The growing adoption of life cycle assessment (LCA) across productive sectors has yet to be systematically examined in terms of its capacity to drive environmental transformation beyond methodological assessment. This systematic review (2018–2024) explores how LCA functions as a catalyst for environmental change in products, processes, and systems. Following PRISMA 2020 guidelines, 657 records from Scopus, Web of Science, and ScienceDirect were screened, yielding 50 high-quality studies assessed using the Critical Appraisal Skills Programme (CASP) tool; bibliometric network analysis via VOSviewer complemented qualitative thematic synthesis. Findings reveal a shift from conventional standardized life cycle assessment methodologies toward integrated frameworks such as LCSA, incorporating regionalized characterization factors, uncertainty quantification, and digital technologies. Applications across energy, agri-food, manufacturing, construction, and waste management support SDGs 12, 13, and 9 by identifying hotspots, comparing technologies, and informing policy. However, inconsistencies in functional units, system boundaries, and impact methods, alongside limited social and economic integration, restrict cross-study comparability. The evidence indicates that LCA is evolving from an assessment tool into a deliberative decision-making infrastructure, requiring harmonized yet context-specific methodologies and robust social indicators for equitable implementation. This review offers original value by combining bibliometric and critical methodological synthesis to map how life-cycle thinking induces environmental transformation, revealing the gap between evaluative capacity and transformative implementation.

The construction sector is a major contributor to resource depletion and greenhouse gas emissions, underscoring the importance of adopting sustainable practices to meet environmental and climate goals. However, current assessments often underestimate impacts because of narrow system boundaries and insufficiently localized material inventory data, creating a critical research gap in accurately evaluating building sustainability. This study therefore applies to a comprehensive Life Cycle Assessment (LCA) framework to evaluate the environmental performance of key construction materials and to investigate strategies for integrating circular design and renewable energy to reduce carbon footprints. The results reveal that medium-term environmental impacts are approximately 20–30% higher than previously reported, while the Global Warming Potential of conventional brick increases by about 23% when additional life-cycle stages are considered. Furthermore, the analysis demonstrates that design-for-disassembly and recycling-oriented approaches can significantly enhance material recovery and reduce waste. These findings imply that developing harmonized, region-specific material databases and promoting circular construction alongside renewable energy integration are essential for improving LCA accuracy and achieving meaningful reductions in the environmental footprint of buildings.

The textile industry is facing increasing pressure to improve its sustainability performance across environmental, economic, and social dimensions. A substantial share of textile production relies on polymer-based fibers, such as polyester, polyamide, and acrylics, whose production, use, and end-of-life management raise significant sustainability challenges. In this context, life cycle-based assessment tools have become essential for supporting informed decision-making and guiding the transition toward more circular textile systems. This review critically examines the application of Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and Social Life Cycle Assessment (S-LCA) within the textile sector, with a specific focus on polymeric textile materials and circular economy strategies. The analysis highlights the strengths and limitations of each methodology, emphasizing persistent challenges related to system boundary definition, data availability and quality, methodological heterogeneity, and limited comparability across studies. Particular attention is given to how methodological choices influence the robustness and interpretability of sustainability outcomes, especially when assessing circular solutions for polymer-based textiles. The review reveals that, despite their conceptual complementarity, LCA, LCC, and S-LCA are often applied in a fragmented manner, limiting their integration into holistic sustainability assessments. Overall, this work underscores the need for greater methodological alignment and integrated frameworks to enhance the decision-making relevance of life cycle-based tools and to effectively support sustainable and circular transitions in the textile industry.

