Introduction

Arsenic (As) is a common contaminant in groundwater. It is the 20th most abundant element in the crust of the Earth (Villalba et al. 2020). Arsenic contamination in groundwater is a global threat, with more than 20 countries including China (Guo et al. 2008; Zhang et al. 2017), Thailand (Tiankao and Chotpantarat 2018), India (Khan et al. 2022; Sridharan and Nathan 2018), Bangladesh (Huq et al. 2020; Islam et al. 2022), the United States (Gong et al. 2014), Mexico (Rodriguez-Cantu et al. 2022), Argentina (Alcaine et al. 2020), and Pakistan (Shahid et al. 2018a, b) reporting arsenic poisoning in drinking water (He and Charlet 2013). Particularly, the situation of arsenic poisoning in drinking water in China is serious. As early as in the 1980s, Xinjiang, the biggest provincial administrative government in China, reported its first case of arsenic poisoning from drinking water (Wang et al. 1983). Later, large-scale arsenic poisoning in drinking water were reported in Shanxi and Inner Mongolia (Guo et al. 2014; Sun 2004). At present, these provinces are still among the most serious arsenicosis-stricken provinces in China (He et al. 2020). Long-term intake of arsenic-contaminated groundwater can cause skin pigmentation, hyperkeratosis, ulcers, and can threaten the health of internal organs such as the liver, kidneys, and lungs (Shaji et al. 2021), and severe arsenic poisoning can even lead to skin and lung cancers (Rasheed et al. 2017). It is reported that in the West Bengal, India, endemic arsenic poisoning has not only endangered the lives and health of millions of people, but also adversely affected their offspring through genetic means (Bhowmick et al. 2018). The International Agency for Research on Cancer (IARC) classified arsenic as a Class 1 human carcinogen (IARC 2011). Earlier, the permissible value of arsenic in drinking water was set as 50 µg/L, but due to the serious health threat of arsenic the World Health Organization (WHO) changed the maximum permissible value of arsenic in drinking water to 10 µg/L (WHO 1993).

The main sources of arsenic in groundwater are geological formations (e.g., sediments/rocks, soil, and volcanic rocks) (Kim et al. 2012; Kumar et al. 2016; Santha et al. 2022), geothermal activities (Bundschuh and Maity 2015), coal mining (Cao et al. 2021), and anthropogenic factors (Li et al. 2020; Nottebaum et al. 2020). The presence of arsenic in groundwater is associated with host minerals, as well as the redox state and pH in the aquatic environments (Chakraborty et al. 2015), making arsenic a redox sensitive element (Carraro et al. 2015; Chakraborty et al. 2022; Meng et al. 2003). Arsenic in natural water exists as inorganic form, while organic form of arsenic tends to be low in natural groundwater (Park et al. 2023; Schreiber 2021). The most common chemical species of arsenic in natural water are As(III) and As(V), and As(III) is often considered more toxic than As(V) due to its ability to bind to sulfhydryl groups, thereby affecting the function of proteins (NRC 1999). Therefore, gaining specific knowledge of the chemical species and distribution of arsenic in groundwater can be helpful for the reduction in the human health risk. In this regard, many scientific papers have been published to reveal the occurrence, migration, and affecting factors of different species of arsenic in groundwater. Among the existing research, Cao et al. (2022) revealed the spatiotemporal variability of groundwater arsenic under the long-term groundwater abstraction conditions, and this research demonstrated that groundwater abstraction could severely alter the biogeochemical environments in which the enrichment of groundwater arsenic might be significantly different. Ke et al. (2022) focused on the arsenotrophic microbiome in groundwater, and their research suggested that the diversities of bacteria are higher in high arsenic groundwater than in low arsenic groundwater, and the concentrations of SO42− and arsenic and the levels of oxidation–reduction potential (ORP) and pH are important factors affecting the groundwater microbial populations. In addition, Li et al. (2022) showed that the intensive irrigation in agricultural areas would benefit the release of arsenic into groundwater. These recent studies have tremendously help researchers to better understand the mechanisms of groundwater arsenic enrichment and migration.

