https://orcid.org/0000-0003-1006-8757
Abstract
In order to identify and effectively control the impact of NO3− pollution on human health, on the basis of investigation, sampling, analysis and testing, statistical analysis software (SPSS19), groundwater pollution analysis software, Nemera comprehensive index method, correlation analysis method and human health risk assessment model are applied for analysis and research. The results indicate that the groundwater in the study area is mainly Class II water, with overall good water quality. The main influencing factors for producing Class IV are NO3−, Fe, F− and SO42−. The use of agricultural fertilizers is the main source of NO3− exceeding standards in groundwater in this area. There are significant differences in the health hazards caused by NO3− pollution in groundwater among different populations, and infants and young children are more susceptible to nitrate pollution. The division of pollution areas and high-risk groups plays an important guiding role in preventing health risks. The new achievements will help people improve their awareness of risk prevention, caring for the environment, respecting nature and implementing precise policies, promoting society to step onto the track of scientific and healthy development.
HIGHLIGHTS
Scientific evaluation of groundwater quality was conducted and the main factors affecting water quality were analyzed.
Scientific evaluation was conducted on NO3− pollution in the research area and the main sources of NO3− were identified.
The significant differences in the health hazards of NO3− pollution were identified.
The research results have an important guiding role in preventing health risks.
INTRODUCTION
Groundwater is one of the precious natural resources and the amount of groundwater resources accounts for one-third of the total water resources. Groundwater is closely related to people's production and life (Alireza et al. 2020; Tian et al. 2020a, 2020b, 2020c, 2020d), Groundwater is particularly important in areas with insufficient surface water resources (Tian et al. 2021). However, as the drinking water source of 70% of China's population, the groundwater has been polluted (Sun et al. 2020a, 2020b; Cao et al. 2023a), and the shallow groundwater and deep groundwater polluted by nitrides, phosphates and heavy metal ions have reached 80 and 30%, respectively (Sun et al. 2021; Cao et al. 2023b). Because groundwater pollution is highly hidden and difficult to detect, it is difficult to control the pollution in groundwater (Cao et al. 2018; Saravanan et al. 2022).
Nitrate pollution in groundwater is a worldwide environmental problem. Nitrate is easy to dissolve and has strong fluidity (Gu et al. 2013; Zhai et al. 2015; Tian et al. 2020a, 2020b, 2020c, 2020d). It can enter underground through leaching and surface runoff (Li et al. 2015). It is a chemical pollutant widely existing in groundwater (Hand et al. 2013; Sun et al. 2019). Drinking groundwater polluted by nitrate for a long time will lead to digestive system cancer, methemoglobinemia, blue baby syndrome and other diseases posing a serious threat to human health (Han 2014; China 2016; Sun et al. 2017; Chen et al. 2020). Nitrate-contaminated groundwater will cause harm when it enters the human body, therefore, it is necessary to evaluate the harm and degree of nitrate-contaminated groundwater. Human Health Risk Assessment (HHRA) is a qualitative and quantitative assessment method for the hazard degree of polluted groundwater to human body (Ni et al. 2010; Sun et al. 2022a, 2022b).
In 1983, the National Academy of Sciences (NAS) proposed for the first time a ‘four-step method’ based on hazard identification, dose–effect assessment, exposure assessment and risk characterization to assess the risks of environmental pollutants to human health. Then the United States Environmental Protection Agency (USEPA) made a more detailed description of health risk assessment. At present, the ‘four-step’ health risk assessment model is applied to the health risk assessment of various pollutants in various environmental media. Saravanan et al. (2022) and Zhang et al. (2021) used models to evaluate the impact of high nitrate in groundwater on human health in different regions.
Algorithms and models have been widely applied in various fields such as resource allocation (Deng et al. 2022a; Xu et al. 2023), public management (Deng et al. 2022b, 2022c) and health services (Duan et al. 2022; Huang et al. 2023). The article selects the HHRA model recommended by the USEPA to identify and assess the risk of nitrate pollution in groundwater in the Datong Basin. This helps to develop effective risk management measures, achieve sustainable and healthy development and achieve good results. Through model sensitivity analysis, the model is sensitive to the influence of pollutant concentration. Simulation methods can help us better understand the process of groundwater pollution and provide a basis for formulating effective prevention and control measures. The risk assessment method for groundwater pollution can quantitatively evaluate the degree of groundwater pollution risk and provide scientific decision-making basis for decision-makers.
