Search Results (6,028)

The housing sector in major cities is facing escalating challenges due to rapid population growth and land scarcity. Consequently, vertical growth has been adopted as a strategic solution to optimize land use while balancing economic, social, and environmental needs. This study examines the phenomenon of vertical growth of the Dammam Metropolitan Area (DMA) in Saudi Arabia, from an urban sustainability perspective, focusing on evaluating the current state of multi-story buildings, their determinants, and their impact on quality of life and infrastructure efficiency. This study utilizes a systematic review methodology and a conceptual approach to develop an integrated framework for sustainable vertical growth. Furthermore, an empirical validation was conducted by projecting this framework onto vertical housing projects in Dammam, focusing on challenges related to design, construction quality, shared service management, and the suitability of apartments for family needs. The results indicate that the shift toward vertical growth achieves land-use efficiency, limits random horizontal expansion, and provides economic opportunities. However, it faces social and cultural constraints, most notably the resistance of some families to changing traditional ownership patterns, limited privacy and green spaces, and challenges in building maintenance and operations. The study highlights the importance of integrating urban planning, governance, architectural design, and infrastructure to ensure the sustainability of vertical growth and provide suitable housing alternatives. The study recommends further field research to assess social acceptance, improve quality-of-life indicators, and develop policies encouraging sustainable vertical expansion in alignment with Saudi Vision 2030 and the 2030 Sustainable Development Goals (SDGs), ensuring cities are more resilient, efficient, sustainable, and liveable. Full article

This study presents a gate-to-gate life cycle assessment (LCA) of an industrial sweet cherry sorting and packing facility in Greece, directly addressing environmental sustainability in agri-food supply chains through data-driven impact quantification and improvement pathways in post-harvest operations. The assessment focuses on a gate-to-gate system boundary encompassing all processes inside the cherry sorting and packing facility, while upstream cherry production and downstream waste management are modeled and reported separately to provide system-level context. Core-stage hotspots are then analyzed in detail in the Results section, highlighting the dominant role of electricity use compared with packaging materials. The functional unit is defined as 1 kg of packed, market-ready cherries at the factory gate. Primary data are obtained from high-resolution, batch-level measurements of mass flows, energy use, water consumption, packaging materials and waste streams over a full processing season, structured as virtual sensor outputs. These sensor-informed operational data are combined with secondary life cycle inventory information from established databases to quantify climate change impacts and identify environmental hotspots across materials, energy, water, and waste, thereby delivering a quantified picture of environmental performance in the post-harvest stage. The results show that corrugated cardboard and associated packaging components are among the main contributors within the facility-level, gate-to-gate system, while the Core stage accounts for 28.43% of total GWP100. Upstream cherry production dominates the overall Upstream–Core–Downstream climate footprint with 70.61% of total impacts. Moreover, practical mitigation scenarios are modeled, including packaging optimization, partial substitution of grid electricity with photovoltaic generation, and increased water recirculation. Ιn the combined mitigation scenario, where packaging optimization, low-carbon electricity and improved water management are implemented simultaneously, total GWP100 decreases from 114,207.32 to 92,500.27 kg CO₂-eq (−19.0%) relative to the baseline, providing actionable sustainability improvements for industry stakeholders and supporting Sustainable Development Goals (SDGs) related to climate action and resource efficiency. In addition, the proposed virtual sensor architecture and data workflow support continuous monitoring, eco-efficiency management and near-real-time LCA implementation in post-harvest agri-food systems, enabling operational sustainability. Full article

