Improving groundwater vulnerability assessment in structurally controlled hard rock aquifer: insight from lineament density and land use/land cover pattern.

A comprehensive seasonal assessment of groundwater vulnerability was conducted in the weathered hard rock aquifer of the upper Swarnrekha watershed in Ranchi district, India. Lineament density (Ld) and land use/land cover (LULC) were integrated into the conventional DRASTIC and Pesticide DRASTIC (P-DRASTIC) models and were extensively compared with six modified models, viz. DRASTIC-Ld, DRASTIC-Lu, DRASTIC-LdLu, P-DRASTIC-Ld, P-DRASTIC-Lu, and P-DRASTIC-LdLu, to identify the most optimal model for vulnerability mapping in hard rock terrain of the region. Findings were geochemically validated using NO3- concentrations of 68 wells during pre-monsoon (Pre-M) and post-monsoon (Post-M) 2022. Irrespective of the applied model, groundwater vulnerability shows significant seasonal variation, with > 45% of the region classified as high to very high vulnerability in the pre-M, increasing to Ì´67% in post-M season, highlighting the importance of seasonal vulnerability assessments. Agriculture and industries' dominant southern region showed higher vulnerability, followed by regions with high Ld and thin weathered zone. Incorporating Ld and LULC parameters into DRASTIC-LdLu and P-DRASTIC-LdLu models increases the 'Very High' vulnerability zones to 17.4% and 17.6% for pre-M and 29.4% and 27.9% for post-M, respectively. Similarly, 'High' vulnerable zones increase from 32.5% and 25% in pre-M to 33.8% and 35.3% in post-M for respective models. Model output comparisons suggest that modified DRASTIC-LdLu and P-DRASTIC-LdLu perform better, with accurate estimations of 83.8% and 89.7% for pre-M and post-M, respectively. However, results of geochemical validation suggest that among all the applied modified models, DRASTIC-LdLu performs best, with accurate estimations of 34.4% and 20.6% for pre-M and post-M, respectively.

Water quality dynamics and underlying controls in the Halton Region, Ontario.

We assessed the hydrochemistry of 15 watersheds in the Halton Region, southern Ontario, in high resolution (n > 500 samples across n > 40 streams) to characterize water quality dynamics and governing controls on major and trace element concentrations in this rapidly urbanizing region. In 2022, major water quality parameters were generally in line with historic monitoring data yet significantly different across catchments, e.g., in specific conductance, turbidity, phosphate and chloride, and trace element concentrations. Distinct hydrochemical signatures were observed between urban and rural creeks, with urban stream sections and sites near the river mouths close to Lake Ontario having consistently higher chloride (up to 700 mg/L) and occasional enrichment in nutrients levels (up to 8 and 20 mg/L phosphate and nitrate, respectively). Particularly upper reaches exhibited hydrochemical signatures that were reflective of the catchment surface lithologies, for instance through higher dissolved Ca to Mg ratios. Unlike for chloride and phosphate, provincial water quality guidelines for trace elements and heavy metals were seldom surpassed (on < 10 occasions for copper, zinc, cadmium, and uranium). Concentrations of other trace elements (e.g., platinum group elements or rare earth elements) were expectedly low (< 0.3 µg/L) but showed spatiotemporal concentration patterns and concentration-discharge dynamics different from those of the major water quality parameters. Our results help improve the understanding of surface water conditions within Halton's regional Natural Heritage Systems and demonstrate how enhanced environmental monitoring can deliver actionable information for watershed decision-making.

Seasonal variation, spatial distribution and risk assessment of microplastics in surface waters of Periyar River, Kerala, India.

