Shift of nitrate sources in groundwater due to intensive livestock farming on Jeju Island, South Korea: With emphasis on legacy effects on water management

Groundwater hydrochemistry, source identification and health assessment based on self-organizing map in an intensive mining area in Shanxi, China

The Changzhi Basin in Shanxi is renowned for its extensive mining activities. It's crucial to comprehend the spatial distribution and geochemical factors influencing its water quality to uphold water security and safeguard the ecosystem. However, the complexity inherent in hydrogeochemical data presents challenges for linear data analysis methods. This study utilizes a combined approach of self-organizing maps (SOM) and K-means clustering to investigate the hydrogeochemical sources of shallow groundwater in the Changzhi Basin and the associated human health risks. The results showed that the groundwater chemical characteristics were categorized into 48 neurons grouped into six clusters (C1-C6) representing different groundwater types with different contamination characteristics. C1, C3, and C5 represent uncontaminated or minimally contaminated groundwater (Ca-HCO3 type), while C2 signifies mixed-contaminated groundwater (HCO3-Ca type, Mixed Cl-Mg-Ca type, and CaSO4 type). C4 samples exhibit impacts from agricultural activities (Mixed Cl-Mg-Ca), and C6 reflects high Ca and NO3- groundwater. Anthropogenic activities, especially agriculture, have resulted in elevated NO3- levels in shallow groundwater. Notably, heightened non-carcinogenic risks linked to NO3-, Pb, F-, and Mn exposure through drinking water, particularly impacting children, warrant significant attention. This research contributes valuable insights into sustainable groundwater resource development, pollution mitigation strategies, and effective ecosystem protection within intensive mining regions like the Changzhi Basin. It serves as a vital reference for similar areas worldwide, offering guidance for groundwater management, pollution prevention, and control.

Tracing the impacts of ecological water replenishment on the sources and transformation of groundwater nitrate through isotope and microbial analysis

Ecological water replenishment (EWR) changes the recharge conditions, flow fields, and physicochemical properties of regional groundwater. However, the resulting impacts on mechanisms regulating the sources and transformation of groundwater nitrate remain unclear. This study investigated how EWR influences the sources and transformation processes of groundwater nitrate using an integrated approach of Water chemistry analysis and stable isotopes (δ15N-NO3- and δ18O-NO3-) along with microbial techniques. The results showed that groundwater NO3-N decreased from 12.98 ± 7.39 mg/L to 7.04 ± 8.52 mg/L after EWR. Water chemistry and isotopic characterization suggested that groundwater nitrate mainly originated from sewage and manure. The Bayesian isotope mixing model (MixSIAR) indicated that EWR increased the average contribution of sewage and manure sources to groundwater nitrate from 46 % to 61 %, whereas that of sources of chemical fertilizer decreased from 43 % to 21 %. Microbial community analysis revealed that EWR resulted in a substantial decrease in the relative abundance of Pseudomonas spp denitrificans, from 13.7 % to 0.6 %. Both water chemistry and microbial analysis indicated that EWR weakened denitrification and enhanced nitrification in groundwater. EWR increases the contribution of nitrate to groundwater by promoting the release of sewage and feces in the unsaturated zone. However, the dilution effect caused by EWR was stronger than the contribution of sewage and fecal sources to groundwater nitrate. As a result, EWR helped to reduce groundwater nitrate concentrations. This study showed the effectiveness of integrated isotope and microbial techniques for delineating the sources and transformations of groundwater nitrate influenced by EWR.

Implication of self-organizing map, stable isotopes combined with MixSIAR model for accurate nitrogen control in a well-protected reservoir

Nitrogen pollution and eutrophication in reservoirs is a global environmental geochemical concern. Occasional algal blooms still exist in reservoirs that have undergone pollution treatment. The lack of quantitative evidence of nitrogen sources and fate limits long-term stable ecological safety management. This work applied an approach integrated zonal mapping, stable isotopes (δ18OH2O, δ15Nnitrate, δ18Onitrate, and δ13C-DIC) and a Bayesian isotope model to analyze regional and seasonal differences in the contribution and sources of nitrogen to a well-protected reservoir. The values of δ18Onitrate and the positive relationship between NO3- and δ13C-DIC suggested that nitrification was the primary NO3- production in the rivers. While Denitrification was present at only a few sites. Results of the MixSIAR model coupled the NO3-/Cl- indicator revealed that the domestic sewage contributed high riverine NO3- loading (68.6 ± 10.6 %) in the dry season. In the wet season, the main nitrate sources of upper watershed were ammonia and carbamide fertilizers (47.5 % and 40.3 %). While the domestic sewage was still the major contributor of downstream region (a dense residential area), indicating possible problems with rainwater and sewage drainage networks. The results implied that the colleting and treatment of sewages were the priority in downstream region, and non-point source pollution control and wastewater treatment plant upgrading were essential to control nitrate pollution in the two upstream regions. These findings provide new insights into precise nitrogen pollution traceability and identification of treatment priorities in the sub-region, and promote the management other well-protected watershed in similar need of further nitrogen contamination control.

