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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

天然ガスからのアミン系CO₂除去におけるエネルギー効率のトレードオフとプロセス最適化:ニジェールデルタガスシステムの比較Aspen HYSYS研究 (AI 翻訳)

B. Maduike, V. O. Ndubueze, Mike Osagie Odigie, J. Adjene

Asian Journal of Biotechnology and Bioresource Technology📚 査読済 / ジャーナル2026-05-01#CCUS経営インパクト: コスト削減対象セクター: oil_gas
DOI: 10.9734/ajb2t/2026/v12i2294
原典: https://doi.org/10.9734/ajb2t/2026/v12i2294

🤖 gxceed AI 要約

日本語

本研究は、Aspen HYSYSシミュレーションを用いて、天然ガスからのCO₂除去におけるMEA、DEA、MDEAの3つのアミン溶媒の性能を比較した。MDEAはエネルギー効率とコストで優れ、MEAは除去効率が高いがエネルギー消費が大きい。結果は、溶媒選択がプロセス目標に依存することを示し、低炭素ガス処理への示唆を与える。

English

This study compares MEA, DEA, and MDEA solvents for CO2 removal from natural gas using Aspen HYSYS simulation. MDEA offers superior energy efficiency and cost, while MEA achieves higher removal efficiency but with higher energy penalty. Results highlight trade-offs and provide a framework for optimizing CO2 capture in emerging gas regions.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本のGX文脈では、CCUS技術の効率化は重要であり、本研究成果はアミン法のエネルギー消費削減に寄与する可能性がある。ただし、ニジェールデルタのガス組成に特化しているため、日本の天然ガス事情への直接適用には調整が必要。

In the global GX context

Globally, this study contributes to low-carbon gas processing and CCUS optimization, relevant to ISSB/TCFD disclosure on emissions reduction. It offers a simulation-based approach for improving energy efficiency in CO2 capture, supporting transition finance and carbon management strategies.

👥 読者別の含意

🔬研究者:Provides comparative performance data on amine solvents for CO2 capture, useful for process optimization research.

🏢実務担当者:Offers guidance on solvent selection for gas processing plants to balance efficiency and cost.

🏛政策担当者:Highlights potential for reducing flaring and improving carbon management in gas-producing regions.

📄 Abstract(原文)

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.

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