Explanatory subgraph attacks against Graph Neural Networks.

Graph Neural Networks (GNNs) are often viewed as black boxes due to their lack of transparency, which hinders their application in critical fields. Many explanation methods have been proposed to address the interpretability issue of GNNs. These explanation methods reveal explanatory information about graphs from different perspectives. However, the explanatory information may also pose an attack risk to GNN models. In this work, we will explore this problem from the explanatory subgraph perspective. To this end, we utilize a powerful GNN explanation method called SubgraphX and deploy it locally to obtain explanatory subgraphs from given graphs. Then we propose methods for conducting evasion attacks and backdoor attacks based on the local explainer. In evasion attacks, the attacker gets explanatory subgraphs of test graphs from the local explainer and replace their explanatory subgraphs with an explanatory subgraph of other labels, making the target model misclassify test graphs as wrong labels. In backdoor attacks, the attacker employs the local explainer to select an explanatory trigger and locate suitable injection locations. We validate the effectiveness of our proposed attacks on state-of-art GNN models and different datasets. The results also demonstrate that our proposed backdoor attack is more efficient, adaptable, and concealed than previous backdoor attacks.

A case of peritoneal Burkitt's lymphoma mimic of peritoneal tuberculosis.

Peritoneal lymphomatosis is a rare presentation of lymphoma that can mimic peritoneal tuberculosis. The computed tomography findings in both conditions include omental caking, thickening, and nodularity. We report the case of a 41-year-old man who presented with intermittent abdominal pain and distension. Abdominal CT initially suggested peritoneal tuberculosis due to the thickening of the peritoneum and greater omentum with multiple nodules. However, 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) images showed diffuse metabolic activity increase in the thickened peritoneum, omentum, and mesentery. An omental biopsy was performed under ultrasonography guidance, and histopathological examination revealed a high-grade Burkitt lymphoma. It is crucial to distinguish peritoneal lymphomatosis from tuberculosis, as the prognosis and management of the two conditions are vastly different.

Multiple isotopes reveal the driving mechanism of high NO3- level and key processes of nitrogen cycling in the lower reaches of Yellow River.

The continuous increase of nitrate (NO3-) level in rivers is a hot issue in the world. However, the driving mechanism of high NO3- level in large rivers is still lacking, which has limited the use of river water and increased the cost of water treatment. In this study, multiple isotopes and source resolution models are applied to identify the driving mechanism of high NO3- level and key processes of nitrogen cycling in the lower reaches of the Yellow River (LRYR). The major sources of NO3- were sewage and manure (SAM) in the low-flow season and soil nitrogen (SN) and chemical fertilizer (CF) in the high-flow season. Nitrification was the most key process of nitrogen cycling in the LRYR. However, in the biological removal processes, denitrification may not occur significantly. The temporal variation of contributions of NO3- sources were estimated by a source resolution model in the LRYR. The proportional contributions of SAM and CF to NO3- in the low-flow and high-flow season were 32.5%-52.3%, 44.2%-46.2% and 36.0%-40.8%, 54.9%-56.9%, respectively. The driving mechanisms of high NO3- level were unreasonable sewage discharge, intensity rainfall runoff, nitrification and lack of nitrate removal capacity. To control the NO3- concentration, targeted measures should be implemented to improve the capacity of sewage and wastewater treatment, increase the utilization efficiency of nitrogen fertilizer and construct ecological engineering. This study deepens the understanding of the driving mechanism of high nitrate level and provides a vital reference for nitrogen pollution control in rivers to other area of the world.

[Analysis on Contamination Characteristics, Pollution Source Identification and Ecological Risk Assessment of Polycyclic Aromatic Hydrocarbons of Groundwater in a Large Coking Plant Site of Province].

