Search Results (271,949)

The UN General Assembly (2015) emphasizes sustainable pathways to enhance resilience for people and nature, with future development driven by data and evidence. Sustainable development frameworks (e.g., the UN 2030 Agenda and the 2016 Paris Climate Agreement) highlight the importance of data and evidence in assessment and decision-making that respects national policies and priorities. Global advances in Earth observation (EO) data provision and digital solutions that increase efficiencies, timeliness, and affordability are making major contributions. However, many existing platforms rely on externally hosted cloud infrastructures and generic global classifications of environments that may not align with domestic statutory definitions, limiting national control over data governance, methodological standards, and regulatory reporting. These constraints have raised growing concerns regarding data and technological sovereignty for countries seeking authoritative, policy-ready environmental information. Using Wales (United Kingdom; UK) as an exemplar, this study showcases the design and implementation of a flexible, sovereign National Digital Infrastructure (NDI) that uses the Open Data Cube (ODC) to apply Living Earth, a novel and customizable approach for EO-focused environmental monitoring. Outputs are time series of land cover and habitat maps and change products, including post-event (e.g., fire, flood) management, which address key policy requirements and support land and water resource management (from freshwater to marine environments), while ensuring public dissemination. Major advantages include the sharing of consistent datasets across governments and partner organizations, minimizing duplication of effort, improving transparency, traceability, and reproducibility, fostering collaboration between diverse stakeholders and communities, promoting inclusivity in environmental management decision-making, and supporting sustainable outcomes. Full article

Lakes are sensitive indicators of climate change and exhibit distinct responses to climatic variability. Using in situ eddy covariance and meteorological observations from Nam Co (“large lake”) and a small lake (“small lake”) adjacent to Nam Co, we evaluate the performance of the FLake model in simulating lake processes. The model generally reproduces the seasonal variations in mixed-layer depth and surface water temperature, although diurnal amplitudes are underestimated. Simulated sensible and latent heat fluxes agree well with observations when appropriate lake depth and light extinction coefficients are applied, with RMSEs of ~1 °C, 8 W m⁻², and 22 W m⁻² for lake surface temperature, sensible heat flux, and latent heat flux, respectively. For the “large lake”, latent heat flux simulations differ markedly between land-based and lake-based forcing, primarily due to differences in wind speed and air temperature. Long-term simulations (1981–2024) suggest progressive warming of lake surface waters, strengthened thermal stratification, and increasing surface heat fluxes, with downward longwave and shortwave radiation and near-surface air temperature identified as the dominant climatic drivers. Full article

This study investigates the impact of green organizational support and green self-efficacy on promoting employees’ pro-environmental behaviors, framed within Social Cognitive Theory and Social Exchange Theory. The direct and indirect impacts of green organizational support on employees’ green advocacy and pro-environmental behaviors remain insufficiently examined in the literature. This study aims to clarify the factors affecting pro-environmental behaviors within the workplace and to examine the relationship among green organizational support, green self-efficacy, green advocacy, and pro-environmental behavior. Data was gathered from 154 employees via a structured questionnaire, and the proposed model was analyzed using SmartPLS 4. The study findings demonstrate that both green organizational support and green advocacy directly and positively influence workplace pro-environmental behaviors. The impact of green self-efficacy on the eco-friendly behaviors of employees could not be validated. The results are useful for the development of sustainability strategies for organizations and the establishment of an environmentally conscious corporate culture. Full article

Phosphorus is crucial for reconstructing long-term feedback mechanisms between climate, the environment and ecology, as well as for assessing global biogeochemical changes. This study documents two thin yet laterally continuous phosphorite beds from the lower Nenjiang Formation (Late Cretaceous) of the Songliao Basin in NE China and evaluates their mineralogical characteristics and paleoenvironmental significance. The phosphorite beds occur in sharp contact with adjacent black shale and contain well-preserved Ostracoda and conchostracan fossils, providing biological constraints on the depositional conditions. Bulk rock compositions indicate elevated P₂O₅ contents, ranging from approximately 20 to 30 wt%. Mineralogical analyses reveal that the dominant phosphate mineral is carbonate-fluorapatite (CFA), accompanied by minor quartz, hydromica, goethite and pyrrhotite. Integrated fossil, sedimentological, and geochemical evidence suggests that CFA precipitated in a deep, stratified, eutrophic lacustrine environment. Enhanced productivity, biological enrichment and microbial decomposition of organic matter likely promoted phosphorus enrichment in bottom waters, facilitating CFA precipitation at or near the sediment-water interface during deposition and early diagenesis. Variations in physicochemical conditions, including pH and Ca²⁺ concentrations, may have further influenced mineral precipitation and subsequent diagenetic processes. These findings contribute to our understanding of phosphorus precipitation mechanisms in lacustrine basins and provide new constraints on the Late Cretaceous paleoenvironment of the Songliao Basin. Full article