The economic resilience of agricultural enterprises is increasingly relevant for maintaining processing continuity and food quality in highly perishable agro-food chains. This study examines the associations between financial knowledge, financial management competency, business liquidity, and operational food-processing continuity in Türkiye’s tea sector. A quantitative cross-sectional design was employed, using structured survey data from 203 senior managers across 86 public and private tea-processing firms in Rize Province. The data were analysed using Ordinary Least Squares regression, mediation analysis, exploratory factor analysis, and robustness checks in accordance with OECD/INFE guidelines. Results indicate a significant deficit in theoretical financial knowledge (mean score: 4.47/10) alongside widespread overconfidence among 85% of managers. Applied financial management competency is positively associated with perceived business liquidity (β = 0.336, p < 0.001), suggesting that practical budgeting, cash-flow planning, and financial decision-making capabilities are relevant to maintaining operational funding capacity. In contrast, cash-flow difficulties are not significantly explained by firm-level financial knowledge, managerial competency, liquidity, or ownership structure (R² = 0.014, p = 0.722), indicating that these difficulties may reflect broader seasonal and sector-wide financing constraints. The findings challenge the assumption of a linear relationship between theoretical financial knowledge and managerial outcomes. They suggest a dual policy approach that combines applied financial management training with structural financing mechanisms to ensure the continuity of fresh leaf procurement and processing. While the study does not directly measure food safety, post-harvest losses, or SDG outcomes, the results have potential implications for reducing processing disruptions and supporting more resilient agro-food processing systems. Full article

Artificial intelligence has become constitutive of smart city governance, yet data and algorithmic challenges remain analytically separated in existing scholarship, obscuring their recursive coupling and consequences for the built environment. This review synthesises 82 peer-reviewed studies (2020–2025) drawn from a deduplicated corpus of 876 records, combining PRISMA-guided methodology with VOSviewer and CiteSpace bibliometric mapping. Annual output rose from 78 publications in 2020 to 224 in 2024, with ten leading countries contributing roughly 84% of the corpus. The keyword network organises into five thematic clusters spanning AI technical foundations, data governance, algorithmic governance, sustainability, and built-environment governance; emerging 2023–2025 couplings between digital twin and SDG 11, and between generative AI and SDG 11, mark a shifting research frontier, while the algorithmic governance → SDG 16 linkage constitutes the strongest single ribbon in the synthesis. The study advances a double-helix coupling mechanism specifying directional propagation, reverse modulation, and structural cross-linking between data and algorithmic strands, reframing building energy management, digital-twin operation, and smart infrastructure as governance arrangements whose sustainability legitimacy depends on the simultaneous integrity of both strands. Full article

Podophyllum hexandrum Royle (1834) (Himalayan Mayapple), a key Himalayan medicinal plant and source of podophyllotoxin for anticancer drugs, is declining due to overharvesting, habitat loss, and climate change. This study, conducted from May to September 2024 across nine populations in Swat, Pakistan, assessed its ethnobotanical importance and conservation status. A total of 331 participants (270 individual surveys + 61 group discussions) were included. Using ethnobotanical surveys, IUCN-CMP threat frameworks, and spatial analysis, results showed high cultural value (Use Value = 0.63–0.92) and strong consensus for rheumatism (ICF = 0.91) and fever (ICF = 0.89). Fidelity levels were 94% for rheumatism and 88% for fever. Only 35% of respondents demonstrated conservation awareness. Overharvesting was the main threat, followed by habitat degradation and climate change. The species showed restricted distribution (EOO = 4250 km²; AOO = 295 km²), high fragmentation (0.68), and a 35% population decline over 10 years. It is assessed as Endangered (EN B1ab (iii, v)). This study provides the first integrated ethnobotanical–GIS assessment of P. hexandrum in the Hindu Kush–Himalaya region of Pakistan, offering measurable conservation baselines and community perception data previously unavailable. Findings align with global medicinal plant decline trends and support integration with CBD, SDGs (3 and 15), and potential CITES listing. Urgent conservation actions are required, including community-based management, habitat restoration, sustainable harvesting, ex situ conservation, and policy enforcement. Full article

Environmental degradation caused by unsustainable farming practices has depleted soil resources across sub-Saharan Africa. Conservation agriculture (CA) has been promoted to reverse this damage, yet outcomes remain variable, and the role of long-term training is underexplored. Using propensity score matching with 238 smallholder households across five communities in Ghana, we examine the impacts of long-term CA training. Specifically, we assess whether participation in a training program characterized by repeated engagement and follow-up workshops improves yields, farmer knowledge of soil health, and soil indicators (nitrogen and carbon). Farmers receiving long-term CA training did not exhibit significantly better soil chemical metrics. However, they demonstrated significantly more accurate knowledge of soil health (nitrogen, p < 0.001; carbon, p < 0.05), produced a 10.7% higher maize yield (kg/acre) (p < 0.001), and reported fewer soil problems, including fertilizer runoff, top-soil erosion, and waterlogging, compared to conventional farmers (all p < 0.05). We conclude that long-term CA training enhances farmer knowledge and maize yields, suggesting it is a critical intervention for improving productivity and farm management resilience, even where direct improvements in measured soil metrics are not immediately detectable. These findings highlight the need for training programs to emphasize the full suite of CA principles and for evaluation timeframes of 5–10 years to capture soil regeneration. Full article