The rural areas at the northern foot of the Qinling Mountains are critical for maintaining the sustainability of society development in and around the Xi’an City, the capital city of Shaanxi Province in China, because the Golden Basin Reservoir in these areas provides fresh water supply for the southern part of the Xi’an City. Groundwater, however, is of particular importance to the people living in rural areas (Xu et al. 2023). Numerous scholars have conducted many studies on nitrogen, fluoride, and arsenic contamination of groundwater in different parts of the Guanzhong Plain (Li et al. 2014a; Li et al. 2023; Luo et al. 2014; Nsabimana et al. 2023; Wu and Sun 2016; Ren et al. 2021; Zhang et al. 2018, 2022a, 2022b; Wang and Li 2022). Wang et al. (2023) have recently investigated the impacts of climate change on groundwater level in this area, benefiting the understanding into the mechanisms of groundwater system responses to external forces. However, this research did not consider the response of arsenic concentration to external forces. An early investigation in rural drinking water quality in the Huyi District, Xi’an, showed that arsenic exceeded the WHO and national standards of arsenic, indicating serious health risk to local residents (Chang et al. 2019). In addition, Qiao et al. (2020) quantified the health risk of groundwater in the Guanzhong Plain, and found that arsenic posed carcinogenic health risk and non-carcinogenic risk to humans. However, as the fourth biggest plain in northwest China, groundwater in the Guanzhong Plain is still not well studied for arsenic contamination, and the distribution and different chemical species of arsenic in groundwater as well as their effects on human health are not clear. Therefore, this study was conducted to (1) characterize the groundwater hydrochemistry and spatial distribution of arsenic in the area, (2) analyze the controlling factors that may affect arsenic enrichment in groundwater, (3) calculate the different chemical species of arsenic and analyze the main factors controlling the variation of arsenic speciation, and (4) estimate the probabilistic health risks caused by arsenic. The outcomes of this research may benefit local and regional protection and management of groundwater for drinking purpose, and this research can also act as a reference for other areas facing similar arsenic poisoning problems in the world.

Materials and Methods

Study Area

The study area is located in central part of the Guanzhong Plain, Shaanxi Province, China bordered by the Qinling Mountains in the south, and Wei River in north. It covers four main county-level administration regions, i.e., Yangling District of Xianyang City, Mei County, Zhouzhi County, and Huyi District of Xi'an City (Fig. 1). With elevations ranging from 370 to 1200 m, the study area has a generally high elevation in the south and a low elevation in the north. The landform types include the Qinling Mountains, Loess Plateau, and Wei River Plain. This study area has a warm-temperate continental monsoon climate with a cold and dry winter, but a very hot and rainy summer (Yang et al. 2022). Due to the influence of landscape, the climate of the mountainous areas and plains varies significantly from north to south. The average annual temperature is 13.2 °C, with January being the coldest month and July the hottest (Wang and Li 2022; Zhou et al. 2022). Precipitation shows a decreasing trend from south to north, showing large regional differences, intra-annual variations and inter-annual variations. The average annual precipitation is 700–900 mm in the mountainous areas, but is 500–700 mm in the plains (Wang et al. 2023).

Fig. 1
figure 1

Location of study area and sampling sites

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The study area is mostly a low-lying fault basin, and there is a wide distribution of Quaternary loose sediments with a thickness of several hundred meters in the area. The Quaternary loose sediments are permeable and can be easily recharged by precipitation and rivers, thus containing rich groundwater resources (Nsabimana et al. 2022). Influenced by surface topography, groundwater in the area is mainly discharged horizontally, from south to north towards the Wei River (Wang et al. 2023). The water-bearing formation is mainly the Quaternary loose sedimentary layers which are widely distributed and continuous throughout the region. The water-rich areas are mainly distributed along the Wei River and its tributaries as well as in the pluvial fans in front of the Qinling Mountains (Nsabimana and Li 2022). On the contrary, the Loess Plateau has weaker groundwater abundance due to its poor geological and hydrogeological conditions. Controlled by topography, groundwater flows generally from the Qinling Mountains to the Wei River in the south of the study area, and from the Loess Plateau to the Wei River in the north of the study area (Zhang et al. 2022a). Groundwater in this area is recharged widely by precipitation, but river percolation, irrigation infiltration, and lateral inflow are also important ways of groundwater getting recharged (Zhang et al. 2022b). On the contrary, groundwater in this area is primarily discharged by evaporation, artificial abstraction, and lateral outflow.