Impact of typhoons on anthropogenic nitrogen sources in Lake Sihwa, South Korea

This study investigated the nitrate dual isotopic compositions (δ15NNO3 and δ18ONO3) of water samples to trace nitrate sources in Lake Sihwa, which encompasses various land-use types (e.g., urban, industry, wetland, and agriculture). The biogeochemical interactions of anthropogenic nitrogen sources (e.g., soil, road dust, and septic water) were also evaluated through multiple pathways from terrestrial boundaries to the water column. Based on increased concentrations of dissolved total nitrogen (DTN; 3.1 ± 1.6 mg/L) after typhoon, the variation of element stoichiometry (N:P:Si) in this system shifted to the relatively N-rich conditions (DIN/DIP; 14.1 ± 8.1, DIN/DSi; 1.4 ± 1.8), potentially triggering the occurrence of harmful algal blooms. Furthermore, discriminative isotopic compositions (δ15NNO3; 4.0 ± 2.1 ‰, δ18ONO3; 6.1 ± 4.3 ‰) after the typhoon suggested the increased DTN input of anthropogenic origins within Lake Sihwa would be mainly transported from urban sources (76 ± 9 %). Consequently, the isotopic-based approach may be useful for effective water quality management under increased anthropogenic activities near aquatic systems.

Assessment of environmental forensic indicator for anthropogenic groundwater contamination via target/suspect/nontarget analysis using HRMS techniques

This study compared target/suspect/nontarget analysis via liquid chromatography-high-resolution mass spectrometry (LC-HRMS) with traditional environmental forensic methods, specifically nitrate and its stable N isotope, in assessing groundwater pollution from livestock manure and agriculture. Using an in-house database of 1471 target and suspects, 35 contaminants (pesticides, veterinary drugs, surfactants) were identified, some uniquely linked to specific pollution sources, such as sulfamethazine and 4-formylaminoantipyrine in manure-affected areas. Pesticides were widespread, typically showing higher intensity in agricultural zones. On the other hand, the results of stable N isotope analysis (δ15N-NO3: 4.8 to 16.4‰) indicated the influence of human activities such as fertilizers, sewage, and manure in all sampling sites, including the control site far from the pollution sources and cannot differentiate the specific sources. The study underscores LC-HRMS's efficacy in different pollution sources, surpassing the limitations of stable N isotope analysis, and provides valuable insights for polluted groundwater source tracking strategies.

Using unsupervised machine learning models to drive groundwater chemistry and associated health risks in Indo-Bangla Sundarban region

Groundwater is an essential resource in the Sundarban regions of India and Bangladesh, but its quality is deteriorating due to anthropogenic impacts. However, the integrated factors affecting groundwater chemistry, source distribution, and health risk are poorly understood along the Indo-Bangla coastal border. The goal of this study is to assess groundwater chemistry, associated driving factors, source contributions, and potential non-carcinogenic health risks (PN-CHR) using unsupervised machine learning models such as a self-organizing map (SOM), positive matrix factorization (PMF), ion ratios, and Monte Carlo simulation. For the Sundarban part of Bangladesh, the SOM clustering approach yielded six clusters, while it yielded five for the Indian Sundarbans. The SOM results showed high correlations among Ca2+, Mg2+, and K+, indicating a common origin. In the Bangladesh Sundarbans, mixed water predominated in all clusters except for cluster 3, whereas in the Indian Sundarbans, Cl--Na+ and mixed water dominated in clusters 1 and 2, and both water types dominated the remaining clusters. Coupling of SOM, PMF, and ionic ratios identified rock weathering as a driving factor for groundwater chemistry. Clusters 1 and 3 were found to be influenced by mineral dissolution and geogenic inputs (overall contribution of 47.7%), while agricultural and industrial effluents dominated clusters 4 and 5 (contribution of 52.7%) in the Bangladesh Sundarbans. Industrial effluents and agricultural activities were associated with clusters 3, 4, and 5 (contributions of 29.5% and 25.4%, respectively) and geogenic sources (contributions of 23 and 22.1% in clusters 1 and 2) in Indian Sundarbans. The probabilistic health risk assessment showed that NO3- poses a higher PN-CHR risk to human health than F- and As, and that potential risk to children is more evident in the Bangladesh Sundarban area than in the Indian Sundarbans. Local authorities must take urgent action to control NO3- emissions in the Indo-Bangla Sundarbans region.