Solar Radiation Modification (SRM) is increasingly discussed as a potential supplement to climate-change mitigation, yet public and stakeholder judgments remain sensitive to knowledge, framing, and perceived risks. We examined how a structured university classroom module on SRM reshaped student perceptions using a matched pre–post survey design. Participants were students enrolled in an English-taught global climate change course (N = 106); 103 students provided valid matched responses after applying pre-specified exclusion rules. Self-rated SRM knowledge increased substantially after the module (mean change +0.47 on a 1–3 scale; Wilcoxon signed-rank p (Holm-adjusted) < 1 × 10⁻⁷; Cohen’s dz = 0.67). Support for SRM research remained moderately positive but did not increase (pre mean 3.76 to post mean 3.54 on a 1–5 scale). In contrast, support for stratospheric aerosol injection (SAI) deployment declined (pre mean 3.42 to post mean 2.95; p (Holm-adjusted) = 0.0084; dz = −0.33), and preferences shifted away from prioritizing climate intervention toward low-carbon development (mean change −0.68 on a 1–5 priority scale; p (Holm-adjusted) = 0.0001; dz = −0.45). Post-lecture models indicated that perceived benefits versus risks was the most consistent correlate of support across outcomes. Open-ended responses most frequently emphasized feasibility, unintended consequences, governance, and moral hazard. Overall, students largely endorsed SRM research as valuable while becoming more cautious about deployment and political prioritization, suggesting that balanced, structured instruction can sharpen sensitivity to evidence, uncertainty, and potential trade-offs that students also weighed in the survey. Full article

Microplastics (MPs) are increasingly recognized as a global environmental threat. Emerging evidence suggests they may have metabolic consequences. In this review, we synthesize current findings from animal and in vitro studies to propose a mechanistic framework linking MP exposure to type 2 diabetes mellitus (T2DM). This framework is uniquely centered on the gut–liver axis and macrophage-centric immune networks. We systematically delineate evidence suggesting that MPs can compromise intestinal barrier integrity, instigate gut dysbiosis, and promote pro-inflammatory M1 polarization of macrophages in experimental models. This immune activation is proposed to subsequently amplify hepatic inflammation, potentially contributing to systemic insulin resistance (IR) and pancreatic β-cell dysfunction. We emphasize that while this pathway is biologically plausible, direct causal evidence in humans remains limited and is a critical knowledge gap. Integrating multi-level evidence from animal models and in vitro systems, we delve into the trans-organ immunometabolic effects of MPs within adipose tissue, pancreas, and skeletal muscle, establishing their role as a novel class of “metabolic disruptors.” Critically, we assess the key controversies and knowledge gaps pertaining to dose–response relationships, particle-specific toxicity (size, polymer type, and additives), the effects of complex environmental mixtures, and the urgent need for robust human validation. We advocate for future research priorities, including multi-omics integration, advanced organ-on-a-chip platforms, prospective cohort studies, and targeted intervention strategies, to propel this field from mechanistic exploration toward clinical and public health relevance. Finally, this synthesis underscores that mitigating the production and environmental release of MPs, alongside developing strategies to impede their bioavailability and accumulation, represents a crucial public health imperative for the prevention of environment-related metabolic diseases. Full article