Sample Collection and Analyses

For this research, groundwater samples were collected in July 2021 from 73 shallow domestic water wells in the rural areas of the study area, and the sampling locations are shown in Fig. 1. The sampling sites were selected in major villages to reflect the rural groundwater quality, thus these sampling sites were distributed uniformly in the study area. The procedures of sampling, storage, and handling strictly followed the national standards (Ministry of Environmental Protection of the P.R. China 2020). Before the samples were collected, the wells were pumped for 5–10 min, after which the sampling containers were rinsed three times with the water to be taken. Parameters that can be easily changed such as pH, conductivity, and ORP were measured directly in the field using portable pH test device, portable conductivity test device, and portable ORP test device. All the portable devices were calibrated before sampling using calibration liquids. Other indicators were sent to the laboratory of the Mineral Resources Investigation Center of the China Geological Survey in Xi’an for further analysis. All tests followed the national technical regulations (Ministry of Land and Resources of the P. R. China 2006). Among the parameters analyzed, K+, Na+, Ca2+, Mg2+, F−, NO2−, and NO3− were measured by ion chromatography. HCO3−, Cl−, CO32−, and SO42− were measured by titration. TDS was measured by drying and weighing method. Fe and Mn were determined by plasma emission spectrometry. Arsenic was determined using atomic fluorescence spectrometry. Cr6+ was determined using UV–Vis spectrophotometry. All the instruments for the physicochemical analyses were pre-calibrated to ensure the reliability of the analyses. In addition, the analyses were carried out through blank samples and triplicates. To ensure the accuracy of the data, the percentage error of ion balance (%CBE) was also calculated for all water samples after the physicochemical analyses (Eq. 1), and the results indicated that over 95% of the samples had an analytical error less than ± 5%, and the highest analytical error is 6.2%, which proved the reliability of the analyzed data.

$${\text{\% CBE}} = \frac{{\sum {{\text{Cations}}} - \sum {{\text{Anions}}} }}{{\sum {{\text{Cations}}} { + }\sum {{\text{Anions}}} }} \times 100\%$$
(1)

Human Health Risk Quantification

The USEPA model (USEPA 1989) was used to calculate the carcinogenic and non-carcinogenic health risks of arsenic for adults and children. Considering that drinking water intake was the most important exposure pathway, oral ingestion was considered in this research. In addition, groundwater was also used for washing hands and faces and shower, dermal contact was considered as the secondary exposure pathway, while other exposure pathways such as intake via food consumption and inhalation were ignorable (Wu et al. 2020). The health risk was calculated by the following equations (Li et al. 2019a, b):

The equation for calculating the exposure dose for oral ingestion is as follows:

$${\text{CDI}} = \frac{{{\text{CW}} \times {\text{IR}} \times {\text{EF}} \times {\text{ED}}}}{{{\text{BW}} \times {\text{AT}}}}$$
(2)

where CDI is the chronic daily intake dose (mg/kg d); CW is the concentration of the contaminant in groundwater (mg/L); IR is the daily drinking water rate (L/d); EF is exposure frequency (d/a); ED is the exposure duration and this variable indicates the number of years during which the objects are exposed to the contaminants (a); BW is the body weight (kg); and AT is the average time of exposure (d). For non-carcinogenic risk assessment, AT = EF × ED, while for carcinogenic risk quantification, AT = EF × T (T is the average life span in the study area).

The equation for calculating the exposure dose for skin contact is as follows:

$${\text{DAD}} = \frac{{{\text{DA}}_{{{\text{event}}}} \times {\text{EV}} \times {\text{ED}} \times {\text{EF}} \times {\text{SA}}}}{{{\text{BW}} \times {\text{AT}}}}$$
(3)

where DAD is the dose of contaminant exposure by dermal contact (mg/kg d); DAevent is the absorbed dose by dermal contact (mg/cm2); EV is the frequency of daily dermal contact events such as swimming, bathing, and washing (times/d); SA is the surface area of exposed skin (cm2); ED, EF, BW, AT, and other parameters have the same meaning as those in Eq. (1). DAevent can be calculated using the following equation:

$${\text{DA}}_{{{\text{event}}}} = K_{p} \times {\text{CW}} \times t_{{{\text{event}}}} \times 10^{ - 3}$$
(4)

where Kp is the skin permeability coefficient for harmful substances (cm/h); tevent is the length of a single skin contact (h). The values for all variables are shown in Table 1, and the values were adjusted to fit the actual situation in China (Zhang et al. 2019a, b).

