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Accurate identification of nitrate (NO3-) sources is the premise of non-point source pollution control in watersheds. The multiple isotope techniques (δ15N-NO3-, δ18O-NO3-, δ2H-H2O, δ18O-H2O), combined with hydrochemistry characteristics, land use information, and Bayesian stable isotope mixing model (MixSIAR), were used to identify the sources and contributions of NO3- in the agricultural watershed of the upper Zihe River, China. A total of 43 groundwater (GW) and 7 surface water (SFW) samples were collected. The results showed that NO3- concentrations of 30.23% GW samples exceeded the WHO maximum permissible limit level, whereas SFW samples did not exceed the standard. The NO3- content of GW varied significantly among different land uses. The averaged GW NO3- content in livestock farms (LF) was the highest, followed by vegetable plots (VP), kiwifruit orchards (KF), croplands (CL), and woodlands (WL). Nitrification was the main transformation process of nitrogen, while denitrification was not significant. Hydrochemical analysis results combined with NO isotopes biplot showed that manure and sewage (M&S), NH4+ fertilizers (NHF), and soil organic nitrogen (SON) were the mixed sources of NO3-. The MixSIAR model summarized that M&S was the main NO3- contributor for the entire watershed, SFW, and GW. For contribution rates of sources in GW of different land use patterns, the main contributor in KF was M&S (contributing 59.00% on average), while M&S (46.70%) and SON (33.50%) contributed significantly to NO3- in CL. Combined with the traceability results and the situation that land use patterns are changing from CL to KF in this area, improving fertilization patterns and increasing manure use efficiency are necessary to reduce NO3- input. These research results will serve as a theoretical foundation for controlling NO3- pollution in the watershed and adjusting agricultural planting structures.

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Global changes such as seawater intrusion and freshwater resource salinization increase environmental stress imposed on the aquatic microbiome. A strong predictive understanding of the responses of the aquatic microbiome to environmental stress will help in coping with the "gray rhino" events in the environment, thereby contributing to an ecologically sustainable future. Considering that microbial ecological networks are tied to the stability of ecosystem functioning and that abundant and rare biospheres with different biogeographic patterns are important drivers of ecosystem functioning, the roles of abundant and rare biospheres in maintaining ecological networks need to be clarified. Here we showed that, with the increasing salinity stress induced by the freshwater-to-seawater transition, the microbial diversity reduced significantly and the taxonomic structure experienced a strong succession. The complexity and stability of microbial ecological networks were diminished by the increasing stress. The composition of the microorganisms supporting the networks underwent sharp turnovers during the freshwater-to-seawater transition, with the abundant biosphere behaving more robustly than the rare biosphere. Notably, the abundant biosphere played a much more important role than the rare biosphere in stabilizing ecological networks under low-stress environments, but the difference between their relative importance narrowed significantly with the increasing stress, suggesting that the environmental stress weakened the "Matthew effect" in the microbial world. With in-depth insights into the aquatic microbial ecology under stress, our findings highlight the importance of adjusting conservation strategies for the abundant and rare biospheres to maintain ecosystem functions and services in response to rising environmental stress.

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Biochar was a kind of restoration material for soil pollution. Investigation about biochar amendment on the Sb transformation in rice plants is scarce. The pot experiment was conducted to evaluate the impact of biochar on the iron plaque formation in Sb-contaminated soil, and the translocation and accumulation of Sb in rice seedings. After the straw and husk biochar amendments (5% by weight), the levels increased on average by 20.0% and 16.0% for exchangeable Sb in soil, and by 233.3% and 74.8% for soluble Sb in pore water, respectively; but the residual fractions of Sb decreased by 18.5% and 15.1%. The iron plaque formation on rice root surface was enhanced, but its sequestration capacity for Sb decreased due to increasing competition for binding sites led by the elevated phosphorus and silicon levels in pore water after biochar application. The shoot Sb content sharply increased by 215.8% upon straw biochar application.

