Search Results (2,295)

Background/Objectives: This study examines how seasonality, pollution, and sample type (water and sediment) influence the presence and distribution of antibiotic resistance genes (ARGs), with a focus on antibiotic resistance genes (ARGs) located on plasmids (the complete set of plasmid-derived sequences, including ARGs) in a tropical urban river. Methods: Samples were collected from three sites along a pollution gradient in the Virilla River, Costa Rica, during three seasonal campaigns (wet 2021, dry 2022, and wet 2022). ARGs in water and sediment were quantified by qPCR, and metagenomic sequencing was applied to analyze chromosomal and plasmid-associated resistance profiles in sediments. Tobit and linear regression models, along with multivariate ordination, were used to assess spatial and seasonal trends. Results: During the wet season of 2021, the abundance of antibiotic resistance genes (ARGs) such as sul-1, intI-1, and tetA in water samples decreased significantly, likely due to dilution, while intI-1 and tetQ increased in sediments, suggesting particle-bound accumulation. In the wet season 2022, intI-1 remained low in water, qnrS increased, and sediments showed significant increases in tetQ, tetA, and qnrS, along with decreases in sul-1 and sul-2. Metagenomic analysis revealed spatial differences in plasmid-associated ARGs, with the highest abundance at the most polluted site (Site 3). Bacterial taxa also showed spatial differences, with greater plasmidome diversity and a higher representation of potential pathogens in the most contaminated site. Conclusions: Seasonality and pollution gradients jointly shape ARG dynamics in this tropical river. Plasmid-mediated resistance responds rapidly to environmental change and is enriched at polluted sites, while sediments serve as long-term reservoirs. These findings support the use of plasmid-based monitoring for antimicrobial resistance surveillance in aquatic systems. Full article

South Dongting Lake is an essential aquatic ecosystem that receives substantial water inflows from the Xiangjiang and Zishui Rivers. However, it is significantly impacted by human activities, including mining, smelting, and farming. These activities have led to serious contamination of the lake’s sediments with heavy metals (HMs). This study investigated the distribution, mobility, and influencing factors of HMs at the sediment–water interface. To this end, sediment samples were analyzed from three key regions (Xiangjiang River estuary, Zishui River estuary, and northeastern South Dongting Lake) using traditional sampling methods and Diffusive Gradients in Thin Films (DGT) technology. Analysis of fifteen HMs (Pb, Bi, Ni, As, Se, Cd, Sb, Mn, Zn, V, Cr, Cu, Tl, Co, and Fe) revealed significant spatial heterogeneity. The results showed that Cr, Cu, Pb, Bi, Ni, As, Se, Cd, Sb, Mn, Zn, and Fe exhibited high variability (CV > 0.20), whereas V, Tl, and Co demonstrated stable concentrations (CV < 0.20). Concentrations were found to exceed background values of the upper continental crust of eastern China (UCC), Yangtze River sediments (YZ), and Dongting Lake sediments (DT), particularly at the Xiangjiang estuary (XE) and in the northeastern regions. Speciation analysis revealed that V, Cr, Cu, Ni, and As were predominantly found in the residual fraction (F4), while Pb and Co were concentrated in the oxidizable fraction (F3), Mn and Zn appeared primarily in the exchangeable fractions (F1 and F2), and Cd was notably dominant in the exchangeable fraction (F1), suggesting a high potential for mobility. Additionally, DGT results confirmed a significant potential for the release of Pb, Zn, and Cd. Contamination assessment using the Pollution Load Index (PLI) and Geoaccumulation Index (Igeo) identified Pb, Bi, Ni, As, Se, Cd, and Sb as major pollutants. Among these, Bi and Cd were found to pose the highest risks. Furthermore, the Risk Assessment Code (RAC) and the Potential Ecological Risk Index (PERI) highlighted Cd as the primary ecological risk contributor, especially in the XE. The study identified sediment grain size, pH, electrical conductivity, and nutrient levels as the primary influencing factors. The PMF modeling revealed HM sources as mixed smelting/natural inputs, agricultural activities, natural weathering, and mining/smelting operations, suggesting that remediation should prioritize Cd control in the XE with emphasis on external inputs. Full article