Table 1 Exposure parameters for adults and children
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To calculate the carcinogenic risk, the following equation is usually used:

$$R = E \times {\text{SF}}$$
(5)

where R is the carcinogenic risk index (dimensionless); E is the exposure dose (mg/kg d) to groundwater by oral intake or dermal contact, i.e., CDI or DAD; SF is the slope factor of the contaminants ((mg/kg d)−1).

The total carcinogenic risk index (CRi) can be calculated by summing the carcinogenic risk index of oral intake (Ro) and the carcinogenic risk index of dermal exposure (Rd) as follows:

$${\text{CR}}_{i} = R_{o} + R_{d}$$
(6)

The non-carcinogenic risk index is usually calculated using the following assessment model:

$${\text{NCHQ}} = E/{\text{RfD}}$$
(7)

where NCHQ is the non-carcinogenic risk index (dimensionless); E is the groundwater exposure dose (mg/kg d) by oral intake or dermal contact route, i.e., CDI or DAD; RfD is the reference dose (mg/kg d).

The total non-carcinogenic risk index (HQi) can be expressed by summing the carcinogenic risk index of oral intake (NCHQo) and the carcinogenic risk index of dermal exposure (NCHQd) is as follows:

$${\text{HQ}}_{i} = {\text{NCHQ}}_{o} + {\text{NCHQ}}_{d}$$
(8)

Monte Carlo Simulation

In the traditional health risk assessment process, a specific value is used for the exposure parameter, while in reality these parameter values have some uncertainty (Ganyaglo et al. 2019). Monte Carlo simulation method is widely used to quantify the uncertainty associated with health risk models (Liu et al. 2022). It uses random sampling and statistical tests to obtain approximate solutions to the problem. This is done by simulating the generated random numbers based on the probabilistic process of constructing events from the probability distributions of the measured data. In this research, the Crystal Ball software was used to calculate the risk level for adults and children by performing 10,000 stochastic iterations. The procedures of Monte Carlo simulation include Define Assumptions, Define Predictions, Determine Run Preferences, and Run Simulation.

The probability distributions of total arsenic were fitted using Crystal Ball risk simulation software embedded in Microsoft Excel. In this software, different probability distributions for total arsenic can be automatically calculated, and then ranked by Anderson–Darling test. The P–P and Q–Q plots were inspected to determine if there is any systematic variation in the magnitude of residuals (Mondal and Polya 2008). The uncertainties of the model parameters of intake rate (IR), body weight (BW), and exposure frequency (EF) were considered according to the recommended value of the Ministry of Environmental Protection of the People’s Republic of China (2014) and relevant studies conducted in China (Zhang et al. 2019a, b; Liu et al. 2022), and it was determined that IR showed a normal distribution, BW showed a log-normal distribution, and EF showed a triangular distribution. The distribution types of the pollutant and exposure parameters are shown in Table 2.

Table 2 Range of exposure parameters and contaminants concentration distribution
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Results and Discussion

Basic Hydrochemical Characteristics

The water quality parameters of groundwater in the study area were statistically analyzed, and the maximum and minimum values, mean, median, standard deviation of all parameters considered in this study are shown in Table 3. These parameters were also compared with the national groundwater quality standards (General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China 2017), and the proportions of groundwater samples falling within each groundwater quality classification are also listed in Table 3. Table 3 shows that the pH value in the study area varied from 6.83 to 7.94, with a mean value of 7.44, indicating that the groundwater in the area is weakly alkaline. The Chinese groundwater quality standards classify groundwater quality into five classes, and the upper limit of class III represents the guideline values for domestic purpose. In this study, 87.7% of groundwater samples in this study area show TDS less than 1 g/L, indicating freshwater, and 10.9% of the samples are brackish water with TDS ranging within 1–2 g/L. High TDS groundwater is represented with high SO42− and Na+ contents, indicating strong evaporative enrichments and water–rock interactions in the area. The Fe and Mn contents in some groundwater samples exceeded the standard limit for class III, indicating that the groundwater in some local areas might be in a reduction environment, which can also be evidenced by very low ORP values in some areas. Guanzhong Plain has developed agriculture. The application of nitrogen fertilizer has been increasing year after year to increase agricultural production, which has increased surface nitrogen pollution and exacerbated nitrate pollution in groundwater (Zhang et al. 2019a, b). Soluble nitrates leached from the use of fertilizers during agricultural activities will migrate in the aquifer with groundwater flow, expanding nitrate pollutions in groundwater (Li et al. 2014b). In this study, high nitrate concentrations were detected in 32.8% of groundwater samples, indicating that groundwater quality is strongly influenced by agricultural activities.