According to the research on the Datong Basin from 2020 to 2021, there are areas with high nitrate content in the groundwater in the Datong Basin. The maximum nitrate content (N) reaches 474 mg/L. The high concentration of nitrate groundwater will affect human health after long-term drinking. In order to improve people's risk awareness, scientifically and reasonably prevent the occurrence of risks and ensure that human health is not harmed, it is necessary to conduct a health risk assessment of groundwater in the Datong Basin.
Through research, the health risk model was first introduced into the health risk assessment of groundwater pollution in the Datong area of Shanxi Province. The current water quality status, water quality impact factors, 
exceeding the standard status and health risks caused by 
exceeding the standard were identified in the study area. The conclusion that 
exceeding the standard has different health risks for different populations was drawn, which has practical significance for guiding people to scientifically and reasonably plant crops and use fertilizers in an appropriate amount.
The establishment of the model is based on three exposure environments: drinking water, skin and respiration. The model also has certain limitations. In the future, we should further research and develop simulation and evaluation methods to improve the accuracy and reliability of prediction and evaluation, in order to protect the sustainable use and management of groundwater resources.
MATERIALS AND METHODS
Study area
The Datong Basin is located in Shanxi Province, China, 112°15′–114°17′ E and 39°05′–40°33′ N. The total area of the plain area is about 7,440 km2. The climate is characterized by dry climate, less rain, more sandstorms, large temperature difference between day and night, and sufficient sunlight. The average annual precipitation is between 363 and 414 mm. It belongs to the Haihe River system, the Sanggan River is the main river, and its tributaries include the Huihe River, the Huangshui River, the Shili River, the Yuhe River and the Hunhe River. The Datong Basin is surrounded by mountains, of which the highest peak is 2,426 m above sea level. The terrain in the center of the basin is open and flat, with an altitude of 1,100–950 m. At present, it has formed a relatively complete industrial system focusing on coal production, such as electric power, chemical industry, building materials, machinery and food. It is one of the energy and heavy chemical bases in China. The basin is densely populated. According to statistics, the current population of the Datong Basin is about 2.6 million. The Datong Basin is a Cenozoic graben type fault basin developed on the Mesozoic fold basement. The NE, EW and SN trending faults form the basin boundary, respectively. The groundwater aquifer system includes the karst aquifer system, the basalt fissure pore aquifer system, the bedrock fissure aquifer system and the quaternary pore aquifer system. Human activities have caused groundwater pollution, especially the excessive use of nitrogen fertilizer in agricultural production.
Sampling and measurements
Distribution of sampling points.
The water sample test was completed by the testing agency with the national certification, and the sample preparation was carried out in strict accordance with the geological and mineral industry standard of the People's Republic of China, ‘Method for Analysis of Groundwater Quality’ DZ/T 0064. According to different test items, the water samples are subject to evaporation, color reagent addition, acidification, reduction and other treatments. Cl−, 
, F− and 
were determined by ion chromatography (IC); Ca2+, Mn and TFe were determined by inductively coupled plasma emission spectrometer (ICP-OES), and total dissolved solids (TDS) were determined by the gravimetric method. The total hardness was determined by EDTA-2Na titration. The pH value was measured by the glass electrode method.
To ensure the accuracy and reliability of the analysis method, the spiked recovery method was used for determination. Each sample was analyzed 12 times, and the average analysis value and spiked recovery rate were calculated. The recovery rate (average of 12 times) of the item for spiked recovery determination should be controlled between 90 and 110%, and the relative standard deviation (RSD%) of 12 analyses of a single standard sample (or spiked recovery sample) should be calculated, with a requirement of RSD% ≤ 15%.
In total, four standard control samples and standard samples, such as GBW08606, were inserted into each batch of samples (control different items separately) and the accuracy of five recovered samples were analyzed and controlled simultaneously. The requirements of the specifications were strictly followed and the recovery rate of spiking was controlled at 80–120, 90–110 and 95–105%, respectively, according to different spiking quantities.
Standard sample monitoring and anion and cation balance monitoring are used for 
and other projects. The absolute value of the relative error E of the anion and cation balance was less than 5%, which is reliable data. After testing, all data obtained were reliable.
