Search Results (1,683)

This study presents the first cradle-to-gate life cycle assessment (LCA) of T-shirt production using viscose and Lyocell fibers, benchmarked against cotton and polyester under consistent system boundaries. The analysis covers spinning, knitting, wet processing, garment assembly, and regionalized energy supply. Results show that cotton T-shirts exhibit the lowest global warming potential (14.1 kg CO₂eq/kg) but the highest water demand (2.9 m³/kg) in China. Polyester garments, although less water-intensive, contribute significantly to plastic accumulation (1.0 kg/kg shirt) compared to cellulose-based fibers (0.1 kg/kg shirt). Within man-made cellulose fibers, Lyocell generally outperforms viscose in toxicity-related categories—reducing freshwater ecotoxicity by 35% and human non-carcinogenic toxicity by 62%—thanks to its closed-loop solvent recovery. However, Lyocell also shows the highest carbon footprint (21.6 kg CO₂eq/kg) unless produced in regions with cleaner energy mixes. Regional sensitivity analysis indicates that shifting production from China to Brazil could reduce global warming impacts by up to 38%. Overall, these results highlight the trade-offs across fiber types and demonstrate the importance of both material choice and production geography in driving sustainability within textile supply chains. Full article

Hybrid-electric propulsion and alternative energy carriers are being considered to mitigate the climate impact of short-range regional aviation. Within this framework, the HERA (Hybrid Electric Regional Architecture) project investigates advanced propulsion architectures for a next-generation 72 passenger regional platform. This work presents a cradle-to-grave Life Cycle Assessment of two HERA reference configurations and compares them with a conventional 70 passenger turboprop representative of current service aircraft. The analysis focuses on lithium–sulphur batteries, proton exchange membrane fuel cells, liquid hydrogen storage tanks, and electric motors. The assessment is implemented through a parametric LCA tool supported by a detailed Life Cycle Inventory based on Ecoinvent v3.8 and evaluated using ReCiPe 2016 midpoint indicators. The system boundary includes raw material extraction, manufacturing and assembly, operation under defined mission profiles, maintenance with component replacement, and End-of-Life (EoL) treatment. Results show that the operational phase remains the main driver of climate change impacts, exceeding 95% of total CO₂ equivalent emissions across configurations. The battery-based hybrid reduces fuel consumption but increases manufacturing and maintenance burdens. The fuel cell configuration shows a more balanced life cycle profile, with platinum identified as a critical hotspot. Full article

This study aims to show a detailed life cycle assessment (LCA) approach of battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs), with an emphasis on determining the electrical carbon intensity at which these vehicles reach life-cycle greenhouse gas (GHG) parity. The analysis was conducted in openLCA v2.0.3 using the Ecoinvent v3.9.1 database under a European use-phase context, with a functional unit of 150,000 km. BEVs were evaluated for two representative lithium-ion battery chemistries (NMC622 and LFP) under three electricity carbon intensity scenarios (50, 400, and 850 g CO₂/kWh), while ICEVs were modeled for both gasoline and diesel pathways. Results show that BEV life-cycle GHG emissions vary between 91 and 221 g CO₂-eq/km across different combinations of electricity mix, battery chemistry, and end-of-life conditions. When isolating electricity carbon intensity as the primary variable under a fixed BEV configuration, emissions increase approximately linearly with grid emission factor. Under average European electricity conditions (400 g CO₂/kWh), BEVs exhibit lower life-cycle GHG emissions than gasoline ICEVs, whereas under coal-intensive electricity conditions (850 g CO₂/kWh) this advantage may be reduced or reversed. The break-even electricity carbon intensity is derived by linear interpolation under a fixed BEV configuration (NMC622, 60 kWh, constant lifetime and EoL conditions), yielding a threshold of approximately 600 g CO₂/kWh. The results further indicate that this threshold is influenced by battery chemistry, production-related emissions, recycling efficiency, and assumed vehicle lifetime. These findings highlight the importance of simultaneous progress in electricity decarbonization and end-of-life recycling to secure the environmental benefits of vehicle electrification, and they provide a threshold-oriented framework for policy-relevant interpretation of comparative vehicle LCA results. Full article

