The separation of carbon dioxide (CO₂) and hydrogen sulfide (H₂S) from sour natural gas is an important step in gas processing and emission control. This study applies a rate-based Aspen Plus simulation to examine solvent-based CO₂/H₂S removal under conditions representative of the Shurtan Gas Chemical Complex in Uzbekistan. Monoethanolamine (MEA) and methyldiethanolamine (MDEA) are evaluated as reference solvents with respect to separation performance and energy demand. The rate-based modeling framework accounts for reaction kinetics and mass transfer effects in the absorber–regenerator system. Simulation results indicate that both solvents achieve high acid gas removal efficiencies. From an engineering perspective, the results provide practical guidance for solvent selection and energy optimization in existing acid gas removal units, supporting pilot-scale deployment under industrial operating conditions. Sensitivity analysis suggests that increasing gas throughput beyond 30 t/h leads to a gradual reduction in CO₂ capture efficiency, primarily due to mass transfer limitations. From a techno-economic perspective, the lower energy demand of the MDEA-based system may imply reduced operating costs. The captured CO₂ stream reaches a purity of around 99.5%, which is compatible with downstream soda ash production. Overall, the results provide a screening-level assessment supporting further detailed evaluation.

Post-combustion CO₂ capture using monoethanolamine (MEA) is a mature mitigation technology, yet its high energy demand and complex dynamics remain major challenges. This study presents a unified dynamic modeling and control framework for an MEA-based absorption–regeneration system, focusing on a comparative evaluation of PID, fuzzy logic control (FLC), and model predictive control (MPC) under realistic operating disturbances. A control-oriented surrogate model was developed in MATLAB R2024b/Simulink and validated against published benchmark trends. The control objective was to maintain CO₂ capture efficiency above 90% while minimizing reboiler energy consumption under ±10% inlet CO₂ concentration and flue gas flow disturbances. Simulation results showed that PID control ensures basic stability but exhibits slow recovery and high energy usage, while FLC improves robustness with limited dynamic improvement. MPC consistently maintained capture efficiency above the target value, reduced the settling time by approximately 37%, and achieved a 12.4% reduction in average reboiler duty compared to PID control. The results demonstrate that a unified, implementation-oriented modeling framework enables the effective assessment of advanced control strategies and supports the energy-efficient operation of industrial MEA-based CO₂ capture systems.

The separation and purification of carbon dioxide (CO₂) from sour gas streams is critical for emission reduction and industrial reuse. This study presents a chemical absorption-based process simulation of CO₂ (carbon dioxide) and H₂S (hydrogen sulfide) separation using Aspen Plus V12.0, focusing on solvent-based treatment using an aqueous monoethanolamine (MEA) system selected based on industrial applicability and regeneration performance. The process was modeled for two gas streams originating from the Shurtan Gas Chemical Complex: a raw feed stream containing 3.42% CO₂ and 0.09% H₂S, and a treated dry gas containing 2.1% CO₂. The goal was to achieve high-purity CO₂ recovery (≥99.5%) with flow rates of 30 t/h and 20 t/h, respectively. Rate-based modeling was employed to simulate mass transfer and chemical kinetics in the absorber and regenerator columns. The simulation results indicated that at optimal solvent flow and absorber temperature (40–45 °C), over 98.6% CO₂ and 99.9% H₂S removal could be achieved. The specific energy requirement for solvent regeneration was estimated at 2.3 GJ per ton of CO₂, aligning with industrial efficiency benchmarks. The purified CO₂ is intended for use in the production of sodium carbonate (Na₂CO₃) at the Dehkanabad Potash Plant, which converts 20 t/h of CO₂ into 296,000 tons/year of calcined soda with 77% process efficiency. This approach enhances gas resource utilization while reducing atmospheric emissions. The model serves as a techno-economically viable foundation for scaling up CO₂ capture and utilization (CCU) in the Uzbek chemical industry.

Carbon capture is an essential technology for reducing industrial CO₂ emissions, particularly in the power and cement sectors. Among the various capture methods, solvent-based absorption systems are widely used due to their efficiency and scalability, making the selection of the right solvent critical for near-term applications. This study analyzes several solvents for use in an absorption-based CO₂ capture system, emphasizing identifying the most suitable solvent for 2025–2030. The research methodology involves process modeling in Aspen Plus, sensitivity analysis, and evaluation of the regeneration duty for each solvent. The objective is to achieve at least 90% CO₂ capture and 95% CO₂ purity. The flue gas composition considered in this analysis is 19.8% CO₂, 9.3% O₂, 63% N₂, 7.5% H₂O, and other trace gases. Various solvents are evaluated to determine their effectiveness in capturing CO₂ while minimizing the energy consumption during solvent regeneration. A sensitivity analysis was conducted to optimize the system’s performance based on the solvent type, operating conditions, and regeneration duty. The results showed that amine blends demonstrated a CO₂ capture rate of 92% and a CO₂ purity of 96%, with regeneration energy requirements of around 3.2 GJ/ton of CO₂, significantly lower than those of traditional MEA systems, which typically require around 4.0 GJ/ton. In contrast, ionic liquids showed a CO₂ capture rate of 89% and a purity of 95%, with a regeneration energy of 2.8 GJ/ton, though their current cost is higher, limiting their immediate large-scale application. Annual capital expenditure (CAPEX) calculation revealed that amine blends could potentially reduce the CAPEX by 15–20% compared to MEA, while amino acid salts showed similar CAPEX reductions with a capture efficiency of 90%. Overall, the results indicate that hybrid amine solvents are the most cost-effective and practical solution for 2025–2030, with ionic liquids and amino acid salts emerging as promising alternatives as their costs decrease.