Search Results (58)

The increasing accumulation of plastic waste—especially from packaging and post-consumer sources—calls for the development of sustainable recycling strategies. Due to the challenges associated with sorting mixed waste, directly processing waste streams offers a practical approach. Polyethylene terephthalate (PET) and high-density polyethylene (HDPE) are common consumer plastics, but they are difficult to recycle together due to immiscibility and degradation. In mixed waste, recycled HDPE (r-HDPE) often contaminates the recycled PET (r-PET) stream. Additive manufacturing (AM) offers a promising solution to upcycle these mixed polymers into functional products with minimal waste. This study investigates the processing and characterization of r-PET/r-HDPE blends for AM, focusing on the role of compatibilizers in enhancing their properties. Blends were melt-compounded using a twin-screw extruder to improve dispersion, followed by direct pellet-based 3D printing. A compatibilizer (0–7 php) was incorporated to improve miscibility. Rheological testing showed that the 5 php compatibilizer optimized viscosity and elasticity, ensuring smoother extrusion. Thermal analysis revealed a 30 °C increase in crystallization temperature and a shift in decomposition temperature from 370 °C to 400 °C, indicating improved thermal stability. Mechanical testing showed a tensile strength of 35 MPa and 17% elongation at break at optimal loading. Scanning electron microscopy (SEM) confirmed reduced phase separation and improved morphology. This work demonstrates that properly compatibilized r-PET/r-HDPE blends enable sustainable 3D printing without requiring polymer separation. The results highlight a viable path for the conversion of plastic waste into high-value, customizable components, contributing to landfill reduction and advancing circular economy practices in polymer manufacturing. Full article

This study reports the synthesis of activated carbon from dwarf elder, a lignocellulosic precursor, yielding a material with a high specific surface area (500.43 m²/g) and mesoporous structure (median pore radius: 3.88 nm). The physicochemical properties of the obtained carbon were characterized using field-emission scanning electron microscopy (FE-SEM), Brunauer–Emmett–Teller (BET) analysis, and Fourier-transform infrared spectroscopy (FTIR), confirming its suitability for aqueous-phase sorption applications. Batch experiments demonstrated carbon’s efficacy in adsorbing amlodipine besylate (AMB), a model pharmaceutical pollutant, with a maximum capacity of 325.9 mg/g under optimized conditions (pH 10.0, room temperature). Systematic evaluation of key parameters, such as initial AMB concentration, sorbent dosage, pH, and agitation speed revealed that sorption kinetics adhered to pseudo-second-order and Elovich model. The high efficiency of the synthesized carbon material, coupled with its low-cost and eco-friendly synthesis, positions it as a promising candidate for the scalable remediation of AMB and structurally related pharmaceuticals from contaminated water sources. Full article

Heavy metal contamination in water resources presents a significant environmental and public health challenge, with lead being particularly concerning due to its toxicity and persistence. This study reports the green synthesis of Fe-Ti mixed oxide nanoparticles (NPs) using dextrose as a green source and investigates their effectiveness in lead removal from aqueous solutions. The synthesized NPs were characterized using XRD, FTIR, XPS, SEM-EDS, and BET analysis, revealing an amorphous structure with a high surface area (292.89 m² g⁻¹) and mesoporous characteristics. XPS analysis confirmed the presence of mixed Fe³⁺/Fe²⁺ valence states in a Ti⁴⁺-rich framework, creating diverse binding sites for lead adsorption. The material exhibited optimal lead removal at pH 5, with adsorption following pseudo-second-order kinetics (R² > 0.99) and a Langmuir isotherm model (R² > 0.98). Maximum adsorption capacity reached 25.10 mg g⁻¹ at 40 °C, showing endothermic behavior. The low point of zero charge (PZC, 0.22) and surface hydroxyl groups enabled efficient lead binding possibly through multiple mechanisms. Dose optimization studies established 6 g L⁻¹ as the optimal adsorbent concentration. The synergistic combination of iron’s affinity for heavy metals and titanium’s structural stability, coupled with environmentally friendly synthesis, resulted in a promising material for sustainable water treatment applications. Full article

