Search Results (31,436)

Mesoporous silica nanoparticles (MSNs) are promising nanomaterials for many applications, including water remediation, owing to their high surface area, tunable mesoporosity, and modifiable silanol-rich surfaces. However, their conventional synthesis often relies on costly tetraethyl orthosilicate (TEOS), cationic surfactants, organic solvents, and energy-intensive hydrothermal processing. Herein, a facile sustainable room-temperature sol–gel route is reported using inexpensive sodium silicate as the silica source, L-ascorbic acid as a mild biodegradable acid catalyst, and a binary nonionic surfactant system, Triton X-100/polysorbate 80, as the structure-directing template. The method replaces alkoxysilanes and hazardous cationic templates and eliminates external heating. It enables the production of uniform spherical MSNs with a locally ordered mesoporous structure, high specific surface area up to 551.5 m² g⁻¹, and large pore volume up to 1.98 cm³ g⁻¹. The adsorption capability of the optimized MSNs as nano-adsorbents was demonstrated using amoxicillin (AMX) as a model pharmaceutical contaminant. The optimized sample showed maximum AMX uptake at pH 5.0, followed pseudo-second-order kinetics, and fitted the Langmuir isotherm with a monolayer capacity of 91.3 mg g⁻¹. In spiked water matrices, the optimized MSNs recovered 88.5% and 84.4% of AMX from tap water spiked at 10 and 50 mg L⁻¹, respectively, and 83.5% and 81.0% from synthetic municipal wastewater spiked at the same concentrations, with RSD values below 5%. The adsorbent further retained 94% of its initial capacity after five adsorption–desorption cycles. This work establishes a scalable green route for producing high-quality MSNs and demonstrates the feasibility of the resulting silanol-rich mesoporous nano-adsorbents for pharmaceutical micropollutant removal, while also indicating their potential suitability as carrier platforms for drug-delivery applications. Full article

Geobacter sulfurreducens is a model bacterium widely used in microbial fuel cell (MFC) research due to its efficient extracellular electron transfer. However, the high cost of synthetic media limits the scalability of these systems, making agro-industrial byproducts like cheese whey a sustainable alternative. This study evaluated cheese whey as a growth medium for G. sulfurreducens and its influence on biofilm development on graphite bars electrodes. Bacterial growth kinetics and biofilm architecture were characterized using Atomic Force Microscopy (AFM) as the primary quantitative tool, supplemented by Scanning Electron Microscopy (SEM). Growth curves revealed a diauxic-like transition within the first 48 h, with high cell viability (94%). AFM analysis demonstrated a non-linear topographical evolution: an initial attachment phase was followed by a peak in structural heterogeneity at 14 days (S_q = 683.08 nm), eventually reaching a mature, confluent state at 21 days with a maximum thickness of ~8 μm. Energy-Dispersive Spectroscopy (EDS) confirmed an organic and mineral matrix consistent with bacterial biomass and whey components. These results demonstrate that cheese whey effectively supports the growth of G. sulfurreducens and the formation of structurally complex biofilms, highlighting its potential as a low-cost substrate for microbial cultivation and dairy waste valorization. Full article

The red imported fire ant (Solenopsis invicta Buren) is a destructive invasive pest, and conventional chemical control faces challenges related to environmental contamination and resistance development, highlighting the need for novel control agents and greener management strategies. In this study, pyrethrins-mediated silver nanoparticles (Pyr-AgNPs) were synthesized via a green route, characterized, and evaluated for their insecticidal activity, environmental stability, and metabolic effects on S. invicta workers. Bait bioassays showed that Pyr-AgNPs exhibited high toxicity to S. invicta, causing 100% cumulative corrected mortality at 500 mg·kg⁻¹ after 9 days of feeding, with a 5-d LC₅₀ of 116.83 mg·kg⁻¹. Exposure assays further demonstrated that Pyr-AgNPs had good environmental stability and residual efficacy, as bait containing 1000 mg·kg⁻¹ Pyr-AgNPs still caused 100% cumulative corrected mortality after 9 days following 96 h of outdoor exposure, significantly outperforming the pyrethrins treatment. LC-MS-based untargeted metabolomic analysis revealed that treatment with Pyr-AgNPs markedly altered the metabolic profile of S. invicta workers, with 607 differential metabolites identified, mainly belonging to organic acids and derivatives, lipid and lipid-like molecules, amino acids and peptides, cofactors, and redox-related metabolites. Pathway enrichment analysis indicated that these metabolic disturbances were primarily associated with energy metabolism, redox homeostasis, and membrane lipid metabolism. Overall, these findings provide preliminary mechanistic clues into the toxicity of Pyr-AgNPs and support their potential application in the sustainable management of S. invicta. Full article

