New Framework Unites Resilience and Sustainability to Guide Ageing Infrastructure Decisions

Every bridge, dam, tunnel and power grid that modern society depends on is quietly growing older, and the decisions about how to keep these assets standing and functioning have never been more consequential. A new study published in Communications Engineering argues that the way engineers and policymakers weigh resilience against sustainability is fundamentally broken, because the two concepts live in different time domains. Resilience is about the short term: how quickly a structure recovers after an earthquake, flood or other shock, and how reliably it keeps delivering services while that recovery unfolds. Sustainability is about the long term: the cumulative environmental, economic and social impacts of a structure across its entire life, from the quarry that supplied its concrete to the demolition crew that will one day take it down. Because these temporal scales rarely meet in a single analytical frame, adaptation decisions for ageing critical infrastructure remain fragmented, and the regulatory frameworks meant to deliver both resilience and sustainability are falling behind escalating expectations.

The research team, led by Marco Domaneschi of the Politecnico di Torino together with Nadiia Kopiika, Roberta Di Bari, Paola Cavallaro, Valentina Villa, Sotirios Argyroudis and Stergios-Aristoteles Mitoulis, affiliated with institutions including University College London, MetaInfrastructure and Brunel University of London, set out to close this gap with a unified, decision-oriented framework. Rather than analysing trade-offs between resilience and sustainability metrics separately, the authors integrate short-term recovery dynamics with long-term life-cycle performance inside a single optimisation structure that explicitly links the two temporal dimensions. According to the team, existing decision frameworks have not previously combined resilience and sustainability across these domains within one unified optimisation approach. The work is part of the European Union-funded ReCharged project on climate-aware resilience for critical and interdependent infrastructure systems, supported through HORIZON-MSCA funding and UK Research and Innovation guarantees.

The technical core of the framework rests on three established pillars of infrastructure assessment, brought together in a new way. The first is Life Cycle Assessment, or LCA, the standardised method for quantifying environmental impacts such as carbon emissions, energy demand and resource depletion across every stage of a structure’s existence. The second is Life Cycle Cost, or LCC, which aggregates all monetary expenditure from initial construction through maintenance, repair and eventual decommissioning, discounted over time. The third is multi-criteria decision analysis, or MCDA, a family of techniques for ranking alternatives when objectives conflict, as they inevitably do when a cheaper option carries a heavier carbon footprint or a faster recovery comes at the price of a shorter service life. What the new framework adds is a recovery-based formulation of resilience that is tied directly to retrofit implementation, allowing the speed and quality of post-hazard recovery to be treated as a decision variable rather than an afterthought.

This coupling matters because resilience has long been measured in ways that resist direct comparison with sustainability metrics. A bridge that returns to full traffic within days of a flood scores well on recovery, but if achieving that speed required heavy steel reinforcement produced in carbon-intensive furnaces, the long-term environmental ledger tells a different story. Conversely, a low-impact design using recycled materials might take weeks to restore after damage, imposing economic losses that dwarf the carbon savings. By formulating resilience as a recovery-based variable linked to retrofit choices, and then embedding it alongside LCA and LCA-derived carbon metrics within the MCDA optimisation, the researchers make these competing quantities commensurable. Decision-makers can finally ask, in a single calculation, which adaptation strategy delivers the best balance of rapid recovery, low lifetime cost, minimal emissions and extended longevity.

To demonstrate the framework in action, the team applied it to a landmark ageing bridge, evaluating six distinct adaptation strategies under competing objectives of resilience, cost, carbon and service life. The bridge serves as an ideal test case precisely because it embodies the dilemma facing thousands of structures worldwide: it was built for a design life and traffic load that modern conditions have overtaken, and its owners must choose between doing little and accepting growing risk, intervening heavily with conventional strengthening, or pursuing more transformative options. Each of the six strategies was scored across the full suite of metrics, with the optimisation structure revealing trade-offs that would remain invisible if resilience and sustainability were assessed in separate silos, as is the current norm in infrastructure governance.

