Pollution Of Water Bodies Research Articles

Advances in Chitosan-Based Materials for Application in Catalysis and Adsorption of Emerging Contaminants

The increasing disposal of emerging contaminants in the environment is a worldwide concern due to environmental impacts, such as toxicity, hormonal disorders, and bioaccumulation. The persistence of these pollutants in water bodies makes conventional pollutant removal techniques inefficient or partial, thus requiring the development of new, more effective, sustainable remediation technologies. Therefore, chitosan-based materials have emerged as a promising alternative for application in catalysis and contaminant removal. The biopolymer has functional properties that make it an excellent adsorbent capable of removing more specific pollutants, such as pharmaceuticals, microplastics, agricultural pesticides, and perfluoroalkyl and poly-fluoroalkyl substances, which are increasingly in evidence today. Therefore, this review of recent and advanced research into using chitosan to manufacture catalytic and adsorption materials offers an innovative approach to treating contaminants in aqueous environments, significantly reducing their presence and impact. It discusses the advantages of using chitosan as an adsorbent and catalyst and its role as a support for catalysts and biocatalysts. In addition, the review highlights the diversity of the physical forms of chitosan, such as particles, membranes, and hydrogels, and its possible chemical modifications, highlighting its effectiveness in catalytic applications and the removal of a wide range of emerging contaminants.

Detecting floating litter in freshwater bodies with semi-supervised deep learning

Researchers and practitioners have extensively utilized supervised Deep Learning methods to quantify floating litter in rivers and canals. These methods require the availability of large amount of labeled data for training. The labeling work is expensive and laborious, resulting in small open datasets available in the field compared to the comprehensive datasets for computer vision, e.g., ImageNet. Fine-tuning models pre-trained on these larger datasets helps improve litter detection performances and reduces data requirements. Yet, the effectiveness of using features learned from generic datasets is limited in large-scale monitoring, where automated detection must adapt across different locations, environmental conditions, and sensor settings. To address this issue, we propose a two-stage semi-supervised learning method to detect floating litter based on the Swapping Assignments between multiple Views of the same image (SwAV). SwAV is a self-supervised learning approach that learns the underlying feature representation from unlabeled data. In the first stage, we used SwAV to pre-train a ResNet50 backbone architecture on about 100k unlabeled images. In the second stage, we added new layers to the pre-trained ResNet50 to create a Faster R-CNN architecture, and fine-tuned it with a limited number of labeled images (≈1.8k images with 2.6k annotated litter items). We developed and validated our semi-supervised floating litter detection methodology for images collected in canals and waterways of Delft (the Netherlands) and Jakarta (Indonesia). We tested for out-of-domain generalization performances in a zero-shot fashion using additional data from Ho Chi Minh City (Vietnam), Amsterdam and Groningen (the Netherlands). We benchmarked our results against the same Faster R-CNN architecture trained via supervised learning alone by fine-tuning ImageNet pre-trained weights. The findings indicate that the semi-supervised learning method matches or surpasses the supervised learning benchmark when tested on new images from the same training locations. We measured better performances when little data (≈200 images with about 300 annotated litter items) is available for fine-tuning and with respect to reducing false positive predictions. More importantly, the proposed approach demonstrates clear superiority for generalization on the unseen locations, with improvements in average precision of up to 12.7%. We attribute this superior performance to the more effective high-level feature extraction from SwAV pre-training from relevant unlabeled images. Our findings highlight a promising direction to leverage semi-supervised learning for developing foundational models, which have revolutionized artificial intelligence applications in most fields. By scaling our proposed approach with more data and compute, we can make significant strides in monitoring to address the global challenge of litter pollution in water bodies.