Magnonic Chern insulators host chiral edge modes that propagate unidirectionally along system boundaries and are protected against elastic backscattering by the non-zero Chern number. These modes have been observed in several magnetic materials and are promising candidates for low-dissipation spin-transport platforms. A key open question concerns how edge excitations lose coherence when coupled to realistic environmental degrees of freedom. We theoretically analyse decoherence in chiral magnon edge modes of a honeycomb ferromagnet with Dzyaloshinskii-Moriya interactions. Starting from a microscopic spin model, a Holstein-Primakoff expansion is performed and the resulting bosonic Haldane Hamiltonian is derived explicitly. Edge modes in a zigzag ribbon geometry are obtained via exact lattice diagonalisation, and their spatial profiles are used to construct a momentum-resolved open-system description. Within the Born-Markov and secular approximations, a Lindblad master equation is derived and used to compute relaxation, pure dephasing, coherence decay and entanglement loss. The results identify which features of decoherence are constrained by band topology, such as the suppression of elastic backscattering, and which remain sensitive to environmental noise irrespective of the Chern number. Numerical simulations show the dependence of decoherence on momentum, temperature, edge localisation and group velocity, and provide experimentally accessible predictions for coherence times and line-widths. The developed framework provides a unified approach to dissipative dynamics in topological magnonics, bridging microscopic spin-wave theory and open-system formalisms.

Abstract We unveil a quantum Pontus-Mpemba effect enabled by the Liouvillian skin effect in a dissipative tight-binding chain with asymmetric incoherent hopping and coherent boundary coupling. The skin effect, induced by non-reciprocal dissipation, localizes relaxation modes near the system boundaries and gives rise to non-orthogonal spectral geometry. While such non-normality is often linked to slow relaxation, we show that it can instead accelerate relaxation through a two-step protocol -realizing a quantum Pontus-Mpemba effect. Specifically, we consider a one-dimensional open chain with coherent hopping J, asymmetric incoherent hoppings J R = J L , and a controllable end-to-end coupling . For = 0, the system exhibits the Liouvillian skin effect, with left and right eigenmodes localized at opposite edges. We compare two relaxation protocols toward the same stationary state: (i) a direct relaxation with = 0, and (ii) a two-step (Pontus) protocol where a brief coherent evolution transfers the excitation across the lattice before relaxation. Although both share the same asymptotic decay rate, the two-step protocol relaxes significantly faster due to its reduced overlap with the slow boundary-localized Liouvillian mode. The effect disappears when J R = J L , i.e., when the skin effect vanishes. Our results reveal a clear connection between boundary-induced non-normality and protocol-dependent relaxation acceleration, suggesting new routes for controlling dissipation and transient dynamics in open quantum systems.

Driven suspensions, where energy is input at a particle scale, are a framework for understanding general principles of out-of-equilibrium organization. A large number of simple interacting units can give rise to non-trivial structure and hierarchy. Rotationally driven colloidal particles are a particularly nice model system for exploring this pattern formation, as the dominant interaction between the particles is hydrodynamic. Here, we use experiments and large-scale simulations to explore how strong confinement alters dynamics and emergent structure at the particle scale in these driven suspensions. Surprisingly, we find that large-scale density fluctuations (many times the particle size) emerge as a result of confinement, and that these density fluctuations sensitively depend on the degree of confinement. We extract a characteristic length scale for these fluctuations, demonstrating that the simulations quantitatively reproduce the experimental pattern. Moreover, we show that these density fluctuations are a result of the large-scale recirculating flow generated by the rotating particles inside a sealed chamber. This surprising result shows that, even when system boundaries are far away, they can cause qualitative changes to mesoscale structure and ordering.

Abstract This paper revisits the group controllability of two‐time scales multi‐agent systems, aiming to achieve innovation from the perspective of heterogeneity and switching topology. To accomplish this objective, the singular perturbation system theory and boundary layer theory are introduced to model the systems. Then, Wonham's Geometric Methods alongside concepts, such as invariant subspaces and controllable state sets, are employed to establish criteria for group controllability. Furthermore, we propose a method to construct switching sequences aimed at ensuring group controllability. Numerical simulations validate the effectiveness of the derived conclusions.

