Data and code for: From wardrobe to wall — global potential, performance, and psychological acceptance of post-consumer textile composites in buildings

This dataset supports a three-study analysis of post-consumer clothing as a feedstock for building insulation and non-structural building components. Study 1 is a Monte Carlo material-flow and carbon model (N = 100,000 draws per pathway, seed 2026) whose thermal conductivity–density–humidity relationship was fitted to 11 measured Airlay panels made from sorted and unsorted post-consumer clothing (transcribed from Dama et al., 2025, https://doi.org/10.1016/j.dibe.2025.100657). Study 2 harmonizes 26 control-referenced observations from 5 peer-reviewed experiments on textile waste in cement-based and polymer-bonded building materials, each verified in the original article. Study 3 compiles verified quantitative evidence on the acceptance of recycled-origin products by consumers and construction professionals. Files: Supplementary_Data_S1.xlsx (six sheets; each sheet also provided as CSV: S1a–S1f); Supplementary_Code_S2.py (plain-text Python source that reproduces all results) with requirements.txt; three .drawio files (editable diagram sources of manuscript Figs. 1, 4 and 5a; open with https://app.diagrams.net). README.md defines all variables, units and verification levels. All inputs are from published sources; no human participants and no personal data are included.