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Heavy metal(loid) (HM) pollution in agricultural soils has become an environmental concern in antimony (Sb) mining areas. However, priority pollution sources identification and deep understanding of environmental risks of HMs face great challenges due to multiple and complex pollution sources coexist. Herein, an integrated approach was conducted to distinguish pollution sources and assess human health risk (HHR) and ecological risk (ER) in a typical Sb mining watershed in Southern China. This approach combines absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models with ER and HHR assessments. Four pollution sources were distinguished for both models, and APCS-MLR model was more accurate and plausible. Predominant HM concentration source was natural source (39.1%), followed by industrial and agricultural activities (23.0%), unknown sources (21.5%) and Sb mining and smelting activities (16.4%). Although natural source contributed the most to HM concentrations, it did not pose a significant ER. Industrial and agricultural activities predominantly contributed to ER, and attention should be paid to Cd and Sb. Sb mining and smelting activities were primary anthropogenic sources of HHR, particularly Sb and As contaminations. Considering ER and HHR assessments, Sb mining and smelting, and industrial and agricultural activities are critical sources, causing serious ecological and health threats. This study showed the advantages of multiple receptor model application in obtaining reliable source identification and providing better source-oriented risk assessments. HM pollution management, such as regulating mining and smelting and implementing soil remediation in polluted agricultural soils, is strongly recommended for protecting ecosystems and humans.

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The study aimed to evaluate trace metals in the groundwater of Chattogram City located on the southeastern coast of Bangladesh and assess their potential health risks. Given the city's unique characteristics as both a coastal and industrial hub in Bangladesh, a knowledge gap persists particularly in the assessment of trace metals. A random sampling technique was applied to collect one hundred and seventeen groundwater samples from different wards of the city to analyze some trace metals (Cr, Cd, Fe, Cu, Mn, Pb, and Zn) and the quality of the collected water samples was evaluated using different indices, such as Heavy Metal Evaluation Index (HEI), Groundwater Quality Index (GWQI), Heavy Metal Pollution Index (HPI), and Degree of Contamination (Cd). The average concentration of all the studied metals except Fe, Mn, and Cd satisfied the Bangladesh drinking water standards. The Fe, Mn, and Cd content were observed higher in shallow wells (depth 10-150 ft) followed by intermediate (151-300 ft) and deep wells (>300 ft). However, the Cr, Cu, and Zn content did not significantly change with aquifer depth. The spatial distribution map showed that the highest values of Mn and Cu were observed in the west-northern region of the city. Metal As was only found in shallow and intermediate aquifers. The HEI suggested that about 9 % of samples fall into the higher degree of pollution category similar to the GWQI, while 37 % and 42 % of samples exhibited a higher degree of pollution in the case of HPI and Cd, respectively. The positive correlations and loadings found in the statistical analysis indicated that Fe, Mn, and Cu originated from the same sources. A variety of industrial activities might be ascribed to this type of pollution. However, an average Hazard Quotient (HQ) through ingestion was found to be greater than 1 for Cd, and the Carcinogenic Risk (CR) values for children were identified as two-fold higher than that of adults. Raising social awareness, avoiding the usage of groundwater without proper treatment, and strict regulations and monitoring by the concerned authority are recommended in the study.

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The worldwide contamination of aquatic ecosystems by plastics is raising concern, including their potential impacts on the base of the food chain, which has been poorly documented. This study sought to examine, for the first time, the presence of nanoplastics (NPs) in biofilms from freshwater streams/rivers. They were collected at selected polluted sites, such as the industrial sector for plastic recycling and production, miscellaneous industries, agriculture, municipal wastewaters/effluents and road runoffs. In parallel, the functional properties of sampled biofilms were determined by proteins, lipids, esterase (lipase), viscosity and oxidative stress. The results revealed that biofilms collected at the plastic industries and road runoffs contained the highest NP levels based on size exclusion chromatography, fluorescence detection and a new nanogold sensor visualization method. Examination of the chromatographic elution profiles showed increased abundance and size of NPs in the 10-150 nm size range at the polluted sites. Biofilms from the plastic industry site had elevated levels of aldehydes (oxidative stress) and lipids compared to the other sites. Biofilms collected at the municipal sites had elevated levels of proteins and esterases/lipases, with a decrease in total lipids. Biofilms collected at agriculture sites had the lowest levels of NPs in this campaign, but more samples would be needed to confirm these trends. In conclusion, biofilms represent an important sink for plastics in freshwater environments and display signs of distress upon oxidative stress.