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Based on the study of the content, forms, and spatial distribution of phosphorus (P) in the surface and columnar sediments of the Sihe River, the relationships between the total phosphorus (TP) and various forms of P and the basic physical and chemical properties of sediment and their ecological significance were deeply discussed. The forms of P in the sediment were defined including soluble and loosely bound P (S/L-P), Al-bound P (Al-P), Fe-bound P (Fe-P), reductant soluble P (RS-P), Ca-bound P (Ca-P), and residual P (RES-P) using the method of selectively sequential extraction. The results indicated that ω (TP) was 421.84-1188.65 mg·kg-1 in the surface sediment. Among the six forms of P, the content of Ca-P was the highest, accounting for more than 40% of TP, followed by the content of Fe-P, accounting for more than 20% of TP. The content of S/L-P was the lowest, which only accounted for approximately 0.4% of TP. The contents of TP and various forms of P in the surface sediments of the downstream area of the Sihe River were higher than those of the upstream area of the river, which was induced by the discharge of industrial wastewater and domestic sewage in the urban areas nearby the downstream portion of the Sihe River. The contents of TP in the upper samples of the two sediment profiles were obviously higher than those in the bottom samples, indicating that the P pollution in the water environment of the Sihe River has been intensifying in recent years. Among all forms of P in the sediment profiles, Ca-P accounted for the largest proportion, followed by Res-P. The correlation analysis results showed that significant correlations were observed between Fe and Fe-P, Al and Al-P, Ca and Ca-P, and TOC and RS-P in the surface sediments; the same correlations had not been found in the sediment profiles. The calculated results of Fe and TP molar ratio indicated that the sediments of the Sihe River could further accumulate P. The percentage of bioavailable P (BAP) in sediment was 25%-50%.

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Pollution of atmospheric particulate matter carrying heavy metals has posed a great threat to various ecosystem compartments. Here, a total of 540 samples from four ecosystem compartments (plant leaves, foliar dust, surface soil, and subsoil) were collected in urban soil-plant systems to characterize the heavy metal concentration and composition of foliar dust, to verify the suitability of foliar dust as an environmental monitor, and to explore the importance of foliar dust in shaping the heavy metal composition in plant leaves. We found that the concentrations of all detected elements (lead, zinc, copper, chromium, nickel, and manganese) in foliar dust were the highest among the four ecosystem compartments. The mass of element per unit leaf area, considering both the dust retention amount and the heavy metal concentration of foliar dust, had significant positive correlations with the degree of heavy metal pollution in soil. Foliar dust could reflect ambient elemental composition most reliably among the four ecosystem compartments. The above findings show that foliar dust is more suitable for environmental monitoring than soil and plant materials in urban areas. In addition, the elemental composition of plant leaves differed significantly with different soil-plant systems although species identity dominated the leaf elemental composition. The variation partitioning model and the partial correlation analysis confirm that foliar dust plays a more important role in shaping the elemental composition of plant leaves than soil. This study provides a new way for environmental pollution monitoring and contributes to a comprehensive understanding of atmospheric particulate matter.

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The level, source, and risk of toxic elements in traditional agricultural soils are particularly crucial for the sustainable development of agriculture. An important agricultural production base was selected, a total of 251 topsoil samples were collected, eight toxic elements (As, Cd, Cr, Cu, Hg, Ni, Pb, Zn) in soil were analyzed, and environmental and health risk assessments were conducted. Results showed that all concentrations of eight elements in soil samples were lower than the risk screening values with negligible pollution risk. Approximately 83.8% of Hg in soil was originated from atmospheric deposition related to industrial emissions, 53.2% of Cd was derived from direct industrial activities, and the other elements came from soil parent materials or agricultural activities. Accumulation risk of As in agricultural products, potential ecological risk from Cd, and As's ingestion risk and Cr's dermal contact risk should be paid more attention. More stricter monitoring and coping countermeasures and strategies should be established to ensure the sustainable development of agriculture.

