Lithium Pollution and Its Associated Health Risks in the Largest Lithium Extraction Industrial Area in China.

Lithium (Li) is an important resource that drives sustainable mobility and renewable energy. Its demand is projected to continue to increase in the coming decades. However, the risk of Li pollution has also emerged as a global concern. Here, we investigated the pollution characteristics, sources, exposure levels, and associated health risks of Li in the Jinjiang River basin, the largest area for Li2CO3 production in China. Our results revealed the dominant role of Li extraction activities in the pollution of the river, with over 95% of dissolved Li in downstream river water being emitted from this source. Moreover, the Li concentration in aquatic plants (i.e., water hyacinth) and animals (i.e., fish) significantly increased from upstream to downstream areas, indicating a significant risk to local aquatic ecosystems. More importantly, our study found that local residents were suffering potential chronic noncarcinogenic health risks primarily from consuming contaminated water and vegetables. We also investigated the pollution characteristics of associated elements present in Li ores (e.g., Rb, Cs, Ni, and F-). By uncovering the remarkable impact of Li extraction activities on the Li content in ecosystems for the first time, our study emphasizes the importance of evaluating Li pollution from Li-related industrial activities, including mining, extraction, and recovery.

Development of an analytical method to quantify N-acyl-homoserine lactones in bacterial cultures, river water, and treated wastewater.

N-Acyl-homoserine lactones (AHL) play a major role in the communication of Gram-negative bacteria. They influence processes such as biofilm formation, swarming motility, and bioluminescence in the aquatic environment. A comprehensive analytical method was developed to elucidate the "chemical communication" in pure bacterial cultures as well as in the aquatic environment and engineered environments with biofilms. Due to the high diversity of AHLs and their low concentrations in water, a sensitive and selective LC-ESI-MS/MS method combined with solid-phase extraction was developed for 34 AHLs, optimized and validated to quantify AHLs in bacterial conditioned medium, river water, and treated wastewater. Furthermore, the developed method was optimized in terms of enrichment volume, internal standards, limits of detection, and limits of quantification in several matrices. An unanticipated variety of AHLs was detected in the culture media of Pseudomonas aeruginosa (in total 8 AHLs), Phaeobacter gallaeciensis (in total 6 AHLs), and Methylobacterium mesophilicum (in total 15 AHLs), which to our knowledge have not been described for these bacterial cultures so far. Furthermore, AHLs were detected in river water (in total 5 AHLs) and treated wastewater (in total 3 AHLs). Several detected AHLs were quantified (in total 24) using a standard addition method up to 7.3±1.0 µg/L 3-Oxo-C12-AHL (culture media of P. aeruginosa).

Determination of Macrolides in Water Using Solid-Phase Extraction and Supercritical Fluid Chromatography-Tandem Mass Spectrometry.

Macrolides are a group of compounds used to treat bacterial infections in humans and animals. Their widespread use results in the contamination of the water environment, which, on the one hand, has a detrimental effect on aquatic organisms and, on the other hand, can lead to the emergence of resistant strains of microorganisms. All of the above determines the need for monitoring of these compounds in the environment, particularly, in water objects. Usually, the high-performance liquid chromatography combined with tandem mass spectrometry method is used to solve this problem, however, this work shows the possibility of using the supercritical fluid chromatography-tandem mass spectrometry method. An approach for the determination of four common macrolides, namely erythromycin, clarithromycin, midecamycin, and josamycin, was developed. The use of solid-phase extraction allowed to achieve limits of quantification at 0.57-6.8 ng/L. The presented approach was validated and tested on a real object-a sample of municipal wastewater.

Concentrations, probabilistic human and ecological risks assessment attribute to antibiotics residues in river water in China: Systematic review and meta-analysis.