Basin-wide tracking of nitrate cycling in Yangtze River through dual isotope and machine learning

The nitrate (NO3-) input has adversely affected the water quality and ecological function in the whole basin of the Yangtze River. The protection of water sources and implementation of "great protection of Yangtze River" policy require large-scale information on water contamination. In this study, dual isotope and Bayesian mixing model were used to research the transformation and sources of nitrate. Chemical fertilizers contribute 76 % of the nitrate sources in the upstream, while chemical fertilizers were also dominant in the midstream (39 %) and downstream (39 %) of Yangtze River. In addition, nitrification process occurred in the whole basin. Four machine learning models were used to relate nitrate concentrations to explanatory variables describing influence factors to predict nitrate concentrations in the whole basin of Yangtze River. The anthropogenic and natural factors, such as rainfall, GDP and population were chosen to take as predictor variables. The eXtreme Gradient Boosting (XGBoost) model for nitrate has a better predictive performance with an R2 of 0.74. The predictive models of nitrate concentrations will help identify the nitrate distribution and transport in the whole Yangtze River basin. Overall, this study represents the first basin-wide data-driven assessment of the nitrate cycling in the Yangtze River basin.

Leaching of soil legacy nitrogen in intact soil columns and significance of soil macropore structure

Excessive application of chemical fertilizers accumulates nitrogen in soil (soil legacy nitrogen), and its release has a long-term impact on environmental quality. The information regarding leaching of soil legacy nitrogen and role of soil pore structure is scarce. Fifteen undisturbed soil cores with a depth of ~200 mm were collected from five paddy fields in a subtropical area of China, and soil pore structure was characterized with X-ray computed tomography. The batch leaching column experiments were conducted to investigate the nitrogen leaching from the soil cores. In the leachate, inorganic nitrogen (NO3--N and NH4+-N) accounted for 73-85 % of total dissolved nitrogen (TDN), which showed small variations among the five sampling sites. The NO3--N, NH4+-N and TDN concentrations in the leachate over the number of leaching times could be well fitted with the Gaussian, exponential or linear models, suggesting that different nitrogen forms showed variable leaching dynamics. NO3--N and TDN leaching losses continued to increase with the number of leaching times, whereas NH4+-N leaching from the soil had a threshold value. Combination of changes in soil nitrogen content after leaching, the lagging effect of soil legacy nitrogen may be partly attributed to the continuous transformation of NH4+-N and organic nitrogen into NO3--N in the soils. Besides the nitrogen content in the soil, the most important factor of soil pore structure controlling NO3--N and TDN leaching loss was the fractal dimension; NH4+-N was mainly controlled by connectivity. The present study highlighted the importance of soil pore structure and nitrogen format transformation in the leaching of soil legacy nitrogen.

Source identification and potential health risks of fluoride and nitrate in groundwater of a typical alluvial plain

A comprehensive understanding of the role of natural and anthropogenic factors in groundwater pollution is essential for sustainable groundwater resource management, especially in alluvial plains with intensive anthropogenic activities. Numerous studies have focused on the contribution of individual factors on groundwater pollution in alluvial aquifers, but distinguishing the effects of natural and anthropogenic factors is limited. In this study, 64 wells were sampled in different seasons from the Yellow River alluvial plain in China for hydrochemical and isotopic analysis to investigate the spatiotemporal distribution, sources and health risks of fluoride and nitrate in alluvial aquifers. Results showed that fluoride contamination was widely distributed without significant seasonal variation, and 78.1 % of the dry season samples and 65.6 % of the wet season samples showed fluoride concentrations above the permissible limit (1.5 mg/L). High-F- groundwater was generally accompanied by Na-HCO3 and Na-HCO3·SO4 water types. Fluoride was from a natural origin mainly associated with mineral dissolution, competitive adsorption, cation exchange, and evaporation. Groundwater nitrate contamination was spatially sporadic and showed significant seasonal differences. Only 13.6 % of the dry season samples and 3.2 % of the wet season samples had NO3- concentrations exceeded the permissible limit of 50 mg/L. The hydrochemical phase evolved from bicarbonate or sulfate type to chloride type with increasing nitrate concentration. Manure and sewage attributed to agricultural activities contributed the most nitrogen to groundwater, followed by soil organic nitrogen and chemical fertilizers, revealing the anthropogenic origin of nitrate. Nitrification was the dominant nitrogen transformation process in the wet season, and denitrification was prevalent in the dry season. Oral ingestion of high fluoride groundwater was a major threat to human health, especially for infants. This study provided a significant reference for water resources management in alluvial aquifers.