HHRA MODEL AND PARAMETER ACQUISITION
Groundwater quality health risk assessment is an effective method to quantitatively evaluate the hazard degree of hazardous substances in groundwater to human body. Generally, the assessment starts from hazard identification and then carries out dose–effect analysis to evaluate exposure and risk characterization (Zhou et al. 2016; Tian et al. 2020a, 2020b, 2020c, 2020d). On the basis of field investigation, sampling and indoor analysis (hazard determination), combined with the information on the harmful effects of chemicals on human health provided by the International Center for Research on Cancer (IARC), determine the health effects of nitrate on humans (dose–effect relationship) (Chen 2010; Chen et al. 2016).
At present, there are many risk models for evaluating the hazards of groundwater pollutants to human beings, among which the HHRA model recommended by the USEPA (Chen et al. 2017; Zhai et al. 2017; Javaid et al. 2019) is the most widely used in groundwater pollutant risk assessment (Su et al. 2013; Zhang et al. 2017; Mahmoud et al. 2018). In this paper, the health risk caused by nitrate pollution in groundwater in the Datong Basin is scientifically evaluated by using the evaluation model.
Hazard identification
The first step in HHRA is to identify hazards, that is, to determine the potential adverse effects of human intake of hazards, the possibility of such adverse effects, and the certainty and uncertainty of such adverse effects. The objective is to evaluate the evidence weight of adverse health effects according to the evaluation results of all existing toxicity and action mode data.
In order to achieve this goal, more detailed site-related data and historical information, concentration data of pollutants in groundwater and other samples of the site, analysis data of physical and chemical properties of the site, climate, hydrological and geological characteristics information and data of the site (location), relevant information such as land use mode, sensitive people and buildings of the site and surrounding plots are needed.
Dose–response assessment
) (USEPA 2005). The determination of 
is as follows:
The standard value of nitrate is 10 mg/L (USEPA 2001; Yang et al. 2012).
Exposure assessment
Exposure assessment is a process of measuring, estimating or predicting the intensity, time and frequency of people's exposure to pollutants in the medium. Exposure assessment is the quantitative basis for risk assessment, which is mainly the assessment of exposure environment, environmental concentration, receptor exposure route, environmental medium and exposure.
is the daily average exposure dose through drinking water (mg/kg d); 
is the daily average exposure dose of skin contact route (mg/kg d) and C is the measured concentration of nitrate in groundwater (mg/L).The values of the parameters are shown in Table 1.
Meaning and value of each parameter
| Parameter meaning | Value | |||||
|---|---|---|---|---|---|---|
| Children | Females | Males | Infants | Unit | ||
| EF | Exposure frequency | 365 | 365 | 365b | 365 | D/a |
| BW | Average body weight | 32.02e | 60.4a | 69.55a | 7.68e | kg |
| ABS | Gastrointestinal absorption coefficient | 0.5c | 0.5c | 0.5c | 0.5c | |
| IR | Amount of drinking water | 1.5b | 2f | 2f | 0.65b | L/d |
| ED | Exposure duration | 6b | 30b | 30b | 0.5d | a |
| SA | Body surface areas | 9,035.2 | 1,600a | 1,700a | 3,416 | cm2 |
| AT | Average exposure time | 2,190 | 10,950 | 10,950 | 182.5b | d |
| EV | Bathing frequency | 1b | 1b | 1b | 1b | Time/d |
| ET | Bath time | 0.167c | 0.167c | 0.167c | 0.167c | h/d |
| CF | Unit conversion facter | 0.002b | 0.002b | 0.002b | 0.002b | L/cm3 |
| KP | Dermal adsorption | 0.001b | 0.001b | 0.001b | 0.001b | Cm/h |
| Parameter meaning | Value | |||||
|---|---|---|---|---|---|---|
| Children | Females | Males | Infants | Unit | ||
| EF | Exposure frequency | 365 | 365 | 365b | 365 | D/a |
| BW | Average body weight | 32.02e | 60.4a | 69.55a | 7.68e | kg |
| ABS | Gastrointestinal absorption coefficient | 0.5c | 0.5c | 0.5c | 0.5c | |
| IR | Amount of drinking water | 1.5b | 2f | 2f | 0.65b | L/d |
| ED | Exposure duration | 6b | 30b | 30b | 0.5d | a |
| SA | Body surface areas | 9,035.2 | 1,600a | 1,700a | 3,416 | cm2 |
| AT | Average exposure time | 2,190 | 10,950 | 10,950 | 182.5b | d |
| EV | Bathing frequency | 1b | 1b | 1b | 1b | Time/d |
| ET | Bath time | 0.167c | 0.167c | 0.167c | 0.167c | h/d |
| CF | Unit conversion facter | 0.002b | 0.002b | 0.002b | 0.002b | L/cm3 |
| KP | Dermal adsorption | 0.001b | 0.001b | 0.001b | 0.001b | Cm/h |
aThese data come from PRCMEP (2014).
bThese data come from USEPA (1989).
cThese data come from USEPA (1991).
dThese data come from USEPA (2004).
eThese data come from PRCMH (2003).
fThese data come from Tian et al. (2020a, 2020b, 2020c, 2020d).