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Microplastics provide a unique habitat for microorganisms, forming the plastisphere. Yet the ecology of the plastisphere, including the microbial composition, functions, assembly processes, and interaction networks, needs to be understood. Here, we collected microplastics and their surrounding water samples in freshwater and seawater ecosystems. The bacterial and fungal communities of the plastisphere and the aquatic environment were studied based on 16S and internal transcribed spacer (ITS) high-throughput sequencing. We found that the plastisphere had a distinct microbial community and recruited a noteworthy proportion of unique species compared to the aquatic environment community, potentially altering ecosystem microbial community and causing microbial invasion. Using a random-forest machine-learning model, we identified a group of biomarkers that could best distinguish the plastisphere from the aquatic environment. Significant differences exist in microbial functions between the plastisphere and the aquatic environment, including functions of pathogenicity, compound degradation, as well as functions related to the cycling of carbon, nitrogen, and sulfur. And these functional differences were expressed differently in freshwater and seawater ecosystems. The oxidation-reduction potential, salinity, the concentrations of nitrogen-related ions (NO3-, NO2-, and NH4+), and the concentration of dissolved organic carbon in the surrounding environment drive the variation of the plastisphere. But environmental physicochemical properties explain less of the microbial community variation in the plastisphere than that in the aquatic environment. Niche-based processes govern the assembly of the plastisphere community, while neutral-based processes dominate the community assembly of the aquatic environment. Furthermore, compared to the aquatic environment, the plastisphere has a network of less complexity, more modules, higher modularity, and more competitive links in freshwater ecosystems, but the pattern is reversed in seawater ecosystems. Altogether, the microbial ecology of the new anthropogenic ecosystem-plastisphere-is unique and exerts different effects in freshwater and seawater ecosystems.

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Microplastics have been detected in various environments, yet the differences between microplastics in different environments are still largely unknown. Scientists have proposed the concept of the "microplastic cycle," but the evidence for the movement of microplastics between different environments is still scarce. By screening the literature and extracting information, we obtained microplastic data from 709 sampling sites in freshwater, seawater, freshwater sediment, sea sediment, and soil in China. Based on the similarity between microplastics and biological communities, here we propose the concept of a "microplastic community" and examine the differences, links, and diversity of microplastic communities in different environments. Wilcoxon sign-ranks test, Kruskal-Wallis test, and analysis of similarities (ANOSIM) showed that there were significant differences in abundance, proportion of small microplastics, and community composition (shape, color, and polymer types) of microplastics in different environments. The Mantel test showed that there were significant correlations between microplastic community composition in different environments. Network analysis based on community similarity further confirmed the links between microplastic communities. The distance decay models revealed that the links weakened with the increase of geographic distance, suggesting that sampling sites with closed geographical locations had similar pollution sources and more easily to migrate or exchange microplastics. The microplastic diversity integrated index (MDII) was established based on the diversity of microplastic shape, color, and polymer types, and its indication of the number of microplastic pollution sources was verified by the statistical fitting relationship between the number of industrial pollution sources and MDII. Our study provides new insight into the differences and links between microplastics in different environments, which contributes to the microplastic risk assessment and demonstrates the "microplastic cycle." The establishment of the microplastic diversity integrated index could be used in source analysis of microplastics.

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Heavy metals have always been a research hotspot due to their persistence, hazard and bioaccumulation. Microorganisms are highly sensitive to heavy metal pollution and play an important role in the material cycling and energy flow of the ecosystem. In order to further explore the influence of heavy metals on the diversity, composition, and function of microbial communities in the wetland sediment ecosystem, and to find suitable indicators to reflect heavy metal pollution status, we collected sediments from Huangjinxia nature reserve and determined the physicochemical properties, heavy metal (Cu, Cr, Ni, Pb, Zn, and Mn) concentrations, and microbial information. We found that: the contamination status of the study area stood at a moderate level evaluated by the pollution load index (PLI); heavy metals explained more of microbial community variation than the sediment physicochemical properties; in particular, Cr and Mn negatively affected microbial α-diversity; heavy metals significantly affected the structure of microbial communities, elements Cr, Pb, and Zn showed uniformly negative associations with the relative abundance of bacteria Nitrospirae (including class Nitrospira and order Nitrospirales), Bacteroidetes (including class Bacteroidia), and Verrucomicrobia; moreover, heavy metals affected predicted functions of microbial communities, including metabolic functions, genetic information processes, and functions related to the carbon cycle and the nitrogen cycle. Based on the relative abundance of sensitive microbial taxa and predicted functions, bioindicators [Bacteroidia], 1/[Nitrospira], 1/[Nitrification], and 1/[Aerobic nitrite oxidation] were established to reflect and predict the contamination status of heavy metals in sediments. Our in-depth research on the effects of heavy metals on microorganisms and the establishment of bioindicators provide references and new perspectives for environmental monitoring and management.