In an era of accelerating geopolitical realignments and intensifying climate volatility, the interconnected domains of land, food, and climate have emerged as critical axes of global inequality, demanding renewed attention within sustainability education. This study addresses the central problem that existing geography, environmental, and sustainability curricula rarely engage with the geopolitical forces shaping Water, Energy, Land and Food (WELF), thereby obscuring progress toward achieving SDG 2 (Zero Hunger), SDG 13 (Climate Action) and SDG 15 (Life on Land). Situated within the Water, Energy, Land, and Food (WELF) nexus. Employing a Systematic Literature Review methodology, guided by PRISMA protocols and grounded in Political Ecology Theory, findings reveal that agricultural protectionism and land-grabbing dynamics originating from the Global North exacerbate climate-induced food insecurity and land dispossession in the Global South. Critically, the synthesis demonstrates that these dimensions of climate–food geopolitics remain inadequately addressed in existing curricula, leaving learners ill-equipped to critically analyze the structural forces underlying land-based vulnerabilities. The study recommends embedding land–food–climate geopolitics into sustainability curricula through decolonial, systems-thinking pedagogies; integrating scenario-based simulations of land-centric climate negotiations; and developing transdisciplinary modules that combine geospatial land-use analysis, political economy of agrifood systems, and indigenous land knowledge. Full article

Water temperature fluctuations directly affect the feeding, reproduction, and survival of aquatic animals. Understanding the molecular networks that regulate temperature responses is therefore critical for selective breeding of thermotolerant strains. In this study, we first assessed the thermotolerant performances of two Procambarus clarkii populations (selected and normal cultured populations) with contrasting thermal endurance capacities. Temperature stress challenges showed that the selected population exhibited great endurance capacities to both heat and cold stresses. Further comparative transcriptomic analysis showed that cold stress mainly upregulated energy metabolism genes, whereas heat stress affected oxidative stress and membrane-related genes in both populations. However, we found that immune-related pathway genes were significantly downregulated in the selected population in response to heat challenge. Furthermore, heat shock proteins (HSPs), E3 ubiquitination, and autophagy-related genes showed contrasting expression patterns between the thermotolerant and normal cultured populations, suggesting that transcriptional regulations of these signaling pathways may contribute to thermal tolerance. Collectively, these results provide a reference for breeding thermotolerant P. clarkii strains and supporting the sustainable development of the aquaculture industry. Full article

Energy-intensive firms are key participants in China’s carbon emissions trading system (CETS). However, evidence on whether CETS promotes the green transformation (GT) of these firms remains limited. In this study, a multi-period difference-in-differences (DID) model is applied to investigate the impacts of CETS on the GT of 529 listed firms from six energy-intensive industries over the period 2007–2024. Results show that CETS significantly promotes GT, and the findings remain robust after parallel trend, placebo, propensity score matching (PSM)-DID, Goodman-Bacon decomposition, and alternative variable tests. Further analysis reveals that internal control and green technological innovation (Ginn) positively moderate the effects of CETS on the GT of energy-intensive firms. Heterogeneity analysis reveals that the promoting effect is more pronounced in highly competitive industries and among firms with stronger green reputations. These findings provide empirical evidence on the effectiveness of CETS in facilitating the GT of energy-intensive firms. Full article

