Abstract

In order to quantify the hydrochemical characteristics of groundwater in Hailun, analyze the hydrochemical process, and evaluate its health risks associated with nitrate intake, 77 shallow groundwater samples were collected and analyzed. The results show that groundwater in the study area is weakly acidic and groundwater chemical type was dominated by HCO3-Ca, HCO3•Cl-Ca, HCO3-Ca•Na and HCO3•Cl-Ca•Na. Rock weathering and dissolution, ion exchange, and human activities are the main reasons affecting the chemical composition of shallow groundwater in Hailun. The weathering and dissolution process of silicate under weakly alkaline conditions is the source of Na. The dissolution of calcite, dolomite, and gypsum are the main form of water–rock interaction. Results of health risk assessment show that the HQ value for adult males, adult females, children, and infants were in range of 0–1.52, 0–1.75, 0–3.58 and 0–6.08, respectively, and with a mean value of 0.19, 0.22, 0.44, 0.75, respectively. The harm of NO3 pollution is in the order of infant > child > adult female > adult male. The results of this study made local governments pay attention to drinking water safety issues for local residents.

HIGHLIGHTS

  • In order to quantify the hydrochemical characteristics of groundwater in Hailun, analyze the hydrochemical process, and evaluate its health risks associated with nitrate intake, 77 shallow groundwater samples were collected and analyzed.

  • The special purpose of this study is to: (1) explore the hydrochemical characteristics of groundwater; (2) understand the evolution of groundwater and the sources of major ions through factor analysis and hydrochemical analysis; (3) use the parameters recommended in the USEPA2004 guidelines and the HHRA model assesses the health risks of groundwater as drinking water.

  • For the first time, the study population was divided into four categories: adult males, adult females, children and infants.

  • The health risks of nitrate intake by different genders and age groups were studied. It is expected that the health risks of nitrate intake by different genders and ages can be obtained.

  • The results of the study will help local governments strengthen management and governance in places where the groundwater environment is fragile, thereby effectively improving the quality of drinking water for local residents.

INTRODUCTION

Groundwater is one of the most precious resources on the planet (Jha et al. 2007). It can meet the needs of human survival and development, including for living and drinking, agricultural irrigation, industrial production, etc. (Peiyue et al. 2011). However, over the past three decades, due to the rapid development of agricultural modernization in China, the demand for groundwater has been increasing (Chen et al. 2018). As a result, a series of environmental geological problems have emerged, such as aquifer drying (Rizeei et al. 2019), land subsidence (Raeisi et al. 2018), seawater intrusion (Yang et al. 2019), soil secondary salinization (Qiu et al. 2017), nitrate pollution (Li et al. 2016) and wetland degradation (Zhu et al. 2015). Among these hazards, nitrate pollution has attracted much attention from the social and scientific communities, mainly because it adversely impacts human health. According to studies, NO3-N in water has a greater harmful effect on humans and aquatic organisms. Methaemoglobinemia occurs when water with a nitrate content greater than 10 mg/L is drunk for a period of time (Jones et al. 2019). If the methemoglobin content in the blood is 70 mg/L, choking can occur (De Roos et al. 2003). Nitrate intake from drinking water is a risk factor for colon or rectal cancer (DellaValle et al. 2014). The above studies are based on the dietary and drinking water intake of nitrate (Schullehner et al. 2018).

Health risk assessment of groundwater is essential. Common pollutants in groundwater include fluoride (F), nitrate (NO3-N), ammonia nitrogen (NH4-N), nitrite (NO2-N), and heavy metals (Ma et al. 2016; Zhang et al. 2018). Su et al. (2013) evaluated the health risks of nitrate nitrogen in groundwater in agricultural wastewater irrigation areas in northeast China, and the results of the study were that the health risks in urban areas were lower than that of agricultural irrigation areas. Health risk assessments successfully compared the risk between adults and children (Su et al. 2013). Zhai et al. (2017) evaluated the health risks of nitrate nitrogen in groundwater in the northeast Plain. The results of the study were that the NO3 concentration in the southeast and northeast of the study area was the highest (Zhai et al. 2017). Li et al. (2014) calculated the health risks of nitrate nitrogen in groundwater in the industrial park in northwest China, and the research results show that the annual health risk is higher than the highest acceptable level recommended by the International Commission on Radiological Protection.

The Songnen Plain is China's most important commodity grain production base. Hailun is an important part of the northeast of the Songnen Plain and plays an important role in agricultural production. Since 1995, cereal production, especially rice production, has increased significantly (Luo et al. 2018). At the same time, with the increase of rice yield, the area irrigated by groundwater rapidly increased. Because surface water is far from meeting the needs of human agricultural production, farmers have to extract groundwater from aquifers for dryland irrigation. However, the hydrogeochemical characteristics of groundwater and drinking water quality in agricultural irrigation areas (Hailun) are still not very clear. This may limit the protection and proper use of groundwater resources, especially drinking water safety issues for local residents.

The purpose of this research can be summarized as: (1) explore the hydrochemical characteristics of groundwater; (2) understand the evolution of groundwater and the sources of major ions through factor analysis and hydrochemical analysis; (3) use the HHRA model to assess the health risks of groundwater as drinking water, with the parameters recommended in the USEPA (2004) guidelines. For the first time, the study population was divided into four categories: adult males, adult females, children and infants. The health risks of nitrate intake by different genders and age groups were studied. It is expected that the health risks of nitrate intake by different genders and ages can be obtained. The results of the study will help local governments strengthen management and governance in places where the groundwater environment is fragile, thereby effectively improving the quality of drinking water for local residents.