Risk characterization
is the non-carcinogenic oral hazard coefficient (dimensionless); 
is the non-carcinogenic skin hazard coefficient (dimensionless); 
is the reference dose of drinking water (mg/kg d), taken as 1.6; 
is the reference dose absorbed by skin (mg/kg d), taken as 1.0; 
is the intake dose of drinking water (mg/kg d); 
is the skin absorbed dose (mg/kg d) and 
is the total risk coefficient (dimensionless).For groundwater risk control value based on non-carcinogenic effect, the non-carcinogenic risk threshold recommended by USEPA is 1 (Huang et al. 2017; Javed et al. 2018; Wu et al. 2018).
In order to provide targeted and effective protection according to different groups of people, this paper carries out 
risk assessment for infants (one year old and below), children (2–17 years old), adult males and adult females, respectively. See Table 1 for specific parameters.
Data analysis
The distribution of groundwater chemical concentration and the correlation of its components were analyzed by statistical analysis software (SPSS 19). This method reveals the correlation between different chemical components of groundwater.
Water quality analysis
The quality standard for groundwater of the People's Republic of China (QSGC) is adopted for evaluation (GB/T14848-2017) (National Standard of the People's Republic of China 2017).
of the individual components, respectively. According to the standards in Table 2, the formula for calculating the F value of comprehensive evaluation score is as follows:
is the average value of evaluation score 
of each single component; 
is the maximum value in the evaluation score 
of single component and N is the number of participating projects. Quality evaluation and grading of single component
| Category | I | II | III | IV | V |
|---|---|---|---|---|---|
| Fi | 0 | 1 | 3 | 6 | 10 |
| Category | I | II | III | IV | V |
|---|---|---|---|---|---|
| Fi | 0 | 1 | 3 | 6 | 10 |
Then, according to the F value, the groundwater quality is classified according to the method specified in the standard (see Table 3).
Classification of comprehensive evaluation of groundwater quality
| Code | I | II | III | IV | V |
|---|---|---|---|---|---|
| Level | Excellent | Good | Preferably | Poor | Range |
| Pollution degree | Uncontaminated | Slight pollution | Medium pollution | Heavy pollution | Severe pollution |
| F | <0.80 | ≥0.80, <2.50 | ≥2.50, <4.25 | ≥4.25, <7.20 | ≥7.20 |
| Code | I | II | III | IV | V |
|---|---|---|---|---|---|
| Level | Excellent | Good | Preferably | Poor | Range |
| Pollution degree | Uncontaminated | Slight pollution | Medium pollution | Heavy pollution | Severe pollution |
| F | <0.80 | ≥0.80, <2.50 | ≥2.50, <4.25 | ≥4.25, <7.20 | ≥7.20 |
RESULTS AND DISCUSSION
General characteristics of groundwater quality
and Cl− in the groundwater, which meet the requirements for drinking water and industrial water and meet the needs of human health. The average concentration of 
in the study area is 31.06 mg/L, which has exceeded the standard for healthy drinking water. The maximum concentration of 
is 474 mg/L, which is 15 times higher than the standard value and the CV value reaches 2 indicating that 
is distributed unevenly and has health risks (Table 4 and Figure 2). Chemical characteristic values of groundwater in the study area (pH: dimensionless, other material units: mg/L)
| CaCO3 | TDS | pH | Cl− |  |  | Fe | F− | |
|---|---|---|---|---|---|---|---|---|
| MIN | 129 | 198 | 7.42 | 4.17 | 10.8 | 0.11 | 0.019 | 0.34 |
| MAX | 1,175 | 1,935 | 8.64 | 302 | 1,074 | 474 | 0.64 | 2.25 |
| AVG | 295.61 | 512.82 | 8.13 | 39.4 | 105.53 | 31.06 | 0.1 | 0.89 |
| SV | ≤450 | ≤1,000 | 6.5 ≤ pH ≤ 8.5 | ≤250 | ≤250 | ≤20.0 | ≤0.3 | ≤1.0 |
| CV | 0.55 | 0.68 | 0.02 | 1.55 | 1.3 | 2 | 1.18 | 0.44 |
| CaCO3 | TDS | pH | Cl− | | | Fe | F− | |
|---|---|---|---|---|---|---|---|---|
| MIN | 129 | 198 | 7.42 | 4.17 | 10.8 | 0.11 | 0.019 | 0.34 |
| MAX | 1,175 | 1,935 | 8.64 | 302 | 1,074 | 474 | 0.64 | 2.25 |
| AVG | 295.61 | 512.82 | 8.13 | 39.4 | 105.53 | 31.06 | 0.1 | 0.89 |
| SV | ≤450 | ≤1,000 | 6.5 ≤ pH ≤ 8.5 | ≤250 | ≤250 | ≤20.0 | ≤0.3 | ≤1.0 |
| CV | 0.55 | 0.68 | 0.02 | 1.55 | 1.3 | 2 | 1.18 | 0.44 |
Notes: MIN, minimum value; AVG, average value; MAX, maximum value; CV, coefficient of variation; SV, Standard value.
