Search Results (464)

The construction sector is central to achieving the objectives of the European Green Deal (EGD). While existing research on transition risks predominantly focuses on project- or firm-level challenges, less is known about the transition risks implied by high-level EU policy documents. This study addresses this gap by systematically analysing 101 EGD-related policy and guidance documents published between 2019 and February 2025. A mixed human–AI content analysis approach was applied, combining human expert manual coding with automated validation using large language models (Kimi K2 and GLM 4.6). The final dataset contains 2752 coded risk references organised into eight main categories and twenty-six subcategories. Results show that transition risks are most frequently associated with environmental, economic, and legislative domains, with Climate Change Impact, Cost of Transition, Pollution, Investment Risks, and Implementation Variability emerging as the most prominent risks across the corpus. Technological and social risks appear less frequently but highlight important systemic and contextual vulnerabilities. Overall, analysis of the EGD policy texts reveals the green transition as being constrained not only by environmental pressures but also by financial feasibility and execution capacity. The study provides a structured, policy-level risk profile of the EGD and demonstrates the value of hybrid human–LLM analysis for large-scale policy content analysis and interpretation. These insights support policymakers and industry stakeholders to anticipate structural uncertainties that may affect the construction sector’s transition toward a low-carbon, circular economy. Full article

In the context of China’s dual-carbon agenda and the Digital China initiative, elucidating the role of digital literacy in shaping consumption-based household carbon emissions (HCE) is essential for advancing low-carbon urban living and supporting a broader green transition. Existing research has rarely examined, at the individual level, how digital capability shapes household consumption decisions and the structure of carbon emissions. Accordingly, this study draws on matched household-individual microdata from the China Family Panel Studies (CFPS). We employ a two-way fixed effects model, kernel density analysis, and qualitative comparative analysis. We test the nonlinear effect of digital literacy on household consumption-related carbon emissions and examine its heterogeneity. We also examined the mediating role of perceived environmental pressure, social trust and income level. The research results show that: (1) The net impact of digital literacy on carbon emissions related to household consumption shows an inverted U-shaped curve, rising first and then falling. When digital literacy is low, it mainly increases emissions by expanding consumption channels, reducing transaction costs and improving convenience. Once digital literacy exceeds a certain threshold, the mechanism will gradually turn to optimize the consumption structure, so as to support the low-carbon transformation of individuals. (2) The impact of digital literacy on HCE is structurally different in different types of consumption. In terms of transportation and communication expenditure, the emission reduction effect is the most significant, and with the improvement in digital literacy, this effect will become more and more obvious. For housing-related consumption, the turning point appeared the earliest. With the improvement in digital literacy, its effect will enter the emission reduction stage faster. (3) Digital literacy can reduce carbon emissions related to household consumption by enhancing residents’ perception of environmental pressure and strengthening social trust. However, it may also increase emissions by increasing residents’ incomes, because it will expand the scale of consumption, which will lead to an increase in carbon emissions related to household consumption. (4) The heterogeneity analysis shows that as digital literacy improves, carbon emissions increase more strongly among rural residents, people with low human capital, low-income households, and women. However, the turning-point threshold for emission reduction is relatively lower for women and rural residents. (5) Low-carbon transitions in household consumption are shaped by dynamic interactions among multiple factors, and multiple pathways can coexist. Digital literacy can work with environmental responsibility to endogenously promote low-carbon consumption behavior. It can also, under well-developed infrastructure, empower households and amplify the emission-reduction effects of technology. Full article