STUDY AREA

Study area description

The study region is located in the central part of Heilongjiang Province in northeast China, encompassing an area of 4,668 km2 between the latitudes of 46°58′E and 47°52′E and longitudes of 126°14′N and 127°45′N (Figure 1). The study area included Helen city and 23 towns, with a total population of approximately 799,838. Because it is located in the mid-latitudes of the northern hemisphere and belongs to a temperate continental semi-humid monsoon climate, the four seasons are distinctive. Rainfall is mainly concentrated in June–August, with an average annual rainfall of about 600 mm and an average annual temperature of 1–2 °C (Li et al. 2018). The elevation is higher in the northeast, and east, but is lower in the west, and southwest, with elevations ranging from 190 to 450 m above mean sea level. There are four types of landforms in the study area, including valleys and floodplains in the west, sloping plains in the middle, hilly areas in the northeast, and high plains in the east. Although the Hailun River, Zhayin River, and Sandaowulong River pass through the area, the seasonal variations in surface water are not suitable for agricultural production. In dry periods, when rivers are low and cannot meet the needs of agricultural production, large areas of groundwater are usually extracted for irrigation.

Figure 1

Location and sampling points of the study area.

Figure 1

Location and sampling points of the study area.

The flow direction of groundwater is consistent with the trend of terrain and the flow direction of surface water, which is from northeast to southwest. The distribution of groundwater resources is uneven, showing a pattern of scarcity in the east and north, and abundance in the west and south. In the western plains, groundwater resources are relatively abundant. Quaternary diving, confined water and Cretaceous confined water are the main mining layers in this area (Zhang et al. 2017). The groundwater level ranged from 5 to 15 m in the dry season. Under normal circumstances, the water output of a single well is 300–500 m3/day. In the high plains in the east and the hilly areas in the northeast, the Cretaceous confined water and bedrock fissure water develop, but its water output is generally less than 200 m3/day.

MATERIALS AND METHODS

Sampling and measurements

According to the research plan, from June 2019 to October 2019, 77 shallow groundwater samples were collected in two batches. Shallow groundwater samples were taken from wells used primarily for water supply and irrigation in rural areas. Generally, the depth of water wells is less than 50 m, and their distribution is shown in Figure 1. The spatial distribution of sampling points is not uniform, but is consistent with the distribution of each village, which can objectively reflect the characteristics of groundwater mining status in the study area. In the process of sampling, it is performed in accordance with the sample collection specifications of the China Geological Survey. Each sampling well must be cleaned by pumping water for more than 10 minutes in accordance with groundwater sampling guidelines. Sampling is mainly divided into three steps. The first step is to rinse the vial with well water three times, then fill with water and seal. In the second step, the groundwater sample is stored in a 4 °C incubator. The third step is to return the sample to a qualified laboratory for testing.

In this study, groundwater samples were tested in the laboratory of the Shenyang Institute of Geology and Mineral Resources which has the groundwater testing qualification issued by China.

The laboratory test index includes pondus Hydrogenii (pH), total dissolved solids (TDS), calcium (Ca2+), magnesium (Mg2+), potassium (K+), sodium (Na+), chloride (Cl), sulfate (SO42–), bicarbonate (HCO3), nitrate (NO3), nitrite (NO2) and ammonium (NH4+). TDS and pH were measured in the field using a calibrated multi-parameter water quality analyzer (HACH-HQ40D). The concentrations of major cations (Ca, Na, K, Mg) were determined in the laboratory using plasma spectroscopy (ICP-6300), and the concentration of major anions (HCO3, Cl, SO4, and NO3) were determined in the laboratory using ion chromatography (ICS-3000). The concentration of NO2 and NH4 were obtained using gas phase molecular absorption spectrometry (GMA-3376).

Human Health Risk Assessment (HHRA) model

The Human Health Risk Assessment (HHRA) model is an assessment method for assessing the risks of the various elements in groundwater to human health. It describes the degree of harm to the human body under oral and skin exposure pathways, and proposes recommendations to protect human health (Tian et al. 2019). The HHRA is based on four steps: (1) Hazard identification; (2) Dose-response assessment; (3) Exposure assessment; (4) Risk characterization (Adimalla et al. 2019a, 2019b).

Step 1: Hazard identification (Tian et al. 2020a, 2020b). The purpose of hazard identification is to determine the nature and intensity of the source of the risk. This method of assessment requires the collection of a large amount of data, including detailed data on the geography, population, economic development, geology, meteorology, and hydrogeology of the study area.

Step 2: Dose-response assessment (Ford et al. 2017):
formula
(1)
where RfD represents the chronic reference dose (mg/kg/d), NOAEL represents the No Observed Adverse Effect Level (mg/kg/d), LOAEL represents the Lowest Observed Adverse Effect Level (mg/kg/d), UFs represents the uncertainty factors.
Step 3: Exposure assessment (Zhai et al. 2017):
formula
(2)
formula
(3)
formula
(4)

The meanings and assignment of the different parameters for Health Risk Assessment are summarized in Table 1.