Polycyclic aromatic hydrocarbons (PAHs), as a highly toxic persistent organic pollutant, are commonly found in soil and water environments. In recent years, the pollution of PAHs in groundwater has attracted wide attention from scientists. To study the pollution characteristics and sources of polycyclic aromatic hydrocarbon in groundwater of the coking site, 16 PAHs priorly controlled by the US EPA were analyzed and discussed. In this study, we identified the contamination characteristics of PAHs in groundwater, analyzed the pollution sources of PAHs, and evaluated the ecological risk of PAHs in the coking site by combining statistical techniques, the positive matrix factorization (PMF) model, and risk quotient (RQ) methods. The results indicated that the total detection rate of PAHs in groundwater of the coking plant was 46.7%. The concentrations of PAHs in groundwater of the coking plant ranged from below the detection limit to 444.9 µg·L-1, with the average value of 1.88 µg·L-1. The concentration of PAHs in the groundwater of different production workshops was significantly different. The most polluted workshop was in the tar-refining area, and the concentration of 16 PAHs was 444.9 µg·L-1. Based on the PMF model, we identified the two primary contamination sources of PAHs in groundwater of the coking plant:① oil combustion and ② coal and biomass combustion and oil leakage. The contribution ratios of the two sources to PAHs of groundwater were 38.6% and 61.4%, respectively. The results of the ecological risk assessment indicated that Σ16PAHs in groundwater of the coking plant had high ecological risk, and the ecological risk of single PAHs in 53.4% of the groundwater sampling site was at a high ecological risk level. In conclusion, it is urgent to carry out the treatment and restoration of the groundwater environment in the coking plant site.

Spatial patterns in water quality and source apportionment in a typical cascade development river southwestern China using PMF modeling and multivariate statistical techniques.

River cascade development is one of the human activities that have the most significant impact on the water environment. However, the mechanism of cascade development affecting river hydrochemical components still needs to be further studied. In this study, water quality index(WQI), positive matrix factorization(PMF) model and multivariate statistical techniques were used to identify the mechanism of cascade development affecting river hydrochemical components in an typical cascade development Rivers, Lancang River, China. The results showed that the water quality of Lancang River is relatively good due to less affected by human activity. The spatial variation of river hydrochemistry is affected by the development of cascade reservoirs, and shows three patterns: irregular variation (pH and DO), fluctuating decreasing (Na+, Cl-, SO42- and HCO3-) and multi-peak variation (TN, TDN, NO3--N and NH4+-N). It's worth noting that the concentration of the most hydrochemical parameters is higher in the upper reaches (less human activities) than that in the middle and lower reaches of river due to the retention effect of the reservoir on the chemical composition. The PMF model outputs revealed that the rock weathering and internal source, sewage and soil nitrogen, and chemical fertilizer were primary material sources of Lancang River. Compared with the natural channel zone (41.0%), the interaction of water-rock has more influence on chemical component in the reservoir area (56.3%), while the contribution of fertilizer (11.2%) to the river hydrochemistry is less. The sites of downstream of the reservoir dam were affected by the retention of the reservoir and the disturbance of the bottom drainage, which leads to the weakening of the influence of the sewage (44.7%) on the river material and the increase of the contribution of fertilizer (25.0%). These results could provide valuable information in controlling the eutrophication of cascade reservoirs and the scientific construction of river cascade reservoirs.

Quantitative identification of groundwater contamination sources by combining isotope tracer technique with PMF model in an arid area of northwestern China.