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It is challenging to interpret hydrogeochemical datasets with complex natural and anthropogenic genesis in intensive industrial areas. This paper elucidates the hydrogeochemical characteristics and pollution sources of groundwater in an industrial park, East China, combining the self-organizing map (SOM), hydrochemical graphs, and correlation analysis. The results show that the total dissolved solids of groundwater range from 73.45 to 997.92 mg/L and can be regarded as freshwater. The pH varies greatly from 6.44 to 9.90, most of samples belonging to weakly acidic-weakly alkaline. The groundwater can be classified into five clusters by SOM, representing the non- or least-polluted groundwater (cluster D), high salt groundwater (cluster A), high NH4+-N and HCO3- groundwater (cluster B), high Fe and Mn groundwater (cluster C), and high pH groundwater (cluster E), which were contaminated by industrial salts, historical agriculture activity, industrial reducing substances, and industrial alkali, respectively. The natural evolution of groundwater (cluster D) in the study area is mainly controlled by mineral weathering/dissolution. The contributions of calcite, dolomite, gypsum, halite, and silicate mineral to groundwater solute are 55.8-66.3%, 15.1-18.0%, 9.0-10.7%, 2.5-10.1%, and 2.3-9.4%, respectively, based on the mass conservation. The contaminated groundwaters (all other clusters except for cluster D) have different hydrochemical characteristics associated with the pollution sources. In addition, the relatively reductive environment in quaternary flu-lacustrine sediments favored the formation of high level of Fe, Mn, and NH4+-N in groundwater. This study provides a new insight into the characteristic contaminants and their distributions in groundwater and the associated pollution sources based on the large datasets in an intensive industrial area. The data evaluation methods and results of this study could be useful to the groundwater usage management and pollution control in this area and other industrial areas.

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Air pollution, originating from both natural and human-made sources, presents significant threats to human health and the environment. This review explores the latest technological advancements in air quality sensors focusing on their applications in monitoring a wide range of pollution sources from volcanic eruptions and wildfires to industrial emissions, transportation, agricultural activities and indoor air quality. The review categorizes these sources and examines the operational principles, system architectures, and effectiveness of various air quality monitoring instruments including low-cost sensors, gas analyzers, weather stations, passive sampling devices and remote sensing technologies such as satellite and LiDAR. Key insights include the rapid evolution of sensor technology driven by the need for more accurate, real-time monitoring solutions that are both cost-effective and widely accessible. Despite significant advancements, challenges such as sensor calibration, standardization, and data integration remain critical for ensuring reliable air quality assessments. The manuscript concludes by emphasizing the need for continued innovation and the integration of advanced sensor technologies with regulatory frameworks to enhance environmental management and public health protection.

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The river-connected Dongting Lake (DT) and Poyang Lake (PY), and the gate-controlled Taihu Lake (TH) and Chaohu Lake (CH) are the four important lakes in the Yangtze River Basin. The comprehensive Water Quality Index (WQI), the Eutrophication Integrated Index (TLI(Σ)), and the Positive Matrix Factorization (PMF) model were employed to evaluate water quality and the contribution of pollution sources for these lakes. The results show that WQI for all lakes indicated generally good water quality, with DT scoring 73.52-86.18, the highest among them. During the wet season, the eutrophication degree of river-connected lake was medium, and that of gate-controlled lakes was high. The surface runoff and agricultural non-point sources are the main pollution sources for both types of lakes, but their impact is more pronounced in gate-controlled lakes during the wet season. The study provides evidence support for scientific understanding of water quality problems and management strategies in these areas.

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In many developed and developing nations, lakes are the primary source of drinking water. In the current scenario, due to rapid mobilization in anthropogenic activities, lakes are becoming increasingly contaminated. Such practices not only destroy lake ecosystems but also jeopardize human health through water-borne diseases. This study employs advanced hierarchical clustering through multivariate analysis to establish a novel method for concurrently identifying significantly polluted lakes and critical pollutants. A systematic approach has been devised to generate rotating component matrices, dendrograms, monoplots, and biplots by combining R-mode and Q-mode analyses. This enables the identification of contaminant sources and their grouping. A case study analyzing five lakes in Bengaluru, India, has been conducted to demonstrate the effectiveness of the proposed methodology. Additionally, one pristine lake from Jammu & Kashmir, India, has been included to validate the findings from the aforementioned five lakes. The study explored correlations among various physical, chemical, and biological characteristics such as temperature, pH, dissolved oxygen, conductivity, nitrates, biological oxygen demand (BOD), fecal coliform (FC), and total coliform (TC). Critical contaminants forming clusters included conductivity, nitrates, BOD, TC, and FC. Factor analysis identified four primary components that collectively accounted for 85% of the overall variance. Following identification of pollution hotspots, the study recommends source-based pollution control and integrated watershed management, which could significantly reduce lake pollution levels. Continuous monitoring of lake water quality is essential for identifying actual contaminant sources. These findings provide practical recommendations for maximizing restoration efforts, enforcing regulations on pollutant sources, and improving water quality conditions to ensure sustainable development of lakes.