High-altitude mine wastelands in Southwest China present formidable challenges for ecological rehabilitation due to extreme climatic stressors and multi-element contamination. Ecological restoration is closely related to soil environment. However, the mechanism by which parent material-induced heterogeneity governs spontaneous vegetation succession is still poorly understood. We established 36 plots (216 quadrats) to investigate the soil physical and chemical properties and vegetation restoration of propylite, porphyry and siltstone in the Xifanping Copper Mine, Sichuan Province. Furthermore, fifteen metal/metalloid elements (Au, Ag, Mo, W, Cu, Pb, Zn, Hg, As, U, Se, Cr, Sn, Ti, Total Fe₂O₃), soil pollution and vegetation structure were evaluated. The study area exhibited severe composite pollution (mean Nemerow integrated pollution index = 8.09), primarily driven by Au, Ag, Mo, W, and Cu. Vegetation surveys identified 34 vascular plant species from 12 families. Propylite-derived substrates supported significantly higher species richness, Shannon–Wiener diversity, and soil organic matter than porphyry and siltstone. Redundancy analysis (RDA) identified soil organic matter (SOM) and bulk density (BD) as dominant environmental filters, with SOM explaining 14.03% of community variance (p < 0.01). Two native pioneers, Potentilla supina and Cynoglossum wallichii, were identified as specialized uranium (U) accumulators with bioconcentration factors of 13.39 and 4.49, respectively. Lithological inheritance dictates early successional trajectories by influencing edaphic structure and nutrient bioavailability. The identified U-accumulating species provide a valuable genetic resource for implementing Assisted Natural Regeneration (ANR) and developing sustainable phytoremediation strategies in contaminated alpine ecosystems. Full article

Urban business-to-business distribution in Casablanca relies heavily on light commercial vehicles (LCVs) operating in a constrained street environment where loading/unloading access, intersection capacity, and recurring bottlenecks jointly shape performance and environmental impacts. However, high-resolution freight origin–destination (OD) observations and junction calibration data are limited, which complicates direct estimations of congestion and externalities attributable to commercial activity. This study develops a reproducible, large-scale modeling workflow that couples tour-based freight demand generation in order units with simulation-based traffic assignment (SBA) on a metropolitan network and translates network performance into emissions and monetary losses. Warehouses are modeled as primary producers and commercial activity zones as attractors via sector-tagged production and attraction functions; the resulting order distribution is converted to OD vehicle trips using the tour-based trip generation procedure with the mean targets-per-tour fixed to one to ensure numerical stability, yielding a direct-shipment approximation appropriate for stress–response analysis. Junction impedance is represented through turn-type volume–delay relationships and node-level impedance procedures, and congestion is evaluated using vehicle kilometers traveled/vehicle hours traveled (VKT/VHT)-based indicators, delay-intensity measures, and link/node bottleneck rankings. Across demand-scaling scenarios, VKT increases from 302,159 to 1,017,686 veh·km/day, while network delay rises nonlinearly from 392.5 to 2738.4 veh·h/day, indicating saturation-driven amplification of time losses. The Handbook of Emission Factors for Road Transport (HBEFA)-compatible emission estimates scale with activity: total carbon dioxide (CO₂) increases from 154.1 to 519.5 t/day, and nitrogen oxides (NOx) and particulate matter (PM_2.5) totals rise proportionally under fixed fleet assumptions. Monetizing delay with a purchasing-power-adjusted value-of-time range yields a congestion cost per trip that increases from approximately 0.20 to 0.41 Moroccan dirham, MAD/trip (at 60 MAD/veh·h), consistent with rising delay intensity. Bottleneck extraction shows welfare losses to be structurally concentrated on a small persistent corridor set, led by ‘Boulevard de la Résistance’, with recurrent hotspots including ‘Rue d’Arcachon’ and ‘Rue d’Ifni’. The framework supports policy-relevant reporting of congestion, emissions, and welfare impacts under data scarcity, with explicit sensitivity bounds. Full article

