The influence of floating marine debris (FMD) on coastal and marine communities and ecosystems is undeniable, and attention is increasingly focused on ecologically and biologically important coastal areas. To protect marine life and valuable resources from FMD pollution, identifying FMD accumulation zones is recognized as a priority. One of the coastal ocean processes found governing the distribution of FMD is water convergence (frontal zones). These fronts are driven by various oceanographical factors. To date, the transport and accumulation of FMD in relation to fronts in coastal areas is poorly understood. To address this knowledge gap, we reviewed various types of ocean fronts as well as FMD accumulation along frontal zones in coastal areas defined as the region between the coastline and the shelf break. Frontogenesis (physical processes related to frontal formation) were reviewed alongside studies on FMD accumulation in frontal zones to identify physical factors that drive the pathways and accumulation in these areas. This review will contribute to our understanding of accumulation hotspots of FMD within ocean fronts and identify gaps for further research on developing a proxy for FMD hotspot identification in ecologically important coastal areas.

Pollution from mineral exploitation is an important risk factor affecting surface water environment in mineral regions. It is urgent to construct a simple and accurate model to assess the surface water pollution risk from mineral exploitation in the regional scale. Thus, taking a mining province namely Liaoning in northeastern China as the study area, we proposed a framework to simulate the transport process of pollutants from mineral exploitation points to the surrounding surface water based on the \"source-sink\" theory. In our framework, we adopted the regional growth method (RGM) to extract the potential polluted water area as the certain \"sink\" considering the influence of the topography, and then applied Minimum Cumulative Resistance (MCR) model to assess the surface water pollution risk from mineral exploitation. The results revealed that: (1) 9.5% of the water areas were located at the potential impact area of MEPs. (2) The total value of resistance surface in Liaoning is relatively low, and gradually decreased from west to east. (3) MEPs in Liaoning had a high risk and seriously threatened the surface water environment, among 2125 MEPs, 733 MEPs (32.99%) were assessed as extremely high risk level, and about 35% of the MEPs were distributed within 10KM buffer zone of surface water. (4) Water pollution risk of MEPs in Dalian, Tieling, Fuxin and Dandong need to be emphasized. (5) Compared to previous studies, we considered the topographical influence before applying MCR model directly, so the results of water pollution risk were more reliable. This study provides a methodological support and scientific reference for the water environment protection and regional sustainable development.

Microplastics (MPs), discovered in oceans, lakes, and rivers, can infiltrate the food chain through ingestion by organisms, potentially posing health risks. Our research is the first to study the composition and distribution of MPs in Bosten Lake\'s sediment. In May, the average abundance of MPs was 0.95±0.72 particles per 10 gs, and in October, it was 0.90±0.61 particles per 10 gs. Bohu Town had the highest MP abundance, with 1.75±0.35 particles per 10 gs in spring and 2 ± 0 particles per 10 gs in autumn. In May, 53 % of the MPs were transparent, while in October, black MPs constituted 58 %. The predominant morphology was fibrous, accounting for 61 % of the total. MPs in the size range of 0.2-1 mm made up 91 % and 66 % of the total in May and October, respectively. The most common types of MPs in May were polyethylene terephthalate (PET) at 40 % and polyethylene (PE) at 26 %. In October, PET was the most prevalent at 71 %, followed by poly(ether-ether-ketone)(PEEK) at 11 %. Certain microbial taxa, such as Actinobacteriota, Pseudomonas, and Vicinamibacteraceae, associated with MP degradation or complex carbon chain breakdown, were notably enriched in sediment areas with high MP concentrations. A significant positive correlation was observed between the abundance of MPs in sediments and Actinobacteriota. Additionally, the abundance of Thiobacillus, Ca.competibacter, and other bacteria involved in soil element cycling showed a significant positive correlation with the organic matter content in the sediments. Anaerobic bacteria like Thermoanaerobacterium displayed a significant positive correlation with water depth. Our study reveals the presence, composition, and distribution of MPs in Bosten Lake\'s sediments, shedding light on their potential ecological impact.

