Search Results (28,806)

Biochar derived from açaí (Euterpe oleracea Mart.) processing residues represents a sustainable strategy to improve fertility and mitigate acidity in highly weathered tropical soils. This study evaluated the effects of açaí biochar (0 and 12 Mg ha⁻¹), combined with dolomitic limestone (0, 75%, and 100% of the recommended rate), on chemical, biological, and agronomic attributes of a clayey Ferralsol cultivated with cowpea (Vigna unguiculata (L.) Walp) in the Amazon. A field experiment was conducted in a randomized block design with six treatments and four replicates. Soil samples were collected from the rhizosphere and from the 0–5, 5–10, and 10–20 cm layers to determine pH, exchangeable Al, pseudo-total concentrations of K, Ca, Mg, total carbon (TC), organic carbon (OC), microbial biomass carbon (MBC), β-glucosidase, and cellulase activity. Biochar increased soil pH (0–10 cm), reduced exchangeable Al, and increased pseudo-total K throughout the soil profile, whereas liming primarily increased Ca and Mg availability and contributed to acidity correction. A significant biochar × lime interaction was observed for exchangeable Al in surface layers, while Mg responses varied depending on depth and treatment combination. Biochar also enhanced cellulase activity, total carbon (TC), and microbial biomass carbon (MBC), while reducing β-glucosidase in surface layers, with no effect on organic carbon (OC) determined by the Walkley–Black method. Cowpea grain yield increased by 16% with biochar and showed additive response to lime, reaching 1460 kg ha⁻¹ under combined application, 13.6% higher than lime alone. These results indicate that açaí biochar acts as a complementary amendment for improving soil fertility, biological functioning, and crop performance in acidic tropical soils. Full article

Photocatalytic extraction of uranium from radioactive wastewater is crucial for environmental safety and sustainable nuclear energy development. It is widely recognized that photocatalysts with donor-acceptor (D-A) or D-π-A structures exhibit enhanced charge separation efficiency, thereby showing excellent photocatalytic performance. Herein, we presented a counterintuitive design of a donor-donor covalent-organic framework (D-D COF) for efficient photocatalytic uranium extraction. A twisted D-D COF (COF-BCTB-Py) was synthesized via solvothermal condensation using bicarbazole and pyrene as dual electron-donor units. The COF featured a well-defined AA-stacked porous structure, high specific surface area (963 m²·g⁻¹), suitable band gap (2.44 eV), and exceptional chemical, thermal, and radiation stability. Impressively, in the presence of 5% methanol, it delivered an ultrahigh uranium uptake capacity of 4278 mg·g⁻¹ with fast kinetics and >97% removal efficiency in complex water matrices, challenging the traditional stereotype of low-activity D-D COFs. Mechanistic studies revealed that soluble U(VI) was converted into crystalline (UO₂)O₂·2H₂O via in situ generated hydrogen peroxide rather than being reduced to U(IV). This work provides an unconventional design strategy to design efficient photocatalysts for uranium recovery from nuclear wastewater. Full article

Illegal, unreported, and unregulated fishing threatens marine ecosystem health and sustainable fisheries management, highlighting the need for reliable fishing-vessel behavior recognition from Automatic Identification System (AIS) trajectories. However, AIS-derived operational states often exhibit overlapping motion patterns, particularly between Underway and Fishing and between Anchored and Moored. This study proposes FishFormer, a local–global spatio-temporal deep learning framework designed for recognizing four AIS-status-derived fishing-vessel operational states: Underway, Fishing, Anchored, and Moored. FishFormer integrates dual-stream spatio-temporal attention, local–global feature fusion, and feed-forward feature enhancement to capture long-range trajectory dependencies, local motion variations, and heterogeneous kinematic features. Experiments on 8139 real-world AIS trajectory segments from U.S. coastal waters show that FishFormer achieves 96.63% overall accuracy and an F1-score of 0.9661. Compared with seven baseline models under a unified experimental protocol, FishFormer shows superior recognition performance, while ablation, confusion-matrix, and robustness analyses further verify the effectiveness of the proposed modules and their contribution to reducing errors among similar behavior states. These results indicate that local–global spatio-temporal learning improves AIS-based operational-state recognition and can provide a behavioral information layer for fishing-vessel activity monitoring and fishery management decision support. Full article

