Search Results (5,826)

Livestock production occupies a paradoxical position with respect to climate change: farm animals are highly vulnerable to heat stress, feed and water scarcity, and climate-sensitive disease, while the sector contributes an estimated 14.5% of anthropogenic greenhouse gas emissions, most of which is biogenic methane from enteric fermentation. This review evaluates the evidence for precision livestock farming (PLF)—continuous, automated, real-time monitoring of individual animals’ health, welfare, production and environmental impact—across dairy and beef cattle, small ruminants, pigs, and poultry. For mitigation, precision feeding and additive-dosing strategies have been associated with enteric methane reductions of approximately 10–25%; for adaptation, wearable and non-invasive sensors have been reported to detect heat-stress-related behavioural changes before productivity losses become apparent, and smart climate-control systems have been associated with housing energy-use reductions of roughly 5–10%. Much of this evidence derives from single-farm, small-sample or short-duration studies and should be read as indicative rather than generalisable. Adoption remains constrained by high investment costs, limited interoperability, insufficient technical support, and uneven applicability to extensive and smallholder systems. We conclude that PLF is a valuable enabling technology that, combined with genetic, nutritional, and management strategies, can strengthen the resilience and environmental sustainability of livestock systems under a changing climate. Full article

Makkah faces substantial heat-stress challenges associated with extreme temperatures, dense urban form, and the large numbers of pilgrims present during Hajj and Umrah, creating important public health concerns. Recent heat-related fatalities highlight the need for complementary strategies that address outdoor as well as indoor heat exposure, alongside conventional cooling approaches such as air conditioning. This article examines the potential role of nature-based and complementary engineered interventions in mitigating urban heat stress in Makkah, focusing on afforestation, urban greening, and the possible use of artificial water bodies, contingent on sustainable water management. Drawing on case studies and published evidence from arid and heat-prone regions, including China, Pakistan, Saudi Arabia, and the wider Middle East, we summarize reported cooling effects, implementation experience, and feasibility considerations and assess their potential relevance to Makkah. The perspective highlights critical challenges related to water scarcity, spatial constraints, ecological impacts, and governance, while proposing phased implementation pathways that could be evaluated incrementally. If carefully designed and integrated with urban planning and climate-adaptation strategies, nature-based and complementary interventions could potentially reduce human heat stress, reduce cooling demand, and strengthen climate resilience in Makkah. However, their effectiveness, water requirements, environmental impacts, and scalability require evaluation under Makkah-specific environmental and operational conditions. Full article

Cellulose-based functional materials have attracted increasing attention for portable environmental monitoring and pollutant management; however, achieving a robust integration of functional components with cellulose substrates remains challenging due to weak interfacial adhesion and instability of conventional coating strategies. Herein, a binder-free liquid-phase epitaxy (LPE) strategy was developed to construct lanthanide metal–organic framework (Ln-MOF) coatings directly on unmodified cellulose fibers, yielding a stable and multifunctional Ln-MOF/cellulose composite material. The LPE process enabled uniform growth of Ln-MOF layers on cellulose paper, resulting in homogeneous luminescence with relative standard deviations below 2% and stable fluorescence performance over a wide pH range of 3–11. By regulating the Eu³⁺/Tb³⁺ ratio, the obtained composite paper exhibited tunable dual-emission characteristics and enabled smartphone-assisted ratiometric visualization of dipicolinic acid (DPA), a representative biomarker of bacterial spores, with a linear response range of 0–2000 μM and a detection limit of 10 μM. Furthermore, the anionic Ln-MOF coating endowed the cellulose material with charge-selective adsorption capability, allowing efficient removal of cationic dyes while maintaining structural integrity after four regeneration cycles. The applicability of the LPE strategy was further demonstrated using different lanthanide–organic linker systems. This work provides a versatile approach for fabricating stable cellulose/MOF composite materials and highlights their potential applications in portable chemical sensing and selective water purification. Full article