Rice monoculture systems, often involving double- or triple-cropping cycles annually, require intensive agricultural practices that can lead to land degradation. This study evaluates land degradation within the long-term rice monoculture systems of Nakhon Sawan, Thailand, using the Sustainable Development Goal 15.3.1 framework. By focusing exclusively on persistent rice-growing areas, the study minimized the confounding signals of land-use conversion, allowing for an evaluation of the trajectories driven by combined agricultural management and climatic factors. The assessment integrated land use and land cover (LULC), soil organic carbon (SOC) stocks, and land productivity. Findings indicate that 83% of the original paddy area remained long-term monoculture, with LULC-related degradation limited to 4% of the original paddy cultivation area. While SOC depletion was observed in a few districts, a broader potential carbon accretion trend was identified across the province, likely driven by sustainable post-harvest practices such as stubble retention and organic amendments. Land productivity analysis revealed partial stress only in a few districts. The study demonstrated that long-term rice cultivation did not result in widespread deterioration of soil health on an aggregate provincial scale; however, district-localized degradation hotspots suffering from soil organic carbon depletion and climate-induced productivity stress were identified, demanding targeted regional management. Full article

Against the backdrop of rapid urbanization, urban land-resource use faces the dual challenge of improving efficiency while maintaining ecological sustainability. Enhancing urban land green use efficiency contributes to the achievement of the United Nations Sustainable Development Goals, particularly SDG 11 and SDG 15. As an emerging governance approach for urban green infrastructure, the National Sponge City Policy (NSCP) aims to address urban waterlogging through nature-based solutions while improving land multifunctionality and ecological carrying capacity. Based on city-level panel data from 2005 to 2022, this study employs a difference-in-differences (DID) approach to identify the policy effect of the NSCP on ULGUE and further examines three transmission channels: innovation effects, infrastructure-support effects, and population-agglomeration effects. The novelty of this study lies in integrating the NSCP into the analytical framework of urban land green use efficiency, extending previous research that mainly focused on waterlogging control, water-resource management, and ecological benefits, and further developing a “policy intervention-factor reallocation-ULGUE improvement” mechanism pathway. The empirical results show that the NSCP significantly improves land green use efficiency in pilot areas, and this conclusion remains valid across multiple robustness checks. The mechanism analysis indicates that strengthened green innovation capacity, improved green infrastructure, and population agglomeration are key channels through which the policy effect is realized. Heterogeneity analysis further reveals that the policy effect varies across regions, dominant industrial structures, and industrial-base types. Overall, the NSCP promotes green spatial governance and efficient resource utilization, providing important institutional experience for coordinating ecological protection and urban development. Full article

Food industry by-products represent an abundant and underexploited source of bioactive compounds, dietary fibers and proteins with significant potential for functional food development. Recent studies estimate that up to 30 to 50% of processed raw materials are discarded as by-products, while food waste contributes approximately 8–10% of global greenhouse gas emissions, equivalent to nearly 3.3 billion tons of CO₂ annually. This review critically evaluates advances (2015–2026) in the valorization of food industry by-products, with a focus on technological efficiency, health-related evidence, and environmental impact. Specifically, it addresses the following research question: to what extent do current valorization strategies provide measurable technological, nutritional, and environmental advantages over conventional food production systems? Emerging extraction technologies including ultrasound- and microwave-assisted extraction (20–40 kHz, 30–60 °C), supercritical fluid extraction (200–350 bar, 35–60 °C), enzymatic hydrolysis, and fermentation demonstrated improvements in extraction yields (up to 20–50% increases compared to conventional methods) and higher purity in the recovered compounds. These approaches enable the isolation of compounds such as pectins from citrus peels, polyphenols from grape pomace, galacto-oligosaccharides from dairy whey, and collagen from fish by-products. From an environmental perspective, valorization strategies can reduce waste disposal and associated emissions by up to 30%, depending on the scale and type of by-product processing. Furthermore, these approaches contribute directly to circular economy models and support multiple Sustainable Development Goals, particularly SDG 12 (responsible consumption and production) and SDG 13 (climate action). However, challenges remain, including variability in raw material composition, scalability limitations, and the limited availability of high-quality clinical evidence supporting health benefits. By integrating nutritional potential, technological feasibility, and sustainability indicators, this review provides a comprehensive and critical assessment of the current state of by-product valorization and identifies key gaps for future research. Full article

