Pollution Of Water Bodies Research Articles

Cheese whey generation, management and potential for biogas production in Mexico and the State of Jalisco

ABSTRACT Pollution of water bodies and process upset in treatment plants in Mexico by cheese whey discharges is a matter of concern where scant inspection and law enforcement may aggravate the situation. This study analyzes the current state of environmental regulatory compliance and the impacts of whey discharges with particular emphasis on the country’s leading dairy-producing state, Jalisco. Subsequently, cheese whey characteristics and current valorisation volume and uses are discussed in detail. From there, anaerobic digestion is presented as a key technology for cheese whey treatment mainly to comply with wastewater regulations, with recovery of biogas as bonus. From there, the volume of cheese whey discharged to the environment and potential equivalence in biogas and electricity production is calculated considering both the technologies commonly used in industrial applications and for farms and small producers. Also, the potential electricity generation and prevented atmospheric impact are calculated and framed against the current Mexican energy and emissions inventory. Finally, a review of past efforts to disseminate the use of anaerobic digesters to produce biogas from organic waste in Mexico is undertaken, followed by a discussion of the basic requirements for a strategy to sustainably manage and treat whey discharges.

A recyclable and high porosity vinasse-based biochar with enhanced superficial active sites for antibiotics recovery

Antibiotic pollution in water bodies is a global environmental issue. For adsorbing antibiotic residues, biochar produced by direct high temperature pyrolysis faces challenges in balancing adsorption capacity and recyclability due to limited active sites. Thus, a recyclable and high-porosity vinasse-based biochar was developed via co-pyrolysis of K2FeO4 one-pot method. The co-pyrolysis biochar's surface area was augmented by 143 times, from 3.4 m²/g to 490.9 m²/g. The maximum theoretical adsorption capacity of the co-pyrolysis biochar for norfloxacin (NOR) increased from 4.4 mg/g to 364.9 mg/g, an approximate 83-fold enhancement. The surface of the biochar was rich in active groups (C-O, C-Fe, and -OH), which acted as the active sites to enhance the adsorption of NOR. The adsorption mechanism involved a variety of interactions, including pore-filling, hydrogen bond, π-π interactions, surface complexation, and electrostatic interactions. Importantly, the biochar is magnetic and can be recycled attributed to the generation of ferriferous oxides during the carbonization. After three cycles of reuse, the adsorption efficiency of vinasse-based biochar for NOR still exceeded 70 %. Such biochar prepared by this facile and feasible co-pyrolysis method show the potential to enhance active sites for removal of antibiotic from aquatic systems.

Pollution resistance and removal efficiency of mesophytic plants of polluted water bodies

With the development of cities and economic growth, the eutrophication of urban park landscape water has become a hot topic in environmental governance and research at home and abroad. Using indoor water pollution simulation experiments, the decontamination and pollution resistance performance of six aquatic plants were studied. The research results found that all six aquatic plants can reduce the pH value of eutrophic water bodies. The pH of the Lythrum salicaria L. (Q) and Iris tectorum Maxim (Y) treatment systems was the lowest which are 7.34 and 7.48, respectively. They were significantly lower than the control group (CK). The content of nitrogen and phosphorus elements were reduced by six types of plants in the wastewater. After the completion of the experiment, the total nitrogen (TN) removal efficiency of Y was as high as 66.2%, and its content decreased from 9.49 to 3.21 mg/l. The removal rates of total phosphorus (TP) by six types of plants ranged from 59.1 to 81.3% and they were significantly higher than the CK. Among them, the removal rate of TP in wastewater by Y treatment exceeded 80%, which is superior to other plants and significantly different from CK. After the completion of the experiment, the content of chlorophyll a (chl a) in the water treated with Y was the lowest (6.6 mg/l). It was significantly lower than the other treatments (P<0.05). The contents of chl a in Y decreased by 37.1% compared to the initial level. Compared to CK, it is 54.1% lower and the content of chl a in CK showed an increasing trend with time delay. Overall analysis shows that the microsystems formed by the six plants all have a certain improvement effect on water quality, effectively inhibiting the proliferation of algae in eutrophic water bodies. Among them, planting iris has the best effect. Bangladesh J. Bot. 53(3): 757-763, 2024 (September) Special

Performance and Mechanism of Porous Carbons Derived from Biomass as Adsorbent for Removal of Cr(VI)