Urban underground space is increasingly being developed to alleviate surface land constraints and support low-carbon urban development. However, carbon emission reduction (CER) benefits remain inadequately quantified and are not comparable across underground infrastructure types, largely due to the absence of a unified assessment framework, inconsistent system boundaries, and the omission of multi-pathway mitigation mechanisms such as carbon capture and storage and biological sequestration. This study proposes a CER benefit assessment framework for urban underground space that integrates mitigation mechanism identification, pathway analysis, and benefit accounting, explicitly incorporating biological carbon sequestration, carbon substitution, and carbon capture and storage within a unified accounting structure. Accounting models are then established for three representative underground infrastructure systems: transportation, public and commercial services, and municipal utilities. Using Nanjing as a case city to operationalize and validate the proposed assessment framework, we estimate CER across multiple pathways and compare regional differences. The results indicate that underground transportation infrastructure provides the largest benefit (8.74 × 105 tCO2e per year), mainly driven by travel substitution and energy savings in station buildings. Underground public and commercial facilities achieve 6.64 × 105 tCO2e per year, dominated by green-building energy savings and geothermal integration. Municipal utilities contribute a smaller but strategically important reduction, as they provide a long-term carrier for carbon capture and storage and are structurally integrated within underground utility corridors, totaling 0.98 × 105 tCO2e per year citywide. Overall, the findings reveal differentiated mitigation mechanisms and spatial heterogeneity across underground infrastructure systems, providing a theoretical basis for optimizing urban spatial planning and informing low-carbon transition policies.

The rapid expansion of China’s immersed tunnel construction has resulted in substantial consumption of reinforced concrete and construction energy, thereby generating considerable greenhouse gas (GHG) emissions during the construction stage. Unlike conventional tunnels, immersed tunnels require large cross-sectional dimensions, complicated geological conditions (e.g., varying seabed burial depth and settlement grade requirements), and unique structural parameters, leading to distinct emission characteristics that are currently insufficiently understood. To address this gap, this study aims to quantify construction-stage GHG emissions of immersed-tube segments, identify key influencing factors linking construction parameters and material input with GHG emissions, and develop simplified predictive models for design-stage estimation. A total of 51 immersed-tube segments from three representative cross-sea tunnel projects in China were examined. Under a unified system boundary and functional unit (covering material production and processing, material transportation, and on-site construction energy consumption), the life-cycle assessment (LCA) framework was applied to quantify the construction-stage emissions of each immersed-tube segment. The construction-stage GHG emissions of a single segment range from 1.56 × 104 to 2.71 × 104 t CO2 eq (mean ≈ 2.40 × 104 t CO2 eq). Correlation and partial correlation analyses demonstrated that the total mass of construction materials exhibits the strongest correlation with GHG emissions, followed by the element volume, concrete cross-sectional area, settlement grade, and burial depth. The results further indicate that material intensity is the dominant determinant of GHG emissions for immersed tubes, while the effects of seabed and settlement conditions mainly operate through structural scale and material demand. Finally, two linear regression models were developed, and the model based on total material mass provides the most accurate prediction of construction-stage emissions. The immersed-tube volume can be used to estimate approximate GHG emissions at the design stage, whereas the total material mass serves as a better predictor when detailed material input data are available. This study is based on segment-level data from three Chinese projects and focuses on the construction stage; therefore, transferability requires further validation. Material intensity is the dominant determinant, and the total-material-mass model is the most accurate predictor.

A global transition in biosolids processing, driven by concerns over greenhouse gas emissions and emerging contaminants, demands robust sustainability assessments. While life cycle assessment (LCA) is widely adopted, methodological inconsistencies across studies have limited the comparability and reliability of results. This study addresses this gap by systematically reducing variability in published LCA estimates, providing a harmonized baseline for the environmental performance of biosolids processing technologies. The study adopted a harmonization approach to align methodological choices across 19 LCA studies covering four biosolid processing systems. Harmonisation significantly reduced variability and clarified comparative environmental outcomes: anaerobic digestion had the lowest mean harmonized global warming potential, while incineration and composting remained the highest-impact systems. Pyrolysis presented the widest postharmonization range, reflecting ongoing uncertainties and technological heterogeneity. A biosolids LCA benchmarking tool was also proposed to enable the development of customized harmonization results based on site-specific conditions. Moreover, a novel approach, partial harmonization, was introduced to serve as a sensitivity analysis that isolates the influence of individual LCA inputs to identify key sources of variation. Among 92 LCA inputs, this method identified inputs such as electricity mix, system boundaries for energy recovery, and fertilizer substitution assumptions as dominant drivers of variability.

