Search Results (724)

A short-term performance test of blended biodiesel (FAME), green diesel (HVO), and diesel was experimentally assessed in a 100 kW Cummins 6BTAA5.9-G12 diesel engine under multiple load conditions. The objective was to determine the technical feasibility, operational trade-offs, and optimal blend formulations for renewable energy deployment in diesel power plants. All tested blends operated stably without engine modification, confirming the “drop-in capability” of FAME–HVO mixtures for existing diesel engines. Specific fuel consumption (SFC) increased notably at high loads, with penalties up to 15.15% for B30D20 and B35D15 relative to neat diesel, although overall efficiency improved with load. Among the ternary fuels, B30D10 and B30D20 provided the most balanced compromise between combustion reactivity and flow properties. Exhaust gas temperatures rose with load for all fuels, with FAME-rich blends exhibiting higher temperatures than neat diesel, while coolant-side analysis showed D100 and D50 as thermally favorable and B50–B100 imposing the highest cooling demand. The results emphasize the need for injection system recalibration on an energy basis for HVO-rich fuels, and for strengthened filtration and maintenance practices for FAME-rich blends to avoid filter clogging and injection instability. Considering performance, operability, and system stability up to 100 kW, B30D10 and B35D15 are identified as optimal compromise blends. The study highlights the necessity of future work on long-term durability, fuel system compatibility, supply chain robustness, and techno-economic viability to safely scale green diesel use in Indonesian stationary power generation. Full article

The rapid expansion of wireless connectivity has led to vast amounts of radio-frequency (RF) energy being continuously radiated into the environment, much of which is dissipated due to severe propagation losses. Recycling this otherwise wasted RF energy is, therefore, a critical enabler for energy-efficient and sustainable wireless systems. RF energy harvesting nodes and passive backscatter communication devices provide promising solutions by enabling battery-less or low-maintenance operation for future green networks. However, both paradigms suffer from fundamental limitations, including restricted communication range, near–far effects, and insufficient harvested energy at extended distances. This review examines how cooperative relays can address these challenges by harvesting ambient RF energy and assisting both information transfer and power delivery. From a communication perspective, we review cooperative backscatter communication and harvest-then-transmit (HTT) protocols, highlighting how multi-hop relaying significantly extends coverage and improves throughput for energy-constrained devices. Particular emphasis is placed on tag-to-tag (T2T) backscatter systems, relay-assisted architectures, decode-and-forward and amplify-and-forward protocols, and optimal multi-access time allocation strategies that mitigate the doubly near–far problem in passive networks. From an energy-transfer perspective, the review is structured around three pillars: wireless power transfer (WPT), multi-hop energy transfer (MET), and integrated charging-and-sensing frameworks. We discuss relay deployment and placement optimisation, UAV-enabled mobile energy relays, waveform and beam-forming design, and the transition from idealised linear harvesting models to practical nonlinear rectification models. Key practical constraints, such as regulatory limits, safety compliance, self-interference, protocol overhead, synchronisation, and imperfect channel knowledge, are systematically reviewed. The paper concludes by identifying the scalability limits of multi-hop cooperative systems, outlining how the joint optimisation of energy relaying and cooperative communication enables RF energy recycling for sustainable, low-carbon wireless networks and highlighting open challenges and future research directions. Full article

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

Diallyl trisulfide (DATS), a volatile natural sulfur-containing compound derived from garlic, possesses antifungal and preservative potential. However, its biocontrol efficacy against postharvest gray mold of tomato and the molecular mechanisms underlying fruit quality maintenance remain unclear. In this study, we systematically investigated the inhibitory effect of DATS fumigation on postharvest gray mold, its role in fruit quality maintenance, and the associated molecular mechanisms through in vitro antifungal assays, physiological and biochemical measurements, transcriptome sequencing, and correlation analysis. In vitro experiments showed that DATS at 50 μL L⁻¹ completely inhibited spore germination and germ tube elongation of Botrytis cinerea in a concentration-dependent manner, and disrupted spore membrane integrity (FDA-positive spores dropped from 73.4% to 2.9% at 50 μL L⁻¹). In vivo experiments demonstrated that Bc + DATS treatment completely inhibited lesion development compared to the control Bc, enhanced the activities of superoxide dismutase, catalase and peroxidase (e.g., CAT activity 2.20-fold higher than Bc on day 3), decreased malondialdehyde accumulation (0.65-fold of Bc on day 4), and delayed the declines in total soluble solids, titratable acidity, soluble sugars and vitamin C content (VC content 4.14-fold higher than Bc on day 4). Transcriptomic analysis revealed that DATS treatment up-regulated genes involved in plant hormone signal transduction, ubiquitin-mediated proteolysis, and phenylalanine metabolism, while down-regulating core MAPK kinases and histidine decarboxylase. Correlation analysis demonstrated significant associations between the expression of these pathway genes and antioxidant enzyme activities, vitamin C content, and lesion diameter. Collectively, DATS achieves effective control of postharvest gray mold and maintenance of fruit quality in tomato through direct antifungal activity, synergistic activation of hormone/MAPK signaling, reprogramming of phenylalanine metabolism, and modulation of membrane lipid homeostasis. This study provides a theoretical and practical basis for developing DATS as a green postharvest preservative to reduce food loss and ensure food safety. Full article