Combined physiological, metabolomic and response surface approaches to analyze copper stress resistance mechanisms and repair potential of Epipremnum aureum

Phytoremediation is commonly used to remediate copper (Cu) pollution in water bodies. Epipremnum aureum is often used as a restoration plant because of its rapid reproduction, high population density and high landscape value. However, neither its ability to remediate Cu-polluted water nor its mechanism of resistance to Cu stress has been fully clarified. Therefore, the present study revealed the Cu removal ability and resistance mechanism of E. aureum through physiology and metabolomics. And based on the results of this study, the response surface was applied to the application of plant growth regulator (PGR) to propose a precise restoration program. We first examined the growth physiological indices and repair of Cu in E. aureum under different Cu stress levels and found that the resistance mechanism of E. aureum to Cu was significantly initiated at 400 mg·L-1. And as the level of Cu stress increased, the Cu content in the plant also increased, and the underground part was the main accumulating part. The translocation factor of E. aureum was <1, and the bioconcentration factor was greater than 1 at all different Cu concentrations. Subsequently, metabolomics studies on E. aureum concluded that arginine and proline metabolism, indole alkaloid synthesis and brassinosteroid biosynthesis are the major pathways involved in the mechanism of Cu stress resistance in E. aureum. Based on these results, we proposed that salicylic acid, sodium nitroprusside and 2,4-epibrassinolide could be selected as PGRs, and further optimized the administration of PGRs using response surfaces. The optimized scheme allowed E. aureum to reach a maximum Cu removal of 84.39 % under 400 mg·L-1 Cu stress, which was 35.61 % higher than the non-fortified treatment. This study provides supporting materials and application options for the Cu repair capacity and resistance mechanisms of E. aureum.

Duckweed-based optical biosensor for herbicide toxicity assessment

In response to the pervasive issue of herbicide pollution in environmental water bodies, particularly from herbicides used extensively in agriculture, traditional chemical-based water quality analysis methods have proven costly and time-consuming, often failing to meet regulatory standards. To overcome these limitations, global environmental agencies have turned to rapidly-growing species like duckweed as bioindicators for herbicide and pesticide contamination. However, conventional biological assessment methods, such as the 168-h duckweed growth inhibition test, are slow and lack real-time monitoring capabilities. To address this challenge, we developed an innovative approach by integrating opto-mechanical technology with duckweed to create a cost-effective biosensor for herbicide detection, priced under $10 USD per system. This advancement allows for the rapid detection of herbicide impacts on duckweed growth within just 48 h, significantly improving upon traditional methods. Our biosensor achieves detection limits of 10 ppm (p < 0.05) for glyphosate and 1 ppm (p < 0.05) for glufosinate, both prominent herbicides globally. This mini-biosensing platform offers a practical alternative to the official method, which requires 168 h and higher thresholds (36.4 ppm for glyphosate and 34.0 ppm for glufosinate) for routine environmental analysis. Thus, these duckweed-based optical biosensors represent a promising advancement in environmental monitoring, enhancing accessibility and efficacy for widespread adoption globally.

Effect of Heavy Metal Phytoremediation on Phytochemical Fingerprint and Bioactivity of Pistia stratiotes: A Quest for Re-routing Disposal to Commercial Application

Phytoremediation is one of the non-energy consuming processes of remediating polluted water. However, the disposal of post-remediated plants poses a threat of the re-introduction of pollutants back into the ecosystem. Re-routing remediated pollutants for commercial application could be one way to reduce the re-introduction of pollutants in an ecosystem. Heavy metal pollution in water bodies is one issue, which can be mitigated to an extent with phytoremediation. In the current study, the effect of heavy metal phytoremediation on the phytochemical fingerprint and bioactivity of Pistia stratiotes L. was investigated. Pistia stratiotes L. was subjected to different concentrations of iron (Fe) and lead (Pb), in the range of 5-20 ppm. Different parameters such as heavy metal estimation (in plants and water post-treatment), thin layer chromatography (TLC), antioxidant activity, and antiurolithic activity were measured. Post remediation, heavy metal concentration was found to be comparatively higher in roots (16.515 ± 0.008 mg.g-1 and 5.25 ± 0.086 mg.g-1 when treated with 15 ppm iron and lead respectively). TLC revealed differences between the fingerprints of treated and untreated plants. Some bands increased in intensity as the concentration of heavy metal increased, while some bands which were present in untreated, were absent in treated plant samples. Antioxidant activity of treated plants shows lesser IC50 values, compared to untreated, in that, treated leaves show better activity (IC50 = 1.8 ± 0.5220 mg.mL-1 of leaf treated with 2 ppm iron as opposed to IC50 &gt; 5 mg.mL-1 of untreated leaf extract). The treated plants revealed good antiurolithic activity compared to untreated, in that, the percentage inhibition showed by Iron treated leaves and roots was better (96.87% and 98.95% exhibited by iron-10 ppm treated leaves and roots respectively), while the untreated showed a maximum of only 68.75% inhibition. The results suggest that the bioactivity of the plant extracts increases post-remediation. Potential applications of these extracts can be explored such as nanoparticle synthesis, drug discovery, etc.