Energy transition is most often examined through the lens of technological development and integration, including renewable energy sources, energy storage systems, and digital energy management solutions. In practice, however, the actual performance of energy systems—understood as both energy efficiency and environmental impact across the life cycle—depends not only on technical parameters but also on decision-making processes, operational practices, and management capabilities. This paper aims to conceptualize energy and environmental awareness as a determinant influencing energy system performance at organizational and system levels. The study is based on a structured review of the literature from energy engineering, life cycle assessment, and energy management, complemented by a comparative analysis of how similar energy technologies are utilized under different decision-making contexts. On this basis, an integrated analytical framework is proposed that combines conventional energy and environmental performance indicators with awareness-related dimensions, including energy knowledge, perception of environmental risk, and managerial competence. The analysis demonstrates that insufficient energy awareness leads to systematic gaps between the technological potential of energy systems and their actual performance, resulting in increased environmental burdens despite high nominal technical efficiency. The proposed framework helps to explain performance variability in energy systems operating under comparable technical conditions and highlights the importance of incorporating managerial and competency-related factors into life cycle assessments and energy transition policies. The paper contributes to the literature by extending energy system evaluation beyond purely technical criteria and offers practical implications for the design of energy systems, industrial energy management, and policy instruments supporting sustainable energy transitions. Full article

Under the global energy transition, liquefied petroleum gas (LPG) remains an important transitional fuel. However, persistent safety risks in storage and transportation continue to limit its sustainable development. This study aims to evaluate the sustainability of China’s LPG storage and transportation system and identify practical improvement pathways. A “1+4” C-STSM multidimensional framework was developed by combining accident fault-tree analysis, comparative review of domestic and international standards, and a systematic assessment of storage, transportation, monitoring, and safety technologies. The results show that the sustainability of LPG systems depends on the coordinated performance of infrastructure, transportation, monitoring, and safety barriers across the full supply chain. China has made progress in engineering facilities and safety management, but still faces weaknesses in intrinsic safety, barrier integrity, intelligent monitoring, and life-cycle governance. The main gap with international advanced practice lies in insufficient system integration rather than the lack of basic technologies. Improving LPG sustainability requires a coordinated pathway that combines safer infrastructure, intelligent monitoring, stronger barrier management, and better regulatory coordination. Such an approach can enhance industrial safety while supporting low-loss, low-emission energy transition. Full article

Background/Objectives: Given the narrow therapeutic range of tacrolimus and substantial inter-individual variability in trough levels, both total daily dose and the trough level-to-dose ratio are commonly used to guide dose optimization. In this study, Life-Cycle Pharma tacrolimus was compared with immediate-release tacrolimus in a real-world setting. Methods: This longitudinal observational study included kidney transplant recipients at two Hungarian university clinics. Sixty-three (63) patients completed the study and were included in the statistical analysis. They received either Life-Cycle Pharma-tacrolimus (n = 40) or immediate-release tacrolimus (n = 23) as maintenance therapy in the two study arms, each combined with everolimus or mycophenolic acid and corticosteroids. Patients were enrolled 4–6 weeks after transplantation and prospectively followed for 48 months. Tacrolimus trough level, total daily dose and their ratio were recorded at each of the seven follow-up visits during the 48-month study period. Epidemiological data, patient characteristics, laboratory parameters (including eGFR, de novo donor-specific antibodies, and CMV and BK virus incidence), and acute rejection episodes were monitored. Results: The mean age at enrolment was 53.35 years, and 41 patients (65.08%) were male. A stable therapeutic maintenance trough level was achieved in both study arms. Life-Cycle Pharma tacrolimus required a 30% lower total daily dose than immediate-release tacrolimus to achieve comparable exposure. A gradual decline in eGFR was observed in the immediate-release tacrolimus arm (a mean decrease of 6.06 mL/min/1.73 m² over 4 years) from a baseline level of 58.52 mL/min/1.73 m² (±16.69), whereas GFR increased in the Life-Cycle Pharma tacrolimus arm (a mean increase of 4.76 mL/min/1.73 m² over the same period) from a significantly lower baseline level of 46.55 mL/min/1.73 m² (±17.04). Conclusions: Both formulations provided effective long-term maintenance immunosuppression in kidney transplant recipients and maintained stable trough levels. Life-Cycle Pharma tacrolimus represents a potential option for dose minimization, and it also helped to stabilize renal function despite the worse baseline condition. Full article