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The safety of human health and agricultural production depends on the quality of farmland soil. Risk assessment of heavy metal pollution sources could effectively reduce the hazard of soil pollution from various sources. This study has identified and quantitatively analyzed pollution sources with geostatistical analysis and the APCS-MLR model. The potential ecological risk index was combined with the APCS-MLR model which has quantitatively calculated the source contribution. The results revealed that As, Cr, Cd, Pb, Zn, and Cu were enriched in soil. Geostatistical analysis and the APCS-MLR model have apportioned four pollution sources. The Mn and Ni were attributed to natural sources; As and Cr were from agricultural activities; Cu and Zn were originated from natural sources; Cd and Pb were derived from atmospheric deposition. Atmospheric deposition and agricultural activities were the largest contributors to ecological risk of heavy metals in soil, which accounted for 56.21% and 36.01% respectively. Atmospheric deposition and agricultural activities are classified as priority sources of pollution. The combination of source analysis receptor model and risk assessment is an effective method to quantify source contribution. This study has quantified the ecological risks of soil heavy metals from different sources, which will provide a reliable method for the identification of primary harmfulness sources of pollution for future studies.

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This study explored the levels, distribution, potential sources, ecological risks and estrogenic activities of 14 bisphenol analogues (BPs) in soil under eight land-use types in the megacity of Chengdu, China. Eleven BPs were detected in the soil samples and the total concentrations ranged from 32.3 to 570 ng/g d.w. Levels of bisphenol BP (BPBP) in the soil (up to 208 ng/g d.w.) only second to the most dominant compound bisphenol A (BPA) were found. Relatively higher Σ14BP accumulation in the soil was observed in the commercial and residential areas (median: 136 ng/g d.w. and 131 ng/g d.w.) compared with agricultural area (median: 67.5 ng/g d.w.). Source identification indicated the role of atmospheric particulate deposition and consecutive anthropogenic activities in BP emission. The ecotoxicity assessment implied that BPA, bisphenol S (BPS), bisphenol F (BPF) and bisphenol PH (BPPH) might pose low to medium risk to the ecosystem due to their extensive use and biological effects. The calculated 17ß-estradiol equivalents of BPs were in the range of 0.501-7.74 pg E2/g d.w, and the estrogenic activities were inferior to those contributed by natural estrogens in the soil.

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Risk assessment and pollutant source analysis are crucial tools for the management and protection of coastal ecosystems. The distribution patterns, risk assessment, and potential sources of heavy metals (Cd, Cr, Fe, Ni, Cu, Zn, As, Hg, and Pb) in surface sediment were analyzed in the Qiongzhou Strait, China, in summer and autumn of 2022. Heavy metals in autumn showed higher ecological risk than that in summer. Seasonal shifts in ocean currents may result in variations in heavy metal accumulation and dispersion. Cd and Hg were the priority heavy metals found, and according to the Positive Matrix Factorization results, the study area contains five sources of pollution, with natural sources, shipping-related activities, and industrial activities being the primary contributors. This study indicated that pollutants from adjacent areas should be considered for managing the environmental quality of Qiongzhou Strait.

