Search Results (1,108)

Unionid mussel populations in a section of the Clinch River in Virginia, USA, has declined substantially, but the causes of the decline remain unknown. To investigate this zone of decline (ZOD), we deployed juvenile freshwater mussels (Villosa iris in 2012 and Lampsilis fasciola in 2013) in both cages and silos at sites within the Clinch River System. We analyzed mussel tissues for trace element and organic contaminant concentrations, shells for trace elements, and environmental media (total water, dissolved water, particulate sediment, and bedload sediment) for both inorganic and organic contaminants. We found a few differences between mussels deployed in cages and those deployed in silos: survival was slightly lower in cages due to periodic sedimentation. Our results identified the ZOD based on the accumulation of trace elements (notably As, Cu, Fe, Mn, Ni, and Sr), polycyclic aromatic hydrocarbons (PAHs), and δ¹⁵N enrichment, with especially high concentrations found in the human-impacted tributaries, Dumps Creek and Guest River. Some correlations were found between environmental media and both mussel tissues and shells. In particular, PAHs and Mn had several significant relationships between bioaccumulated concentrations and environmental concentrations. Finally, Co, Cu, Fe, and V in soft tissues negatively correlated with mussel growth, whereas bioaccumulated PAH concentrations correlated negatively with resident mussel densities. Full article

Various pretreatment methods for the valorization of sunflower husks (SHs) for H₂ gas generation through fermentation by Escherichia coli were investigated. We analyzed thermal treatment (TT), acid hydrolysis (AH), and alkaline hydrolysis (AlkH) at different substrate concentrations (50 g L⁻¹, 75 g L⁻¹, 100 g L⁻¹, and 150 g L⁻¹) and dilution levels (undiluted, 2× diluted, and 5× diluted). A concentration of 75 g L⁻¹ SH that was acid-hydrolyzed and dissolved twice in the medium yielded optimal microbial growth, reaching 0.3 ± 0.1 g cell dry weight (CDW) L⁻¹ biomass. The highest substrate level enabling effective fermentation was 100 g L⁻¹, producing 0.37 ± 0.13 (g CDW) × L⁻¹ biomass after complete fermentation, while 150 g L⁻¹ exhibited pronounced inhibitory effects. It is worth mentioning that the sole alkaline treatment was not optimal for growth and H₂ production. Co-fermentation with glycerol significantly enhanced both biomass formation (up to 0.42 ± 0.15 (g CDW) × L⁻¹)) and H₂ production. The highest H₂ yield was observed during batch growth at 50 g L⁻¹ SH hydrolysate with 5× dilution, reaching up to 5.7 mmol H₂ (g sugar)⁻¹ with glycerol supplementation. This study introduces a dual-waste valorization strategy that combines agricultural and biodiesel industry residues to enhance clean energy generation. The novelty lies in optimizing pretreatment and co-substrate fermentation conditions to maximize both biohydrogen yield and microbial biomass using E. coli, a widely studied and scalable host. Full article

There is an increasing demand for the development of efficient and sustainable battery recycling processes. Currently, many recycling processes rely on toxic inorganic acids to recover materials from high-value battery chemistries such as lithium nickel manganese cobalt oxides (NMCs) and lithium cobalt oxide (LCOs). However, as cell manufacturers seek more cost-effective battery chemistries, the value of the spent battery value chain is increasingly diluted by chemistries such as lithium iron phosphate (LFPs). These cheaper alternatives present a difficulty when recycling, as current recycling processes are geared towards dealing with high-value chemistries; thus, the current processes become less economical. To date, much research is focused on treating a single battery chemistry; however, often, the feed material entering a battery recycling facility is contaminated with other battery chemistries, e.g., LFP feed contaminated with NMC, LCO, or LMOs. This research aims to selectively leach various battery chemistries out of a mixed feed material with the aid of a green organic acid, namely oxalic acid. When operating at the optimal conditions (2% solids, 0.25 M oxalic acid, natural pH around 1.15, 25 °C, 60 min), this research has proven that oxalic acid can be used to selectively dissolve 95.58% and 93.57% of Li and P, respectively, from a mixed LFP-NMC mixed feed, all while only extracting 12.83% of Fe and 8.43% of Mn, with no Co and Ni being detected in solution. Along with the high degree of selectivity, this research has also demonstrated, through varying the pH, that the selectivity of the leaching system can be altered. It was determined that at pH 0.5 the system dissolved both the NMC and LFP chemistries; at a pH of 1.15, the LFP chemistry (Li and P) was selectively targeted. Finally, at a pH of 4, the NMC chemistry (Ni, Co and Mn) was selectively dissolved. Full article