Microplastics, an emerging contaminant, are widespread in oceans around the world, and rivers are the key conveyors of these pollutants into the oceans. There exists a dearth of available data pertaining to seasonal fluctuation, spatial distribution and risk assessment of microplastics in rivers extending from upper reaches to the lower reaches. The collection of such data is of utmost importance for the purpose of formulating beneficial management strategies for riverine microplastics. In order to bridge this research gap, an investigation was made in the Periyar River in Kerala, India, which is exposed to anthropogenic stress and is at risk of microplastic pollution. A total of eighteen sites (six sites each from downstream, midstream and upstream) along the 244 km of the river were investigated across three seasons in a year. The study revealed a discernible pattern in the spatial distribution of microplastic concentrations, wherein there was a rise in abundance from the upstream to midstream and then a sudden increase of abundance along the downstream regions towards the lower reaches. The highest mean microplastic abundance of 124.95 items/L was obtained during the monsoon season followed by post-monsoon season i.e. 123.21 items/L and pre-monsoon i.e. 120.50 items/L. The predominant forms of microplastics were found to be fibres, fragments and filaments. Most prevalent polymer types acquired were polyethylene (PE) and polypropylene (PP). Pollution hazard index (PHI) and pollution load index (PLI) were also evaluated to assess the water quality of this river. The findings of this study conclude that the Periyar River is polluted with microplastics throughout its course and offer significant insights into the detection of microplastic origins in river systems and lend support to the implementation of potential measures aimed at mitigating their impact.

[Occurrence and Risk Assessment of N-nitrosamines and Their Precursors in Qingjiang River Basin].

N-nitrosamines are a type of nitrogen-containing organic pollutant with high carcinogenicity and mutagenicity. In the main drinking water sources of small and medium-sized towns in China, the contamination levels of N-nitrosamines remain unclear. In addition, there is still lack of research on the concentration of N-nitrosamines and their precursors in tributary rivers. In this study, eight N-nitrosamines and their formation potentials （FPs） were investigated in the Qingjiang River, which is a primary tributary of the Yangtze River. The sewage discharge sites were also monitored, and the environmental influencing factors, carcinogenic and ecological risks caused by N-nitrosamines, and their precursors were evaluated. The results showed that six N-nitrosamines were detected in water samples of the Qingjiang River, among which NDMA [（10 ±15） ng·L-1], NDEA [（9.3 ±9.3） ng·L-1], and NDBA [（14 ±7.8） ng·L-1] were the dominant N-nitrosamines, whereas seven N-nitrosamines were detected in chloraminated water samples, among which NDMA-FP [（46 ±21） ng·L-1], NDEA-FP [（26 ±8.3） ng·L-1], and NDBA-FP [（22 ±13） ng·L-1] were the dominant N-nitrosamine FPs. The concentrations of N-nitrosamines in the middle reaches of the Qingjiang River were higher than those in the upper and lower reaches. Furthermore, the concentrations of N-nitrosamines in the sample sites of sewage discharge and tributaries were significantly higher than those in other sampling sites. The monitoring results at the direct sewage discharge points indicated that the main source of N-nitrosamines in river water was the sewage carrying N-nitrosamines and their precursors. In addition, the concentrations of the three dominant N-nitrosamines including NDMA, NDBA, and NDEA were positively correlated with each other, mainly because of their similar sewage sources. The average carcinogenic risk to residents due to N-nitrosamine in drinking water sources was 2.4×10-5, indicating a potential carcinogenic risk. Moreover, due to the high concentrations of N-nitrosamine formation potentials in the Qingjiang River, the carcinogenic risk of drinking water may be even higher. The ecological risk assessment showed that the ecological risk quotient values of N-nitrosamines in the Qingjiang River watershed were lower than 0.002, which was negligible.

Evaluating the surface water pollution risk of mineral resource exploitation via an improved approach: a case study in Liaoning Province, Northeastern China.

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.

Occurrence of pharmaceuticals in Latin America: case study on hazard assessment and prioritization in Costa Rica.