Digital twin technology is widely promoted as a transformative step for precision livestock farming, yet no fully realized, engineering-grade digital twins are deployed in commercial dairy or poultry systems today. This work establishes the current state of knowledge on dairy and poultry digital twins by synthesizing evidence through systematic database searches, thematic evidence mapping and critical analysis of validation gaps, carbon accounting and adoption barriers. Existing platforms are better described as near-digital-twin systems with partial sensing and modelling, digital-twin-inspired prototypes, simulation frameworks or decision-support tools that are often labelled as twins despite lacking continuous synchronization and closed-loop control. This distinction matters because the empirical foundation supporting many claims remains limited. Three critical gaps emerge: life-cycle carbon impacts of digital infrastructures are rarely quantified even as sustainability benefits are frequently asserted; field-validated improvements in feed efficiency, particularly in poultry feed conversion ratios, are scarce and inconsistent; and systematic reporting of failure rates, downtime and technology abandonment is almost absent, leaving uncertainties about long-term reliability. Adoption barriers persist across technical, economic and social dimensions, including rural connectivity limitations, sensor durability challenges, capital and operating costs, and farmer concerns regarding data rights, transparency and trust. Progress for cows and chickens will require rigorous validation in commercial environments, integration of mechanistic and statistical modelling, open and modular architectures and governance structures that support biological, economic and environmental accountability whilst ensuring that system intelligence is worth its material and energy cost. Full article

The paper presents a comparative economic and environmental assessment of high-temperature steam turbine technologies (subcritical, supercritical, ultra-supercritical, and advanced ultra-supercritical cycles) within the energy transition. The research employs a model-based analysis to evaluate the cost of electricity production across countries with divergent environmental, social and governance (ESG) strategies, reflected in their carbon pricing mechanisms. The developed model estimates the economic feasibility and optimal timing for the transition to high-efficiency technologies, based on the projected fuel cost dynamics. Within the framework of the model, the optimal energy transition timings for implementing advanced ultra-supercritical steam turbine technologies were established: 2031 for the energy transition model in the Russian Federation (a country with developing ESG principles) and 2018 for the model in the Czech Republic (a country with an emerging ESG strategy). The results indicate that while carbon pricing mechanisms influence economic feasibility, hydrocarbon fuel costs remain the predominant factor. The study concludes that the enhancement of conventional generation technologies aligns with all three pillars of the ESG framework and facilitates the transition to a sustainable development model for the energy sector and the national economy. Full article

This study presents an integrated Life Cycle Sustainability Assessment (LCSA) of the Natural gas-to-methanol (NGTM) and methanol-to-gasoline (MTG) pathways using Aspen HYSYS process modeling, Environmental Life Cycle Assessment (LCA), Social Life Cycle Assessment (SLCA), and Life Cycle Costing (LCC). The results reveal significant variability in sustainability performance across process units. The DME and MTG Reactors Section generates the highest direct greenhouse gas (GHG) emissions at 0.86 million tons CO₂-eq, representing 54.9% of total global warming potential, while the Compression Section consumes 2717.5 TJ/year of energy, making it the dominant source of electricity-related indirect emissions. Distillation and Purification withdraws 31,100 Mm³/year of water—approximately 99% of total demand—yet delivers 86.6% of the overall economic surplus despite high operating costs. Social impacts concentrate in the Methanol Reactor Looping and DME and MTG Reactors Sections, with human health burdens of 305.79 and 804.22 DALYs, respectively, due to catalyst handling and high-pressure operations. Sensitivity results show that methanol purity rises from 0.9993 to 0.9994 with increasing methane content, while gasoline output decreases from 3780 to 3520 kg/h as natural gas flow increases. The findings provide process-level evidence to support sustainable development of natural gas-based fuel conversion industries, aligning with Qatar National Vision 2030 objectives for industrial diversification and lower-carbon energy systems. Full article

With the growing trend of incorporating waste and industrial by-products in infrastructure, airport pavements built with sustainable materials are of increasing interest. This research developed six theoretical concrete mixtures for airport pavement and evaluated their financial, social and environmental cost within a stochastic triple bottom line framework. A Monte Carlo simulation was used to capture uncertainty in key parameters, particularly material transport distances, embodied carbon, and cost variability, allowing a probabilistic comparison of conventional and sustainable mixtures. The results showed that mixtures incorporating supplementary cementitious materials, recycled concrete aggregate and geopolymer cement consistently outperformed the ordinary Portland cement benchmark across all triple bottom line dimensions. Geopolymer concrete offered the greatest overall benefit, while the mixture containing blast furnace slag aggregate demonstrated how long haulage distances can significantly erode sustainability gains, highlighting the importance of locally available materials to sustainability. Overall, the findings provide quantitative evidence that substantial triple bottom line cost reductions are achievable within current airport pavement specifications, and even greater benefits are possible if specifications are expanded to include emerging low-carbon technologies such as geopolymer cement. These outcomes reinforce the need for performance-based specifications that permit the use of recycled materials and industrial by-products in pursuit of sustainable airport pavement practice. Full article