Sustainable catalytic hydrogenation of high concentration nitrate to ammonia over Ruthenium-based catalysts

Elevated nitrate levels in natural water bodies significantly disrupt the global nitrogen cycle and pose a substantial environmental and human health risk. This study investigates the selective conversion of nitrate to ammonia via catalytic hydrogenation. This highly efficient and selective process offers a sustainable alternative to traditional ammonia production methods while simultaneously addressing nitrate pollution. Ruthenium (Ru) catalysts supported on ceria (CeO2), titania (TiO2), and tin dioxide (SnO2) were synthesized using a simple impregnation method, incorporating oxygen vacancies and low Palladium (Pd) loadings (0.25–0.5 wt%) to enhance catalytic performance. Ru-Pd/CeO2 exhibited superior activity and selectivity, maintaining near 100 % ammonia selectivity across various nitrate concentrations. At 75 °C, complete conversion of 2000 ppm nitrate to ammonia was achieved within 80 min using Ru-Pd/CeO2, and the yield of ammonia can reach up to 16440 mg•h−1•gRu-1. Subsequent ammonia enrichment through evaporation yielded pure ammonia solutions up to 3.6 wt%. Characterization and theoretical calculations suggest that abundant oxygen vacancies on the CeO2 surface and efficient hydrogen spillover from Pd nanoparticles synergistically contribute to the Ru-Pd/CeO2 catalyst’s superior performance. The catalyst exhibited excellent stability and reusability, maintaining high activity and selectivity over four cycles. This research presents a promising strategy for addressing nitrate pollution in water bodies while offering a sustainable and environmentally friendly route for ammonia synthesis. The findings of this study lay the foundation for further advancing and potentially implementing catalytic hydrogenation technology for nitrate pollution remediation and ammonia synthesis.

Improved naphthalene photodegradation rate of CN/Pt-P25 photocatalyst by effectively tuning Pt chemical states via H2 secondary annealing

Photocatalytic technology holds promising prospects for remediating naphthalene pollution in water bodies. In this work, the CN/Pt-P25 photocatalyst was successfully prepared via photodeposition combined with co-pyrolysis methods, and employed for naphthalene photodegradation under simulated sunlight. The chemical state of Pt was found to have a significant impact on the photocatalytic activity. H2 secondary annealing effectively tuned Pt chemical states, increasing the proportion of Pt0 species on the CN/Pt-P25 photocatalyst from 41.91 % to 62.24 %. The improved proportion of Pt0 species proportion led to a reduction in the bandgap, which induced changes in the band positions and notably enhancing the separation efficiency of photogenerated electron-hole pairs. Under simulated sunlight irradiation, (H2) CN/Pt-P25 photocatalyst achieved complete naphthalene photodegradation within 100 min. Thus, photocatalysts containing a high proportion of Pt0 species exhibited an improved performance in naphthalene photodegradation. These findings provide new insights into the application of photocatalytic technology for the remediation of PAHs.

Thiadiazol ligand-based laccase-like nanozymes with a high Cu+ ratio for efficient removal of tetracyclines through polymerization

A promising water treatment technology involves inducing the polymerization of organic pollutants to form corresponding polymers, enabling rapid, efficient, and low CO2 emission removal of these pollutants. However, there is currently limited research on utilizing polymerization treatment technology for removing tetracyclines from water. In this study, we synthesized a laccase-mimic nanozyme (Cu-ATZ) with a high Cu+ ratio using 2-amino-1,3,4-thiadiazole as a ligand inspired by natural laccase. The Cu-ATZ exhibited enhanced resistance to more severe application conditions and improved stability compared to natural laccase, thereby demonstrating a broader range of potential applications. The excellent catalytic properties of Cu-ATZ enabled the nanozyme to be used in the polymerization process to remove tetracyclines from water. In order to simulate actual antibiotic pollution of water bodies, tetracyclines were added to the water from sewage treatment plants. Following Cu-ATZ treatment of the water sample, the chemical oxygen demand (COD) content was found to have decreased by over 80 %. In conclusion, this study presented a novel approach for tetracycline elimination from water.