Chemical concentration distribution map of groundwater (pH: dimensionless, other material units: mg/L).
Chemical concentration distribution map of groundwater (pH: dimensionless, other material units: mg/L).
Nitrate pollution of groundwater
Class I area accounts for 6% of the sample data, Class II area accounts for 8% of the sample data, Class III area accounts for 52% of the sample data, Class I–III water is mainly distributed in Shuozhou, Daixian and Wutai Area, Class IV area accounts for 13% of the sample data, mainly distributed in Datong, Hunyuan and Lingqiu, Class V area accounts for 21% of the sample data, mainly distributed in Zuoyun and Yingxian areas, as well as Yanggao and Guangling areas. The results show that the nitrate pollution degree of groundwater in this area is high and has zoning. Overall, the over standard rate of 
is 34%. The high content of 
should be highly valued and health risk assessment should be carried out. 
Proportion of various types of nitrates.
Zoning map of nitrate pollution.
Groundwater quality evaluation
With the development of industry and agriculture, the discharge of industrial wastewater and the continuous use of agricultural fertilizers and pesticides, the groundwater quality in the study area is deteriorating, and the groundwater pollution continues to occur and develop. Finding out the current situation and distribution of groundwater quality can effectively support the construction of national ecological civilization and provide basis for ecological restoration.
Pie chart of groundwater quality type.
, Fe, F−, 
, total hardness (CaCO3) and TDS. Through the research, the current situation and distribution characteristics of groundwater quality are found out, which can effectively support the construction of national ecological civilization and provide a reliable basis for ecological restoration. 
Zoning of groundwater quality.
SPSS19 software was used for correlation analysis of eight parameters: 
, TDS, Cl−, CaCO3, pH, F−, Fe and 
(Table 5) (Nakagawa et al. 2016). 
was significantly correlated with CaCO3 and Cl− at 0.01 level, and 
and 
were significantly correlated at 0.05 level (Jalali 2011). The significant correlation between 
and CaCO3, Cl−, 
indicates that the increase in 
concentration is related to the use of 
fertilizers and organic fertilizers in agricultural production, as well as the discharge of sewage in people's lives (Rahmati et al. 2014; Lasagna et al. 2016). Therefore, it is believed that the unreasonable use of fertilizers and the discharge of sewage in human production and life are the main reasons for the increase in 
concentration in groundwater (Li et al. 2016).