The increasing presence of pharmaceutical contaminants, such as paracetamol, in water sources necessitates the development of efficient and sustainable treatment technologies. This study investigates the photocatalytic degradation and mineralization of paracetamol under visible light using nickel-doped titanium dioxide (Ni–TiO₂) catalysts synthesized via the sol-gel method. The catalysts were characterized through Raman spectroscopy, UV–Vis diffuse reflectance spectroscopy (UV–Vis DRS), and surface area measurements. Ni doping enhanced the visible light absorption of TiO₂, reducing its band gap from 3.11 eV (undoped) to 2.49 eV at 0.20 wt.% Ni loading, while Raman analysis confirmed Ni incorporation with anatase as the predominant phase. The Ni(0.1%)-TiO₂ catalyst exhibited the highest photocatalytic activity, achieving 88% total organic carbon (TOC) removal of paracetamol (5 ppm) after 180 min under optimal conditions (catalyst dosage, 3 g L⁻¹). Stability tests demonstrated 84% retained efficiency over five cycles, with a kinetic rate constant of 0.010 min⁻¹. Hydroxyl radicals were identified as the main reactive species. The catalyst maintained high performance in tap water, achieving 78.8% TOC removal. These findings highlight the potential of Ni(0.1%)-TiO₂ as a cost-effective, visible light-active photocatalyst for the removal of pharmaceutical pollutants, with promising scalability for industrial water treatment applications. Full article

Background: Laying hens, which are widely utilized for consumption and export in various regions, experience prolonged antibiotic exposure due to their longer lifespan, increasing the risk of antibiotic resistance and impacting the microbial environment of poultry slaughterhouses. Given the significance of extended-spectrum-β-lactamase (ESBL)-producing Escherichia coli in food safety, this study aimed to investigate the prevalence of ESBL genes in E. coli isolated from a laying hen slaughterhouse in Konya, Turkey. Methods: Sampling was conducted using a convenient sampling approach, and a total of 150 samples were collected from a single slaughterhouse over six visits during both warm (June–August) and cold (January–March) seasons to evaluate seasonal variations. Samples were categorized into environmental sources (personnel, air, wastewater, eggs) and carcass-related sources (cloaca, carcasses at critical control points, final product). Classical cultural and molecular techniques and antimicrobial susceptibility tests were used for ESBL presence and gene characterization. For sequence analysis, the bidirectional Sanger Gene sequence analysis method was applied. Results: PCR-based detection identified 10 of the 17 isolates as E. coli by amplifying the uspA gene, and bidirectional Sanger sequencing further confirmed these isolates at the species level. The E. coli isolates were detected at various sampling areas, including personnel, carcasses after evisceration, and raw wastewater samples collected at different time points. In the multiplex PCR analysis, most ESBL isolates were positive for the blaCTX-M gene. The co-existence of blaTEM and blaCTX-M genes was detected in five samples. Additionally, three genes (blaSHV, blaCTX-M, and blaOXA) were identified in a carcass sample after evisceration. All ESBL-producing isolates harbored the blaCTX-M1 gene, and multiple antibiotic resistance was observed across all isolates. The presence of these genes was strongly associated with resistance to ampicillin, amoxicillin-clavulanic acid, aztreonam, cefepime, cefpodoxime, cefuroxime, and cephalothin, highlighting the critical role of blaCTX-M in driving the multidrug resistance patterns observed in this study. The highest resistance rate (80%) was observed in “personnel” and “carcass samples after evisceration”, while all isolates remained sensitive to carbapenems (imipenem and meropenem). Conclusions: Our findings highlight the importance of the laying hen slaughter line as a potential source of contamination with ESBL-producing E. coli, which poses significant implications for food safety and public health. These findings underscore the need for improved control measures to mitigate ESBL E. coli transmission in poultry processing and highlight the importance of optimizing antibiotic use strategies in laying hen farming. Full article

Pharmaceutical contamination of water sources has become a critical environmental challenge. Bentonite (BN), a natural clay mineral, has gained attention due to its high surface area, cation exchange capacity, and cost-effectiveness, making it a promising adsorbent for removing contaminants. This study explores the potential of BN and its acid-treated form (BA1) as effective adsorbents for the removal of tetracycline hydrochloride (TC) from aqueous solutions. Comprehensive characterization was performed using analytical techniques, including XRF, XRD, SEM/TEM, XPS, TG/DTG, and CO₂ and N₂ adsorption–desorption isotherms. The results indicate that BA1 is a mesoporous material with a surface area exceeding 165 m²·g⁻¹. The adsorption process was fitted to a pseudo-second-order kinetic model. BA1 achieved a maximum adsorption capacity of 40.98 mg·g⁻¹ and removal efficiency of up to 99% within only 30 min at an optimal pH of 5. Equilibrium isotherm calculations for BA1 show the best fit for the Freundlich model R² > 0.9923, indicating a favorable adsorption process. The material was reused over seven consecutive cycles to evaluate the regeneration capacity of the clay mineral materials. BN stands out for its effectiveness, cost-effectiveness, and environmental sustainability as a promising material for water treatment applications. Full article