Co/N-codoped carbon nanoplate array coated carbon fiber cathode for solar driven uranium extraction from complex radioactive wastewater

Organics bring great challenge on uranium reduction due to the formation of stubborn complexes between uranyl ions (UO22+) and organics. Herein, we developed an effective strategy to synchronously degrade organics and extract uranium from complicated radioactive wastewater, accompanied with electricity generation, by a novel self-driven photocatalytic fuel cell (NSPFC) system, in which a three-dimensional (3D) Co/N-doped carbon nanoplate array (Co-N-C/CF) decorated carbon fiber is employed as the cathode for highly efficient UO22+ reduction. Compared to pure CF, the optimized Co-N-C/CF cathode increases the rate constants (k) by 9 and 9.1 times for UO22+ and organic elimination, respectively, and improves electricity output by 2 times (Pmax, 1180 μW/cm2). This improvement should be ascribed to the 3D morphology of Co-N-C/CF that provided plenty of surface area for U(VI) reduction, and the doping of N and Co, which effectively increased the U(VI) adsorption sites and optimized the electron behavior on the cathode, respectively. These features endow the NSPFC system with excellent adaptability in treating complex radioactive wastewater with a wide range of pollutant concentration, pH, co-existed ions, pollutant organics and natural organic matters. Fascinating activity is also achieves in treating polluted seawater or under real sunlight illumination. This work not only provides a outstanding nanostructured cathode for uranium reduction but also suggests a charming system to resourcefully treatment of radioactive wastewater or polluted water bodies.

A review on photocatalytic degradation of aromatic organoarsenic compounds in aqueous environment using nanomaterials

AbstractAromatic organoarsenic compounds (AOCs) have proven to be both a boon and a curse by boosting profit maximization in livestock production and at the same time contributing to the pollution of water bodies, the chief cornerstone of the ecosystem. Interestingly, photocatalytic degradation using nanomaterials has emerged as an effective method to mitigate AOC pollution. Thus, this study aims to review and analyze original research works directed toward the photocatalytic degradation of AOC in the aqueous environment. In this study, the photocatalytic degradation efficiency of various nanomaterials is investigated for different aromatic organoarsenic compounds. In addition, an empirical analysis was conducted on the impact of electron trapping and radical scavengers. Furthermore, photocatalytic degradation kinetics and mechanisms were pragmatically discussed. Also, recyclability, stability, and real‐life applicability were empirically evaluated. According to this review, most nanomaterial materials had maximal photocatalytic degradation efficiencies of &gt;75% for most AOCs within an average time of 6–330 min. The radical scavenging study revealed that ●OH and O2● mechanistically play a major role in AOC degradation than electrons and holes. Additionally, it was shown that expended photocatalysts can be eluted mostly with H2O/NaOH and recycled up to 3–6 rounds with a degradation efficiency of &gt;80% in most cases while maintaining their original structural integrity. This indicates that the method has the potential to be both environmentally friendly and industrially scalable. Ultimately, research gaps were highlighted, which can help researchers identify future research hotspots and open doors for technique advancement.

Carcass decay inhibits denitrification indirectly by regulating the microbiota and physicochemical properties in a model water system

Abstract Animal carcass decomposition is involved in nitrogen (N) cycle in the aquatic ecosystems, for example denitrification, volatilization and leaching. The denitrification process is a crucial part of the nitrogen cycle, helping to alleviate biological toxicity resulting from nitrate accumulation. However, it is still unknown whether and how cadaver decay affects the denitrifiers and their activity in river water. In this study, six denitrifiers (encoding napA, narG, nirK, nirS, norB and nosZ, respectively) and denitrifying activity were investigated in a model water system with nitrogen pollution from corpse decomposition using high‐throughput sequencing, real‐time quantitative PCR and denitrifying enzyme activity (DEA) assay. Cadaver decay increased the quantity and altered the composition of denitrifying microbiota. Multiple regression on distance matrices revealed that corpse decay had a significantly greater impact on the denitrification communities than temperature. To our surprise, the DEA decreased in the contaminated water by cadavers. The multiple regression models revealed that the abundance of denitrifying taxa and the gene copies may jointly predict changes in DEA, with highest contribution coming from the norB‐type Hydrogenophaga. Further, the partial least squares path model (PLS‐PM) showed that corpse decay indirectly inhibited DEA via the denitrification community and water physicochemical properties. Synthesis and applications. This study provides important insights into how cadaver decomposition can reduce denitrification activity in water systems. These findings can assist us in scientifically managing and remediating polluted water bodies.

