Health risk assessment of drinking groundwater in rural areas of Ru village and surrounding areas in Wutai County, China

pollution in groundwater is a global environmental problem. Nitrates are easy to dissolve and have strong fluidity (Hand et al. 2013; Zakhem & Hafez 2015; Tian et al. 2020a; Zhang et al. 2021). It can enter the underground through leaching and surface runoff (Tian et al. 2020c). It is a chemical pollutant widely present in groundwater (Sun et al. 2019; Amir et al. 2021). Long-term consumption of contaminated groundwater can lead to diseases, such as digestive system cancer, methemoglobinemia, and blue baby syndrome, posing a serious threat to human health (Chen 2010, 2016, 2020; Gu et al. 2013). After nitrate-contaminated groundwater enters the human body, it can cause harm to the human body. Therefore, it is necessary to evaluate the harm and degree of nitrate-contaminated groundwater. HHRA is a qualitative and quantitative method for assessing the degree of harm to human health caused by contaminated groundwater (Li et al. 2016; Mahmoud et al. 2018; Javaid et al. 2019).

In 1983, the National Academy of Sciences (NAS) of the United States first proposed 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 1989, 1991, 2001, 2004, 2005) provided 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. Su et al. (2013) used models to evaluate the impact of high nitrate levels in groundwater in different regions on human health.

Rucun Township and its surrounding areas are the foundation of grain production in Wutai County. In order to increase agricultural production, farmers use a large amount of nitrate fertilizers. The rural areas in this area mainly rely on groundwater as their drinking water source. It is necessary to investigate the distribution pattern and pollution status of nitrate in this area, evaluate the health risks of nitrate in drinking groundwater, and ensure the health of the rural population. Firstly, the study area did not specifically study the history of nitrate pollution in groundwater. Secondly, no one in the study area conducted a health risk assessment of nitrate pollution in groundwater. Finally, this study identified the current situation of nitrate pollution in the region and constructed a health risk model suitable for the study area, drawing quantitative conclusions on the regional health risk situation. It has a positive guiding role in preventing the health risks of drinking groundwater for rural populations in this region. It is of great significance for achieving the national development strategy of ‘Healthy China’.

The research area is located in Rucun Township and surrounding areas of Wutai County in the central eastern part of Shanxi Province, with geographical coordinates of 113° 15′ 00″–113° 30′ 00″ E and 38° 40′ 00″–38° 50′ 00″ N. It belongs to a typical continental monsoon climate, and suitable crops for growth include corn, millet, oilseeds, oats, beans, potatoes, etc. Belonging to the Zhongshan terrain with intermountain basins (Rucun, Wutai, Doucun basins) and river valleys, the overall terrain is high in the north and low in the south. The exposed strata include the Archean, Proterozoic, Lower Paleozoic Cambrian, Ordovician carbonate rocks, Upper Paleozoic Carboniferous, Permian clastic rocks, Neogene Upper Tertiary, and Quaternary loose rocks. The Quaternary loose layer is mainly composed of loess, with a precipitation infiltration coefficient of 0.1. The geotectonic part is located at the junction of Zhoushan syncline of Luliang Taihang fault block and Mount Wutai block uplift and Fuping dome-like structural unit, and the Hutuo River new rift is located in the west. The main rivers in the area include Qingshui River and its tributary Siyang River, which are the first- and second-level tributaries of the Hutuo River. Qingshui River originates from Zixia Valley and Dongtai Valley of Mount Wutai, with a total length of 104 km and an annual runoff of 255 million m³. Siyang River, originating from Xiaobai Village, has a total length of 20 km and an annual total runoff of 56.27 million m³. The main source of supply for groundwater in the area is atmospheric precipitation, and the discharge of groundwater is basically the same as that of surface water in the northeast-southwest direction. It overflows in the area of Pingshang Village at the intersection of the Hutuo River and the Qingshui River and flows into the Hutuo River.

The reliability test of water sample data is carried out by using the anion and cation balance test method, and the absolute value of the relative error E of the anion and cation balance is less than 5% as the reliable data. After the test, all data are reliable data.