Current carbon accounting in the power sector often relies on annual average emission factors, which suffer from ill-defined system boundaries, update delays, and insufficient temporal granularity. To address these limitations, this study introduces a high-spatiotemporal-resolution dynamic measurement model for grid carbon emission factors, grounded in carbon emission flow theory. Applied to a regional grid in northern China, the model employs nodal carbon–emission–flow balance to construct system-level matrix equations. This approach accurately traces the spatiotemporal transmission paths of carbon emissions, enabling refined, node-level, and hourly carbon accounting. A case study demonstrated that our model significantly outperformed existing static methods based on interprovincial power exchange in both resolution and accuracy. The results revealed pronounced spatiotemporal heterogeneity in grid emission factors: diurnal fluctuations reach up to 45% in maximum deviation, closely coupled with renewable energy output, while spatial disparities between high- and low-emission regions reach a factor of 4.7, highlighting the critical roles of generation mix and grid topology. This study confirms that high-resolution emission factors effectively overcome the biases of traditional methods, providing a critical data foundation for green electricity trading, demand-side response, and regionally differentiated emission-reduction policies. Our approach offers key methodological and policy insights for building new-type power systems and advancing carbon neutrality goals.

This study calculates the carbon footprint of chemical coagulants and operational energy for residential and industrial (whey digestion) wastewater treatment using ReCiPe 2016 methodology within a clearly defined system boundary from cradle to gate. Data from water treatment facilities have been analyzed to quantify environmental impacts and identify sensitive design parameters. The estimated emission of treating 1 m3 of wastewater from whey digestion (7.1195 kg CO2 eq) is over 50 times higher than that of a residential one (0.1349 kg CO2 eq). Life cycle impact assessment (LCIA) reveals that iron (III) chloride (40% in H2O) and operational electricity consumption have higher impact categories compared to other design components. The uncertainty analysis indicates that electricity consumption (r = 0.4) is the dominant contributor to emissions, with a mean value of 4.22 kg CO2-eq per m3 of wastewater treated. In contrast, iron (III) chloride emerges as the most sensitive parameter (r = 0.88) with small variations in dosing causing a disproportionately large impact on overall emissions. Therefore, the optimized use of an iron-based coagulant, the adoption of membrane electrolysis, and the integration of renewable electricity into the process supply chains have been identified as effective strategies for reducing emissions.

Research concerning the adverse health effects of per- and polyfluoroalkyl substances (PFAS) continues to grow. With the recent releases of nationwide data on PFAS in drinking water and public drinking water system service boundaries, it is now possible to conduct nationwide geospatial analyses on the relationships between PFAS in drinking water and aspects of health. To examine associations between PFAS in drinking water and cancer history prevalence in the United States. We examined cancer history prevalence, at the census tract level, among adults aged ≥ 18 years diagnosed with any cancer in or prior to 2022 using the United States Population Level Analysis and Community EStimates dataset. We obtained data for PFAS in public drinking water from the Fifth Unregulated Contaminant Monitoring Rule (UCMR 5, 2023-ongoing). We used geographic information systems to spatially join water system boundaries (n = 9,733) with census tracts applying population-weighted areal interpolation. We calculated prevalence ratios (PRs) and 95% confidence intervals (CIs) for the associations between PFAS in drinking water and prevalence of cancer history, adjusted for census tract-level sociodemographics, health conditions and behaviors, and environmental factors. This analysis included 76,606 census tracts with an average cancer history prevalence of 7.8%. We observed positive associations of cancer history prevalence with PFAS levels in drinking water for 6:2-FTS, PFBA, PFBS, PFHpA, PFHxA, PFHxS, PFNA, PFOA, PFPeA, and PFPeS (p < 0.01). For example, for 6:2-FTS, the adjusted PR comparing the highest quintile (0.0182-0.663µg/L, population-weighted) to samples below the minimum reporting level (< 0.005µg/L) was 1.04 (95% CI 1.02-1.07, p < 0.001). No associations were observed for HFPO-DA and PFOS. Models mutually adjusted for correlated PFAS showed generally similar results. Higher levels of certain PFAS in drinking water were independently associated with higher cancer history prevalence. Future research should examine the relationships between individual-level cancer outcomes and individual-level exposure to PFAS in drinking water.