Antibiotics residues even low concentrations increases human health risk and ecological risk. The current study was conducted with the aims of meta-analysis concentrations of antibiotics in river water including amoxicillin (AMX), tetracyclines (TCN), sulfamethoxazole (SMX), ciprofloxacin (CIP), trimethoprim (TMP), azithromycin (AZM) and amoxicillin (AMX) and estimates human health and ecological risks. Search was performed in databases including Scopus, PubMed, Web of Science, Embase, Science direct, Cochrane, Science Direct, Google Scholar were used to retrieve scientific papers from January 1, 2004 to June 15, 2024. The concentration of antibiotics residues was meta-analyzed using random effects model in water river water based on type of antibiotics subgroups. Human health risk assessment from ingestion and dermal contact routs was estimated using target hazard quotient (THQ), total target hazard quotient (TTHQ), carcinogenic (CR) and ecological hazard quotient (EHQ) of antibiotics in river water was estimated using monte carlo simulations (MCS) model. Sixty-two papers on antibiotics in river water with 272 data-reports (n = 28,522) were included. The rank order of antibiotics residues in river water based on pooled concentration was SMX (66.086 ng/L) > CIP (26.005 ng/L) > TCN (17.888 ng/L) > TMP (6.591 ng/L) > AZM (2.077 ng/L) > AMX (0.029 ng/L). The overall pooled concentration of antibiotics residues in river water was 24.262 ng/L, 95 %CI (23.110-25.413 ng/L). TTHQ for adults and children due to antibiotics in water was 2.41E-3 and 2.36E-3, respectively. The sort of antibiotics based on their quota in TTHQ for adults and children was AMX > CIP > TMP > AZM > TCN > SMX. Total CR in adults and children was 2.41E-03 and 2.36E-03, respectively. The sort of antibiotics based on percentile 95 % EHQ was SMX (7.70E+03) > TCN (7.63E+01) > TMP (7.03E-03) > CIP (2.86E-03) > AMX (5.71E-04) and TEHQ values due to antibiotics in river water in China was equal to 7.78E+03. Current study suggests that conduct effective monitoring and water quality control plans to reduce concentration of antibiotics especially SMX, TCN, and CIP in river water of China.

Exploring correlations between microplastics, microorganisms, and water quality in an urban drinking water source.

The microplastic pollution in freshwater system is gradually becoming more severe, which has led to increasing attention on the distribution and potential harmful effects of microplastics. Moreover, microplastics may have an impact on river ecology and pose risks to ecosystems. Therefore, it is important to reveal this process. This study aimed to explore correlations between microplastics and free-living microorganisms in an urban drinking water source of Xiangjiang River by using multivariate statistical analysis. The results indicated that the abundance of microplastics (size 50 µm to 5 mm) in surface water and sediments ranged from 0.72 to 18.6 (mean ± SD: 7.32 ± 2.36) items L-1 and 26.3-302 (150 ± 75.6) items kg-1 dry weight (dw), respectively, suggesting potential microplastic pollution despite the protected status as a drinking water source. Higher microplastic abundances were observed in urban areas and the downstream of wastewater plants, with mostly granular shape, transparent and black color as well as 50-100 µm in size. The multivariate statistical analysis presented that the abundance of microplastics is not significantly correlated with water indicators, due to the complexity of the abundance data. The water indicators showed an obvious correlation with microplastics in colors of transparent and black, and smaller sizes of 50-100 µm. This is also true for microplastics and microorganisms in water and sediment. Proteobacteria was the main prokaryote in water and sediments, being positively correlated with 50-100 µm microplastics; while Chloroplastida was the dominated eukaryotes, presenting a weak correlation with smaller-size microplastics. Overall, when considering the properties of microplastics such as shape, color and size, the potential correlations with water indicators and microorganisms were more evident than abundance. This study provides new insights into the multivariate statistical analysis, explaining the potential correlations among microplastic properties, microorganisms and environmental factors in a river system.

Adsorption of antiretroviral drugs, abacavir, nevirapine, and efavirenz from river water and wastewater using exfoliated graphite: Isotherm and kinetic studies.