Deciphering spatio-seasonal patterns, driving forces, and human health risks of nitrate and fluoride enriched water bodies in the Inner Mongolia Reaches of the Yellow River Basin, China

The ecology and environment of the Yellow River Basin is threatened by fluoride and nitrate contamination induced by anthropogenic activity and geogenic factors. As a result, deciphering the spatio-temporal variability of fluoride and nitrate contamination in this area remains a challenge. Three hundred eighty-six samples of surface water and groundwater from the Inner Mongolia Reaches of the Yellow River Basin were taken for this investigation. According to the results of the multivariate statistical and geostatistical analyses, the fluoride pollution was primarily discovered in the middle and lower reaches of the study area and was determined to be more severe during the dry season. In contrast, nitrate contamination was found to be more severe during the wet season while being widely distributed in groundwater and concentrated in areas with intensive agricultural activities. The primary mechanisms governing the spatial-seasonal patterns of NO3- and F- pollution were shown by the principal component analysis, isotopic, and hydrochemical diagrams. The water-rock interaction or evaporation was crucial in the enrichment of F-. The human inputs (e.g., fertilizer or sewage) dominated fluoride and nitrate contamination. Additionally, the alkaline environment played a role in the generation of NO3- and F-. The health risk assessment concluded that the threat of fluoride contamination was greater than that of nitrate contamination. Children faced the greatest health risks, followed by females and males. These findings would serve as a guide for water management and pollution control in the Yellow River Basin.

Designing dynamic groundwater management strategies through a composite groundwater vulnerability model: Integrating human-related parameters into the DRASTIC model using LightGBM regression and SHAP analysis

Groundwater nitrate contamination has emerged as a pressing global concern. Given its potential for long-term impacts on aquifers, protective measures should primarily focus on prevention. Drawing on the theory of groundwater vulnerability (GV), the original DRASTIC model and parameters related to human activities are employed as inputs and integrated with the LightGBM regression algorithm to facilitate nitrate index (NI) prediction tasks. The SHAP analysis is conducted to effectively examine the contribution of parameters to the NI prediction and interpret the issue of parameter interactions. In addition, to mitigate the limitations of the intrinsic GV model, a composite nitrate index (CNI) is developed by linearly combining the DRASTIC index with the NI. The framework presented in this study provides adaptive strategies for managing groundwater resources over different time periods. A representative region for arid and semiarid climates, the Yinchuan region, is studied using the framework. As compared to 2012, the intrinsic GV index has changed spatially in 2022. Human activities have increased the influence of the nitrate concentration as shown by the Pearson correlation coefficient of -0.082 between the DRASTIC index and nitrate concentration. A significant increase in pollution levels was predicted by NI, ranging from -0.116 to 0.968. According to SHAP analysis, the significant increase in NI levels in 2022 was mainly due to high-value industrial and agricultural production. In 2022, 12.02% of the areas had an increase of at least 0.549 in the CNI. 42.1% of the areas were classified as moderate or high CNI levels. The farm was identified as a high-contributing source to nitrate pollution. The small-scale agricultural and livestock activities in non-urban areas also contribute to groundwater pollution. Dynamic groundwater management strategies need to be implemented in high-growth and high-level CNI areas.

Effects of recharge process on groundwater nitrate concentration in an oasis of Tengger Desert hinterland, China

Groundwater nitrate concentrations cannot be effectively diluted in an oasis of desert hinterland without direct recharge from external rivers. Therefore, there is an urgent need to understand the relationship between groundwater nitrate concentration and the groundwater recharge process. Using hydrochemicals, stable isotopes, LUCC, and combining these with the MixSIAR model, the distributions of groundwater nitrate concentration in the Dengmaying Basin (DMYB) in 2006 and 2020 were obtained. The contributions of groundwater recharge and nitrate sources were also quantified. With the development of agriculture in the DMYB, groundwater irrigation leakage has gradually become a crucial recharge source of groundwater, with a recharge proportion reaching 30.3%. From 2006 to 2020, under the influence of well irrigation and agricultural fertilization, the groundwater nitrate concentration in the DMYB increased significantly, with an increased range of 1.3 ~ 14.3 mg L-1. Moreover, the δ15N-NO3- and δ18O-NO3- values of nitrate in cultivated soil water were similar to those in groundwater, which also proves the process of carrying nitrate from the vadose zone into groundwater by irrigation water. The contribution of anthropogenic sources (54.9%) to groundwater nitrate exceeded that of natural sources (45.1%) to groundwater nitrate in the DMYB. These results indicate that the potential for nitrate pollution in groundwater must be considered, even in desert oases.