To solve the problem of heavy metal hexavalent chromium (Cr(VI)) pollution in water bodies, this study was carried out to prepare nitrogen-doped porous carbon by using bamboo shoots as the raw material and KHCO3 as the activator, which has a good ability to remove Cr(VI) from water bodies. The prepared N-doped carbon materials were characterized by thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FT-IR), elemental analysis, and scanning electron microscopy (SEM). The results showed that the prepared carbon material had hierarchical pore structures and abundant functional groups, which is conducive to the adsorption of Cr(VI). The effects of various factors on the adsorption performance of Cr(VI), such as the carbon materials prepared under different conditions, the pH of the initial solution, the concentration of the initial solution, and the contact time between the carbon and Cr(VI), were explored. The results showed that the bamboo shoot-based nitrogen-doped carbon materials, especially BSNC-800 (prepared at 800 °C with a mass ratio of KHCO3 to bamboo shoot of 4:1), performed well in removing Cr(VI) from a water solution. The maximum adsorption of Cr(VI) by BSNC-800 under equilibrium conditions was 385.8 mg g−1 (conditions: at the pH of 2 with the initial concentration of 400 mg L−1). The adsorption kinetics and isotherms were analyzed, and the adsorption mechanism was discussed. It can be found that the adsorption of Cr(VI) by BSNC-800 fits better with the Langmuir isotherm model and the pseudo-second-order kinetic model. The adsorption mechanism between the Cr(VI)-containing solution and BSNC-800 was controlled by membrane diffusion and chemisorption. The results broaden the ways of utilizing biomass resources as precursors of carbon materials, which is significant and helpful for applying biomass carbon materials as adsorbents for wastewater treatment.

Bacillus amyloliquefaciens strain NSB4 bacteria for treating wastewater for fuel cell application

Pollutants in water bodies come from a variety of sources, including but not limited to domestic, industrial, municipal etc. Water contamination and energy shortages are global problems that require significant attention. Therefore, it is essential to synthesize sustainable energy and transport waste-free water to the water reception points. Concerns about energy shortages and water contamination have prompted the development of microbial fuel cell technology. Microorganisms are used by the electrochemical cell nature of MFCs to digest the organic wastes and produce energy anaerobically. Focusing on single-chambered mediator-less MFCs operating in batch mode, this study assesses the efficacy of a novel bacterial strain Bacillus amyloliquefaciens NSB4, as an exoelectrogen regarding electricity yield and waste elimination. Results from the strain's electrochemical characterization showed a maximum current density of 0.4804A/m2 and a power density of 41.281mW/m2. Additionally, the columbic efficiency (72%) and COD reduction efficiency (90.46%) were also remarkably high. Growth of the anodic biofilm during the MFC process displayed the crucial performance of the exoelectrogen used. SEM images of the biofilm are also presented in the study.

Resource Utilization of Rare-Earth-Rich Biomass and Ammonia Nitrogen Effluent from Mining

The post-treatment of heavy metal-enriched plants in mining areas and the purification of ammonia and nitrogen pollution in water bodies are significant for the ecological environment of ionic rare earth mining areas. Herein, we focused on the biochar production potential of Dicranopteris pedata, characterizing biochar prepared by an oxidative modification process and an iron modification process. We conducted adsorption experiments to comparatively investigate the adsorption performance of biochar on NH4+ and studied the fertilizer application and migration toxicity of the adsorbed biochar for rare earth elements (REEs). Results indicated that ~332.09 g of biochar could be produced per unit area of D. pedata under 100% clipping conditions. The Brunauer–Emmett–Teller (BET) specific surface area of oxidized biochar (H2O2BC) increased, and the pore size of iron-modified biochar increased. The adsorption behavior of biochar toward NH4+ was well represented by the pseudo-second-order and Langmuir models. H2O2BC demonstrated the strongest adsorption of NH4+ with maximum theoretical equilibrium adsorption of 43.40 mg·g−1, 37.14% higher than that of pristine biochar. The adsorption process of NH4+ on biochar is influenced by various physicochemical mechanisms, including pore absorption, electrostatic attraction, and functional group complexation. Furthermore, the metal ions in the biochar did not precipitate during the reaction process. The adsorbed NH4+ biochar promoted the growth of honey pomelo without risking REE pollution to the environment. Therefore, it can be applied as a nitrogen-carrying rare earth fertilizer in low rare earth areas. This study provides a theoretical basis and technical support for the phytoremediation post-treatment of rare earth mining areas and the improvement of ammonia nitrogen wastewater management pathways in mining areas.