E-commerce has become the driving force of regional sustainable development in the digital age. E-commerce has generated considerable economic benefits, but its resource and environmental costs have not been given sufficient attention. This study utilizes the national e-commerce demonstration city (NEDC) as a quasi-natural experiment and employs the difference-in-differences (DID) model to examine the influence of e-commerce on urban electricity consumption. The results show that e-commerce significantly reduces urban electricity intensity. Further analysis reveals that population agglomeration, economic agglomeration, and green innovation are potential channels. Meanwhile, the effect of e-commerce has obvious urban heterogeneity. The promising government and efficient market can significantly regulate the role of e-commerce in electricity utilization. Moreover, with the addition of more pilot cities, the inhibitory effect of e-commerce on electricity intensity will be weakened. These findings provide empirical evidence and implications for understanding the digitalization and energy use. Full article

Lutein and zeaxanthin are macular carotenoids known for their protective role against major eye diseases. The bio-accessibility of these macular carotenoids is extremely low, with a limited amount synthesised in plants. Quantifying these compounds in plants/biological samples is challenging because of their structural similarity. Although numerous methods have been reported for quantifying macular carotenoids, there is currently no unified chromatographic technique that can be applied for the separation and quantification of these carotenoids across diverse matrices over a broad dynamic range while also incorporating an effective extraction step. Biochemical processes during digestion and absorption further lower carotenoid levels in the body (bioavailability), making precise measurement of their esterified forms necessary. Here, we incorporate an alkaline hydrolysis extraction and present a single liquid chromatographic method applicable to both PDA and MS detection for the separation and quantification of lutein and zeaxanthin across various matrices (food, digesta, and Caco-2 cells) and concentration ranges. It utilises common solvents for the mobile phase system and a C30 column. The reverse-phase method achieved excellent recoveries in spiked samples, acceptable relative standard deviations (RSDs) for validation parameters, and offers potential for high-throughput analysis while being transferable between matrices (from plant to Caco-2 cells). Full article

Amid growing environmental pressure and increasing demand for resource sustainability, the efficient recovery of valuable metals from spent lithium-ion batteries (LIBs) has become a critical challenge in the field of resource recycling. Therefore, a novel approach is presented for selective lithium (Li) and manganese (Mn) separation from LiNi_xCo_yMn_1−x−yO₂ by combining carbothermic reduction roasting and selective leaching. Low-cost glucose (C₆H₁₂O₆) was selected as the reduction roasting reductant, which converts the cathode materials into water-soluble lithium carbonate (Li₂CO₃), water-insoluble cobalt (Co), nickel (Ni), and manganese oxide (MnO). Wet magnetic separation was employed to preferentially extract Li while simultaneously removing excess carbon from Ni, Co, and MnO. Under optimal roasting conditions at 600 °C for 90 min followed by wet magnetic separation with a liquid–solid ratio of 30 mL/g for 30 min, 95.42% of Li was preferentially extracted. Subsequently, at a formic acid (HCOOH) concentration of 1.6 mol/L, liquid–solid ratio of 6 mL/g, and leaching time of 30 min, 94.29% of Mn was selectively extracted from the wet magnetic separation products, whereas Ni and Co were leached at 6.13% and 7.22%, respectively. The acid-leaching residue can be recycled as a Ni-Co alloy. Full article

Hydropower refurbishment is increasingly recognized as a key strategy for maintaining renewable electricity generation and minimizing the environmental and social impacts of developing new infrastructure. With much of the global hydropower fleet approaching or exceeding its original design life, refurbishment decisions must strike complex trade-offs between technical performance, environmental impacts, economic viability, and social acceptability. This review provides a comprehensive summary of the scientific and policy literature on sustainable hydropower refurbishment, with a particular focus on the integration of life cycle assessment (LCA) and multi-criteria decision analysis (MCDA) from a circular economy perspective. The study systematically reviews the latest results in the fields of environmental LCA, life cycle costing (LCC), social LCA (S-LCA), and integrated life cycle sustainability assessment (LCSA), highlighting their application in the refurbishment and modernization of hydropower plants. The results show that construction-related impacts, particularly those associated with concrete and steel, dominate the environmental load over the life cycle, making refurbishment and component recycling highly effective strategies for reducing embodied emissions. The integration of LCA and MCDA allows for the transparent prioritization of refurbishment alternatives by explicitly considering stakeholder preferences and trade-offs between environmental, economic, social, and technical criteria. Overall, the results support the use of integrated, multi-criteria life cycle frameworks as reliable decision-making tools for managing sustainable hydropower refurbishment and long-term energy system resilience. Full article