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Microplastics have been of great concern in recent years due to bioaccumulation and their toxic effects on organisms. However, few studies have focused on microplastics in the natural river ecosystem and the relationship between microplastics and microbes. Therefore, to understand the concentration and characteristics of microplastics and explore the impact of microplastics on the microbial community, sediment samples were collected from the Huangjinxia Reservoir, which is the water source of a water diversion project in western China. Results showed that the concentration of microplastics in the study area ranged from 233.33 ± 70.24 items·kg-1 to 870 ± 238.12 items·kg-1, with an average of 558.10 ± 291.45 items·kg-1. After clustering the sediments according to the microplastic concentration, there was a significant difference in the Chao1 index of microbial community between groups, indicating that microplastics might have affected microbial diversity of the sediments. Additionally, Anosim, MRPP, and Amova analyses indicated that microplastics might have an impact on the structure and composition of microbial communities. Moreover, function prediction assays suggested that microplastics might have differential impacts on various microbial community functions. To our knowledge, this is the first study to explore the impact of microplastics on microbes in sediments of a natural river ecosystem, providing a basis for further study of the interaction between microplastics and microbes in similar habitats.

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The Yellow River Delta (YRD) region is an important production base in Shandong Province. It encompasses an array of diversified crop systems, including the corn-wheat rotation system (Wheat-Corn), soybean-corn rotation system (Soybean-Corn), fruits or vegetables system (Fruit), cotton system (Cotton) and rice system (Rice). In this study, the communities of ammonia oxidizer-, denitrifier- and nitrogen (N)-fixing bacteria in those cropping systems were investigated by Illumina Miseq sequencing. We found that Rice soil exhibited significantly higher diversity indices of investigated N-cycling microbial communities than other crop soils, possibly due to its high soil water content. Wheat-Corn soils had higher abundances of nitrification gene amoA and denitrification genes nirK and nirS, and exhibited higher soil potential nitrification rate (PNR), compared with Soybean-Corn, Cotton and Fruit soils. Consistently, redundancy analysis (RDA) showed that soil water content (SWC), electrical conductivity (EC), and total nitrogen (TN) were the most important influencing factors of the diversity and structure of the investigated N-cycling microbial.

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Mining activities are considered the most important factor causing heavy metal accumulation in surface soil and it is important to understand the spatial distribution and source of heavy metals in typical steppes. In this study, the contents, spatial distribution, and sources of heavy metals were determined using geostatistical analyses, multivariate statistical analyses, and a positive matrix factorization (PMF) model using 152 soil samples collected from a grassland near the Sheng-Li coal base. The results shows that the mean concentration of heavy metals is low and does not threaten the quality of the local soil. However, the concentrations of eight heavy metals (Cu 15.04 mg kg-1, Zn 49.30 mg kg-1, Cd 0.11 mg kg-1, Pb 20.00 mg kg-1, Se 0.12 mg kg-1, Ge 1.45 mg kg-1, As 9.06 mg kg-1, and Sn 2.52 mg kg-1) are higher than their mean background values in soil in Inner Mongolia. High coefficients of variation for the heavy metals, especially Ge (1.03), and As (0.56), indicate that the concentrations of the elements are affected by the presence of the open-pit mines. Multivariate statistical and geo-statistical analyses show that Ge and As are highly correlated (R2 = 0.67, P < 0.01), suggesting that they have the same source. Using geostatistical and PMF models, we identified five potential pollution sources in the study area: 1) Industrial pollution (21.2 %), which includes smelting activity and open-pit coal mines, as suggested by elevated levels of Zn, Cd, Ge, and Cu; 2) Germanium mining (7.6 %), as indicated by higher levels of Ge and As; 3) Natural sources (37.2 %), as indicated by higher levels of Mn and Ni; 4) Coal mining activity (8.5 %), as indicated by higher levels of Sn and Cr; 5) Coal conveyor belts and high vehicular traffic, as indicated by elevated levels of Pb and Se. Taken together, the results of this study indicate that the coal base has a significant effect on the heavy metal concentration in the grassland. Therefore, the identification of the spatial distribution of heavy metals in the area may be key to controlling the pollution in the grassland. The results of this study can help to reduce pollution sources, cut down on pollution transport. So that zonal pollution control and ecological protection in the typical steppe region is achieved.

