Nitrate pollution in the shallow groundwater of a rapidly urbanizing coastal area: Insight from spatial-seasonal distribution and source identification in Xiamen, China

Affected by excessive fertilizer application and livestock breeding, the problem of nitrate pollution in the groundwater in the Mihe alluvial–diluvial fan area is becoming increasingly prominent, which poses a great threat to human production and life. Given this, the risk of nitrate pollution in the shallow groundwater of the Mihe alluvial–diluvial fan is evaluated by introducing a data envelopment analysis (DEA) method. Using this model, 28 groundwater sampling points are selected as the decision-making unit (DMU); the nitrogen and pesticide application rate, livestock and poultry stock, groundwater burial depth, aquifer water abundance, and vegetable planting area are taken as the model input; and the nitrate content is taken as the model output to quantitatively calculate the pollution risk index to form a spatial distribution map of pollution risk. The calculation using the model shows that the average pollution risk index of the study area is 0.382, the spatial variation is 1.12, the pollution risk index gradually decreases from south to north, and agricultural planting and livestock and poultry breeding are the main pollution sources. The calculation of nitrate pollution risk using this model not only enriches the nitrate pollution evaluation model but also provides a basis for further implementing the action of reducing fertilizer use by increasing its efficiency and strengthening the prevention of agricultural diffused pollution.

Purpose: The aim of the study was to examine impact of agricultural practices on nitrate pollution in groundwater in India Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: a significant environmental concern with far-reaching implications for human health, ecosystem integrity, and water resource management. It is evident that agricultural activities such as fertilizer application, irrigation methods, and land management practices play a pivotal role in exacerbating nitrate contamination of groundwater. The studies highlighted the complex interactions between agricultural activities and hydrological processes, elucidating the pathways through which nitrates migrate from soil to groundwater. Unique Contribution to Theory, Practice and Policy: Diffuse Pollution Theory, Hydrological Connectivity Theory & Sustainable Agriculture Theory may be used to anchor future studies on impact of agricultural practices on nitrate pollution in groundwater in India. Encourage the adoption of sustainable agricultural practices that minimize nitrate pollution while maintaining agricultural productivity. This includes promoting precision agriculture techniques, cover cropping, and integrated nutrient management systems to optimize fertilizer use and reduce nitrate leaching. Strengthen regulations and enforcement mechanisms to limit nitrate pollution from agricultural activities. This may include setting stringent water quality standards for nitrate concentrations in groundwater and implementing monitoring programs to assess compliance.

Nitrate pollution in groundwater has become a global concern. One of the most important issues in controlling the nitrate pollution of groundwater is to identify the pollution source quickly and accurately. In this review, we firstly summarized the isotopic background values of potential sources of nitrate pollution in groundwater in 17 provinces (cities, autonomous regions) and 29 study areas in China, which could provide the fundamental database for subsequent research. Secondly, we reviewed the research progress of nitrate isotopes combined with multiple tracers for tracing nitrate in groundwater, and discussed their applicable conditions, advantages, and disadvantages. We found that halides and microorganisms combined with nitrate isotopes could accurately trace the pollution sources of domestic sewage, excrement and agricultural activities. The combination of Δ17O and nitrate isotopes could effectively distinguish the source of atmospheric deposition of nitrate in groundwater. The combination of groundwater age and nitrate isotopes could further determine the time scale of nitrate pollution. In addition, we summarized the application cases and compared the characteristics of mass balance mixing model, IsoSource model, Bayesian isotope mixing model, and EMMTE model for quantitative identification of nitrate pollution in groundwater. For the complexity and concealment of groundwater pollution sources, the coupling of nitrate isotopes with other chemical and biological tracing methods, as well as the application of nitrate isotope quantitative models, are effective tools for reliably identifying groundwater nitrate sources and transformation processes.

