Abstract

The present study was conducted to appraise the suitability and human health risk of groundwater in a rapid urbanization area of North China. Groundwater samples were collected from phreatic and confined aquifers throughout the study area during pre- and post-monsoon seasons. Results show groundwater, regardless the depth, is slightly alkaline in nature and relatively fresh with the total dissolved solids within 600 mg/L. The hydrochemical facies of phreatic and confined groundwater are dominantly HCO3-Ca·Mg, followed by HCO3-Na. Groundwater in the study area, regardless the depth, is suitable for irrigation with almost no salinity and sodium hazards if proper drainage measures are undertaken. The entropy weight water quality index evaluating results show all phreatic and confined groundwater is suitable for drinking purposes. The overall potential non-carcinogenic risk posed by nitrogen (NO3-N, NH4-N) and heavy metals (As, Zn, Fe, Mn) through drinking water ingestion exists in the southwestern area and a small local area in the central study area, and is higher for children. Special attention should be paid to the arsenic because its hazard quotient was very high in some local areas. This study will benefit the protection and utilization of groundwater in near-suburb areas around the world.

INTRODUCTION

Groundwater is indispensable for ecosystem maintenance, agriculture, economic development, and domestic water supply around the world (Li & Qian 2018; Li et al. 2018b). It is especially significant in arid and semiarid regions due to the rare precipitation and inadequate surface water (Xiao et al. 2018). Much attention has been paid to groundwater availability, sustainability, and variation under the influence of human activities and climate change (Shao et al. 2014; Gu et al. 2017b; Xiao et al. 2017b; Hao et al. 2018; Havril et al. 2018). Groundwater quality should also be a concern because it not only determines the suitability for various purposes but also influences human health and social-economic development. Therefore, gaining a comprehensive understanding of groundwater quality is essential for the rational management and sustainable utilization of groundwater resources.

However, rapid urbanization and population growth have resulted in significant influences on groundwater quality and usually lead to its deterioration. In addition, groundwater has been suffering climate change and environmental changes, which may also result in significant influences on groundwater quality. Nitrogen (nitrate-nitrogen, nitrite-nitrogen, and ammonia-nitrogen) pollution is one of the most serious issues for groundwater quality throughout the world. Nitrogen contamination is mainly caused by anthropogenic factors such as sewage water infiltration, reclaimed water irrigation, and fertilizer application (Khatri & Tyagi 2015). As well, heavy metal pollutions has also been found to be globally a groundwater issue. Polluted groundwater may pose potential harm to humans through various exposure pathways like dermal contact and drinking water intake (Li 2016). Numerous researchers have focused on these issues across the world. For example, Macdonald et al. (2016) paid extra attention to the groundwater quantity and quality in the Indo-Gangetic basin, and indicated that the access to potable groundwater within 60% of aquifers is restricted by poor water quality. Lapworth et al. (2017) studied the groundwater quality of sub-Saharan Africa, and suggested inadequate waste management and source protection have led the shallow urban groundwater quality to become very poor, which causes significant influence on the domestic lives and health of 250 million people. Li (2016) summarized groundwater quality research and future challenges in western China, and pointed out that rapid industrialization and urbanization have induced serious groundwater pollution, and approximately 18% of groundwater cannot be directly utilized by human society. Related studies have been conducted in vast countries such as India, Turkey, Ghana, and China (Varol & Davraz 2015; Boateng et al. 2016; Chabukdhara et al. 2017; Gu et al. 2017a; Huang et al. 2018), and concluded that groundwater quality issues have become serious worldwide and should be paid as much attention as the groundwater quantity issues (Li 2016).

Beijing, the largest megacity in the North China Plain, has experienced rapid urbanization, industrialization, and population growth in the past 70 years. Groundwater has made great contributions to the development of urbanization, society, economy, and agriculture in this rapid development period, but has also been suffering a rapid decrease of water quantity and serious groundwater pollution. Water supply is not only restricted by the exhaustion of the groundwater resource, but also threatened by the deterioration in quality (Gu et al. 2018). This deterioration in the quality of groundwater was found in both shallow phreatic aquifers and deep confined aquifers (Xiao et al. 2017a) and has attracted public concern. Many researchers have paid attention to groundwater quality and its deterioration, driven by both natural and anthropogenic factors (Zhai et al. 2015; Gu et al. 2017a, 2018; Xiao et al. 2017a; Yu et al. 2017; Yin et al. 2019). For example, Sun et al. (2012) reported that nitrate pollution has become a major concern for the local water authority in the northwest of Beijing plain since the 1980s. Liu et al. (2014) identified the sources and behavior of nitrate contamination in the urban core of Beijing, and indicated wastewater and denitrification processes are the most common sources of nitrate pollutants for groundwater in the central urban area. Zhai et al. (2015) investigated the groundwater chemistry and quality in the exploited aquifers in southern Beijing, and found that relatively poor quality groundwater was mainly distributed in the industrial and residential areas and showed a trend of expanding from the urban to the near-suburb area. Wang et al. (2018) conducted a study on the temporal variation in groundwater hydrochemistry in a reclaimed water irrigation region in southeastern Beijing, and indicated that anthropogenic input of pollutants has led to shallow groundwater suffering salinization and nitrate contamination. Previous studies have provided a great deal of knowledge on groundwater chemistry in Beijing, but very few comprehensive assessments regarding groundwater quality and health risks have been conducted in terms of the rapid urbanization area.

