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To assess groundwater nitrate contamination and its human health risks, 489 unconfined groundwater samples were collected and analyzed from Zhangjiakou, northern China. The spatial distribution of principle hydrogeochemical results showed that the average concentrations of ions in descend order was HCO3−, SO42−, Na+, Ca2+, Cl−, NO3−, Mg2+ and K+, among which the NO3− concentrations were between 0.25 and 536.73 mg/L with an average of 29.72 mg/L. In total, 167 out of 489 samples (~ 34%) exceeded the recommended concentration of 20 mg/L in Quality Standard for Groundwater of China. The high NO3− concentration groundwater mainly located in the northern part and near the boundary of the two geomorphic units. As revealed by statistical analysis, the groundwater chemistry was more significantly affected by anthropogenic sources than by the geogenic sources. Moreover, human health risks of groundwater nitrate through oral and dermal exposure pathways were assessed by model, the results showed that about 60%, 50%, 32% and 26% of the area exceeded the acceptable level (total health index>1) for infants, children, adult males and females, respectively. The health risks for different groups of people varied significantly, ranked: infants> children> adult males>adult females, suggesting that younger people are more susceptible to nitrate contamination, while females are more resistant to nitrate contamination than males. To ensure the drinking water safety in Zhangjiakou and its downstream areas, proper management and treatment of groundwater will be necessary to avoid the health risks associated with nitrate contamination.

To assess the loading profiles of groundwater nitrate (NO3−) and fluoride (F−), their spatial distributions, geochemistry and associated health risks were determined for 131 groundwater samples from eastern (ESR), central (CSR) and Trans-Indus Salt Ranges (TSR) in Pakistan. Groundwater NO3− concentrations were 0.2–308 mg/L (mean 59 mg/L) in ESR, 2.7–203 mg/L (mean 73 mg/L) in CSR and 1.1–259 mg/L (mean 69 mg/L) in the TSR. Forty-one %, 57% and 36% of the ESR, CSR and TSR samples, respectively, exceeded the WHO and Pak-NEQs permissible limit of 50 mg/L NO3−. Likewise, groundwater F− concentrations ranged from 0.1–1.8 mg/L (mean 0.6 mg/L), 0.1–2.7 mg/L (mean 0.9 mg/L) and 0.3–2.5 mg/L (mean 1.6 mg/L) mg/L in the ESR, CSR and TSR sites, respectively. In this case, 3%, 17% and 27% of the ESR, CSR and TSR samples, respectively, exceeded the WHO and Pak-NEQs permissible limit of 1.5 mg/L F. Oxidation of coal and coal waste resulted in the release of NO3− to groundwater. By contrast, enrichment of F− in groundwater was due to dissolution and cation exchange processes. Elevated values of the Higher Pollution Index (PI) and Health Risk Index (HRI) reflect a non-acceptable carcinogenic risk for drinking water NO3− and F− which should be addressed on a priority basis to protect human health.

An increased nitrate (NO3−) concentration in groundwater has been a rising issue on a global scale in recent years. Different consumption mechanisms clearly illustrate the adverse effects on human health. The goal of this present study is to assess the natural and anthropogenic NO3− concentrations in groundwater in a semi arid area of Rajasthan and its related risks to human health in the different groups of ages such as children, males, and females. We have found that most of the samples (n = 90) were influenced by anthropogenic activities. The background level of NO3− had been estimated as 7.2 mg/L using a probabilistic approach. About 93% of nitrate samples exceeded the background limit, while 28% of the samples were beyond the permissible limit of 45 mg/L as per the BIS limits. The results show that the oral exposure of nitrate was very high as compare to dermal contact. With regard to the non-carcinogenic health risk, the total Hazard Index (HITotal) values of groundwater nitrate were an average of 0.895 for males, 1.058 for females, and 1.214 for children. The nitrate health risk assessment shows that about 38%, 46%, and 49% of the samples constitute the non-carcinogenic health risk to males, females, and children, respectively. Children were found to be more prone to health risks due to the potential exposure to groundwater nitrate.