Heavy metal contamination of water sources has emerged as a major global environmental concern, affecting both aquatic ecosystems and human health. Therefore, this study aims to remove hexavalent chromium from an aqueous solution utilizing activated carbon developed from Spathodea campanulata. Chemical treatment with H₃PO₄ followed by thermal activation was employed to enhance the adsorption capability of the precursor material. On the other hand, a full factorial design of 2⁴ including pH (3 and 9), contact time (30 and 60 min), initial chromium concentration (40 and 100 mg/L), and adsorbent dosage of 0.2 and 0.6 g/100 mL was used to optimize the batch-wise adsorption of hexavalent chromium. The characterization results showed that the prepared activated carbon is composed of various functional groups (FTIR), a high specific surface area of 1054 m²/g (BET), morphological cracks (Scanning Electron Microscopy), and a pH point of zero charge of 5.8. The maximum removal efficiency of 96.5% was recorded at optimum working conditions of pH 3, contact time of 60 min, adsorbent dosage of 0.6 g/100 mL, and initial chromium concentration of 40 mg/L. Additionally, kinetics and isotherm studies revealed that the pseudo-second-order model with R² of 0.98 and the Sips model with R² of 0.99 were found to fit the adsorption data better, suggesting homogenous surface and chemisorption. Overall, this research suggests that Spathodea campanulata could be a promising natural source for the development of adsorbents with potential applications in remediating chromium-saturated wastewater at an industrial scale. Full article

Background: Tear fluid, rich in proteins, is a promising source of novel biomarkers for ocular and systemic health. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is the primary method for biomarker discovery. Still, factors such as limited sample volume, extracellular protein contamination, and reflex tearing can significantly impact results. Glass microcapillary tubes minimize these issues. Schirmer strips remain the most common collection method due to existing LC-MS/MS protocol optimization. Methods: In this study, we evaluated multiple digestion protocols for the shotgun quantitative LC-MS/MS analysis of small-volume tear fluid samples collected using glass capillary tubes. Protocol optimization was performed using pooled samples and then compared with the analysis of individual samples. Results: Using the optimized protocol, one μL samples were processed using a timsTOF Pro 2 mass spectrometer (Bruker) coupled online with an Evosep One liquid chromatography system (Evosep), leading to the identification of an average of 361 ± 63 proteins in pooled samples and 525 ± 123 proteins in individual small-volume tear fluid samples. Conclusions: This protocol highlights the practicality of using glass capillary tubes for comprehensive LC-MS/MS-based tear proteomics analysis, paving the way for detailed proteomics characterization of individual tear fluid samples rather than pooled samples. By shifting from pooled to individual samples, this approach greatly accelerates tear biomarker discovery, advancing precision and personalized medicine. Full article

Chitosan-based biosorbents are particularly valuable in environmental applications, such as wastewater treatment for contaminant removal. However, several challenges remain in optimizing their production and performance related to improving adsorption efficiency, stability, scalability, cost, and sustainable sourcing for large-scale applications. The removal of Methylene Blue (MB) and Orange 16 (O16) from aqueous solutions was studied using a biosorbent derived from the waste biomass of the brewing industry, specifically Saccharomyces pastorianus immobilized into chitosan. The biosorbent (obtained by a straightforward entrapment technique) was characterized using Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Analysis (EDAX) to evaluate its structural properties. The biosorption behavior toward organic contaminants, specifically a cationic and an anionic dye, was investigated. Key operational factors that influenced the biosorbent’s efficiency were examined, including the initial dye concentration, dye type, pH of the aqueous solution, and the amount of biosorbent used. These factors were evaluated during the initial stage of the biosorption studies to assess their impact on the overall performance and effectiveness of the biosorbent in removing the dyes from aqueous solutions. Using this eco-friendly biosorbent, the biosorption capacities obtained using the Langmuir isotherm model were 212.77 mg/g in the case of MB dye and 285.71 mg/g in the case of O16 mg/g, and the results confirmed that the biosorption process is based on a physical mechanism as suggested by the energy values of the process, E, obtained using the DR model: the obtained values of 6.09 kJ/mol (MB dye) and 7.07 kJ/mol (O16 dye) suggest a process based on electrostatic interaction bonds. These results indicate that residual biomass of Saccharomyces pastorianus, as a byproduct of a biotechnological process, can be exploited as a biosorbent by immobilization in an organic matrix (chitosan) for the retention of polluting organic species from the aqueous environment present in aqueous solutions in moderate concentrations. Full article