Table 3 Statistics of water quality parameters
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The dominant ions determine the type of groundwater. According to the average values, the dominance of cations in groundwater is Ca2+  > Mg2+  > Na+  > K+, while the dominance of anions is HCO3− > SO42− > Cl−. The content of Ca2+ in groundwater ranges from 30.4 to 220 mg/L. Similarly, HCO3− is the main anion in groundwater with an average content of 289.16 mg/L. Thus, the Piper diagram (Fig. 2) suggests that the HCO3-Ca·Mg type is the dominant hydrogeochemical type, indicating that shallow groundwater in the area is dominated by fresh water which are typical hydrochemical characteristic of groundwater in recharge zones (Wang et al. 2022a). In addition, the SO4·Cl-Ca·Mg type occurs in some areas of the region, suggesting the secondary effects of evaporation and human activities.

Fig. 2
figure 2

Piper diagram of groundwater samples

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Concentration and Enrichment of Arsenic in Groundwater

The basic statistical analysis of arsenic concentrations in shallow groundwater in the study area showed that the concentrations of arsenic in groundwater ranged from 1.46 to 8.69 μg/L with a mean value of 2.66 μg/L, a median value of 2.29 μg/L, and a standard deviation of 1.24. According to the Chinese groundwater quality standards (General Administration of Quality Supervision, Inspection and Quarantine of the P. R. China and Standardization Administration of the P. R. China 2017), the concentration of arsenic in groundwater is within the groundwater quality standard limit for grade III. The World Health Organization also recommended guideline value of arsenic concentration in drinking water is 10 μg/L. In this research, the arsenic concentration in the groundwater samples is below this limit. However, arsenic is easy to accumulate and difficult to decompose in soil and plants, and can enter human body through food chain, which is harmful to human health (Ivy et al. 2022). Previous studies have shown that the arsenic content in drinking water in the Qinling area in southern Xi’an and eastern Xi’an is low, while the arsenic content in drinking water in the western Xi’an such as in the Huyi District (as high as 47 μg/L) is distinctly higher than in other areas, indicating a potential cancer risk to human health (Gao et al. 2022).

To obtain the spatial distribution characteristics of arsenic in groundwater in the study area, ordinary kriging interpolation technique was used for spatial interpolation, and the Golden Software Surfer 13 was used for the preparation of spatial distribution map. From Fig. 3, it can be seen that the content of arsenic in groundwater in Zhouzhi and Mei counties is low, while the content of arsenic in groundwater in the area around the Huyi District is significantly higher than that in the other areas. Researchers have shown that minerals associated with hydrothermal deposits, such as arsenopyrite (FeAsS) and fluorspar (CaF2), are important sources of arsenic (Shahid et al. 2018a, b). Water–rock interactions between geothermal water and the hydrothermal deposits can produce dissolution of these minerals (Alarcon-Herrera et al. 2013), and it leads to high concentrations of arsenic in groundwater. There is a wide distribution of geothermal water in Xi’an, the region's active faults and widely distributed fractures provide convenient channels for the migration of arsenic in geothermal water to shallow groundwater. Therefore, the high concentration of arsenic found in shallow groundwater in the area can be partially explained by the upward movement of geothermal water and confined groundwater (Gao et al. 2020b).