The rapid increase in demand and consumption of groundwater in the past few decades has imposed colossal pressure on the stakeholders responsible for groundwater management. Assessment of groundwater vulnerability and knowledge about hydrogeological settings are crucial for a particular region, especially at a local scale, to manage groundwater resources effectively. The present study aimed to develop a modified DRASTIC model to demarcate groundwater vulnerability zones based on experimental analysis of field samples to make the model more feasible at local scale. Four techniques were implemented in this study to determine groundwater vulnerability zones: (a) DRASTIC; (b) DRASTIC–AHP (analytic hierarchy process); (c) Modified DRASTIC; (d) Modified DRASTIC–AHP. The best groundwater vulnerability model was determined based on validation results with groundwater nitrate concentration. The comparative assessment showed that the Modified DRASTIC–AHP outperformed the other models. More than 50% of the study area was classified as ‘high’ (33.06%) and ‘very high’ (21.31%) groundwater vulnerability zones. The vulnerability map shows that high vulnerable zones dominate in the northwestern part and in some portions of the floodplain near central part of the study area. The results of this study envision that inclusion of experimentally derived parameters can be used to modify the conventional DRASTIC model and obtain better results at local scale.

Groundwater nitrate is a concern in the Great Lakes Basin (GLB) of North America. Concentrations vary based on hydrogeologic setting and surface contamination pressures. The first objective of this study was to characterize groundwater nitrate trends in a spatial and temporal context across three unique hydrogeologic and land-use settings in the GLB, at research sites in Norfolk, Guelph, and Acton, in southwestern Ontario, Canada. The second objective was to compare groundwater nitrate trends at the sites to determine the potential influence of hydrogeologic setting on seasonal nitrate variability. Groundwater nitrate-N concentrations and additional parameters were measured at 25 monitoring wells at the three sites, once every 2 months from June 2014 to July 2016 (13 sampling events). The dominant land-use pressure at all three sites is agricultural; however, the type of agriculture and the amount of natural and urban land vary. The Guelph site had the highest nitrate concentrations, while the Acton and Norfolk mean concentrations were similar. Seasonally, nitrate was found to be highest during the spring and early summer periods at all three sites. Several monitoring locations had cyclical patterns in nitrate concentrations, while others remained consistent except for isolated peak events. Comparison of multiple years reveals the expression of a relationship between climatic conditions during winter months and nitrate concentrations, indicating the importance of antecedent conditions to groundwater nitrate concentrations. The combination of climatic conditions, land-use pressure, and hydrogeologic setting plays an important role in the characteristics of groundwater nitrate time-series trends.

The 2016 Kumamoto earthquake had a significant impact on groundwater levels and quality. In some areas, the groundwater level increased significantly due to the release of groundwater from upstream mountainous regions. Conversely, the groundwater level in other areas greatly decreased due to the creation of new fracture networks by the earthquake. There were also significant changes in certain groundwater quality variables. In this study, we used clustering based SOM (self-organizing maps) analysis to improve the understanding of earthquake effects on groundwater quality. We were especially interested in effects on groundwater used for drinking purposes and in nitrate concentration. For this purpose, we studied groundwater nitrate (NO3&minus, + NO2&minus, &ndash, N) concentrations for the period 2012&ndash, 2017. Nitrate concentration changes were classified into seven typical SOM clusters. The clusters were distributed in three representative geographical regions: a high concentration region (&gt, 4 mg/L), a low concentration region (&lt, 1.6 mg/L) with minimal anthropogenic loading area, and an intermediate concentration region (2&ndash, 4 mg/L). Depending on these regions, the nitrate concentration changes just before and after the earthquake had both increasing and decreasing trends between 2015&ndash, 2017. This points to complex physiographical relationships for release of stored upstream groundwater, promotion of infiltration of shallow soil water/groundwater, and nitrate concentration as affected by earthquakes. We present an analysis of these complex relationships and a discussion of causes of nitrate concentration changes due to earthquakes.