Table 1

Summary of parameters used to calculate chronic daily intake

Exposure route/exposure factorSymbolValueUnitsReference/source
Water ingestion rate – adult IRWa L/day Harries & Harper (2004); Rani et al. (2013)  
Water ingestion rate – child IRWc L/day Harries & Harper (2004)  
Exposure frequency EF 365 days/year Duggal et al. (2013)  
Exposure duration – adult EDa 70 Year Harries & Harper (2004)  
Exposure duration – child EDc Year Harries & Harper (2004)  
Body weight – adult BWa 70 Kg Harries & Harper (2004); Rani et al. (2013)  
Body weight – child BWc 15 Kg Harries & Harper (2004)  
Average time – adult ATa 25,550 Days AT = EF × ED 
Average time – child ATc 2,190 Days AT = EF × ED 
Absorbed dose per event DAevent Calculated value mg/cm2-event Equation (3) 
Exposure time – adult ETa 0.58 Hours/day USEPA (2004)  
Exposure time – child ETc Hours/day USEPA (2004)  
Event frequency – adult EVa Event/day USEPA (2004)  
Event frequency – child EVc Event/day USEPA (2004)  
Skin surface area – adult SAa 18,000 cm2 USEPA (2004)  
Skin surface area – child SAc 6,600 cm2 USEPA (2004)  
Conversion factor CF 0.001 L/cm3 1 L = 1,000 cm3 
Dermal permeability coefficient Kp Contaminant of potential concern (COPC)-specific cm/hour USDOE (2011)  
Gastrointestinal absorption factor GIABS COPC-specific Unitless USDOE (2011)  
Reference dose-ingestion/dermal RfDing/derm COPC-specific mg/kg/day USDOE (2011)  
Exposure route/exposure factorSymbolValueUnitsReference/source
Water ingestion rate – adult IRWa L/day Harries & Harper (2004); Rani et al. (2013)  
Water ingestion rate – child IRWc L/day Harries & Harper (2004)  
Exposure frequency EF 365 days/year Duggal et al. (2013)  
Exposure duration – adult EDa 70 Year Harries & Harper (2004)  
Exposure duration – child EDc Year Harries & Harper (2004)  
Body weight – adult BWa 70 Kg Harries & Harper (2004); Rani et al. (2013)  
Body weight – child BWc 15 Kg Harries & Harper (2004)  
Average time – adult ATa 25,550 Days AT = EF × ED 
Average time – child ATc 2,190 Days AT = EF × ED 
Absorbed dose per event DAevent Calculated value mg/cm2-event Equation (3) 
Exposure time – adult ETa 0.58 Hours/day USEPA (2004)  
Exposure time – child ETc Hours/day USEPA (2004)  
Event frequency – adult EVa Event/day USEPA (2004)  
Event frequency – child EVc Event/day USEPA (2004)  
Skin surface area – adult SAa 18,000 cm2 USEPA (2004)  
Skin surface area – child SAc 6,600 cm2 USEPA (2004)  
Conversion factor CF 0.001 L/cm3 1 L = 1,000 cm3 
Dermal permeability coefficient Kp Contaminant of potential concern (COPC)-specific cm/hour USDOE (2011)  
Gastrointestinal absorption factor GIABS COPC-specific Unitless USDOE (2011)  
Reference dose-ingestion/dermal RfDing/derm COPC-specific mg/kg/day USDOE (2011)  
Step 4: Risk characterization (Kumar et al. 2019).
formula
(5)
formula
(6)
formula
(7)
formula
(8)
where HQing indicates a non-carcinogenic hazard by ingestion of water (non-dimensional), HQderm indicates a non-carcinogenic hazard through dermal absorption of water (non-dimensional). If the HQ exceeds 1, there may be a potential non-carcinogenic effect in humans (Tian et al. 2020a, 2020b). If the HQ value is less than 1, this indicates that no non-carcinogenic risk is caused from any substance in the water.

Software

This article mainly uses SPSS software and MapGIS software for analysis and research. SPSS19.0 is used for factor analysis, principal component analysis and statistical analysis of ion concentration. MapGIS software (version 6.7) is a geographic information system software platform. MAPGIS is used to draw geographic location maps, sample distribution maps, hydrochemical-type maps, ion concentration spatial distribution maps, and groundwater EWQI evaluation maps.

RESULTS AND DISCUSSION

The groundwater chemistry is mainly affected by both natural and human factors. Natural factors include regional hydrogeological conditions, chemical composition of precipitation, evaporation and concentration, ion exchange, weathering and dissolution of rocks. Human factors include over-exploitation of groundwater, sewage recharge, pesticide use and fertilizer use.

Physicochemical characteristics

The results of statistical analysis of the physical and chemical indexes of the groundwater samples in the study area are shown in Table 2. The pH range of groundwater samples ranged from 6.14 to 7.60, with a mean value of 6.93. The pH value indicates that the groundwater environment in the study area is weakly acidic. According to WHO guidelines, the permissible value for drinking water is in the pH range of 6.5–8.5. TDS indicates total solids dissolved in the groundwater. According to WHO guidelines, the TDS value of the groundwater for drinking should be less than 500 mg/L. In the groundwater of the study area, the TDS value ranged from 98.91 to 1,920.13 mg/L, with a mean value of 561.81 mg/L. The highest concentration of TDS is mainly distributed in three towns, namely Fengshan Town, Shuanglu Town and Xiangfu Town (Figure 2(d)). According to QSGC, approximately 36.36% of TDS samples exceed Class III values (Figure 3).