The specific aims of this study are to: (1) investigate the geochemical characteristics of groundwater in rapid urbanization areas of Beijing; (2) assess the suitability of shallow phreatic water and deep confined water for irrigation and drinking purposes; and (3) determine the potential health risks caused by multiple pollutant exposure through groundwater ingestion. The present study can improve the understanding of groundwater quality in rapid urbanization areas of Beijing and other similar megacities around the world.

MATERIALS AND METHODS

Study area

The study area is a typical near-suburb area of North China, located in eastern Beijing (Figure 1). This area extends from 116°28′ to 116°58′ east longitude and between 40°00′ and 40°18′ north latitude, covering an area of about 1,021 km2. The Chaobai River, running from north to south, is the largest river in the study area. The runoff of the river is controlled by the upstream reservoirs (Miyun reservoir and Huairou reservoir) and rainfall. The study area is characterized by a temperate continental semi-humid monsoon climate with an annual temperature of 11.5 °C. The mean annual rainfall is approximately 625 mm, with more than 80% occurring in the rainy season from June to September. The average annual potential evaporation is about 1,175 mm, which is approximately two times that of the annual rainfall.

Figure 1

Location of the study area (a) within China, (b) within Beijing, and (c) sampling sites within the study area.

Figure 1

Location of the study area (a) within China, (b) within Beijing, and (c) sampling sites within the study area.

The study area is mostly covered by Quaternary deposits, with the Quaternary deposits' depth gradually increasing from 200 m in the northwest to 600 m in the southeast. The Quaternary aquifers are composed of two to three layers of gravels and sands with the lithologies getting finer and finer from northwest to southeast. Groundwater is mainly pore-water occurring in the Quaternary aquifers and flows from northwest to southeast regionally. According to the regional lithology distribution, a relative continuous clay layer occurs at the depth of 40–50 m (Figure 2). Aquifers above this layer are defined as shallow phreatic aquifers, and those below are regarded as deep confined aquifers. Aquifers are mainly recharged by lateral inflow, rainfall infiltration, irrigation infiltration, and surface water leakage, and discharged as evaporation, lateral outflow, and artificial abstraction.

Figure 2

The hydrogeological cross section along the A–A’.

Figure 2

The hydrogeological cross section along the A–A’.

Sample collection and analysis

Forty-five boreholes, including 22 shallow boreholes (shallow phreatic groundwater (SGW)) and 23 deep boreholes (deep confined groundwater (DGW)), were used as the sampling sites in this study (Figure 1). All the boreholes were sampled in both pre-monsoon and post-monsoon seasons of 2017. Prior to sampling, boreholes were pumped for about three borehole volumes to eliminate the influence of stagnant water and monitored until the electrical conductivity (EC) of pumping groundwater was stable. Samples were taken in 2.5 L plastic bottles, which had been pre-cleaned three times using the water to be sampled. The sampling procedure and preservation followed is as described by Huang et al. (2016).

Parameters such as temperature (T), pH, EC were measured in situ using a multi-parameter instrument (Multi 350i/SET, Munich, Germany). Samples for major chemistry analysis were sent to the Laboratory of Groundwater Sciences and Engineering of the Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences (LGSE-IHEG-CAGS). Major cations (K+, Na+, Ca2+, Mg2+) and four trace elements (As, Zn, Fe, Mn) were analyzed using inductively coupled plasma-mass spectrometry (Agilent 7500ce ICP-MS, Japan). SO42−, Cl, NO3, and NH4+ were measured by ion chromatography (Shimadzu LC-10ADvp, Japan). HCO3 and total dissolved solid (TDS) were determined by acid–base titration and gravimetric analysis, respectively. All samples have percent charge balance errors within ±5%.

