Thematic evolution of Life Cycle Assessment in construction and demolition waste management: before and after ISO 14040 and the Paris Agreement
Bibliographic record
Abstract
ABSTRACT: The rapid increase in construction and demolition waste (C&DW) poses significant environmental challenges, requiring innovative approaches for sustainable management. This study systematically explores these challenges through a text-mining analysis of 1,135 Life Cycle Assessment (LCA) studies on C&DW management, spanning from January 1997 to July 2024, using the PRISMA framework. Total link strength (TLS), indicating the level of association between research topics, and occurrence (OCC), representing the frequency of thematic mentions, are employed to identify knowledge gaps and trends in sustainable construction waste management. Using co-occurrence analysis, the study identified four major clusters of research themes: sustainability assessment (TLS=484, OCC=729), material and waste management (TLS=169, OCC=193), construction materials like concrete (TLS=80, OCC=86), and life cycle cost analysis (TLS=14, OCC=14). The most frequent keywords included “environmental assessment”, “recycling”, and “circular economy”, indicating strong emphasis on environmental performance and resource efficiency. Central themes included recycled aggregate concrete, circular economy, life cycle cost, and environmental assessment. Thematic evolution analysis revealed a 1320% rise in publications after ISO 14040 (2006) standardized LCA, with research pivoting from methodological development to sustainability topics like green roofs, industrial ecology, and carbon emissions. The 2015 Paris Agreement prompted an interdisciplinary shift integrating circular economy, embodied carbon, digital tools like building information modeling (BIM), and life cycle costing. The most recent phase highlights the emergence of decarbonization, social LCA, and artificial intelligence as expanding areas of focus. This study provides actionable insights into the evolution of LCA in C&DW management, emphasizing recycled aggregate concrete and circular economy principles for decarbonization. It highlights digital tools like BIM and AI to enhance life cycle costing and sustainability, supporting policies for a circular construction economy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.027 | 0.042 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".