EPD-Grounded Carbon–Resilience Allocation for Low-Carbon Concrete Supply: Decision Fidelity, Route Validation, and Correlated-Disruption Stress Testing

Abstract

Green construction teams need a defensible way to convert product-specific concrete carbon declarations into supply decisions that recognize delivery and disruption exposure. Prediction-to-optimization workflows can obscure a critical evidence boundary: verified environmental product declaration (EPD) values can support formal supplier comparison, whereas machine-learning estimates require decision-level validation before allocation. We introduce an evidence-aligned framework that separates observed EPD attributes, model-estimated screening outputs, scenario-derived A4 transport, and assumption-based disruption stress and assigns each a specific decision role. After harmonization and deduplication, the analysis contained 45,739 EPD records from 663 plants. Model transportability was audited using plant, company, temporal, and geographic holdouts, followed by direct comparison of predicted and EPD-observed rankings and allocations. A prospective external cohort added 22 declarations from 14 plants and seven derivation-unseen companies; the frozen model reduced record-level MAE by 6.6% relative to the frozen training median, while the supplier-ranking gate retained the EPD-grounded path. Formal strength-constrained optimization minimized observed EPD A1–A3 plus scenario A4 under plant-share caps. Across nine city–strength cases, a 40% cap produced three-plant allocations with mean Herfindahl–Hirschman Index 0.36. Under a 10% independent plant-disruption stress rate, it reduced the probability of losing at least half of supply from 0.100 to 0.027; mean and median A1–A4 premiums were 14.57% and 7.76%. Benefits remained measurable across disruption probabilities of 5–30% and pairwise correlations of 0–0.50. An OpenStreetMap routing check covered 79 plant–project pairs: median distance error was 6.39%, 17 of 18 allocation decisions were unchanged, and the remaining case had 0.026% route-evaluated objective regret. The contribution is a transparent carbon–concentration frontier with an empirical decision-fidelity gate: prediction supports early screening, whereas EPD values anchor formal allocation. The framework provides extensible planning evidence while preserving clear boundaries between comparative scenarios and operational procurement.