Waste reduction and reduced environmental impacts are the aims behind the European Union's accelerated paradigm shift toward a circular economy. Although the transport industry is an important sector, limited applications and implementations of the circular economy have been reported in the railway industry. To accelerate the transition, potential barriers that slow down the implementation process should be identified and addressed. This study consists of a structured questionnaire followed by an interview, which focuses on identifying and evaluating the importance of circular economy implementation barriers for the Swedish railway system. The study shows that different organizations include circular economy implementation in their future plans. Meanwhile, the experts highlighted that the current business model, economic competitiveness of virgin materials, logistical challenges, and regulatory inconsistencies slow down the transition process. The pillars of system innovation and implementation have been analyzed, and the results show that "Business models, investments, and procurement" are the most important pillar category, followed by "Infrastructure". The results also show that the prominent barriers are "Market price advantage of virgin materials", "Lack of supply chain integration", "Storage and site limitations", and "Complexity of wideranging products and volumes reaching End-of-Life". These barriers highlight that the economic competitiveness of virgin materials, logistical challenges, and regulatory inconsistencies are the most prominent issues.

The EU aims to accelerate the transition to a circular economy to reduce waste and its environmental impact since the linear economy model imposes significant environmental burdens. Resources are finite, and the consequences of environmental degradation, climate change, and disaster risks cannot be ignored. The construction industry accounts for over 38% of waste in Europe, so it has become inevitable to activate road maintenance as one of the enablers for the transition towards circular economy strategies.

This study aims to explore circular economy (CE) frameworks, indicators, and sustainable maintenance and rehabilitation (M&R) materials and methods. For this purpose, a systematic review has been conducted to explore the transition towards the circular economy and its interconnectivity with the road Pavement Management System (PMS). Scopus and Web of Science (WoS) are the primary databases that have been explored. Google Scholar also has been explored to complete the references. By examining and analyzing 62 papers from the mentioned databases, 26 relevant papers have been selected. By examining the previous practices of CE implementation, the review highlights how pavement maintenance of road have evolved to become more circular. This study highlights different CE frameworks, indicators, and sustainable maintenance materials, methods, and technologies that can facilitate circular PMS practices.

Climate-related failures pose increasing risks to railway operation and maintenance, requiring robust assessments to support effective resilience planning. Accordingly, this study presents a comprehensive risk assessment to identify, quantify, and prioritize climate-related failure modes (CRFMs). CRFMs were identified through text mining of 15-year corrective maintenance records across all five Swedish railway regions. A probabilistic model was then developed to analyze the risk of identified CRFMs, considering both operational and maintenance costs. Risk distributions were derived using Monte Carlo simulation and summarized by Expected Value of Risk (EVoR) and Conditional Value at Risk (CVaR0.90). As a result, 14 CRFMs were identified, accounting for 47% of all failure records. Their annual trend and seasonal distribution align well with periods of increased extreme weather events and dominant seasonal climate hazards. Furthermore, clustering the regional profile of CRFMs reveals regional similarity. The CRFMs were then prioritized, showing that 4 modes (i.e., Track deformation, Snow and ice, Buckling, and Rail breakage/crack) account for 73% of total CVaR0.90. The amplification of total risk in the tail indicates a 74% higher cost burden under extreme conditions. Finally, regional climate vulnerability was assessed using risk metrics normalized by track length and traffic density.

A linear economy is a traditional resource consumption model characterized by a “take-make-dispose” pattern without focusing on sustainable practices and climate change. The circular economy (CE) approach considers the entire life cycle of goods and services, aiming to minimize resource use and environmental impacts while contributing to sustainable development. It involves designing out waste and pollution and keeping high-value use for products and materials.

As the construction industry generates over 35% of Europe’s waste, activating the rail sector as a key driver for advancing circular economy strategies has become essential. So, optimizing resource use and mitigating environmental and societal impacts is important. Therefore, it is important to explore how circularity aspects (e.g., repairability, reusability, recoverability) are applicable for railway systems. This paper evaluates CE in Swedish rail infrastructure. The methods used in this study consists of literature review, interview and survey. Literature review, including circular economy frameworks, indicators, developments in the rail sector, and CE standards documents, have been considered in the study. Thereafter, interview and survey have been conducted with Swedish railway experts to explore the CE in the railway system.

Sustainable decision support system for asset management essentially requires an integrated approach that considers operational performance, maintenance strategies, environmental sustainability, and economic efficiency. This study presents a systematic methodology for identifying and selecting Key Performance Indicators (KPIs) for translating complex environmental data into quantitative insights for railway and manufacturing assets. The proposed framework integrates life cycle assessment (LCA) based indicators across upstream, core, and downstream life-cycle stages to quantify environmental impacts across the full asset life cycle. The Global Warming Potential (GWP) considered as the primary indicator, reflecting the essential role of carbon emissions in sustainability objectives, while energy consumption, waste management, and service water are defined as secondary KPIs. Tertiary KPIs include resource use and recycled content, providing additional support to circularity and reduced carbon emissions goals. This framework provides a consolidated foundation for comparing and optimizing maintenance (corrective and predictive) and replacement strategies. Overall, this work contributes to support effective environmental monitoring to determine Optimal Replacement Time (ORT) for railway assets.