In this work, exfoliated graphite was used to adsorb antiretroviral drugs from river water and wastewater. The exfoliated graphite was prepared from natural graphite by intercalating it with the acids and exfoliating it at 800 °C. It was characterized using Fourier Transform Infrared Spectroscopy which showed phenolic, alcoholic, and carboxylic functional groups between 1000 cm-1 and 1700 cm-1. Energy-dispersive X-ray spectroscopy results showed carbon as the main element with splashes of oxygen. The Scanning Electron Microscopy images showed increased c-axis distance between graphene layers after intercalation, which further increased after the exfoliation. The exfoliation resulted in elongated distorted cylinders, which were confirmed by the lower density (0.0068 g/mL) of exfoliated graphite material compared to the natural graphite (0.54 g/mL). The X-ray diffraction pattern showed the characteristics of hexagonal phase graphitic structure by the diffraction plane (002) at 26.74°. Raman spectroscopy results showed the natural graphite, graphite intercalated, and exfoliated graphite contained the D, G, D', and G' peaks at about 1350 cm-1, 1570 cm-1, 2440 cm-1, and 2720 cm-1, respectively indicating that the material's crystallinity was not affected by the modification. The highest antiretroviral drugs removal (95-99%), from the water was achieved with a solution pH of 7, an adsorbent mass of 30 mg, and an adsorption time of 30 min. The kinetic model and adsorption isotherm studies showed that the experimental data fit well in pseudo-second-order kinetics and is well explained by Freundlich's adsorption isotherm. The maximum adsorption capacity of the exfoliated graphite for antiretroviral drugs ranges between 1.660 and 197.0, 1.660-232.5, and 1.650-237.7 mg/g for abacavir, nevirapine, and efavirenz, respectively. The obtained removal percentages were 100% in river water, 63-100% in influent and 70-100% in effluent wastewater unspiked samples.

Dynamic patterns and potential drivers of river water quality in a coastal city: Insights from a machine-learning-based framework and water management.

River water quality continues to deteriorate under the coupled effects of climate change and human activities. Machine learning (ML) is a promising approach for analyzing water quality. Nevertheless, the spatiotemporal dynamics of river water quality and their potential mechanisms in changing environments remain incomprehensively understood through available ML-based researches. Here, we developed a ML-based framework integrating a self-organizing map (SOM) model with a random forest (RF) model. This framework was applied to simultaneously investigate the spatiotemporal patterns and potential drivers of river permanganate (CODMn), ammonia nitrogen (NH3-N), and total phosphorus (TP) dynamics across 34 sites from 2010 to 2020 in a coastal city threatened by deteriorating water environment in southeastern China. The sites were divided into two clusters in the spatial context with different water quality conditions. The year of 2015 for NH3-N and 2018 for CODMn and TP were identified as the key turning points of water quality variations. Features including sewage discharge, population dynamics, percentage of cultivated land, and fertilizer application contributed greatly to water quality deterioration. The increase in forest vegetation reflected by percentage of forest and leaf area index may improve water quality. The ML-based modeling framework demonstrated a promising way to address the spatiotemporal dynamics of river water quality, and provided insights for water management in a coastal city with intensifying human-nature interactions.

Balancing river water pollution and agricultural development: A tradeoff threshold approach.