Pharmaceuticals are considered as contaminants of emerging concern, and their occurrence in diverse environmental matrices has been described during the last 25 years. Nonetheless, pharmaceutical occurrence has not been evenly described worldwide, and reports from some geographical areas such as most parts of Latin America are scarce. This work aims to address the situation of water pollution due to pharmaceuticals in Latin America by means of two main goals: i. First, reviewing the monitoring studies performed in Latin America on this topic (period 2009-2024), which were conducted in Brazil, Mexico, Colombia, Ecuador, Peru and Argentina, to highlight the most frequently detected compounds from each therapeutic group in the region. ii. Second, analyzing the case of Costa Rica through the hazard assessment and prioritization of pharmaceuticals based on the monitoring performed in this country (years 2011; 2018-2019). The monitoring in Costa Rica comprised a total of 163 sampling points: wastewater treatment plants (WWTPs) (14 urban WWTPs plus two landfill WWTPs; total samples n = 44 influents and n = 34 effluents), nine hospital effluents (n = 32), wastewater from livestock farms (six swine farms and seven dairy farms; n = 23 influents and n = 37 effluents), 64 continental surface water sampling points (n = 137), and 61 coastal seawater sampling points (n = 61). Risk assessment of detected concentrations by the hazard quotient (HQ) approach (period 2018-2019) revealed a total of 25 medium or high-hazard compounds (out of 37 detected compounds). The prioritization approach (which included the Frequency of Appearance (FoA), the Frequency of PNEC exceedance (FoE), and the Extent of predicted no-effect concentration (PNEC) exceedance (EoE)), showed a critical list of nine pharmaceuticals: caffeine, diphenhydramine, acetaminophen, lovastatin, gemfibrozil, ciprofloxacin, ibuprofen, doxycycline and norfloxacin. These compounds should be taken into account as a first concern during the implementation of environmental policies related to pharmaceutical products in the region.

Spatio-temporal variation in water quality due to the anthropogenic impact in Rudrasagar Lake, a Ramsar site in India.

Rudrasagar Lake, a vital habitat for diverse flora and fauna, supports over 2000 households to sustain their daily livelihoods. The current study attempts to examine the impact of human activities on spatio-temporal variation in the water quality of the study area. The study integrates extensive field surveys, sample processing, and statistical analysis to assess the recent status of wetland health. Latin Square Matrix (LSM) was employed to select the sampling sites while the Inverse Distance Weighting (IDW) interpolation technique was used for spatial variation mapping. Modified Weighted Arithmetic Water Quality Index (MWAWQI) and Comprehensive Pollution Index (CPI) were utilized for assessing seasonal variation water quality and pollution loads, respectively. The results showed that dissolved oxygen (DO) was strongly influenced by the tributaries, and recreational activities have substantially influenced the highest concentrations of biochemical oxygen demand (BOD), and total suspended solids (TSS). The central portion of the lake is particularly susceptible to pollution from extensive fishing and recreational activities while peripheral sites are strongly influenced by agricultural run-offs, seepages from brick industries, and municipal wastes characterized by high concentrations of pH, total hardness (TH), oxidation-reduction potential (ORP). The findings reveal remarkable spatio-temporal fluctuations and highlight the areas within the lake susceptible to anthropogenic activities. The study proposed a sustainable management model to ameliorate anthropogenic threats. Moreover, the study contributes to the scientific understanding of the challenges and ensures the long-term viability of wetland health as a vital ecological and socio-economic resource.

Microplastics in urban water systems, Tehran Metropolitan, Iran.

Urban water systems are potential sources of secondary microplastics (MPs) as well as a distributor of MPs in the environment. In the present study, the presence of MPs in the urban water systems of the Tehran Metropolitan (Capital of Iran) was investigated. In addition, the probable relationship of MPs with different land uses (i.e., residential-commercial, forest, military, and highway) was assessed. The results showed that all parts of Tehran's urban water system in the study area were contaminated with MPs (107.1 ± 39, 37.8 ± 10.5, 48.3 ± 3.1, 46.9 ± 5.6, 59.4 ± 26.5, 1.7, 2.0 ± 0.6, 7.9 ± 1, 1.8 ± 0.2 particles/liter at the residential, integrated, military, forest, highway runoffs, drinking water, groundwater, seasonal river, and the effluent of the wastewater treatment plants; respectively). However, significant differences were found between different land uses. As expected, the residential runoff had the highest rate of MPs pollution, with 107.1 ± 39 particles/liter. According to the obtained results and our estimation, more than five million MPs/day can enter into the water bodies and soil of the study area through the wastewater treatment plants. While there are significant differences in MPs in the different land uses, our findings suggest that residential areas and highways need further attention in controlling the spread of MPs in urban areas.

Assessment of the surface water quality and primary health risk in urban wastewater and its receiving river Kathajodi, Cuttack of eastern India.