Hybrid additive manufacturing (HAM) integrates additive and subtractive processes within a unified production system, combining the geometric flexibility and material efficiency of additive manufacturing with the dimensional accuracy and surface quality of conventional machining. This review provides a comprehensive analysis of HAM technologies through a proposed four-criterion classification framework encompassing process integration strategy, additive manufacturing process type, machine architecture, and application domain. DED-based, PBF-based, and polymer-based hybrid systems are examined alongside integrated hybrid machines, retrofit solutions, and robotic architectures. A comparative analysis of representative commercial platforms evaluates build envelope, integration strategy, and monitoring capability. Documented performance outcomes across aerospace, automotive, energy, and biomedical sectors confirm substantial improvements in surface quality, fatigue performance, dimensional accuracy, and material efficiency relative to conventional manufacturing routes. Current limitations are critically assessed across technical, process integration, and economic dimensions, and a structured near-to-long-term research roadmap is proposed, prioritising in-process sensing and toolpath standardisation, digital twin-based adaptive process planning, and ultimately autonomous hybrid manufacturing cells with lifecycle certification. These findings position HAM as a central enabling technology for intelligent, flexible, and sustainable production within Industry 4.0 and Industry 5.0 paradigms. Full article

Devoting attention to the mechanisms of enhancing energy efficiency through the transition to clean energy sources plays a vital and active role in moving forward towards environmental sustainability in the industrial economy. Industrial CO₂ emissions across the Gulf Cooperation Council (GCC) remain persistently high despite growing regional commitments to clean energy transition and sustainability. This study examines the key determinants of industrial CO₂ emissions in all six GCC member states over the period 2004–2022, focusing on energy efficiency, electricity consumption, oil use, trade openness, and economic growth. The analysis employs advanced panel econometric techniques, including cross-sectional dependence tests, second-generation unit root tests, and panel autoregressive distributed lag estimators, to identify both short-run and long-run relationships among the variables. The results reveal that in the short run, energy intensity is the sole statistically significant driver of industrial emissions. In the long run, energy intensity continues to increase emissions, while trade openness significantly reduces them. Neither oil consumption nor industrial electricity use exerts a significant positive long-run effect on emissions, pointing to a gradual decoupling driven by improving industrial energy efficiency and cleaner electricity generation. These findings suggest an emerging decoupling between industrial activity and carbon emissions in the GCC, driven by improvements in energy efficiency. For GCC economies pursuing economic diversification and net-zero targets, reducing industrial energy intensity and expanding low-carbon energy sources remain critical pathways toward sustainable industrial development. Full article

The energy transition in maritime shipping is increasing the importance of alternative fuels and port infrastructure capable of handling them in a safe, regular, and economically justified manner. In this context, LNG remains a transitional fuel with a relatively high level of technological and organizational maturity, particularly in regions characterized by intensive liner, ferry, and RO-RO traffic. This article proposes a universal model for organizing LNG distribution within the port–transport system, based on three interdependent dimensions: demand potential, infrastructure readiness, and operational feasibility. The model structure enables the classification of ports according to their functions within the regional bunkering network and the identification of nodes of the greatest systemic importance. The model was validated using data on vessel calls, the structure of container and RO-RO traffic, LNG infrastructure status, and monthly traffic variability. The analysis demonstrated that the most justified LNG distribution arrangement in the Baltic Sea is polycentric in nature and concentrated in ports, combining a high degree of transport regularity with confirmed LNG readiness. The results indicate that the rationale for LNG infrastructure development is selective in nature and depends on the actual position of a port within the transport network, rather than solely on cargo throughput volume. The proposed model also retains its applicability to other alternative fuels after adjustment of technological, regulatory, and operational parameters. By supporting the selective development of alternative-fuel infrastructure in ports with the highest systemic relevance, the model contributes to sustainable maritime transport planning and to the transition toward lower-emission port–transport systems. Full article