(1) Background. Food sovereignty and local sustainability are ensured by large agro-industrial holdings and small-scale farms; this synergy forms a complementary model of the agrifood system. Maintaining this model’s balance requires the creation of a unified digital ecosystem that integrates all suppliers and consumers into production chains, thereby eliminating unnecessary intermediaries. (2) Methods. This study employs a comprehensive methodological framework, including systems analysis and mathematical modeling, to develop service algorithms. Object-oriented design and software engineering methods facilitated the development and implementation of a service-oriented architecture for the digital system. (3) Results. The study presents a multi-tier architecture featuring an integration bus based on a service-oriented approach. To implement direct supply-and-demand coupling strategies, the system integrates both internal services (microeconomic indicators) and external services (macroeconomic indicators). Additionally, a recommender system based on neural networks and mathematical models was developed to personalize consumer requests and manage product sales. (4) Conclusions. The software solution is consistent with the AgTech 4.0 concept and enables the creation of a seamless environment for interstate trade. The implementation of the system enhances the transparency of the “product footprint”, facilitates the redistribution of surpluses, and, consequently, contributes to price stabilization. Full article

Using liquid hydrogen (LH₂) in aviation creates a difficult design problem for cryogenic storage systems, especially in the early design stage. At that point, environmental, economic, and technical aspects need to be considered together. Here, a sustainability assessment framework is presented for LH₂ aircraft storage tank configurations from a life-cycle perspective. The study includes 24 design alternatives. These are obtained by changing the material combinations of the main structural components, while the overall tank architecture is kept unchanged. The environmental and economic dimensions are assessed through life-cycle assessment (LCA) and life-cycle costing (LCC), whereas the technical dimension is represented by the system mass. Since the relative importance of the criteria is usually not fixed at this stage, Unweighted TOPSIS (UW-TOPSIS) is first used to examine the alternatives under different weighting scenarios. The most competitive solutions are then re-evaluated by a standardised TOPSIS variant (vector-normalised weights, Z-standardised distances) with objective weighting methods. The results show that the configurations based entirely on Al2219-T8 for the main structural components remain top-ranked and more stable under the examined scenarios, whereas mixed-material configurations are more sensitive to changes in weighting assumptions. In this way, the exploratory stage is kept separate from the later weighting stage, where the weights are computed from the decision matrix of the reduced set. This is suitable for early aerospace design, where subjective preferences are often not yet available. Full article

Sustainable and resilient road infrastructure requires the early identification of pavement deterioration mechanisms that emerge under complex urban traffic conditions, particularly at signalized intersections where repeated stop–go operations, queue persistence, and lane-wise freight concentration generate highly nonuniform structural loading. However, most existing intelligent transportation studies emphasize crash prediction, traffic-state estimation, or mobility optimization, while the infrastructure-performance consequences of freight-dominant interrupted flow remain insufficiently addressed. To support proactive pavement management and resilient urban road operation, this study proposes a traffic simulation-driven deep learning framework for predicting lane-level pavement deterioration under freight loading and stop–go urban traffic conditions. A high-resolution PTV Vissim 2024 microscopic simulation environment was developed for a four-leg signalized urban intersection, and a structured multi-scenario design was used to generate progressively increasing operational stress regimes, ranging from baseline flow to freight-dominant oversaturated operation. The resulting lane-wise dataset integrates direct traffic variables with pavement-oriented descriptors, including the Lane Freight Loading Index (LFLI), Stop–Go Severity Index (SGSI), ESAL proxy, queue persistence, and Loading Asymmetry Index (LAI). To learn the complex relationship between traffic operation and infrastructure degradation, a new Freight-Aware Lane Interaction Transformer Network (FLIT-Net) is introduced. The proposed model combines feature embedding, lane-interaction self-attention, freight-aware gating, residual refinement, and multi-task regression to jointly predict rutting risk, fatigue-cracking risk, and the Pavement Deterioration Index (PDI). Experimental results show that FLIT-Net outperforms MLP, CNN, LSTM, Bi-LSTM, and generic Transformer baselines, achieving RMSE/MAE/$R^2$ values of 0.041/0.032/0.9687 for rutting risk, 0.044/0.034/0.9635 for fatigue-cracking risk, and 0.031/0.024/0.9824 for PDI. Sensitivity and scenario-wise analyses further confirm that deterioration increases monotonically with freight intensity, stop–go severity, and queue persistence, highlighting the importance of lane-resolved deterioration intelligence for sustainable maintenance prioritization. The proposed framework bridges traffic microsimulation, pavement-oriented feature engineering, and freight-aware deep learning, providing a decision-support basis for improving the performance, safety, and resilience of urban pavement infrastructure. Full article