Accurate estimation of groundwater levels in river basins is essential for effective water resource planning. Innovations in deep learning and artificial intelligence (AI) have been introduced into this field to enhance the accuracy of long-term groundwater level estimation. This study employs the Transformer deep learning model to estimate groundwater levels, with a benchmark comparison against the long short-term memory (LSTM) model. These models were applied to estimate groundwater levels in the Yellow River Basin, where approximately 1100 monitoring wells are located. Monthly average groundwater level data from the period 2018–2023 were collected from these wells. The two models were used to estimate groundwater levels for the period 2003–2017 by incorporating remote sensing information. The Transformer model was enhanced to simultaneously capture features from both historical temporal data and surrounding spatial data, while automatically enhancing key features, effectively improving estimation accuracy and robustness. At the basin-averaged scale, the enhanced Transformer model outperformed the LSTM model: R² increased by approximately 17.5%, while RMSE and MAE decreased by approximately 12.4% and 10.9%, respectively. The proportion of poorly predicted samples decreased by an average of approximately 12.1%. The estimation model established in this study contributes to improving the quantitative analysis capability of long-term groundwater level variations in the Yellow River Basin. This could be helpful for water resource development planning in this densely populated region and likely has broad applicability in other river basins. Full article

This comprehensive study investigates the spatial distribution of metals in surface water, their accumulation in fish tissues, and their impact on the gut microbiome dynamics of fish in the Qi River, Huanggang City, Hubei Province. Three distinct sampling regions were established: the mining area (A), the transition area (B), and the distant area (C). Our results revealed that metal concentrations were highest in the mining area and decreased with increasing distance from it. The bioaccumulation of metals in fish tissues followed the order of gut > brain > muscle, with some concentrations exceeding food safety standards. Analysis of the gut microbiota showed that Firmicutes and Proteobacteria dominated in the mining area, while Fusobacteriota were more prevalent in the distant area. Heavy metal pollution significantly altered the composition and network structure of the gut microbiota, reducing microbial associations and increasing negative correlations. These findings highlight the profound impact of heavy metal pollution on both fish health and the stability of their gut microbiota, underscoring the urgent need for effective pollution control measures to mitigate ecological risks and protect aquatic biodiversity. Future research should focus on long-term monitoring and exploring potential remediation strategies to restore the health of affected ecosystems. Full article

The paper presents the results of investigations into the relationship between selected water quality parameters and hydrological streamflow drought in a small river situated in the Mazovian Lowlands in Poland. As hydrological streamflow drought periods become more frequent in Poland, investigations about the relationship between flow and water quality parameters can be an essential contribution to a better understanding of the impact of low flow on the status of water rivers. Data from a three-year study of a small lowland river along with significant agricultural land management was used to analyze the connection between low flows and specific water quality indicators. The separation of low-flow data from water discharge records was achieved using two criteria: Q90% (the discharge value from a flow duration curve) and a minimum low-flow duration of 10 days. During these periods, the concentration of water quality indicators was determined based on collected water samples. In total, 30 samples were gathered and examined for pH, suspended sediments, dissolved substances, hardness, ammonium, nitrates, nitrites, phosphates, total phosphorus, chloride, sulfate, calcium, magnesium, and water temperature during sampling. The study’s main aim was to describe the relation between hydrological streamflow droughts and chosen water quality parameters. The analysis results demonstrate an inverse statistically significant relationship between concentration and low-flow values for total hardness and sulfate. In contrast, there was a direct relationship between nutrient indicators, suspended sediment concentration, and river hydrological streamflow drought. Statistical tests were applied to compare the datasets between years, revealing statistical differences only for nutrient indicators. Full article

The uMlazi River receives effluents from wastewater work before feeding the Shongweni Dam. However, local communities are consuming fish from this dam for protein supplements. This study was undertaken to investigate the metal concentrations in the water and sediment, the general health of Coptodon rendalli and Oreochromis mossambicus, and metal bioaccumulation. Sampling was conducted during the dry (July–August) and wet seasons (November and December) in 2021. Water was sampled using acid-pre-treated sampling bottles, whereas sediment was collected using the Van Veen grab at the inflow, middle, and dam wall. Fish were collected, and their tissues were digested using aqua regia. Metal concentrations were measured using inductively coupled plasma optical emission spectroscopy (ICP-OES). This data manuscript reports the physical parameters of the water and concentrations of antimony, arsenic, cadmium, copper, iron, manganese, lead, selenium, and strontium in the water and sediment from the Shongweni Dam. Moreover, the fish morphometric data and metal concentrations observed in the muscle are also presented. This data could be used as baseline information on metal concentrations in the Shongweni Dam. Moreover, it provides insight into the potential impact of wastewater effluents on metal increases in freshwater bodies. Full article