This study examines how the strategic integration of digital transformation and national innovation capacity contributes to accelerating sustainable development in Saudi Arabia by focusing on six Sustainable Development Goals (SDGs): SDG 4—Quality Education, SDG 7—Affordable and Clean Energy, SDG 8—Decent Work and Economic Growth, SDG 9—Industry, Innovation and Infrastructure, SDG 12—Responsible Consumption and Production, and SDG 13—Climate Action. Using annual data on ICT use, ICT access, R&D expenditure, and patent applications, the analysis evaluates both the direct and joint relationships between these indicators and SDG performance. Digital transformation is captured through ICT use and ICT access, while national innovation capacity is represented by R&D expenditure and patent applications, reflecting the input and output dimensions of formal innovation activity. The findings indicate that the direct long-run effects of digital transformation and national innovation capacity on the six SDGs are not statistically significant, suggesting that these domains have not yet become standalone drivers of educational advancement, clean-energy adoption, economic performance, industrial upgrading, sustainable resource management, or emissions reduction. In contrast, their interaction produces substantial positive effects on SDG 4, SDG 7, SDG 8, and SDG 9, highlighting improvements in educational quality, renewable energy transition, productivity, and industrial innovation. The interaction also has significant negative effects on SDG 12 and SDG 13, as reflected by reductions in CO₂ intensity and environmental pressures. These results indicate that meaningful progress toward the SDGs emerges when digital capabilities and national innovation capacity evolve jointly, rather than through isolated improvements in ICT infrastructure or innovation inputs. Robustness checks using a composite SDG index confirm the stability of these complementary effects. These findings suggest that Saudi Arabia can accelerate progress toward the SDGs by adopting integrated policies that link ICT expansion with stronger R&D systems, patent commercialization, technological innovation, and sustainability-oriented industrial transformation across education, energy, industry, resource efficiency, and climate action. Full article

Globally, wildfires are increasingly threatening forest ecosystems and human well-being, requiring proactive management strategies. Integrating wildfire mitigation with bioenergy production presents a dual opportunity to reduce fire risk while contributing to clean energy. This study builds upon previous work by incorporating updated annual heat load estimates from 32 off-grid communities in northern Canada to assess the amount of biomass at risk of wildfire that could be mobilized to meet local bioenergy needs. Our results reveal that energy consumption in the remote communities considered was previously significantly underestimated, with an average of 11,710 MWh per year, and a minimum and maximum of 1869 and 43,867 MWh per year, respectively. With the updated dataset, which includes both space heating and electricity energy usage, the average energy demand is approximately 300% higher than earlier estimates. Despite this substantial increase in energy consumption, the amount of biomass needed to meet local energy demand per year ranges from 352 to 8276 odt per year, representing only a small fraction (approximately 1.67% on average) of the total biomass identified as being at risk within a 10 km buffer. This corresponds to fuel treatment areas ranging from 4 to 222 hectares per year (around 51 ha on average), depending on the community. The results presented here, based on updated energy data, provide important insights into the operational feasibility of this approach. To be successful, implementation will require strong community leadership and collaboration with fire management agencies to design consistent and cost-effective fuel treatment strategies that are tailored to each community’s environmental conditions and energy needs. Full article

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

Grid-connected photovoltaic–battery energy storage–electric vehicle (PV-BESS-EV) charging stations require supervisory energy management that can coordinate tariff response, carbon-intensity signals, peak constraints, storage utilization, and converter-level operability within a transparent evidential framework. This study develops a bounded-reference rule-based supervisory energy management system (RB-SEMS) that preserves lower-level local converter controllers while generating operating modes and saturated reference commands for BESS power, grid exchange, and EV charging limits. A dual-time-scale evaluation framework is established by combining short-time switching/control simulations for dynamic traceability and SOC-sensitive protection with 24 h, 15 min EMS-level energy-balance simulations for cost, carbon, peak, PV utilization, EV service, and storage throughput assessment. Selected daily reference-injection cases are retained as copied-model diagnostic checks rather than as full-day switching-level validation. Under the D4-LSOC condition, RB-SEMS reduces the reported post-startup DC-bus deviation from 46.13 V to 40.60 V and the filtered BESS peak from 269.18 kW to 84.42 kW. In the E1-TOU scenario, E1-TOU-cost reduces daily total cost from 623.57 CNY to 564.05 CNY, lowers peak-period grid import from 183.75 kWh to 126.75 kWh, and increases local PV utilization from 71.13% to 78.71%; E1-PC66 further reduces the maximum 15 min grid import from 77.88 kW to 66.00 kW. Under the prescribed E2-PCC scenario, E2-CP reduces the calculated grid-related CO₂ emissions from 550.29 kg to 500.42 kg, whereas the price-only diagnostic increases them to 572.29 kg. Same-metric PV-SC and MILP comparisons, tested-range sensitivity analysis, and a throughput-based degradation proxy clarify that RB-SEMS is an interpretable supervisory baseline for cost–carbon–peak–cycling trade-off analysis rather than a cost-optimal controller or regionally validated proof of carbon reduction. Full article