Accurate prediction of the Remaining Useful Life (RUL) of lithium-ion batteries is essential for improving the reliability, safety, and maintenance planning of electric vehicles and energy storage systems. However, battery degradation is a complex and nonlinear process influenced by multiple operational conditions, making reliable RUL estimation a challenging task. Although numerous data-driven approaches have been proposed in the literature, many studies focus primarily on improving prediction accuracy using a single modeling technique, while limited attention has been given to systematic comparisons of different algorithms and the quantification of prediction uncertainty. This study proposes a comprehensive data-driven framework for lithium-ion battery RUL prediction by integrating both traditional machine learning and deep learning approaches. A Convolutional Neural Network (CNN) model is developed to capture nonlinear degradation patterns from battery cycling data. The dataset was divided using a battery-wise validation strategy to evaluate model generalization. In addition, conventional machine learning algorithms, including k-Nearest Neighbors (KNNs), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), are implemented to perform a comparative analysis of different predictive models. Key degradation-related features derived from voltage, current, temperature, and cycle information are extracted through a structured preprocessing pipeline. Furthermore, prediction uncertainty is quantified by constructing confidence intervals around the estimated RUL values. The predictive performance of the models is evaluated using prognostic metrics such as Root Mean Square Error (RMSE), Relative Prediction Error (RPE), and Prognostic Horizon (PH). The performance of the models is evaluated using multiple prognostic metrics, including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the coefficient of determination (R²), to ensure a comprehensive assessment of prediction accuracy. The experimental results demonstrate that the proposed framework provides accurate RUL predictions. Among the evaluated models, the CNN achieved the best performance with a Mean Absolute Error (MAE) of 7.75 and a Root Mean Square Error (RMSE) of 10.80, outperforming traditional machine learning models such as Random Forest and XGBoost. The KNN model also showed competitive performance with an RMSE of 12.07 and an R² value of 0.64, indicating that similarity-based learning can effectively capture battery degradation patterns. Full article

The durability of interior coatings is an important factor in the environmental performance of buildings, as the service life of the coatings directly determines the frequency of maintenance, material costs, and the overall life cycle impact. This study proposes the use of wet scrub resistance as a functional indicator of durability, providing an open dataset of commercial paints, analyzing their performance trends, and developing an integrated assessment framework. Data were collected through long-term tests according to EN ISO 11998 and EN 13300 standards from 2004 to 2025, ensuring the reliability and comparability of the results. The analysis shows that 56.8% of the tested paints met resistance class 1 and 31.5% met resistance class 2, meaning that these two classes account for almost 90% of all samples. Only around 10% of the paints were classified as class 3, while the share of the worst paints (classes 4–5) was only 1.6%. Long-term data show that class 1 has remained dominant for many years, exceeding 80% in some periods, but an increase in class 2 paints has been observed in recent years. The results of the study provide a quantitative basis for assessing the durability of coatings, allow for the prediction of maintenance intervals and analysis of technological advances, and facilitate data-driven decision-making, including the selection of sustainable building materials. The structured and standardized nature of the dataset also allows for its application in data-driven materials science, including the future development of machine learning models for predicting the durability of coatings and optimizing paint formulations based on sustainability criteria. Full article

