Energy–Efficiency Trade-Offs and Process Optimization in Amine-Based CO₂ Removal from Natural Gas: A Comparative Aspen HYSYS Study of Niger Delta Gas Systems

Abstract

The efficient removal of carbon dioxide (CO₂) from natural gas remains a critical challenge in gas processing due to its implications for energy efficiency, operational cost, and environmental sustainability. Despite the widespread use of amine-based absorption systems, there remains a need for systematic evaluation of solvent performance under conditions representative of developing gas infrastructures. This study addresses this gap by investigating the energy–efficiency trade-offs and process optimization of three conventional amine solvents—Monoethanolamine (MEA), Diethanolamine (DEA), and Methyldiethanolamine (MDEA)—using Aspen HYSYS simulation, with application to typical Niger Delta gas compositions. A steady-state absorber–stripper model was developed using the Electrolyte Non-Random Two-Liquid (e-NRTL) thermodynamic framework to simulate CO₂ absorption and solvent regeneration under varying operating conditions (30–50 bar, 30–50°C absorber; 100–130°C stripper; 4–12% CO₂ feed). Key performance indicators, including CO₂ removal efficiency, cyclic loading capacity, regeneration energy requirement, solvent degradation, and techno-economic cost, were systematically evaluated, alongside sensitivity analysis of feed composition. Results reveal distinct performance trade-offs among the solvents. MEA achieved the highest CO₂ removal efficiency (≈96%) and fastest absorption kinetics, but incurred the greatest regeneration energy penalty (≈3600 kJ/mol CO₂) and degradation rate. MDEA demonstrated superior energy efficiency (≈2200 kJ/mol CO₂), enhanced chemical stability, and the lowest overall cost (~$30/ton CO₂), albeit with lower removal efficiency (≈86%). DEA exhibited intermediate performance across all metrics. Increasing CO₂ concentration reduced removal efficiency for all solvents, though MEA showed greater resilience under high-acid gas conditions. Statistical analysis confirmed significant differences (p < 0.05) among solvents, particularly in energy consumption and cost. The study provides novel insights into the balance between absorption efficiency and energy sustainability, highlighting that solvent selection should be guided by process objectives rather than a single performance metric. From an industrial perspective, MDEA is recommended for large-scale operations prioritizing energy efficiency and cost reduction, while MEA remains suitable for high-purity gas applications. Beyond process-level findings, this work contributes to the broader discourse on low-carbon gas processing, offering a simulation-based framework for optimizing CO₂ capture in emerging gas-producing regions. The results have important implications for policy and industry, particularly in supporting energy-efficient gas utilization, reducing flaring, and advancing carbon management strategies in the Niger Delta and similar hydrocarbon systems.