Issue 12, 2025

Assessing the environmental footprint of electrochromic windows: a comparative LCA with AI-based forecasting

Abstract

This investigation assesses electrochromic windows as a novel green alternative to traditional double-pane windows through a life cycle assessment, which analyzes and compares both types of windows. The life cycle assessment was conducted using the impact categories of TRACI 2.1 in the SimaPro 9.1 application, with ecoinvent, and 1 m2 of each window type as the functional unit for the comparisons. The manufacturing of EC windows yielded a total CO2 generation of 49.6 kg CO2, and the manufacturing of double-pane windows resulted in 76.05 kg CO2. In the manufacturing of electrochromic glass windows, the float glass production process contributed 9.79 kg of CO2 at that stage of fabrication. From the sensitivity analysis, it was determined that using 10% less electricity during electrochromic window production can lower carbon emissions for electrochromic windows by 1.51 kg CO2. These life cycle assessment impact results were later used for advanced AI-predictive modeling using Python's scientific ecosystem, including PyTorch for neural network implementation, scikit-learn for data preprocessing and metric calculation, and custom-built hierarchical architectures to develop both Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System models. Considering that 200 m2 of double-pane windows were replaced by electrochromic windows, the embodied impact of electrochromic window production would be offset by the operational impact of 30.1 t CO2 in 10.5 months. Since the lifespans of both window types are similar, electrochromic windows are promising green alternatives to double-pane windows.

Graphical abstract: Assessing the environmental footprint of electrochromic windows: a comparative LCA with AI-based forecasting

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Article information

Article type
Paper
Submitted
31 Jul 2025
Accepted
21 Oct 2025
First published
27 Oct 2025
This article is Open Access
Creative Commons BY-NC license

RSC Sustainability, 2025,3, 5653-5664

Assessing the environmental footprint of electrochromic windows: a comparative LCA with AI-based forecasting

M. Rabbani, O. Tahti, S. E. Arthur, M. A. Hopping, C. J. Barile, M. H. Karim, A. Fahimi and E. Vahidi, RSC Sustainability, 2025, 3, 5653 DOI: 10.1039/D5SU00638D

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