Global climate change necessitates urgent carbon reduction, with the building sector being a major contributor. This study conducts a comprehensive life cycle carbon emission analysis of a nearly zero-energy office building in Shenyang, China, using the LCA theory and the carbon emission factor method. The calculation covers the production and transportation of building materials, construction, operation, and demolition stages. The results show that the building’s average annual carbon emission intensity is 56.36 kgCO₂e/(m²·a). The operation stage contributes the largest share, with an intensity of 37.83 kgCO₂e/(m²·a), primarily due to HVAC energy consumption. The material production and transportation stage follows, accounting for 31.67% of total emissions. Compared to conventional buildings, the proportion of operational emissions in this nearly zero-energy building is relatively lower, while the share from material production is significantly higher due to the use of high-performance insulation and components. Based on these findings, targeted carbon reduction strategies are proposed for each life cycle stage, emphasizing low-carbon material selection, renewable energy utilization, and efficient design. This study provides a quantitative reference for achieving carbon reduction goals in the building sector. Full article

Public transportation (PT) is key to breaking the vicious cycle of private vehicles, a critical sustainability challenge in developing countries. The increase in population raises the number of private cars, and this trend continues. PT plays a vital role in reducing car use, traffic congestion, and environmental pollution. Fare is crucial to the system’s ability to encourage passengers to use PT. It affects mobility, the quality of life, and the sustainability of the system. This study aims to examine Istanbul’s optimal fare system using the BWM (Best–Worst Method) for PT fare for the first time. Furthermore, it is the first study to compare fare structures and criteria for Istanbul, Europe’s second-largest city, where transportation affects quality of life. The most frequently used fare structures and criteria in the literature and practice were weighted by experts using BWM surveys for the Istanbul Metro. The results show that distance-based fare (DBF) (43.7%) is the best fare structure, while flat fare (FF) (12.2%) is the weakest. For the criteria weightings, benefit received (24.4%) and social equity (22.7%) are seen as superior. Finally, the impact of the criterion on the fare structure was demonstrated through analysis, and its importance for experts in evaluating PT was highlighted. Full article

This study compares hydrogen production pathways from water—using renewable-powered electrolysis (alkaline, water-based)—and biomass (gasification), under harmonized system boundaries and a common functional unit of 1 kg H₂ at 99.97% purity. It examines technological efficiency and environmental impacts, including cradle-to-gate Life Cycle Assessments (LCAs) of each pathway, focusing on global warming potential (GWP100), water consumption, land use, acidification, cumulative energy demand, and the critical minerals footprint. The analysis highlights the roles of water electrolysis and biomass gasification within South Africa’s energy landscape, considering the integration of renewable electricity, energy quality, and co-product allocation. Economic factors, such as the Levelized Cost of Hydrogen (LCOH), are evaluated alongside environmental indicators. The study emphasises the environmental challenges of biomass gasification, notably water use and emissions, and contrasts these with the climate benefits of renewable-powered electrolysis. It also reviews policy initiatives and government programs that support hydrogen and sustainable energy in South Africa, aligning with the SDGs. Overall, the findings underscore the trade-offs in hydrogen development, emphasising opportunities for resource utilisation while addressing deployment challenges. Full article

Livestock manure management contributes substantially to agricultural greenhouse gas emissions, making the adoption of low-carbon approaches urgent in ecologically sensitive regions. This study focuses on the County-wide Livestock Manure Resource Utilization Project in Danjiangkou City, the core water source area of China’s South-to-North Water Diversion Project. Based on field survey data, IPCC Guidelines, and a life cycle assessment framework, this study established a carbon accounting boundary covering excretion, collection, storage, treatment, and utilization stages. A scenario analysis was conducted to compare 2023 baseline emissions with 2026 project emissions and to quantify the carbon reduction potential. The research findings indicate that the overall carbon reduction rate following the project’s implementation reached 40.8%. However, the effectiveness varied considerably across the four management models. The Sedimentation–Crop Model and the Housing–Bedding Integrated Model, which employed integrated systemic interventions, achieved reductions of 61.50% and 60.09%, respectively. In contrast, the “124” Healthy Breeding Model and the Raised-Bedding Composting System, which relied primarily on single-stage upgrades, achieved reductions of only 32.04% and 27.70%. This disparity suggests that in decentralized livestock operations, isolated technological improvements fall short; meaningful decarbonization requires systemic interventions across the entire manure management chain. The findings provide a reference for low-carbon livestock manure management and regional development in ecologically sensitive areas. Full article