Kathajodi, the principal southern distributary of the Mahanadi River, is the vital source of irrigation and domestic water use for densely populated Cuttack city which receives anthropogenic wastes abundantly. This study assesses the contamination level and primary health status of urban wastewater, and its receiving river Kathajodi based on the physicochemical quality indices employing inductively coupled plasma mass spectroscopy and aligning with guidelines from the United States Environmental Protection Agency (USEPA) and WHO. The high WQI, HPI, and HEI in the catchment area (KJ2, KJ3, and KJ4) indicate poor water quality due to the influx of domestic waste through the primary drainage system and effluents of healthcare units. A high BOD (4.33-19.66 mg L-1) in the catchment indicates high organic matter, animal waste, bacteriological contamination, and low DO, resulting in deterioration of water quality. CR values beyond limits (1.00E - 06 to 1.00E - 04) in three locations of catchment due to higher Cd, Pb, and As indicate significant carcinogenic risk, while high Mn, Cu, and Al content is responsible for several non-carcinogenic ailments and arsenic-induced physiological disorders. The elevated heavy metals Cd, Cu, Fe, Mn, Ni, and Zn, in Kathajodi, could be due to heavy coal combustion, vehicle exhaust, and industrial waste. On the other hand, Cu, Fe, K, and Al could be from agricultural practices, weathered rocks, and crustal materials. Positive significant (p ≤ 0.05) Pearson correlations between physicochemical parameters indicate their common anthropogenic origin and similar chemical characteristics. A strong correlation of PCA between elements and physiological parameters indicates their role in water quality deterioration. Assessing the surface water quality and heavy metal contents from this study will offer critical data to policymakers for monitoring and managing public health concerns.

A case study of using artificial neural networks to predict heavy metal pollution in Lake Iznik.

Artificial neural networks offer a viable route in assessing and understanding the presence and concentration of heavy metals that can cause dangerous complications in the wider context of water quality prediction for the sustainability of the ecosystem. In order to estimate the heavy metal concentrations in Iznik Lake, which is an important water source for the surrounding communities, characterization data were taken from five different water sources flowing into the lake between 2015 and 2021. These characterization results were evaluated with IBM SPSS Statistics 23 software, with the addition of the lake water quality system. For this purpose, seven distinct physicochemical parameters were measured and monitored in Karasu, Kirandere, Olukdere and Sölöz water sources flowing into the lake, to serve as input data. Concentration levels of 15 distinct heavy metals in Karsak Stream originating from the lake were as the output. Specifically, Sn for Karasu (0.999), Sb for Kirandere (1.000), Cr for Olukdere (1.000) and Pb and Se for Sölöz (0.995) indicate parameter estimation R2 coefficients close to 1.000. Sn stands out as the common heavy metal parameter with best estimation prospects. Given the importance of the independent variable in estimating heavy metal pollution, conductivity, COD, COD and temperature stood out as the most effective parameters for Karasu, Olukdere, Kirandere and Sölöz, respectively. The ANN model emerges as a good prediction tool that can be used effectively in determining the heavy metal pollution in the lake as part of the efforts to protect the water budget of Lake Iznik and to eliminate the existing pollution.

Pollution, spatial distribution, and health risks assessment of nutrient concentration in surface water resources of Maroon-Jarahi Basin in southwestern Iran.

Nowadays, the introduction of nutrients caused by human activities is considered an environmental issue and a significant problem in river basins and coastal ecosystems. In this study, the concentration of nutrients ( NO 3 - and PO 4 3 - ) in the surface water sources of the Maroon-Jarahi watershed in the southwest of Iran was determined, and the pollution status and health risk assessment were done. The average concentration of nitrate and phosphate in Ludab, Maroon, Zard, Allah, Jarahi rivers, and Shadegan wetland were obtained at 2.25-0.59, 4.59-1.84, 4.07-2.02, 5.40-2.81, 11.51-4.67, 21.63 and 6.20 (mg/l), respectively. A comparison of the results with the World Health Organization (WHO) limit showed that nitrate was lower than in all stations, but phosphate was higher than the limit in some stations of the Maroon, Allah, Jarahi rivers, and Shadegan wetland. Calculation of linear regression analysis showed significant positive relationships between nitrate and phosphate in all surface water sources (except Ludab) and based on the N/P ratio, nitrogen was estimated as the limiting factor in phytoplankton growth (N/P < 16). The evaluation of the status of the Nutrient pollution index (NPI) was observed as: Shadegan > Jarahi > Allah > Maroon > Zard > Ludab that the Jarahi River and Shadegan wetland were in the medium pollution class (1 < NPI ≤ 3) and other waterbodies were in the non-polluted to low pollution state (NPI < 1). Calculation of the chronic daily intake (CDI) showed that water body nutrients cause more non-carcinogenic health risks through the oral route than dermal exposure, and according to HI, children's health is more at risk than adults. Findings showed that surface water resources especially downstream of the Maroon-Jarahi watershed are at eutrophication risk, and to control the nearby human activities and as a result increase the nutrients in these water resources, measures should be taken.