The distribution of groundwater chemical concentration and the correlation between various components were analyzed using statistical analysis software (SPSS19). The correlation between different chemical components of groundwater was revealed using this method (Li et al. 2015; Sun et al. 2021; Anju & Kavita 2022; Du et al. 2022).

The Durov diagram drawn using AqQA software was used to reflect and describe the chemical characteristics of groundwater in the study area (Dzulfakar et al. 2011; Huang et al. 2017; Sun et al. 2017, 2022a, 2022b).

Groundwater quality health risk assessment is an effective method to quantitatively evaluate the hazard degree of hazardous substances in groundwater to the human body. Generally, the assessment starts with hazard identification and then carries out dose–effect analysis to evaluate exposure and risk characterization (Chen et al. 2017; Alireza et al. 2020; Sun et al. 2023a). 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) (Marghade et al. 2021; Nitika et al. 2021; Sun et al. 2023b).

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 United States Environmental Protection Agency (USEPA) (Sun et al. 2017, 2020b) is the most widely used in groundwater pollutant risk assessment (Sun et al. 2020a). The health risk of nitrate pollution in groundwater in Rucun Township and surrounding areas was scientifically evaluated using this evaluation model.

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 (Javed et al. 2019; Saravanan et al. 2022; Sun et al. 2023b).

In order to achieve this goal, more detailed site-related data and historical information are needed; concentration data of pollutants in site groundwater and other samples; 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.

In the risk assessment of Rucun Township and surrounding areas, the standard value of groundwater nitrate was determined to be 10 mg/L (USEPA 2001).

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.

The meanings of the parameters in the above two equations are as follows: is the daily average exposure dose through drinking water (mg/kg/day). is the daily average exposure dose of skin contact route (mg/kg/day); C is the measured concentration of nitrate in groundwater (mg/L).

The meanings of other parameters are shown in Table 1.

In the above three formulas, each parameter represents the following meanings: is the noncarcinogenic oral hazard coefficient (dimensionless). is the noncarcinogenic skin hazard coefficient (dimensionless). is the reference dose of drinking water (mg/kg/day), taken as 1.6. is the reference dose absorbed by skin (mg/kg/day), taken as 1.0. is the intake dose of drinking water (mg/kg/day). is the skin absorbed dose (mg/kg/day). is the total risk coefficient (dimensionless).

For groundwater risk control value based on noncarcinogenic effect, the noncarcinogenic risk threshold recommended by USEPA is 1 (Ni et al. 2010; Zhou et al. 2016; Xu et al. 2021; Zhang et al. 2021; Sun et al. 2022a, 2022b).

In order to provide targeted and effective protection according to different groups of people, this paper carries out risk assessment for infants (1-year-old and below), children (2–17 years old), adult males, and adult females, respectively. See Table 1 for specific parameters.

Statistical analysis can reflect a rough overview of the chemical composition of groundwater in a certain region or period of time. In order to understand the hydrochemical characteristics of groundwater in the region, statistical analysis was conducted on various indicators of shallow groundwater water sample detection data in Rucun Township and surrounding areas using SPSS19 software to obtain the statistical characteristic values of hydrochemical components, as shown in Table 2.

Table 2

Statistical table of groundwater indicators (pH dimensionless, other indicators in mg/L)

.	CaCO3 (mg/L) .	TDS (mg/L) .	(mg/L) .	pH .	(mg/L) .	(mg/L) .	K+ (mg/L) .	Na+ (mg/L) .	Cl− (mg/L) .	(mg/L) .	(mg/L) .
AVG	289.97	288.18	43.99	7.71	67.56	21.28	1.94	11.93	14.95	29.18	663.52
MAX	530.40	512.00	109.40	8.22	134.50	46.50	6.68	52.60	51.10	245.20	1,362.00
MIN	191.00	201.00	5.94	7.18	38.00	8.01	0.39	3.93	4.28	0.49	443.70
SD	79.98	82.43	33.77	0.24	19.33	9.43	1.46	8.83	12.49	42.97	172.66
CV	0.28	0.29	0.77	0.03	0.29	0.44	0.75	0.74	0.84	1.47	0.26