Nitrate as an important water pollutant, causing eutrophication was analyzed in Pakistan at different water sources (hand pump (HP), bore hole (BH) and tube well (TW)) to assess the contamination level caused by NO3-. NO3- concentrations in the HP water samples were 31 mg L-1 to 59 mg L-1, in BH 20 mg L-1 to 79 mg L-1 while in TW water samples it was between 29 to 55 mg L-1. The association of NO3- with other selected parameter in groundwater can be determined by using statistical approaches. Different physicochemical parameters (pH, electrical conductivity (EC), temperature and dissolved oxygen (DO)) were studied in groundwater samples of the research district. The Pearson correlation coefficient (r) for groundwater characteristics were calculated. Hierarchical Cluster Analysis (HCA) was used to categorize samples based on their groundwater quality similarities and to find links between groundwater quality factors. The key relationship of the groundwater for HP samples on EC and TDS (r = 1) had a great correlation, while all other parameters correlations were lower (r = 0.40), BH's parameters on WT and WSD (r = 0.57), WT and pH (r = 0.57), EC and DO (r = 0.50), DO and TDS (0.50), EC and TDS (r = 1) had a quite high correlation, while all other parameters correlations were less than (r = 0.40), on the other hand, tube well parameters on TDS and EC (r = 1) had a perfect correlation, DO and pH (r = 0.75) parameters correlations were less than (r = 0.40).

High concentrations of nitrate in groundwater pose a threat to human health. To quantify groundwater nitrate pollution in China's Changchun New District and evaluate its human health risks, 98 grou...

Acid rain with a relatively high concentration of ammonium and nitrate can accelerate rock weathering. However, its impact on groundwater nitrate is uncertain. This study evaluated the dual isotopic composition of nitrate (δ15N-NO3- and δ18O-NO3-) from precipitation to groundwater in a rural mountainous area affected by acid rain. The average concentration for NH4+ is 1.25 mg/L and NO3- is 2.59 mg/L of acid rain. Groundwater NO3- concentrations ranged from 4+ concentrations ranged from 0.06 to 0.28 mg/L. The results show that groundwater δ18O-NO3- values (-4.7‰ to +4.2‰) were lower than the values of rainfall δ18O-NO3- (+24.9‰ to +67.3‰), suggesting that rainfall NO3- contributes little to groundwater NO3-. Groundwater δ15N-NO3- values (+0.1‰ to +7.5‰) were higher than the values of δ15N-NO3- derived from the nitrification of rainfall NH4+ (less than -4.7‰ in the study area), suggesting that nitrification of rainfall NH4+ also contributes little to groundwater NO3-. This implies that rainfall NO3- and NH4+ have been utilized. The dual isotopic composition of nitrate shows that baseline groundwater NO3- is derived mainly from nitrification of soil nitrogen. The denitrification process is limited in the groundwater system. This study shows that the rainfall NO3- and NH4+ contribute little to groundwater NO3-, improving the understanding of the nitrogen cycle in areas with a high concentration of NH4+ and NO3- in rainfall.

At present, groundwater nitrate pollution in China is serious. The use of microorganisms for biological denitrification has been widely applied, and it is a universal and efficient in situ groundwater remediation technique, but this approach is influenced by many factors. In this study, glucose was adopted as the carbon source, four different concentrations of 0, 2, 5 and 10 g/L were considered, and natural groundwater with a nitrate concentration of 300.8 mg/L was employed as the experimental solution. The effect of the carbon source concentration on the nitrate removal rate in groundwater was examined through heterotrophic anaerobic denitrification experiments. The results showed that the nitrate removal rate could be improved by the addition of an external carbon source in the process of biological denitrification, and an optimal concentration was observed. At a glucose concentration of 2 g/L, the denitrification effect was the best.