Microplastic remediation strategies often overlook the management and valorization of the recovered waste, limiting their overall sustainability. Herein, we propose a closed-loop water remediation strategy in which polyethylene terephthalate microplastics (MicroPET) are not only removed from water but also converted into new magnetic nanomaterials for subsequent remediation cycles. MicroPET was initially harvested using magnetic iron oxide nanoflowers (NFs) and subsequently depolymerized by neutral hydrolysis, achieving an unscaled gravimetric PET mass conversion of 97%. Upon process scale-up and downstream purification, an isolated monomer yield of 28.7% was obtained for both purified terephthalic acid (TPA) and ethylene glycol (EG), as confirmed by ¹H-NMR, FTIR, Raman, and osmometric analyses. The recovered supernatant from the unscaled hydrolysis was directly reused as the reaction medium for the microwave-assisted synthesis of maghemite magnetic iron oxide nanoparticles (MIONPs), producing bimodal single-core nanoparticles composed of 5 ± 1 and 29 ± 6 nm crystallites. Despite the absence of the multicore nanoflower architecture and the associated reduction in magnetic performance, the synthesized nanoparticles still demonstrated a remarkable MicroPET harvesting capacity of 1000 mg g⁻¹ under optimized conditions (compared with 10,000 mg g⁻¹ achieved by the original NFs). Furthermore, both the pristine nanoparticles and the MicroPET-loaded hybrid materials efficiently catalyzed methylene blue degradation through a heterogeneous Fenton-like process, with alternating magnetic field activation increasing the decolorization efficiency by ≈20% compared with room-temperature conditions. These results demonstrate that PET-derived EG can be directly reintegrated into the synthesis of functional magnetic nanomaterials, establishing a circular strategy that combines pollutant removal, plastic waste valorization, and catalytic water remediation. Full article

Drought is one of the most damaging abiotic stresses affecting global crop productivity, and its frequency and severity are projected to increase under ongoing climate change. Silicon (Si), although not classified as an essential nutrient, is increasingly regarded as a “quasi-essential” beneficial element that improves crop performance under water-limited conditions. This review summarises the physiological mechanisms of Si-induced drought tolerance, based mainly on literature published in the past five years. Rather than presenting these mechanisms as an inventory of separate physiological effects, the review reframes them as a coordinated stress-tolerance network linked by shared transcriptional regulation, and it organises the evaluation around three conceptual tensions that remain unresolved in the literature: the opposite direction of Si’s effect on transpiration, the extent to which Si-accumulating grasses and Si-excluding dicots rely on equivalent mechanisms, and the non-linearity of dose responses. Si uptake and transport via Lsi1, Lsi2, and Lsi6, and the resulting difference between Si-accumulating and Si-excluding species, are discussed together with the enhancement of root growth and aquaporin-mediated hydraulic conductance; stomatal and photosynthetic regulation; osmotic adjustment through compatible solute accumulation; enzymatic and non-enzymatic antioxidant defence; hormonal signalling involving abscisic acid, jasmonic acid, ethylene, and auxin; reinforcement of cell walls and vascular tissue; and the transcriptional networks coordinating these responses. Si’s influence on rhizosphere nutrient dynamics and the dependence of its efficacy on genotype, dose, and application method are also considered. A consolidated mechanistic scheme is presented, showing how these pathways converge on a drought-tolerant phenotype characterised by sustained growth, improved water-use efficiency, and faster recovery. Future research priorities, including field validation, standardisation of application protocols, multi-omics integration, and Si–microbiome interactions, are outlined to support the translation of these mechanistic insights into practical drought-management strategies. Full article

Water treatment plants are essential urban infrastructure with direct implications for public health and everyday life. Data-driven management has received growing attention in drinking water treatment, particularly for optimizing chemical dosing to improve operational efficiency, reduce costs, and ease operator workload. AI-based prediction of coagulant dosage has therefore become an active research topic. Existing studies, however, have focused mainly on model architecture, with less attention to data validity and cost control. In practice, many plants face data-quality problems, including inconsistent dosing records under similar water-quality conditions. Conventional data cleaning may also remove large portions of the dataset, which can weaken model reliability. This study proposes an artificial intelligence (AI) modeling framework for coagulation dosing that handles anomalous data, emphasizes data quality assurance, and combines cost-oriented feedforward prediction with feedback control. A genetic algorithm-optimized backpropagation (GA-BP) neural network was first evaluated on controlled laboratory data and full-scale plant data using the same core model architecture, allowing the effects of model configuration to be separated from those of data quality. Historical plant records were subsequently cleaned through expert-guided validation, approximate time-delay alignment, and turbidity-based classification of operating conditions. Settled-water turbidity was then used as a feedback signal to dynamically adjust subsequent coagulant dosage and assess the resulting chemical savings. Changes in the input structure produced only modest improvements in full-scale prediction performance (R² = 0.53–0.72). In contrast, data cleaning and process-based data organization markedly improved predictive performance, with R² values increasing to 0.927–0.969. Standalone AI models achieved only moderate dosage reductions, while their integration with real-time turbidity feedback provided the best cost-control performance. The model-based control strategy reduced average coagulant consumption by 10.37%, with a maximum reduction of 21.33% at a settled-water turbidity target of 1.9 nephelometric turbidity units (NTU). Across the evaluated feedback-control scenarios, manual dosing was up to 32.83% higher than the corresponding feedback-controlled dosage. Overall, AI models can fit coagulation-dosing data and predict coagulant dosage with sufficient accuracy, but data quality assurance remains the main factor determining model performance. Effective cost control also requires real-time turbidity-based feedback regulation rather than model outputs alone. Full article