Nowadays, groundwater quality has deteriorated because of intensive human activities. It is important to accurately identify the pollution source for controlling the deterioration of groundwater quality. However, the accuracy of the current source analysis method needs to be improved. In this study, we combined hydrochemical method, isotope tracing technique and PMF model, for the first time, to trace the source of groundwater pollution in Beichuan River basin, Qinghai Province, China. According to the results, there were 35.8% of Fe, 34.1% of total hardness, 24.3% of SO42- and 8.09% of NO3- samples exceeded the Grade III standards for Groundwater quality in China, which indicated that the groundwater in the study area has been significantly affected by human activities. Hydrochemical method suggested that the chemical component originated from rock weathering, cation exchange and mineral dissolution. Based on isotope tracing technique (δ15N-NO3-, δ18O-NO3-, δ34S-SO42- and δ18O-SO42-), the primary sources of nitrate and sulfate in groundwater were soil nitrogen and oxidation of sulfide minerals in the forest area, domestic sewage and oxidation of sulfide minerals in the urban and industrial area, and mixed sources in the village and agricultural area. Finally, the pollution source of groundwater was distinguished by combining the PMF model, isotope tracing technique and hydrochemical method. Results showed that the main pollutant of groundwater is domestic sewage in the urban, village and industrial area. The contribution rates to groundwater pollution were 60.7%, 60.8% and 57.8%, respectively. However, in the forest and agricultural area, the main source changed to water-rock interaction and chemical fertilizer, and the contribution rates to groundwater quality were 53.5% and 61.0%, respectively. Our results suggested that the coupling tracing methodology can improve the accuracy of source resolution in the water environment and it can be applied to other areas of the world.

Primal-Dual Fixed Point Algorithms Based on Adapted Metric for Distributed Optimization.

This article considers distributed optimization by a group of agents over an undirected network. The objective is to minimize the sum of a twice differentiable convex function and two possibly nonsmooth convex functions, one of which is composed of a bounded linear operator. A novel distributed primal-dual fixed point algorithm is proposed based on an adapted metric method, which exploits the second-order information of the differentiable convex function. Furthermore, by incorporating a randomized coordinate activation mechanism, we propose a randomized asynchronous iterative distributed algorithm that allows each agent to randomly and independently decide whether to perform an update or remain unchanged at each iteration, and thus alleviates the communication cost. Moreover, the proposed algorithms adopt nonidentical stepsizes to endow each agent with more independence. Numerical simulation results substantiate the feasibility of the proposed algorithms and the correctness of the theoretical results.

Spatiotemporal Variation in Groundwater Quality and Source Apportionment along the Ye River of North China Using the PMF Model.

Groundwater quality deterioration has attracted widespread concern in China. In this research, the water quality index (WQI) and a positive matrix factorization (PMF) model were used to assess groundwater quality and identify pollution sources in the Ye River area of northern China. Research found that TH, SO42-, and NO3- were the main groundwater pollution factors in the Ye River area, since their exceeding standard rates were 78.13, 34.38, and 59.38%, respectively. The main groundwater hydrochemical type has changed from HCO3-Ca(Mg) to HCO3·SO4-Ca(Mg). These data indicated that the groundwater quality was affected by anthropogenic activities. Spatial variation in groundwater quality was mainly influenced by land use, whereas temporal variation was mainly controlled by rainfall. The WQI indicated that the groundwater quality was better in the flood season than in the dry season due to the diluting effect of rainfall runoff. Notably, farmland groundwater quality was relatively poor as it was affected by various pollution sources. Based on the PMF model, the main groundwater pollution sources were domestic sewage (52.4%), industrial wastewater (24.1%), and enhanced water-rock interaction induced by intensely exploited groundwater (23.6%) in the dry season, while in the flood season they were domestic sewage and water-rock interaction (49.6%), agriculture nonpoint pollution (26.1%), and industrial wastewater and urban nonpoint pollution (23.9%). In addition, the mean contribution of domestic sewage and industrial sewage to sampling sites in the dry season (1489 and 322.5 mg/L, respectively) were higher than that in the flood season (1158 and 273.6 mg/L, respectively). To sum up, the point sources (domestic sewage and industrial wastewater) remain the most important groundwater pollution sources in this region. Therefore, the local government should enhance the sewage treatment infrastructure and exert management of fertilization strategies to increase the fertilizer utilization rate and prevent further groundwater quality deterioration.

Research Advances in the Analysis of Nitrate Pollution Sources in a Freshwater Environment Using δ15N-NO3- and δ18O-NO3.