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Given that microplastics (MPs) in groundwater have been concerned for risks to humans and ecosystems with increased publications, a Contrasting Analysis of Scales (CAS) approach is developed by this study to synthesize all existing data into a hierarchical understanding of MP accumulation in groundwater. Within the full data of 386 compiled samples, the median abundance of MPs in Open Groundwater (OG) and Closed Groundwater (CG) were 4.4 and 2.5 items/L respectively, with OG exhibiting a greater diversity of MP colors and larger particle sizes. The different pathways of MP entry (i.e., surface runoff and rock interstices) into OG and CG led to this difference. At the regional scale, median MP abundance in nature reserves and landfills were 17.5 and 13.4 items/L, respectively, all the sampling points showed high pollution load risk. MPs in agricultural areas exhibited a high coefficient of variation (716.7%), and a median abundance of 1.0 items/L. Anthropogenic activities at the regional scale are the drivers behind the differentiation in the morphological characteristics of MPs, where groundwater in residential areas with highly toxic polymers (e.g., polyvinylchloride) deserves prolonged attention. At the local scale, the transport of MPs is controlled by groundwater flow paths, with a higher abundance of MP particles downstream than upstream, and MPs with regular surfaces and lower resistance (e.g., pellets) are more likely to be transported over long distances. From the data-scaled insight this study provides on the accumulation of MPs, future research should be directed towards network-based observation for groundwater-rich regions covered with landfills, residences, and agricultural land.

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The northern plain of Henan in the lower reaches of the Yellow River is an area where the Yellow River is frequently diverted. The shallow groundwater quality in this area is poor， and many types of components have been found to be exceeding the limit value； however， the contribution of various environmental factors to water quality needs to be further quantified. In order to clarify the genesis of water quality of shallow groundwater in the study area， 330 groups of shallow groundwater samples were collected via a regional water quality survey. The evolution of shallow groundwater quality in the Yellow River diversion area of northern Henan was revealed using the principal component-absolute principal component score-multiple linear regression （PCA-APCS-MLR） model. The results showed that the components with a shallow groundwater excess rate greater than 10% in descending order were manganese， iron， total hardness， total dissolved solids， sodium， fluoride， arsenic， chloride ions， sulfate， and ammonium. In particular， the excess rate of manganese reached 76%. The four factors of dissolution enrichment， native origin of soil， redox conditions， and agricultural activities were identified as the main reasons for poor groundwater quality， which accounted for 71.24% of the cumulative interpretation rate of variance. In addition， the recharge from the surface water also influenced the groundwater quality. The effects of dissolution between the water and aquifer matrix and redox condition in the aquifer of the Yellow River dried-riverway like Xinxiang were significantly enhanced， resulting in the increasing concentration of iron， arsenic， total hardness， TDS， and other components in groundwater. Fluoride enrichment was caused by dissolution enrichment， the origin of the soil， and lateral replenishment of the Yellow River. Groundwater with high manganese concentration was widely affected by the soil matrix. Nitrate pollution of the groundwater was caused by the extensive use of chemical fertilizers in agricultural activities in individual areas.

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Antibiotic resistance is one of the most concerned global health issues. However, comprehensive profiles of antibiotic resistance genes (ARGs) in various environmental settings are still needed to address modern antibiotic resistome. Here, Arctic soils and representative contaminated samples from ARG pollution sources were analyzed using metagenomic approaches. The diversity and abundance of ARGs in Arctic soils were significantly lower than those in contaminated samples (p < 0.01). ARG profiles in Arctic soils were featured with the dominance of vanF, ceoB, and bacA related to multidrug and bacitracin, whereas those from ARG pollution sources were characterized by prevalent resistance to anthropogenic antibiotics such as sulfonamides, tetracyclines, and beta-lactams. Mobile genetic elements (MGEs) were found in all samples, and their abundance and relatedness to ARGs were both lower in Arctic soils than in polluted samples. Significant relationships between bacterial communities and ARGs were observed (p < 0.01). Cultural bacteria in Arctic soils had clinically-concerned resistance to erythromycin, vancomycin, ampicillin, etc., but ARGs relevant to those antibiotics were undetectable in their genomes. Our results suggested that Arctic environment could be an important reservoir of novel ARGs, and antibiotic stresses could cause ARG pollution via horizontal gene transfer and enrichment of resistant bacteria.

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Further improving the quality of surface water is becoming more difficult after the control of main point-sources, especially in the complex pollution area with mixed industrial and agricultural productions, whereas the pollution source apportionment might be the key to quantify different pollution sources and developing some effective measures. In this study, a technical framework for source apportionment based on three-dimensional fluorescence and microbial traceability model is developed. Based on screening of the main environmental factors and their spatiotemporal characteristics, potential pollution sources have been tentatively identified. Then, the pollution sources are further tested based on the analysis of fluorescence excitation-emission matrix (EEM) and the similarity of fluorescence components in surface water and potential pollution sources. At the same time, the correlation between microbial species and pollution sources is constructed by analyzing the spatiotemporal characteristics of microbial composition and the response of main species to environmental factors. Therefore, pollution source apportionment is quantified using PCA-APCS-MLR, Fast Expectation-maximization for Microbial Source Tracking (FEAST), and Bayesian community-wide culture-independent microbial source tracking (SourceTracker). PCA-APCS-MLR could not effectively distinguish the contributions of different industrial sources in the complex environment of this study, and the contribution of unknown sources was high (average 39.60%). In contrast, the microbial traceability model can accurately identify the contribution of 7 pollution sources and natural sources, effectively reduce the proportion of unknown sources (average of FEAST is 19.81%, SourceTracker is 16.72%), and show better pollution identification and distribution capabilities. FEAST exhibits a more sensitive potential in source apportionment and shorter calculation time than SourceTracker, thus might be used to guide the precise regional pollution control, especially in the complex pollution environments.