Identification of nitrate sources and fate in basins with complex backgrounds is essential for understanding the controlling factors of regional groundwater nitrates pollution and its prevention. In this study, hydrochemistry, the concentration of dissolved nitrogenous species, multiple isotopes (δD-H2O, δ18O-H2O, δ15N-NH4+, δ15N-NO3- and δ18O-NO3-) and Bayesian model (SIMMR) were applied to identify the nitrate sources and major transformation processes under different land uses and complicated hydrological conditions in Qingyi River basin with an area of 8700km2, east China. A total of 28 groundwater samples of forest-dominated areas in mountainous, forest-farmland in piedmont, and farmland-residential in plain were collected in Jul 2019. The results showed that concentrations of N species, hydrochemistry and isotopic composition had significantly differences under distinctive backgrounds generally. In mountainous area, nitrate concentrations were as low as of 1.9-6.3mg/L, and low TDS (23.6-60.8mg/L), depleted δD-H2O(-43.3±6.7‰) and δ18O-H2O (-7.2±1.0‰) were observed with δ15N-NO3- values of +1.1±0.8‰, which implies that 18.4% and 81.6% of groundwater nitrate were from soil organic nitrogen (SON) and atmosphere precipitation (AP), respectively. In piedmont areas, moderate nitrate(1.0-35.6mg/L), TDS(91.6-253.9mg/L), and relative enriched δD-H2O(-40.1±4.1‰), δ18O-H2O(-6.7±0.5‰) were detected with δ15N-NO3- values +2.8±2.2‰, and the SIMMR model suggested 37.3% nitrates were derived from SON and 31.1% from chemical fertilizers (CF) .With increasing of residential areas, higher TDS(186.5-643.8mg/L) and nitrate(5.4-58.5mg/L) as well as enriched δD-H2O(-38.6±6.5‰) and δ18O-H2O(-6.4±0.7‰) indicated higher anthropogenic inputs in plain areas with δ15N-NO3- values +6.3±2.3‰, with the origins of 31.8% SON and 30.9% manure&sewage (M&S). From the recharge and runoff areas to the discharge areas, major nitrate sources altered from SON to CF and M&S due to variation of land uses, and the denitrification became the dominant process rather than nitrification owing to gradually decreasing oxidization condition. Incomplete nitrification was proved by negative correlations of δ15N-NH4+ and δ15N-NO3- in recharge and runoff areas. And the occurrence of obvious denitrification was deduced by low redox parameters and major ions in discharge zone. Finally, a conceptual model was proposed to reveal the pattern of groundwater nitrate sources and fate in Qingyi River Basin. This study provided a reliable and integrated approach for recognition and understanding of the nitrate sources and fate in large watershed under complicated land-uses and hydrological conditions. Keywords: groundwater; nitrate, sources identification; δ15N-NH4+; Qingyi River basin

Access to safe drinking water is one of the fundamental human rights and an important part of healthy living. This study considered various land use methods, used geostatistical analysis, and triangular random model to explore nitrogen pollution and estimate its potential risk to human health for local populations in Songnen Plain of Northeast China and recognize parameter uncertainties. Nitrate concentrations in groundwater ranged from 0.01 to 523.45 mg/L, more than 72.35% of the samples exceeded Grade III threshold (20 mg/L of N) as per China's standard, and nitrate nitrogen content is greater than 20 mg/L accounted for around 60% of the research area, mainly distributed in the eastern and central high plain area. The nitrate-nitrogen content of groundwater in the town land was significantly higher than that of agricultural land, and the ammonia nitrogen content was conversely. The townland's risk value was two times that of agricultural land, considering different land use methods would avoid overestimating or underestimating regional risk value. Non-carcinogenic risks (HI) of two land use were above the safety level (i.e., HI > 1), suggesting that groundwater nitrate would have significant health effects on the age groups, and further threaten children. There was a wide range of fluctuations in the uncertainty of nitrogen concentration and model evaluation parameters; triangular random model was more sensitive to data changes, which could reduce the uncertainty. The contribution rate of nitrate-nitrogen concentration to risk was above 90%, which explained the need for random sampling to improve the evaluation results reliability. The findings in this paper will provide new insight for solving uncertainties in water safety management.

Nitrate pollution of groundwater through spatial models is investigated in this paper by using a sample of nitrate values at monitoring wells using the data from four seasons of a year, in which data are sparse. Two spatial modelling strategies are formulated at two levels, in which Strategy 1 comprises: three variations of kriging-based models (ordinary kriging, simple kriging and universal kriging), which are constructed at Level 1 to predict nitrate concentrations; and a Multiple Co-Kriging (MCoK) model is used at Level 2 to enhance the accuracy of the predictions. Strategy 2 is also at two levels but employs Indicator Kriging (IK) at Level 1 as a probabilistic spatial model to predict areas at risk of exceeding two thresholds of 37.5 mg/L and 50 mg/L of nitrate concentration, and Multiple Co-Indicator Kriging (MCoIK) at Level 2 for a better accuracy. The improvements at Level 2 for both strategies are remarkable and hence they are used to gain an insight into inherent problems. The results of a study delineate areas with excessive nitrate concentrations, which are in the vicinity of urban areas and hence reflect poor planning practices since the 1990s. The results further reveal the patterns on sensitivities to seasonal variations driven by aquifer recharge and strong dilution processes in spring times; and on the role of pumpage impacting aquifers giving rise to possible hotspots of nitrate concentrations.

