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Climate-Regulating Industrial Ecosystems: An AI-Optimised Framework for Green Infrastructure Performance

Author

Listed:
  • Shamima Rahman

    (Faculty of Business, Torrens University, Melbourne, VIC 3000, Australia)

  • Ali Ahsan

    (Faculty of Business, Torrens University, Melbourne, VIC 3000, Australia)

  • Nazrul Islam Pramanik

    (Faculty of Business, Torrens University, Melbourne, VIC 3000, Australia)

Abstract

This paper presents an Industrial–Ecological Symbiosis Framework that enables industrial operations to achieve quantifiable ecological gains without compromising operational efficiency. The model integrates Mixed-Integer Linear Programming (MILP) with AI-optimised forecasting to allow real-time adjustments to production and resource use. It was tested across the apparel manufacturing, metalworking, and mining sectors using publicly available benchmark datasets. The framework delivered consistent improvements: fabric waste was reduced by 10.8%, energy efficiency increased by 15%, and carbon emissions decreased by 14%. These gains were statistically validated and quantified using ecological equivalence metrics, including forest carbon sequestration rates and wetland restoration values. Outputs align with national carbon accounting systems, SDG reporting, and policy frameworks—specifically contributing to SDGs 6, 9, and 11–13. By linking industrial decisions directly to verified environmental outcomes, this study demonstrates how adaptive optimisation can support climate goals while maintaining productivity. The framework offers a reproducible, cross-sectoral solution for sustainable industrial development.

Suggested Citation

  • Shamima Rahman & Ali Ahsan & Nazrul Islam Pramanik, 2025. "Climate-Regulating Industrial Ecosystems: An AI-Optimised Framework for Green Infrastructure Performance," Sustainability, MDPI, vol. 17(15), pages 1-24, July.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:15:p:6891-:d:1712616
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    References listed on IDEAS

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    2. Samsatli, Sheila & Samsatli, Nouri J., 2018. "A multi-objective MILP model for the design and operation of future integrated multi-vector energy networks capturing detailed spatio-temporal dependencies," Applied Energy, Elsevier, vol. 220(C), pages 893-920.
    3. Wenmei Fei & Alex Opoku & Kofi Agyekum & James Anthony Oppon & Vian Ahmed & Charles Chen & Ka Leung Lok, 2021. "The Critical Role of the Construction Industry in Achieving the Sustainable Development Goals (SDGs): Delivering Projects for the Common Good," Sustainability, MDPI, vol. 13(16), pages 1-21, August.
    4. Camila I. Donatti & Celia A. Harvey & David Hole & Steven N. Panfil & Hanna Schurman, 2020. "Indicators to measure the climate change adaptation outcomes of ecosystem-based adaptation," Climatic Change, Springer, vol. 158(3), pages 413-433, February.
    5. Yuanxi Li, 2024. "Industrial variety, interregional industrial linkages, and regional resilience: evidence from China," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 73(3), pages 1321-1338, October.
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