Search Results (7,595)

The accelerating global energy transition has substantially increased demand for critical minerals such as copper, nickel, and lithium, positioning mining firms as key actors in the decarbonization of energy systems. However, the expansion of mineral extraction raises important sustainability challenges because mining activities remain highly energy- and carbon-intensive. This study investigates whether green innovation can simultaneously improve environmental performance and financial performance in critical mineral mining firms and examines the moderating role of institutional governance. Using a balanced panel of 35 publicly listed mining companies from Australia, Canada, Chile, Brazil, and Indonesia over the period 2015–2024, the analysis applies fixed-effects panel regressions complemented by dynamic specifications and multiple robustness tests, including alternative variable definitions and System Generalized Method of Moments (GMM) estimation. The results show that green innovation significantly reduces carbon intensity, indicating that environmental investments in renewable energy integration, electrification, and process efficiency contribute to improving emissions performance in mining operations. Green innovation also enhances firm financial performance, although the benefits emerge gradually over time, suggesting delayed financial gains followed by long-term efficiency improvements. Furthermore, governance quality strengthens the positive relationship between green innovation and firm performance, highlighting the importance of institutional environments in shaping the economic returns of sustainability strategies. By providing firm-level evidence across major mineral-producing economies, this study contributes to the literature on critical minerals, environmental finance, and the institutional dimensions of the just energy transition. Full article

Phosphorus deficiency in the environment induces phosphate (Pi) starvation responses of plants, in which the phosphate transporter is one of the most critical functional genes in this response mechanism. As a prevalent green manure crop in China, Vicia villosa plays a critical role in sustainable agricultural systems, and the expression of its phosphate transporter gene (VvPHT1) is modulated by soil phosphorus availability, highlighting its key adaptive function in nutrient acquisition and utilization under low-Pi conditions. Functional studies of this gene and its promoter contribute to exploring the molecular mechanisms of the tolerance of green manure crops to low phosphorus stress and to improving phosphorus-efficient V. villosa varieties. In this study, analysis of the VvPHT1 promoter sequence revealed a 1524 bp region containing multiple root-specific cis-regulatory elements, including five NODCON2GM, one NODCON1GM, six OSE2ROOTNODULE, one OSE1ROOTNODULE, and fifteen ROOTMOTIFTAPOX1 motifs. Histochemical GUS staining of transgenic Arabidopsis (Arabidopsis thaliana (L.) Heynh.) showed that the VvPHT1 promoter directed root-specific expression of the GUS reporter gene. A fusion expression vector pCAMBIA1300-VvPHT1--GFP was constructed and transformed into tobacco (Nicotiana tabacum L.) cells for subcellular localization analysis, indicating that the protein encoded by VvPHT1 was localized to the plasma membrane. To quantify its expression, VvPHT1 transcript levels in VvPHT1-overexpressing Arabidopsis (OEPHT1) lines were analyzed by quantitative real-time PCR (qRT-PCR) under different phosphorus supply conditions. The results demonstrated that under low-Pi conditions, the expression of VvPHT1 was significantly upregulated in the OEPHT1 lines compared to those of normal-Pi conditions. Furthermore, under low-Pi treatment, the OEPHT1 lines showed significantly increased fresh weight, primary root length, phosphorus content, and chlorophyll content compared to the wild-type Arabidopsis (WT), while no such differences were observed under normal-Pi conditions. In conclusion, the VvPHT1 promoter exhibits root-specific activity, and the VvPHT1 gene encodes a plasma-membrane-localized phosphate transporter that is strongly induced by phosphorus deficiency. Its overexpression enhances phosphorus uptake and plant growth under low-Pi conditions, suggesting that VvPHT1 likely functions as a high-affinity phosphate transporter involved in the adaptation to phosphorus starvation. Full article