A supervised machine learning approach to discriminate the effect of carcass leachate on shallow groundwater quality around on-farm livestock mortality burial sites

The evaluation of leachate leakage at livestock mortality burial sites is challenging, particularly when groundwater is previously contaminated by agro-livestock farming. Supervised machine learning was applied to discriminate the impacts of carcass leachate from pervasive groundwater contamination in the following order: data labeling, feature selection, synthetic data generation, and classification. Physicochemical data of 359 water samples were collected from burial pits (LC), monitoring wells near pits (MW), pre-existing shallow household wells (HW), and background wells with pervasive contamination (BG). A linear classification model was built using two representative groups (LC and BG) affected by different pollution sources as labeled data. A classifier was then applied to assess the impact of leachate leakage in MW and HW. As a result, leachate impacts were observed in 40% of MW samples, which indicates improper construction and management of some burial pits. Leachate impacts were also detected in six HW samples, up to 120 m downgradient, within one year. The quantitative decision-making tool to diagnose groundwater contamination with leachate leakage can contribute to ensuring timely responses to leakage. The proposed machine learning approach can also be used to improve the environmental impact assessment of water pollution by improper disposal of organic waste.

Extended pilot test of a cross-injection in situ denitrification system for pre-emptive treatment of municipal well water

Elevated groundwater nitrate concentrations have been linked to deleterious health and environmental effects. A significant source of the nitrate is nitrogen fertilizers applied to agricultural landscapes. Beneficial Management Practices (BMPs), including the optimization of fertilizer use and selective crop rotations, have proven to be effective in some cases. The city of Woodstock in southern Ontario relies on public wells for all of its municipal supply. Several of the wells have experienced chronic increases in nitrate concentrations exceeding the maximum allowable limit of 10 mg/L N-NO₃^-. While BMPs are established, an interim reduction plan based on enhanced in situ denitrification (Cross Injection System, CIS) in a 15 m thick zone of high nitrate mass flux within the aquifer zone was evaluated. Based in the results of preliminary acetate injection experiments, a C:N ratio of 2.35, (approximately 260 mg acetate/L), was selected to optimize the denitrification reaction. Injections were performed for six hours a day every day for a period of approximately two months. Dissolved oxygen (DO) and nitrate concentrations recorded over time indicated that reduction of both commenced within a few days of the beginning of the acetate injections and reduced levels were maintained for the remainder of the two-month injection period. Denitrification occurred throughout the profile although nitrate reduction was the highest in the lower groundwater velocity zones. An overall reduction of nitrate of 50% was achieved through the treated section of the aquifer. It is estimated that an upscaled treatment system utilizing a treatment width of only 70 m would be sufficient to reduce the nitrate concentrations to below the drinking water limit demonstrating the potential for the CIS method to functions as an interim groundwater nitrate reduction strategy.

Appraisal of groundwater quality with WQI and human health risk assessment in Karamık wetland and surroundings (Afyonkarahisar/Turkey)

Groundwater in Karamık wetland and surroundings, which is one of the important wetlands in Turkey, was examined and the chemical properties and quality of groundwater were determined in the present study. In addition, the possible risks to human health as a result of groundwater usage were investigated along with spatial analyses carried out using Geographic Information Systems (GIS). Physicochemical analyses were carried out on 25 samples taken from groundwater. The dominant ions in the study area are Ca, Mg, and HCO₃. When the results are compared with the limit values in the valid drinking water guidelines such as TSI-266 (Standards for drinking waters, 2005) and WHO (Guidelines for drinking-water quality, 2011), the groundwaters were not suitable for use as drinking water in terms of NO₃, Fe, Pb and As. The analysis results were evaluated together with GIS and Water Quality Index (WQI) methods. In the evaluations with the WQI method, 76% of the samples were in the "poor water" class. The groundwater in the study area is polluted by both geogenic and anthropogenic sources. For this reason, health risk assessment was performed due to the use of groundwater in the region by the local people in different areas, especially as drinking water, and the negative effects of water quality. Accordingly, there are non-carcinogenic negative effects on health in terms of NO₃, As, Pb and Fe parameters from the use of groundwater by children. In addition, Pb and As concentrations are at carcinogenic levels for both children and adults in all groundwater samples collected from the study area. Therefore, it is not recommended to use groundwater as drinking water without treatment.

Quantitative identification of nitrate and sulfate sources of a multiple land-use area impacted by mine drainage