This paper addresses the critical challenge of identifying cost-effective coalitions of social media influencers to promote environmental sustainability (ES) messages under budget constraints. Traditional influencer marketing often relies on heuristics that ignore relational dependencies and heterogeneous agent costs, leading to redundant coverage and suboptimal resource allocation. To overcome these limitations, we introduce a novel Relational Cooperative Game (RG) framework that formalizes pre-determined dependencies among influencers and followers using closure operators, enabling a portfolio of polynomial-time identification algorithms for Minimal Winning Coalitions (MWCs). We further extend this model to the Weighted Cost-Relational Game (WCRG) to optimize campaigns with heterogeneous influencer costs. We prove that finding a Minimum-Cost Winning Coalition (MCWC) is NP-hard via reduction from weighted set cover and propose two complementary algorithms: (1) a Greedy Cost–Benefit (GCB) algorithm that operates in polynomial time and empirically achieves optimal solutions across all tested instances; a logarithmic approximation guarantee is established for the restricted single-antecedent model; and (2) an Integer Linear Programming (ILP) formulation enhanced with Strongly Connected Component (SCC) preprocessing to handle cyclic dependencies and yield exact optimal solutions for moderate instances. Extensive empirical validation, ranging from a representative six-agent cyclic scenario to large-scale synthetic networks (up to 300 agents), confirms the framework’s robustness and scalability. Results demonstrate that GCB consistently achieves optimal solutions (approximation ratio = 1.000×) with subsecond runtime (<0.2 s) and minimal memory overhead (<50 MB), while ILP-SCC leverages graph condensation for rapid exact solving. Compared to size-based baselines, WCRG achieves up to 95.2% cost savings by systematically leveraging cost-efficient micro-influencers, empirically validating that minimizing coalition size does not guarantee cost efficiency. These findings establish WCRG as a scalable, budget-aware optimization toolkit for maximizing the impact of sustainability campaigns through relational coalition design. Full article

Understanding how economic growth (GDP), livestock production (LPI), agriculture, forestry and fishing (AFF), renewable energy consumption (REN), and urbanization (URB) influence carbon emissions is essential for designing effective climate policies in rapidly developing economies such as India. This study examines the long-run and short-run effects of these factors on CO₂ emissions in India during 1990–2024 using the Dual Adjustment Approach (DAA) and the Autoregressive Distributed Lag (ARDL) model. The DAA framework decomposes variables into permanent (trend) and transitory (cyclical) components, allowing a simultaneous assessment of long-run equilibrium and short-run dynamics. Both DAA and ARDL models indicate that GDP and LPI increase CO₂ emissions in the long run, while REN reduces them. AFF exerts a weak effect on emissions compared with the other determinants. URB is associated with lower long-run emissions, supporting the urban efficiency hypothesis, but this depends on sustained infrastructure investment and policy support, rather than automatic results of current urbanization levels. The transitory component analysis shows that short-run fluctuations in GDP increase emissions, while the effects of the remaining variables are driven by long-run structural changes. The findings highlight the importance of expanding renewable energy deployment, improving environmental efficiency in agricultural and livestock production systems, and promoting sustainable urban development to reduce carbon emissions in the case of India. Full article

