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RECORD NUMBER: 7 OF 13

Main Title Performance and Modeling of a Hot Potassium Carbonate Acid Gas Removal System in Treating Coal Gas.
Author Ferrell, J. K. ; Staton, J. S. ; Rousseau, R. W. ;
CORP Author North Carolina State Univ., Raleigh. Dept. of Chemical Engineering.;Environmental Protection Agency, Research Triangle Park, NC. Air and Energy Engineering Research Lab.
Year Published 1987
Report Number EPA/600/7-87/023;
Stock Number PB88-131297
Additional Subjects Fuel gas ; Coal gas ; Gasification ; Potassium carbonates ; Mathematical models ; Amines ; Solvents ; Air pollution control ; Acid gas removal ; Stationary sources
Holdings
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Status
NTIS  PB88-131297 Some EPA libraries have a fiche copy filed under the call number shown. 07/26/2022
Collation 164p
Abstract
The report discusses the performance and modeling of a hot potassium carbonate (K2CO3) acid gas removal system (AGRS) in treating coal gas. Aqueous solutions of K2CO3, with and without amine additive, were used as the acid gas removal solvent in the Coal Gasification/Gas Cleaning Test Facility at North Carolina State University. The AGRS consisted of a packed absorption column, one or more flash tanks for intermediate pressure reduction, and a packed stripping column operated with a reboiler. The removal of CO2, H2S, COS, and other species from the crude coal gas was studied, and data on the distribution of these gases in regeneration exit streams were obtained. Operating conditions for the selective removal of sulfur species were also examined. A system model for chemical solvents was developed and incorporated in a simulation program. The model was based on mass transfer rate of a key component, CO2, with the assumption that non-key reactive components affect the equilibrium of the key component, but not its mass transfer rate. The absorption and stripping of non-key components were assumed to be controlled by equilibrium between the gas and liquid phases in these columns. An isothermal flash model for chemical solvents was also developed and included in the program. Agreement between program predictions and pilot plant data was good.