The rapid increase in urbanization and intensive coal mining activities have accelerated the deterioration of surface water quality. Environmental problems caused by the accumulation of nitrate and sulfate from natural, urban, and agricultural sources have attracted extensive attention. Information on nitrate and sulfate sources and their transformations is crucial for understanding the nitrogen and sulfur cycles in surface water. In this study, we monitored nitrate and sulfate in three representative rivers in mining cities in northern China. The main pollution sources and biogeochemical processes were identified by using stable isotopes (δD, δ¹⁸O_H2O, δ¹⁵N, δ¹⁸O_NO3, δ³⁴S and δ¹⁸O_SO4) and hydrochemistry. The contribution of natural and anthropogenic sources was quantitatively estimated based on a Bayesian mixed model. The results indicated a large variation in sulfate and nitrate sources between the different rivers. Nitrate in the Tuohe River mainly derived from manure/sewage (57.9%) and soil N (26.9%), while sulfate mainly derived from manure/sewage (41.7%) and evaporite dissolution (26.8%). For the Suihe River, nitrate was primarily sourced from chemical fertilizer (37.9%) and soil nitrogen (34.8%), while sulfate was mainly sourced from manure/sewage (33.1%) and chemical fertilizer (21.4%). For the Huihe River, nitrate mainly derived from mine drainage (56.6%) and manure/sewage (30.6%), while sulfate predominantly originated from mine drainage (58.3%) and evaporite dissolution (12.9%). Microbial nitrification was the major pathway for the migration and transformation of nitrate in the surface water. However, denitrification and bacterial sulfate reduction (BSR) did not play a significant role as aerobic conditions prevailed. In this study, we elucidated the sources and transformation mechanisms of nitrate and sulfate. Additionally, we provided a reference for formulating a comprehensive strategy for effective management and remediation of surface water contaminated with nitrate and sulfate in mining cities.

Hydrothermal carbonization improves the quality of biochar derived from livestock manure by removing inorganic matter

The application of hydrothermal carbonization to improve biomass-derived energy sources is crucial because of insufficient supplies of fossil fuels and concerns associated with the impact of fossil fuels on the environment. Hydrothermal carbonization technology has been developed to circumvent the energy-intensive drying step required for the thermal conversion of high-moisture organic feedstocks into fuel. In this study, the quality of livestock manure was upgraded, and its energy density was increased through hydrothermal carbonization at various temperatures. The evolution of waste biomass under hydrothermal carbonization was chemically analyzed. The increased carbon content of the resulting biochar upgraded its fuel properties, leading to energy savings in the treatment process. After hydrothermal carbonization, the H/C and O/C ratios were lower owing to chemical conversion. The optimal temperature for hydrothermal carbonization was approximately 220 °C. The inorganic content resulted in a lowered degree of agglomeration and reduced the likelihood of fouling during combustion. The thermogravimatric analysis also provided the changing combustion characteristics due to the increased fixed carbon content. Fourier transform infrared spectra revealed that hydrothermal carbonization reaction reduced the numbers of C-O and C-H functional groups and increased the number of aromatic C-H functional groups. The equilibrium moisture content decreased rapidly when hydrothermal carbonization was conducted at temperatures higher than 200 °C, and the initial moisture content was reduced by 75% after hydrothermal carbonization at 300 °C.

Hydrochemical assessments and driving forces of groundwater quality and potential health risks of sulfate in a coalfield, northern Ordos Basin, China

Groundwater is the primary water source in coalfields under arid and semiarid climates. However, the problem of excessive concentrations of sulfate, which is a constant component in coalfields, and its potential health risks are often neglected in Northwest, China. To determine the groundwater quality, health threats, and driving forces of sulfate in coal mine groundwater, this study performed hydrochemical and isotopic analyses of 61 groundwater samples from a typical coalfield in northwestern China. We found that phreatic groundwater had lower total dissolved solid (TDS) and freshwater hydrochemical types (mainly Ca-HCO₃ and Ca-Na + K-HCO₃ types). In contrast, confined groundwater showed saline affinity (Na + K-SO₄ type) and high TDS values, and the quality was unacceptable for drinking, with EWQI values larger than 100, which could be attributed to its high SO₄^2- concentration. In addition, confined groundwater was also unsuitable for irrigation with high values of electric conductivity (EC), sodium absorption ratio (SAR), and Na%. Combining with isotopic analysis (δD, δ¹⁸O_water, δ³⁴S and δ¹⁸O_sulfate), the sulfate of confined and phreatic groundwater was controlled by gypsum dissolution and irrigation activities. As for public human health, SO₄^2- poses potential non-carcinogenic risks to various populations, especially children. Therefore, the impact of geogenic and anthropogenic factors should be paid attention to, including the reduction of the use of sulfur-containing fertilizers and discharge of sulfur-containing sewage; and the water treatment should be carried out. Importantly, there is a need to adopt a strategy of water supply from multiple sources to ensure human health.