This study investigates the implications of sewage contamination in the coastal and riverine environments of Hout Bay, Cape Town, South Africa. Chemical analyses were applied to quantify the presence of pollutants such as pharmaceutical and personal care products (PPCPs) in sentinel marine organisms such as mussels, as well as microbial indicators of faecal contamination in river water and seawater, for estimating the extent of impact zones in the coastal environment of Hout Bay. This research investigated the persistent pharmaceuticals found in marine outfall wastewater effluent samples in Hout Bay, examining whether these substances were also detectable in marine biota, specifically focusing on Mytilus galloprovincialis mussels. The findings reveal significant levels of sewage-related pollutants in the sampled environments, with concentrations ranging from 32.74 to 43.02 ng/g dry weight (dw) for acetaminophen, up to 384.96 ng/g for bezafibrate, and as high as 338.56 ng/g for triclosan. These results highlight persistent PPCP contamination in marine organisms, with increasing concentrations observed over time, suggesting a rise in population and pharmaceutical use. Additionally, microbial analysis revealed high levels of E. coli in the Hout Bay River, particularly near stormwater from the Imizamo Yethu settlement, with counts exceeding 8.3 million cfu/100 mL. These findings underscore the significant impact of untreated sewage on the environment. This study concludes that current sewage treatment is insufficient to mitigate pollution, urging the implementation of more effective wastewater management practices and long-term monitoring of pharmaceutical levels in marine biota to protect both the environment and public health. Full article

Rapid socio-economic development and the impact of human activities have exerted tremendous pressure on the groundwater system of the Dawen River Basin (DRB), the largest tributary in the middle and lower reaches of the Yellow River. Hydrochemical studies on the DRB have largely centered on the upstream Muwen River catchment and downstream Dongping Lake, with some focusing solely on karst groundwater. Basin-wide evaluations suggest good overall groundwater quality, but moderate to severe contamination is confined to the lower Dongping Lake area. The hydrogeologically complex mid-reach, where the Muwen and Chaiwen rivers merge, warrants specific focus. This region, adjacent to populous areas and industrial/agricultural zones, features diverse aquifer systems, necessitating a thorough analysis of its hydrochemistry and origins. This study presents an integrated hydrochemical, isotopic investigation and EWQI evaluation of groundwater quality and formation mechanisms within the multiple groundwater types of the central DRB. Central DRB groundwater has a pH of 7.5–8.2 (avg. 7.8) and TDSs at 450–2420 mg/L (avg. 1075.4 mg/L) and is mainly brackish, with Ca²⁺ as the primary cation (68.3% of total cations) and SO₄²⁻ (33.6%) and NO₃⁻ (28.4%) as key anions. The Piper diagram reveals complex hydrochemical types, primarily HCO₃·SO₄-Ca and SO₄·Cl-Ca. Isotopic analysis (δ²H, δ¹⁸O) confirms atmospheric precipitation as the principal recharge source, with pore water showing evaporative enrichment due to shallow depths. The Gibbs diagram and ion ratios demonstrate that hydrochemistry is primarily controlled by silicate and carbonate weathering (especially calcite dissolution), active cation exchange, and anthropogenic influences. EWQI assessment (avg. 156.2) indicates generally “good” overall quality but significant spatial variability. Pore water exhibits the highest exceedance rates (50% > Class III), driven by nitrate pollution from intensive vegetable cultivation in eastern areas (Xiyangzhuang–Liangzhuang) and sulfate contamination from gypsum mining (Guojialou–Nanxiyao). Karst water (26.7% > Class III) shows localized pollution belts (Huafeng–Dongzhuang) linked to coal mining and industrial discharges. Compared to basin-wide studies suggesting good quality in mid-upper reaches, this intensive mid-reach sampling identifies critical localized pollution zones within an overall low-EWQI background. The findings highlight the necessity for aquifer-specific and land-use-targeted groundwater protection strategies in this hydrogeologically complex region. Full article

In this study, a magnet-integrated fabric phase sorptive extraction (MI-FPSE) protocol was developed in combination with high pressure liquid chromatography—diode array detection (HPLC-DAD) for the simultaneous determination of five phenylurea pesticides (i.e., chlorbromuron, diuron, linuron, metoxuron, monuron) in environmental water samples. To produce the MI-FPSE device, two individual sol-gel coated carbowax 20 M (CW 20 M) cellulose membranes were fabricated and stitched to each other, while a magnetic rod was inserted between them to give the resulting device the ability to spin and serve as a stand-alone microextraction platform. The adsorption and desorption step of the MI-FPSE protocol was optimized to achieve high extraction efficiency and the MI-FPSE-HPLC-DAD method was validated in terms of linearity, sensitivity, selectivity, accuracy, and precision. The limits of detection (LODs) were found to be 0.3 μg L⁻¹. The relative recoveries were 85.2–110.0% for the intra-day and 87.7–103.2% for the inter-day study. The relative standard deviations were better than 13% in all cases. The green character and the practicality of the developed procedure were assessed using ComplexGAPI and Blue Analytical Grade Index metric tools, showing good method performance. Finally, the developed method was successfully used for the analysis of tap, river, and lake water samples. Full article

