Lucas Cody, David Barbee, Jacob Lee, Roger Pope, Ryan Chartier, Marty Lail, Jak Tanthana, RTI International
Abstract Number: 361
Working Group: Control and Mitigation Technology
Abstract
Water-lean solvents (WLS) for CO2 capture gained interest because of their reduced parasitic penalty from energy needed for solvent regeneration. Commercial implementation, however, hinges on successful control of amine emissions. Previous research studied aerosol emissions from aqueous solvents, similar information is not available for emissions from use of these novel water-lean solvents.
We conducted studies from fundamental and operational aspects to reduce the overall amine emissions from RTI’s non-aqueous solvent eCO2Sol™. We used our 4-6 kW equivalent bench-scale gas absorption system (BsGAS). It consists of a CO2 absorber column with intercoolers and water wash section, and a solvent regenerator column with a thermosiphon reboiler and interstage heaters. A simulated flue gas with 15% CO2, 2.3-4.2% H2O was used. SO3 particulates were generated by reacting SO2 with O2 in air over a silica supported V2O5 catalyst at 450°C. The SO3 particulates mimic the presence of SOX and fly ash in the flue gas that provide nucleation sites for growth of aerosols. SMPS and APS instruments monitored the aerosol particle size distribution. A FTIR spectrometer monitored total amine emissions at the absorber and wash outlets. Process variables were liquid/gas ratio (L/G, mass basis), intercooling profile, absorber lean solvent temperature, water wash L/G, water wash return temperature, and flue gas inlet saturation temperature. The CO2 capture rate was maintained close to 90% capture rate.
Results from parametric testing suggested that the presence of the aerosols in the flue gas could increase the overall emissions by 10X compared to the baseline emissions from NAS’s vapor pressure. The temperature bulge in the absorber column drove aerosol growth. The PCA and PLS techniques applied to the parametric data derived a multivariate statistical model. The final model predicated aerosol emissions with ±15% accuracy.