This paper develops a theoretical model to analyze the protective effect and nonlinear mechanism of preferential rules of origin (ROOs) on regional supply chains amid global value chain restructuring and rising regional supply chain security demands. Supported by numerical simulations and a triple difference-in-differences (DDD) empirical approach based on the China–ASEAN Free Trade Agreement (CAFTA), the findings reveal a nonlinear, inverted U-shaped relationship between ROO stringency and supply chain stability—exhibiting a typical Laffer curve characteristic. Moderate restrictions significantly promote intra-regional intermediate goods procurement and stabilize regional supply chain layout, while excessively stringent rules raise enterprise compliance costs and restrain integration. These findings carry important implications for regional economic resilience and sustainable development. While our empirical analysis focuses on economic resilience (measured through regional procurement stability), we discuss how well-designed ROO may also support broader sustainability goals, including contributions to SDG 8 (Decent Work and Economic Growth) and SDG 17 (Partnerships for the Goals) through more stable and inclusive regional production networks. The study highlights the need for careful calibration of ROO stringency to balance protective effects with compliance costs in pursuit of both resilient and sustainable regional trade governance. Full article

The development of sustainable and efficient plant growth substrates is crucial for modern agriculture. This study assessed the potential of plant pellets formulated from various lignocellulosic residues, either with or without bamboo biochar (BB-char) and arbuscular mycorrhizal fungi (AMF), to support seed germination and early seedling growth. Four types of residues, including coconut coir (CO), corn cob (CC), leaves from the genus Dipterocarpus (DL), and teak leaves (TL), were combined with soil and paper waste to produce eight pellet formulations, with commercial peat pellets serving as a control. Chemical analyses revealed significant variation among the pellet types, with pH values ranging from 6.40 to 7.65, electrical conductivity (EC) from 3.64 to 11.62 mS cm⁻¹, and differences in organic matter, carbon, and nutrient contents [nitrogen (N), phosphorus (P), potassium (K)], reflecting the influence of residue type and the addition of BB-char and AMF. Phytotoxicity screening using aqueous extracts demonstrated species-specific responses, with cucumber exhibiting high tolerance across treatments, whereas chili seeds were more sensitive. Final germination percentage (FGP) and seedling growth assays in greenhouse conditions showed that pellets derived from CC and CO, particularly when combined with BB-char and AMF (T6 and T7), enhanced shoot and root development in carrot, chili, cucumber, and tomato, approaching the performance of commercial peat pellets. In contrast, DL- and TL-based pellets resulted in lower germination and growth. These findings indicate that both the physicochemical properties of lignocellulosic wastes and the combination of BB-char and AMF are important factors influencing pellet efficacy, highlighting the potential of CC- and CO-based pellets as sustainable peat alternatives for early-stage plant cultivation. Full article