.	CaCO3 (mg/L) .	TDS (mg/L) .	(mg/L) .	pH .	(mg/L) .	(mg/L) .	K+ (mg/L) .	Na+ (mg/L) .	Cl− (mg/L) .	(mg/L) .	(mg/L) .
AVG	289.97	288.18	43.99	7.71	67.56	21.28	1.94	11.93	14.95	29.18	663.52
MAX	530.40	512.00	109.40	8.22	134.50	46.50	6.68	52.60	51.10	245.20	1,362.00
MIN	191.00	201.00	5.94	7.18	38.00	8.01	0.39	3.93	4.28	0.49	443.70
SD	79.98	82.43	33.77	0.24	19.33	9.43	1.46	8.83	12.49	42.97	172.66
CV	0.28	0.29	0.77	0.03	0.29	0.44	0.75	0.74	0.84	1.47	0.26

AVG, average; MAX, maximum value; MIN, minimum value; SD, standard deviation; CV, coefficient of variation.

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From Table 2, it can be seen that TDS and CaCO₃ are relatively high, indicating a higher hardness and mineralization of groundwater. In terms of ion composition, the average concentration of is the highest, followed by ⁠, ⁠, ⁠, Cl⁻, Na⁺, and K⁺, indicating that it dominates the ions in groundwater. Additionally, the average concentration of ⁠, ⁠, ⁠, Cl⁻, and Na⁺ is relatively high, indicating a higher absolute concentration in groundwater. The pH value of the groundwater in the study area is between 7.18 and 8.22, indicating that the groundwater is slightly alkaline. The coefficient of variation is a characteristic of variable amplitude and stability. The smaller the variable amplitude, the stronger the stability, and the smaller the coefficient of variation, and vice versa. The large coefficient of variation indicates that the factors influencing the formation and evolution of groundwater chemical components are complex. The pH coefficient of variation is the smallest, reflecting its stability in the groundwater of the region. TDS, CaCO₃, ⁠, ⁠, not only have high concentrations, but also are relatively stable. The coefficient of variation of is the highest, while the coefficients of variation of Cl⁻, Na⁺, and K⁺ are relatively large, indicating that their concentration values vary significantly in different regions and are susceptible to factors such as hydrological and meteorological conditions, topography, aquifer media, and human activities. The standard deviation (SD) and coefficient of variation of are both high, indicating that the concentration of in the region is high and there is a significant difference in concentration between different regions. From the statistical results, the minimum value of is 5.94 mg/L, the maximum value is 109.4 mg/L, and the average value is 43.99 mg/L. The average value exceeds the limit value of Class III water by 20 mg/L. Overall, it has an impact on groundwater quality, with a coefficient of variation of 0.77, indicating that has obvious variation characteristics and significant differences in distribution across regions.

From the chemical analysis results of groundwater, it can be seen that the cation of groundwater in the study area is mainly calcium-type water, while the anion is bicarbonate type, indicating that coexists with and ⁠.

Pearson correlation coefficient matrix is a widely used tool in hydrogeochemistry, which can quantitatively and clearly represent the correlation between various ions or indicators. This article uses SPSS19 software to calculate the correlation coefficient matrix of water quality indicators, as shown in Table 3.

Table 3

Correlation matrices of hydrochemical parameters of groundwater

.	.	CaCO3 .	TDS .	pH .	.	.	K+ .	Na+ .	Cl− .	.	.
	1
CaCO3	.697**	1
TDS	.749**	.955**	1
pH	−.311	−.220	−.225	1
	.588**	.886**	.835**	−.160	1
	.424*	.694**	.713**	−.081	.413*	1
K+	−.410*	−.282	−.235	−.212	−.325	−.161	1
Na+	.316	.251	.480**	.024	.063	.576**	.051	1
Cl−	.716**	.494**	.667**	−.117	.456*	.253	−.083	.586**	1
	−.005	.515**	.517**	.237	.588**	.486**	.151	.302	.242	1
	.640**	.751**	.716**	−.409*	.528**	.584**	−.391*	.167	.208	−.066	1