Cadmium is an element that is unnecessary for the functioning of plant and animal organisms, and its widespread presence in the environment poses a serious threat to human and animal health. Therefore, effective methods are being sought to remediate soils contaminated with this element, including through the enrichment of degraded soils with organic matter. To this end, the effectiveness of selected organic sorbents, including starch, fermented bark, compost and humic acids, in mitigating the transfer of cadmium and other heavy metals from soil to plants was assessed. Model studies compared the effects of 15 and 30 mg of cadmium (Cd) per kg of soil with an uncontaminated control sample. The sorbents were applied on a carbon basis at a rate of 3 g C per kg of soil. The test plant was Zea mays. Cadmium was found to significantly impair plant growth, causing reductions of 21%, 85%, and 77% in leaf greenness, aboveground biomass and root biomass, respectively. Excess cadmium increased the translocation of lead, chromium, copper, nickel, zinc, iron, and manganese from the roots to the aboveground parts of the plant, while simultaneously limiting their uptake. All of the organic sorbents tested reduced the negative impact of cadmium on leaf greenness, except starch. Compost and HumiAgra significantly improved the condition of Zea mays plants weakened by cadmium exposure. Cadmium contamination increased soil acidification. pH was positively correlated with maize yield and the SPAD leaf greenness index and negatively correlated with the cadmium translocation index and cadmium content in the aboveground parts of maize. Compost and humic acids are among the most effective and practically feasible approaches for reducing cadmium bioavailability in soil and its accumulation in Zea mays, and are therefore recommended for the remediation of cadmium-contaminated soils. Full article

Deep learning models represent one of the most advanced and effective approaches in predictive modeling. Their hierarchical architectures enable the extraction of complex, non-linear feature relationships and the identification of latent patterns within data, making them highly suitable for tasks involving high-dimensional or unstructured inputs. However, these models are computationally demanding, requiring significant processing resources and time. Furthermore, their predictive performance is largely contingent upon the availability of large-scale datasets. In this study, a Deep Green Framework is employed for the prediction of two computer vision tasks. CIFAR-10 and CIFAR-00 have been taken for image classification. Fifteen convolutional neural network (CNN) variants categorized into light-weight and heavy-weight are trained for the prediction of these two datasets. Based on energy footprint, time, memory usage, Top-1 accuracy, Top-3 accuracy, model size, and model parameters. The study highlights that MobileNetV3-Small produces the best outcomes when compared to other trained models having low task latency and higher efficiency, making it highly suitable for edge environments where resources are scarce. Full article

To mitigate fossil fuel dependency and facilitate the transition towards a green economy, utilization of hydrogen energy has emerged as a paramount objective. Nevertheless, during transportation, this goal introduces novel challenges pertaining to material integrity, notably hydrogen embrittlement. This review systematically examines contemporary research on hydrogen embrittlement in natural gas pipelines conveying hydrogen blends and elucidates the hydrogen sources, permeation pathways, and embrittlement mechanisms. By scrutinizing the intrinsic material attributes and operational environments, this study provides an in-depth analysis of the pivotal factors influencing the susceptibility of pipeline steel to hydrogen embrittlement, thereby furnishing a theoretical foundation for the enduring safety of hydrogen pipelines. Full article

Conventional spatial frequency domain imaging (SFDI) based optical property inversion is inefficient, while deep learning methods suffer from heavy reliance on large-scale real datasets. To address this contradiction, a simulation-driven approach for subsurface fruit bruise discrimination was proposed. An SFDI simulation environment was built with Blender to generate 800 paired datasets of diffuse reflectance images and optical transport coefficients, overcoming the high cost and long cycle of real dataset acquisition. We designed the CBAM-GAN-U-Net model and adopted surface profile correction in the prediction method to eliminate curved surface-induced non-planar distortion, with the whole method validated on liquid phantoms, green apples and crown pears. This prediction method achieved high accuracy in predicting the reduced scattering coefficient μ_s′, with NMAE of 0.021 ± 0.007 (phantoms), 0.039 ± 0.012 (severely bruised green apples) and 0.044 ± 0.015 (severely bruised crown pears), outperforming U-Net and GANPOP. Based on the predicted μ_s′, a discrimination strategy combining coefficient of variation, mean ratio and receiver operating characteristic (ROC) curve analysis was adopted, attaining 100% accuracy for non-bruised/bruised fruit discrimination, with misclassification rates of 6% (green apples) and 8% (crown pears) for mild/severe bruise differentiation. This method enables accurate subsurface fruit bruise detection, providing a reliable technical solution for the fruit and vegetable industry and helping reduce postharvest supply chain losses. Full article