Optimizing the Activation of WWTP Wet-Weather Operation Using Radar-Based Flow and Volume Forecasting with the Relative Economic Value (REV) Approach

Wastewater treatment plants (WWTPs) connected to combined sewer systems must cope with high flows during wet-weather conditions, often leading to bypass and thus pollution of water bodies. Radar rainfall forecasts coupled with a rainfall-runoff model provides flow and volume forecasts that can be used for deciding when to switch from normal to wet-weather operation, which temporarily allows for higher inflow. However, forecasts are by definition uncertain and may lead to potential mismanagement, e.g., false alarms and misses. Our study focused on two years of operational data from the Damhuså sewer catchment and WWTP. We used the Relative Economic Value (REV) framework to optimize the control parameters of a baseline control strategy (thresholds on flow measurements and radar flow prognosis) and to test new control strategies based on volume instead of flow thresholds. We investigated two situations with different objective functions, considering higher negative impact from misses than false alarms and vice versa, and obtained in both cases a reduction of the rate of false alarms, higher flow thresholds and lower bypass compared to the baseline control. We also assess a new control strategy that employs thresholds of predicted accumulated volume instead of predicted flow and achieved even better results.

CaO composite improves the conversion efficiency of free radicals in the catalytic activation of permonsulfate by Cu-based oxides

The advanced oxidation technology based on persulfate has excellent performance in the efficient removal of refractory organic pollutants in water bodies, among which the heterogeneous catalytic activation system has been studied extensively due to its characteristics of convenient operation, low energy consumption, and no secondary pollution. Many studies have been focused on improving the overall oxidation efficiency of target substrates in heterogeneous catalytic oxidation systems. Herein, a series of bimetallic composite oxides (CaOMOx) (M = Cu, Fe, Ni, etc.) were prepared by combining inert metal oxides—CaO with various transition metal oxides, and were used for permonosulfate (PMS) activation. Among them, the introduction of CaO has the most obvious effect on the catalytic efficiency of CaOCuO/PMS system. Almost 100 % of benzothiazole (BTH) was degraded within 40 min at 0.3 g/L PMS and 0.15 g/L CaOCuO. The mechanism study showed that the introduction of CaO significantly increased the content of oxygen vacancies (OVs) on CaOCuO, and thus promoted the formation of surface hydroxyl groups to strengthen the adsorption capacity for PMS. In addition, the introduction of CaO enhanced the reducibility of Cu species and thus promoted the transformation of Cu2+ to Cu+, ensured the continuous and rapid generation of SO4•-, thereby promoting the improvement of oxidation efficiency. Our study provides a novel strategy for improving the conversion efficiency of free radical in heterogeneous persulfate catalytic oxidation systems.

Bismuth oxyiodide-based composites for advanced visible-light activation of peroxymonosulfate in pharmaceutical mineralization

The presence of pharmaceutical pollutants in water bodies represents a significant environmental and public health concern, largely due to their inherent persistence and potential to induce antibiotic resistance. Advanced oxidation processes (AOPs) that employ peroxymonosulfate (PMS) activation have emerged as an effective means of degrading these contaminants. Bismuth oxyiodides (BiOI), which are known for their visible-light photocatalytic properties, demonstrate considerable potential for removal of pharmaceutical pollutants. This study examines the synthesis and performance of BiOI-based composites with barium ferrite (BFO) nanoparticles for enhanced PMS activation under visible light. BiOI and Bi5O7I were synthesized via solvothermal and electrodeposition methods, respectively, and their morphologies and crystalline structures were observed to exhibit distinctive characteristics following annealing. The formation of the composite with BFO resulted in an improvement in the catalytic properties, which in turn enhanced the surface area and availability of active sites. The objective of the photocatalytic studies was to evaluate the degradation and mineralization of tetracycline (TC) under visible light, PMS, and combined conditions. The Bi5O7I(ED)-BFO catalyst was identified as the optimal candidate, achieving up to 99.8% TC degradation and 99.4% mineralization within 90 min at room temperature. The synergistic effect of BFO in BiOI-based composites significantly enhanced performance across all conditions, indicating their potential for efficient remediation of pharmaceutical pollutant. The material's performance was further evaluated in tap water, where the degradation efficiency decreased to 56.4% and mineralization to 38.2%. These results reflect the challenges posed by complex water matrices. However, doubling the PMS concentration to 5 mM led to improved outcomes, with 93.8% degradation and 81.4% mineralization achieved. These findings demonstrate the material's robust potential for treating pharmaceutical pollutants in real-world conditions, advancing sustainable water treatment technologies.