Microplastic Pollution in High Population Density Zones of Selected Rivers from Southeast Asia.

Southeast Asia (SEA) faces significant environmental challenges due to rapid population growth and economic activity. Rivers in the region are major sources of plastic waste in oceans. Concerns about their contribution have grown, but knowledge of microplastics in the area is still limited. This article compares microplastic levels in sediment and water from urban zones of three major rivers in SEA: Chao Phraya River (Thailand), Saigon River (Vietnam), and Citarum River (Indonesia). The study reveals that in all three rivers, microplastics were found, with the highest concentrations in Chao Phraya's water (80 ± 60 items/m3) and Saigon's sediment (9167 ± 4559 items/kg). The variations in microplastic sizes and concentrations among these rivers may be attributed to environmental factors and the exposure duration of plastic to the environment. Since these rivers are important water supply sources, rigorous land-use regulations and raising public awareness are crucial to mitigate plastic and microplastic pollution.

Distribution and bioaccumulation of trace elements in two Cyprinidae fish species in the Indus river, Pakistan, including the impact of hydraulic structure on macroinvertebrates' biodiversity.

The concentration of trace elements (chromium, lead, zinc, copper, manganese, and iron) was determined in water, sediment and tissues of two Cyprinidae fish species - Labeo rohita and Tor putitora - collected from the eight sampling stations of Indus River in 2022 for four successive seasons (autumn, winter, spring, summer), and also study the present condition of macroinvertebrates after the construction of hydraulic structure. The obtained results of trace element concentrations in the Indus River were higher than the acceptable drinking water standards by WHO. The nitrate concentration ranges from 5.2 to 59.6 mg l-1, turbidity ranges from 3.00 to 63.9 NTU, total suspended solids and ammonium ions are below the detection limit (<0.05). In the liver, highest dry wt trace elements (µg/g) such as Cr (4.32), Pb (7.07), Zn (58.26), Cu (8.38), Mn (50.27), and Fe (83.9) for the Labeo rohita; and Tor Putitora has significantly greater accumulated concentration (Cr, Pb, Zn, Cu, Mn, Fe) in muscle and liver than did Labeo rohita species. Additionally, lower number of macroinvertebrates were recorded during the monsoonal season than pre-monsoon and post-monsoon. Local communities surrounded by polluted environments are more probably to consume more fish and expose them to higher concentrations of toxic trace elements (lead and copper). The findings also provide a basis for broader ecological management of the Indus River, which significantly influenced human beings and socioeconomic disasters, particularly in the local community.

Contrast Media-driven Anthropogenic Gadolinium: Knowns and Unknowns.

Gadolinium-based contrast agents (GBCAs) have augmented the capabilities of MRI, which has led to their widespread and increasing use in radiology practice. GBCAs are introduced into the environment through disposal of unused product and elimination after intravenous injection, both primarily via liquid dispersion into the environment. This human introduction of gadolinium into the environment, referred to as anthropogenic gadolinium, is associated with the detection of gadolinium in water systems, raising concerns for potential adverse impact and prompting certain mitigation actions. This article summarizes the existing knowledge and problem scope, conveys the relevant underlying chemical principles of chelate dissociation, and offers an inferred perspective that the magnitude of the problem is most unlikely to cause human harm. The merits and limitations regarding possible mitigation tactics, such as collecting urine after GBCA administration, use of lower-dose high-relaxivity macrocyclic GBCAs, and the option for virtual contrast-enhanced examinations, will be discussed. Finally, the potential for monitoring gadolinium uptake in bone will be presented, and recommendations for future research will be offered. © RSNA, 2024 See also the article by Ibrahim et al in this issue. See also the article by McKee et al in this issue.