The rapid expansion of artificial intelligence has intensified the demand for high-performance data centers, leading to unprecedented pressures on energy, water, and material resources. This critical review examines the emerging challenges associated with resource management in AI-driven data centers by focusing on the interplay between computational growth and environmental constraints. The analysis integrates recent advances in energy efficiency, cooling technologies, and hardware design while highlighting the increasing water footprint of thermal management systems and the material implications linked to semiconductor manufacturing and infrastructure scaling. Particular attention is given not only to the trade-offs between performance optimization and sustainability but also to the limitations of current metrics used to assess resource efficiency. The review identifies key gaps in the literature, including the lack of integrated frameworks that simultaneously address energy, water, and material flows. Finally, this review provides insights into pathways for a more sustainable AI infrastructure by synthesizing present-day knowledge, critically evaluating existing strategies, and emphasizing the need for systemic approaches that align technological innovation with resource conservation and long-term environmental resilience. Full article

Climate change strongly impacts the physiological processes in the grapevine. Two Romanian autochthonous cultivars, Șarba and Fetească neagră (Vitis vinifera L.), grown under semi-arid conditions in 2024 (De Martonne Index: 23.6; Hydrothermal Coefficient: 0.75), showed different physiological behaviours. Leaf gas exchange parameters (A, g_s, E, C_i) and water use efficiency (WUE) were assessed at three phenophases (flowering, berry growth, and véraison), while photosynthetic pigment indices (Chl a/b, Chl/C+X) and leaf dry matter content (dm) were additionally determined at harvest maturity. Multivariate analysis consistently separated the two cultivars into distinct physiological groups: responses consistent with near-isohydric behaviour in Șarba and anisohydric behaviour in Fetească neagră, based on gas-exchange parameters interpreted within the established isohydric/anisohydric framework, as direct water potential measurements were not performed. Șarba exhibited a water-conserving strategy at véraison—characterised by early stomatal closure, high WUE, and maintained chlorophyll—protecting vine water status at the cost of reduced leaf carbon assimilation. Fetească neagră, by contrast, kept its stomata progressively open, sustaining high gas exchange rates in a pattern consistent with progressively declining shoot water potential. Berry sugars are expected to concentrate passively late in ripening, while severe deficit risks berry shrivelling and, under prolonged drought, premature senescence of basal leaves, to our knowledge, a phenomenon not previously reported for this cultivar. These findings support cultivar-specific management, with implications for irrigation scheduling and varietal selection under climate change. Full article

Sustainable river basin management requires an integrated approach that considers interactions among hydrological resources, socioeconomic development, and ecological protection. Existing studies have mainly focused on evaluating system development and coupling coordination, with limited attention to optimization-based regulation. This study conducts optimal operation of coupling coordination for the integrated system considering water resources, socioeconomic, and ecological environment. Initially, an indicator framework integrating multiple dimensions is developed to characterize system performance, followed by the application of the coupling coordination degree model to assess subsystem evolution and overall coordination. The obstacle degree model is further employed to diagnose dominant limiting factors and determine adjustable variables with regulatory potential. Finally, an optimization model is formulated to maximize the coupling coordination degree under constraints related to total water consumption, green ecological development, and regional feasibility, and NSGA-II is applied to obtain optimal regulation schemes. The results showed that the coupling coordination degree increased from 0.72 to 0.83 (+15.2%). Under the proposed operation strategy, the coupling coordination degree was further improved across all seven league-level cities, with average increases of 0.007–0.012 during the operation period. Optimization further improved coordination in all cities, demonstrating the effectiveness of the proposed framework for sustainable basin management. The proposed framework supports coordinated development and sustainable resource management in the Yellow River Basin. Full article

