Search Results (7,183)

As declared in the European Green Deal, the decarbonization of the EU energy system is essential for achieving Europe’s climate neutrality targets, demanding a substantial expansion of renewable energy sources and the rapid phase-out of coal and gas. It is therefore essential that newly installed PV products within the EU are designed to avoid creating additional environmental burdens due to environmental impacts during production and at the end of life (EOL) of photovoltaic (PV) modules. This study presents a life cycle assessment (LCA) of sustainable/green PV module designs in terms of recyclability using advanced high-quality recycling technologies. It compares two product systems both based on mono c-Si PV technology and the glass–glass (G–G) module design: 1. Passivated Emitter and Rear Contact (PERC) and 2. Tunnel Oxide Passivated Contact (TOPCon) cell technologies, which are assessed under production scenarios in China and Germany, and two recycling scenarios (hypothetical high-recovery recycling and partial recycling) using inventory data from eco-invent and literature sources. The results across most impact categories show that the PERC and TOPCon module designs produced in Germany with high-recovery recycling as the end-of-life strategy exhibit lower impacts than those produced in China with partial recycling as the end-of-life strategy under the adopted assumptions such as electricity mix and end-of-life modelling choices for module-only impacts (excluding BOS components). The climate change results show that TOPCon cell design under high-recovery recycling yields 10.4% lower emissions than the PERC cell design under partial recycling in Germany and 9.7% lower in China. However, both module designs emit 26.6% and 27.2% less GHG emissions when produced in Germany compared to production in China, respectively, which is line with earlier studies. With the exception of human toxicity, both PERC and TOPCon cell technologies perform better in this study than previously reported in reviewed LCA studies, reflecting the use of more recent state-of-the-art industry data concerning manufacturing requirements. The sensitivity analysis carried out on the design changes and electricity grid mix available shows that any improvements in the design process and increases in renewable energy penetration into the grid corresponds to a proportional reduction in environmental impacts across all impact categories. Full article

This perspective focuses on the field of solid waste recovery and resource utilization for end-of-life (EoL) wind turbine blades. Wind energy plays a central role in the global transition toward low-carbon energy systems owing to its technological maturity, scalability, and widespread resource availability. As global installed wind power capacity exceeded 1000 GW in 2024, improving the life-cycle energy efficiency and resource productivity of wind energy systems has become increasingly important. In this context, wind turbine blades (WTBs), the most material-intensive components with high embodied energy, are approaching large-scale end-of-life replacement, with global EoL blade waste projected to reach 2–4 million tons by 2030. Although blades may reach the end of their structural service life, they contain substantial quantities of reinforcing fibers and polymeric matrices that embody significant material and manufacturing energy. Integrating blade recycling into the wind energy value chain represents a critical opportunity to reduce dependence on energy-intensive virgin materials and lower life-cycle energy consumption and associated carbon emissions. However, the realization of energy-efficient circular utilization remains constrained by several challenges, including inefficient heat and mass transfer during blade depolymerization, limited valorization of resin-derived products, and performance degradation of recovered fibers. This perspective examines the material characteristics of blades from a life-cycle energy utilization standpoint, assesses existing recycling pathways, and identifies key technological and system-level bottlenecks. Emphasis is placed on process intensification, product upgrading, and design-for-circularity strategies to support the long-term sustainability of wind power systems. Full article