Roles of Nitrogen- and Sulphur-Containing Groups in Copper Ion Adsorption by a Modified Chitosan Carboxymethyl Starch Polymer

Owing to the toxicity and widespread use of copper, the pollution caused by copper ions has become a long-standing environmental and industrial challenge. In this study, a new adsorbent was developed to dispose of and remove copper ions from water. The modified chitosan–carboxymethyl starch (MCTS-CMS) polymer was characterised, and FTIR and SEM-EDS confirmed the successful graft modification of the receptor. The adsorption behaviour was investigated through various parameters, and the results showed that the optimal parameters were pH > 4.0, an adsorption time of 30 min, a reaction temperature of 293 K, and an initial concentration of 100–120 mg/L. The experimental data exhibited a good fit with pseudo-second-order models, and the Langmuir isotherm revealed that the polymer was found to be highly suitable for adsorption, with a maximum adsorption capacity of 321.16 mg/g. Thermodynamic analysis revealed that the adsorption process was exothermic and spontaneous. XRD and XPS confirmed the generation of posnjakite after the adsorption and the predominant roles of nitrogen- and sulphur-containing groups in the adsorption. Further analysis confirmed the existence of chemisorption and physical adsorption, with chemisorption mainly facilitating the Cu(II) absorption of the polymer. MCTS-CMS showed an excellent removal efficiency of 98% in acidic solutions. On the basis of these findings, the MCTS-CMS polymer demonstrates excellent performance and high selectivity in the removal of copper ions from industrial wastewater or polluted water bodies. This work recommends expanding the polymer’s practical applications to contribute to water purification efforts.

Preparation of dandelion flower extract-based polyvinyl alcohol-chitosan-dandelion-CuNPs composite gel for efficient bacteriostatic and dye adsorption

A multifunctional composite gel with efficient bacteriostatic and dye adsorption properties was prepared using polyvinyl alcohol, chitosan, and soybean isolate protein as carriers, CuNPs prepared by green reduction of dandelion extract as bacteriostatic agent, and glutaraldehyde as cross-linking agent. The composite gel showed good inhibition capacity of Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa with the diameter of inhibition zone of 27.0–28.3 mm by agar diffusion method. The composite gel antibacterial rate remained above 90 % after 14 days of preparation. After 6 times reuse of composite gel in water, the antibacterial rate remained above 90 %, proving its good stability and reusability. Adding dandelion extract and CuNPs greatly improved the gel antioxidant property, acquiring free radical scavenging rate at 95.6 %. This composite gel had good biocompatibility and adsorption performance, and the maximum adsorption amount of methylene blue and methyl orange was 40.36 mg/g and 41.81 mg/g, respectively. To sum up, the green composition of composite gel has good antimicrobial performance and high dye adsorption, which holds significant promising for treating the water body pollution and protecting the environment. To build cost-effective antibacterial and dye adsorption process on a large-scale, in-depth exploration about this topic is still needed to develop.

Lycopene mitigates atrazine-induced hypothalamic neural stem cell senescence by modulating the integrated stress response pathway

BackgroundAtrazine, a widely used herbicide, has become a major pollutant in agricultural water bodies. Pesticide contamination, including atrazine, is linked to a high incidence of age-related neurodegenerative diseases, suggesting its neurotoxic potential. Lycopene, a potent antioxidant, is renowned for its diverse pharmacological effects, especially its neuroprotective properties. However, the underlying pharmacological mechanisms of lycopene and its impact on potential pathways against atrazine-induced hypothalamic damage have not been elucidated. PurposeOur study aimed to elucidate how lycopene ameliorates hypothalamic injury triggered by atrazine exposure, with a special focus on the pluripotency of neural stem cells (NSCs) and pathways involved in cell senescence. MethodsMice were administered lycopene and/or atrazine via gavage for 21 days. The C17.2 NSC cell line and specific molecular inhibitors were utilized to examine the potential protective effects of lycopene in vitro. Morphological changes and ultrastructural damage in the hypothalamus were observed by hematoxylin-eosin staining and transmission electron microscopy, respectively. The mechanisms of action of lycopene were explored through various methods, including senescence β-galactosidase staining, multiplex immunofluorescence, Western blotting and qRT‒PCR. ResultsOur results indicated that lycopene notably ameliorated atrazine-induced histological and ultrastructural damage, as well as the loss of intact and mature neurons in mouse hypothalami. Additionally, hypothalamic NSCs (HtNSCs) and microglia were recruited to areas of neuronal injury after atrazine exposure; intriguingly, lycopene treatment reduced this recruitment. Through in vivo and in vitro assays, we elucidated the outcomes of atrazine-induced HtNSC recruitment and neuronal loss, along with the neuroprotective mechanisms of lycopene. Mechanistically, lycopene prevents atrazine-induced senescence in HtNSCs and enhances their proliferation and differentiation by inhibiting the integrated stress response (ISR) signaling pathway, thus promoting the renewal of damaged neurons in the hypothalamus. ConclusionsCollectively, the results of the present study reveal, for the first time, that lycopene mitigates atrazine-induced HtNSC senescence by modulating the ISR signaling pathway. These findings offer novel insights into the role of lycopene in preventing and alleviating NSC senescence and suggest its potential development as a new therapy for neurodegenerative diseases.