With the evolution of social structure and the intensification of population aging, traditional community service centers struggle to meet residents’ complex needs due to their functional singularity and spatial rigidity. In response to the continuously evolving social structure and functional requirements, this research proposes a strategy based on the “Separation of Support and Infill,” distinguishing between the building’s permanent Support Structure and its replaceable Infill Components. These two parts are combined with modularization to achieve long-term spatial adaptability and sustainability throughout the entire life cycle. In terms of functional space, through the combination of vertical stratification, horizontal staggering and spatial permeability, a three-dimensional composite space system is constructed, which not only enhances the functional flexibility but also improves the environmental performance. Taking a design case in Yicheng District, Zhumadian City as an example, through a comparative analysis with the traditional building model, the comparative analysis demonstrates that this framework increases the Floor Area Ratio (FAR) by approximately 0.15 compared to traditional models. Furthermore, the modular characteristics significantly enhance demountability and reusability, reducing construction and demolition waste while lowering life-cycle costs by an estimated 15% to 25%. These studies show that the support structure and the composite functional space system can not only promote social interaction and community cohesion but also reduce the life-cycle cost and carbon emissions. The framework proposed in this paper constructs a theoretical and practical system for sustainable community buildings from the perspectives of functional compounding and low-carbon community development. Its innovation lies in its flexible spatial organization mode and the enhancement of the sustainability of community buildings. Full article

Current food systems are highly complex, with interdependencies across regions, resources, and actors, and conventional food production is a major contributor to climate change. Transitioning to sustainable protein sources is therefore critical to meet the nutritional needs of a growing global population while reducing environmental pressures. Filamentous fungi present a promising solution by converting agro-industrial side streams into mycoproteins—nutrient-dense, sustainable proteins with a carbon footprint more than ten times lower than beef. This review evaluates the potential of mycoproteins derived from fungi cultivated on low-cost substrates, focusing on their role in advancing sustainable food systems. Evidence indicates that mycoproteins are rich in protein (13.6–71% dw), complete amino acids, fiber (4.8–25% dw), essential minerals, polyphenols, and vitamins while maintaining low fat and moderate carbohydrate content. Fermentation efficiency and product quality depend on substrate type, nutrient availability, and fungal strain, with advances in bioreactor design and AI-driven optimization enhancing scalability and traceability. Supported by emerging regulatory frameworks, mycoproteins can reduce reliance on animal-derived proteins, valorize agricultural by-products, and contribute to climate-resilient, nutritionally rich diets. Integration into innovative food products offers opportunities to meet consumer preferences while promoting environmentally sustainable, socially equitable, and economically viable food systems within planetary boundaries. Full article

The growing emphasis on sustainable manufacturing has motivated the integration of environmental and social factors into traditional assembly line balancing problems (ALBPs). This study introduces a Sustainable Mixed-Model Assembly Line Balancing Problem (S-MMALBP) that jointly considers task precedence, machine selection, worker allocation, carbon-emission control, and green-rating incentives. An exact optimization model is formulated to minimize total operating cost while satisfying sustainability and capacity constraints. To address the problem’s combinatorial complexity, an Adaptive Large Neighborhood Search (ALNS) metaheuristic is developed, incorporating customized destroy and repair operators, adaptive penalty updating, and a simulated-annealing-based acceptance criterion. An analytical lower bound is derived to evaluate the algorithm’s performance, and an enhanced constructive method, Precedence-Driven Task Grouping (PDTG), is proposed to generate high-quality initial solutions. Computational experiments on benchmark instances confirm that the ALNS achieves near-optimal solutions with deviations below 5% from the lower bound, while solving large instances within seconds. A real-world case study on aircraft assembly involving 166 tasks further validates the model’s applicability, achieving a cost deviation below 4% from the theoretical bound under realistic sustainability constraints. The results demonstrate that the proposed model provides an effective and scalable decision-support tool for designing environmentally and socially responsible production systems. The study is the first to incorporate sustainability and worker–machine decisions into a mixed-model ALB framework solved by a tailored ALNS and lower bound. Full article