Forests are vital regulators of global carbon balance, yet accelerating deforestation and land-use conversion continue to erode their capacity to sequester carbon. This research quantifies forest restoration and carbon sequestration potential across Visakhapatnam, India, by integrating imaging spectroscopy with machine learning at medium spatial resolution. Using 33 spectral and environmental predictors, an ensemble Random Forest model was developed and benchmarked against a K-Nearest Neighbors algorithm. The Random Forest approach demonstrated markedly higher predictive strength, explaining 87% of the spatial variability in tree cover, while maintaining low error margins. By excluding agricultural and urban areas, the analysis identified approximately 104,800 hectares of restorable land. The restorable area corresponds to an estimated carbon sequestration potential of about 0.12 petagrams, underscoring the district’s significant yet underutilized capacity to contribute to regional and national climate goals. The research highlights how integrating spectroscopy-derived vegetation metrics with ensemble learning enables spatially precise, policy-relevant restoration planning. By linking medium-resolution environmental data with carbon accounting, this framework advances a scalable pathway for data-driven forest recovery and nature-based climate mitigation, bridging the gap between site-specific ecological assessments and large-scale sustainability initiatives. Full article

Perovskite oxides show excellent catalytic performance for thermochemical CO₂ splitting, with A/B-site cation substitution further enhancing redox activity. While traditional first-principles methods are computationally expensive, machine learning (ML) provides an efficient approach to perovskite optimization. In this paper, machine learning is employed to investigate and predict the performance of perovskite catalysts in CO₂ decomposition reactions. Based on 227 perovskite compositions (A₁A₂)(B₁B₂)O₃ curated from experimental literature, a total of five ML models are used, including Decision Tree, Bagging, Random Forest, Extra Trees, and Gradient Boosting Regression (GBR). The Random Forest model performed best. After hyperparameter optimization, the Random Forest model achieved an R² of 0.910 and an MAE of 41.528 on an independent test set. SHAP analysis indicated that the thermal reduction temperature (T₁) and the B1-site stoichiometric fraction (C_b₁) are the most influential features governing the predicted CO yield. A higher CO yield is predicted when C_b₁ ranges from 0.6 to 0.8, and T₁ exceeds 1300 °C. This behavior can be attributed to the enhanced formation of oxygen vacancies at elevated temperatures and the optimized electronic structure induced by appropriate B-site stoichiometry. Full article

Ochratoxin A (OTA), a secondary metabolite produced by Penicillium and Aspergillus species, contaminates food and feed globally, posing serious threats to both livestock and human health. Among current detoxification strategies, probiotic-based degradation of OTA has emerged as a key research focus. This study aimed to isolate safe probiotic strains with high OTA-detoxifying efficacy to support their potential application in feed and food industries. A total of 57 bacterial strains were isolated from environmental samples, including soil, moldy feed, and animal feces. Among these, a novel strain identified as Bacillus amyloliquefaciens MM28 demonstrated strong OTA-degrading activity, removing 86.31% of OTA (0.4 µg/mL) within 48 h. Whole-genome analysis indicated that B. amyloliquefaciens MM28 harbors functional genes related to glucose metabolism, membrane transport, and properties associated with antibacterial, antioxidant, and immunomodulatory activities, suggesting multiple beneficial traits. In a 28-day chronic exposure study, mice were administered B. amyloliquefaciens MM28 via gavage (1 × 10⁸ CFU/mL). Results showed that both female and male mice in the MM28 group exhibited higher body weight and improved growth performance compared to the PBS control group. Furthermore, intestinal morphology was enhanced in the MM28 group, as indicated by greater villus length and villus-length-to-crypt-depth ratio. The expression of proinflammatory cytokines was also reduced in the treated animals. Moreover, analysis of gut microbiota composition revealed that MM28 supplementation led to an increased abundance of Bacteroides and Desulfovibrio, alongside a reduction in Lachnospira and Oscillospira. In conclusion, this study demonstrates that Bacillus amyloliquefaciens MM28 is a safe and efficient strain capable of degrading OTA. These findings highlight its promising potential as a biological detoxifying agent in food and feed industries. Full article