In recent years, the use of warm-season species, which are species requiring less water, has been pursued in continental areas, but their dormancy and spring green-up need to be properly defined. In urban green areas, we find that small-scale microclimatic differences, while less intense than classical urban–rural gradients, still influence vegetation performance and spring green-up. This study examines the impact of microclimatic temperature variation on the spring green-up of different cool-season and warm-season turfgrasses in the continental climate of Madrid, Spain. The evaluation of colour change during the spring green-up process has been conducted using different vegetation indices, and mathematical models for correlating temperature with the indices’ values have been obtained. The results indicate that with average temperatures varying by about 1.3 °C and 0.9 °C in January and February, respectively, there have been marked differences in spring green-up, especially in cool-season turfgrasses, of almost one month. In contrast, differences in warm-season turfgrasses were reduced. Among the four vegetation indices, Canopeo has proved to be the best for detecting the early stages of spring green-up, with R² values ranging from 0.43 to 0.92. Meanwhile, the tailored greenness index for turfgrass was the most effective for determining the moment at which warm-season grasses achieve the colouration of cool-season grasses, with R² ranging from 0.79 to 0.85. Finally, the green leaf index was particularly valuable for identifying differences among species and sectors throughout the entire spring green-up process. Models based on this index achieve high R² values (0.57 to 0.94), but these models predict the moment at which warm-season grasses achieve cool-season grasses’ colouration later than it actually occurs. Understanding how turfgrasses respond to these localised microclimatic conditions is essential for selecting resilient species and improving maintenance strategies in parks, sports areas, and other components of urban green infrastructure. Full article

In order to address corrosion and pollution problems of liquid acids and limitations of traditional solid acids, sulfated MOF-808-SO₄ catalysts were developed by creating unsaturated sites in MOF-808 for sulfate grafting with ligand defect engineering. Characterization verified framework integrity, successful sulfate coordination, and maintenance of high surface areas and tunable porosity. Temperature-programmed desorption of ammonia (NH₃-TPD) establishes a clear consistent trend between defect density and the concentration as well as the strength of acid sites, indicating that a higher degree of ligand deficiency promotes the formation of more abundant and stronger acid centers. For esterification of acetic acid with n-butanol, the catalyst prepared by replacing 40 mol% of BTC with BDC achieved ≥99% conversion of acetic acid under mild conditions of 2.0 wt% catalyst loading and 1:2 alcohol/acid molar ratio at 120 °C for 6 h, outperforming conventional solid acids. This performance stems from high-density strong Brønsted acid sites strongly coordinated at defects and an open pore structure facilitating diffusion. The catalyst was easily recovered by ethanol washing and maintained stable activity over five cycles without loss of catalytic capability. This work suggests defect engineering as an effective strategy for tuning acidity and catalytic performance in MOF-based solid acids for green esterification. Full article

Compost offers high potential for sustainable agriculture, but its agronomic outcomes vary. This critical review combines qualitative evidence with literature-derived quantitative benchmarks for compost maturity, salinity, nutrient loading, application-rate classes and monitoring triggers. Evidence demonstrates that mature, stable composts consistently improve soil health, including aggregation, water-holding capacity, soil organic carbon (SOC), and nutrient availability while boosting crop yield and establishment. These high-quality composts are characterized by low phytotoxicity, moderate C:N ratios, acceptable EC levels, and pathogen compliance. However, benefits are not universal. Immature or poorly stabilized compost poses risks of phytotoxicity, ammonia toxicity, and nitrogen immobilization. Excessive application rates are associated with nutrient imbalances, increased salinity, nitrate leaching, phosphorus runoff, greenhouse-gas trade-offs, and cumulative contaminant loading. To enhance the precision of rate recommendations, this review categorizes applications into four distinct tiers: starter or maintenance (2–5 Mg dry matter ha⁻¹), common agronomic (5–20 Mg ha⁻¹), rehabilitation (20–35 Mg ha⁻¹), and high-risk (>35 Mg ha⁻¹). It posits that the final application rate must be dictated by the most limiting factors, such as crop nitrogen requirements, soil-test phosphorus levels, salinity tolerance, contaminant thresholds, hydrologic risk, or specific management objectives. In conclusion, while manure-based composts enhance short-term fertility, they introduce significant risks of phosphorus accumulation and salinity compared to green-waste alternatives. This review, therefore, redefines compost not as a generic organic amendment, but as a quality-controlled, rate-sensitive input essential for precision nutrient management. Full article