Nitrate is usually the main pollution factor in the river water and groundwater environment because it has the characteristics of stable properties, high solubility and easy migration. In order to ensure the safety of water supply and effectively control nitrate pollution, it is very important to accurately identify the pollution sources of nitrate in freshwater environment. At present, as the most accurate source analysis method, isotope technology is widely used to identify the pollution sources of nitrate in water environment. However, the complexity of nitrate pollution sources and nitrogen migration and transformation in the water environment, coupled with the isotopic fractionation, has changed the nitrogen and oxygen isotopic values of nitrate in the initial water body, resulting in certain limitations in the application of this technology. This review systematically summarized the typical δ15N and δ18O-NO3- ranges of NO3- sources, described the progress in the application of isotope technique to identify nitrate pollution sources in water environment, analyzed the application of isotope technique in identifying the migration and transformation of nitrogen in water environment, and introduced the method of quantitative source apportionment. Lastly, we discussed the deficiency of isotope technique in nitrate pollution source identification and described the future development direction of the pollution source apportionment of nitrate in water environment.

Identification of Sources and Transformations of Nitrate in the Intense Human Activity Region of North China Using a Multi-Isotope and Bayesian Model.

Nitrate (NO3-) contamination in water is an environmental problem of widespread concern. In this study, we combined the stable isotopes of NO3- (δ15N and δ18O) and water (δ2H and δ18O) with a Bayesian mixing model (SIAR) to identify the sources and transformation of NO3- in groundwater and rivers in the Ye River basin of North China. The results showed that the mean NO3- concentrations in groundwater were 133.5 and 111.7 mg/L in the dry and flood seasons, respectively, which exceeded the required Chinese drinking water standards for groundwater (88.6 mg/L) (GB14848-2017). This suggests that groundwater quality has been severely impacted by human activity. Land use significantly affected the concentration of NO3- in the Ye River basin (p < 0.05). However, the NO3- concentrations in groundwater and river water had no obvious temporal variation (p > 0.05). The principal mode of nitrogen transformation for both groundwater and river water was nitrification, whereas denitrification did not significantly affect the isotopic compositions of NO3-. The sources of NO3- mainly originated from sewage and manure, soil nitrogen, and NH4+ in fertilizer for groundwater and from sewage and manure for the river water. According to the SIAR model, the primary sources of nitrate found in groundwater and river were sewage and manure in the Ye River basin. The proportional contributions of sewage and manure to nitrate contamination of groundwater and river were 58% and 48% in the dry season and 49% and 54% in the flood season, respectively. Based on these results, we suggest that the local government should enhance the sewage treatment infrastructure, construct an effective waste storage system to collect manure, and pursue a scientific fertilization strategy (such as soil formula fertilization) to increase the utilization rate of nitrogen fertilizer and prevent nitrate levels from increasing further.

Assessment of the Evolution of Groundwater Chemistry and Its Controlling Factors in the Huangshui River Basin of Northwestern China, Using Hydrochemistry and Multivariate Statistical Techniques.

Groundwater is an eco-environmental factor and critical resource required for human life and socioeconomic development. Understanding the evolution of groundwater chemistry and its controlling factors are imperative for preventing its deterioration and ensuring its sustainable use. We studied the characteristics of groundwater chemistry in the Huangshui River Basin in Qinghai Province, China using hydrochemical techniques. Additionally, we identified the controlling factors of groundwater chemistry in this region using multivariate statistical techniques. Seventeen hydrochemical parameters of groundwater were investigated at 156 sites in June 2019. The results showed that total hardness, Fe, NO3-, SO42-, and Cl- were primary pollution factors of groundwater in this region, and that 33.3%, 35.3%, 8.97%, 23.1%, and 7.69% of the samples exceeded Grade III standards for groundwater quality in China, respectively. Land use types also significantly affected groundwater hydrochemistry. The hydrochemical composition of groundwater in industrial areas is more strongly influenced by human activities. The major hydrochemical types identified in the region were HCO3-Ca·Mg and HCO3·SO4-Ca·Mg. Additionally, high proportions of SO4 (50.6%), Na (32.1%), and Cl (13.5%) groundwater types revealed the influence of anthropogenic activities on the groundwater hydrochemistry. Rock weathering was the major factor influencing the groundwater hydrochemistry, while evaporation-condensation and anthropogenic activities also influenced the hydrochemical characteristics of groundwater. The hydrochemical composition of groundwater was mainly controlled by silicate rock weathering. The main controlling factors of groundwater hydrochemistry were water-rock interactions, "physicochemical" factors (nature processes), domestic sewage, chemical fertilizer, and industrial sewage (human activities).