This paper outlines the methodological and analytical foundation for RAMS (Reliability, Availability, Maintainability, and Safety) and Lifecycle Cost (LCC) assessment within the NRPCES project, supporting future development of Economic Replacement Time (ERT) considering sustainability KPIs and decision-support tools. The work is aligned with relevant European standards, notably EN 50126 for RAMS and EN 60300 for LCC, and provides a generic, transferable framework applicable across multiple industrial sectors. The primary objective of this study is to define how probabilistic RAMS indicators and cost drivers can be derived from operational and maintenance data and integrated into a consistent LCC structure. A comprehensive RAMS modelling framework for repairable systems is presented, combining homogeneity testing, trend analysis, and parametric stochastic processes. In addition, CO2 emissions and carbon costs associated with maintenance activities have been identified through maintenance data records and interviews with experts. Thereafter, RAMS outputs are directly linked to LCC drivers, ensuring that failure frequency, repair duration, and downtime are explicitly reflected in economic assessments. The methodology is demonstrated through railway crossing assets installed in the Swedish railway network.

Railway operation is considered as the most sustainable transportation. However, such observation often neglects environmental considerations during the maintenance stage, which is a carbon-intensive phase. This study aims to quantify carbon emissions related to the maintenance stage. In this study, we focused on railway turnout crossings (fixed manganese and movable) as a use-case located on Bandel (track section) 120 near Boden in Sweden for CO2 estimations. We utilize 14 years (2010-2023) of maintenance data collected from the Swedish Transport Administration (Trafikverket or TRV) databases. Results indicate that logistics (transportation) during the maintenance stage are the most significant contributors to fuel consumption and CO2-e emissions. Further, the interrelation between fixed and movable crossings demonstrates that the environmental impact of movable crossings is substantially higher than that of fixed crossings. The insight of this study can be integrated into decision-making models that combine Life Cycle Cost (LCC) and climate impact to optimize railway crossing replacement strategies.

The frequency and intensity of extreme weather events pose various types of hazards and vulnerabilities to the railway system. This article aims to challenge the assumption that a single, nationally and internationally aggregated model is sufficient to capture region-specific failure patterns. While useful, these national models are often unable to account for linkages and feedback between heterogeneous regions and associated railway failure mechanisms and processes. This study develops and evaluates regional-national specific machine learning (ML) framework to enhance the classification of climate-related railway failures utilizing a synchronized five-fold cross-validation strategy.

We illustrate the approach through a case study of the Switches and Crossings (S&C) assets across five railway operational regions in Sweden, over a 24-year period, to demonstrate meaningful climate variability. Our methodology provides a consistent procedure that consistently compares national models with region-specific models. Results show that the localized model outperforms the national baseline, with improvements of up to 2.0% in Matthews Correlation Coefficient and 1.2% in F1-score at the 24-hour window preceding failure. Shapley Additive Explanations (SHAP) analysis revealed regionally distinct predictors, such as snow accumulation in the North and weather data coverage issues in the West. The results provide a basis for further process refinement, offering interpretable insights for operation and maintenance planning, risk assessment and supporting climate adaptation actions to achieve a climate-proof and resilient railway system. 

As critical infrastructure, railways are highly vulnerable to climate hazards intensified by climate change. However, awareness of these risks is low, and comprehensive studies outlining these hazards and their impacts on railways are also scarce. To address these gaps, this review aims to identify climate-related risks, clarify the hazard-impact relationships and risk interconnections, and explore strategies to account for the influence of climate change on these risks. To this end, a systematic literature review was conducted in two stages. First, 71 peer-reviewed papers were collected through developing search strings, applying inclusion/exclusion criteria, and performing backward/forward citation searches. Second, the required information was systematically extracted from the papers and critically analyzed to address the research objectives. As a result, 24 climate hazards and 29 associated impacts were identified and categorized. The hazards and impacts having the most and least occurrence in the literature were also highlighted. Informative matrices were developed to correlate hazards with impacts and illustrate the cascading effects of the impacts. Four distinct approaches used to address the effects of climate change on climate risks were identified and critically discussed. The study also highlights critical gaps in the literature to guide future research.

The primary focus of the present work is to determine the optimal vulnerability patch release time using multi-attribute utility theory (MAUT) by considering two objectives that are cost minimisation and reliability maximisation. The novelty of the study lies in multi-phased research methodology for identifying the attributes affecting the software patch release time through a combination of literature review and the grey-Delphi approach for guiding the optimisation process. The literature has directly considered the weights of the attributes without emphasising their interrelationships, which is overcome by the use of the DEMATEL methodology under the grey environment in the current study for the evaluation of weights of selected attributes. The implications of the study will help in achieving the sustainable development goals pertaining to innovation and infrastructure. A numerical example is used to demonstrate the relevance of the optimisation problem.