Operationalising circular economy in mega infrastructure projects: a data-driven analysis

Abstract

The construction sector is among the most resource-intensive industries globally, with large-scale infrastructure projects generating substantial construction waste due to their scale, complexity, and execution uncertainties. While Circular Economy (CE) principles are increasingly promoted to address these challenges, their implementation at project sites remains largely disposal-oriented and insufficiently guided by data-driven prioritization approaches. The study presents a risk-based, site-centric assessment of construction waste streams to support practical CE implementation in large-scale infrastructure projects. Primary waste generation and material consumption data were collected from 58 infrastructure project sites, including metro, nuclear and hydel projects, over one year. The methodology integrates the Waste Generation Index (WGI) to normalize waste against issued material quantities, pareto analysis to identify dominant waste contributors, and Failure Mode and Effects Analysis (FMEA) to diagnose process-level failures based on severity, occurrence, and detectability. The study distinguishes between high-volume waste streams, including Construction and Demolition (C&D) waste and ferrous scrap, and high-inefficiency waste streams, including electrical waste, wood waste, and plastic waste. Results indicate that C&D waste exhibits the highest concentration of critical risk failure modes, driven by concreting losses and design-execution deviations. Although ferrous waste is largely recycled, the high-risk levels indicate upstream inefficiencies such as cutting losses and limited reuse of steel off cuts. Electrical waste emerges as a hidden high-risk hotspot, showing high waste intensity and risk even though its total quantity is relatively small. The findings demonstrate that effective CE interventions should consider both waste dominance and process risk, rather than waste quantity alone.