Balancing environmental protection and social-economic development in agricultural land use management is a dilemma for decision-makers. Based on the modelling of the impacts of land use changes on river water pollution by SWAT model, the tradeoff between tea plantation expansion and river water quality was detected. SWAT model performs well in simulating the non-point source (NPS) pollution in agricultural watershed. The results showed that the tea plantation area expanded dramatically from 44 km2 in 2000 to 169 km2 in 2020 at the high cost of forest land. Consequently, the mean contents of NO3--N and TN have significantly increased by 100% and 91% respectively in the past 20 years. And the NO3--N in river water accounted for over 80% of TN in the tea plantation area. The NO3--N and TN concentrations were positively related with the proportions of tea plantation area (Tea%) at different periods. The high pollution levels of NO3--N and TN are priority control targets for river water quality management. The results indicated that the proportion of tea plantation thresholds lead to abrupt changes in river water quality. When the Tea% exceeded 3.0% in 2000, the probability of N pollution increased sharply. Whereas in 2020, it is suggested that the Tea% should not exceeds 18% to avoid sudden deterioration of water quality. The critical interval value of the Tea% for sudden change in N pollution showed an obvious increase tendency. The accelerating of nutrient pollution in rivers reduced the sensitivity of water quality to tea plantation expansion. Our results can provide new insights and empirical evidence for balancing the tradeoff between agricultural development and river water quality protection by demonstrating the carrying capacity threshold of river water environment for the expansion tea plantation.

Comprehensive river water quality monitoring using convolutional neural networks and gated recurrent units: A case study along the Vaigai River.

Effective monitoring of river water quality is required for long-term water resource management. Convolutional Neural Networks and Gated Recurrent Unit-based water quality monitoring (CNGRU-WQM) were used in this investigation to develop a comprehensive monitoring system along the Vaigai River. The system was designed to collect real-time data on several crucial water quality parameters. The collected characteristics encompassed factors like water pollution levels, turbidity, pH readings, temperature, and total dissolved solids, offering a comprehensive view of river water quality. The monitoring system was methodically set up, with sensors strategically positioned at various locations along the river. This ensured that data collection would take place at regular intervals. The CNGRU-WQM model achieved a validation accuracy of 97.86%, surpassing the performance of other state-of-the-art approaches. Particularly noteworthy is the fact that the actual use of this system incorporates real-time warnings, which enable stakeholders to be instantly informed if water quality measurements surpass pre-set criteria. The study's contributions include its efficient river water quality monitoring system, which encompasses a variety of indicators, and its ability to significantly affect environmental conservation efforts by offering a helpful tool for informed decision-making and timely interventions.

Integrating deep learning techniques for effective river water quality monitoring and management.

Effective river water quality monitoring is essential for sustainable water resource management. In this study, we established a comprehensive monitoring system along the Kaveri River, capturing real-time data on multiple critical water quality parameters. The parameters collected encompassed water contamination levels, turbidity, pH measurements, temperature, and total dissolved solids (TDS), providing a holistic view of river water quality. The monitoring system was meticulously set up with strategically positioned sensors at various river locations, ensuring data collection at regular 5-min intervals. This data was then transmitted to a cloud-based web portal, facilitating storage and analysis. To assess water quality, we introduced a novel hybrid approach, combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. The proposed CNN-LSTM model achieved a validation accuracy of 98.40%, surpassing the performance of other state-of-the-art methods. Notably, the practical application of this system includes real-time alerts, promptly notifying stakeholders when water quality parameters exceed predefined thresholds. This feature aids in making informed decisions in water resource management. The study's contributions lie in its effective river water quality monitoring system, which encompassing various parameters, and its potential to positively impact environmental conservation efforts by providing a valuable tool for informed decision-making and timely interventions.

Geostatistical appraisal of water quality, contamination, source distribution of potentially toxic elements (PTEs) in the lower stretches of Subarnarekha River (Odisha), India, and health risk assessment by Monte Carlo simulation approach.