In the context of the global transition toward sustainability and energy efficiency, the retrofitting of existing service buildings has become a strategic priority. With the increasing adoption of electric vehicles (EVs) and the need to reduce greenhouse gas emissions, adapting these buildings is essential to achieving low-carbon urban environments. This paper presents a numerical tool developed to simulate the energy performance of a service building and to evaluate the impact of multiple energy efficiency measures on energy consumption and CO₂ emissions. The assessed measures include the installation of photovoltaic panels on roofs and facades, optimization of Heating, Ventilation, and Air Conditioning (HVAC) systems through temperature set-point adjustments, improvements to the building envelope and integration of electric mobility infrastructure. The analysis focuses on an existing building in Lisbon, Portugal, considering both individual and combined effects of these strategies. The results indicate that combined implementation of all measures, including EV integration, can reduce energy demand and CO₂ emissions by up to approximately 50%. However, regulatory uncertainty regarding EV accounting remains a challenge, highlighting the need for clearer policies to support sustainable urban transformation. Full article

Heavy metal (HM) contamination in urban soils is a pressing global issue, particularly in rapidly industrializing regions like Kazakhstan, where anthropogenic activities such as transportation, energy production, and manufacturing exacerbate accumulation in ecosystems. In Almaty, the largest city in Kazakhstan, urban expansion and legacy pollution pose risks to soil functions, biodiversity, and public health through bioaccumulation and migration pathways. This study evaluates the spatial distribution and ecological impacts of total heavy metal concentrations (HMs) (Pb, Cd, As, Zn, Cu, Ni, Co, Mo, Mn) in Almaty’s soils to inform remediation strategies. Soil samples (n = 73) were collected using a systematic grid sampling method across urban, industrial, and peri-urban zones in Almaty. HM concentrations were determined via X-ray fluorescence spectrometry (XRF) following GOST 33850-2016 standards. Pollution indices (contamination factor K_c and integrated pollution index Z_c) were calculated relative to Kazakhstani permissible limits (PDK RK) and Russian approximate permissible concentrations (ODK RF). Statistical analyses included Spearman’s correlation, boxplots, and coefficient of variation. Morphological, physicochemical (pH, humus content), and biological assessments evaluated degradation. Spatial interpolation via GIS mapped the hotspots. HM distributions showed significant variability, with As, Zn, and Ni exceeding norms in >90% of samples (median K_c ≈ 5 for As). Z_c classified >70% of sites as hazardous or extremely hazardous (Z_c > 32), with hotspots in central-eastern districts (Z_c 90–145). Strong correlations (ρ ≥ 0.6) identified a technogenic group (Pb–Zn–Cu–Ni) from traffic and industry, contrasting predominantly geogenic elements with possible anthropogenic contribution (As–Co–Mo–Mn). Pollution induced soil compaction, reduced humus/pH, and disrupting biogeochemical cycles. Local exceedances were noted near TECs, factories, and transport hubs. Almaty’s soils exhibit pervasive technogenic HM pollution, driven by urban sources, leading to ecosystem degradation and health risks. Future research should incorporate vertical profiling and isotopic sourcing for refined risk models. Prioritized monitoring and phytoremediation in hotspots are recommended to enhance resilience, aligning with UN SDGs for sustainable cities and ecosystems. Future research should incorporate vertical profiling and isotopic sourcing for refined risk models. Full article