Fig. 3
figure 3

Spatial distribution of As in groundwater

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The Pearson correlation matrix was used to further understand the correlation between arsenic and other physicochemical parameters, and the results are presented in Fig. 4. From Fig. 4, it can be seen that arsenic in groundwater was negatively correlated with ORP (r =  − 0.455) and was positively correlated with pH (r = 0.417), which indicated that alkaline reduction environment favors arsenic enrichment in the study area. Arsenic in groundwater can be very easily adsorbed by some positively charged minerals in the aqueous media, such as iron, aluminum oxides, hydrous aluminum, and hydrous iron ore. With the increase in pH, the positive charge of these colloidal and clay minerals gradually decreases, reducing the adsorption of arsenate and arsenite and making the concentration of arsenic in the surrounding water environment gradually increase. Changes in oxidation–reduction potential (ORP) affect the adsorption-resolution processes of arsenic in sediments, which in turn affect the concentration of arsenic in the water matrix. An aqueous environment with high pH and low ORP promotes the desorption of arsenic from sediments into groundwater and enhances its continuous accumulation in it (Gillispie et al. 2019). Many studies around the world have shown that arsenic in groundwater has a very intimate relationship with Fe and Mn (Haque and Johannesson 2006; Willis et al. 2011). In a reducing environment, the reductive dissolution of Fe/Mn oxide minerals is thought to be the main cause of arsenic enrichment in groundwater (Islam et al. 2004). In aqueous media, Fe/Mn oxide minerals are the main carriers of arsenic in groundwater system, as confirmed by the correlation of arsenic with Fe (r = 0.242) and Mn (r = 0.449) in Table 4. Arsenic was also positively correlated with HCO3− (r = 0.272), which is the main anion in the groundwater of the study area with a concentration ranging from 125 to 642 mg/L (Table 3). High concentration of HCO3− in groundwater is usually associated with high pH values which would further promote the desorption of arsenic.

Fig. 4
figure 4

Main existing chemical species of As and their percentage

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Table 4 Results of parameter sensitivity analysis
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Occurrence Species of Arsenic

Studies on arsenic in groundwater have mainly concentrated on the total arsenic concentration which can be helpful to make a simple judgment on the pollution status of water bodies. However, total arsenic concentration cannot accurately analyze the biological effectiveness of arsenic. The toxicity of arsenic in water varies with its chemical valences, and the toxicity of arsenite (As(III)) is higher than that of arsenate (As(V)) (Ferguson and Gavis 1972; Guo et al. 2007). Therefore, to fully understand the biogeochemical cycling process, the chemical form of arsenic should be further explored. In this research, we adopted the PHREEQC model to calculate the different chemical species of arsenic, and the content of each chemical form of arsenic is listed as a percentage in this paper, and the results are shown in Fig. 5.

Fig. 5
figure 5

Pearson correlation matrix of physicochemical parameters

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According to the simulation results, the major form of arsenic in most of the groundwater was HAsO42− and H2AsO4−. It can be seen from Fig. 4 that HAsO42− is absolutely dominant in most of the water samples, with its content ranging from 16.49 to 88.66%, and the content of H2AsO4− in most water samples ranged from 11.32 to 49.83%. However, the main species of arsenic at sampling points G1-26 and G1-28 are relatively special, which are dominated by H3AsO3, with its content accounting for 98.82% and 96.11%, respectively. There are some differences in the species of arsenic at point G1-27, where the content of H3AsO3 accounted for 51.04%, and HAsO42− accounted for 38.1%, followed by a small amount of H2AsO4− and H2AsO3−. Sampling point G1-29 was dominated by H2AsO4− with a ratio of 70.49%, followed by HAsO42− accounting for 17.17% and H3AsO3 accounting for 12.33%.In addition, the total amount of H3AsO4, AsO43−, AsO33−, HAsO32−, and H4AsO3+ in groundwater accounted for only 0.002–1.18%, indicating that they are minimal chemical species of arsenic.