In the present study, the status of water quality, environmental contamination in the lower stretch of Subarnarekha River with respect to potentially toxic elements (PTEs), its seasonal distribution, and ecotoxicological health impacts were investigated. For this purpose, a combination of indexing approaches and geospatial methods was used. The estimated water quality index (WQI) has shown that the river water falls under "moderate to very poor" category during the pre-monsoon and "moderate to poor" category in the post-monsoon season. The abundance of PTEs (Pb, Cu, Ni, Cd, Fe, and Cr) was on the higher side during the pre-monsoon in comparison with the post-monsoon season. The results of contamination index (Cd) and heavy metal evaluation index (HEI) explain that Subarnarekha River has low-to-moderate levels of contamination with PTEs in the majority of sampling sites. However, HPI indicated that the river water is moderate-to-highly contaminated with PTEs in both seasons. Principal component analysis (PCA) and cluster analysis (CA) reveal that anthropogenic sources are prime contributors to PTEs contamination in Subarnarekha River. The potential non-cancerous health concerns for child and adults due to Cr and Pb in some sampling stations along the river stretch have been observed. The carcinogenic risk (CR) has been established for Cr, Pb, and Cd in Subarnarekha River with Cr (> 10-4) as the most unsafe element. Monte Carlo simulation (MCS) indicates a high risk of cancer hazards due to Cr (values > 1E-04) in present as well as future for both child and adults.

Migration characteristics of microplastics in riparian soils and groundwater.

Investigations have revealed the presence of microplastics in both soil and groundwater, but the migration characteristics from soil to groundwater remain incompletely understood. In this study, two sampling sections consisting of soil-groundwater-river water were established near Lianxi Bridge and Xilin Bridge along the Jiuxi River in Xiamen. A total of 22 soil samples, 36 groundwater samples, and 18 river water samples were collected. Microplastics were detected in all samples with an abundance range of 392-836 n/kg in soil (mean, 655 ± 177 n/kg), 0.58-2.48 n/L groundwater (mean, 1.23 ± 0.42 n/L), and 0.38-1.80 n/L in river water (mean, 0.86 ± 0.41 n/L). Flakes predominantly constituted the shape of microplastics found in soil, while fibers dominated those present in water. Black, yellow, and red were the dominant color types. Polyamide (PA) and polyethylene (PE) were the main components of microplastics within soils, whereas polyethylene terephthalate (PET), polypropylene (PP), and PA prevailed within water. Microplastic particle sizes ranged from 39 to 2498 µm in soils, mainly from 29 to 3394 µm in water. The upstream section displayed higher abundances of microplastic compared to the downstream, revealing the soil particles having an intercepting effect on microplastics. The distribution and migration of microplastics in soil and groundwater are affected by many factors, including natural and anthropogenic factors, such as soil depth, soil properties, pore structure, hydrodynamics, hydraulic connections between groundwater and surface water, the extensive utilization and disposal of plastics, irrational exploitation of groundwater, and morphology and types of microplastics. These research findings contribute to a better understanding of the pathways, migration capacity, and influencing factors associated with microplastic entry into groundwater, thereby providing valuable technical support for the development of strategies aimed at controlling microplastic pollution.

Prevalence of antibiotic resistance genes in bacteria from Gomti and Ganga rivers: implications for water quality and public health.

Rivers serve as a significant habitat and water sources for diverse organisms, including humans. An important environmental and public health concern is the increase in antibiotic-resistant bacteria (ARBs) and genes (ARGs) in aquatic ecosystems brought about by excessive pollutant flow. The research highlighted that river water, which is receiving discharge from wastewater treatment plants, is harbouring multidrug-resistant bacteria. River water samples were collected in January, April, July and October 2022 from three separate locations of each Gomti and Ganga river. A total of 114 bacteria were isolated from Gomti as well as the Ganga River. All the isolates were tested for their resistance to various antibiotics by disc diffusion method. The isolated bacteria were tested for the antibiotic resistance genes using PCR and were identified by 16s rRNA sequencing. The ARBs percentages for each antibiotic were as follows: ampicillin (100%); cefotaxime (96.4, 63.1%); erythromycin (52.6, 57.8%); amikacin (68.4, 50.8%); tetracycline (47.3, 54.3%); nalidixic acid (47.3, 45.6%); streptomycin (68.4, 49.1%); gentamycin (43.8, 35%); chloramphenicol (26.3, 33.3%); neomycin (49.1, 29.8%) and ciprofloxacin (24.5, 7.01%). Further, antibiotic resistance genes in Gomti and Ganga water samples disclose distinctive patterns, including resistance to ermB (25, 40%); tetM (25, 33.3%); ampC (44.4, 40%) and cmlA1 (16.6%). Notably cmlA1 resistant genes were absent in all bacterial strains of the Gomti River. Additionally, gyrA gene was not found in both the river water samples. The presence of ARGs in the bacteria from river water shows threat of transferring these genes to native environmental bacteria. To protect the environment and public health, constant research is necessary to fully understand the extent and consequences of antibiotic resistance in these aquatic habitats.