Correlation table of water chemistry parameters
| CaCO3 | TDS | pH | Cl− |  |  | Fe | F− | |
|---|---|---|---|---|---|---|---|---|
| CaCO3 | 1 | |||||||
| TDS | .838** | 1 | ||||||
| pH | −.200* | −0.04 | 1 | |||||
| Cl− | .474** | .782** | 0.049 | 1 | ||||
 | .804** | .797** | −0.04 | .433** | 1 | |||
 | .518** | .656** | −0.06 | .525** | .231* | 1 | ||
| Fe | 0.007 | 0.081 | −0.11 | 0.146 | −0.02 | 0.066 | 1 | |
| F− | 0.064 | .390** | .311** | .394** | 0.126 | .313** | 0.15 | 1 |
| CaCO3 | TDS | pH | Cl− | | | Fe | F− | |
|---|---|---|---|---|---|---|---|---|
| CaCO3 | 1 | |||||||
| TDS | .838** | 1 | ||||||
| pH | −.200* | −0.04 | 1 | |||||
| Cl− | .474** | .782** | 0.049 | 1 | ||||
| | .804** | .797** | −0.04 | .433** | 1 | |||
| | .518** | .656** | −0.06 | .525** | .231* | 1 | ||
| Fe | 0.007 | 0.081 | −0.11 | 0.146 | −0.02 | 0.066 | 1 | |
| F− | 0.064 | .390** | .311** | .394** | 0.126 | .313** | 0.15 | 1 |
*At 0.05 level, there was significant correlation.
**At 0.01 level, there was significant correlation.
HEALTH RISKS FOR ADULT WOMEN AND MEN
pollution of groundwater usually does not cause harm to adult males in the area. However, in Yingxian County, Dongxiao village and Nancun village, 
pollution has health risks. The maximum HI value of adult women is 9.84 and about 10% of the study area has health risks. It is distributed in Yingxian County, Dongxiao village and Nancun village. There is a health risk of 
pollution, which is basically the same as that of adult males. The results showed that 
pollution of groundwater in the study area did little harm to the adult population; however, about 10% of the study area belongs to the health risk area, which is located in the middle and northeast of the study area. Adult female risk areas (HI < 1) roughly overlap with male risk areas (Figure 7). However, the maximum HI for women and men were 9.84 and 8.55, respectively. Therefore, compared with adult women, adult men have a lower risk, which is due to physiological factors. This finding is consistent with that of Weining plain in Northwest China, and emphasizes the importance of gender in the process of HHRA. 
Health risk distribution map.
HEALTH RISKS FOR INFANTS AND CHILDREN
The health risk calculation results of children and infants are shown in Figure 7. Low-risk areas for infants are distributed around Shuozhou City and Datong City, while high-risk areas are distributed in Yingxian County, Dongxiao village, South village, Zuozhi and Fanshi. The high-risk area accounts for 39%, indicating that 39% of infants' HI is unacceptably high. The HI value in this area is between 1.01 and 25.32, indicating that infants in this area have a high potential health risk. For children, 83% of the study areas had acceptable HI levels distributed in Shuozhou City, Datong City and most of the surrounding areas. The HI of 17% of children in the study area is unacceptably high. The HI value in this area is between 1.08 and 14.21, distributed in Yingxian County, Dongxiao village, Nancun and other areas, indicating that children in this area have high potential health risks. The HI value of children is lower than that of infants, and the maximum value is 14.21. The total area of health risk area is 21% less than that of infants.
in infants in the Datong Basin is higher than that of minors and adults, and the risk of women is higher than that of men, and infants need to be protected more, which is related to the difference in weight of different age groups. The results are consistent with those of Chen et al. (2005). The risk ratio of different populations is shown in Figure 8. The risk in urban areas is lower than that in rural areas, mainly due to the use of 
fertilizer and organic fertilizer in rural areas, and cities are not affected by 
fertilizer and organic fertilizer. 
Risk proportion chart of different categories of people.
DISCUSSION
It can be seen from Figures 1, 4 and 6 that in the alluvial-proluvial plain area with low altitude and small topographic gradient, agricultural production activities are relatively developed, and the amount of fertilizer and other fertilizers used in farmland is large. Farmland irrigation and rainfall in plain areas are the main recharge sources of groundwater (Amir et al. 2021; Zhang et al. 2021). After farmland irrigation or rainfall, most of the water, except for partial evaporation and absorption by plants, seeps into the aeration zone or groundwater. The nitrogen components contained in fertilizer will gradually enter the groundwater environment with the infiltration of groundwater, resulting in nitrate pollution in groundwater (Anju & Kavita 2022). Therefore, compared with the mountainous areas with higher altitude and larger topographic gradient, the groundwater in the alluvial-proluvial plain areas with lower altitude and smaller topographic gradient is more vulnerable to agricultural non-point source pollution (Marghade et al. 2021; Nitika et al. 2021).