4th International Conference on Recycling and Reuse (R and R) / Workshop on ERA-NET -- OCT 24-26, 2018 -- Istanbul, TURKEY WOS: 000504452200040 Legislative measures like the Waste Framework Directive enforce the European Union member countries to increase the re-use of waste and/or the extraction of secondary raw materials. The Nitrate Directive requires the implementation of relevant measures to decrease groundwater nitrate concentration. This study evaluated the potential use of two dominant organic wastes in Turkey, tea factory waste and hazelnut husk, as potential carbon sources to stimulate nitrate removal in low cost permeable reactive barrier (PRB) systems. Leaching and batch experiments were carried out to determine the dissolution level and the degree of the heterotrophic denitrification process. Both organic substrates and inherent microbial communities supported the reduction of nitrate (NO 3-) to nitrogen (N) gases. However, the percentage of organic substrate played an important role in the removal of nitrogenous compounds. The highest nitrate removal efficiencies were observed in flasks with 40% tea factory waste and 100% hazelnut husk, which were 64% and 97%, respectively. The corresponding zero-order reaction rates and half-lives were 3.03 mg N L-1 d(-1) and 6 d(-1) for tea factory waste and 5.17mg N L-1 d(-1) and 4.4 d(-1) for hazelnut husk. Of particular note, both wastes supported the denitrifying populations at such an excellent level that 99% of the nitrate was removed in the column study for a duration of 51 d under low and high flow rate conditions. Thus, the release of nitrate, ammonium and total organic carbon from wastes was not limiting its suitability in PRB systems. Istanbul Univ, Environm Engn Dept, Ecosafefarming Project Program of the Turkish Institution of Higher Education; Scottish Funding Council GRPE; University of Strathclyde The principal author gratefully acknowledges the financial support by the Program of the Turkish Institution of Higher Education. The authors would like to acknowledge the support of the Scottish Funding Council GRPE and the University of Strathclyde for the support of infrastructure for the research.

Background Nitrate is one of the most common chemical contaminants of groundwater, and it is an important unqualified factor of rural groundwater in Yantai. In order to assess the risk of exposure to drinking water nitrate for adults and juveniles, in recent years, we monitored the nitrate concentrations in rural drinking water,a model was also used to assess the human health risk of nitrate pollution in groundwater. Methods From the year 2015 to 2018, the drinking water in rural areas of Yantai was tested according to the “Sanitary Standard for Drinking Water” (GB5749–2006). The principal component analysis was used to analyze the relationship between groundwater chemicals and nitrate. The model was used to assess human health risks of groundwater nitrate through the drinking water and skin contact. Results A total of 2348 samples were tested during the year 2015–2018.Nitrate and total dissolved solids, total hardness, chloride are all relevant, the above indicators may come from the same source of pollution; The median nitrate content (CEXP50) was 17.8 mg / L; the risk of exposure in each group was ranked as: Juveniles > Adult female > Adult male;the median health risk (HQ50) for minors and adults exceed 1. Conclusions The concentrations of nitrate is stable and does not change over time. The high concentration of nitrate in rural areas of Yantai may be the result of the interaction of fertilizers and geological factors. The risk of exposure to nitrate in juveniles and adults is above the limit, so it is necessary to be on the alert for the high levels of nitrate.

The establishment of the sources and driven-forces of groundwater nitrate pollution is of paramount importance, contributing to agro-environmental measures implementation and evaluation. High concentrations of nitrates in groundwater occur all around the world, in rich and less developed countries.In the case of Spain, 21.5% of the wells of the groundwater quality monitoring network showed mean concentrations above the quality standard (QS) of 50 mg/l. The objectives of this work were: i) to predict the current probability of having nitrate concentrations above the QS in Andalusian groundwater bodies (Spain) using past time features, being some of them obtained from satellite observations; ii) to assess the importance of features in the prediction; iii) to evaluate different machine learning approaches (ML) and feature selection techniques (FS).Several predictive models based on an ML algorithm, the Random Forest, were used, as well as, FS techniques. 321 nitrate samples and respective predictive features were obtained from different groundwater bodies. These predictive features were divided into three groups, regarding their focus: agricultural production (phenology); livestock pressure (excretion rates); and environmental settings (soil characteristics and texture, geomorphology, and local climate conditions). Models were trained with the features of a year [YEAR (t0)], and then applied to new features obtained for the next year – [YEAR(t0+1)], performing k-fold cross-validation. Additionally, a further prediction was carried out for a present time – [YEAR(t0+n)], validating with an independent test. This methodology examined the use of a model, trained with previous nitrates concentrations and predictive features, for the prediction of current nitrates concentrations based on present features. Our findings showed an improvement in the predictive performance when using a wrapper with sequential search for FS when compared to the use alone of the Random Forest algorithm. Phenology features, derived from remotely sensed variables, were the most explanative features, performing better than the use of static land-use maps or vegetation index images (e.g., NDVI). They also provided much more comprehensive information, and more importantly, employing only extrinsic features of groundwater bodies.