Recent advances in the source identification and remediation techniques of nitrate contaminated groundwater: A review

Researchers have long been committed to identify nitrate sources in groundwater and to develop an advanced technique for its remediation because better apply remediation solution and management of water quality is highly dependent on the identification of the NO₃^- sources contamination in water. In this review, we systematically introduce nitrate source tracking tools used over the past ten years including dual isotope and multi isotope techniques, water chemistry profile, Bayesian mixing model, microbial tracers and land use/cover data. These techniques can be combined and exploited to track the source of NO₃^- as mineral or organic fertilizer, sewage, or atmospheric deposition. These available data have significant implications for making an appropriate measures and decisions by water managers. A continuous remediation strategy of groundwater was among the main management strategies that need to be applied in the contaminated area. Nitrate removal from groundwater can be accomplished using either separation or reduction based process. The application of these processes to nitrate removal is discussed in this review and some novel methods were presented for the first time. Moreover, the advantages and limitations of each approach are critically summarized and based on our own understanding of the subject some solutions to overcomes their drawbacks are recommended. Advanced techniques are capable to attain significantly higher nitrate and other co-contaminants removal from groundwater. However, the challenges of by-products generation and high energy consumption need to be addressed in implementing these technologies for groundwater remediation for potable use.

Identification and apportionment of shallow groundwater nitrate pollution in Weining Plain, northwest China, using hydrochemical indices, nitrate stable isotopes, and the new Bayesian stable isotope mixing model (MixSIAR)

Groundwater nitrate (NO₃^-) pollution is a worldwide environmental problem. Therefore, identification and partitioning of its potential sources are of great importance for effective control of groundwater quality. The current study was carried out to identify the potential sources of groundwater NO₃^- pollution and determine their apportionment in different land use/land cover (LULC) types in a traditional agricultural area, Weining Plain, in Northwest China. Multiple hydrochemical indices, as well as dual NO₃^- isotopes (δ¹⁵N-NO₃ and δ¹⁸O-NO₃), were used to investigate the groundwater quality and its influencing factors. LULC patterns of the study area were first determined by interpreting remote sensing image data collected from the Sentinel-2 satellite, then the Bayesian stable isotope mixing model (MixSIAR) was used to estimate proportional contributions of the potential sources to groundwater NO₃^- concentrations. Groundwater quality in the study area was influenced by both natural and anthropogenic factors, with anthropological impact being more important. The results of LULC revealed that the irrigated land is the dominant LULC type in the plain, covering an area of 576.6 km² (57.18% of the total surface study area of the plain). On the other hand, the results of the NO₃^- isotopes suggested that manure and sewage (M&S), as well as soil nitrogen (SN), were the major contributors to groundwater NO₃^-. Moreover, the results obtained from the MixSIAR model showed that the mean proportional contributions of M&S to groundwater NO₃^- were 55.5, 43.4, 21.4, and 78.7% in the forest, irrigated, paddy, and urban lands, respectively. While SN showed mean proportional contributions of 29.9, 43.4, 61.5, and 12.7% in the forest, irrigated, paddy, and urban lands, respectively. The current study provides valuable information for local authorities to support sustainable groundwater management in the study region.

Ultrafiltration concentrated biogas slurry can reduce the organic pollution of groundwater in fertigation

Biogas slurry has the problems of having a low concentration, having a large production volume, and containing many small-molecule organic pollutants. During the fertigation process of biogas slurry, many small-molecule organic pollutants may pose potential pollution risks to groundwater. In this study, the ultrafiltration membrane technology was used to separate small-molecule organics in the biogas slurry to prepare ultrafiltration concentrated biogas slurry (UCBS). To research the impact of UCBS and raw biogas slurry (RBS) on the small-molecule organic pollution of groundwater, a laboratory soil column simulation leaching device was used to conduct leaching experiments with 4 types of UCBS and RBS in acric ferralsols and hydragric anthrosols for two quarters (8 fertilization periods). The results of the study show that both UCBS and RBS caused nitrate pollution to groundwater. UCBS has a lower risk of organic pollution to groundwater than RBS. Irrigating UCBS in hydragric anthrosols has a higher risk of organic pollution of groundwater than that in acric ferralsols. Analysis of the molecular weight distribution of dissolved organic matter (DOM) in the leaching solution showed that the organic pollutants were mainly small molecules <10 kDa. According to 3D excitation-emission matrix (3D-EEM) analysis, the main organic pollutants in the leaching solution were fulvic acid, microbial protein metabolites and humic acid organic compounds. The research results show that the pretreatment of biogas slurry by ultrafiltration can reduce the risk of small-molecule organic pollution of groundwater in land application, which can provide a new scientific basis to standardize biogas slurry land application technical guidelines and reduce groundwater pollution.