Today, manufacturing products, processes and assembly lines can be optimized by mirroring the allied physical assets and counterparts available over system boundaries, which can be done by Digital Twin (DT). Manufacturing teams can analyze different data sources and reduce failures by using DT, which in turn can increase production efficiency and decrease industrial breaks. But, it is difficult to mount DT structures and fundamental frameworks due to evident barriers and challenges. Accordingly, the present study is conducted with the purpose to report crucial barriers and drivers that can uplift the ease of implementation of DT in the manufacturing industries. The identification of DT barriers and drivers is presented to help policymakers and decision-makers establish effective strategies to address DT implementation. The synergies between barriers, sub-barriers, drivers and sub-drivers are presented in the study, where a seven-stage research methodology based on entropy weightage method and simple additive weighting technique is presented for evaluation. This study discusses the theoretical concept of DT, its design components from manufacturing insights and presents an application framework of DT for smart manufacturing system design. In the study, five major DT drivers with nineteen sub-drivers are categorized. Additionally, six major DT barriers with thirty-five sub-barriers are also categorized and presented. The study evaluated DT drivers and barriers for persuading the implementation of DT in manufacturing industries and reported critical insights related to the theoretical foundation of DT modelling to develop a smart manufacturing system. The chief novelty of the study lies in inducing the synergies between barriers, sub-barriers, drivers and sub-drivers for the due implementation of DT under the prospects of manufacturing industries.

Abstract The agricultural sector urgently requires scalable solutions to reduce greenhouse gas (GHG) emissions from residue management. Biochar offers a promising carbon removal pathway, but its adoption is limited by technical, regulatory, and economic barriers. A key constraint is the lack of system designs that can accommodate multiple feedstocks while complying with land application regulations. This study designs and evaluates an integrated biochar production system that enables the separate processing of straw and manure through parallel pyrolysis lines, while optimising internal energy use. Environmental and economic assessments were conducted using a case study of the University of Leeds Research Farm, under a cradle-to-grave system boundary. The results show that the system can produce 300 t of biochar annually, sequester 350 t CO 2 e, and reduce manure management emissions by 75%, with an additional 30 t CO 2 e avoided through surplus heat utilisation. The carbon abatement cost is estimated at £226 per t CO 2 e, primarily driven by capital (38%), operational (32%), and electricity (30%) costs. Sensitivity analysis highlights that straw availability, determined by both yield and crop rotation, is the primary factor influencing system performance. Among the mitigation strategies for addressing heat shortfalls, procuring external straw is identified as the most effective option. This study presents a novel and adaptable system framework for on-farm biochar deployment, addressing key barriers to implementation. The findings provide quantitative insights into the trade-offs between cost, carbon removal, and design decisions, and offer a foundation for scaling biochar use across the agricultural sector. Graphical Abstract