Multilithologic interbedded reservoirs commonly consist of frequent alternations of fine-grained rocks, carbonate rocks, and soluble evaporite interlayers. The contrasts in mechanical properties and fluid–rock interactions tend to induce hydraulic-fracture deflection, height containment, and complex cross-interface propagation. To elucidate fracture initiation and cross-layer connectivity, a self-developed true-triaxial hydraulic fracturing simulation system was used to systematically investigate the effects of lithologic configuration, fracturing-fluid viscosity, injection rate, interface position, and injection-fluid type on fracture morphology and cross-interface behavior. Integrated analyses were performed by jointly interpreting injection-pressure responses and three-dimensional fracture reconstructions. The interactions between hydraulic fractures and lithologic interfaces/natural fractures can be categorized into three modes: (i) deflection with restricted growth, (ii) penetration without activation, and (iii) penetration with synchronous activation. Under water-based fluids, soluble evaporite interlayers predominantly develop dissolution-induced conductive pathways, which reduce stress concentration at the fracture tip and weaken interface strength, thereby promoting activation of interfaces or natural fractures. Moderately increasing viscosity and injection rate enhances cross-layer connectivity while lowering the probability of passive activation of interfaces/natural fractures; however, excessively high injection rates may induce fluid diversion and increase the likelihood of complex fracture growth. The injection-fluid type exerts a pronounced control on breakdown pressure and connectivity patterns: supercritical CO₂ yields the lowest initiation pressure, water-based fluids the highest, and alcohol-based fluids an intermediate response. In the pressure curves, attenuation of propagation pressure corresponds to enhanced cross-layer penetration, whereas a sustained pressure increase indicates dominant diversion or restricted propagation. These findings provide experimental support for parameter optimization and fracture-control design in multilithologic interbedded reservoirs in Southwest China and analogous geological settings. Full article

Energy-efficient operation of industrial thermal systems is a key requirement for sustainable manufacturing and resource-aware process design, particularly under environmental constraints such as dew-point conditions. In this context, minimizing energy consumption while maintaining stable thermal regulation is essential to reduce operational costs and improve system sustainability. This work presents an energy-aware experimental comparison of three control strategies—classical PID, fractional-order PID (FOPID), and hysteresis control—applied to a real thermoelectric thermal regulation system operating under dynamic ambient conditions and dew-point constraints. Unlike conventional control studies focused primarily on tracking performance, this research adopts a sustainability-oriented multi-criteria evaluation framework that explicitly positions energy consumption as a first-order assessment dimension alongside thermal regulation quality and control effort. A set of physically consistent performance indicators is introduced, including total energy consumption, control effort, energy-per-regulation metrics, and a global energy efficiency index, enabling a comprehensive assessment of industrial thermal control strategies from a resource efficiency perspective. Experimental results demonstrate that controller evaluation strongly depends on the inclusion of energy-based metrics. While PID control achieves competitive tracking performance with low error, FOPID provides the best overall trade-off between thermal accuracy and energy consumption, resulting in the highest energy efficiency index. In contrast, hysteresis control, despite its structural simplicity and robustness, leads to higher energy usage due to frequent switching dynamics, reducing its suitability for energy-constrained sustainable applications. The results highlight that thermal regulation near dew-point constraints should be evaluated through an energy-aware multi-criteria framework rather than through pure tracking metrics, enabling a more complete characterization of controller performance for sustainable industrial applications. The proposed framework provides a scalable methodology for evaluating and designing energy-efficient control strategies, supporting sustainable industrial operation and contributing to resource optimization principles aligned with circular economy objectives. Full article

