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Integrating circular economy and life cycle assessment strategies in climate-resilient buildings: An artificial intelligence approach to enhance thermal comfort and minimize CO2 emissions in Iran

Author

Listed:
  • Tajadod, Omid Ebrahimi
  • Ravanshadnia, Mehdi
  • Ghanbari, Milad

Abstract

Climate change is a significant threat to humanity and must be addressed in building design. This study introduces a novel framework that integrates Circular Economy (CE) principles into the design of residential buildings, addressing not only operational energy but also embodied carbon emissions, material reuse, and end-of-life strategies. By extending the focus beyond operational performance, it bridges the gap between lifecycle sustainability and architectural design, offering actionable insights for achieving environmentally and economically efficient buildings. This study investigates the integration of circular economy (CE) principles to enhance thermal comfort and reduce CO2 equivalent emissions in residential buildings in Iran from 2021 to 2022. A multi-layer perceptron artificial neural network (ANN) was developed and validated using performance metrics, including mean square error (MSE) and the coefficient of correlation (R), achieving high accuracy with MSE = 0.39e−2 MWh and R values of 0.9974, 0.99854, and 0.99886 for training, validation, and testing, respectively. Using Grasshopper software with Ladybug and Honeybee plugins, four residential building plans were simulated, and the best design solution (BS) demonstrated an 8 %–12 % increase in PMV and a 21 %–26 % reduction in thermal load across different zones compared to the worst solution (WS). The optimal configuration achieved a thermal comfort index of 64.13 % with a window-to-wall ratio (WWR) of 50 %, minimum U-value (WLC1 and WID1), and shading dimensions of 0.3 m and 4 for DSH and NSH, respectively. These findings show that the proposed ANN model is effective in predicting CO2 equivalent emissions and guiding CE-based design strategies. The study provides actionable insights for reducing carbon emissions through CE principles, supporting contractors, homebuyers, and policymakers in advancing sustainable construction practices.

Suggested Citation

  • Tajadod, Omid Ebrahimi & Ravanshadnia, Mehdi & Ghanbari, Milad, 2025. "Integrating circular economy and life cycle assessment strategies in climate-resilient buildings: An artificial intelligence approach to enhance thermal comfort and minimize CO2 emissions in Iran," Energy, Elsevier, vol. 320(C).
  • Handle: RePEc:eee:energy:v:320:y:2025:i:c:s0360544225007066
    DOI: 10.1016/j.energy.2025.135064
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