A High Rate of Recurrent Vulvovaginal Candidiasis and Therapeutic Failure of Azole Derivatives Among Iranian Women.

Recurrent vulvovaginal candidiasis (RVVC) is one of the most prevalent fungal infections in humans, especially in developing countries; however, it is underestimated and regarded as an easy-to-treat condition. RVVC may be caused by dysbiosis of the microbiome and other host-, pathogen-, and antifungal drug-related factors. Although multiple studies on host-related factors affecting the outcome have been conducted, such studies on Candida-derived factors and their association with RVVC are lacking. Thus, fluconazole-tolerant (FLZT) isolates may cause fluconazole therapeutic failure (FTF), but this concept has not been assessed in the context of Candida-associated vaginitis. Iran is among the countries with the highest burden of RVVC; however, comprehensive studies detailing the clinical and microbiological features of this complication are scarce. Therefore, we conducted a 1-year prospective study with the aim to determine the RVVC burden among women referred to a gynecology hospital in Tehran, the association of the previous exposure to clotrimazole and fluconazole with the emergence of FLZT and fluconazole-resistant (FLZR) Candida isolates, and the relevance of these phenotypes to FTF. The results indicated that about 53% of the patients (43/81) experienced RVVC. Candida albicans and C. glabrata constituted approximately 90% of the yeast isolates (72 patients). Except for one FLZT C. tropicalis isolate, FLZR and FLZT phenotypes were detected exclusively in patients with RVVC; among them, 27.9% (12/43) harbored FLZR strains. C. albicans constituted 81.2% of FLZR (13/16) and 100% of the FLZT (13/13) isolates, respectively, and both phenotypes were likely responsible for FTF, which was also observed among patients with RVVC infected with fluconazole-susceptible isolates. Thus, FTF could be due to host-, drug-, and pathogen-related characteristics. Our study indicates that FLZT and FLZR isolates may arise following the exposure to over-the-counter (OTC) topical azole (clotrimazole) and that both phenotypes can cause FTF. Therefore, the widespread use of OTC azoles can influence fluconazole therapeutic success, highlighting the necessity of controlling the use of weak topical antifungals among Iranian women.

The clinical profiles and outcomes of HIV-negative cryptococcal meningitis patients in type II diabetes mellitus.