Light-converting polymer coatings and films are emerging passive photonic materials for spectral engineering in sustainable and protected agriculture. By absorbing ultraviolet or weakly used spectral components and re-emitting in visible bands that overlap with photosynthetic pigments and plant photoreceptor action regions, these materials can modify the radiation environment without additional electrical energy input. This critical narrative review analyses light-converting polymer films and coatings from a materials and coatings perspective, with emphasis on photophysical mechanisms, polymer matrices, luminophore families, coating fabrication routes, optical transparency, photoluminescence, aggregation phenomena, photostability and scalability. The photobiological background is included as a concise framework that justifies the spectral targets of the conversion process. Rare-earth complexes, inorganic phosphors, quantum dots, aggregation-induced-emission systems and organic dyes are compared as candidate luminophores. Particular attention is devoted to the general challenges associated with organic luminescent coatings, including dispersion, aggregation, optical transparency, photostability, and scalability. A PMMA/PDI coating system is discussed only as an illustrative case study demonstrating these broader materials-design considerations. Extrusion, solution casting, spin-coating, dip-coating and sol–gel processing are evaluated as fabrication strategies for laboratory and large-area greenhouse applications. The work concludes by identifying the main gaps that must be addressed before practical deployment: quantitative UV–Vis and photoluminescence characterization, absolute quantum yield, haze and scattering, thickness and morphology mapping, accelerated UV aging, weathering resistance, toxicity assessment and crop-specific validation. Full article

Urban public spaces contribute to sustainable urban development by supporting social interaction, cultural identity, pedestrian experience, environmental comfort and commercial vitality. However, limited comparative evidence explains how user satisfaction differs between public spaces shaped by contrasting spatial identities. This study compares Melaka Jonker Street (MJS), a heritage-oriented commercial public space, and Bukit Bintang Kuala Lumpur (BBKL), a contemporary commercial public space, to examine how selected urban space attributes shape user satisfaction and sustainability interpretation. A quantitative comparative survey involving 542 respondents was analysed using descriptive statistics, Cronbach’s alpha, the Mann–Whitney U test, the Relative Importance Index (RII), comparative gap analysis, the User Satisfaction Balance Score (USBS) and exploratory factor analysis (EFA). The findings show that, within the shared attributes examined, MJS recorded stronger satisfaction patterns than BBKL, with the largest satisfaction gaps observed in accessibility, light sculpture, waterscape lighting and green elements. Satisfaction in MJS was mainly shaped by heritage identity, historical buildings, street art walls, water elements and accessibility, reflecting a cultural–environmental sustainability pattern. In contrast, satisfaction in BBKL was more closely associated with activity intensity, media architecture and contemporary visual experience, reflecting a socio-economic-commercial sustainability pattern. These results provide context-specific evidence that sustainable public space performance is shaped by the relationship between urban space attributes, spatial identity and everyday user experience. The findings contribute to urban design and public space research by integrating user satisfaction with sustainability interpretation and by providing context-sensitive planning and design implications for heritage-oriented and contemporary commercial public spaces in Malaysia. Full article

The recycling of spent lithium-ion batteries and selected complex electronic waste fractions is commonly evaluated using isolated metrics such as leaching yield, metal removal efficiency, and reagent consumption. However, this approach fails to address the central challenge of sustainable valorization: integrating upstream conversion with downstream selective recovery without shifting environmental and separation burdens. This review focuses specifically on spent LIBs as the primary model system, while also drawing insights from related e-waste streams (e.g., printed circuit boards and polymer-containing residues) where the interface-driven framework applies. It examines how key interfaces—solid–fluid, polymer–metal–fluid, membrane–solution, electrode–electrolyte, and crystal–solution—govern metal mobilization, selectivity, effluent quality, product purity, and scalability. Emphasis is placed on hydrothermal and supercritical water processing, PVC/CPVC (Polyvinyl Chloride/Chlorinated Polyvinyl Chloride)-assisted metal mobilization and membrane-based recovery techniques, including nanofiltration, membrane distillation, membrane distillation crystallization, ion exchange, and electrochemical methods. Supercritical water and membrane processes are complementary only when upstream chemistry is designed to facilitate downstream separation. PVC-rich waste is reconsidered as a reactive chlorine source, provided that corrosion, HCl formation, and salt precipitation are controlled. Critical gaps include incomplete mass balances, limited multicomponent studies, weak integration between process stages, and scarce techno-economic and life-cycle analyses. A roadmap is proposed for scalable, integrated hydrothermal–membrane systems enabling efficient resource recovery and water reuse. Full article