Machine Learning Techniques for Monitoring Water Quality in Water Resources

More than 66% of the Earth's total surface area is covered by water. Clean water is one of the basic needs of everyday life. Consistent pollution of water bodies can have far-reaching effects on the lives of living organisms. The World Health Organization has reported that the provision of safe drinking water for human consumption is a challenge that has reached alarming levels. This is because nearly 70% of the total water withdrawals worldwide are used in agriculture. To determine the water's suitability for human consumption, Tests are typically conducted by examining the properties of water in terms of physical, biological, and chemical conditions. There are various methods to measure water quality. Recently, an ongoing process has been shown to improve water quality. To solve this problem, this paper is using a machine learning model to Contribution for creation a smart model capable of classifying potable and non-potable water that is released to the water share by the competent authorities and the ability of Machine Learning models to monitor and predict water, especially Managing and Planning Water Resources. datasets were utilized in training and evaluating machine learning models, which includes (3276) samples with nine attributes and two labels indicating water usability According to the in our work the (Random Forest) algorithm have the best Through the results that appeared by accuracy (0.954084, 0. 882484, and 0. 931849 for three sizes of data.) and then (Decision Tree, K-Nearest Neighbor, Logistic Regression, SVC) sequentially. Index Terms—Machine Learning, potable water, Water Quality, water resources.

Advanced Processes in Water Treatment: Synergistic Effects of Hydrodynamic Cavitation and Cold Plasma on Rhodamine B Dye Degradation

The increasing pollution of water bodies, due to the constant release of highly toxic and non-biodegradable organic pollutants, requires innovative solutions for environmental remediation and wastewater treatment. In this study, the effectiveness of different Advanced Oxidation Processes (AOPs) for the purification of water contaminated with Rhodamine B (RhB) dye at a concentration of 5 mg/L were investigated and compared. Using the classical ozonation strategy as a benchmark treatment, the research showed over 99% degradation of RhB within 4 min in a laboratory-scale batch setup with a capacity of 0.2 L. In contrast, a “chemical-free” process exploiting ultrasound (US) technology achieved a 72% degradation rate within 60 min. Further experiments were conducted using a pilot-scale rotor-stator hydrodynamic cavitation (HC) reactor on a 15 L solution leading to 33% of RhB removal in the presence of hydrogen peroxide (H2O2) at 75 mg/L. However, the use of an innovative cavitational reactor, which hybridizes HC with cold plasma, showed remarkable efficiency and achieved 97% degradation of RhB in just 5 min when treating a 5 L solution at an inlet pressure of 20 bar in a loop configuration. In addition, a degradation rate of 58% was observed in a flow-through configuration, emphasising the robustness and scalability of the HC/electrical discharge (ED) plasma technology. These results underline the potential of hybrid HC/ED plasma technology as an intensified and scalable process for the purification of water, as it offers a catalyst- and oxidant-free protocol.

Efficient degradation of methylene blue and HCHO by nonmetallic B-doped g-C3N5: activity and mechanism analysis

To solve the pollution of natural water bodies by organic dyes and the exceeding of indoor HCHO standards caused by renovation, the study realized the band gap modulation of g-C3N5, a novel semiconductor photocatalytic material, by using H3BO3 as a source of nonmetallic B. The prepared B/g-C3N5 has shown excellent photocatalytic performance and stability for organic dye degradation in water bodies and indoor HCHO removal. The degradation rate of methylene blue (MB) reached 95% in 60 min of visible light, and the removal rate of HCHO reached 96.3% in 180 min of visible light. The MB and HCHO were efficiently degraded to small molecule inorganic compounds such as CO2 and H2O under the oxidation of active groups such as ·O2 − and h+. The doping of nonmetallic B realizes the efficient separation of e−-h+ of g-C3N5, improve the absorption performance of visible light, and broaden the spectral range significantly. The modulation of the g-C3N5 band gap provides a potential application scenario for the development of novel photocatalytic materials.

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.