On the use of coprostanol to identify source of nitrate pollution in groundwater

Effect of hydrogeological conditions and surface loads on shallow groundwater nitrate pollution in the Shaying River Basin: Based on least squares surface fitting model

Nitrate pollution in groundwater is a severe problem in Shimabara Peninsula, Nagasaki Prefecture, Japan. Previous studies have investigated water quality characteristics in the northern part of the peninsula and shown serious effects of nitrate pollution in the groundwater. The present study aimed to investigate the groundwater quality in the southern areas of the peninsula for improved understanding of the water quality status for the entire peninsula. Groundwater samples were collected at 56 locations in Minami-Shimabara City from 28 July to 4 August 2021. The spatial distribution of water quality constituents was assessed by Piper-trilinear and Stiff diagrams for major ion concentrations. One agricultural area in the western parts exceeded Japanese recommended standards for water. According to the Piper-trilinear diagram, 44 sampling sites (78.6%) were classified as alkaline earth carbonate type, nine sites (16.1%) as alkaline earth non-carbonate type, and three sites (5.3%) as alkaline carbonate type. Stiff diagrams displayed Ca-HCO3 water type for most of the sites. Na-HCO3 and Mg-HCO3 types were found in coastal areas. Principal component analyses showed that the first component corresponded to dissolved constituents in groundwater and denitrification, the second effects of ion exchange and low nitrate pollution, and the third effects of severe nitrate pollution. Hierarchical cluster analysis was used to classify the groundwater into five groups. The first group included sites with relatively high nitrate concentration. The second group had relatively low ion concentration, distributed from center to eastern parts. The third group included intermediate ion concentration, distributed at lower altitudes along the coastal line. The fourth and fifth groups had a higher ion concentration, especially characterized by high sodium and bicarbonate concentration.

Nitrate pollution has become an environmental problem of global concern. One effective way for controlling the nitrate pollution of water is to identify the pollution source and reduce the input of nitrate. This study traces and quantifies the sources of nitrate contamination to groundwater and surface water in the northeastern suburbs of Beijing, where an emergency groundwater source zone is located. Nitrogen and oxygen stable isotope analysis, geospatial analysis techniques, principal component analysis, correlation analysis, and a Bayesian isotope mixing model were used to achieve our goals. The results show that the main sources of nitrate pollution in groundwater were manure and sewage (M&S) (42.6 %) > soil nitrogen (SN) (26.6 %) > in fertilizer and rain (NHF&R) (24.5 %) > fertilizer (NOF) (5.0 %) > in atmospheric deposition (NAD) (1.3 %), and main sources of nitrate in surface water were M&S (28.8 %) > SN (20.4 %) > NAD (19.8%) > NOF (16.5%) > NHF&R (14.5 %). Due to the high permeability of the aquifer in the study area, there was a strong hydraulic connection between groundwater and surface water. The discharge of treated wastewater (reclaimed water) into the mostly dried river channel in the study area might aggravate nitrate pollution in the groundwater.

Quantifying nitrate pollution sources of shallow groundwater and related health risks based on deterministic and Monte Carlo models: A study in Huaibei mining area, Huaibei coalfield, China

An overview of in-situ remediation for nitrate in groundwater

Abstract. Contamination of groundwater with nitrate poses a major health risk to millions of people around Africa. Assessing the space–time distribution of this contamination, as well as understanding the factors that explain this contamination, is important for managing sustainable drinking water at the regional scale. This study aims to assess the variables that contribute to nitrate pollution in groundwater at the African scale by statistical modelling. We compiled a literature database of nitrate concentration in groundwater (around 250 studies) and combined it with digital maps of physical attributes such as soil, geology, climate, hydrogeology, and anthropogenic data for statistical model development. The maximum, medium, and minimum observed nitrate concentrations were analysed. In total, 13 explanatory variables were screened to explain observed nitrate pollution in groundwater. For the mean nitrate concentration, four variables are retained in the statistical explanatory model: (1) depth to groundwater (shallow groundwater, typically < 50 m); (2) recharge rate; (3) aquifer type; and (4) population density. The first three variables represent intrinsic vulnerability of groundwater systems to pollution, while the latter variable is a proxy for anthropogenic pollution pressure. The model explains 65 % of the variation of mean nitrate contamination in groundwater at the African scale. Using the same proxy information, we could develop a statistical model for the maximum nitrate concentrations that explains 42 % of the nitrate variation. For the maximum concentrations, other environmental attributes such as soil type, slope, rainfall, climate class, and region type improve the prediction of maximum nitrate concentrations at the African scale. As to minimal nitrate concentrations, in the absence of normal distribution assumptions of the data set, we do not develop a statistical model for these data. The data-based statistical model presented here represents an important step towards developing tools that will allow us to accurately predict nitrate distribution at the African scale and thus may support groundwater monitoring and water management that aims to protect groundwater systems. Yet they should be further refined and validated when more detailed and harmonized data become available and/or combined with more conceptual descriptions of the fate of nutrients in the hydrosystem.