This study investigates whether the optimal utilization of the biomass potential contained in municipal solid waste (MSW) can support the implementation of circular economy (CE) principles and contribute to climate policy objectives, particularly the reduction in greenhouse gas (GHG) emissions in the waste management sector. The analysis evaluates whether waste-to-energy recovery can support the objectives of the European Green Deal, including a 55% reduction in GHG emissions by 2035 and the achievement of climate neutrality by 2050. The assessment was conducted for two MSW streams generated in a Polish municipality: separately collected biowaste and residual MSW remaining after meeting European reuse and recycling targets. The study summarizes the results of detailed experimental investigations of the physicochemical and fuel properties of these waste streams. Proven and commercially available energy recovery technologies, including anaerobic digestion (AD) of biowaste and incineration of residual waste, were analyzed. GHG emissions were assessed using a life cycle assessment (LCA) approach, taking into account both direct emissions and avoided emissions resulting from the substitution of conventional energy and fertilizer production. The experimental results revealed significant variability in the biodegradability and energy potential of individual biowaste fractions, with the highest biogas yields observed for kitchen waste. Residual waste exhibited a considerable calorific value and a significant share of renewable energy due to its biomass content. The results indicate that the share of renewable energy in electricity generated from waste is expected to increase from 46.1% in 2025 to 49.9% in 2040. In relation to the total electricity demand of the analyzed city, energy recovered from waste accounts for 1.8 ± 0.3% in 2025 and 1.3 ± 0.2% in 2040. Scenario-based modeling demonstrated that the target system, maximizing energy recovery from both biowaste and residual waste, achieves a consistently negative GHG emission balance throughout the analyzed period (2025–2040), ranging from −72 ± 15 kg CO₂-eq/ton in 2025, through the most favorable value of −81 ± 17 kg CO₂-eq/ton in 2035, to −57 ± 12 kg CO₂-eq/ton in 2040, expressed per ton of total managed biowaste and residual waste. Full article

The holistic assessment of building life cycles requires integrating economic, environmental, and social dimensions, including occupational risks and cost management. However, building maintenance planning is often treated separately from sustainability assessment and construction cost classification systems. This study proposes a methodology that integrates maintenance and repair budgets with sustainability evaluation through a unified coding structure linking construction and maintenance work units. The approach combines economic cost analysis, environmental footprint indicators (carbon, water, energy, and ecological footprints), and occupational risk assessment within a life cycle framework. The methodology incorporates prevention through design by analyzing ergonomic and safety risks associated with construction work units and predicting future risks throughout the building’s service life. The structure has four phases: temporal planning of interventions, classification and coding of work units, impact analysis using sustainability indicators, and synthesis of results in a maintenance planning model. The data is integrated in a database using an exchange format compatible with sustainability analysis tools and BIM environments. The methodology is applied through a case study of social housing in Andalusia. Results show that maintenance interventions can be connected to construction work units in the assessment of the three dimensions. Full article

Traditional petroleum-based packaging suffers from pollution and functional limits, making it unsuitable for next-generation food systems. In contrast, bio-based smart packaging—combining renewable substrates with responsive components—transforms packaging from a passive shell into an active quality monitor and supply chain information node through three interconnected pillars: renewability, real-time responsiveness to freshness markers, and digital traceability. Market figures confirm this shift, with the smart food packaging sector projected to reach USD 48.97 billion by 2028 (CAGR 4.49% from 2023). This review covers recent progress in natural polymers (cellulose, chitosan, alginate, gelatin) and bio-based polyesters (PLA, PHA). Their multiscale structures enable tunable mechanical and barrier properties while serving as hosts for intelligent functions. Two functional directions stand out: active preservation (antimicrobial, antioxidant, gas-regulating, stimulus-controlled release) and intelligent sensing (colorimetric indicators, bio-based sensors, nano-amplified signals for real-time freshness monitoring). Beyond material functions, digital tools such as IoT and blockchain turn packaging into interactive data nodes, linking material intelligence with full traceability to enhance food safety and supply chain efficiency. Key challenges remain with long-term operational stability, production costs, scalable manufacturing, and life cycle assessments. Nevertheless, bio-based smart packaging is expected to evolve through biomimetic design, process innovation, and system-level integration toward adaptability, multifunctionality, and intelligence, ultimately supporting safer, more transparent, efficient, and sustainable food systems. Full article