BACKGROUND: The clinical profiles and outcomes of cryptococcal meningitis have been shown to vary depending on the underlying condition. The aim of this study was to investigate clinical characteristics and outcomes in patients with and without type II diabetes mellitus. METHODS: A retrospective study was performed. Clinical data of HIV-negative cryptococcal meningitis patients with type II diabetes mellitus (n = 26) and without type II diabetes mellitus (n = 52) referring to the Jiangxi Chest Hospital between January 2012 to December 2018 were analyzed. The data were analyzed using chi square, none-parametric tests, and logistic regression. P-values < 0.05 were considered significant. RESULTS: In this study, cryptococcal meningitis patients suffering from type II diabetes mellitus had a higher mortality (23.08% vs. 7.69%; P = 0.055), and required longer hospitalization (59.58 vs. 42.88 days; P = 0.132). Moreover, cerebrospinal fluid examinations revealed that cryptococcal meningitis patients with type II diabetes mellitus had higher opening pressure (271.54 vs. 234.23 mmH2O; P = 0.125).The results of multivariate regression analysis revealed that cryptococcal meningitis patients with type II diabetes were more often presented with visual disorders (28.54% vs. 11.54%; [95% CI 0.056-0.705]; p = 0.012), and had higher cerebrospinal fluid protein levels (1027.62 ± 594.16 vs. 705.72 ± 373.88 mg/l; [95% CI 1.000-1.002]; p = 0.016). Among patients with type II diabetes mellitus, nausea and vomiting was more frequent at the initial visit in those died (100% vs. 50%; p = 0.027), and 66% of died type II diabetes mellitus patients were poorly controlled blood glucose level, compared with 30% in survival type II diabetes mellitus patients. CONCLUSION: This study suggests that cryptococcal meningitis patients with type II diabetes mellitus differ significantly from cryptococcal meningitis patients without type II diabetes mellitus with respect to clinical symptoms such as visual disorders and cerebrospinal fluid examination. The presence of nausea and vomiting among type II diabetes mellitus patients could have implication in mortality.

Characteristics and source apportionment of polycyclic aromatic hydrocarbons of groundwater in Hutuo River alluvial-pluvial fan, China, based on PMF model.

PAH contamination in water environment has become an important water quality problem in China. In this study, groundwater PAHs were monitored in September 2019 at 48 groundwater sites, and statistical analysis and positive matrix factorization (PMF) model were used to analyze the characteristic of PAHs in groundwater and to identify the pollution sources of PAHs in the Hutuo River Basin, Hebei Province, China. The results showed that the concentration of the PAHs in groundwater was low and the total PAHs (∑PAHs) ranged from below detection limit to 260.6 ng/L and with a mean value of 17.7 ng/L. The concentration of PAHs in groundwater was obviously affected by the land use. Based on molecular ratio method, the main source of PAHs in groundwater is the biomass combustion, while the results of PMF source analysis were more accurate and the results showed that the primary sources and contribution rate of PAHs in groundwater were wood, coal, and gasoline sources (41.4%), followed by oil and diesel sources (39.4%), and natural gas combustion (19.2%). There was obvious spatial variation in the contribution of pollution sources to PAHs at the sites of different land uses in this region. The highest contribution of nature gas combustion, oil and diesel sources, and wood, coal, and gasoline combustion to PAHs was found in the urban area (0.617 ng/L), industrial area (0.380 ng/L), and village area (0.379 ng/L), respectively. The results can provide scientific basis for the prevention and control of PAH contamination in groundwater in this area.

Tracing sulfate origin and transformation in an area with multiple sources of pollution in northern China by using environmental isotopes and Bayesian isotope mixing model.

Sulfate (SO42-) contamination in groundwater and surface water is an environmental problem of widespread concern. In this study, we combined stable isotope analyses of SO42- (δ34S and δ18O) and water (δ2H and δ18O) with a Bayesian mixing model (SIAR), for the first time, to identify sources and transformation of SO42- in an area of northern China with multiple potential sources of pollution. The overall values of δ34S and δ18O-SO42- ranged from 1.3‰ to 16.3‰ and -3.8‰-8.8‰ in groundwater, and from -1.1‰ to 9.3‰ and 2.7‰-9.2‰ in surface waters, respectively. Analyses of SO42- isotopes and water chemistry indicated that SO42- in groundwater and surface water mainly originated from mixing of oxidation of sulfate, sewage, chemical fertilizers, dissolution of evaporite and precipitation. There was no significant correlation between δ34S and δ18O and SO42- concentration in groundwater, indicating that bacterial sulfate reduction did not affect the SO42- isotopic composition. SIAR model showed the main sources of SO42- in groundwater and surface water comprised oxidation of sulfide minerals and sewage. In groundwater, oxidation of sulfide minerals and sewage accounted for 37.5-44.5% and 35.5-42.7% of SO42-, respectively. In regard to surface waters, the contribution of oxidation of sulfide minerals to SO42- was higher in the wet season (31.8 ± 9.9%) than in the intermediate (22.4 ± 7.8%) and dry (20.9 ± 8.2%) seasons, but the contribution proportion of sewage was slightly lower in the wet season (19.9 ± 8.5%) than in the intermediate (23.8 ± 8.7%) and dry (24.2 ± 8.5%) seasons. This study indicates that it is necessary for local government to improve the treatment infrastructure for domestic sewage and optimize methods of agricultural fertilization and irrigation to prevent SO42- contamination of groundwater and surface water.