This dataset presents environmental observations collected in August 2021 from 18 port and harbor sites located around Jeju Island, Korea. It includes physical, biogeochemical, and greenhouse gas (GHG) variables measured in surface seawater, such as temperature, salinity, dissolved oxygen, nutrients, chlorophyll-a, pH, total alkalinity, and dissolved inorganic carbon. Concentrations and air–sea fluxes of nitrous oxide (N₂O), methane (CH₄), and carbon dioxide (CO₂) were also quantified. All measurements were conducted following standardized analytical protocols, and certified reference materials and duplicate analyses were used to ensure data accuracy. Consequently, the dataset revealed that elevated nutrient accumulation in port and harbor waters and GHG concentrations tended to be higher at sites with stronger land-based influence. During August 2021, most sites functioned as sources of N₂O, CH₄, and CO₂ to the atmosphere. This integrated dataset offers valuable insights into the influence of anthropogenic and hydrological factors on coastal GHG dynamics and provides a foundation for future studies across diverse semi-enclosed marine systems. Full article

This study focused on the carbonate system dynamics and air–sea CO₂ fluxes in the open-ocean waters of the Madeira–Tore Seamount Complex during August 2024. Surface water properties revealed pronounced latitudinal gradients in sea surface temperature (21.9–23.1 °C), salinity (36.2–36.7), and dissolved oxygen (228–251 µmol Kg⁻¹), influenced by mesoscale eddies and topographically driven upwelling. Despite oligotrophic conditions, distinct phytoplankton assemblages were observed, with coccolithophores dominating southern seamounts and open-ocean stations, and green algae and diatoms indicating episodic nutrient input. Surface total alkalinity (TA: 2236–2467 µmol Kg⁻¹), dissolved inorganic carbon (DIC: 2006–2183 µmol Kg⁻¹), and pCO₂ (467–515 µatm) showed spatial variability aligned with water mass characteristics and biological activity. All stations exhibited positive air–sea CO₂ fluxes (2.8–11.5 mmol m⁻² d⁻¹), indicating the region is a CO₂ source during summer. Calcite and aragonite saturation states were highest in stratified, warmer waters. Principal Component Analysis highlighted the role of physical mixing, carbonate chemistry, and biological uptake in structuring regional variability. Our findings emphasize and contribute to the complex interplay of physical and biogeochemical drivers in modulating carbon cycling and ecosystem structure across Atlantic seamounts. Full article

Background/Objectives: The integration of machine learning (ML) and artificial intelligence (AI) has revolutionized the pharmaceutical industry by improving drug discovery, development and manufacturing processes. Based on literature data, an ML model was developed by our group to predict the formation of binary co-amorphous systems (COAMSs) for inhalation therapy. The model’s ability to develop a dry powder formulation with the necessary properties for a predicted co-amorphous combination was evaluated. Methods: An extended experimental validation of the ML model by co-milling and X-ray diffraction analysis for 18 API-API (active pharmaceutical ingredient) combinations is presented. Additionally, one COAMS of rifampicin (RIF) and ethambutol (ETH), two first-line tuberculosis (TB) drugs are developed further for inhalation therapy. Results: The ML model has shown an accuracy of 79% in predicting suitable combinations for 35 APIs used in inhalation therapy; experimental accuracy was demonstrated to be 72%. The study confirmed the successful development of stable COAMSs of RIF-ETH either via spray-drying or co-milling. In particular, the milled COAMSs showed better aerosolization properties (higher ED and FPF with lower standard deviation). Further, RIF-ETH COAMSs show much more reproducible results in terms of drug quantity dissolved over time. Conclusions: ML has been shown to be a suitable tool to predict COAMSs that can be developed for TB treatment by inhalation to save time and cost during the experimental screening phase. Full article