The aim of this review is to provide a critical synthesis of peer-reviewed literature focusing exclusively on MSWI, rather than the broader field of Waste-to-Energy, based on a search in Scopus and a structured narrative synthesis. The methodology comprised eight Scopus queries defined for the main analytical axes of MSWI, deduplication, screening according to the established eligibility criteria, a layered corpus design, and domain-specific weighting of evidence within the framework of a structured narrative synthesis. This yielded 5435 unique records after deduplication, from which the main time window of 2010–2026 and a layer of publications from 2019 to 2026 were extracted. The review shows that the net balance of MSWI does not result from a single parameter or a single evaluation metric, but from the interplay between feedstock variability, combustion management, air pollution control (APC) configuration, residue management, and the utilisation of recovered heat and energy. Modern APC systems have reduced stack emissions, but do not eliminate the significance of transient states or the transfer of pollutants to fly ash and APC residues. Bottom ash exhibits conditional potential for material and metal recovery, whilst fly ash and APC residues remain the main constraint on recovery pathways. Environmental, climatic, health and economic assessments remain highly sensitive to system boundaries, functional units, counterfactual scenarios, the local energy mix, the quality of exposure reconstruction and integration with district heating. The added value of the review lies in maintaining MSWI as the sole analytical core and integrating the process, emissions, residues and system assessments within a single interpretative framework focused on comparability, trade-offs and the MSWI system balance. Full article

Background: Live-streaming e-commerce has emerged as a significant retail channel, especially in the apparel industry, characterized by high impulse-driven purchase rates and elevated product returns. Reverse logistics processes associated with these returns generate considerable environmental impacts that require systematic evaluation. Methods: This study performs a gate-to-gate Life Cycle Assessment (LCA) using SimaPro software, with a functional unit of 1 kg for one pair of returned jeans. Secondary inventory data were obtained primarily from the Ecoinvent database and supplemented with literature-based estimates for transport distances and packaging masses. Results: Key hotspots analyzed include transportation modes, packaging materials, and waste disposal pathways. Transportation mode selection was the dominant environmental hotspot, with air freight exhibiting the highest impacts across most midpoint and endpoint categories. Low-density polyethylene (LDPE) packaging and landfill disposal of textile waste were also major contributors to global warming, ozone formation, and resource depletion. Conclusions: The findings underscore the necessity of integrating Circular Supply Chain (CSC) principles into reverse logistics network design for live-streaming platforms. Optimizing transportation modes and packaging choices can effectively balance operational responsiveness with environmental sustainability. This study offers empirical evidence and practical decision-supporting insights for more sustainable return management in high-return digital retail environments. Full article

Data centers are essential to modern infrastructure, but are significant contributors to greenhouse gas (GHG) and related environmental challenges. Despite energy efficiency improvements, rising electricity demands driven by technologies like AI pose challenges to sustaining low-emission sector growth. Regulatory requirements mandate data center operators to report electricity use and emissions, yet current methods, particularly pertaining to indirect sources, remain insufficient. This study explores how life cycle assessment (LCA)-based estimates of data center IT equipment impacts compared with commonly used corporate GHG accounting methods: average-data and spend-based. Environmental impacts were modeled at both grouped and granular levels to support enterprise-wide reporting and operational decision-making. Sensitivity and uncertainty analysis validate the robustness of the LCA models. Scenario analysis was also conducted to assess emission abatement strategies, including on-site renewable energy generation and operation with a low-carbon electricity grid. The results show that the LCA approach produced emissions of 0.710 CO₂ eq/kWh, along with additional burdens that are not captured through carbon-only metrics. The LCA results are closely aligned with the average-data method (0.723 kg CO₂ eq/kWh) while the spend-based method yielded substantially higher estimates (1.07 kg CO₂ eq/kWh), highlighting the inaccuracies associated with volatile market prices. Scenario analysis identifies grid decarbonization as the most effective mitigation pathway, while also demonstrating environmental trade-offs across impact categories. Findings highlight the importance of comprehensive LCA-based assessment methods to improve emission reporting accuracy, transparency, and sustainability-focused decision-making in the data center sector. Full article

