In the light of increasing fears about climate change, greenhouse gas mitigation technologies have assumed growing importance. In the United States, energy related CO2 emissions accounted for 98% of the total emissions in 2007 with electricity generation accounting for 40% of the total. Carbon capture and sequestration (CCS) is one of the options that can enable the utilization of fossil fuels with lower CO2 emissions. Of the different technologies for CO2 capture, capture of CO2 by chemical absorption is the technology that is closest to commercialization. While a number of different solvents for use in chemical absorption of CO2 have been proposed, a systematic comparison of performance of different solvents has not been performed and claims on the performance of different solvents vary widely. This thesis focuses on developing a consistent framework for an objective comparison of the performance of different solvents. This framework has been applied to evaluate the performance of three different solvents – monoethanolamine, potassium carbonate and chilled ammonia. In this thesis, comprehensive flowsheet models have been built for each of the solvent systems, using ASPEN Plus as the modeling tool. In order to ensure an objective and consistent comparison of the performance of different solvent systems, the representation of physical properties, thermodynamics and kinetics had to be verified and corrected as required in ASPEN Plus. The ASPEN RateSep module was used to facilitate the computation of mass transfer characteristics of the system for sizing calculations. For each solvent system, many parametric simulations were performed to identify the effect on energy consumption in the system. The overall energy consumption in the CO2 capture and compression system was calculated and an evaluation of the required equipment size for critical equipment in the system was performed. The degradation characteristics and environmental impact of the solvents were also investigated. In addition, different flowsheet configurations were explored to optimize the energy recuperation for each system.