Evaluation of groundwater quality for irrigation purposes

EC of groundwater was used to evaluate irrigation suitability regarding the salinity of groundwater. In addition, several water quality indicators including sodium adsorption ratio (SAR), sodium percentage (%Na), and permeability index (PI) were introduced to assess the suitability of SGW and DGW for agricultural irrigation purposes in the present study. Their formulas are listed below. All the ions are expressed in milliequivalent per liter (meq/L): 
formula
(1)
 
formula
(2)
 
formula
(3)

The criteria of agricultural irrigation water quality classifications are presented in Table 1. Water quality can be divided into excellent, good, acceptable, and unacceptable classifications based on the EC and SAR values, and be classified into suitable, marginally suitable, and unsuitable classifications according to %Na. In terms of PI, the water quality for agricultural purposes are divided into three categories including good, suitable, and unsuitable (Doneen 1964).

Table 1

Criteria of irrigation water quality classifications based on EC, SAR, %Na

EC (μS/cm)SARIrrigation water quality%NaIrrigation water quality
<250 <10 Excellent <30 Suitable 
250–750 10–18 Good 30–60 Marginally suitable 
750–2,250 18–26 Acceptable >60 Unsuitable 
>2,250 >26 Unacceptable   
EC (μS/cm)SARIrrigation water quality%NaIrrigation water quality
<250 <10 Excellent <30 Suitable 
250–750 10–18 Good 30–60 Marginally suitable 
750–2,250 18–26 Acceptable >60 Unsuitable 
>2,250 >26 Unacceptable   

Entropy-weighted water quality index

Water quality index (WQI) is a widely used method to determine the overall quality of water for drinking purposes (Abbasnia et al. 2019). In this study, an improved WQI method, named entropy-weighted water quality index (EWQI), was introduced to obtain the overall suitability of groundwater for drinking purposes. The introduction of information entropy in the weight determination of hydrochemical indicators can greatly improve the assessment accuracy which may be influenced by the ignorance of weight in WQI. The procedures of EWQI have been described in detail by Amiri et al. (2014). The classification criteria of groundwater quality based on EWQI are listed in Table 2 and water quality is divided into excellent, good, medium, poor, and extremely poor categories.

Table 2

Classification criteria of groundwater quality based on EWQI

EWQIRankWater quality
<50 Excellent 
50–100 Good 
100–150 Medium 
150–200 Poor 
>200 Extremely poor 
EWQIRankWater quality
<50 Excellent 
50–100 Good 
100–150 Medium 
150–200 Poor 
>200 Extremely poor 

Health risk assessment

The possible health hazards caused by pollutants in water can be assessed using a human health risk assessment model (HHRA model) proposed by the United States Environmental Protection Agency (US EPA). The main exposure paths of human beings to groundwater pollutants are through dermal contact and drinking water intake. Generally, the risk of groundwater caused by dermal contact is negligible. Thus, the present study focused on the non-carcinogenic risk through drinking water intake pathway.

The chronic daily intake (CDI) dose through drinking water intake can be calculated using the following equation (Qasemi et al. 2018a, 2019; Yousefi et al. 2019): 
formula
(4)

In this expression, C refers to the pollutant concentrations in groundwater. IR indicates the ingestion rate of drinking water, and 0.6 L and 1.0 L are recommended for children under 12 years old and adults, respectively, in national guidelines. EF represents exposure frequency, and its value is 365 days for both children and adults in this study. ED denotes exposure duration, and its values are 12 years for children and 25 years for adults (Li et al. 2018a). BW expresses the average body weight, and its values for children and adults are 15.9 kg and 56.8 kg, respectively. AT is the average time, which is equal to ED × 365 for non-carcinogenic risk.

The potential non-carcinogenic risk of a certain pollutant can be represented by the hazard quotient (HQi), which is computed using the follow equation (Fallahzadeh et al. 2018; Qasemi et al. 2018b; Dehghani et al. 2019; Yousefi et al. 2019): 
formula
(5)
where RfD is the reference dosage for non-carcinogenic contaminants through drinking intake pathway.
The overall potential non-carcinogenic risk posed by multiple contaminants (1, 2, …, i) is usually assessed using the hazard index (HI). The expression of HI is as follows (Yousefi et al. 2018): 
formula
(6)

RESULTS AND DISCUSSION

General groundwater chemistry

The descriptive statistical summaries of major physical and chemical parameters of both SGW and DGW during the pre-monsoon and post-monsoon seasons are presented in Table 3. The standard World Health Organization (WHO) values for drinking purposes are also used.