Aquaculture expansion to meet global protein demand has intensified concerns over nutrient pollution and greenhouse gas (GHG) emissions. While floating treatment wetlands (FTWs) are proven for water quality improvement, their potential to mitigate GHG emissions in marine aquaculture remains poorly understood. This study quantitatively evaluated the dual capacity of Sesuvium portulacastrum FTWs to (a) regulate dissolved inorganic nitrogen (DIN) and (b) reduce CO₂/N₂O emissions in grouper aquaculture systems. DIN speciation (NH₄⁺, NO₂⁻, NO₃⁻) and CO₂/N₂O fluxes of six controlled ponds (three FTW and three control) were monitored for 44 days. DIN in the FTW group was approximately 90 μmol/L lower than that in the control group, and the water in the plant group was more “oxidative” than that in the control group. The former groups were dominated by NO₃⁻, with lower dissolved inorganic carbon (DIC) and N₂O concentrations, whereas the latter were dominated by NH₄⁺ during the first 20 days of the experiment and by NO₂⁻ at the end of the experiment, with higher DIC and N₂O concentrations on average. Higher primary production may be the reason that the DIC concentration was lower in the plant group than in the control group, whereas efficient nitrification and uptake by plants reduced the availability of NH₄⁺ in the plant group, thereby reducing the production of N₂O. A comparison of the CO₂ and N₂O flux potentials in the plant group and control group revealed that, in the presence of FTWs, the CO₂ and N₂O emissions decreased by 14% and 36%, respectively. This showed that S. portulacastrum FTWs effectively couple DIN removal with GHG mitigation, offering a nature-based solution for sustainable aquaculture. Their low biomass requirement enhances practical scalability. Full article

Penta-graphene, a novel two-dimensional carbon allotrope entirely composed of pentagonal carbon rings, has attracted increasing attention due to its unique geometric structure, mechanical robustness, and intrinsic semiconducting nature. In this study, we systematically investigate the adsorption behavior of three typical dissolved gases in transformer oil (CO, C₂H₂, and C₂H₄) on penta-graphene using first-principles calculations based on density functional theory. The optimized adsorption configuration, adsorption energy, charge transfer, adsorption distance, band structure, density of states, charge density difference, and desorption time are analyzed to evaluate the sensing capability of penta-graphene. Results reveal that penta-graphene exhibits moderate chemical interactions with CO and C₂H₂, accompanied by noticeable charge transfer and band structure changes, whereas C₂H₄ shows weaker physisorption characteristics. The projected density of states analysis further confirms the orbital hybridization between gas molecules and the substrate. Additionally, the desorption time calculations suggest that penta-graphene possesses good sensing and recovery potential, especially under elevated temperatures. These findings indicate that penta-graphene is a promising candidate for use in gas sensing applications related to the monitoring of dissolved gases in transformer oils. Full article