Background: This study aimed to (a) assess the prevalence of multidrug-resistant (MDR) Enterobacteriaceae in the waters of two rivers and wastewater treatment plants (WWTPs) in a region of Catalonia, Spain; (b) genetically characterize the MDR strains; and (c) compare extended-spectrum β-lactamase (ESBL)-producing Escherichia coli isolates from environmental and human sources. Methods: A total of 62 samples were collected from the influent and effluent of 31 WWTPs and 29 river water samples from 11 sites. Simultaneously, 382 hospitalized patients were screened for MDR Enterobacteriaceae using rectal swabs. All isolates underwent antibiotic susceptibility testing and whole-genome sequencing. Results: MDR Enterobacteriaceae were detected in 48.4% of WWTP samples, with 18.5% ESBL-producing E. coli and 1.5% (one sample) OXA-48-producing K. pneumoniae in influents, and 12.8% ESBL-producing E. coli in effluents. In river waters, 5.6% of samples contained ESBL-producing E. coli and 1.4% (1 sample) contained VIM-producing Enterobacter cloacae complex strains. Among patients, 10.2% (39/382) carried MDR Gram-negative bacilli, of which 66.7% were ESBL-producing E. coli. In aquatic ecosystems E. coli ST131 (13.3%) and ST162 (13.3%) were the most common strains, while in humans the common were E. coli ST131 (33.3%), ST69 (11.1%) and ST410 (7.4%) in humans. The most frequent environmental antibiotic resistance genes (ARG) were bla_CTX-M-15 (24%) and bla_TEM-1B (20%), while the most common ARGs were bla_TEM-1B (20.4%), bla_CTX-M15 (18.4%) and bla_CTX-M-27 (14.3%). IncF plasmids were predominant in environmental and human strains. Conclusions: ESBL-producing E. coli and carbapenemase-producing Enterobacteriaceae are present in aquatic environments in the region. Phylogenetic similarities between environmental and clinical strains suggest a possible similar origin. Further studies are necessary to clarify transmission routes and environmental impact. Full article

Many effluents from human activities discharged into freshwater ecosystems cause chemical pollution. Chemical pollution in rivers is a serious threat to freshwater ecosystems due to the associated potential human health risks. This study determined the extent of chemical pollution, identified potential sources of pollution and assessed human health risk in the Moopetsi River, an intermittent river in the Limpopo Province of South Africa. Chemical analyses were conducted on water and sediment samples collected during high-flow, low-flow and intermittent-flow regimes. The findings showed seasonal variations in the chemical pollution levels in the sediments and the highest contamination was measured during intermittent flow. The enrichment factor and geoaccumulation index values identified chromium and nickel as major contributors to sediment contamination. The mean arsenic, chromium and nickel levels exceeded the established guideline values. An evaluation of human health risk was conducted using ingestion and dermal absorption pathways. The results showed that ingestion has greater non-carcinogenic and carcinogenic risks than dermal exposure, especially for children during intermittent flow. The elements of great concern for non-carcinogenic risk were chromium, manganese and nickel and for carcinogenic risk, they were arsenic, chromium, nickel and lead. The outcome of this study is useful for waste management and conservation to reduce environmental degradation and human health risk. Full article

Plains River networks are important natural ecosystems that play a vital role in storing, draining, conserving, and purifying water. This study selected the river network in the northern plain of Jiaxing as the research area. Samples were collected in October 2023. Sediments were collected using a sampler and divided into five layers according to the collection depth, namely the surface layer (5 cm), the second layer (15 cm), the third layer (25 cm), the fourth layer (35 cm), and the bottom layer (45 cm). This study analyzed the vertical distribution of each form of phosphorus, the vertical distribution of the microbial community, and the response between the two in the sediments of this plain river network. The results showed high sediment TP concentrations (633.9–2534.7 mg/kg) in this plain river network. The vertical distribution trend of Fe-P was almost the same as that of TP and had the highest concentration (134.9–1860.1 mg/kg). Ca-P is the second highest phosphorus content, which is also an inert phosphorus component, as well as Al-P, and both exhibit a relatively low percentage of surface layers. Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria showed heterogeneity in the vertical distribution of sediments. The river network sediments in the Plains River have a high potential for phosphorus release, with most sites acting as phosphorus “sources”. The sediments in the second of these layers show a strong tendency to release phosphorus. Bottom sediments have a low capacity to both adsorb and release phosphorus. The findings of this study will provide a theoretical foundation for the prevention and management of river networks in this plain. Full article