The pollution of nitrate (NO3-) in groundwater has become an environmental problem of general concern and requires immediate remediation because of adverse human and ecological impacts. NO3- removal from groundwater is conducted mainly by chemical, biological, and coupled methods, with the removal efficiency of NO3- considered the sole performance indicator. However, in addition to the harmless form of N2, the reduced NO3- could be transformed into other intermediates, such as nitrite (NO2-), nitrous oxide (N2O), and ammonia (NH4+), which may have direct or indirect negative impacts on the environment. Therefore, increasing N2 selectivity is a significant challenge in reducing NO3- in groundwater, which seriously impedes the large-scale implementation of available remediation technologies. In this work, we comprehensively overview the most recent advances in N2 selectivity regarding the understanding of emerging groundwater NO3- removal technologies. Mechanisms of by-product production and strategies to enhance the selective reduction of NO3- to N2 are discussed in detail. Furthermore, we proposed topics for further research and hope that the total environmental impacts of remediation schemes should be evaluated comprehensively by quantifying all potential intermediate products, and promising strategies should be further developed to enhance N2 selectivity, to improve the feasibility of related technologies in actual remediation.

In the present study, we used a variance decomposition based global sensitivity index to evaluate the sensitivity of input variables and their contribution for non-carcinogenic health risks via intake and dermal pathways. Groundwater samples were collected from an industrial sector (Tiruppur region) of south India during the month of January 2020. These samples were analysed for nitrate, which varied from 10 to 290 mg L−1 having the mean of 87 mg L−1. Nearly 58% of the samples surpassed the permissible limit (45 mg L−1) defined by the World Health Organization. Total hazard index (THI) ranged from 0.29 to 8.52 for children, 0.28 to 8.26 for women, and 0.24 to 6.99 for men. The first-order effect (FOE) and second-order effect (SOE) were derived for the three different age groups using Sobol sensitivity approach. The FOE scores showed that nitrate concentration in groundwater is the most sensitive parameter followed by exposure frequency for children, men and women via oral pathway. The SOE scores showed that nitrate concentration along with ingestion rate had greater sensitiveness in the oral input model. The higher SOE was obtained for the interaction of nitrate with skin surface area for children via dermal pathway, but it was not significant for women and men. These results suggest that epidemiology due to nitrate risk should be studied taking into account of concentration of nitrate, exposure frequency, fraction of contact and body weight. Additionally, ingestion rate and skin surface area were considered for the assessment of health risks for children.

Elevated levels of nitrate in groundwater are an important concern for health and the environment. The overapplication of nitrogen (N) fertilizer to croplands is one of the major sources of high nitrate content in groundwater. In this study, we analyse the nitrate concentrations in Korean groundwater based on data from groundwater quality monitoring wells (n=1,022–2,072), which were sampled twice annually over a recent 13-year analysis period (2001–2013). We report that groundwater nitrate levels are decreasing, despite steadily increasing groundwater use. The maximum nitrate concentration decreased from 168.91 to 48.11 mg/L, while the mean values also show a gradual decreasing trend. Nonparametric Mann-Kendall tests on nitrate concentrations also confirm the decreasing trend. The nitrate decrease is more clearly evident in agricultural groundwater as compared to domestic and drinking groundwaters. This decrease of nitrate in groundwater coincides with a large decline in N fertilizer application due to reduced cropland areas, more sustainable agricultural practices, and progressive improvement of sewage disposal services. This study proposes that the long-term adoption of best practices in agriculture has had a positive impact on groundwater nitrate control.