Table 2

Statistics of the measured parameters for groundwater samples

ParametersUnitMinimumMaximumMeanSDCV(%)
Shallow GW pH – 6.14 7.60 6.93 0.35 5.07 
TDS mg/L 98.91 1,920.13 561.81 396.26 70.53 
Ca2+ mg/L 16.12 315.00 106.01 70.65 66.64 
Mg2+ mg/L 3.75 70.37 23.72 14.15 59.65 
K+ mg/L 0.76 41.17 3.95 6.75 171.05 
Na+ mg/L 4.90 215.97 35.23 37.26 105.75 
Cl mg/L 0.13 317.38 87.01 89.58 102.95 
SO42− mg/L 0.21 448.97 62.97 80.78 128.29 
HCO3 mg/L 34.67 809.00 249.79 126.41 50.61 
NO3-N mg/L 0.0000 112.42 14.32 24.26 169.43 
NO2-N mg/L 0.0000 2.23 0.09 0.28 324.28 
NH4-N mg/L 0.0000 4.01 0.18 0.58 314.35 
ParametersUnitMinimumMaximumMeanSDCV(%)
Shallow GW pH – 6.14 7.60 6.93 0.35 5.07 
TDS mg/L 98.91 1,920.13 561.81 396.26 70.53 
Ca2+ mg/L 16.12 315.00 106.01 70.65 66.64 
Mg2+ mg/L 3.75 70.37 23.72 14.15 59.65 
K+ mg/L 0.76 41.17 3.95 6.75 171.05 
Na+ mg/L 4.90 215.97 35.23 37.26 105.75 
Cl mg/L 0.13 317.38 87.01 89.58 102.95 
SO42− mg/L 0.21 448.97 62.97 80.78 128.29 
HCO3 mg/L 34.67 809.00 249.79 126.41 50.61 
NO3-N mg/L 0.0000 112.42 14.32 24.26 169.43 
NO2-N mg/L 0.0000 2.23 0.09 0.28 324.28 
NH4-N mg/L 0.0000 4.01 0.18 0.58 314.35 

CV = coefficient of variation, SD = standard deviation, NO3-N = nitrate concentration, calculated as nitrogen, NO2-N = nitrite concentration, calculated as nitrogen, NH4-N = ammonium concentration, calculated as nitrogen.

Figure 2

Spatial distributions of groundwater chemical indexes (NO3, NO2, NH4+, and TDS).

Figure 2

Spatial distributions of groundwater chemical indexes (NO3, NO2, NH4+, and TDS).

Figure 3

Bar charts of different anions in groundwater chemical indexes.

Figure 3

Bar charts of different anions in groundwater chemical indexes.

There are significant differences between the anion and cation of the concentrations in groundwater. The concentrations of SO42–, Cl, and HCO3 in the groundwater are in the ranges of 0.21–448.97, 0.13–317.38 and 34.67–809.00 mg/L, respectively (Table 3). In shallow groundwater, the average concentration of anions is arranged in the following order: HCO3 > Cl > SO42–. According to QSGC classification, 3.89% of SO42– in groundwater samples exceeded Grade III levels (>250.00 mg/L; Figure 3), and 6.49% of Cl in groundwater samples exceeded Grade III levels (>250.00 mg/L) mg/L; Figure 3). As shown in Table 3, the concentrations of Ca2+, K+, Na+, and Mg2+ in groundwater are in the ranges of 16.12–315.00, 0.76–41.17, 4.90–215.97, and 3.75–70.37 mg/L, respectively. The average concentrations of cations in shallow groundwater are arranged in the order of Ca2+ > Na+ > Mg2+ > K+.

Table 3

The correlation coefficients of groundwater chemical indices in the study area

ParameterpHTDSCa2+Mg2+K +Na+ClSO42HCO3NO3NO2NH4+
pH 1.00            
TDS −0.30 1.00           
Ca2+ −0.28 0.97 1.00          
Mg2+ −0.34 0.91 0.88 1.00         
K+ −0.09 0.51 0.44 0.48 1.00        
Na+ −0.06 0.78 0.69 0.65 0.47 1.00       
Cl −0.51 0.83 0.83 0.83 0.41 0.58 1.00      
SO42− −0.22 0.89 0.83 0.71 0.50 0.83 0.67 1.00     
HCO3 −.30 0.40 0.41 0.41 0.13 0.53 0.10 0.39 1.00    
NO3 −0.25 0.75 0.65 0.68 0.55 0.60 0.54 0.64 0.08 1.00   
NO2 −0.06 0.09 0.14 0.05 −0.04 0.05 0.02 0.08 0.10 0.10 1.00  
NH4+ 0.03 −0.07 −0.05 −0.05 −0.06 −0.05 −0.06 −0.02 0.02 −0.09 0.40 1.00 
ParameterpHTDSCa2+Mg2+K +Na+ClSO42HCO3NO3NO2NH4+
pH 1.00            
TDS −0.30 1.00           
Ca2+ −0.28 0.97 1.00          
Mg2+ −0.34 0.91 0.88 1.00         
K+ −0.09 0.51 0.44 0.48 1.00        
Na+ −0.06 0.78 0.69 0.65 0.47 1.00       
Cl −0.51 0.83 0.83 0.83 0.41 0.58 1.00      
SO42− −0.22 0.89 0.83 0.71 0.50 0.83 0.67 1.00     
HCO3 −.30 0.40 0.41 0.41 0.13 0.53 0.10 0.39 1.00    
NO3 −0.25 0.75 0.65 0.68 0.55 0.60 0.54 0.64 0.08 1.00   
NO2 −0.06 0.09 0.14 0.05 −0.04 0.05 0.02 0.08 0.10 0.10 1.00  
NH4+ 0.03 −0.07 −0.05 −0.05 −0.06 −0.05 −0.06 −0.02 0.02 −0.09 0.40 1.00 