Tissue scaffolds are one of the main components of the tissue engineering triad, playing a vital role in tissue engineering. However, their production procedures heavily rely on solvent-intensive and energy-demanding methods. This raises serious questions about industrial-scale manufacturability, residual solvent toxicity to living health, and sustainability for nature and the environment. Therefore, the main aim of this study is to identify robust scaffolds that provide a suitable microenvironment for resident cells and promote tissue regeneration, while reducing waste through environmentally friendly production methods. In this context, the scalable and ecologically friendly production methods emerge as necessary alternatives as biodegradable polymer scaffolds are used in more therapeutic settings. Clinically applicable and green synthesis-based supercritical carbon dioxide (scCO₂) technologies, melt electrowriting (MEW), and solvent-free processing techniques are the main topics of this study for a critical analysis of biodegradable polymer scaffold production techniques. Scaffold structure–property correlations, polymer selection and interactions, production procedures, the benefits and drawbacks of existing fabrication technologies, and sustainability issues are discussed in detail. It aims to contribute a novel perspective and approach to literature by presenting and comparing production-oriented approaches as sustainable and green methods. The challenges in the development of biodegradable tissue scaffolds, along with the significance of green manufacturing techniques, are also revealed. The approach is designed to connect processing factors to scaffold features in addition to evaluating current technologies. This review tries to offer a framework for producing biodegradable polymer scaffolds in a sustainable and clinically implementable context. Full article

Subway-hub blocks are critical areas where the pressures of metropolitan populations and environmental quality are closely interconnected. This study constructs a “pressure–context–carrier–response” (PCRC) framework (F1–F7) to systematically reveal the correlations between built-environment characteristics and environmental performance. The results demonstrate that resource allocation (F7) and comprehensive response (F5) display notable “asymmetric differentiation”. The socio-economic environment (F2, F3) considerably influences the concentration of green-space resource allocations (F7) (p < 0.01), with affluent blocks demonstrating a clear advantage in resource distribution. The thermo-ecological composite response (F5), which includes NDVI and LST, demonstrates “statistical convergence” (p = 0.894) across various block types, indicating that resource inputs cannot be linearly transformed into environmental efficiency. This disconnection is ascribed to two physical limitations: firstly, the stochastic nature of spatial distribution (Global Moran’s I ≈ 0) restricts the scale effects of green spaces; secondly, the nonlinear limitations of the physical medium indicate that under conditions of high pressure load (F1) and elevated spatial capacity (F6), the regulatory effectiveness of greening demonstrates a significant diminishing marginal return effect. Therefore, intervention planning must shift from controlling macro-level indicators to optimising micro-level accuracy to address ecological performance constraints in densely populated metropolitan areas. Full article