Efficient removal and stepwise recovery of various heavy metals from water by using calcium carbonate with different activity

Heavy metals in wastewater have caused serious environmental contamination in the world. However, a key challenge with the most effective solution through chemical precipitation is the high pH of in the effluent by the use of lime. Herein, we propose a strategy using highly active calcium carbonate (HACC) for enhancing its slow-release activity, which efficiently removes heavy metal contamination while avoiding high pH of the effluent. The HACC demonstrate a removal of more than 99 % for Cd(II), Cu(II), Zn(II) and Pb(II) from the composite contaminated water within 50 min, while maintaining the pH of the effluent close to neutral. In addition, mechanistic analyses unveil that the free heavy metals in different solutions combine with OH– and CO32– released from HACC in different precipitation behaviors to form their respective precipitates, thereby discovering the mechanism of regulating the precipitation rates of different heavy metals by controlling the activity of calcium carbonate. Based on it, the stepwise recovery of heavy metals was realized by adjusting the calcium carbonates with different activity. The present work provides guidance for gentle and efficient removal of heavy metal pollution in water bodies and inspires the future development of recovery of heavy metals.

Z-scheme γ-Fe2O3/g-C3N4 in Photo-Fenton reaction for oxytetracycline degradation: Mechanism study and DFT calculation

With the urbanization and industrialization of the world, the pollution of water due to the misuse of antibiotics is increasing. In this study, a Z-scheme γ-Fe2O3/g-C3N4 composite photocatalyst was prepared, and the removal efficiency of oxytetracycline (OTC) reached 85.7% within 60 min under the Photo-Fenton reaction system higher than that of g-C3N4 and γ-Fe2O3. The composite has great anti-interference capability and sustainability, and the recyclability was demonstrated using hysteresis return lines data. The photoelectrochemical characterization was analyzed to investigate the effect of the building of Z-scheme heterojunction on the photogenerated carrier separation efficiency. The charge behavior of heterojunction interfaces was probed in conjunction with DFT calculations, and differential charge maps were used to visualize charge distributions to analyze possible charge transfer pathways. In addition, the active substances in the system were identified by ESR data and capture experiments. The results showed that ·OH was the dominant active substance for OTC degradation. Meanwhile, LC-MS data combined with Fukui function calculations led to the derivation of a possible degradation pathway dominated by ·OH. This research provides a reference for subsequent studies of non-homogeneous Photo-Fenton systems and offers a viable option for mitigating OTC pollution in water bodies.

Integrating vision-based AI and large language models for real-time water pollution surveillance.

Water pollution has become a major concern in recent years, affecting over 2 billion people worldwide, according to UNESCO. This pollution can occur by either naturally, such as algal blooms, or man-made when toxic substances are released into water bodies like lakes, rivers, springs, and oceans. To address this issue and monitor surface-level water pollution in local water bodies, an informative real-time vision-based surveillance system has been developed in conjunction with large language models (LLMs). This system has an integrated camera connected to a Raspberry Pi for processing input frames and is further linked to LLMs for generating contextual information regarding the type, causes, and impact of pollutants on both human health and the environment. This multi-model setup enables local authorities to monitor water pollution and take necessary steps to mitigate it. To train the vision model, seven major types of pollutants found in water bodies like algal bloom, synthetic foams, dead fishes, oil spills, wooden logs, industrial waste run-offs, and trashes were used for achieving accurate detection. ChatGPT API has been integrated with the model to generate contextual information about pollution detected. Thus, the multi-model system can conduct surveillance over water bodies and autonomously alert local authorities to take immediate action, eliminating the need for human intervention. PRACTITIONER POINTS: Combines cameras and LLMs with Raspberry Pi for processing and generating pollutant information. Uses YOLOv5 to detect algal blooms, synthetic foams, dead fish, oil spills, and industrial waste. Supports various modules and environments, including drones and mobile apps for broad monitoring. Educates on environmental healthand alerts authorities about waterpollution.