Spatiotemporal Patterns in River Water Quality and Pollution Source Apportionment in the Arid Beichuan River Basin of Northwestern China Using Positive Matrix Factorization Receptor Modeling Techniques.

Deteriorating surface water quality has become an important environmental problem in China. In this study, river water quality was monitored in July (wet season) and October (dry season) 2019 at 26 sites, and a water quality index (WQI) and positive matrix factorization (PMF) model were used to assess surface water quality and identify pollution sources in the Beichuan River basin, Qinghai Province, China. The results showed that 53.85% and 76.92% of TN, 11.54% and 34.62% of TP, 65.38% and 76.92% of Fe, and 11.54% and 15.38% of Mn samples in the dry and wet seasons, respectively, exceeded the Chinese Government's Grade III standards for surface water quality. The spatial variation in water quality showed that it gradually deteriorated from upstream to downstream as a result of human activity. The temporal variation showed that water quality was poorer in the wet season than in the dry season because of the rainfall runoff effect. The PMF model outputs showed that the primary sources of pollution in the wet season were mineral weathering and organic pollution sources, domestic and industrial sewage, and agricultural and urban non-point pollution sources. However, in the dry season, the primary sources were mineral weathering and organic pollution sources, industrial sewage, and domestic sewage. Our results suggest that the point pollution sources (domestic and industrial sewage) should be more strictly controlled, as a priority, in order to prevent the continued deterioration in water quality.

Spatio-temporal Variation of Groundwater Quality and Source Apportionment using Multivariate Statistical Techniques for the Hutuo River Alluvial-Pluvial Fan, China.

Groundwater quality deterioration has become an environmental problem of widespread concern. In this study, we used a water quality index (WQI) and multivariate statistical techniques to assess groundwater quality and to trace pollution sources in the Hutuo River alluvial-pluvial fan, China. Measurement data of 17 variables in 27 monitoring sites from three field surveys were obtained and pretreated. Results showed that there were 53.09% of NO3-, 18.52% of SO42- and 83.95% of total hardness (TH) in samples that exceeded the Grade III standard for groundwater quality in China (GB/T 14848-2017). Based on WQI results, sampling sites were divided into three types: high-polluted sites, medium-polluted sites and low-polluted sites. The spatial variation in groundwater quality revealed that concentrations of total dissolved solids (TDS), Cl-, TH and NO3- were the highest in high-polluted sites, followed by medium-polluted and low-polluted sites. The temporal variation in groundwater quality was controlled by the dilution of rainwater. A principal component analysis (PCA) revealed that the primary pollution sources of groundwater were domestic sewage, industrial sewage and water-rock interactions in the dry season. However, in the rainy and transition seasons, the main pollution sources shifted to domestic sewage and water-rock interactions, nonpoint pollution and industrial sewage. According to the absolute principal component scores-multivariate linear regression (APCS-MLR), most water quality parameters were primarily influenced by domestic sewage. Therefore, in order to prevent the continuous deterioration of groundwater quality, the discharge of domestic sewage in the Hutuo River alluvial-pluvial fan region should be controlled.

Assessment of sources and transformation of nitrate in the alluvial-pluvial fan region of north China using a multi-isotope approach.