Groundwater nitrate pollution

In recent years, nitrogen pollution of groundwater (NO3-N, NO2-N and NH4-N) has become one of the main factors affecting groundwater quality (Rahmati et al. 2019). NO3-N concentrations ranged from 0.00 to 112.42 mg/L with an average of 14.32 mg/L. According to WHO guidelines, the limited concentration for NO3-N in water is 10 mg/L. According to QSGC classification, 24.67% of groundwater samples exceeded Grade III levels (20.00 mg/L of N; Figure 3). The spatial distribution of NO3-N concentrations greater than 200 mg/L are mainly distributed in Fengshan Town, Aimin Town and Xiangfu Town (Figure 2(a)). NO2-N concentrations ranged from 0.00 to 2.23 mg/L with an average of 0.09 mg/L. Concentrations in 40.26% of groundwater samples exceeded Grade III levels (0.02 mg/L of N; Figure 3). According to WHO guidelines, the allowable concentration for NO2-N is 3 mg/L. The spatial distribution of NO2-N concentrations greater than 3 mg/L is mainly distributed in Yongfu Town (Figure 2(b)).

The concentration of NH4-N ranged from 0 to 4.01 mg/L, with an average of 0.18 mg/L. The concentrations in 80.52% of the groundwater samples were less than the Grade III levels (0.2 mg/L; Figure 3), reflecting a relatively stable spatial distribution (Figure 2(c)). According to WHO guidelines, the allowable concentration for NH4-N in water is 0.3 mg/L. The increase of nitrate concentration is closely related to the use of chemical fertilizers and the infiltration of surface nitrogen (Chitsazan et al. 2019).

Durov diagram and groundwater hydrochemical types

The Durov diagram drawn by MapGIS software is used to reflect and describe the groundwater chemical characteristics of the study area (Mgbenu & Egbueri 2019). The upper triangle consisting of the main anions (SO42–, Cl and HCO3) is divided into four regions: A (sulfate type), B (chloride type), C (bicarbonate type) and D mixed type); Similarly, the left triangle consisting of the main cations is also divided into four regions: E (calcium type), F (magnesium type), G (sodium type) and H (mixed type). The chemical difference between anions and cations in groundwater is shown in Figure 4. The pH of the groundwater sample is around 7.0, and the TDS of the sample is concentrated at 300–500 mg/L. For the main anions of groundwater samples, the number of water samples falling in areas A, B, C and D was 0, 16, 17, and 44, respectively. Most of the samples are plotted in the D field, indicating that the anions in groundwater are dominated by mixed types. The blue filled circles in the field of C belonged to the bicarbonate type, indicating the dominant anion of HCO3. For the main cations of groundwater samples, the number of water samples falling in areas E, F, G and H was 67, 0, 3, and 9, respectively. Most of the samples were plotted in the field of E, suggesting the dominance of Ca2+ in the groundwater. In summary, HCO3 and Cl are the main anions in groundwater, while Ca and Na are the main cations. The groundwater in the shallow aquifer in Hailun area is mainly controlled by HCO3-Ca, HCO3•Cl-Ca, HCO3-Ca•Na and HCO3•Cl-Ca•Na types.

Figure 4

Durov diagram of groundwater samples.

Figure 4

Durov diagram of groundwater samples.

Silicate weathering

In 1970, Gibbs used the Gibbs plot to quantitatively analyze the evolution of surface water. Subsequently, the Gibbs plot is widely used to study the relationship between groundwater hydrochemistry and aquifer lithology (Ramachandran et al. 2019). A Gibbs diagram is divided into three parts, each of which reveals an evolutionary mechanism: evaporation dominance, rock dominance and precipitation dominance. As shown in Figure 5, the ratio of Cl/(Cl + HCO3), (Na+ + K+)/(Na+ + K+ + Ca2+) and TDS is plotted. Most of the samples are plotted in the middle part of the diagrams, indicating that all of the samples (77 samples) are dominated by rock weathering and dissolution. The results show that rock weathering and dissolution controls the ionic composition of groundwater in this area. Groundwater chemistry is less affected by precipitation and evaporation, indicating that the groundwater level in the study area is buried deeper and groundwater is less affected by evaporation.

Figure 5

The Gibbs plot of the groundwater samples.

Figure 5

The Gibbs plot of the groundwater samples.

The relationship between Na+ and Cl in Figure 6 can show the degree of the enrichment of Na+ in groundwater samples. In general, if the ratio of Na+ vs Cl is approximately equal to 1, the dissolution of the hydrochloride is the only source of Na+ (Banks & Banks 2019). The ratios of Na+ vs Cl in the study area varied from 0.14 to 189.63, with a mean value of 8.08, which means that there is another possible source of Na+. About 82% of the samples are below the 1:1 line, indicating that they may be affected by both human activities and silicate weathering. The ratios of (Ca2+ + Mg2+) vs HCO3 in the study area varied from 0.74 to 10.87, with a mean value of 2.17, which means that Ca2+ and Mg2+ also participate in another non-carbonate chemical reaction. About 74% of the samples are below the 1:1 line, indicating that the excess Ca2+ and Mg2+ may react with Cl to materialize non-carbonate salts, such as CaCl2 and MgCl2. The chemical formula of silicate can be expressed as NaAlSi3O8. The weathering and dissolution process of silicate under weakly alkaline conditions is shown in Equation (9) (Adimalla et al. 2019a, 2019b). Excessive Ca2+ and Mg2+ can exchange Na+ from the minerals in the aquifer, causing the concentration of Na+ to increase in groundwater. The exchange adsorption of Ca2+ and Mg2+ with Na+ is also an important source of Na+ in groundwater (Karunanidhi et al. 2020).
formula
(9)
Figure 6

The plot of the ratio of Na+ vs Cl (a), Ca2+ + Mg2+ vs HCO3 (b).

