Cement production is one of the key industries responsible for emissions of greenhouse gases, especially carbon dioxide (CO₂), which influence climate change. In order to reach zero carbon in the cement industry, various deep decarbonization pathways involving carbon capture, storage, and utilization (CCSU), using low-carbon material and fuel, optimal process control, and waste heat utilization techniques must be implemented. As for the example of Uzbekistan, approximately 30 facilities generate more than 15 Mt of cement annually and are responsible for 11.3% of the country’s total CO₂ emissions. In this study, decarbonization pathways for cement plants in Uzbekistan, including CCSU, the use of alternative fuels, electrification, and waste heat integration techniques, are compared based on existing challenges and opportunities. The availability of alternative fuel and material resources suitable for the total production capacity, the comparison of post-combustion, pre-combustion, and oxyfuel combustion CCSU methods for the cement plant, and the use of energy-efficient technologies are discussed.

Climate change, especially global warming, is observed due to greenhouse gases released on an industrial scale. For this reason, progress is being made around the world to reduce CO₂ emissions and transition to sustainable energy sources. One of the most mature methods of capturing CO₂ from flue gases in industrial sectors is chemical absorption. This work analyzed the absorption process involved in capturing CO₂ from the flue gases of a 1 Mt cement plant. The Aspen Plus modeling package was used to simulate the flue gas pre-treatment; absorption column; and regeneration unit. As a result of the modeling, the optimal values of column sizes; heat duty; and solvent make-up that require the least capital and operational costs for capturing CO₂ in the flue gases of this plant were determined. When a 40% MEA solution was used, and the CO₂ loading in the absorption-stripping process was 0.25 mol/mol, the reboiler heat duty was 4.06 MJ/kg CO₂.

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.

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.