In municipal wastewater treatment plants (WWTPs), anaerobic digestion of municipal mixed sludge (MMS) often yields low energy recovery and operational instability due to imbalances between primary and secondary sludges. Anaerobic co-digestion (AcoD) with readily biodegradable wastes, such as fruit and vegetable waste (FVW), can enhance process stability and biogas production. Life cycle assessment (LCA) methodology is used in this study to evaluate the environmental performance of implementing AcoD of MMS and FVW in a municipal WWTP, compared with a business-as-usual scenario combining mono-digestion of MMS and incineration of FVW. The LCA was modelled in openLCA 2.5 using the ecoinvent 3.9.1 database (cut-off allocation approach), and impacts were assessed with the ReCiPe 2016 Midpoint (H) method, focusing on climate change, terrestrial acidification, fossil fuel depletion, and marine eutrophication. Results indicate that AcoD reduces impacts across all environmental categories, mainly due to higher biogas yields that increase on-site electricity generation and decrease reliance on grid electricity. Improved total solids removal also lowers digestate production and composting-related burdens. Electricity consumption remains the main hotspot in both scenarios, highlighting the importance of energy efficiency and electricity mix. Sensitivity analysis on methane content (61–65% v/v) confirms the robustness of AcoD’s environmental benefits. Full article

This study presents a comprehensive life cycle assessment (LCA) of 30 variants of pitched roofs compositions, focusing on global, regional, and local environmental indicators. The aim of this study was to quantify the environmental footprint of roof structures, comparing traditional technical solutions with modern systems using bio-based materials. The results show that the integration of solid wood elements and bio-based insulations significantly increases carbon sequestration potential, with the best identified composition showing a significantly negative GWP-total. A dynamic analysis of the optimal variant over time horizons of 50, 100 and 150 years, confirming the stability of environmental benefits in the long term, is presented. In order to achieve a global character, the best composition is modified and optimized for mild, cold and warm climate zones. The work provides important background for decarbonization of the construction sector and the design of adaptive, low-emission building envelope structures. Full article

Glass-Fiber-Reinforced Polymer (GFRP) bars are emerging as an alternative to steel reinforcement in concrete structures thanks to their high mechanical performance and intrinsic resistance to corrosion. Nevertheless, their actual sustainability must be verified through an assessment that considers long-term durability, life cycle environmental impacts, and economic feasibility. The replacement of steel reinforcement with GFRP in concrete bridge decks is herein evaluated through an integrated methodology. First, a comprehensive literature review examines the degradation processes observed experimentally and the associated long-term evolution of mechanical properties, providing the basis for defining realistic durability scenarios. Subsequently, a comparative Life Cycle Assessment is conducted adopting a cradle-to-grave system boundary and using Environmental Product Declarations to build the Life Cycle Inventory and perform the Impact Assessment. Normalization and weighting phases are included for a better understanding of the overall impacts of the two alternatives. In parallel, a Cost Analysis is performed consistently with the system boundaries and scenarios considered in the Life Cycle Assessment. Finally, the Envision protocol, a framework to evaluate sustainability and resilience of infrastructures, is applied to identify credits directly influenced by the adoption of GFRP reinforcement. The results show that steel reinforcement exhibits lower initial environmental impacts and remains more economical over short service life horizons. However, if the extended durability of GFRP is considered, the reduction in heavy maintenance activities allows this solution to achieve superior environmental performance and improved economic balance. The Envision-based evaluation further confirms the potential contribution of GFRP reinforcement to higher sustainability ratings in infrastructure projects. Full article