Reactive polymeric membranes are emerging as promising platforms for advanced water and wastewater treatment because they combine separation with in situ contaminant transformation. Unlike conventional membranes, which mainly retain pollutants, reactive polymeric membranes can enrich, activate, and degrade micropollutants during permeation through built-in radical, redox-active, conductive, or porous catalytic domains. This review discusses the development of intrinsic reactive polymer membranes for oxidative filtration, with emphasis on the links between polymer structure, transport behavior, reactive oxygen species generation, and degradation pathways. Key membrane classes are discussed, including stable-radical polymers, redox-active polymer networks, conductive polymer membranes, and porous conjugated polymer catalytic layers. The review also highlights the importance of reactive transport kinetics, including convection–diffusion–reaction coupling, residence time, Damköhler and Péclet numbers, and adsorption-enhanced degradation. Challenges such as fouling, polymer aging, leaching, byproduct formation, and toxicity-aware benchmarking are discussed within a broader roadmap for technology translation. The review identifies the grand challenges and milestone-based priorities for developing and deploying reactive polymer membranes, including performance targets, standardized reporting, realistic water matrices, scale-up, technology readiness levels, techno-economic analysis, life cycle assessment, artificial intelligence, and digital twins. Together, these elements guide the translation of reactive polymer membrane systems from laboratory research toward full-scale water treatment applications. Full article

Infrastructure maintenance and emergency repairs require rapidly setting cementitious materials, yet conventional cement presents issues of high energy consumption and substantial CO₂ emissions. Addressing this challenge, this research has developed a ternary alkali-activated cementitious material (CGFM) composed of calcium carbide residue (CCR), granulated blast furnace slag and fly ash. This study separately investigates the effects of CCR content (0–10%), alkali content (6–12%) and activator modulus (1.0–1.5) on workability and early mechanical strength. The hydration mechanism was examined through X-ray Diffraction (XRD), Fourier Transform Infrared (FTIR), Thermogravimetry-Derivative Thermogravimetry (TG-DTG) and Scanning Electron Microscopy-Energy Dispersive Spectroscopy (SEM-EDS) analysis, whilst life cycle assessment was employed to quantify the ecological impacts. Results indicated that a 3% CCR dosage significantly improved the gel structure, achieving a 7-day compressive strength of 69.8 MPa and a 37% increase in flexural strength. At a CCR dosage of 3%, alkali content of 8%, and modulus of 1.4, CGFM achieved a peak compressive strength of 80.2 MPa by the seventh day. This performance is attributable to its substantial gel content and high degree of polymerisation, which results in a dense structure. Life cycle assessment confirmed that compared to sulphoaluminate cement mortar, CGFM mortar reduced CO₂ emissions by 64.6% and energy consumption by 48.6%. Full article

As China’s urban renewal shifts comprehensively toward stock optimisation, everyday micro spaces in high-density old districts have emerged as critical yet underexplored carriers for rebuilding grassroots social capital. However, existing research remains largely confined to static assessments of physical form, lacking systematic insight into the process-based evolution of micro spaces and their governance implications. The aim of this study is to develop a process-based analytical framework that explains how everyday micro spaces emerge, evolve, and stabilise in high-density old urban districts, and to translate that explanation into stage- and type-differentiated governance pathways. Drawing on purposive sampling observation of over 170 micro spaces and snowball-sampled in-depth interviews with 45 residents in Xi’an’s walled historic district, this study employs thematic analysis to examine micro space formation, activation, and governance dynamics. A three-dimensional analytical framework of “Spatial Type–Perceived Need–Life Cycle” is constructed, classifying micro spaces into three categories, identifying a three-tier, nine-level perceived needs spectrum, and tracing a five-stage evolutionary process of Discovery–Activity–Renovation–Management–Identity. The findings reveal that residents’ spontaneous practices and psychological ownership formation are the core endogenous drivers of micro space evolution. The primary structural constraints are ambiguous property rights, institutional vacuums, and a structural rupture at the Renovation-to-Management transition, which we conceptualise as the “high-risk window period”. This study proposes a full life-cycle adaptive governance paradigm. Through phased, type-differentiated interventions, it matches governance supply to the evolving demands of each stage. The paradigm offers both theoretical and practical guidance for stimulating the endogenous vitality of everyday micro spaces in old urban districts. Full article