Contaminant Source Identification in Water Distribution Network (CSWIDN) is critical for ensuring public health, and optimization algorithms are commonly used to solve this complex problem. However, these algorithms are highly sensitive to the problem’s landscape features, which has limited their effectiveness in practice. Despite this, there has been little experimental analysis of the fitness landscape for CSWIDN, particularly given its mixed-encoding nature. This study addresses this gap by conducting a comprehensive fitness landscape analysis of CSWIDN using the Nearest-Better Network (NBN), the only applicable method for mixed-encoding problems. Our analysis reveals for the first time that CSWIDN exhibits the landscape features, including neutrality, ruggedness, modality, dynamic change, and separability. These findings not only deepen our understanding of the problem’s inherent landscape features but also provide quantitative insights into how these features influence algorithm performance. Additionally, based on these insights, we propose specific algorithm design recommendations that are better suited to the unique challenges of the CSWIDN problem. This work advances the knowledge of CSWIDN optimization by both qualitatively characterizing its landscape and quantitatively linking these features to algorithms’ behaviors. Full article

Microalga–bacteria consortia are increasingly recognized for their effectiveness in wastewater treatment, leveraging the metabolic synergy between microalgae and bacteria to enhance nutrient removal and overall treatment efficiency. These systems offer a sustainable approach to addressing pollutants such as nitrogen and phosphorus. However, their potential in removing specific contaminants like steroid hormones is less explored. In this study, a natural microbial consortium, A21, has been characterized and isolated from primary sewage treatment in Madrid and its potential for bioremediation of steroid hormone effluents has been evaluated. The A21 consortium includes Alphaproteobacteria genera Sphingopyxis and Pseudorhizobium and the Cyanobacterium Cyanobium. Sphingopyxis (31.78%) is known for biodegradation, while Pseudorhizobium (15.68%) exhibits detoxification abilities. Cyanobium (14.2%) may contribute to nutrient uptake and oxygen production. The effects of pH, nitrogen sources, and Sodium chloride concentrations on growth were evaluated. The optimal growth conditions were determined to be a pH range of 7 to 9, a salt concentration below 0.1 M, and the presence of a nitrogen source. The consortium also demonstrated effective growth across various types of wastewaters (primary, secondary, and tertiary treatment effluents). Additionally, A21 exhibited the ability to grow in the presence of steroids and transform them into other compounds, such as converting androstenedione (AD) into androsta-1,4-diene-3,17-dione (ADD) and β-estradiol into estrone. Full article

Accurately delineating sediment export dynamics using high-quality vegetation factors remains challenging due to the spatio-temporal resolution imbalance of single remote sensing data and persistent cloud contamination. To address these challenges, this study proposed a new framework for estimating and analyzing monthly sediment inflow to rivers in the cloud-prone Minjiang River Basin. We leveraged multi-source remote sensing data and the Continuous Change Detection and Classification model to reconstruct monthly vegetation factors at 30 m resolution. Then, we integrated the Chinese Soil Loss Equation model and the Sediment Delivery Ratio module to estimate monthly sediment inflow to rivers. Lastly, the Optimal Parameters-based Geographical Detector model was harnessed to identify factors affecting sediment export. The results indicated that: (1) The simulated sediment transport modulus showed a strong Coefficient of Determination (R² = 0.73) and a satisfactory Nash–Sutcliffe Efficiency coefficient (0.53) compared to observed values. (2) The annual sediment inflow to rivers exhibited a spatial distribution characterized by lower levels in the west and higher in the east. The monthly average sediment value from 2016 to 2021 was notably high from March to July, while relatively low from October to January. (3) Erosive rainfall was a decisive factor contributing to increased sediment entering the rivers. Vegetation factors, manifested via the quantity (Fractional Vegetation Cover) and quality (Leaf Area Index and Net Primary Productivity) of vegetation, exert a pivotal influence on diminishing sediment export. Full article