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Estuaries in South Africa are very important for biodiversity conservation and serve as focal points for leisure and tourism activities. The organophosphate flame retardants (OPFRs) levels in these aquatic systems haven't been documented in any studies as of yet. Due to the negative effects of persistent organic pollutants in South African estuaries, we examined the occurrence of eight OPFRs in sediments of two estuaries by studying their spatiotemporal distribution, season variation, and ecological risks. The Sundays Estuary (SDE), a semi-urbanized agricultural surrounding system, recorded an ∑8OPFR concentration in sediments that ranged from 0.71 to 22.5 ng/g dw, whereas Swartkops Estuary, a largely urbanized system, recorded a concentration that ranged from 0.61 to 119 ng/g dw. Alkyl-OPFRs were the prevalent homologue in both estuaries compared to the chlorinated and aryl groups. While TBP, TCPP, and TCrP were the most abundant compounds among the homologue groups. There was no distinct seasonal trend of ∑8OPFR concentration in either estuary, with summer and autumn seasons recording the highest concentrations in SDE and SWE, respectively. Ecological risks in the majority of the study sites for the detected compounds were at low (RQ < 0.1) and medium levels (0.1 ≤ RQ < 1) for certain species of fish, Daphnia magna and algae. However, the cumulative RQs for all the compounds had ∑RQs ≥1 for most sites in both estuaries, indicating that these organisms, if present in both estuaries, may be exposed to potential ecological concerns due to accumulated OPFR chemicals. The scope of future studies should be broadened to include research areas that are not only focus on the bioaccumulation patterns of these compounds but also find sustainable ways to reduce them from these estuarine environments.

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We characterized the elemental and C and N stable isotope compositions of Tillandsia fasciculata Sw., Tillandsia balbisiana Schult. & Schult.f. and Tillandsia recurvata (L.) L. samples collected in Cienfuegos (Cuba). Results showed high enrichment factors for S, Hg, Cd, Pb, P, Zn, Cu, Mo, Sb and Ca in all Tillandsia species, indicating inputs from local anthropogenic activities (road traffic, industries and cement production). Carbon concentrations and δ13C varied from 38.3-47.7 % and -20.4 to -13.4 ‰ within the three species, respectively. δ13C showed seasonal dependence with the dry and wet periods and more 13C-depleted values in urban/industrial areas, coherent with the input of anthropogenic emissions. Nitrogen concentrations (0.4-1.3 %) and δ15N values (-9.9-4.4 ‰) exhibit larger variations and are positively correlated in the three species. The most positive δ15N in T. recurvata (-0.2-4.4 ‰) are attributed to contributions from industrial activities and road traffic. In fact, both δ15N and total nitrogen (TN) values increase in sites with higher road traffic and show significant correlations with typical road traffic and industrial tracers. Finally, we calculate an average total nitrogen deposition rate of 4.4 ± 2.3 kg ha-1 a-1 from N content in T. recurvata, similar to the existing values determined in the region by field measurements, but higher than the global terrestrial average.