Figure 6

The plot of the ratio of Na+ vs Cl (a), Ca2+ + Mg2+ vs HCO3 (b).

Ion exchange

Ion exchange has a significant impact on the chemical properties of groundwater. The ratio of Ca2+ + Mg2+-SO42–-HCO3 (meq/L) and Na+-Cl (meq/L) is close to –1, indicating that the dissolution of calcite, dolomite, and gypsum is the main form of water–rock interaction (Li et al. 2019). Figure 7 can better describe the process of ion exchange in the groundwater. The ratios of Ca2+ + Mg2–-SO42-HCO3 (meq/L) and Na+-Cl (meq/L) in the groundwater range from –6.59 to 10.54, with an average value of –0.49, which means that the ions in groundwater exchange strongly with the ions on the surface of the aquifer rocks (Chitsazan et al. 2019) (Equations (10) and (11)):
formula
(10)
formula
(11)
Figure 7

The plot of the ratio of Ca2+ + Mg2+-SO42-HCO3 vs Na+-Cl.

Figure 7

The plot of the ratio of Ca2+ + Mg2+-SO42-HCO3 vs Na+-Cl.

Carbonate and sulfate dissolution

The chemical formula of calcite can be expressed as CaCO3. As shown in the scatter diagrams of Ca2++ Mg2+ vs HCO3 + SO42–, about 79.22% of the sampling points fall below 10 (Ca2++ Mg2+ < 10) meq/L, indicating that the dissolution of calcite is dominant (Figure 8, Equation (12)) (Yuan et al. 2020). The chemical formula of gypsum can be expressed as CaSO4. Groundwater rich in calcium and sulfate is partially derived from the dissolution of gypsum (CaSO4·2H2O) (Equation (13)). The plot of Ca2+/SO42– vs Cl (meq/L) also confirms this conclusion, and most of the groundwater samples fall above the unit line, indicating that the effect of gypsum dissolution on groundwater chemistry is very small (Figure 9). These reactions usually occur in the recharge area of many sedimentary aquifer environments (Lyu et al. 2019):
formula
(12)
formula
(13)
Figure 8

The plot of the ratio of SO42– + HCO3 vs Ca2+ + Mg2+.

Figure 8

The plot of the ratio of SO42– + HCO3 vs Ca2+ + Mg2+.

Figure 9

The plot of the ratio of Ca2+/SO42– vs Cl.

Figure 9

The plot of the ratio of Ca2+/SO42– vs Cl.

Factor and principal component analyses

Factor analysis and correlation analysis can help determine the source and correlation of ions in groundwater. As indicated in Table 4, TDS has a significant positive correlation with Na+, Ca2+, Mg2+, NO3, SO42–, and Cl, suggesting that the spatial distribution of TDS is mainly affected by Na+, Ca2+, Mg2+, NO3, SO42–, and Cl (Selvakumar et al. 2017a, 2017b). Besides, the high correlation between TDS and NO3 indicates that human activities, especially the use of chemical fertilizers, is one of the important reasons for the change of TDS in groundwater. The presence of NO3, Mg2+ and SO42– in this factor group simultaneously confirms the contribution of agricultural activities to its hydrochemical process (Selvakumar et al. 2017a, 2017b). The high correlation between Ca2+, Mg2+ and Cl indicates that ion exchange is one of the causes for their high concentration. The high correlation between Ca2+ and SO42– indicates that the dissolution of gypsum affects the concentration of Ca2+ and SO42– in groundwater (Guo et al. 2019). Therefore, it is presumed that the main ions of groundwater in the study area are affected by the dissolution of aluminosilicate minerals, the dissolution of gypsum, ion exchange, and human activities.