Water quality should be tested to ensure it is acceptable for the healthy growth of plants and animals, and water hardness is one of the important testing indexes. Herein, a novel approach was proposed to achieve high accuracy and rapid quantitative analyses of water hardness by combining one-point calibration laser-induced breakdown spectroscopy (OPC–LIBS) and aerosolization. First, the water samples are aerosolized via the aerosol generation device and the LIBS spectra of aerosols are obtained. Then, a modified OPC–LIBS model is used to determine the elemental contents of the aerosols via LIBS spectra, in which the plasma temperature is calculated using the Multi-Element Saha–Boltzmann (ME–SB) plot. One suitable standard liquid sample (the concentrations of Ca, Mg, and Sr were 50 mg/L, 50 mg/L, and 500 mg/L, respectively) was selected to evaluate the quantitative performance of the modified OPC–LIBS. Then, the Ca and Mg concentrations in the three real water samples (from the Yangtze River, reservoir, and underground) were detected and quantified by the proposed method, and the quantitative results of three LIBS calibration methods were compared with that of inductively coupled plasma optical emission spectroscopy (ICP–OES). The average relative error of Ca and Mg found in the OPC–LIBS results was lower by 22.23% than the internal standard method and 14.50% lower than the external standard method. The method combining modified OPC–LIBS and aerosolization can achieve high-precision rapid quantification of water hardness detection, which provides a new path for rapid detection of water hardness and is expected to make online detection a reality in the water quality testing field. Full article

Pesticide exposure gradients between occupational, para-occupational, and general populations remain poorly characterized in North African agricultural contexts. This study evaluates urinary pesticide levels among farmers, indirectly exposed individuals, and a control group in Morocco’s Fez-Meknes region. A cross-sectional survey measured pesticide concentrations using LC-MS/MS in urine samples collected from 154 adults residing in both rural and urban areas. A questionnaire was used to gather information from participants regarding factors that may elevate the risk of pesticide exposure. The results revealed that farmers exhibited the highest concentrations of pesticides in their urine, including compounds classified as Ia/Ib by the World Health Organization. Indirectly exposed individuals showed moderate levels of contamination, with notable detections such as dichlofluanid (22.13 µg/L), while the control group had residual traces of neonicotinoids, notably imidacloprid (2.05 µg/L). Multivariate analyses revealed several sociodemographic factors significantly associated with increased pesticide exposure. The main risk factors identified included low education, residence in an agricultural area, and the consumption of untreated water (wells/rivers). Conversely, wearing personal protective equipment was associated with reduced urinary concentrations. This study highlights intense occupational exposure among farmers, secondary environmental contamination among residents living near treated areas, and the widespread dispersion of pesticide residues into urban areas. Full article

Aquatic plants, as sedentary lifestyle organisms that accumulate chemical substances from their surroundings, can serve as valuable indicators of long-term anthropogenic pressure. In Poland, water monitoring is limited both spatially and temporally, which hampers a comprehensive assessment of water quality. Since the implementation of the Water Framework Directive (WFD), biotic elements, including macrophytes, have played an increasingly important role in water monitoring. Moreover, running waters, due to their dynamic nature, are susceptible to episodic pollution inputs that may be difficult to detect during isolated, point-in-time sampling campaigns. The analysis of stable carbon (δ¹³C) and nitrogen (δ¹⁵N) isotope signatures in macrophytes enables the identification of elemental sources, including potential pollutants. Research conducted between 2008 and 2011 encompassed 38 sites along 15 rivers and 108 sites across 21 lakes in northern Poland. This study focused on the isotope signatures of three pondweed species: Stuckenia pectinata, Potamogeton perfoliatus, and Potamogeton crispus. The results revealed statistically significant differences in the δ¹³C and δ¹⁵N values of plant organic matter between river and lake environments. Higher δ¹⁵N values were observed in rivers, whereas higher δ¹³C values were recorded in lakes. Spearman correlation analysis showed a negative relationship between δ¹³C and δ¹⁵N, as well as correlations between δ¹⁵N and the concentrations of Ca²⁺ and HCO₃⁻. A positive correlation was also found between δ¹³C and dissolved oxygen levels. These findings confirm the utility of δ¹³C and, in particular, δ¹⁵N as indicators of anthropogenic eutrophication, including potentially domestic sewage input and its impact on aquatic ecosystems. Full article