DATA-DRIVEN LIFECYCLE ASSESSMENT OF SMART INFRASTRUCTURE COMPONENTS IN RAIL PROJECTS

Abstract

This study provides a systematic review of the integration of lifecycle assessment (LCA) with smart infrastructure and data-driven methodologies in rail projects, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. A total of 134 peer-reviewed studies, published between 2000 and 2023, were systematically identified, screened, and synthesized to ensure methodological rigor and transparency. The review covered literature drawn from environmental science, civil engineering, data science, and governance domains, generating an evidence base supported by more than 25,000 cumulative citations. The findings revealed that rail construction remains the most resource- and energy-intensive stage, with concrete, steel, and ballast dominating embodied emissions. Long-term maintenance, replacement cycles, and end-of-life processes were shown to equal or even exceed construction burdens, underscoring the necessity of recycling strategies and circular economy practices. Electrification and renewable energy integration emerged as decisive factors for operational sustainability, consistently reducing emissions when coupled with energy-efficient technologies such as regenerative braking and lightweight rolling stock. A particularly significant contribution of recent studies was the integration of digital tools—such as IoT sensors, predictive analytics, BIM, and digital twins—into LCA frameworks, transforming sustainability assessments from static, retrospective analyses into dynamic, adaptive systems responsive to real-time performance data. Governance and institutional capacity were also identified as critical, with board-level oversight, compliance frameworks, and international standards shaping the effectiveness of LCA adoption across regions. Comparative evidence confirmed that rail consistently outperforms road and air transport in lifecycle sustainability, particularly under electrification and renewable integration, while cross-border case studies highlighted the importance of shared platforms and regulatory harmonization. Collectively, this review demonstrates that data-driven LCA is not only a methodological advancement but also a conceptual framework that links environmental performance, digital innovation, and governance capacity, establishing it as a foundation for sustainable and resilient rail infrastructure in the digital age.