Effect of hydrogeological conditions on groundwater nitrate pollution and human health risk assessment of nitrate in Jiaokou Irrigation District

Optimizing nitrogen-water use efficiency for nitrate reduction: spatiotemporal strategies and potential of climate-smart kiwifruit agriculture across SSP scenarios.

Nitrate pollution of groundwater has become a global concern as it can affect drinking water quality and human health. In this paper, an extensive hydrochemical investigation was performed to assess the spatial distribution, source identification, and health risk of groundwater nitrate pollution in the Subei Lake basin. The prevalent pollutant, nitrate (NO3-), was identified based on descriptive statistical method and box plots, and most of the other parameters of groundwater samples met water standards and can be used for drinking purpose. The results showed that nearly 23.53% of groundwater samples displays the NO3- concentrations higher than the limit of 50 mg/L recommended by the World Health Organization, and the highest nitrate content (199 mg/L) is mainly distributed around the Mukai Lake. Piper triangle diagram demonstrated that the dominated anions of hydrochemical types exhibit a gradual evolving trend from HCO3- to SO42- and Cl- with increasing nitrate concentration. The correspondence analysis suggested that agricultural activities are identified as the most possible source of nitrate contamination, while the higher content of other parameters in individual groundwater samples may be controlled by natural factors. The impacts of pollutant NO3- on human health were quantified using human health risk assessment method, and results showed that the order of non-carcinogenic health risk values through drinking water intake is Infants>Children>Adult males>Adult females, and 65%, 53%, 41%, and 35% of samples exceed the acceptable risk level (hazard quotient=1), respectively. The main findings obtained from this study can provide valuable insight on drinking water safety and groundwater pollution prevention.

Inverse method using boosted regression tree and k-nearest neighbor to quantify effects of point and non-point source nitrate pollution in groundwater

Nitrate pollution of groundwater is often attributed to excess fertilisation in agriculture. Low quality water, enriched by nitrate and other pollutants percolates down from the root zone through the unsaturated zone to the water table. Accordingly, the vadose zone holds the footprint of all possible groundwater pollution events occurring at the land surface before the pollution imprint arrives in the groundwater. Here we present a study were detailed long-term monitoring of the unsaturated zone reveals the groundwater pollution potential of various representative agricultural setups over the island of Malta. Malta is a semi-arid island in the Mediterranean Sea where groundwater, which is the only natural freshwater resource, suffers from nitrate pollution due to the intensive agricultural landscape. A national monitoring network, comprising of 16 Vadose zone Monitoring Systems (VMS) were installed under the different agricultural setups which represent Malta’s main agricultural practices. The VMS enables continuous monitoring of variations in the unsaturated zone water content, as indication to percolation processes, and frequent sampling of the sediment pore water for chemical analysis and characterisation of pollutant transport across the unsaturated zone.  Results show that the mean nitrate concentrations in the vadose zone underlying fields of potato, forage, mixed outdoor vegetables, greenhouses, vineyards, and orchards were 923 mg/L, 673 mg/L, 416 mg/L, 416 mg/L, 252 mg/L and 33.6 mg/L, respectively. Spatial distribution of the different agricultural setups shows that forage and potato fields are among the most common agricultural setups, with higher occurrence in the central and eastern areas of the island (>50% of the agricultural land area). This agricultural land use distribution spatially links to the high average nitrate concentrations in groundwater under those fields (ranging from 75 to 200 mg/L). On the other hand, lower proportions of potato and wheat fields are cultivated in the north-western areas (25-50% of the total agricultural land area). In the north-western areas, a clay layer situated in the unsaturated zone creates a shallow perched aquifer with a rock matric thickness ranging from 20 to 50 m, which impedes water fluxes from the agricultural fields to the main groundwater system below. The mean nitrate concentrations in the shallow perched aquifer are relatively high ranging from 200 to 350 mg/L due to the aquifer’s low water storage. On the other hand, nitrate concentrations in the regional aquifer underlying the perched aquifer are relatively low ranging from 25 to 100 mg/L.In conclusion, the results show that potato and wheat fields are likely to have the greatest impact on nitrate pollution in the vadose zone and eventual groundwater nitrate contamination. Furthermore, these agricultural land uses are among the most common land uses cultivated in Malta. This implies the significant potential spatial impact of potato and wheat fields on groundwater nitrate pollution. With data being made available from this vadose zone monitoring network we can increasingly understand the pollution potential of different agricultural land uses on groundwater.