.	.	CaCO3 .	TDS .	pH .	.	.	K+ .	Na+ .	Cl− .	.	.
	1
CaCO3	.697**	1
TDS	.749**	.955**	1
pH	−.311	−.220	−.225	1
	.588**	.886**	.835**	−.160	1
	.424*	.694**	.713**	−.081	.413*	1
K+	−.410*	−.282	−.235	−.212	−.325	−.161	1
Na+	.316	.251	.480**	.024	.063	.576**	.051	1
Cl−	.716**	.494**	.667**	−.117	.456*	.253	−.083	.586**	1
	−.005	.515**	.517**	.237	.588**	.486**	.151	.302	.242	1
	.640**	.751**	.716**	−.409*	.528**	.584**	−.391*	.167	.208	−.066	1

** At the 0.01 level (bilateral), there is a significant correlation.

* At the 0.05 level (bilateral), there is a significant correlation.

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From Table 3, it can be seen that the correlation coefficients between TDS and ⁠, CaCO₃, ⁠, ⁠, are all greater than 0.7, indicating that ⁠, CaCO₃, ⁠, ⁠, have a controlling effect on TDS. TDS has a good correlation with Na⁺, Cl⁻, ⁠, indicating that Na⁺, Cl⁻, have a significant contribution to TDS; has a good correlation with Cl⁻, CaCO₃, ⁠, ⁠, K⁺, in addition to TDS, indicating that coexists with Cl⁻, CaCO₃, ⁠, ⁠, K⁺, HCO₃ in groundwater; is related to pH, firstly, it indicates that the pH of water is alkaline, and at the same time, it indicates that the aqueous solution of is weakly alkaline. There is a good correlation between and (correlation coefficient of 0.588), indicating that simple dissolution of gypsum has control over ⁠, but this control is not unique. The correlation between ⁠, ⁠, and (correlation coefficients of 0.528 and 0.584, respectively) indicates the contribution of weathering and leaching of dolomite and calcite to ions in groundwater.

Through correlation analysis, it can be concluded that coexists with Cl⁻, CaCO₃, ⁠, ⁠, K⁺ and in groundwater. This result further supports the conclusion that coexists with and in groundwater chemical analysis.

When HI>1, there is a health risk, and the higher the HI value, the higher the risk. The risk zone for adult women (HI > 1) is greater than that for adult men, and approximately 47.29% of the study area belongs to the health risk zone (Figure 8(b)). This finding is consistent with the findings of Zibo City, China (Liu et al. 2021), where there are differences in the health risks of pollution among different gender groups, and emphasizes the importance of gender in the HHRA process.

Both children and infants have significant health risk areas, with a health risk area ratio of 51.27% for children (Figure 8(c)) and 66.92% for infants (Figure 8(d)), mainly distributed in the eastern part of the study area.

Groundwater is an important source of water for humans, and as surface water pollution worsens and is no longer suitable as a drinking water source, people's dependence on groundwater will continue to rise. According to a survey conducted by the National Health Association and the Ministry of Health, groundwater is the main source of drinking water in rural China, with 74.87% of the population drinking groundwater. The survey shows that rural residents in the study area do not have water treatment devices and directly drink groundwater without any treatment, which poses a hidden danger to their health.