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Karst mountainous areas in Southwest China, the world's largest bare karst area, are faced with growing water shortages. Rainwater harvesting plays an important role in alleviating water shortage. However, there remains a substantial gap in the research regarding the water quality of tanks. Water samples were seasonally collected from ten tanks to investigate the physicochemical properties, microbial communities, and their key influencing factors. The result showed that pH, turbidity, chroma, DOC, and CODMn exceeded drinking water guidelines. The alkaline pH value and the deterioration of sensory properties was the main feature of tank water, from which the over-standard rate of the uncleaned water tanks was higher. Moreover, principal component analyses suggested that tank water quality was influenced by human activities, catchment areas, and material cycling processes within the tanks, of which in-tank microbial activities were the most important driving factors in water quality variation. Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, and Verrucomicrobia were the predominant bacterial phyla in water tanks. Acinetobacter, Cyanobium-PCC-6307, CL500-29-marine-group, Candidatus-Aquiluna, and Exiguobacterium were the most abundant genera. The bacterial communities were significantly affected by the management practices. Higher relative abundance of Cyanobacteria and lower relative abundance of Proteobacteria was detected in the uncleaned tanks, which was a sign of tank water quality deterioration. The microbial community structure was closely related to the environmental factors. There was evidence that the water quality was affected by the existence of a microecosystem dominated by photosynthetic microorganisms in the water tanks. In addition, Acinetobacter, Enterobacter, Pseudomonas, and Legionella identified as the potential opportunistic pathogenic genera were frequently detected but the relative abundances except Acinetobacter were low in the tanks. Overall, our findings indicated that management style influences water quality and bacterial communities of tank water.

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The global issue of heavy metal pollution in surface water poses a significant concern, with the potential to harm public health through various pathways. Given that pollution levels are dependent on water bodies and seasons and their potential impacts on human health vary with children and adults, it is crucial to identify and quantify pollution sources for the development of sustainable management strategies. The current study aimed to evaluate pollution levels and associated health risks of heavy metals and to quantify their pollution sources in various surface water bodies in Khanh Hoa, Vietnam. Water samples were taken from three water bodies (reservoirs, rivers, and narrow waterways) during two seasons (dry and rainy) from 2016 to 2020 and analyzed for seven heavy metals. The results showed that iron had the highest concentration of 392.4 (µg L-1), followed by zinc (25.7 µg L-1), arsenic (3.93 µg L-1), copper (3.77 µg L-1), lead (2.77 µg L-1), chromium (2.71 µg L-1), and cadmium (0.57 µg L-1). Narrow waterways were more polluted with heavy metals (heavy metal pollution index, HPI = 29.5) than other water bodies, such as rivers (23.3) and reservoirs (21.7), and the dry season had a higher HPI (26.5) than the rainy season (24.0). The hazard index for children varied from 1.2 to 1.48, while that for adults was less than 1, suggesting that surface water may have adverse impacts on children's health. The factor analysis identified three primary sources of contamination, namely combustion emissions/street dust, agricultural run-off, and other sources. Cadmium is the most critical metal in determining HPI, while arsenic and chromium are the two key elements potentially influencing children's health. Managing pollution sources, reducing the metal concentration, and controlling the pathways through which metals enter the human body should be implemented for a healthier environment and long-term development.

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The issue of environmental pollution caused by the widespread presence of microplastics (MPs) in environmental media has garnered significant attention. However, research on MPs pollution has mainly focused on aquatic ecosystems in recent years. The sources and pollution characteristics of MPs in the environment, especially in solid waste, have not been well-described. Additionally, there are few reports on the ecotoxicity of MPs, which highlights the need to fill this gap. This review first summarizes the occurrence characteristics of MPs in water, soil, and marine environments, and then provides an overview of their toxic effects on organisms and the relevant mechanisms. This paper also provides an outlook on the hotspots of research on pollution characterization and ecotoxicity of MPs. Finally, this review aims to provide insights for future ecotoxicity control of MPs. Overall, this paper expands our understanding of the pollution characteristics and ecological toxicity of MPs in current environmental media, providing forward-looking guidance for future research.

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Heavy metals (HMs) pollution threatens food security and human health. While previous studies have evaluated source-oriented health risk assessments, a comprehensive integration of environmental capacity risk assessments with pollution source analysis to prioritize control factors for soil contamination is still lacking. Herein, we collected 837 surface soil samples from agricultural land in the Nansha District of China in 2019. We developed an improved integrated assessment model to analyze the pollution sources, health risks, and environmental capacities of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. The model graded pollution source impact on environmental capacity risk to prioritize control measures for soil HMs. All HMs except Pb exceeded background values and were sourced primarily from natural, transportation, and industrial activities (31.26%). Approximately 98.92% (children), 97.87% (adult females), and 97.41% (adult males) of carcinogenic values exceeded the acceptable threshold of 1E-6. HM pollution was classified as medium capacity (3.41 kg/hm2) with mild risk (PI = 0.52). Mixed sources of natural backgrounds, transportation, and industrial sources were identified as priority sources, and As a priority element. These findings will help prioritize control factors for soil HMs and direct resources to the most critical pollutants and sources of contamination, particularly when resources are limited.

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