Structural alterations in scales of Capoeta capoeta (Güldenstädt, 1773) from heavy metal-contaminated river water.

Heavy metal pollution, especially in freshwater, is a serious problem for aquatic organisms and human health. In this study, the scales of Capoeta capoeta living in the Karasu River (Turkey), which is estimated to be contaminated with pollutants, especially heavy metals, were examined for structural anomalies. Two stations on the river were selected for this purpose. Fish and surface water samples were taken at the stations. The heavy metal analyses were carried out in the water and the fish tissue. Heavy metal pollution was detected in the surface water. It was also observed that some heavy metals (As, Cu, Cd, Cr, Mn, Pb, Ni, Zn) accumulate in the fish tissue. Significant structural differences were observed on the dorsal surface of the scales, such as interrupted primary radii, damaged circuli, damaged focus, damaged anterior scale margin, broken focus, deformed scale structure, scattered chromatophores, dilatation of primary radii, loss of focus, damaged annuli, symmetry shift in the lateral line canal, eroded circuli, damaged posterior scale margin, double focus, branching in the primary radii, asymmetric circuli, incomplete annuli and interrupted secondary radii in each of the fish collected from the contaminated site. Heavy metals are suspected to be responsible for the structural anomalies in the scales. Based on these observations, it can be said that fish scales can be used as an effective indicator of water quality.

Aquiflexum gelatinilyticum sp. nov., isolated from river water.

Two Gram-stain-negative, strictly aerobic, rod-shaped, non-motile and non-gliding bacteria, designated as XJ19-10T and XJ19-11, were isolated from river water in Xinjiang Uygur Autonomous Region, PR China. Cells of these strains were catalase-, oxidase- and gelatinase-positive and contained carotenoids but no flexirubins. Growth occurred at 10-30 °C, pH 7.0-9.0 and with 0-2.5% (w/v) NaCl. On the basis of the results of 16S rRNA gene sequence and genome analyses, the two isolates represented members of the genus Aquiflexum, and the closest relative was Aquiflexum aquatile Z0201T with 16S rRNA gene sequence pairwise similarities of 97.9-98.1%. Furthermore, the average nucleotide identities and digital DNA-DNA hybridization identities between the two isolates and other relatives were all less than 82.9 and 28.2 %, respectively, all below the species delineation thresholds. The results of pan-genomic analysis indicated that the type strain XJ19-10T shared 2813 core gene clusters with other three type strains of members of the genus Aquiflexum, as well as having 623 strain-specific clusters. The major polar lipids were phosphatidylethanolamine, phosphatidylcholine, an unidentified aminolipid and unidentified lipids. The predominant fatty acids (>10% of the total contents) were iso-C15 : 0, iso-C15 : 1G, iso-C17 : 0 3-OH and summed feature 9, and MK-7 was the respiratory quinone. On the basis of the results of phenotypic, physiological, chemotaxonomic and genotypic characterization, strains XJ19-10T and XJ19-11 are considered to represent a novel species, for which the name Aquiflexum gelatinilyticum sp. nov. is proposed. The type strain is XJ19-10T (=CGMCC 1.19385T =KCTC 92266T).