Numerous studies have shown that high pH environments are favorable for arsenic desorption from minerals. Iron hydroxide can adsorb a large amount of arsenic in groundwater in low pH environment but arsenic can be released into groundwater environment with the increase of pH (Pierce and Moore 1982). The pH values of groundwater in the study area are generally greater than 7.20, which indicates that it is a neutral environment in the research area, and in this environment, the clay minerals and iron hydroxide have a negative surface charge that exerts counterforce on arsenate and arsenite in the anionic form, while As(V) has a greater negative charge and desorbs more readily than As(III) (Jönsson and Sherman 2008), which may be one of the reasons for the predominance of As(V) in groundwater in the study area. Redox conditions also affect the valence state of arsenic, with arsenic compounds existing mainly as As(V) in an oxidation environment and As(III) in a reduction environment (Ding et al. 2022). Most of the water sample points have ORP values between 40 and 533 mV, indicating that they are in an oxidation environment, so the pentavalent HAsO42− and H2AsO4− are dominant, while the ORP values for samples G1-26 to G1-29 are negative, which indicates a reduction environment, thus making the trivalent H3AsO3 dominant at G1-26 to G1-29.

Two representative sampling points (G1-17 and G1-28) were selected to simulate the effects of acidity/alkalinity and redox conditions on the presence of arsenic using PHREEQC software, with G1-17 in an oxidation environment and G1-28 in a reduction environment. During the simulation, the pe values (pe is a parameter representing the oxidation–reduction conditions in the water solution) were first set unchanged while the pH values were changed to check the effects of pH on the presence of arsenic, and then pH was fixed and pe was changed to analyze the effects of oxidation–reduction conditions on the presence of arsenic. The simulation results are shown in Fig. 6. The simulation results show that in the oxidation environment when the water body is weakly acidic, arsenic in the water body mainly exists in the form of H3AsO3, and when the water body is near neutral, the main species of arsenic in the water body are H3AsO3, H2AsO4−, and HAsO42−. When the pH further increases to higher than 8.5, the main form of arsenic becomes HAsO42−. However, under the reduction conditions, the main form of arsenic in the water is H3AsO3 in the weakly acidic environment, and when the water body is in a weakly alkaline environment, the main form of arsenic in the water is HAsO42−. Since both sampling sites are in a weakly alkaline environment, their arsenic species shows the same trend with the change of pe. When the water body is in strong reduction condition, arsenic in the water body basically exists as As(III), mainly in the form of H3AsO3 and H2AsO3−. As the pe value gradually increased, the contents of H3AsO3 and H2AsO3− gradually decreased, but the content of HAsO42− and H2AsO4− began to show an increasing trend. With the pe value further increased, HAsO42− and H2AsO4− dominated in the water body and their contents remained basically unchanged, while the content of other arsenic species kept almost zero. These simulation results have indicated that H3AsO3 is the primary chemical form of arsenic under the reduction conditions while arsenic exists mainly in the form of HAsO42− and H2AsO4− under the oxidation conditions. However, the contents of them will vary with the changes of pH in the water solution. These results can provide meaningful guidance for the treatment of high arsenic water.

Fig. 6
figure 6

The arsenic species changes with pH changes a G1-17 b G1-28 and pe changes c G1-17 d G1-28 (OS denotes other species)

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Probabilistic Health Risk

The health risk of arsenic in groundwater in the study area to human through both oral and dermal exposure was assessed using a probabilistic approach with Monte Carlo simulations, and the results are shown in Fig. 7. The results show that the probability distribution for the health risk from human exposure to total arsenic follows a log-normal distribution, and the mean carcinogenic risk index for adults and children are 3.19 × 10–5 and 1.11 × 10–4, respectively, and the mean values of HQ for adults and children are 0.18 and 0.41, respectively. Children, who generally have smaller weight than adults, are at higher risk than adults (Li et al. 2016). This is consistent with the results reported in many previous research papers (Guo et al. 2022; Wang et al. 2022b). The probabilities of the risk exceeding the threshold values of CR and HQ for children were 47.3% and 1.8%, respectively, indicating that arsenic in groundwater in the study area poses a high carcinogenic risk to children, while the non-carcinogenic risk for the children may be generally acceptable. Wei et al. (2022) conducted a study on arsenic enrichment in an area of the Yinchuan Basin, and assessed the health risk due to intake of high arsenic groundwater. They also obtained the same conclusion that children are at higher risk than adults, because children with lower body weight have more susceptible immune system than adults.