Ecological river health assessments, based on fish ordination analysis of ecological indicator entities and the biological integrity metrics, responding to the chemical water pollution.

Evaluation of the ecological health of rivers requires a focused examination of how biological indicators respond to chemical stressors to offer key insights for effective conservation strategies. We examined the influence of stressors on aquatic ecosystems by analyzing various ecological entities and biotic integrity metrics of fish communities. A nonmetric multidimensional scaling (NMDS) approach was applied to determine scores based on 19 fish ecological entities (FEs) and a fish-based multi-metric index of biotic integrity (mIBI-F). The composition of fish communities in reference clusters differed from the disturbed clusters due to instream chemical stressors. These chemical stressors, including high levels of nutrients, organic matter, and ionic/suspended solids, were linked to variation in the key indicator FEs, whose guild identities were closely associated with instream chemical degradation. The scores of FEs (abundance weighted) and mIBI-F metrics in the first NMDS axis (NMDS1) were significantly linked with chemical health indicators (p < 0.001), such as total phosphorus (R2 = 0.67 and 0.47), electrical conductivity (R2 = 0.59 and 0.49), and chlorophyll-a (R2 = 0.48 and 0.25). These NMDS1 scores showed better accuracy than the conventional mIBI-F score in capturing river ecological health linked with chemical health status as determined by a multi-metric index of water pollution. Our study suggests that based on the ordination approach, the biological integrity of these systems reflected the chemical health.

Monitoring different sources of marine pollution in the Canarian intertidal zone using Anemonia sulcata as a bioindicator.

Sea anemones have often been used as bioindicators of contamination because they are semisessile organisms that rarelly leave their niche, which is why they are conducive to affecting the ecosystem at the local level. The objective of this work is to determine whether the concentrations of heavy metals and trace elements in the anemone Anemonia sulcata vary depending on the source of contamination present. In 2021 seventy specimens were collected at five sampling points and fourteen specimens were collected in each point (Control Zone, Thermal Power Plant, Sewage Pipe, Harbour and Tourism) in 2021, on the island of Tenerife. All the areas studied characterized by a pollution condition had higher concentrations of metals and trace elements than the control area. The anemones from Harbour presented a greater number of metals with a higher concentration than the other study areas.

Assessment of the water quality and toxicity effects on zebrafish (Danio rerio) of a stream near a phosphorus chemical plant in Guizhou Province, southwestern China.

To reveal the influence of the phosphorus chemical industry (PCI) on regional water environmental quality and safety, the water quality and ecotoxicological effects of a stream near a phosphorus chemical plant (PCP) in Guizhou Province, southwestern China, were investigated based on water samples collected from the stream. The results showed that the average concentrations of NH3-N, TN, P, F-, Hg, Mn, and Ni were 3.14 mg/L, 30.09 mg/L, 3.34 mg/L, 1.18 mg/L, 1.06 µg/L, 45.82 µg/L, and 11.30 µg/L, respectively. The overall water quality of the stream was in the heavily polluted category, and NH3-N, TN, P, F-, and Hg were the main pollution factors. The degree of pollution was in the order of rainy period > transitional period > dry period, and the most polluted sample site was 1100 m from the PCP. After 28 days of exposure to stream water, there was no significant change in the growth parameters of zebrafish. The gills of zebrafish showed a small amount of epithelial cell detachment and a small amount of inflammatory cell infiltration, and the liver tissue displayed a large amount of hepatocyte degeneration with loose and lightly stained cytoplasm. Compared with the control group, the %DNA in tail, tail length, tail moment, and olive tail moment were significantly increased (p < 0.05), indicating that the water sample caused DNA damage in the peripheral blood erythrocytes of zebrafish. The stream water in the PCI area was found to be polluted and exhibited significant toxicity to zebrafish, which could pose a threat to regional ecological security.

Screening of priority antibiotics in Chinese seawater based on the persistence, bioaccumulation, toxicity and resistance.

