Baskaran Divya, Byun Hun-Soo
Department of Chemical and Biomolecular Engineering, Chonnam National University, Yeosu, Jeonnam, 59626, South Korea.
Department of Biomaterials, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Chennai, 600077, India.
Environ Sci Ecotechnol. 2025 Jun 7;26:100587. doi: 10.1016/j.ese.2025.100587. eCollection 2025 Jul.
Mitigating carbon dioxide (CO) emissions, which are a principal contributor to global warming, necessitates prompt and proactive measures. This systematic review evaluates advanced process integration and optimization tools, highlighting the need for a circular economy paired with efficient waste management to achieve effective CO reduction. We systematically examine, for the first time, the applications and limitations of pinch analysis, Process-graph (P-graph), artificial intelligence (AI), computer-aided sustainable design (CASD), Internet-of-Things (IoT) sensor networks, and hierarchical blockchain frameworks. AI alone could save 2.6-5.3 gigatonnes of CO by 2030, and its integration with CASD and IoT enables more sophisticated mitigation strategies. We recommend comprehensive carbon-offset frameworks and green-finance mechanisms to strengthen carbon-trading systems. Circular-economy measures for waste-driven CO reduction remain under-represented in national climate policies owing to cross-sectoral complexity. Future work should advance interdisciplinary tools data science, system modeling, and decision-support frameworks and expand economic-feasibility studies of optimization strategies. Ensuring rigorous data quality, variability accounting, integration, transparency, and replicability is essential. Lastly, sustained collaboration among engineers, scientists, policymakers, and stakeholders is critical for developing scalable, sustainable solutions to climate change.
减少作为全球变暖主要促成因素的二氧化碳（CO）排放需要迅速且积极主动的措施。本系统综述评估了先进的过程集成与优化工具，强调了循环经济与高效废物管理相结合以有效减少CO排放的必要性。我们首次系统地研究了夹点分析、过程图（P-graph）、人工智能（AI）、计算机辅助可持续设计（CASD）、物联网（IoT）传感器网络和分层区块链框架的应用及局限性。仅人工智能到2030年就能节省2.6 - 5.3千兆吨的CO，并且将其与CASD和物联网相结合能够实现更复杂的减排策略。我们建议采用全面的碳抵消框架和绿色金融机制来加强碳交易系统。由于跨部门的复杂性，以废物驱动减少CO的循环经济措施在国家气候政策中仍未得到充分体现。未来的工作应推进跨学科工具，如数据科学、系统建模和决策支持框架，并扩大优化策略的经济可行性研究。确保严格的数据质量、变异性核算、整合、透明度和可重复性至关重要。最后，工程师、科学家、政策制定者和利益相关者之间的持续合作对于开发应对气候变化的可扩展、可持续解决方案至关重要。