Background/Objectives: Cognitive function is fundamental to daily life, and nutrition is a key modifiable determinant of brain health across the lifespan. While plant-based “brain foods” have been emphasized, the contributions of animal-sourced foods (ASF) to neurodevelopment and cognitive performance remain underexplored. This review synthesizes current evidence on the effects of both plant- and animal-derived foods on cognitive outcomes from early development through older adulthood. Methods: A narrative review was conducted focusing on eight major categories of brain-supportive foods—dairy, eggs, seafood, lean meat, berries, leafy green vegetables, nuts, and whole grains. Evidence was evaluated across life stages, considering nutrient bioavailability, dietary patterns, and the interplay between structural, socioeconomic, and environmental factors that influence access to these foods. Results: Nutrient-dense foods, including ASF and plant-based sources, support cognitive outcomes across the life course. In early childhood, eggs, meat, and nuts were linked to improved neurodevelopment and reductions in developmental delays, while evidence for seafood and dairy was more mixed. During adolescence and adulthood, berries, walnuts, vegetables, and whole grains were associated with improvements in executive function, verbal reasoning, and mood, with adequate bioavailable protein from ASF remaining important. Among older adults, higher intake of leafy greens, nuts, berries, and moderate seafood consumption correlated with slower cognitive decline and improved memory. Findings were limited by heterogeneous study designs, dietary assessments, and underrepresentation of adolescents and populations in low- and middle-income countries. Conclusions: Both animal-sourced and plant-based brain foods uniquely support cognitive development, maintenance, and resilience. While nutritional needs vary across the life course, strong evidence supporting distinct food-based dietary recommendations for cognitive outcomes at different ages, particularly adolescents, remains limited. Current findings suggest stage-specific associations, particularly during early development, but more longitudinal and experimental research is needed. Expanding rigorous, inclusive research will be critical for informing nutrition policies that support lifelong cognitive health. Full article

This study deciphers the impacts of urban forests and green spaces (UFGSs) on housing prices through a systematic review of 180 peer-reviewed articles (440 empirical cases) to delineate how various UFGS attributes drive housing price changes, focusing on the direction, intensity, and contextual dependency of these impacts. We identified specific UFGS attributes (e.g., proximity, size, type, quality, accessibility, landscape patterns) and the methodologies assessing their price impacts, primarily hedonic pricing models. Our findings confirm a consistent, albeit highly variable, positive premium from urban forests and related green infrastructure on housing prices. Key drivers include not only proximity and size, but also crucial qualitative attributes like perceived UFGS quality (e.g., tree canopy coverage, wooded park maintenance), which often show stronger or more consistent effects than simple quantitative measures. The analysis also highlights that negative impacts can arise from poorly managed urban forests or certain disamenity-prone green typologies. Significant spatio-temporal heterogeneity is evident, with price effects varying by urban context (e.g., density, development stage) and over time. Socio-economic factors, particularly manifesting as “green gentrification”, which can exacerbate inequalities by disproportionately benefiting higher-income groups, critically moderate these relationships. Furthermore, prevalent non-linear effects (e.g., distance-decay patterns, threshold effects for UFGS size) and complex interactions between different UFGS attributes underscore the nuanced nature of the UFGS–price nexus. This review provides a structured understanding of urban forest and green space capitalization drivers, emphasizing the need for nuanced, evidence-based urban forestry planning and green space management that considers UFGS quality, diversity, and equitable distribution for sustainable urban development. Full article