Background/Objectives: Bone grafting is fundamental in oral implantology in order to achieve appropriate esthetic and functional results. One of the options for bone grafting is the use of allografts, which can be produced using femoral heads removed during orthopedic surgeries in accordance with the principles of the circular economy. The aim of this study is to examine the environmental impacts of the production of cancellous block and granulates of bone graft materials produced in this way. Methods: The cradle-to-gate life cycle assessment was performed at the Petz Aladár University Teaching Hospital Tissue Bank Department, Győr, Hungary, with the system boundaries defined and the bone graft material produced during a production process defined as a functional unit. The environmental impacts were determined with the OpenLCA v2.5.0. software, using the ReCiPe v1.03 2016 midpoint (H) and endpoint (H) assessment methods. Results: During the production process, 500 g of bone graft material is produced in both forms, packaged as 1 g. The carbon footprint of the production of the cancellous bone block was 88,972 kgCO2-Eq, while that of the bone granulates was 100,033 kgCO2-Eq, to which the chemicals used for the degreasing and deantigenization of the bone tissue contributed the most. Within the impact categories, the material resources of metals–minerals, terrestrial ecotoxicity and climate change contributed the most to the environmental impacts. Within most impact categories, electricity was the most significant influencing factor. Conclusions: The environmental impact of the production of bone substitute granulates is greater than that of the bone block, to which the packaging of the products contributes primarily.

The sustainability of wild captured fisheries has historically been examined through the concept of overfishing. But this limited approach is becoming inadequate. This narrative systematic review synthesizes peer-reviewed literature and institutional reports published between 2002 and 2025, with particular emphasis on studies from 2010–2025, addressing the environmental footprints of marine capture fisheries. The study critically synthesizes the global literature to bring attention to effects that stretch far beyond population trends. It is not limited to carbon and energy footprints, but also extends to the local and global impacts in terms of marine habitat loss, biotic stress on ecosystems and effects at higher levels of biodiversity and trophic structure. There is also a focus on the fishing fleets' high carbon dioxide emissions, which are one of the key but overlooked sources of greenhouse gases. The paper also considers the severe and enduring impact of mobile bottom-contacting gears on benthic ecosystems. Habitat modification, sediment erosion and removal of biogenic structures appear as continuous problems. Simultaneously, the widespread issue of by-catch is considered, and its impact on a wide variety of non-target species including endangered and protected ones. In addition to direct impacts, the review deals with cumulative and indirect pressures related to fishing. These include marine plastic pollution from abandoned, lost or discarded fishing gear (ALDFG). The interaction of fisheries with other anthropogenic pressures, particularly climate change, is also investigated, uncovering multiple and complex feedback loops that compound risk to species. Methodological solutions for measuring environmental footprints are reviewed, with particular focus on Life Cycle Assessment (LCA). The most recent methodological innovations are reviewed and compared with long-standing challenges, concerning data availability, system boundaries, spatial resolution and beyond. Nevertheless, LCA is an indispensable method to make such comparative environmental analyses. The synthesis illustrates a large variability within and between gear types, regions, fisheries. This diversity highlights the shortcoming of one-size-fits-all approaches to management. Context-specific strategies are therefore essential. The review concludes that a holistic, ecosystem-based approach to fisheries management is imperative. This approach will need to build on a sound knowledge of environmental footprints but also conform to global sustainability targets, such as the United Nations Sustainable Development Goals 12, 13 and 14. Aligning these requires a shift from single-species evaluations to holistic methods that fully consider the collective effects of fishing on ocean systems.