A multi-isotope approach and mixing model were combined to identify spatial and seasonal variations of sources, and their proportional contribution to nitrate in the Hutuo River alluvial-pluvial fan region. The results showed that the NO3- concentration was significantly higher in the Hutuo River valley plain (178.7 mg/L) region than that in the upper and central pluvial fans of the Hutuo River (82.1 mg/L and 71.0 mg/L, respectively) and in the river (17.0 mg/L). Different land use types had no significant effect on the groundwater nitrate concentration. Based on a multi-isotope approach, we confirmed that the main sources of groundwater nitrate in different land use areas were domestic sewage and manure, followed by soil nitrogen, ammonia fertilizer, nitrate fertilizer and rainwater, and there were no significant spatial or seasonal variations. Combining δ15N-NO3-, δ18O-NO3- and δ37Cl results can increase the accuracy of traceability. Nitrification could be the most important nitrogen migration and transformation process, and denitrification did not significantly affected the isotopic composition of the nitrate. The SIAR model outputs revealed that the main nitrate pollution sources in groundwater and river water were domestic sewage and manure, accounting for 55.9%-61.0% and 22.6% (dry season), 50.3%-60.4% and 34.1% (transition season), 42.7%-47.6% and 35.6% (wet season 2016) and 45.9%-46.7% and 38.4% (wet season 2017), respectively. This work suggests that the random discharge and disposal of domestic sewage and manure should be the first target for control in order to prevent further nitrate contamination of the water environment.

Research Advances in Identifying Sulfate Contamination Sources of Water Environment by Using Stable Isotopes.

As the main anion of groundwater, the content of sulfate affects the drinking water safety and ecological security directly. In recent years, with the acceleration of industrialization and urbanization development, the problem of sulfate pollution in water environments is becoming more and more serious. It is critical to effectively identify the sulfate sources of water environment to ensure human health and the benign evolution of water environment. Due to its "fingerprints" feature, the sulfur and oxygen isotopes of SO42- have been widely used to identify sources of sulfate contamination in water environment. However, research advances in tracing sulfate contamination sources of water environment by using stable isotopes are rarely reported. This paper reviewed the research advances of sulfate isotope technology domestically and abroad, which was used to trace the sources of sulfate pollution in water environment, compared different pre-treatment methods for analyzing the δ34S and δ18O of sulfate, and compiled the ranges of typical values of δ34S and δ18O from different potential sources of sulfate contamination. In this review, the limitation of the technique in traceability of sulfate pollution was also discussed, and the future traceability techniques of sulfate pollution were prospected.

Tracing nitrate pollution sources and transformations in the over-exploited groundwater region of north China using stable isotopes.

Nitrate contamination in groundwater has become an environmental problem of widespread concern. In this study, we used environmental isotopes (δ15N-NO3- and δ18O-NO3-) and an isotope mixing model (SIAR) to identify the main sources of nitrate pollution, and factors controlling nitrate pollution, and to quantify the relative contributions of potential NO3- sources in an over-exploited groundwater region, north China. The results showed that human activities had dramatically increased the mean concentration of groundwater NO3- reaching 124.4 mg/L. In Hutuo River pluvial fan region, groundwater nitrate came from many kinds of pollution sources and the predominant sources were sewage and/or manure. Nitrification might be one of the most important nitrogen transformation processes and groundwater intensely exploited was a major inducing factor for the NO3- pollution. The highest contribution of groundwater NO3- was sewage and/or manure which the percent in the Hutuo River valley plain unit, upper pluvial fans of Hutuo River and central pluvial fans of Hutuo River was 54.9%, 55.0% and 61.8%, respectively, followed by soil N, NH4+ in fertilizer and rain, NO3- fertilizer, and NO3- in precipitation. We suggested that the local government must strengthen the sewage treatment for the collection of domestic sewage, and must prohibit over-exploitation of groundwater in order to prevent NO3- contamination of in groundwater.