Urbanisation reshapes Land Cover and Land Use (LCLU) by driving deforestation, wetland loss, and the conversion of natural and agricultural areas into built environments. However, integrated analyses of LCLU change in response to climate variability in topographically complex, rapidly urbanising African cities remain limited. Therefore, this study examined 2000–2024 LCLU changes in hilly Gasabo District (Kigali, Rwanda) using 30 m Landsat imagery and a Random Trees classifier (92.7% accuracy, 70/30 train-test split), with 2032 projections via a population-driven hybrid trend model. Population estimates/projections 320,516 in 2002 to 967,512 in 2024, 1.41 million by 2032, were derived from Rwanda’s census data and exponential growth modelling (calibrated to 5.05% annual growth). Rapid population growth has driven a 539% expansion of Built-up Areas, accompanied by notable declines in cropland and Forest. Local climate trends (Meteo Rwanda stations) aligned with global datasets (ERA5-Land and CHIRPS): rainfall fluctuation and temperature rose, with strong correlations between population-driven Built-up Areas expansion. From 2024 to 2032, LCLU projections indicate that Built-up Areas will continue to expand by 29.5%. Cropland was forecast to decline to 15.9%, while Forest loss slowed to 5.7%. MLR analysis revealed strong correlations between population-driven expansion of Built-up Areas, cropland/forest loss, warming, and rainfall fluctuations in Gasabo. An ARDL model was applied to address multicollinearity among LCLU predictors, which limited the interpretation of individual coefficients, and confirmed the core MLR correlation trends, with statistically significant (p < 0.05) coefficients. The results highlight the need for data-driven spatial planning in Gasabo (stricter zoning, high-rise buildings, targeted reforestation, climate-resilient green infrastructure) to mitigate population and urbanisation-driven environmental degradation. Full article

Urbanization and climate change intensify urban heat islands and air pollution; therefore, street canyon building planning that accounts for road orientation, shading, thermal environment, and ventilation is crucial. This study uses numerical simulations to investigate how non-uniform wall and road heating affects airflow and pollutant dispersion in street canyons under varying Richardson numbers (Ri) and heating scenarios (windward wall, leeward wall, road surface). The results indicate that large wall–atmosphere temperature differences combined with low incoming wind speed (high Ri) make thermal buoyancy a dominant control on canyon flow and pollutant transport. Heating of the leeward wall and road surface enhances ventilation and pollutant removal (prominently when the Ri ≥ 0.49), whereas heating of the windward wall suppresses dispersion and increases concentrations (prominently when the Ri ≥ 0.12). For a north–south street, diurnal solar heating produces strong micro-environmental contrasts. With easterly winds, morning heating of the windward wall elevates pollutant levels, while afternoon heating of the leeward wall promotes dispersion and lowers concentrations. Specifically, compared with the isothermal condition, the turbulent exchange rate at the top of the street canyon is enhanced to 1.71~6.86 times, while the convective exchange rate is suppressed to 58%~83% in the morning and enhanced to 1.21~1.92 times. These findings suggest that urban planning should limit windward wall temperature rises via shading and greening; thus, single-sided sidewalk and greening layouts on the windward side are recommended. Full article

Nowadays, organic, inorganic, and microbial pollutants are listed as a substantial threat to the environment as well as public health, leading to water contamination. Green technologies such as photocatalytic and photoelectrocatalytic processes have appeared as favorable tools for water remediation, leading to effective degradation of pollutants under environmentally relevant operating conditions. With the rapid development of photocatalysis in the 21st century, heterogeneous catalysts have been extensively engineered to improve light utilization and promote surface redox reactions. This review presents an overview of recent advances in the synthesis, design, and application of heterogeneous catalysts for water purification. Key reaction mechanisms, material modifications, and hybrid processes are discussed. Also, the growing need for environmentally friendly, sustainable, and cost-effective catalytic materials is underlined. Attention was given to the role of molecular modeling in understanding catalytic mechanisms and guiding the design of efficient and sustainable catalytic materials. By critically analyzing contemporary progress, limitations, and emerging trends, this review directs future research activities towards increasingly efficient and scalable water purification methods. Full article

Silver nanoparticles (AgNPs) are widely recognized for their potent antibacterial properties and diverse biomedical applications. While conventional synthesis methods typically rely on chemical-reducing agents that may pose risks to human health and the environment, this study proposes an eco-friendly green synthesis approach utilizing porcine skin extracts. The extracts were prepared through thermal treatment and filtration to serve as a biological reducing agent. Successful synthesis was validated using dynamic light scattering, Fourier transform infrared (FTIR) spectroscopy, UV–Vis spectroscopy, and scanning electron microscopy (SEM). Furthermore, the antimicrobial efficacy of the synthesized AgNPs was evaluated against multidrug-resistant microorganisms, demonstrating significant growth inhibition across various antibiotic-resistant strains. These findings suggest that porcine skin—a readily available bioresource—is a promising precursor for the sustainable production of AgNPs with broad-spectrum antimicrobial potential. Full article