Soil degradation exerts profound impacts on soil ecological functions, global food security, and human development, making the development of effective technologies to mitigate degradation a critical research focus. Microorganisms play a leading role in rehabilitating degraded land, improving soil hydraulic properties, and enhancing soil structural stability. Mosses contribute to soil particle fixation through their unique rhizoid structures; however, the mechanisms underlying their interactions in mixed inoculation remain unclear. Therefore, this study addresses soil and water loss caused by rainfall erosion in the cold black soil region. We conducted controlled laboratory experiments cultivating Bacillus subtilis and cold-adapted moss species, evaluating the erosion mitigation effects of different biological treatments under gradient slopes (3°, 6°, 9°) and rainfall intensities (70 mm h⁻¹, 120 mm h⁻¹), and elucidating their carbon-based structural reinforcement mechanism. The results indicated that compared to the control group, Treatment C significantly increased the mean weight diameter (MWD) and geometric mean diameter (GMD) of soil aggregates by 121.6% and 76.75%, respectively. In separate simulated rainfall events at 70 mm h⁻¹ and 120 mm h⁻¹, Treatment C reduced soil loss by 95.70% and 96.75% and decreased runoff by 38.31% and 67.21%, respectively. Crucially, the dissolved organic carbon (DOC) loss rate in Treatment C was only 21.98%, significantly lower than that in Treatment A (32.32%), Treatment B (22.22%), and the control group (51.07%)—representing a 59.41% reduction compared to the control. This demonstrates the following: (1) Bacillus subtilis enhances microbial metabolism, driving carbon conversion into stable pools, while mosses reduce carbon leaching via physical barriers, synergistically forming a dual “carbon protection–structural reinforcement” barrier. (2) The combined inoculation optimizes soil structure by increasing the proportion of large soil particles and enhancing aggregate stability, effectively suppressing soil loss even under extreme rainfall erosion. This study elucidates, for the first time, the biological pathway through which microbe–moss interactions achieve synergistic carbon sequestration and erosion resistance by regulating aggregate formation and pore water dynamics. It provides a scalable “carbon–structure”-optimized biotechnology system (co-inoculation of Bacillus subtilis and moss) for the ecological restoration of the cold black soil region. Full article

[Background] Brasenia schreberi is a perennial floating leaf aquatic plant with high ecological protection value and potential for economic development, and thus, its endangered mechanisms are of great concern. The rapid endangerment of this species in modern times may be primarily attributed to the deterioration of water and soil environmental conditions, as its growth relies on high-quality water and soil. [Objective] Exploring the responses of B. schreberi to water and soil conditions from the perspective of functional traits is of great significance for understanding its endangered mechanisms and implementing effective conservation strategies. [Methods] This study was conducted in the Tengchong Beihai Wetland, which has the largest natural habitat of B. schreberi in China. By measuring the key functional traits of B. schreberi and detecting the water and soil parameters at the collecting sites, the responses of these functional traits to the water and soil conditions have been investigated. [Results] (1) The growth status of B. schreberi affects the expression of its functional traits. Compared with sporadic distribution, B. schreberi in continuous patches have significantly higher stomatal conductance, intercellular CO₂ concentration, transpiration rate, and vein density, while these plants have significantly smaller leaf area and perimeter. (2) Good water quality directly promotes photosynthetic, morphological, and structural traits. However, high soil carbon, nitrogen, and phosphorus contents can inhibit the photosynthetic rate. The net photosynthetic rate is significantly positively correlated with dissolved oxygen content, pH value, ammonia nitrogen, and nitrate nitrogen contents in the water, as well as the magnesium, zinc, and silicon contents in the soil. In contrast, the net photosynthetic rate is significantly negatively correlated with the total phosphorus content in water and the total carbon, total nitrogen, and total phosphorus content in the soil. (3) Leaf area and perimeter show positive correlations with various water parameters, including the depth, temperature, pH value, dissolved oxygen content, ammonium nitrogen, and nitrate nitrogen content, yet they are negatively correlated with total phosphorus content, chemical oxygen demand, biological oxygen demand, and permanganate index of water. [Conclusions] This study supports the idea that B. schreberi thrives in oligotrophic water environments, while the notion that fertile soil is required for its growth still needs to be investigated more thoroughly. Full article