Investigating sources, driving forces and potential health risks of nitrate and fluoride in groundwater of a typical alluvial fan plain

Groundwater of alluvial fan plains is the foremost water source, especially in arid/semiarid regions. Its contaminants are big issues for water supply and public health concern. To reveal the groundwater chemistry, contaminants sources and health threats in alluvial aquifers, 81 groundwaters were collected from a typical alluvial fan plain of northern China for nitrogen, fluoride and major ions analysis. Statistical analysis and hydrochemical diagrams as well as human health risk assessment were performed. Nitrate is widely distributed and 53% of groundwaters exceed the permissible limit with the maximum concentration up to 326 mg/L. The distributions of nitrite, ammonia and fluoride contaminants are sporadic in spatial, and the concentrations of fluoride in groundwaters are slightly beyond the permissible limit of 1 mg/L. The hydrochemical facies shift from HCO₃-Ca or Mixed HCO₃-Na·Ca type to Mixed Cl-Mg·Ca and ClCa type with the increase of nitrate content. Two factors (Factor-1 and Factor-2) are extracted by factor analysis and account 63% of the total variances. The positive loading of F^- and negative loading of NO₃^- on Factor-2 reveal geogenic and anthropogenic origins, respectively. The significant positive loadings of TDS, TH, SO₄^2-, Cl^-, Ca²⁺, Mg²⁺ on Factor-1 reveal the governing mechanisms on groundwater chemistry by intermixed sources of geogenic origins and anthropogenic inputs. Hydrogeochemical evolution in the study area is driven by both water-rock interaction and anthropogenic forces. Anthropogenic inputs/influences are the dominated forces increasing groundwater nitrate content and salinity in the piedmont zone and the residential and industrial zone of the southeastern lower parts, and would pose potential non-carcinogenic risks to various populations via oral intake pathway. Rational measures should be taken to protect groundwater quality out of the threats of anthropogenic pollution. The geogenic fluoride in groundwater would threat the health of children through oral pathway and should be also concerned. CAPSULE: The driving forces of groundwater chemistry in alluvial fan plains were revealed using integrated approach of factor analysis and geostatistical modelling.

Identification of groundwater pollution from livestock farming using fluorescence spectroscopy coupled with multivariate statistical methods

Extensive livestock farming has highly threatened groundwater quality, thereby necessitating a rapid and effective method to identify groundwater quality in such areas. Fluorescence spectroscopy has been recognized as an interpretable method for tracking anthropogenic influences on water quality, but its applicability in identifying the groundwater pollution from livestock farming remains unknown. In this study, the fluorescence characteristics of dissolved organic matter (DOM) in groundwater from a typical livestock farming area were investigated by using fluorescence excitation emission matrix (EEM)-parallel factor analysis (PARAFAC) coupled with multivariate statistical methods. The results showed that livestock farming significantly altered the content and composition of DOM in groundwater, and these effects were mainly observed in shallow groundwater in the study area. Hierarchical cluster analysis based on fluorescence parameters divided the groundwater samples into three clusters with significantly different pollution degrees: Cluster A, unpolluted; Cluster B, highly polluted; Cluster C, moderately polluted. In particular, the intensity of tryptophan-like fluorescence was high in the polluted groundwater but was almost undetectable in the unpolluted groundwater, suggesting that it is a potential indicator of groundwater quality. Principal component analysis based on the fluorescence parameters explained 91.5% of the variance with the first two principal components, and revealed that the degree of pollution dominated the fluorescence characteristics of groundwater in the study area. In addition, NO₃^- was abundant in Clusters B and C, while it was low in Cluster A, validating the analysis results of fluorescence spectroscopy. These findings indicated that DOM fluorescence was sensitive to livestock farming pollution and could be applied to identify, monitor, and assess groundwater pollution from livestock farming.

Crop Field Level Estimation of Nitrogen Input from Fertilizer Use in Jeju Island, South Korea: Management Methods to Prevent Groundwater NO3-N Contamination

The application of synthetic nitrogen (N) fertilizers has boosted crop yields globally. However, it has also imposed on environmental pollution problems. An estimation of actual fertilizer N inputs at the crop field level is needed to establish effective N management plans to control groundwater NO3-N contamination. Here, a survey to collect the types of cultivated crop and fertilizer application rate was conducted during 2016–2018, covering 44,253 small crop fields (7730 ha) in the western part (Hanrim and Hankyung regions) of Jeju Island, South Korea. Foreign vegetables, citrus fruits, and bulb vegetables are the major crop types grown in the total cultivated areas of 2165.6 ha, 1718.7 ha, and 944.9 ha, respectively. For several crops (green garlic, potato, and chives), the over-use of N fertilizers is observed, the amount of which is 1.73–4.95 times greater than the standard fertilizer application rate. The highest level of fertilizer N input is observed for bulb vegetables in both the regions (Hanrim: 500.5 kg/ha, Hankyung: 487.1 kg/ha), with nearly 80% of the N fertilizer input turned into surplus N loading. A comparison between a spatial interpolation map of the fertilizer N input and that of the groundwater NO3-N concentration implies that the excessive use of synthetic fertilizer results in the degradation of groundwater quality by NO3-N. N management plans for the study area are suggested based on the N fertilizer input at the crop field level. This study highlights that sustainable N management plans should be arranged at the crop field level, considering the spatial heterogeneity of N fertilizer use.