Urban drought pressure is increasing the operational risk and cost of maintaining municipal green infrastructure. Irrigation is still widely managed through fixed routines and fragmented information. To address this challenge, the study develops an integrated operational analysis by combining water consumption records, maintenance data and a GIS inventory for twenty municipal green spaces. System characterisation and performance screening were carried out using hourly meter readings to distinguish typical scheduled irrigation peaks from non-standard consumption patterns. To move from monitoring to control, irrigation needs were estimated using evapotranspiration (ET₀) and a garden-coefficient logic adapted to urban planting conditions and compared with measured consumption. The comparison indicates a potential reduction of 29–61% through improved scheduling and system adjustment. Based on the diagnosis, technical intervention scenarios were defined and assessed using techno-economic metrics, including ground-cover redesign and Mediterranean-adapted planting strategies. To support implementation, options were organised into intervention priorities using a multicriteria tool that balances water savings, costs and feasibility under municipal operations. Coimbra, Portugal is used as a case study, and a pilot application in a city garden, supported by 797 user surveys, clarifies practical constraints for scaling beyond isolated pilots. Turf-free scenarios indicate a 53.4% reduction in water use and a 60.5% reduction in operational costs, with a payback period below three years. The results highlight the potential of data-driven irrigation management to support more resilient, cost-effective and water-efficient municipal green infrastructure across diverse urban contexts. Full article

Asphalt pavements are prone to the formation of microcracks due to aging under environmental factors, and microcapsule-based self-healing technology represents an effective means of preventive maintenance. In this study, corn oil, a renewable and environmentally friendly material, was selected as the asphalt rejuvenator to prepare corn oil microcapsules via in situ polymerization, and the self-healing performance of corn oil microcapsule-modified asphalt was investigated. By analyzing the effects of corn oil microcapsules on the high-temperature performance, salt resistance, chemical structure, and microscopic morphology of asphalt, as well as the influence of temperature, time, and corn oil microcapsule content on the self-healing performance of asphalt mixtures, the self-healing mechanism of corn oil microcapsule-modified asphalt was elucidated at both the microscopic and macroscopic levels. The results showed that during the preparation of corn oil microcapsules, the optimal molar ratio of M_F:M_(M+U) was 2.5, with an emulsification rate of 1.2 kr/min. The prepared corn oil microcapsules exhibited high yield and good encapsulation efficiency, possessed excellent high-temperature resistance that met the requirements of the asphalt mixing stage, and showed superior salt resistance. FTIR analysis confirmed the successful incorporation of microcapsules into the asphalt system. Atomic force microscopy (AFM) observations revealed that the microcapsules mitigated microscopic surface damage caused by aging. The healing index of the asphalt mixtures incorporating corn oil microcapsules increased with prolonged healing time and elevated temperature. By establishing the relationship between the healing index and the content of corn oil microcapsules, the recommended content of corn oil microcapsules within the tested range is 6 wt%. This study elucidates the self-healing mechanism of corn oil microcapsule-modified asphalt from both microscopic (surface parameter recovery) and macroscopic (mechanical property restoration) scales, providing a scientific basis for the application of microcapsule technology in green and sustainable asphalt pavement maintenance. Full article

The optimisation design of agricultural machinery is shifting from offline, experience-driven engineering towards adaptive, data-driven, and closed-loop intelligent optimisation. Conventional approaches based on computer-aided engineering (CAE), empirical testing, mathematical modelling, and static multi-objective optimisation have provided an important engineering foundation, but they remain limited under unstructured field conditions involving soil heterogeneity, crop variability, climatic disturbance, and nonlinear machinery–environment interactions. This review systematically examines the evolution of intelligent optimisation design for agricultural machinery from conventional simulation-based methods to artificial intelligence (AI)- and digital twin (DT)-enabled paradigms. First, mathematical modelling, response surface methodology, discrete element method (DEM), computational fluid dynamics (CFD), multi-body dynamics (MBD), heuristic algorithms, and early AI-assisted surrogate optimisation are reviewed to clarify their contributions and limitations. Second, frontier enabling technologies are analysed, including agriculture-specific large models, generative AI, lightweight edge intelligence, deep reinforcement learning (DRL), embodied AI, federated learning (FL), and privacy-preserving computing. Third, system-level applications integrating DT and AI are discussed, with emphasis on full-lifecycle machinery optimisation, device–edge–cloud collaborative control, multi-agent fleet coordination, predictive maintenance, and Agriculture 5.0-oriented intelligent equipment systems. Key deployment bottlenecks are further identified, including sim-to-real inconsistency, virtual–physical mismatch in DTs, edge-side trade-offs among accuracy, latency, energy consumption, and cost, insufficient validation standards, and economic adoption barriers. Finally, a 2025–2030 roadmap is proposed, highlighting large-model–DT closed loops, control biomimetics, green low-carbon optimisation, and trustworthy human–machine symbiosis for sustainable Agriculture 5.0. Full article