Tree and shrub planting is a widely used strategy to restore degraded semi-arid grasslands. Although nutrient resorption is a key adaptation to nutrient-limited environments, its dynamics at decadal scales remain poorly understood. In this study, we measured species-averaged nitrogen resorption efficiency (NRE) at both community and functional group levels, together with soil nutrients, across 20- and 40-year shrub-planted sites and a 40-year tree-planted site in Inner Mongolia, China. At the community level, green and senesced leaf nitrogen (N) concentrations, NRE, and aboveground biomass did not differ significantly among sites. However, clear differences emerged at the functional group level: Poaceae exhibited higher NRE than forbs and lower senesced leaf N than both forbs and Fabaceae. As restoration progressed, Poaceae replaced forbs as the dominant group, coinciding with increased soil nutrient availability. Notably, NRE in Poaceae declined with increasing soil nutrients, suggesting a shift toward greater reliance on direct soil nutrient uptake. This shift, combined with the production of low-nitrogen litter by dominant Poaceae species, may ultimately slow soil nutrient accumulation. Our findings highlight the importance of functional group dynamics in regulating long-term nutrient resorption and cycling and suggest that managing Poaceae dominance could enhance long-term soil nutrient enrichment and biodiversity in restored semi-arid grasslands. Full article

Urban heat dynamics are strongly influenced by the interaction between built structures, surface materials, and vegetation cover. This study investigates the relationship between land surface temperature (LST) and key urban morphological and structural parameters in a municipality of Thessaloniki, Greece. LST was retrieved from Landsat imagery using the NDVI-based emissivity method within Google Earth Engine (GEE). To characterize the urban form of the study area, a WorldView-2 summer image was classified to extract indices of surface roughness, built-up density, greenness density, building orientation and roof material type. Statistical analyses, including regression models and one-way ANOVA, were applied to assess the influence of these parameters on LST variability. Results reveal significant correlations between LST and both structural and vegetative factors, highlighting the cooling role of urban greenness and the amplifying effect of dense built-up areas and specific roof materials. The findings provide valuable insights into the spatial drivers of urban heat at a high-resolution scale, and offer practical guidance for planning strategies designed to lessen heat intensity in compact urban environments. Full article

Nanofluid flooding technology has demonstrated enormous potential in enhancing the recovery efficiency of unconventional oil and gas resources. However, due to the complex physicochemical properties of nanofluids and their intricate interaction mechanisms in different reservoir environments, the research and application of nanofluids still face numerous challenges. Although existing review articles have systematically covered various aspects of nanofluid flooding technology and its enhanced oil recovery (EOR) mechanisms, they have not comprehensively addressed all facets of nanofluid-based EOR. In particular, they lack detailed introductions to the field applications of nanofluid flooding technology in reservoirs with different geological structural characteristics, the preparation of bio-based nano-oil displacement materials, the technology of forming nanofluids through in situ self-assembly of silica nanoparticles by reservoir microorganisms, and nanomaterial-mediated carbon dioxide flooding and microbial flooding technologies. This paper aims to identify the existing deficiencies in current nanofluid EOR technologies, especially focusing on the green and low-carbon microbial composite nanofluid flooding technology based on the utilization of reservoir microbial resources. Furthermore, targeted future development directions are proposed, with the goal of providing a more comprehensive, in-depth, and forward-looking reference for the theoretical research and industrial application of nanofluid EOR technologies, thereby further promoting the advancement of EOR technologies for low-permeability and tight oil reservoirs. Full article