South Africa’s persistent electricity shortages and recurrent load shedding remain among the most pressing challenges to national economic growth and social stability. This paper presents a techno-economic framework to assess how optimized deployment of photovoltaic (PV) and battery energy storage systems (BESSs) can mitigate these disruptions under realistic grid and regulatory constraints. Despite recent operational improvements at Eskom—including a 10-month period without load shedding in 2024—energy insecurity persists due to aging coal assets, limited transmission capacity, and slow renewable integration. Using hourly demand and solar-resource data for 2023, combined with Eskom’s load-reduction records, a Particle Swarm Optimization (PSO) model identifies cost-optimal hybrid system configurations that minimize the Levelized Cost of Electricity (LCOE) while maximizing coverage of unserved energy. Three deployment scenarios are analyzed: (i) constrained regional grid capacity, (ii) flexible redistribution of capacity across six provinces, and (iii) unconstrained national deployment. Results indicate that constrained deployment covers about 86% of curtailed load at 1.88 USD kWh⁻¹, whereas flexible and unconstrained scenarios achieve over 99% coverage at ≈0.58 USD kWh⁻¹. The findings demonstrate that targeted PV–BESS expansion, coupled with selective grid reinforcement, can effectively eliminate load shedding and accelerate South Africa’s transition toward a resilient, low-carbon electricity system. Full article

Care homes are an energy-intensive component of the health and social care sector, with high demands on heating, lighting, laundry, catering and medical technologies. This constant energy use makes care homes a notable contributor to global greenhouse gas emissions. Decarbonising care homes presents an opportunity to reduce emissions, operational costs, and deliver health co-benefits by improving air quality and thermal comfort. This scoping review mapped the international evidence on decarbonisation in care homes to inform sustainable practice and policy development. Guided by Joanna Briggs Institute methodology, seven databases (CINAHL, EMBASE, IEEE, MEDLINE, PubMed, Scopus, and Web of Science) were searched. Eligible studies included care home facilities, residents or staff with data managed in Covidence and extracted using the “The Greenhouse Gas Protocol Corporate Standard Inventory Accounting”. A total of 22 studies met the inclusion criteria. The evidence was concentrated around Scope 2 emissions, through efforts to monitor and reduce electricity use, while Scope 1 (facility emissions) and Scope 3 (supply chain emissions) remain comparatively underexplored. Evidence was fragmented and revealed risk aversion and care quality concerns related to adopting low-carbon technologies, as well as a growing interest in digital technologies and sustainable food procurement. Care homes should be prioritised within net zero healthcare frameworks, with targeted research, policy guidance, and investment to support decarbonisation. Full article

Breastfeeding is a renewable biological system that simultaneously advances human, environmental, and societal health. Human milk provides unparalleled nutrition and immunological protection, improving infant survival, neurodevelopment, and long-term metabolic outcomes, while reducing maternal risk of breast and ovarian cancer. However, and despite decades of evidence, only 48% of infants under six months are exclusively breastfed worldwide, and breastfeeding remains absent from most sustainability and One Health strategies. This narrative review synthesizes evidence demonstrating that breastfeeding functions as a low-carbon, zero-waste food system that avoids greenhouse gas emissions, land conversion, water consumption, and biodiversity loss linked to commercial milk formula production. At the societal level, breastfeeding reduces health-system costs, strengthens emergency resilience when supply chains fail, and generates long-term economic returns. By integrating evidence across human health, environmental impact and social determinants, this review positions breastfeeding as a strategic One Health intervention and a high-value investment for achieving multiple Sustainable Development Goals. Strengthening policy support—including protection against formula marketing, workplace accommodations, and expansion of baby-friendly systems—is essential to unlock breastfeeding’s potential for planetary and public health. Full article

