Large-scale analysis of environmental and circularity metrics in construction products through automated data extraction using large language models

The selection of construction products significantly impacts building practices as well as environmental and biodiversity outcomes. However, current Environmental Product Declarations (EPDs) lack standardized circularity metrics and contain highly heterogeneous, manufacturer-dependent data, which severely limits sector-wide assessments and data-driven decision-making. Existing methods fail to systematically extract and structure this fragmented information at scale, creating a critical barrier to benchmarking circularity-related metrics, such as circular origin, dismantlability potential, and end-of-life pathways, and environmental performance across construction products. This study addresses this gap by introducing a novel Large Language Model (LLM)-based approach for the reliable extraction and standardization of data from diverse EPDs. Applying this method to 8463 products reveals three key findings: (i) manufacturers deprioritize circular end-of-life pathways; (ii) environmental and biodiversity impacts vary substantially both within and across product categories based on material composition; and (iii) a “circularity paradox” persists, whereby products sourced circularly often end up in landfills. Methodologically, this research establishes the first scalable procedure for comprehensive benchmarking of circularity-related metrics and environmental performance in construction products. Practically, it identifies critical intervention points including the standardization of circularity and environmental reporting in EPDs, the promotion of digital product passports, and the reinforcement of industrial symbiosis with transformation companies. For policymakers, the results highlight how existing regulatory shortcomings perpetuate linear economic models and obstruct consistent, equitable reporting, highlighting the urgent need for more stringent, standardized disclosure requirements to enable nuanced environmental comparisons. • Novel LLM–EPD approach for mapping end-of-life circularity in construction sector. • Manufacturing phase (A1–A3) dominates both environmental and biodiversity impacts. • Some products show circular paradox: recycled origin but landfilled at end-of-life. • Large environmental variability found within product categories due to materials. • More robust EPD validation and standardization needed for reliable comparisons.

Authors

Institutions

Publication Details

Journal
Environmental Impact Assessment Review
Published
2025-10-27
DOI
https://doi.org/10.1016/j.eiar.2025.108243
Citations
2
Primary Topic
Recycled Aggregate Concrete Performance
Type
article
Field-Weighted Citation Impact
2.01
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Large-scale analysis of environmental and circularity metrics in construction products through automated data extraction using large language models

Núria Forcada, Kàtia Gaspar, Roger Vergés
2 citations
Environmental Impact Assessment Review
Recycled Aggregate Concrete Performance
2.01
article

Large-scale analysis of environmental and circularity metrics in construction products through automated data extraction using large language models

Núria Forcada, Kàtia Gaspar, Roger Vergés
article en
2 citations

Abstract

The selection of construction products significantly impacts building practices as well as environmental and biodiversity outcomes. However, current Environmental Product Declarations (EPDs) lack standardized circularity metrics and contain highly heterogeneous, manufacturer-dependent data, which severely limits sector-wide assessments and data-driven decision-making. Existing methods fail to systematically extract and structure this fragmented information at scale, creating a critical barrier to benchmarking circularity-related metrics, such as circular origin, dismantlability potential, and end-of-life pathways, and environmental performance across construction products. This study addresses this gap by introducing a novel Large Language Model (LLM)-based approach for the reliable extraction and standardization of data from diverse EPDs. Applying this method to 8463 products reveals three key findings: (i) manufacturers deprioritize circular end-of-life pathways; (ii) environmental and biodiversity impacts vary substantially both within and across product categories based on material composition; and (iii) a “circularity paradox” persists, whereby products sourced circularly often end up in landfills. Methodologically, this research establishes the first scalable procedure for comprehensive benchmarking of circularity-related metrics and environmental performance in construction products. Practically, it identifies critical intervention points including the standardization of circularity and environmental reporting in EPDs, the promotion of digital product passports, and the reinforcement of industrial symbiosis with transformation companies. For policymakers, the results highlight how existing regulatory shortcomings perpetuate linear economic models and obstruct consistent, equitable reporting, highlighting the urgent need for more stringent, standardized disclosure requirements to enable nuanced environmental comparisons. • Novel LLM–EPD approach for mapping end-of-life circularity in construction sector. • Manufacturing phase (A1–A3) dominates both environmental and biodiversity impacts. • Some products show circular paradox: recycled origin but landfilled at end-of-life. • Large environmental variability found within product categories due to materials. • More robust EPD validation and standardization needed for reliable comparisons.

Environmental Impact Assessment ReviewVol. 117
Median SCP (Spain) (ES), Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 12%
Recycled Aggregate Concrete Performance
2.01
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.