Water pollution greatly impacts humans and ecosystems, so a series of policies have been enacted to control it. The first step in performing pollution control is to detect contaminants in the water. Various methods have been proposed for water quality testing, such as spectroscopy, chromatography, and electrochemical techniques. However, traditional testing methods require the utilization of laboratory equipment, which is large and not suitable for real-time testing in the field. Microfluidic devices can overcome the limitations of traditional testing instruments and have become an efficient and convenient tool for water quality analysis. At the same time, artificial intelligence is an ideal means of recognizing, classifying, and predicting data obtained from microfluidic systems. Microfluidic devices based on artificial intelligence and machine learning are being developed with great significance for the next generation of water quality monitoring systems. This review begins with a brief introduction to the algorithms involved in artificial intelligence and the materials used in the fabrication and detection techniques of microfluidic platforms. Then, the latest research development of combining the two for pollutant detection in water bodies, including heavy metals, pesticides, micro- and nanoplastics, and microalgae, is mainly introduced. Finally, the challenges encountered and the future directions of detection methods based on industrial intelligence and microfluidic chips are discussed.

Anthropogenic activities have been one of the crucial driving factors for water pollution globally, thereby warranting a sustainable strategy for its redressal. In this study, we have developed a hydrogel-biochar nanocomposite for catalytic reduction of water pollutants. To begin with, green synthesis of nickel oxide nanoparticles (NiO NPs) was accomplished from waste kinnow peel extract via the environmentally benign microwave method. The formation of NiO NPs was affirmed from different analytical techniques namely ultraviolet-visible (UV-Vis), Fourier transform infrared (FTIR), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and energy-dispersive spectroscopy (EDS). The FESEM images revealed spherical nature of NiO NPs. The average particle size was found to be 15.61 nm from XRD data. A novel hydrogel-biochar nanocomposite comprising the green NiO NPs, sunflower meal biochar and chitosan was prepared (Cs-biochar@ NiO) and explored as a nanocatalyst towards catalytic reduction of pollutants such as 4-nitrophenol, potassium hexacyanoferrate (III) and organic dyes methyl orange (MO), Congo red (CR), methylene blue (MB) in the presence of a reducing agent, i.e. NaBH4. Under optimized conditions, the reduction reactions were completed by 120 s and 60 s for 4-NP and potassium hexacyanoferrate (III) respectively and the rate constants were estimated to be 0.044 s-1 and 0.110 s-1. The rate of reduction was found to be faster for the dyes and the respective rate constants were 0.213 s-1 for MO, 0.213 s-1 for CR and 0.135 s-1 for MB. The assessment of the nanocatalyst in the reduction of binary dye systems depicted its selectivity towards the anionic dyes CR and MO. The nanocatalyst displayed effective reduction of dyes in real-water samples collected from different sources. Taken altogether, this study validates the design of sustainable hydrogel-biochar nanocatalyst for the efficient reduction of hazardous anthropogenic water pollutants.

Although benthic microbial community offers crucial insights into ecosystem services, they are underestimated for coastal sediment monitoring. Sepetiba Bay (SB) in Rio de Janeiro, Brazil, holds long-term metal pollution. Currently, SB pollution is majorly driven by domestic effluents discharge. Here, functional prediction analysis inferred from 16S rRNA gene metabarcoding data reveals the energy metabolism profiles of benthic microbial assemblages along the metal pollution gradient. Methanogenesis, denitrification, and N2 fixation emerge as dominant pathways in the eutrophic/polluted internal sector (Spearman; p < 0.05). These metabolisms act in the natural attenuation of sedimentary pollutants. The methane (CH4) emission (mcr genes) potential was found more abundant in the internal sector, while the external sector exhibited higher CH4 consumption (pmo + mmo genes) potential. Methanofastidiosales and Exiguobacterium, possibly involved in CH4 emission and associated with CH4 consumers respectively, are the main taxa detected in SB. Furthermore, SB exhibits higher nitrous oxide (N2O) emission potential since the norB/C gene proportions surpass nosZ up to 4 times. Blastopirellula was identified as the main responsible for N2O emissions. This study reveals fundamental contributions of the prokaryotic community to functions involved in greenhouse gas emissions, unveiling their possible use as sentinels for ecosystem monitoring.