Haemodialysis (HD) and online haemodiafiltration (OLHDF) are the main in-centre treatments for kidney failure. Both rely on high water and energy use and produce substantial greenhouse gas emissions. OLHDF provides superior solute clearance and improved survival compared with high-flux HD, but its environmental burden remains less defined. Clarifying these differences supports evidence-based and sustainable treatment decisions. A process-based life cycle assessment (LCA) was performed at the Nephrology, Dialysis and Kidney Transplant Unit, AOU Policlinico di Modena, Italy, in 2024, following ISO 14040 and 14,044 standards. The functional unit was one patient year of treatment, equal to 156 sessions. System boundaries included procurement, water treatment, session operations, travel and waste management. Modelling used OpenLCA with Ecoinvent 3.11 and the Italian electricity grid factor of 0.25kg CO2 per kWh. Scenarios assessed HD-only, OLHDF-only and the real-world Modena treatment mix. Sensitivity analysis varied the share of OLHDF, session frequency, grid intensity and reverse-osmosis (RO) recovery rate and included a reduced-flow OLHDF prescription. The annual footprint was 4469kg CO2-eq, 60,290MJ and 1364 m3 world-eq deprived water per patient year. HD generated 4427kg CO2-eq and OLHDF 4548kg CO2-eq, reflecting slightly higher electricity and water consumption and greater plastic use in OLHDF. Travel contributed 71% of total emissions and procurement 21%. Sensitivity analysis showed changes in RO efficiency and electricity mix had stronger effects than treatment type. HD and OLHDF have comparable environmental profiles. Clinical outcomes should drive modality choice, while sustainability gains depend on improving transport, water recovery, energy management and renewable integration.

Tempe production at the micro, small, and medium enterprise scale may cause environmental impacts due to water and energy use at each production stage. This study analyzes the environmental impacts of tempe production at Bapak Amin’s MSME using the Life Cycle Assessment method. The system boundary was defined as gate to gate with a functional unit of 1 kg of tempe. Environmental impacts were assessed using the ReCiPe 2016 Midpoint (H) model through characterization and normalization. The results show that the boiling process contributed 7.61 × 10⁻² kg CO₂ eq to GWP, 5.206 × 10⁻² m³ to WCP, 3.44 × 10⁻⁶ kg P eq to MEP, and 9.35 × 10⁻¹⁰ kg CFC-11 eq to SOD. The soaking process contributed 2.52 × 10⁻³ m³ to WCP and 1.58 × 10⁻⁵ kg P eq to MEP, while the grinding process contributed 4.25 × 10⁻⁴ kg CO₂ eq to GWP. Soybean washing showed the highest WCP contribution at 5.28 × 10⁻³ m³ and was identified as the main hotspot due to high water use. These findings provide a basis for improving more sustainable tempe production at the MSME scale.

A two-parameter environmental (measured in CO2eq—CO2 is used in this paper to represent the carbon dioxide molecule as opposed to the chemical formula CO2 as is common practice in LCA studies; CO2eq is an abbreviation for CO2 equivalent and may be written as CO2e in the literature) and economic (measured in USD) analysis using life cycle analysis (LCA) and techno-economic analysis (TEA) of repurposed wind turbine blades for structural use in recreational trail bridges (e.g., on hiking trails and golf courses) is described in this paper. The US Department of Energy’s TECHTEST TEA/LCA software (v1.0) platform was used to compare three commercially available trail bridges (a steel truss bridge, an FRP pultruded truss bridge, and a glulam stringer bridge) with a bridge made from retired wind turbine blades (known as a BladeBridge). All bridges had a 50 ft (15.24 m) long by 6 ft (1.83 m) wide deck and were designed for a 90 psf (4.3 kN/m2) live load. The LCA functional unit was the assembled bridge, which was made ready to be shipped from the fabricator. Cradle-to-gate (A1–A3, i.e., raw material extraction, transportation, and manufacturing) system boundaries were used. For the BladeBridge, no embodied carbon was attributed to the blade itself (cut-off system allocation). For the TEA, a USD 660/tonne credit was attributed to the blade. The raw materials for each bridge were determined from detailed construction documents. Manufacturing and transportation energy were determined based on the equipment used for fabrication and geographical location. Direct labor for fabrication was calculated based on a weighted average of salaries taken from the US Bureau of Labor Statistics. The results indicate that raw materials had the biggest effect on embodied CO2eq and that labor had the largest impact on cost for all bridges. The results indicate that the BladeBridge is significantly less expensive to produce and releases less CO2eq into the environment (less Global Warming Potential (GWP)) than the three commercially available bridges. Additional TEA metrics for the BladeBridge, including Technology Readiness Level (TRL) and future market potential, were also evaluated and found to be positive for the BladeBridge technology.