Table 4

Health risk assessment of nitrogen (NO3-N) based on USEPA

SampleHQ(NO3-N)
SampleHQ(NO3-N)
MalesFemalesChildrenInfantMalesFemalesChildrenInfant
GW01 0.03 0.03 0.07 0.11 GW40 0.54 0.63 1.28 2.17 
GW02 0.08 0.09 0.19 0.33 GW41 0.22 0.25 0.51 0.86 
GW03 0.01 0.01 0.02 0.03 GW42 0.42 0.49 1.00 1.69 
GW04 0.16 0.19 0.38 0.65 GW43 0.13 0.15 0.30 0.50 
GW05 0.10 0.12 0.24 0.40 GW44 0.32 0.37 0.76 1.30 
GW06 0.04 0.04 0.09 0.15 GW45 0.16 0.18 0.37 0.62 
GW07 0.01 0.01 0.03 0.05 GW46 1.45 1.67 3.41 5.79 
GW08 0.37 0.43 0.88 1.49 GW47 0.13 0.15 0.30 0.52 
GW09 0.03 0.04 0.07 0.13 GW48 0.01 0.01 0.02 0.04 
GW10 0.00 0.00 0.00 0.00 GW49 0.01 0.01 0.03 0.04 
GW11 0.01 0.01 0.02 0.03 GW50 0.00 0.00 0.00 0.01 
GW12 0.03 0.03 0.07 0.11 GW51 0.10 0.11 0.22 0.38 
GW13 0.01 0.01 0.03 0.05 GW52 0.00 0.00 0.01 0.01 
GW14 0.28 0.32 0.66 1.12 GW53 0.00 0.01 0.01 0.02 
GW15 0.01 0.01 0.01 0.02 GW54 0.27 0.31 0.63 1.08 
GW16 0.00 0.00 0.00 0.00 GW55 0.01 0.01 0.02 0.03 
GW17 0.01 0.01 0.02 0.04 GW56 0.97 1.11 2.27 3.86 
GW18 0.00 0.00 0.00 0.00 GW57 0.00 0.00 0.01 0.01 
GW19 0.02 0.02 0.05 0.08 GW58 0.00 0.00 0.00 0.00 
GW20 0.02 0.02 0.05 0.08 GW59 0.16 0.18 0.37 0.63 
GW21 0.01 0.01 0.01 0.02 GW60 0.00 0.00 0.00 0.00 
GW22 0.00 0.00 0.00 0.00 GW61 0.00 0.00 0.01 0.01 
GW23 0.18 0.21 0.43 0.72 GW62 1.07 1.23 2.52 4.28 
GW24 0.00 0.00 0.00 0.00 GW63 0.31 0.35 0.72 1.22 
GW25 0.00 0.00 0.00 0.00 GW64 0.01 0.01 0.03 0.04 
GW26 0.00 0.00 0.00 0.00 GW65 1.52 1.75 3.58 6.08 
GW27 0.02 0.02 0.04 0.07 GW66 0.55 0.63 1.30 2.20 
GW28 0.30 0.34 0.70 1.19 GW67 0.79 0.91 1.87 3.17 
GW29 0.06 0.06 0.13 0.22 GW68 0.79 0.91 1.87 3.17 
GW30 0.03 0.03 0.07 0.12 GW69 0.00 0.00 0.00 0.00 
GW31 0.05 0.06 0.12 0.20 GW70 0.67 0.77 1.57 2.66 
GW32 0.01 0.01 0.02 0.03 GW71 0.91 1.04 2.13 3.62 
GW33 0.36 0.41 0.85 1.44 GW72 0.01 0.01 0.01 0.02 
GW34 0.13 0.15 0.30 0.51 GW73 0.00 0.00 0.00 0.00 
GW35 0.02 0.02 0.04 0.07 GW74 0.29 0.34 0.69 1.17 
GW36 0.00 0.00 0.01 0.02 GW75 0.04 0.04 0.09 0.16 
GW37 0.01 0.01 0.02 0.04 GW76 0.00 0.00 0.00 0.00 
GW38 0.43 0.49 1.01 1.71 GW77 0.00 0.00 0.00 0.00 
GW39 0.25 0.29 0.60 1.01      
SampleHQ(NO3-N)
SampleHQ(NO3-N)
MalesFemalesChildrenInfantMalesFemalesChildrenInfant
GW01 0.03 0.03 0.07 0.11 GW40 0.54 0.63 1.28 2.17 
GW02 0.08 0.09 0.19 0.33 GW41 0.22 0.25 0.51 0.86 
GW03 0.01 0.01 0.02 0.03 GW42 0.42 0.49 1.00 1.69 
GW04 0.16 0.19 0.38 0.65 GW43 0.13 0.15 0.30 0.50 
GW05 0.10 0.12 0.24 0.40 GW44 0.32 0.37 0.76 1.30 
GW06 0.04 0.04 0.09 0.15 GW45 0.16 0.18 0.37 0.62 
GW07 0.01 0.01 0.03 0.05 GW46 1.45 1.67 3.41 5.79 
GW08 0.37 0.43 0.88 1.49 GW47 0.13 0.15 0.30 0.52 
GW09 0.03 0.04 0.07 0.13 GW48 0.01 0.01 0.02 0.04 
GW10 0.00 0.00 0.00 0.00 GW49 0.01 0.01 0.03 0.04 
GW11 0.01 0.01 0.02 0.03 GW50 0.00 0.00 0.00 0.01 
GW12 0.03 0.03 0.07 0.11 GW51 0.10 0.11 0.22 0.38 
GW13 0.01 0.01 0.03 0.05 GW52 0.00 0.00 0.01 0.01 
GW14 0.28 0.32 0.66 1.12 GW53 0.00 0.01 0.01 0.02 
GW15 0.01 0.01 0.01 0.02 GW54 0.27 0.31 0.63 1.08 
GW16 0.00 0.00 0.00 0.00 GW55 0.01 0.01 0.02 0.03 
GW17 0.01 0.01 0.02 0.04 GW56 0.97 1.11 2.27 3.86 
GW18 0.00 0.00 0.00 0.00 GW57 0.00 0.00 0.01 0.01 
GW19 0.02 0.02 0.05 0.08 GW58 0.00 0.00 0.00 0.00 
GW20 0.02 0.02 0.05 0.08 GW59 0.16 0.18 0.37 0.63 
GW21 0.01 0.01 0.01 0.02 GW60 0.00 0.00 0.00 0.00 
GW22 0.00 0.00 0.00 0.00 GW61 0.00 0.00 0.01 0.01 
GW23 0.18 0.21 0.43 0.72 GW62 1.07 1.23 2.52 4.28 
GW24 0.00 0.00 0.00 0.00 GW63 0.31 0.35 0.72 1.22 
GW25 0.00 0.00 0.00 0.00 GW64 0.01 0.01 0.03 0.04 
GW26 0.00 0.00 0.00 0.00 GW65 1.52 1.75 3.58 6.08 
GW27 0.02 0.02 0.04 0.07 GW66 0.55 0.63 1.30 2.20 
GW28 0.30 0.34 0.70 1.19 GW67 0.79 0.91 1.87 3.17 
GW29 0.06 0.06 0.13 0.22 GW68 0.79 0.91 1.87 3.17 
GW30 0.03 0.03 0.07 0.12 GW69 0.00 0.00 0.00 0.00 
GW31 0.05 0.06 0.12 0.20 GW70 0.67 0.77 1.57 2.66 
GW32 0.01 0.01 0.02 0.03 GW71 0.91 1.04 2.13 3.62 
GW33 0.36 0.41 0.85 1.44 GW72 0.01 0.01 0.01 0.02 
GW34 0.13 0.15 0.30 0.51 GW73 0.00 0.00 0.00 0.00 
GW35 0.02 0.02 0.04 0.07 GW74 0.29 0.34 0.69 1.17 
GW36 0.00 0.00 0.01 0.02 GW75 0.04 0.04 0.09 0.16 
GW37 0.01 0.01 0.02 0.04 GW76 0.00 0.00 0.00 0.00 
GW38 0.43 0.49 1.01 1.71 GW77 0.00 0.00 0.00 0.00 
GW39 0.25 0.29 0.60 1.01      