Hydrogel nanocatalyst composed of nickel oxide (NiO) nanoparticles embedded in PVA-alginate hydrogels were potentially explored toward the reduction of anthropogenic water pollutants. The NiO nanoparticles was accomplished via green method using waste pineapple peel extract. The formation of the nanoparticles was affirmed from different analytical techniques such as UV-Vis, FTIR, XRD, TGA, FESEM, and EDS. Spherical NiO nanoparticles were obtained having an average size of 11.5 nm. The nano NiO were then integrated into PVA-alginate hydrogel matrix forming a nanocomposite hydrogel (PVALg@ NiO). The integration of nano NiO rendered an improved thermal stability to the parent hydrogel. The PVALg@ NiO hydrogel was utilized as a catalyst in the reduction of 4-nitrophenol (4-NP), potassium hexacyanoferrate (III), rhodamine B (RhB), methyl orange (MO), and malachite green (MG) in the presence of a reducing agent, i.e., NaBH4. Under optimized conditions, the reduction reactions were completed by 4.0 min and 3.0 min for 4-NP and potassium hexacyanoferrate (III), respectively, and the rate constant was estimated to be 1.14 min-1 and 2.15 min-1. The rate of reduction was found to be faster for the dyes and the respective rate constants were be 0.17 s-1 for RhB, MG and 0.05 s-1 for MO. The PVALg@ NiO hydrogel nanocatalyst demonstrated a recyclability of four runs without any perceptible diminution in its catalytic mettle. The efficacy of the PVALg@ NiO hydrogel nanocatalyst was further examined for the reduction of dyes in real water samples collected from different sources and the results affirm its high catalytic potential. Thus, this study paves the path for the development of a sustainable hydrogel nanocatalyst for reduction of hazardous pollutants in wastewater treatment.

Super hydrophobic porous silicon surface is prepared using a wet chemical synthesis route. Scanning electron microscopic investigation confirms a correlation between pore size and reaction time. SERS substrates are prepared by silver nanoparticle deposition on porous silicon surface. They exhibit excellent characteristics in terms of sensitivity, reproducibility, stability, and uniformity. They could detect rhodamine 6G in femtomolar range with SERS enhancement factor of ~ 6.1 × 1012, which is best ever reported for these substrates. Molecule-specific sensing of water pollutants such as methylene blue, glyphosate, and chlorpyrifos, is demonstrated for concentrations well below their permissible limits along with excellent enhancement factors. Porous silicon substrate functionalized with Ag nanoparticles demonstrates to be a promising candidate for low-cost, long-life, reliable sensors for environmental conservation applications.

Community-based marine debris removal efforts on the Hawaiian Islands of Kaua\'i and Hawai\'i, spanning 2013-2022, provided large datasets and documented remarkable variations in annual amounts of debris, mainly from abandoned, lost and derelict fishing gear. To test the hypothesis that the influx of marine debris on Hawaiian shores is determined by the proximity of the North Pacific garbage patch, whose pattern changes under the control of large-scale ocean dynamics, we compared these observational data with the output of an oceanographic drift model. The high correlations between the total mass of debris collected and the model, ranging between r = 0.81 and r = 0.84, validate the attribution of the strong interannual signal to significant migrations of the garbage patch reproduced in the model experiments. Synchronous variations in marine debris fluxes on the two islands, separated by >500 km, confirm the large scale of the interannual changes in the North Pacific marine debris system.

Vanillic acid (4-hydroxy-3-methoxybenzoic acid) (VA) is a natural benzoic acid derivative commonly found in herbs, rice, maize, and some fruits and vegetables. However, due to the wide use of VA in various industrial sectors, its presence in the environment might harm living organisms. This study evaluated the toxicity of VA and its isomers, iso-VA and orto-VA. Firstly, the antimicrobial effect of VA and its isomers iso-VA and orto-VA (in doses of 1000; 100, 10, 1; 0.1; 0.01 mg/L) against Escherichia coli, Sarcina spp., Enterobacter homaechei, Staphylococcus aureus and Candida albicans were identified. The toxic effect and protein degradation potential of VA and its isomers were determined using E. coli grpE:luxCDABE and lac:luxCDABE biosensor strains. However, the genotoxicity and oxidative stress generation were assessed with the E. coli recA:luxCDABE biosensor and E. coli strain. The results showed that VA, iso-VA, and orto-VA exhibited antimicrobial activity against all tested bacterial strains. However, VA\'s antimicrobial effect differed from iso-VA and orto-VA. Similar toxic, genotoxic, and oxidative stress-inducing effects were observed for VA and its isomers. Each compound exhibited toxicity, cellular protein degradation, and genotoxic activity against E. coli grpE:luxCDABE, E. coli lac:luxCDABE, and E. coli recA:luxCDABE strains. Analysis of reactive oxygen species (ROS) generation within E. coli cells highlighted oxidative stress as a contributing factor to the toxicity and genotoxicity of VA and its isomers. While the findings suggest potential applications of VA compounds as food preservatives, their presence in the environment raises concerns regarding the risks posed to living organisms due to their toxic and genotoxic characteristics.