Urban parks are often regarded as carbon sinks, yet their net carbon performance depends on the balance between vegetation carbon uptake and maintenance-related emissions, as well as the accurate representation of within-park spatial heterogeneity. This study used backpack LiDAR, field vegetation surveys, and maintenance inventories to quantify annual carbon sequestration, maintenance emissions, and net carbon budget in 44 plots covering nine biotope types across 16 parks in central Xianyang, China. A four-level biotope classification incorporating canopy openness, ground cover, tree composition, and vertical stratification was applied to link LiDAR-derived three-dimensional structure with ecological-unit-level carbon accounting. Carbon sequestration and net carbon budget differed significantly among biotopes, whereas maintenance emissions did not. Closed broadleaved single-layer forest showed the highest carbon sequestration density (0.772 kg C m⁻²), while hard-surfaced partly closed broadleaved single-layer forest showed the lowest value (0.132 kg C m⁻²). Closed woody biotopes functioned as strong carbon sinks, partly closed biotopes as weak sinks, and the partly open short-grass biotope was the only carbon source. Three-dimensional green volume density was the strongest positive predictor of net carbon budget (β = 0.417, p = 0.032), followed by stem density (β = 0.276, p = 0.048), whereas irrigation-related emissions showed a significant negative coefficient (β = −0.276, p = 0.021). Carbon sequestration explained more variation in net carbon budget than maintenance emissions (adjusted R² = 0.409 vs. 0.134). These findings suggest that backpack LiDAR can support fine-scale identification of priority carbon-sink units in urban parks and that low-carbon park management should prioritize three-dimensional woody vegetation structure while reducing high-input irrigation where feasible. Full article

Urbanisation has led to dramatic alterations in pre-existing natural environments, resulting in several subsequent phenomena, such as the disappearance of habitats suitable for many plant and animal species and the concurrent arrival of generalist and non-native species, contributing to environmental homogenisation. Towns and cities serve as crossroads for transport, people, and animals, making them susceptible to colonisation by many types of plant species, dispersed either intentionally or unintentionally by these biotic vectors. Abiotic vectors, such as wind and water, also influence the composition of vegetation assemblages. Urban spontaneous vegetation occurs in (1) undisturbed areas, including brownfield sites, commons, and marginal lots, and (2) disturbed sites, such as green areas, parks, lawns (not subject to weeding), ancient monuments and walls, peripheral and industrial areas, and railways. When disturbance occurs, vegetation remains at early successional stages. Within this framework, with the aim of comparing existing contradictions and identifying knowledge gaps, we reviewed the literature on the characteristics of spontaneous plants and vegetation in urban areas, the different habitats in which they grow, the ecosystem services they provide, and management strategies, considering human perception. Our results highlight that studies on spontaneous plants are well-developed in terms of botany and ecology; however, some gaps remain, particularly regarding their integration into urban design and maintenance practices. Concerning public perception and acceptance, cultural and geographical differences emerged that deserve further investigation. In conclusion, spontaneous plants can represent a valuable heritage for cities, helping to address the challenges posed by the climate crisis. Full article

The pursuit of sustainable winter road maintenance has intensified the need for deicers that balance functional effectiveness, economic viability, and minimal environmental impact. However, the absence of a systematic, multi-dimensional evaluation framework has hindered informed product selection and green procurement. This study develops and validates the Comprehensive Deicer Multi-criteria Evaluation System (CDMES)—a structured assessment framework that integrates economic, functional, environmental, and infrastructural sustainability dimensions. The evaluation index system was constructed for deicers, consisting of 18 indicators including preparation cost, engineering maintenance cost, operability of agent preparation, application difficulty, asphalt binder adhesion loss, minimum application concentration, proportion of active ingredients, effective time, ambient temperature, freezing point, solid dissolution rate, relative snow/ice-melting capacity, seed damage rate, chlorophyll attenuation, soil pH, aqueous solution pH, steel–carbon corrosion rate, and pavement friction attenuation rate. Subsequently, the analytic hierarchy process (AHP) was employed to determine the weight of each indicator, and evaluation criteria were established in accordance with relevant standards and literature. Finally, this weight determination method, combined with the simple additive weighting (SAW) method for index aggregation, forms a quantitative evaluation model. These elements together constitute a comprehensive deicer evaluation system, designated as the Comprehensive Deicer Multi-criteria Evaluation System (CDMES). Validation using three representative deicers—sodium chloride, a composite chloride-based formulation, and an organic acetate-based product—demonstrated that the CDMES can effectively discriminate product performance across multiple sustainability dimensions and identify critical weaknesses that may be obscured by purely compensatory scoring. The framework offers a transparent and reproducible decision-support tool for winter maintenance managers seeking to align deicer selection with sustainability objectives. Full article