Restaurants combine long opening hours, catering demand, kitchen ventilation, DHW, and mixed-fuel cooking loads, making their decarbonisation different from generic commercial retrofit. For small- and medium-sized enterprise (SME) hospitality premises, this makes the transition to net-zero operation a distinct sustainability challenge because a large, process-driven share of demand lies outside conventional building-fabric and building-services retrofit. This single-case study develops a whole-building utility-calibrated OpenStudio/EnergyPlus model for Beit El Zaytoun, a 655.82 m² restaurant in Park Royal, London. Monthly electricity and gas data for June 2024–May 2025 were used to calibrate the baseline at whole-building level. Standalone and cumulative scenarios tested insulation, low-emissivity double glazing, LED lighting and controls, ASHP service scenarios, and an 11 kWp PV array. Baseline demand was 413,895 kWh/yr, equivalent to 631.1 kWh/m²·yr and 75,020 kgCO₂e/yr. The lowest-net-energy analytical package reduced net imported energy to 314,734 kWh/yr and operational carbon to 56,700 kgCO₂e/yr, a retained 24.0% reduction on the source reporting basis; this package is treated as an analytical bound rather than as a final design recommendation because it excludes cooling. The model-derived residual process load, kitchen and catering gas plus kitchen, and back-of-house electricity remained 233,920 kWh/yr across building-focused scenarios. The Residual-Load Index (RLI) rose from 0.57 to 0.74; with ±15% process-load allocation uncertainty, the optimised RLI range was 0.63–0.85, so the post-retrofit balance remained process-load dominated. The case demonstrates a practical decarbonisation ceiling likely to recur in similar high-process-load hospitality premises: fabric, lighting, heat electrification, and PV are necessary but insufficient without catering-equipment, cooking-fuel, kitchen-ventilation, refrigeration-control, sub-metering, and demand-response strategies. The paper contributes whole-building utility-calibrated quantitative evidence and a transferable RLI metric for sub-sector-specific sustainable retrofit policy, and the net-zero transition of SME food-service premises. Full article

Food waste is one of the most pressing obstacles to sustainable development. Reducing food waste in schools and kindergartens constitutes an important component of sustainable waste management. To achieve this reduction, various interventions targeting food waste can deliver multiple benefits across environmental, social, and economic dimensions. Among these, behavioral “nudges” aim to steer consumer choices without restricting options. This study evaluated a novel nudging intervention in the canteens of two primary schools and one kindergarten, with the goal of reducing plate waste. The nudging intervention consisted of a simple, interactive installation designed to encourage children to reflect on their food consumption and portion choices. The installation was integrated into routine lunch service and it combined ball-based voting with visual prompts: the emptier the returned plate, the greater the voting weight for the pupil. Across all institutions the food waste level (soup and second dish combined) was significantly decreased during the nudging intervention: by 31% for primary school no. 84, 18% for school no. 1, and 33% for kindergarten no. 56, although part of this reduction was attributable to lower food production volumes. Plate waste for the second dish decreased in all the considered schools: by 10 g/meal (11%), 19 g/meal (22%), and 52 g/meal (51%), respectively. After the intervention a larger share of the second dish served was consumed than was left on the plates compared to the situation during the baseline monitoring. A shift from plate waste to unserved food, which was one of the goals of the study, could not be unambiguously confirmed. Overall, the new nudging installation appears effective. Substantial changes in food production complicate the possibility of determining the effects of the nudging intervention. Future research should maintain constant production levels across the baseline and intervention periods. In addition, pupils should be given maximum freedom to determine their portion sizes during the nudging intervention. The long-term effects of the nudging approach should also be evaluated. Full article