The headline finding is striking: system-level transformation with limited structural intervention can outperform conventional strategies, achieving stronger trade-offs across resilience, environmental impact, cost and service life extension. In other words, the best answer for an ageing asset is not always the most obvious engineering one. Rather than pouring concrete and steel into a structure to restore it to something like its original condition, rethinking how the system operates, for example by managing loads, rerouting services or upgrading components selectively, can deliver better recovery performance and longer life at lower cost and with a smaller carbon footprint. This result challenges the instinct, deeply embedded in infrastructure practice, that more physical intervention automatically means more safety and more value.

The implications extend well beyond a single bridge. Ageing critical infrastructure is a global problem with a mounting price tag, and the window for cost-effective adaptation is narrowing as climate hazards intensify and asset stocks built during the mid-twentieth century boom approach the end of their design lives. Frameworks like this one offer a scalable pathway for aligning adaptation decisions with both sustainability and resilience objectives under real-world constraints, giving asset owners, regulators and financiers a defensible, quantitative basis for choosing among competing futures. Because the framework is decision-oriented, it is designed to slot into existing governance processes rather than replace them, translating engineering analysis into the kind of ranked, transparent options that procurement and policy processes require.

The study also reflects a deliberate effort to ground the methodology in professional practice. The authors acknowledge a panel of international experts who contributed through a structured questionnaire, including Prof. José Turmo of UPC BARCELONA TECH, Prof. Xiaowei Wang of Tongji University, Prof. Jun Yang of Chongqing Jiaotong University, Dr. Francesco Presta of BG&E, Dr. Francesco Fanigliulo of FaniPro, Prof. Henrry Rojas of the Pontifical Catholic University of Chile, Dr. Konstantinos Katirtzoglou of Four-Tees Engineers Ltd and Dr. Andrea Caristo of AECOM, alongside Paolo Baiardi of SALT AUTOCISA, an ASTM Group company, who supported the assessment of construction operations and intervention procedures. Dr. Raffaele Cucuzza of the Politecnico di Torino contributed to preparing the questionnaire. This engagement with practitioners on both the academic and industrial sides suggests the framework was stress-tested against the practical realities of procurement, construction sequencing and asset management, not merely refined in a theoretical vacuum.

For the engineering community, the methodological significance lies in the explicit linking of temporal domains. Resilience quantification has matured rapidly in the past two decades, with recovery curves, functionality loss metrics and hazard-fragility models now standard tools in seismic and flood risk assessment. Life Cycle Assessment has similarly matured, with standardised impact categories and increasingly granular environmental data for construction materials. Yet the two communities have largely published in parallel, and infrastructure codes still treat post-hazard recovery and life-cycle impact as separate compliance questions. A unified optimisation structure that treats retrofit decisions as the hinge between the two domains provides a concrete template for closing that divide, and the authors position it as a departure from the temporally disjoined approach that has dominated the field.

The broader message for society is that the infrastructure transition now underway, driven by climate adaptation, decarbonisation and the sheer scale of ageing assets, needs decision tools equal to its complexity. Choosing how to adapt a bridge or a grid is no longer a narrow engineering question but a governance question spanning decades of emissions, billions in lifecycle cost and the continuity of services that communities depend on during and after disasters. By making resilience and sustainability speak the same quantitative language within one optimisation frame, this research offers decision-makers a way to see the whole picture at once, and its demonstration that lighter, system-level transformation can beat heavy conventional intervention may reshape how the next generation of adaptation projects is conceived, funded and delivered.

Subject of Research: A unified decision framework integrating resilience and life-cycle sustainability for ageing infrastructure adaptation

Article Title: Operationalizing resilience for sustainable infrastructure governance across the life cycle

Article References: Domaneschi, M., Kopiika, N., Di Bari, R., Cavallaro, P., Villa, V., Argyroudis, S., & Mitoulis, S.-A. (2026). Operationalizing resilience for sustainable infrastructure governance across the life cycle. Communications Engineering. https://doi.org/10.1038/s44172-026-00794-2

Image Credits: AI Generated

DOI: 10.1038/s44172-026-00794-2

Keywords: resilience, sustainability, infrastructure, life cycle assessment, life cycle cost, multi-criteria decision analysis, ageing bridges, retrofit, climate adaptation, critical infrastructure, optimisation, governance