The concept of carbon-neutral buildings encompasses not only carbon emission reductions but also sustainability. Building sustainability includes the physical durability of the structure, the health and safety of its tenants, and harmony with the surrounding environment. The achievement of these goals requires alignment among diverse stakeholders associated with buildings; however, such alignment is limited by economic (cost), environmental (global warming), and social (institutions and policies) factors. This study proposes an operation model that integrates buildings, the carbon permit market, and deep reinforcement learning (DRL) to address these limitations. The DRL model reduces energy consumption while maintaining indoor comfort, generates carbon permits equivalent to the amount of energy saved, and creates a new revenue stream by selling them. To achieve more precise comfort management, the model incorporates a policy that combines predicted mean vote (PMV) and Humidex. In the context of a privately owned commercial office building, the DRL model achieved indoor comfort levels of 98.51% for PMV and 97.22% for Humidex, while reducing energy consumption by 34,376 kWh, lowering carbon emissions by 26,607 kgCO₂eq, and generating USD 176 in carbon permit revenue. These results translated into a total reduction in operating costs of 7.5%, amounting to USD 2951. Consequently, the proposed approach provides cost reductions for building owners, comfort for tenants, efficiency for managers, and carbon emission reductions that contribute to carbon neutrality. Full article

Background: This paper develops a novel, interdisciplinary framework for optimizing high-speed rail (HSR) freight logistics hubs in the Ottawa–Quebec City corridor, addressing critical gaps in geospatial mismatches, static optimization limitations, and narrow sustainability scopes found in the existing literature. Methods: The research methodology integrates a hybrid graph neural network-reinforcement learning (GNN-RL) architecture that encodes 412 nodes into a dynamic graph with adaptive edge weights, fractal accessibility (α = 1.78) derived from fractional calculus (α = 0.75) to model non-linear urban growth patterns, and a multi-criteria sustainability evaluation framework embedding shadow pricing for externalities. Methodologically, the framework is validated through global sensitivity analysis and comparative testing against classical optimization models using real-world geospatial, operational, and economic datasets from the corridor. Results: Key findings demonstrate the framework’s superiority. Empirical results show an obvious reduction in emissions and lower logistics costs compared to classical models, with Pareto-optimal hubs identified. These hubs achieve the most GDP coverage of the corridor, reconciling economic efficiency with environmental resilience and social equity. Conclusions: This research establishes a replicable methodology for mid-latitude freight corridors, advancing low-carbon logistics through the integration of GNN-RL optimization, fractal spatial analysis, and sustainability assessment—bridging economic viability, environmental decarbonization, and social equity in HSR freight network design. Full article

This study presents an economic analysis of different end-of-life (EoL) strategies for light electric vehicles (LEVs). Utilising the case of a shared electric moped scooter, a cost–benefit analysis evaluates the profitability of three EoL scenarios. These scenarios encompass different combinations of R-strategies (reuse, repurpose, recycle), all of which have been shown to offer ecological saving potential in previous research. The net present value (NPV) of the current EoL treatment in Germany amounts to EUR 75.81 per e-moped, while alternative treatments which focus on repurposing the battery and increasing the number of components for reuse account for EUR 300.87 and EUR 379.01 per e-moped, respectively. In addition to providing in-depth insights into key cost factors (e.g., labour costs for disassembly) and benefits (e.g., sale of used components), this study includes sensitivity analyses. The scenarios differ in their sensitivity to changes in disassembly labour costs, spare parts revenue, and the social cost of carbon. Among all tested parameters, variations in the sale prices of components destined for reuse in the current EoL treatment scenario exhibit the highest influence on NPV, with a sensitivity coefficient of 1.43. Overall, component reuse emerges as a profitable EoL strategy, while battery repurposing appears promising for the future. Assuming a generally positive ecological impact of circular product systems for LEVs, this study also confirms their economic viability. From both economic and environmental perspectives, the findings of this study serve as a valuable catalyst for advancing circular product design, thereby facilitating the implementation of EoL strategies for LEVs. Full article