Microbial Degradation of Free and Halogenated Estrogens in River Water-Sediment Microcosms.

Halogenated estrogens are formed during chlorine-based wastewater disinfection and have been detected in wastewater treatment plant effluent; however, very little is known about their susceptibility to biodegradation in natural waters. To better understand the biodegradation of free and halogenated estrogens in a large river under environmentally relevant conditions, we measured estrogen kinetics in aerobic microcosms containing water and sediment from the Willamette River (OR, USA) at two concentrations (50 and 1250 ng L-1). Control microcosms were used to characterize losses due to sorption and other abiotic processes, and microbial dynamics were monitored using 16S rRNA gene sequencing and ATP. We found that estrogen biodegradation occurred on timescales of hours to days and that in river water spiked at 50 ng L-1 half-lives were significantly shorter for 17ß-estradiol (t1/2,bio = 42 ± 3 h) compared to its monobromo (t1/2,bio = 49 ± 5 h), dibromo (t1/2,bio = 88 ± 12 h), and dichloro (t1/2,bio = 98 ± 16 h) forms. Biodegradation was also faster in microcosms with high initial estrogen concentrations as well as those containing sediment. Free and halogenated estrone were important transformation products in both abiotic and biotic microcosms. Taken together, our findings suggest that biodegradation is a key process for removing free estrogens from surface waters but likely plays a much smaller role for the more highly photolabile halogenated forms.

Nontarget Analysis and Comprehensive Characterization of Iodinated Polyfluoroalkyl Acids in Wastewater and River Water by LC-HRMS with Cascade Precursor-Ion Exclusions and Algorithmic Approach.

Poly- and perfluoroalkyl acids (PFAAs) are a large family of widespread contaminants of worldwide concern and well-known as "forever chemicals". Direct emission of PFAAs from the fluorochemical industry is a crucial source of PFAA pollutants in the environment. This study implemented nontarget analysis and comprehensive characterization for a category of new PFAA contaminants, i.e., iodinated PFAAs (IPFAAs), in fluorochemical industry wastewater and relevant contaminated river water by liquid chromatography-high-resolution mass spectrometry with a cascade precursor ion exclusion (PIE) strategy and in-house developed data extraction and processing algorithms. A total of 26 IPFAAs (including 2 isomers of an IPFAA) were found and identified with tentative molecular structures. Semiquantification of the IPFAAs was implemented, and the total concentrations of IPFAAs were 0.16-285.52 and 0.15-0.17 µg/L in wastewater and river water, respectively. The high concentrations in association with the predicted ecotoxicities and environmental behaviors demonstrate that these IPFAAs are worthy of more concern and further in-depth research. The cascade PIE strategy along with the data extraction and processing algorithms can be extended to nontarget analysis for other pollutants beyond IPFAAs. The nontarget identification and characterization outcomes provide new understanding on the environmental occurrence and pollution status of IPFAAs from a comprehensive perspective.

Insights into bacterial community metatranscriptome and metabolome in river water influenced by palm oil mill effluent final discharge.

AIMS: This study aimed to investigate the effect of palm oil mill effluent (POME) final discharge on the active bacterial composition, gene expression, and metabolite profiles in the receiving rivers to establish a foundation for identifying potential biomarkers for monitoring POME pollution in rivers. METHODS AND RESULTS: The POME final discharge, upstream (unpolluted by POME), and downstream (effluent receiving point) parts of the rivers from two sites were physicochemically characterized. The taxonomic and gene profiles were then evaluated using de novo metatranscriptomics, while the metabolites were detected using qualitative metabolomics. A similar bacterial community structure in the POME final discharge samples from both sites was recorded, but their composition varied. Redundancy analysis showed that several families, particularly Comamonadaceae and Burkholderiaceae [Pr(>F) = 0.028], were positively correlated with biochemical oxygen demand (BOD5) and chemical oxygen demand (COD). The results also showed significant enrichment of genes regulating various metabolisms in the POME-receiving rivers, with methane, carbon fixation pathway, and amino acids among the predominant metabolisms identified (FDR < 0.05, PostFC > 4, and PPDE > 0.95). This was further validated through qualitative metabolomics, whereby amino acids were detected as the predominant metabolites. CONCLUSIONS: The results suggest that genes regulating amino acid metabolism have significant potential for developing effective biomonitoring and bioremediation strategies in river water influenced by POME final discharge, fostering a sustainable palm oil industry.