River-connected lakes are characterized by complex hydrological regimes, where hydrodynamic conditions serve as key physical drivers of aquatic ecosystem evolution and eutrophication. However, traditional water-balance methods struggle to accurately quantify water exchange under strong seasonal water-level fluctuations and the backwater effect of the Yangtze River, resulting in significant gaps in understanding lake hydrodynamic features and their seasonal eutrophication response patterns. Taking Dongting Lake as an example, this study employed a two-dimensional hydrodynamic model coupled with the advection–dispersion equation of a conservative tracer to simulate the spatiotemporal patterns of flow velocity and water turnover time during the dry season, rising-water season, wet season, and receding-water season using observed hydrological data from 2017 to 2025. Field sampling data and structural equation modeling were further used to identify the pathways through which hydrodynamic conditions affect lake trophic status. Flow velocity and water turnover time exhibited significant spatiotemporal heterogeneity: water turnover time was generally within 10 d in main flood channels but exceeded 60 d in stagnant floodplain areas and local topographic depressions. Seasonally, it was shortest in the wet season due to enhanced hydrological connectivity, yet longest in the dry season because of weakened hydraulic connection. The effects of hydrodynamics on trophic status were strongly season-dependent: during the rising-water season, hydrodynamics inhibited nutrient accumulation through dilution and flushing; during the wet season, strong runoff promoted external nutrient input; and during the dry season, hydrodynamics mainly affected trophic status by modifying physical habitat conditions for algal growth. These findings reveal the hydrological and hydrodynamic mechanisms regulating eutrophication in typical river-connected lakes, providing direct scientific support for hydrological regulation optimization, zonal eutrophication prevention and control, and water environmental carrying capacity assessment in Dongting Lake and similar systems, enabling lake managers to formulate differentiated pollution control strategies based on the hydrodynamic–trophic status response relationships across different hydrological seasons. Full article

Understanding habitat suitability and environmental preferences of shortbill spearfish (Tetrapturus angustirostris) is essential for assessing and mitigating bycatch risk in pelagic longline fisheries. Using observer data collected by the Chinese Pacific tuna longline fishery, including 19,932 longline sets collected during 2010–2021, we compared five individual modelling algorithms and three ensemble strategies to predict habitat suitability across the Pacific Ocean and identify key environmental drivers. Model performance was evaluated using repeated 10-fold cross-validation with three repetitions. The stacking ensemble achieved the highest predictive performance (AUC = 0.872; TSS = 0.591), followed closely by random forest (RF; AUC = 0.869), although the absolute difference between these two models was small. A sensitivity analysis including log-transformed observed hooks resulted in only minor improvements in RF and stacking performance and did not materially alter the main habitat-suitability patterns. Both generally outperformed the other individual and weighted ensemble models. Permutation-based importance analyses consistently identified salinity as the strongest environmental predictor of habitat suitability, followed by chlorophyll-a concentration, distance to shore, and dissolved oxygen concentration. Partial dependence analyses showed that the stacking ensemble produced smoother and more readily interpretable responses to environmental gradients, particularly salinity and dissolved oxygen, whereas RF placed greater importance on a limited number of dominant predictors. Highly suitable habitat was primarily predicted in subtropical offshore waters of the southeastern Pacific (10° S–25° S, 100° W–130° W), which were characterized by relatively high salinity, moderate dissolved oxygen concentrations, and low chlorophyll-a concentrations. A secondary area of elevated suitability was identified in the central North Pacific (160° E–180° E, 15° N–25° N). Overall, the stacking ensemble provided robust predictions of shortbill spearfish habitat suitability, whereas RF remained useful for identifying dominant environmental correlates. The predicted habitat maps provide a spatial basis for identifying potential bycatch-risk hotspots and supporting adaptive management strategies, such as spatially targeted monitoring and mitigation measures in tuna longline fisheries. Full article

Water body segmentation is essential for flood monitoring, water resource management, and ecological and environmental protection. Recent advances in deep learning and remote sensing have substantially improved the automation and accuracy of water body segmentation. However, existing methods remain susceptible to false positive predictions in complex landscapes containing shadows and dense vegetation. Their ability to delineate fragmented water surfaces and small water bodies is also limited, and their robustness to seasonal variations and transferability across regions require further improvement. This paper presents a comprehensive review of water body segmentation methods, datasets, evaluation metrics, current challenges, and future research directions. It examines representative models derived from U-Net, DeepLabv3+, Transformer, Mamba and the Segment Anything Model (SAM), with particular emphasis on their architectural modifications and improvement strategies. Representative datasets covering rivers, lakes, and reservoirs are summarized, and commonly used evaluation metrics are reviewed and interpreted. Future research should focus on spatiotemporal adaptive multimodal fusion, segmentation strategies for large model integration, fine-grained water body segmentation, and the integration of explainability and physical mechanisms. This review provides a useful reference for improving water body segmentation models, developing high-quality water body datasets, and supporting practical applications in water resource management and environmental monitoring. Full article