Based on the quality status of groundwater and human health risks in the People's Republic of China, and with reference to the quality requirements for drinking water, industrial, agricultural, and other water use, groundwater is classified into five categories based on the level of nitrate content. Groundwater that can be used as drinking water after appropriate treatment is defined as Class IV (nitrate (in N) ≤ 30.0 mg/L), and groundwater that is not suitable as a source of drinking water is defined as Class V (nitrate (in N) > 30.0 mg/L). The investigation found that the main soil of farmland in the study area is composed of loess, which is a permeable layer. is prone to seep into the ground with precipitation, and the excess rate of nitrate in groundwater is 88.93%. Liu et al. (2021) believe that the excessive rate of nitrate pollution in drinking water in Zibo City is 10.76%, Sheng et al. (2019) believe that the highest concentration of nitrate pollution in groundwater in the Zhangye Basin has reached 283.32 mg/L, Xu & Zhang (2018) believe that the content of in shallow groundwater in the Jinghuiqu Irrigation District seriously exceeds the standard, with an average content of 29.78 mg/L, and 99.40% of the area exceeds the standard. The above results are consistent with the results of this study. This indicates that the nitrate pollution of drinking water or groundwater in these areas is severe, and it is necessary to strengthen scientific management and strict control; this is different from the research results of Chen et al. (2022) on nitrate pollution in drinking water sources in Chengdu. The research results on nitrate pollution in drinking water sources in Chengdu show that there is no nitrate pollution phenomenon in drinking water sources in Chengdu. There is nitrate pollution in the groundwater of Rucun Township and its surrounding areas in Wutai County. In order to meet the requirements for healthy drinking water, appropriate measures need to be taken to control the occurrence of nitrate pollution.

There are health risks associated with nitrate pollution in the groundwater of the study area. The health risk areas for adult women are greater than those for adult men, and the health risk areas for children and infants are higher than those for adults and infants. Liu et al. (2021) found in a study on nitrate pollution in drinking water in Zibo City that the highest noncarcinogenic risk of nitrate pollution was 1.99. Sheng et al. (2019) found in a study on nitrate pollution in groundwater in the Zhangye Basin that 32.39% of sampling points had unacceptable health risks for children, and 14.79% had unacceptable health risks for adults. Xu & Zhang (2018) found in their study on nitrate pollution in shallow groundwater in the Jinghui Canal irrigation area that the proportion of noncarcinogenic risk areas reached 66.55%. This is consistent with the results of this study, indicating the need to pay high attention to the health risks of nitrate pollution, with a particular emphasis on the health risks of infants and children.

By analyzing the chemical characteristics, material distribution characteristics, nitrate pollution characteristics, and quality characteristics of groundwater, an HHRA was constructed to evaluate the health risks caused by nitrate in groundwater. Scientific conclusions were drawn.

• 1.

  The groundwater in the research area is severely polluted by ⁠, and pollution areas are mainly concentrated in the main human activity areas. Especially, the excessive use of containing fertilizers and organic fertilizers in agricultural production is the main factor causing groundwater pollution.

• 2.

  The cation in the groundwater of the research area is mainly calcium-type water, while the anion is bicarbonate type.

• 3.

  Nitrate pollution in groundwater poses a health risk to humans. There are significant differences in the health hazards of groundwater pollution on different genders and age groups, with the order of risk being infants > children > adult women > adult men.

• 4.

  It is recommended to scientifically use nitrate fertilizers in agricultural production, and the research results indicate the direction for preventing human health risks.

During the writing process of the paper, members of the hydrogeological survey project team in the key areas of the upper reaches of the Hutuo River at the Harbin Natural Resources Comprehensive Survey Center of the China Geological Survey provided strong support. Two anonymous reviewers and journal editors provided valuable opinions and suggestions, and we would like to express our sincere gratitude.

This study is funded by the ‘Hydrogeological Survey of Key Areas in the Upper Reaches of the Hutuo River (DD20230470)’ project, the ‘Survey of Lakes in Northeast Plain and Mountainous Lake Area (DD20230508)’ project, and the ‘Exploration and Research on the Relationship and Ecological Impact Mechanism of Three Water Transformations in Hulunbuir High Plain (QCJJ2022-43)’ project.

This research was funded by the funding project of Northeast Geological S&T Innovation Center of China Geological Survey (QCJJ2022-43), the Hydrogeological Survey Project (DD20230470), (DD20230508).

The data and material data provided by the laboratory of Harbin Center of Natural Resources Comprehensive Survey, CGS are reliable.

Qifa Sun (1966–), male, senior engineer, doctor, mainly engaged in hydrogeology and environmental geology survey and research.

All relevant data are included in the paper or its Supplementary Information.

The authors have confirmed that they have no conflict to declare.