Fig. 7
figure 7

Probabilistic health risk assessment results. CR of total As for a adults and b children, HQ of total As for c adults and d children

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Sensitivity analysis can be helpful in determining the degree of response and sensitivity of multiple uncertainties to the target outcome (Gao et al. 2020a). A higher absolute value of sensitivity indicates a greater impact on target outcome. Table 4 shows the average sensitivity of health risks to uncertainty parameters in the following order: arsenic concentration > annual exposure frequency (EF) > human body weight > daily intake rate (IR), indicating the variable that contributes most to the health risk is the concentration of pollutants, followed by annual exposure frequency (EF), human body weight, and daily intake rate (IR). Therefore, it is concluded that enhanced control of arsenic concentration in groundwater in the study area can help to reduce significantly the carcinogenic and non-carcinogenic risks to humans. As such, treatment of arsenic and other contaminants becomes a necessity to ensure the safety of residents who consumes the groundwater in rural villages. At present, the groundwater pumped from private wells is not treated before consumed. It is recommended that local governments enhance centralized water supply in rural areas, otherwise, provide water treatment facilities to rural residents. In addition, children are at higher risk than adults, making it necessary for the governments to focus on reducing the health risks to children from arsenic in groundwater. It will be useful if the governments can supply bottled water to vulnerable age groups such as children. Therefore, finding alternative water sources for residents may become a top priority for the local government. Previous investigation indicated that the spring water in the Qinling mountainous region has very good quality, and it is highly suggested the spring water be gathered and supplied to rural residents.

Limitations of this Study

Since Chinese drinking water quality evaluation standards do not require the analysis of As(III) and As(V), Chinese laboratories usually analyze only the total arsenic in water samples. The use of PHREEQC to model the species of arsenic present in water samples may have uncertainties. Therefore, the discussion on the species of arsenic has uncertainty, as the calculated species levels may be slightly different from the measured ones. However, the modeled species are still useful for understanding the speciation of arsenic. In addition, for the health risk assessment, since USEPA did not provide SF and RfD values for As(III), As(V), and organic species, this study did not consider and compare the health impacts of As(III) and As(V). Markley and Herbert (2009) estimated SF and RfD values of As(III) and As(V) in the previous studies. However, the derivation of these values based on cytotoxicity experiments is largely irrelevant to human external does, and the rapid interconversion of As(V) to As(III) in the human GIO system before it is absorbed may produce uncertainty to the assessment results. Therefore, future research is needed to determine the suitable parameter values for gaining more insights into the health impacts of As(III) and As(V) on human health.

Conclusions

In this study, the distribution and enrichment of arsenic in the groundwater in the typical rural areas along the northern foot of the Qinling Mountains were investigated. The different occurrence species of arsenic were calculated using PHREEQC, and the carcinogenic and non-carcinogenic risks caused by total arsenic were assessed using probabilistic models. The main conclusions are as follows:

  1. (1)

    The concentration of arsenic in groundwater ranged from 1.46 to 8.69 μg/L in the studied area. The content of arsenic in groundwater in the area of Huyi District of Xi'an City is significantly higher than that in other areas.

  2. (2)

    Based on the results of the PHREEQC simulation, the main species of arsenic in most groundwater in the study area are HAsO42− and H2AsO4−, except some local samples with H3AsO3 as the main chemical form of arsenic followed by H3AsO4, AsO43−, AsO33−, HAsO32−, and H4AsO3+ which exist in only a relatively small proportion.

  3. (3)

    The simulation results show that when the water is in a weakly acidic environment, arsenic mainly exists as H3AsO3; when the water is in a weakly alkaline environment, the main form of arsenic is HAsO42−. When the water body is under a reduction condition, the main form of arsenic is H3AsO3, followed by a small amount of H2AsO3−, but when the water body is under oxidation, HAsO42− and H2AsO4− dominate in the water solution.

  4. (4)

    The mean carcinogenic risk index for adults and children are 3.19 × 10–5 and 1.11 × 10–4, respectively, and the mean values of HQ for adults and children are 0.18 and 0.41, respectively. This indicates that children are at higher risk due to exposure to arsenic in groundwater. The probability of CR and HQ exceeding the threshold value for children is 47.3% and 1.8%, respectively, indicating that arsenic in groundwater in the study area poses a high carcinogenic risk to children. Enhancing centralized water supply in which water will be treated before supplied and finding alternative water sources are suggested as good measures to reduce the health risk in rural areas.