HEALTH RISK ASSESSMENT

According to the USEPA groundwater quality standards and the corresponding HQ calculation results, the quality classification of NO3-N is shown in Table 4. The HQ value for adult males, adult females, children, and infants were in the range of 0–1.52, 0–1.75, 0–3.58, and 0–6.08, respectively, and with a mean value of 0.19, 0.22, 0.44, and 0.75, respectively. It can be concluded that for health risks from NO3 pollution in groundwater, the harm is in the order of infant > child > adult female > adult male. This shows that minors in the study area are significantly more at risk of NO3 pollution than adults. The increased harm to minors can be attributed to higher gastrointestinal absorption rates associated with groundwater-related activities, and increased sensitivity per unit weight to environmental pollutants.

According to the calculation results of HQ, a spatial distribution map is drawn of the health risk assessment in the study area for infants, children, adult females, and adult males (Figure 10). For adult males and females, the health risks from nitrate (HQ > 1) are mainly concentrated in the south (Hainan Town) and north (Aimin Town) of the study area, which accounts for about 5.60% of the total area, while for children and infants, the health risks from nitrate (HQ > 1) are mainly distributed in the south (Hainan Town, Gongrong Town, Xiangfu Town, and Fengshan Town) and north (Aimin Town and Shuanglu Town) of the study area, which accounts for about 27.41% of the total area.

Figure 10

The spatial distribution map of the risk based on the HHRA model.

Figure 10

The spatial distribution map of the risk based on the HHRA model.

It is worth noting that areas with high health risks of NO3 are distributed in agricultural production areas, especially rice cultivation areas (the middle and lower reaches of the Zhayin River, the upper reaches of the Helen River, and the middle reaches of the Sandaowulong River). The large-scale use of nitrogen fertilizer and irrigation of domestic sewage are the main reasons for the increased health risk of NO3. Therefore, the local government should strengthen the management of groundwater resources and prevent and control the nitrate pollution of groundwater to ensure the safety of drinking water for the local residents.

CONCLUSIONS

This study explored the factors affecting groundwater chemistry, and analyzed the hydrogeological processes of shallow groundwater. Human health risk assessment of nitrate contamination was also performed in accordance with USEPA2004 guidelines. The following three conclusions were established:

  • 1.

    The abundance for groundwater is in the order Ca2+ > Na+ > Mg2+ for cations, and HCO3 > Cl > SO42– for anions, resulting in that the water types were dominated by HCO3-Ca, HCO3•Cl-Ca, HCO3-Ca•Na and HCO3•Cl-Ca•Na types. Groundwater in the study area is weakly acidic.

  • 2.

    Groundwater hydrochemistry shows that rock weathering and dissolution, ion exchange, and human activities are the main reasons affecting the chemical composition of shallow groundwater in Hailun. The weathering and dissolution process of silicate under weakly alkaline conditions is the source of Na+. The dissolution of calcite, dolomite, and gypsum is the main form of water–rock interaction.

  • 3.

    The HQ values for adult males, adult females, children, and infants were in range of 0–1.52, 0–1.75, 0–3.58, and 0–6.08, respectively, and with a mean value of 0.19, 0.22, 0.44, and 0.75, respectively. The harm of NO3 pollution is in the order of infant > child > adult female > adult male. The health risks from NO3 (HQ > 1) are mainly distributed in the Hainan Town and Aimin Town of the study area for adult males and females, while that for children and infants was distributed in the towns of Hainan, Gongrong, Xiangfu, Fengshan, Aimin and Shuanglu.

For human health and the sustainable development of groundwater resources, the following three suggestions are proposed: (1) residents living in the towns of Hainan, Gongrong, Xiangfu, Fengshan, Aimin and Shuanglu are advised to prohibit drinking and mining groundwater; (2) recommend the use of surface water for irrigation, restricting the exploitation of groundwater; (3) reduce the use of chemical fertilizers and fertilize according to the needs of the soil. The results of this study made local governments pay attention to drinking water safety issues for local residents.

ACKNOWLEDGEMENTS

This work was supported by the projects of hydrological and geological survey in Hailun, Bayan and Wuhe Area (Item Number: DD20190340-1). Thanks are extended to Yonggen Zhang, Shanghai Du, and Xiaoqing Sun for helping with mapping and writing skills in the process of writing this paper. We are also grateful to valuable comments and suggestions given by the editors and the anonymous reviewers.

DATA AVAILABILITY STATEMENT

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

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