Several global challenges are converging: rising organic solid waste generation, growing food demand, and increasingly unfavorable conditions for food production, including more frequent and severe droughts, water scarcity, and limited agricultural land for expansion. Bioconverting organic waste into alternative protein sources has emerged as a promising strategy to address waste management and feed production challenges simultaneously. This study presents a comprehensive systematic literature review on protein production through the bioconversion of residual biomass using the black soldier fly (BSF, Hermetia illucens). The BSF is a highly voracious organism during its larval stage and can substantially reduce organic waste volumes while converting them into biomass rich in proteins and lipids with high nutritional value for livestock and aquaculture feed formulations. The review examines Waste-to-Protein systems from three perspectives: technical, economic, and environmental. The technical perspective focuses on production system operations and substrate properties. The economic perspective addresses profitability indicators, capital and operating costs, economies of scale, and the economic performance of incorporating insect-derived protein into animal production systems. From an environmental perspective, Life Cycle Assessment (LCA) is the predominant method for evaluating WtP-BSF systems. Among the systems assessed using LCA, 63% rely on crop-derived substrates for larval feeding. These substrates have intrinsic commercial value, and together with the environmental burdens associated with energy consumption during BSFL rearing, they may constrain the overall sustainability and profitability of WtP-BSF systems. By evaluating factors such as feed dosage, larval density, actual organic waste, and eco-efficiency metrics for livestock feed, opportunities for a circular economy could be developed in developing countries, helping to decrease dependence on landfills. Full article

Mitigating flood risk and planning river corridors in Torrent-type Basins (TBs) requires integrated frameworks that link hydro-geomorphological processes with ecological quality, a combination currently lacking in regional planning. This study presents an integrated hydro-geomorphological and ecological analysis of the Rio Geremeas catchment (Sardinia, Italy), developed within the Regional Sediment Management Plan (PGS). The approach combines multi-scale geomorphological mapping, the IDRAIM eco-morphological framework, and 2D hydro-morphodynamic modelling (MIKE 21C), supported by field surveys and remote sensing of sediment source areas and biological assemblages (riparian vegetation, macroinvertebrates, and fish). Results reveal a direct link between altered sediment dynamics and ecological degradation, with confined reaches showing lower biotic diversity compared to mobile, morphologically functional reaches. 50-year flood simulations identified critical erosion/deposition zones, guiding targeted proposals: restoring sediment continuity by removing hydraulic constraints, controlling invasive species, and managing the river mouth to favour the migration of the European eel. This work provides a transferable, interdisciplinary approach for sediment- and ecosystem-informed river basin planning, directly supporting the EU Water Framework Directive and climate resilience strategies. Full article

Gelatin hydrogels combine biological origin, biodegradability, abundant chemical functionality, and broad processability, but their native thermoreversible physical networks generally lack the stability required for sustained operation. Crosslinking overcomes this limitation while regulating hydration, mechanics, transport, degradation, and responsiveness. This review examines gelatin hydrogel crosslinking from a structure–property–function perspective, connecting molecular design with physicochemical characterization and functional performance. Temperature-induced gelation and ion-mediated physical interactions are compared with small-molecule- and coupling-agent-mediated, enzyme-catalyzed, and photoinduced covalent crosslinking strategies, highlighting their different balances among reversibility, stability, processability, and biocompatibility. Particular attention is given to the characterization methods required to relate junction chemistry and network organization to swelling, thermal behavior, mechanical response, degradation, and molecular or ionic transport. These relationships are evaluated across drug delivery and controlled release, tissue engineering and wound healing, food packaging, preservation and delivery, water remediation and environmental management, wearable sensing and bioelectronics, and energy storage. Across these fields, the central challenge is not to maximize crosslinking, but to balance network stability with the molecular mobility required for function. By integrating complementary crosslinking mechanisms with multiscale characterization, gelatin can be engineered as a programmable platform for advanced soft materials. Full article