Background/Objectives: Airborne viral diseases pose a health risk, due to which there is a growing interest in developing filter materials capable of capturing fine particles containing virions from the air and that also have a virucidal effect. Nanofiber membranes made of poly(vinylidene fluoride) dissolved in N,N-dimethylacetamide and functionalized with copper, silver, and zinc nanoclusters were fabricated via electrospinning. This study aims to evaluate and compare the virucidal effects of nanofibers functionalized with metal nanoclusters against the human influenza A virus A/WSN/1933 (H1N1) and SARS-CoV-2. Methods: A comprehensive characterization of materials, including X-ray diffraction, scanning electron microscopy, microwave plasma atomic emission spectroscopy, thermogravimetric analysis, contact angle measurements, nitrogen sorption analysis, mercury intrusion porosimetry, filtration efficiency, and virucidal tests, was used to understand the interdependence of the materials’ physical characteristics and biological effects, as well as to determine their suitability for application as antiviral materials in air filtration systems. Results: All the filter materials tested demonstrated very high particle filtration efficiency (≥98.0%). The material embedded with copper nanoclusters showed strong virucidal efficacy against the SARS-CoV-2 alpha variant, achieving an approximately 1000-fold reduction in infectious virions within 12 h. The fibrous nanowire polymer functionalized with zinc nanoclusters was the most effective material against the human influenza A virus strain A/WSN/1933 (H1N1). Conclusions: The materials with Cu nanoclusters can be used with high efficiency to passivate and kill the SARS-CoV-2 alpha variant virions, and Zn nanoclusters modified activated porous membranes for killing human influenza A virus A7WSN/1933 (H1N1) virions. Full article

Globally, phosphogypsum (PG) is the primary by-product of the phosphorus industry. Aspergillus niger (A. niger), one of the most powerful types of phosphate-solubilizing fungi (PSF), can secrete organic acids to dissolve the phosphates in PG. This study investigated heavy metal (HM) remediation by PG and A. niger under the co-existence of Pb and Cd. It demonstrated that 1 mmol/L Pb²⁺ stimulated the bioactivity of A. niger during incubation, based on the CO₂ emission rate. PG successfully functioned as P source for the fungus, and promoted the growth of the fungal cells. Meanwhile, it also provided sulfates to immobilize Pb in the solution. The subsequently generated anglesite was confirmed using SEM imaging. The immobilization rate of Pb reached over 95%. Under co-existence, Pb²⁺ and 0.01 mmol/L Cd²⁺ maximized the stimulating effect of A. niger. However, the biotoxicity of Pb²⁺ and elevated Cd²⁺ (0.1 mmol/L) counterbalanced the stimulating effect. Finally, 1 mmol/L Cd²⁺ dramatically reduced the fungal activity. In addition, organic matters from the debris of A. niger could still bind Pb²⁺ and Cd²⁺ according to the significantly lowered water-soluble Pb and Cd concentrations. In all treatments with the addition of Cd²⁺, the relatively high biotoxicity of Cd²⁺ induced A. niger to absorb more Pb²⁺ to minimize the sorption of Cd²⁺ based on the XRD results. The functional group analysis of ATR-IR also confirmed the phenomenon. This pathway maintained the stability of Pb²⁺ immobilization using the fungus and PG. This study, hence, shed light on the application of A. niger and solid waste PG to remediate the pollution of Pb and Cd. Full article

Dissolved gas analysis remains the most widely utilized non-intrusive diagnostic method for detecting incipient faults in insulating liquid-immersed transformers. Despite their prevalence, conventional ratio-based methods often suffer from ambiguity and limited potential for automation applicrations. To address these limitations, this study proposes a unified multiclass classification model that integrates traditional gas ratio features with supervised machine learning algorithms to enhance fault diagnosis accuracy. The performance of six machine learning classifiers was systematically evaluated using training and testing data generated through four widely recognized gas ratio schemes. Grid search optimization was employed to fine-tune the hyperparameters of each model, while model evaluation was conducted using 10-fold cross-validation and six performance metrics. Across all the diagnostic approaches, ensemble models, namely random forest, XGBoost, and LightGBM, consistently outperformed non-ensemble models. Notably, random forest and LightGBM classifiers demonstrated the most robust and superior performance across all schemes, achieving accuracy, precision, recall, and F1 scores between 0.99 and 1, along with Matthew correlation coefficient values exceeding 0.98 in all cases. This robustness suggests that ensemble models are effective at capturing complex decision boundaries and relationships among gas ratio features. Furthermore, beyond numerical classification, the integration of physicochemical and dielectric properties in this study revealed degradation signatures that strongly correlate with thermal fault indicators. Particularly, the CIGRÉ-based classification using a random forest classifier demonstrated high sensitivity in detecting thermally stressed units, corroborating trends observed in chemical deterioration parameters such as interfacial tension and CO₂/CO ratios. Access to over 80 years of operational data provides a rare and invaluable perspective on the long-term performance and degradation of power equipment. This extended dataset enables a more accurate assessment of ageing trends, enhances the reliability of predictive maintenance models, and supports informed decision-making for asset management in legacy power systems. Full article