Unveiling interactions of norfloxacin with microplastic in surface water by 2D FTIR correlation spectroscopy and X-ray photoelectron spectroscopy analyses.

Microplastics (MPs) has shown adsorption of hydrophilic organic matters (HOMs) in aqueous environments. However, it is still difficult to predict the adsorption behaviors of HOMs by different MPs, especially in authentic water systems. In this study, the adsorption behaviors and mechanisms of norfloxacin (NOR) onto polyamide (PA) MPs were investigated in both simulated and real surface water. The results showed that the adsorption equilibrium of NOR by PA in simulated surface water could be achieved within 15 h, while the adsorption rate of NOR in real surface was slowed down, with the equilibrium time of 25 h. Pseudo-second-order model could well describe the adsorption kinetics data. The experimental maximum adsorption capacity of NOR on PA in real surface water (e. g. 132.54 ug/g) was dramatically reduced by 37.5 % compared with that in simulated surface water (e. g. 212.25 ug/g), and the adsorption isotherm would obey Freundlich model. Besides, the leaching of NOR from the surface of PA could occur obviously at acidic environment. Furthermore, the salinity and natural organic matter exhibited significantly adverse effects on the NOR adsorption. Finally, the results of 2D Fourier transform infrared correlation spectroscopy and X-ray photoelectron spectroscopy indicated that the electrostatic, H-bond and van der Waals interactions were involved in the adsorption. More importantly, the sequential functional groups in the adsorption process followed the orders: 1638 (CO) > 1542 amide II (-NH-CO) > 717 (CH2) > 1445 (CO) > 973 amide IV (CONH). This study could provide an insight into the interactions between PA and NOR in different water environments.

Distribution and risk assessment of antibiotics under water level fluctuation in the riparian zone of the Hanjiang River.

The riparian zone (RZ) is an important region connecting surface water and groundwater, and it has widely been acknowledged for its pollutant buffering capacity. However, the decontaminating effect of RZ on trace organic compounds such as antibiotics has received little attention. This study explored the distribution of 21 antibiotics and 4 sulfonamide metabolites in river water and groundwater in the lower reaches of the Hanjiang River. The diffusion and exchange of contaminants between the river and riverbanks under the influence of water conservancy projects (Xinglong Dam and the Yangtze-Hanjiang Water Diversion Project) were investigated. Macrolide antibiotics were prevalent in river water (62.5-100%) and groundwater samples (42.9-80.4%). Ofloxacin and chlortetracycline were detected with the highest concentrations in river water (12.2 ng L-1) and groundwater (9.3 ng L-1) respectively. Higher levels of antibiotics were observed in spring and winter than in other seasons. The river-groundwater interaction has a certain interception effect on antibiotics, especially near riverbanks. Redox sensitive element Fe2+ showed significantly positive correlations with some tetracycline and macrolide antibiotics (p < 0.05), and thus the migration mechanism between Fe2+ and antibiotics under the condition of redox change should be investigated further. Environmental risks posed by antibiotics were assessed for algae, daphnids, and fish in surface water and groundwater. Only clarithromycin and chlortetracycline presented a medium risk to algae (0.1 < RQ < 1), and the rest presented low risk (RQ < 0.1). Nevertheless, the risk range may be further extended by interactions between groundwater and surface water. Accurate understanding of antibiotic transport in RZ is critical for developing management strategies aimed at reducing the pollution load on the watershed.