Biomonitoring of Pesticides in the Reservoirs of the Saratov Region

An assessment of the circulation of pesticides in the Saratov region was carried out. A list of pesticides that pose a potential hazard to public health as a result of chemical pollution of water bodies and aquatic organisms consumed by humans has been determined. It is proposed to use satellite images of the terrain located in the drainage basin area in order to justify the sampling points from surface water household supplies potentially contaminated with pesticides. The methodological aspects of the use of a multicomponent biotest system in establishing the toxicity of pesticides are considered. It is concluded that when arranging the biotesting to assess the toxicity of water and sediment samples containing pesticides in concentrations up to 10 MAC, it is recommended to use aquatic organisms with a minimally developed detoxification system.

Fecal coliform assessment and detection of blaTEM, blaSHV, and tetA in Escherichia coli isolated from selected river waters of Tacloban City, Leyte, Philippines

Fecal coliforms (FCs) are generally used as indicators of fecal pollution in water systems. High levels of FC pollution in water bodies may also be associated with antibiotic resistance. Escherichia coli, a member of the FC group, is generally commensal and harmless. However, some strains can cause various diseases in humans. The prevalence of antibiotic-resistant E. coli has been reported in several river systems worldwide. Herein, we report the most probable number (MPN) of FC and E. coli and the first detection of blaTEM, blaSHV, and i&gt;blaSHVetA antibiotic resistance genes (ARGs) as well as ARG combinations (i.e. blaTEM + tetA and blaSHV + tetA) in E. coli isolates from river waters with high levels of FC in Tacloban City. MPN was determined using a multiple-tube fermentation technique, and ARG was detected using polymerase chain reaction (PCR). Results show that the Bagacay River had the highest MPN of FC and E. coli (both &gt;160,000 MPN/100 mL), followed by the Burayan Creek (&gt;160,000 MPN/100 mL; 160,000 MPN/100 mL), the Mangonbangon River (92,000 MPN/100 mL; 54,000 MPN/100 mL), and the Tigbao River (35,000 MPN/100 mL; 24,000 MPN/100 mL). Among the 113 uidA gene-confirmed E. coli isolates, blaTEM, blaSHV, and tetA were detected in 39 (34.5%), 7 (6.2%), and 83 (73.5%) E. coli isolates, respectively. Moreover, 34 (30%) of the isolates possess both blaTEM and tetA, and five (4.4%) of the isolates have both i&gt;blaSHV and tetA. These results imply that the rivers are unsafe for anthropogenic use and the presence of ARGs in E. coli isolates pose a threat for locals. Hence, the public is urged to ensure safety and awareness in relation to these water environments. Further monitoring and source tracking are recommended to enhance environmental and public health safety among locals.

Supramolecular Binding of Phosphonate Dianions by Nanojars and Nanojar Clamshells.

Despite the widespread use of phosphonates (RPO32-) in various agricultural, industrial, and household applications and the ensuing eutrophication of polluted water bodies, the capture of phosphonate ions by molecular receptors has been scarcely studied. Herein, we describe a novel approach to phosphonate binding using chemically and thermally robust supramolecular coordination assemblies of the formula [RPO3⊂{cis-CuII(μ-OH)(μ-pz)}n]2- (Cun; n = 27-31; pz = pyrazolate ion, C3H3N2-; R = aliphatic or aromatic group). The neutral receptors, termed nanojars, strongly bind phosphonate anions by a multitude of hydrogen bonds within their highly hydrophilic cavities. These nanojars can be synthesized either directly from their constituents or by depolymerization of [trans-CuII(μ-OH)(μ-pz)]∞ induced by phosphonate anions. Electrospray-ionization mass spectrometry, UV-vis and variable-temperature, paramagnetic 1H and 31P NMR spectroscopy, single-crystal X-ray diffraction, along with chemical stability studies toward NH3 and Ba2+ ions, and thermal stability studies in solution are employed to explore the binding of various phosphonate ions by nanojars. Crystallographic studies of 12 different nanojars offer unprecedented structural characterization of host-guest complexes with doubly charged RPO32- ions and reveal a new motif in nanojar chemistry, nanojar clamshells, which consist of phosphonate anion-bridged pairs of nanojars and double the phosphonate-binding capacity of nanojars.