Previous investigations into lithology-driven weathering processes have largely emphasized large-scale spatial assessments, while studies targeting small watershed scales remain scarce. This study investigated two adjacent watersheds (Chengjia: CJ; Datan: DT) under comparable climatic conditions in Guangdong, China, using hydrochemistry and stable carbon isotopes. The CJ watershed exhibited low-TDS (20–66 mg/L) HCO₃-Na·Ca-type waters dominated by silicate weathering, whereas the DT watershed displayed high-TDS (70–278 mg/L) HCO₃-Ca-type waters, indicative of mixed carbonate–silicate weathering. Results of carbon isotope composition of dissolved inorganic carbon confirmed that H₂CO₃-driven weathering was the dominant mechanism in both watersheds. In the CJ watershed, 79.5% of dissolved cations in surface water originated from silicate weathering, yielding a CO₂ consumption rate (CCR) of 0.28 × 10⁶ mol/km²/yr, while carbonate weathering was negligible. Conversely, in the DT watershed, 86.4% of dissolved cations were derived from carbonate weathering, yielding a CCR of 1.94 × 10⁶ mol/km²/yr, whereas silicate weathering contributed only 10.3% of cations with a CCR of 0.23 × 10⁶ mol/km²/yr. The chemical weathering rate of carbonate can be up to 10 times that of silicate, resulting in a larger CCR. This study demonstrated the key impact of lithology on hydrochemical characteristics and CO₂ consumption at small watershed scales. Full article

Biological nitrogen (N) fixation is an ecological method used to provide nutrition for crops and reduce fertilizer application in terrestrial ecosystems. Silver nanoparticles (AgNPs) are becoming environmental contaminants, and, thus, could negatively affect the activity and diversity of soil diazotrophs. To test this, a greenhouse pot experiment for growing maize was performed under different concentrations of AgNPs (0, 1, 5, 10, 20 mg kg⁻¹). We measured the N₂-fixation activity and abundance of nifH gene encoding the nitrogenase reductase subunit and analyzed the diversity, composition and co-occurrence networks of diazotrophic communities in maize rhizospheric soil. Results showed that a lower dose of AgNPs did not show significant influence on soil diazotrophs, while a higher dose of AgNPs decreased both soil N₂-fixation activity and nifH gene abundance, though diazotrophic diversity remained unchanged. AgNPs at 10 mg kg⁻¹ and 20 mg kg⁻¹ strongly shifted the community composition of diazotrophs, increasing the proportions of Bradyrhizobium and Paenibacillus, while decreasing Azospirillum and Rhizobium. Network analysis revealed weakened negative associations among species under AgNPs, with keystone taxa shifting from Bradyrhizobium, Geobacter, Azospirillum and Burkholderia to Bradyrhizobium, Paenibacillus and Skermanella under AgNPs. Soil-soluble Ag, dissolved organic carbon and soil pH were identified as the factors most closely driving the diazotrophic community composition. In conclusion, higher doses of AgNPs could inhibit N₂-fixation activity and shape the diazotrophic communities. These findings provide empirical evidence of AgNPs’ ecological impacts on soil microbial functions. Full article