Corrosion-driven section loss in steel tower structures erodes load-carrying capacity, yet field assessment still relies on subjective visual grading. This paper presents a closed-loop framework coupling quantitative image-based corrosion measurement with stochastic degradation modeling, Monte Carlo reliability simulation, and Sobol’ variance-based global sensitivity decomposition. Two complementary segmentation paths—hue–saturation–value (HSV) color-space thresholding for fleet-scale screening and DeepLabV3+ deep learning for detailed evaluation—convert imagery into calibrated section-loss estimates via nonlinear regression. Three analysis modes (single-image, multi-angle weighted-median fusion, and Oriented FAST and Rotated BRIEF (ORB) feature-matched temporal differencing) feed a Bayesian-updated power-law corrosion growth model whose outputs propagate through a time-dependent limit-state function via 10⁶-sample Monte Carlo simulation. Sobol’ indices rank each uncertain input’s contribution to the reliability-index variance. A field demonstration on a 40-year-old galvanized lattice tower in an ISO 9223 C4 coastal environment shows that the corrosion rate constant and zinc coating thickness together govern 65% of the total reliability variance and that a risk-ranked selective maintenance strategy reduces expected life-cycle cost by 71% relative to blanket intervention. Full article

Against the backdrop of global climate change and the “dual carbon” goals, the issue of agricultural greenhouse gas emissions has garnered increasing attention. As a major grain and oilseed crop in China, carbon emissions from soybean production have a significant impact on the green and low-carbon development of agriculture. Although research on agricultural carbon footprints has grown in recent years, existing studies have largely focused on single regions or specific stages of crop production, and analyses of the carbon footprint of production systems in China’s major soybean-producing regions remain relatively limited. This study employs the Life Cycle Assessment (LCA) methodology to calculate and analyze the carbon footprint of soybean production systems across China’s 10 major soybean-producing provinces, utilizing agricultural input data from 2014 to 2023. The study establishes a carbon footprint accounting system based on two key aspects: carbon emissions from agricultural inputs and soil N₂O emissions. It further analyzes the temporal trends, regional variations, and contribution characteristics of each component within the carbon footprint. The results indicate that the average carbon footprint of soybean production in China is approximately 528 kg CO₂eq/ha (ranging from 273 to 855) and 0.25 CO₂eq/kg of soybean (ranging from 0.13 to 0.46). Specifically, the carbon footprint per unit of area and yield declined simultaneously, indicating a continuous improvement in the low-carbon efficiency of soybean production. Spatially, there are significant regional differences in the carbon footprint of soybean production. Henan, Anhui, and Inner Mongolia have relatively low carbon footprints, while Shaanxi and Shanxi have relatively high levels. In terms of composition, chemical fertilizer inputs and soil N₂O emissions are the primary sources of the carbon footprint in soybean production, with chemical fertilizer inputs being the largest source, accounting for approximately 40–60%, and soil N₂O emissions being the second major source. Overall, differences among regions in natural conditions, agricultural input structures, and production methods result in distinct regional characteristics in the carbon footprint composition. The findings of this study provide a scientific basis for the low-carbon transition of China’s soybean production system and serve as a reference for the formulation of policies related to green agricultural development. Full article