Assessment of the ecological status of the river water system in European North under conditions of ultra-fresh humus waters using biotic indices (Suna River, Lake Onega Basin, Russia).

Protecting rivers and lakes from pollution is crucial for maintaining the health of aquatic ecosystems and ensuring the well-being of both wildlife and humans. Present study intends to examine the water quality of the Suna River (Eastern Fennoscandia in the European North of Russia) to assess the ecological risk. Widespread methods for assessing water quality based on macrozoobenthos and phytoperiphoton were applied. It was found that in conditions of ultra-fresh waters with high humus content, biotic indicators may indicate pollution of water bodies that do not actually experience significant anthropogenic impact. Ratings ranging from 'poor' to 'excellent' were obtained for different stations, reflecting the influence of natural features of different sections of the river. 'Good' water quality was noted at the river stones biotopes. In river gravel, sand and silt biotopes, as well as all lake biotopes, 'mediocre' water quality was found. The low anthropogenic income on the river catchment allows us to conclude that most indices for assessing water quality significantly underestimate the results in the natural conditions of Eastern Fennoscandia. Biotic indices EPT, BBI and EBI are most accurate for assessing the water quality of rivers and lakes in Eastern Fennoscandia.

Advancing nanoarchitectures of 2D WO3/MXene photoanode for enhanced photoelectrocatalytic oxidation of phenol and arsenic in synthetic wastewater

The photoelectrocatalytic advanced oxidation process (PEAOP) necessitates high-performing and stable photoanodes for the effective oxidation of complex pollutants in industrial wastewater. This study presents the construction of 2D WO3/MXene heteronanostructures for the development of efficient and stable photoanode. The WO3/MXene heterostructure features well-ordered WO3 photoactive sites anchored on micron-sized MXene sheets, providing an increased visible light active catalytic surface area and enhanced electrocatalytic activities for pollutant oxidation. Phenol, a highly toxic compound, was completely oxidized at an applied potential of 0.8 V vs. RHE under visible light irradiation. Systematic optimization of operational conditions for the photoelectrocatalytic oxidation of phenol was conducted. The phenol oxidation mechanism was elucidated via high-performance liquid chromatography (HPLC) analysis and the identification of intermediate compounds. Additionally, a mixed model of phenol and arsenic (III) in polluted water demonstrated the capability of WO3/MXene photoanode for the simultaneous oxidation of both organic and inorganic pollutants, achieving complete conversion of phenol and As(III) to non-toxic As(V). The WO3/MXene photoanode facilitated water oxidation, generating a substantial amount of O2•– and •OH oxidative species, which are crucial for the concurrent oxidation of phenol and arsenic. Recyclability tests demonstrated a 99% retention of performance, confirming the WO3/MXene photoanode's suitability for long-term operation in PEAOPs. The findings suggest that integrating WO3/MXene photoanodes into water purification systems can enhance economic feasibility, reduce energy consumption, and improve efficiency. This PEAOP offers a viable solution to the critical issue of heavy metal and organic chemical pollution in various water bodies, given its scalability and ability to preserve ecosystems while conserving clean water resources.

High molecular oxygen activation capacity of carbon defective g-C3N5 for photocatalytic degradation of antibiotics in water

In this study, a carbon deficient g-C3N5 for photocatalytic degradation of antibiotics in water was prepared by thermal polymerization at 600 °C followed by hydrothermal at 180 °C for 12 h, and named CN600-12. The variation of XRD patterns in the physical phase characterization combined with calculations for energy bands in density functional theory (DFT) presents a method for analyzing defects in g-C3N5. The degradation efficiency of CN600-12 on different antibiotics and dyes reached 90% within 90 min, proving its excellent universal applicability. In addition, the prepared CN600-12 has superior stability and environmental friendliness. The burst experiments and ESR data reflect the high yields of oxygenated reactive groups (·O2– and 1O2). The oxygen adsorption capacity of the materials was calculated by combining DFT, the effect of defect configuration on oxygen adsorption was analyzed, and photoelectrochemical characterization explored their photogenerated carrier separation ability. The results show that introducing carbon defects improves the adsorption capacity of the material for oxygen. At the same time, improving the energy band structure and the separation of photogenerated carriers give the material a strong activation capacity for molecular oxygen. This study provides a feasible reference for solving the problem of antibiotic pollution in water bodies.