Failures in critical systems and equipment within nuclear power plants (NPPs) significantly threaten operational safety and reliability. Therefore, rapid and accurate root cause localization during the incipient stages of failure is critical to preventing escalation. Traditional modeling methods often fail to address the inherent structural complexity of NPPs, the diversity of failure modes, and the stochastic mapping relationships between symptoms and causes. To address these challenges, this paper proposes an intelligent fault diagnosis framework integrating knowledge graphs (KGs) and Bayesian networks (BNs). First, by analyzing failure modes and anomaly characteristics, we define discrimination criteria for typical faults. Second, a structured knowledge modeling approach is developed to transform unstructured fault information into a KG, which is subsequently mapped to a BN topology. Finally, to mitigate the subjectivity of expert priors, data-driven structure and parameter learning algorithms are employed to optimize the model, enhancing inference accuracy. Robustness was validated through experiments targeting three fault severity levels, using signed directed graphs (SDGs), support vector machines (SVMs), domain generalization softmax (DG-softmax) and long short-term memory (LSTM) as benchmarks. Experimental results demonstrate that the proposed method maintains high diagnostic precision across varying severities, outperforming traditional data-driven methods in accuracy and stability. This study enhances the interpretability and engineering applicability of intelligent diagnosis in nuclear power systems. Full article

The European Union (EU) and national governments have set clear targets to reduce agricultural emissions, including ammonia from manure spreading practice, with regulations such as the Ambient Air Quality (AQ) and Clean Air Directives, the Common Agricultural Policy (CAP), and the Green Deal, with implication for ecosystem services and landscape planning, reflecting broader environmental sustainability objectives including those addressed by the Sustainable Development Goals (SDGs). Informative Inventory Reports (IIRs) are critical tools within the EMEP/EEA framework for monitoring long-range transboundary air pollution. They utilize three distinct methodological tiers (Tiers 1, 2, and 3) to estimate emission data across Europe. Despite the availability of Earth Observation (EO) data and products from the Copernicus Programme current estimation methods still rarely integrate EO information to produce spatially explicit estimates. This paper reviews current methodologies for estimating ammonia in IIRs and in scientific literature, including advanced methods not yet implemented in official inventories but potentially capable of supporting more spatially explicit and process-oriented estimation. A Medium Effort Methodology (MEM) is identified among those reviewed as a representative methodological pathway for integrating EO information with Tier 3 approaches. Building on this, the paper explores the association between specific EO data and Copernicus products, and input variables required by MEM, identifying opportunities and barriers for environmental monitoring with potential relevance to sustainable agriculture. Full article

The ethical dimensions of sustainability can be overlooked by academics and project professionals despite ethics being relevant to the achievement of United Nations (UN) Sustainable Development Goals (SDGs). A survey of United Kingdom (UK)’s construction industry leaders is used to identify ethical challenges and solutions, while highlighting the link between sustainability, ethics and individual behaviour. A Theory of Planned Behaviour (TPB) approach is employed to scope out a series of ethical scenarios via an analysis of people, work tasks, culture and training, and subsequently validated via an industry workshop. It is argued that while project tools and techniques fail to engage adequately with ethical issues (e.g., stakeholder management), a proactive examination of attitude, norm, control and intention by project managers at appropriate project times can assist with the identification of potential ethical issues: a TPB-based prompt sheet being presented to assist project managers with their ethics work. The paper makes an original contribution that highlights the relationship between sustainability, ethical working practices and UN SDGs. Despite the relevance of ethics to SDGs, no prior study has used TPB to model ethical scenarios in construction project management. Full article

Narrowing urban–rural disparities and advancing the green transition are two key imperatives for sustainable development, yet the relationship between green finance and urban–rural integration remains insufficiently examined. Using panel data for 30 Chinese provinces from 2013 to 2022, this study investigates how green finance is related to urban–rural integration, with particular attention to nonlinear patterns, institutional conditions, and spatial dependence. The results show a positive association between green finance and urban–rural integration. This result remains stable across alternative specifications and various sensitivity checks, including lagged specifications, the Oster bounds test, and placebo tests. Panel threshold models show stronger evidence of nonlinear heterogeneity for innovation capability, while the rationalization of industrial structure threshold provides only suggestive evidence. Interaction models indicate that the interaction terms involving intellectual property protection intensity and marketization level are positive and statistically significant. Estimates from the spatial Durbin model further show that green finance is associated with significant positive net spatial spillovers across neighboring regions, with the model-based indirect effect exceeding the direct effect as a net spatial association after accounting for negative conditional spatial dependence in urban–rural integration. Overall, this suggests that green finance is relevant not only to environmental objectives but also to coordinated and sustainable urban–rural development, with implications for SDGs 10 and 11. Full article