Agricultural non-point source pollution leads to the continuous accumulation of nitrate in groundwater, and high nitrate concentration will cause serious harm to human health. Hypermethemoglobinemia is a health problem caused by high nitrate in drinking water. When the nitrate content is high in the body of newborns, cyanosis will also occur, which will lead to mucous membrane blueness and digestive and respiratory diseases in infants (Saravanan et al. 2022). The intake of large amounts of nitrate has a complex relationship with cancer, adverse reproductive outcomes and other health problems, which requires further research in the future. In this paper, the health risk assessment of adult men, adult women, children and infants is carried out respectively, and the corresponding conclusions are drawn, which is conducive to improving people's awareness of the protection of infants and children against nitrate risk.
Abooalfazl et al. (2019) evaluated fluoride and nitrate pollutants in drinking water resources and their health risks in semi-arid areas of southwestern Iran. This study showed that children, adolescents and adults are vulnerable groups as they are exposed to high concentrations of fluoride and nitrate in drinking water, posing a non-carcinogenic risk. Alimohammadi et al. (2018) conducted a determination and risk assessment of nitrate concentration in bottled water in Iran. The results showed that the nitrate concentration in bottled water ranged from 0.146 to 0.1 mg/L (average 10.55 mg/L), with one type of bottled water having a higher nitrate content than the World Health Organization guidelines. Radfard et al. (2019) conducted a health risk assessment of fluoride and nitrate in drinking water for rural residents in the arid southeastern region of Bardaskan, Iran, and found that the highest and lowest concentrations of nitrate and fluoride occurred in the northeast region. These studies indicate that the health risk of nitrate pollution is a global health issue that needs to be given sufficient attention.
Han et al. (2021) conducted a health risk assessment model on four groups of people: infants, children, adult males and adult females. The results showed that long-term consumption or exposure to groundwater with high nitrate levels in the area would pose great risks to infants and children. Tian et al. (2020a, 2020b, 2020c, 2020d) conducted a study on the health risks of groundwater chemistry and nitrate intake in Helen City, and found that human activities are the cause of the formation of chemical composition in shallow groundwater in Helen. The degree of harm caused by 
pollution is in the order of infants > children > adult females > adult males. The above two conclusions are consistent with this study, and the research results can provide technical reference and theoretical support for the evaluation of groundwater nitrate under the same type of hydrogeological conditions.
The research results of predecessors, as well as the experience and test data obtained from this survey, provide strong support for this study. However, there is limited experimental research on the impact of nitrate pollution on human health, which points out the research direction for future scientific research.
Dynamic monitoring of groundwater indicators, timely detection of changes in pollutants, scientific assessment of pollutant risks, precise implementation of policies and ensuring drinking water safety are suggested.
CONCLUSION
Through research, qualitative and quantitative conclusions have been drawn on the current situation of water quality, influencing factors and 
exceeding the standard in the research area. Qualitative and quantitative conclusions have also been drawn on the health risks caused by 
exceeding the standard. These new achievements will help people improve their awareness of risk prevention, protect the environment, respect nature, implement precise policies and develop scientifically.
Research has found that the groundwater in the study area is mainly classified as Class II water, with overall good quality. Although Class V water has not been identified, Class IV water accounts for a relatively large proportion and requires strengthened monitoring and remediation. The main influencing factors for water quality are 
, Fe, F− and 
.
About 34% of 
samples in the study area exceed the Class III value, and the use of agricultural fertilizer is the main source of 
in the groundwater in the area.
There are significant differences in the health hazards of groundwater 
pollution on different populations, and infants and children are more vulnerable to nitrate pollution.
The division of pollution areas and high-risk groups has an important guiding role for health risk prevention. In the polluted area, people can distinguish people of different sexes and ages for scientific protection.
is significantly correlated with CaCO3, Cl− and 
, and the increase in 
concentration is related to the use of 
fertilizers, organic fertilizers and the discharge of domestic sewage in agricultural production.
In the future, we should further research and develop simulation and evaluation methods to improve the accuracy and reliability of prediction and evaluation, in order to protect the sustainable use and management of groundwater resources.
ACKNOWLEDGEMENTS
Thanks for the support of China Geological Survey projects (DD20208069, DD20211558)!
FUNDING
This research was funded by the funding project of Northeast Geological S&T Innovation Center of China Geological Survey (NO. QCJJ2022-43), Natural Resources Comprehensive Survey Project (DD20230470), (DD20230508), (DD20208069)
AVAILABILITY OF DATA AND MATERIAL
The data and material data provided by the laboratory of Harbin Center of Natural Resources Comprehensive Survey, CGS are reliable.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.
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