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Examination of heavy metal sources in soils from a resource-based region is essential for source identification and implementation of restoration strategies regarding soil contamination. A total of 1069 samples were collected from cropland soils in the Baiyin District (Loess Plateau, Northwest China), a characteristically resource-based region to investigate the sources of arsenic (As), chromium (Cr), copper (Cu), manganese (Mn), nickel (Ni), lead (Pb), vanadium (V), and zinc (Zn). Source identification was analyzed by multiple methods including spatial deviation (SD), correlation analysis (CA), enrichment factor (EF), principal component analysis (PCA), geographic information system (GIS), and positive matrix factorization (PMF). The results showed the combined applications of PMF, GIS, and PCA were accurate, pragmatic, and effective for source apportionment. Three origins were identified and the contribution rates were calculated as follows: approximately 95% of As came from wastewater irrigation; 75, 88, 60, and 76% of Cr, Mn, Ni, and V were separately derived from natural origins; and 81, 93, and 70% of Cu, Pb, and Zn originated from industrial sources, respectively. Natural origins, industrial sources, and wastewater irrigation were the three main contributors of heavy metals to cropland soils in this region.

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Source quantification of heavy metals in farmland is essential for developing and implementing restoration strategies. We used various data analyses to identify and quantify sources of arsenic, cadmium, chromium, copper, mercury, nickel, lead, and zinc in vegetable-growing soils. A new method of collaborative assessment, combining soil environmental quality and agricultural product safety, showed that approximately 5.20% of cultivation systems were multi-contaminated by heavy metals. The nonlinear relationship between pollution sources and the comprehensive contamination situation was established, deriving from a fitted bivariate model. The model revealed that anthropogenic sources and natural origins accounted for 65.8-86.0 and 34.2-14.0% of the comprehensive pollution, respectively. These results suggested that both human activities and natural factors contributed to the decline of local soil quality and the influence of the former was more substantial than that of the latter.

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To better understand the Hg(II) adsorption by some typical soils and explore the insights about the binding between Hg(II) and soils, a batch of adsorption and characteristic experiments was conducted. Results showed that Hg(II) adsorption was well fitted by the Langmuir and Freundlich. The maximum adsorption amount of cinnamon soil (2094.73 mg kg-1) was nearly tenfold as much as that of saline soil (229.49 mg kg-1). The specific adsorption of Hg(II) on four soil surface was confirmed by X-ray photoelectron spectroscopy (XPS) owing to the change of elemental bonding energy after adsorption. However, the specific adsorption is mainly derived from some substances in the soil. Fourier transform infrared spectroscopy (FTIR) demonstrated that multiple oxygen-containing functional groups (O-H, C=O, and C-O) were involved in the Hg(II) adsorption, and the content of oxygen functional groups determined the adsorption capacity of the soil. Meanwhile, scanning electron microscopy combined with X-ray energy dispersive spectrometer (SEM-EDS) more intuitive revealed the binding of mercury to organic matter, metal oxides, and clay minerals in the soil and fundamentally confirmed the results of XPS and FTIR to further elucidate adsorptive phenomena. The complexation with oxygen-containing functional groups and the precipitation with minerals were likely the primary mechanisms for Hg(II) adsorption on several typical soils. This study is critical in understanding the transportation of Hg(II) in different soils and discovering potential preventative measures.

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A field survey was conducted to investigate the concentrations of chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), cadmium (Cd) and lead (Pb) in vegetables, corresponding cultivated soils and irrigation waters from 36 open sites in high natural background area of Wuzhou, South China. Redundancy analysis, Spearman's rho correlation analysis and multiple regression analysis were adopted to evaluate the contributions of impacting factors on metal contents in the edible parts of vegetables. This study concluded that leafy and root vegetables had relatively higher metal concentrations and adjusted transfer factor values compared to fruiting vegetables according to nonparametric tests. Plant species, total soil metal content and soil pH value were affirmed as three critical factors with the highest contribution rate among all the influencing factors. The bivariate curve equation models for heavy metals in the edible vegetable tissues were well fitted to predict the metal concentrations in vegetables. The results from this case study also suggested that it could be one of efficient strategies for clean agricultural production and food safety in high natural background area to breed vegetable varieties with low heavy metal accumulation and to enlarge planting scale of these varieties.

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