Community drinking water sources are increasingly contaminated by various point and non-point sources, with emerging organic contaminants and microbial strains posing health risks and disrupting ecosystems. This study explores the use of zinc oxide nanoparticles (ZnO-NPs) as a non-specific agent to address groundwater contamination and combat microbial resistance effectively. The ZnO-NPs were synthesized via a green chemistry approach, employing a sol-gel method with lemon peel aqueous extract. The catalyst was characterized using techniques including XRD, ATR-FTIR, SEM-EDAX, UV-DRS, BET, and Raman spectroscopy. ZnO-NPs were then tested for photodegradation of quinoline yellow dye (QY) under sunlight irradiation, as well as for their antibacterial and antioxidant properties. The ZnO-NP photocatalyst showed significant photoactivity, attributed to effective separation of photogenerated charge carriers. The efficiency of sunlight dye photodegradation was influenced by catalyst dosage (0.1–0.6 mg L⁻¹), pH (3–11), and initial QY concentration (10–50 mg L⁻¹). The study developed a first-order kinetic model for ZnO-NPs using the Langmuir–Hinshelwood equation, yielding kinetic constants of equilibrium adsorption and photodegradation of Kc = 6.632 × 10⁻² L mg⁻¹ and kH = 7.104 × 10⁻² mg L⁻¹ min⁻¹, respectively. The results showed that ZnO-NPs were effective against Gram-positive bacterial strains and showed moderate antioxidant activity, suggesting their potential in wastewater disinfection to achieve sustainable development goals. A potential antibacterial mechanism of ZnO-NPs involving interactions with microbial cells is proposed. Additionally, Gaussian Process Regression (GPR) combined with an improved Lévy flight distribution (FDB-LFD) algorithm was used to model QY photodegradation by ZnO-NPs. The ARD-Exponential kernel function provided high accuracy, validated through residue analysis. Finally, an innovative MATLAB-based application was developed to integrate the GPR_FDB-LFD model and FDB-LFD algorithm, streamlining optimization for precise photodegradation rate predictions. The results obtained in this study show that the GPR and FDB-LFD approaches offer efficient and cost-effective methods for predicting dye photodegradation, saving both time and resources. Full article

This study focused on fluoride (F⁻) contamination of water sources in Bahimi village, Cameroon. After the first investigation, results revealed that all water samples collected had elevated concentrations of fluoride ions (2.3 ± 0.1) mg/L to (4.5 ± 0.2) mg/L above the WHO guidelines (less than 1.5 mg/L). To mitigate the F⁻ levels, the use of bone char (BC) as an adsorbent material was proposed and its performance was tested. BC was prepared from bovine bones at different calcination temperatures (350 °C, 450 °C, 550 °C and 650 °C) and residence times (1 h and 2 h). The prepared materials were characterized in detail by SEM/EDS, BET, FTIR, and XRD. The BET findings indicated that the surface area of BC samples decreased with increasing calcination temperature and residence time. At a lower heating temperature and holding time (350 °C, 1 h), the prepared BC exhibited a higher specific surface area (112.3 ± 0.3) m²/g and adsorption capacity for F⁻ in the sampled water. Also, the batch adsorption experiments showed that the optimized adsorbent dose of 8 g/L facilitates the reduction in the F⁻ level of the sampled water below the acceptable limit level (1.5 mg/L) within 5 min of treatment. The presence of Ca²⁺ and Mg²⁺ in natural water has a positive effect on the removal of F⁻ in BC resulting in a high adsorption performance range of (72.5 ± 1.4)% to (80.3 ± 0.6)%. It was found that the adsorption of Ca²⁺ on the BC surface occurs via cation exchange with Na⁺. However, an increase in dissolved organic carbon (DOC) in the treated water limited the application of BC. Overall, the study presented a cost-effective adsorbent for the removal of this recalcitrant ion in the water source. Full article

Groundwater contamination by dense nonaqueous phase liquids (DNAPLs) poses a severe environmental threat due to their persistence and toxicity. Modeling DNAPL contamination is essential for understanding their distribution, predicting contaminant spread, and developing effective remediation strategies, but it is also challenging due to their complex multiphase behavior. Over the past few decades, researchers have developed various models, including multiphase flow, mass transfer, and solute transport models, to simulate the distribution of DNAPLs. To understand the research trends in DNAPL modeling in groundwater, a bibliometric analysis was conducted using CiteSpace based on 614 publications from the WoS Core Collection database (1993–2023). The publications were statistically analyzed, and the research hotspots and trends were summarized. The statistical analysis of the publications indicates that the United States is leading the international research on DNAPL models, followed by China and Canada; the collaboration between countries and disciplines in this field needs to be strengthened. Keyword clustering and burst detection reveal that the current research hotspots focus on multiphase flow models, mass transfer models, back diffusion, and practical applications of the models; the research trends are centered on back diffusion mechanisms, the characterization of contamination source zones, and prediction of the contaminant distribution at real-world sites, as well as optimization of the remediation strategies. Full article