Antibiotics are emerging pollutants that have detrimental effects on both target and non-target organisms in the environment. However, current methods for environmental risk assessment primarily focus on the risk to non-target organisms in ecosystems, overlooking a crucial risk of antibiotics - the induction of resistance in targeted bacteria. To address this oversight, we have incorporated resistance (R) risk with persistence, bioaccumulation and toxicity (PBT) to establish a more comprehensive PBTR (persistence, bioaccumulation, toxicity, and resistance) framework for antibiotic-specific risk assessment. Using the PBTR framework, we evaluated 74 antibiotics detected in Chinese seawater from 2000 to 2021, and identified priority antibiotics. Our analysis revealed that the priority antibiotics with R risk accounted for the largest proportion (50% to 70%), followed by P risk (40% to 58%), T risk (16% to 35%) and B risk (0 to 13%). To further categorize these priority antibiotics, we assigned them a risk level according to their fulfillment of criteria related to P, B, T, and R. Antibiotics meeting all four indicators were classified as Grade I, representing the highest risk level. Grade II and Grade III were assigned to antibiotics meeting three or two indicators, respectively. Antibiotics meeting only one indicator were classified as Grade IV, representing the lowest risk level. The majority of priority antibiotics fell into Grade IV, indicating low risk (55% to 79%), followed by Grade III (16% to 45%). The highest risk antibiotic identified in this study was clindamycin (CLIN), categorized as Grade II, in the East China Sea. Our findings aligned with previous studies for 25 antibiotics, affirming the validity of the PBTR framework. Moreover, we identified 13 new priority antibiotics, highlighting the advancement of this approach. This study provides a feasible screening strategy and monitoring recommendations for priority antibiotics in Chinese seawater.

Pharmaceutical-contaminated irrigation water: implications for ornamental plant production and phytoremediation using enrofloxacin-accumulating species.

Enrofloxacin (Enro) has been widely encountered in natural water sources, and that water is often used for irrigation in crop production systems. Due to its phytotoxicity and accumulation in plant tissues, the presence of Enro in water used for crop irrigation may represent economical and toxicological concerns. Here, we irrigated two ornamental plant species (Zantedeschia rehmannii Engl. and Spathiphyllum wallisii Regel.) with water artificially contaminated with the antimicrobial enrofloxacin (Enro; 0, 5, 10, 100, and 1000 µg L-1) to evaluate its effects on ornamental plant production, as well as its accumulation and distribution among different plant organs (roots, leaves, bulbs, and flower stems), and examined the economic and environmental safety of commercializing plants produced under conditions of pharmaceutical contamination. The presence of Enro in irrigation water was not found to disrupt plant growth (biomass) or flower production. Both species accumulated Enro, with its internal concentrations distributed as the following: roots > leaves > bulbs > flower stems. In addition to plant tolerance, the content of Enro in plant organs indicated that both Z. rehmannii and S. wallisii could be safety produced under Enro-contaminated conditions and would not significantly contribute to contaminant transfer. The high capacity of those plants to accumulate Enro in their tissues, associated with their tolerance to it, indicates them for use in Enro-phytoremediation programs.

Count-Based Morgan Fingerprint: A More Efficient and Interpretable Molecular Representation in Developing Machine Learning-Based Predictive Regression Models for Water Contaminants' Activities and Properties.

In this study, we introduce the count-based Morgan fingerprint (C-MF) to represent chemical structures of contaminants and develop machine learning (ML)-based predictive models for their activities and properties. Compared with the binary Morgan fingerprint (B-MF), C-MF not only qualifies the presence or absence of an atom group but also quantifies its counts in a molecule. We employ six different ML algorithms (ridge regression, SVM, KNN, RF, XGBoost, and CatBoost) to develop models on 10 contaminant-related data sets based on C-MF and B-MF to compare them in terms of the model's predictive performance, interpretation, and applicability domain (AD). Our results show that C-MF outperforms B-MF in nine of 10 data sets in terms of model predictive performance. The advantage of C-MF over B-MF is dependent on the ML algorithm, and the performance enhancements are proportional to the difference in the chemical diversity of data sets calculated by B-MF and C-MF. Model interpretation results show that the C-MF-based model can elucidate the effect of atom group counts on the target and have a wider range of SHAP values. AD analysis shows that C-MF-based models have an AD similar to that of B-MF-based ones. Finally, we developed a "ContaminaNET" platform to deploy these C-MF-based models for free use.