Driven by China’s “dual carbon” (carbon peak and carbon neutrality) goals and the national strategy of new-type urbanization, prefabricated construction has emerged as a pivotal pathway toward industrialized and sustainable development in the construction sector—leveraging its distinctive advantages in construction efficiency, cost optimization, environmental performance, and design adaptability. Nevertheless, the inherently sequential and interdependent nature of the full construction process—encompassing off-site component manufacturing, logistics transportation, and on-site assembly—introduces pronounced cross-stage risk transmission mechanisms, with prefabricated components serving as critical risk carriers. Such transmission dynamics significantly impede the scalable and safe deployment of prefabricated construction. To date, scholarly efforts on construction safety in prefabricated buildings have predominantly addressed isolated, stage-specific risks, falling short in quantitatively modeling the coupled propagation of risks across stages, accommodating epistemic uncertainties and latent (i.e., unknown or unobserved) risks, and informing targeted, evidence-based mitigation strategies. To bridge this gap, this study develops a rigorous quantitative framework for assessing cross-stage risk transmission in prefabricated construction safety. Specifically, it aims to (i) uncover the structural patterns and driving mechanisms underlying inter-stage risk propagation; (ii) reduce the likelihood of safety incidents throughout the construction life cycle; and (iii) deliver actionable theoretical insights and methodological guidance for practitioners and policymakers. Methodologically, we first conduct a systematic identification of safety-critical risk factors and establish a hierarchical risk indicator system comprising three first-level dimensions and twenty second-level indicators. Second, using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, causal relationships among risk factors are clarified, while incorporating the Leaky Noisy-or Gate (LNOG) extended model to account for unknown risks. Risk data are processed using triangular fuzzy functions, and a Bayesian network (BN) topology diagram is constructed via the GeNIe 5.0 platform, forming a DEMATEL-LNOG-BN-based model for assessing cross-phase risk transmission. Finally, applying the model to an actual project—”a prefabricated construction project in Shanghai”—the study conducts a cross-phase risk transmission analysis. Through forward probability inference, backward causality tracing, sensitivity analysis, and pathway decomposition, sensitivity comparisons are performed under different LNOG unknown risk parameters. Results are compared with those from the traditional DEMATEL-BN model to validate the stability and consistency of high-sensitivity risk factor identification, comprehensively verifying the applicability and predictive reliability of the proposed DEMATEL-LNOG-BN model. The study quantitatively reveals the progressive diffusion and amplification mechanisms of risks across the production–transportation–assembly process, providing scientific support and practical reference for precise safety risk prevention, critical node control, and the optimization of management systems in prefabricated construction sites. Full article

The recast Energy Performance of Buildings Directive (EPBD) accelerates the transition from nearly zero-energy buildings (nZEBs) to zero-emission buildings (ZEBs), requiring solar readiness and life-cycle Global Warming Potential (GWP) disclosure. Yet operational performance, future-climate adaptation and whole-life carbon (WLC) are still often assessed separately, limiting actionable evidence for residential ZEB design in northern climates. This study provides an integrated design-decision framework coupling annual IDA-ICE simulations under five weather scenarios, including Urban Heat Island (UHI)-adjusted present and 2080 RCP8.5 + UHI files, with an EN 15978/Level(s)-based WLC assessment in One Click LCA for twelve design cases of a Lithuanian dwelling. For the PV-equipped baseline, heating electricity decreases by 24% and cooling increases by 31% from present conditions to 2080 RCP8.5 + UHI. External shading and night purge provide the strongest annual cooling and operative-temperature-exceedance reductions. The ZEB baseline reduces WLC by 19.0% relative to A0; the biogenic-insulation green-roof case gives the lowest non-storage WLC (−25.2%); and battery-assisted cases provide the largest reductions under the static B6 electricity factor (up to −52.1%). The findings provide case-study evidence that EPBD-aligned residential ZEB design should evaluate passive cooling, PV/storage and material choices jointly, rather than sequentially, when developing future performance thresholds and design guidance. Full article