Table 3

Descriptive statistics of physicochemical parameters of shallow and deep groundwater

WHO (2011) Pre-monsoon
Post-monsoon
MinMaxMeanSDMinMaxMeanSD
SGW (n = 22) 
T (°C) – 10.0 20.0 13.8 2.7 14.0 25.0 17.3 
pH 6.5–8.5 7.70 8.00 7.78 0.08 7.60 8.40 8.07 0.16 
EC (μS/cm) – 468 749 575 82 430 860 537 98 
TDS (mg/L) 500 253 429 336 55 286 574 363 68 
K+ (mg/L) – 0.06 1.42 0.66 0.34 0.83 5.78 2.31 1.25 
Na+ (mg/L) 50 104 30.4 22.3 13.4 116 37.8 24.2 
Ca2+ (mg/L) 75 73.8 28.9 19.9 14.1 93.3 57 17.2 
Mg2+ (mg/L) 50 1.9 68.8 36.7 16.9 14.4 40.2 25.4 5.7 
Cl (mg/L) 250 3.8 56.2 14.1 11.1 3.9 83.4 15.7 16.7 
SO42− (mg/L) 250 50 22.1 12.5 55 17.6 12.9 
HCO3 (mg/L) – 229 497 309.2 67.8 128 409 295.9 62 
NO3 (mg/L) 45 0.2 7.8 2.1 2.71 0.2 10.8 2.35 3.09 
NO2 (mg/L) 0.003 0.008 0.003 0.001 0.180 0.031 0.056 
NH4+ (mg/L) – 0.02 0.78 0.11 0.18 0.02 0.12 0.04 0.02 
As (mg/L) 0.01 0.001 0.037 0.006 0.009 0.001 0.035 0.007 0.010 
Zn (mg/L) 0.1 0.002 1.340 0.099 0.287 0.002 0.690 0.103 0.171 
Fe (mg/L) 2.0 0.030 0.260 0.064 0.069 0.030 6.030 0.358 1.269 
Mn (mg/L) 0.4 0.0004 0.3400 0.0441 0.0869 0.0100 1.6400 0.1191 0.3478 
DGW (n = 23) 
T (°C) – 10.0 18.0 13.3 2.5 14.0 24.0 18.0 3.2 
pH 6.5–8.5 7.70 8.20 7.80 0.12 7.80 8.40 8.07 0.15 
EC (μS/cm) – 388 803 554 102 331 684 508 81 
TDS (mg/L) 500 242 457 323 61 210 491 343 76 
K+ (mg/L) – 0.05 1.12 0.6 0.3 0.58 4.72 2.2 1.08 
Na+ (mg/L) 50 5.2 86.2 30.6 24.1 17.4 113 43.5 26.4 
Ca2+ (mg/L) 75 65.1 34.9 22.3 15.9 95.4 55 17 
Mg2+ (mg/L) 50 1.4 54.7 30.9 16 4.8 32.4 23.5 6.8 
Cl (mg/L) 250 3.8 25.7 11.5 5.6 3.3 33.9 13 
SO42− (mg/L) 250 43 23.6 11.2 52 18.7 13.6 
HCO3 (mg/L) – 200 494 293.2 72.1 195 487 311 68.4 
NO3 (mg/L) 45 0.2 5.7 1.82 1.92 0.2 8.1 2.1 2.46 
NO2 (mg/L) 0.010 0.004 0.002 0.060 0.010 0.015 
NH4+ (mg/L) – 0.02 0.42 0.10 0.14 0.02 0.08 0.04 0.02 
As (mg/L) 0.01 0.001 0.014 0.003 0.004 0.001 0.079 0.011 0.019 
Zn (mg/L) 0.1 0.002 0.487 0.081 0.123 0.022 0.987 0.150 0.232 
Fe (mg/L) 2.0 0.030 0.360 0.087 0.101 0.030 1.010 0.160 0.264 
Mn (mg/L) 0.4 0.0100 0.3100 0.0517 0.0804 0.010 0.230 0.047 0.061 
WHO (2011) Pre-monsoon
Post-monsoon
MinMaxMeanSDMinMaxMeanSD
SGW (n = 22) 
T (°C) – 10.0 20.0 13.8 2.7 14.0 25.0 17.3 
pH 6.5–8.5 7.70 8.00 7.78 0.08 7.60 8.40 8.07 0.16 
EC (μS/cm) – 468 749 575 82 430 860 537 98 
TDS (mg/L) 500 253 429 336 55 286 574 363 68 
K+ (mg/L) – 0.06 1.42 0.66 0.34 0.83 5.78 2.31 1.25 
Na+ (mg/L) 50 104 30.4 22.3 13.4 116 37.8 24.2 
Ca2+ (mg/L) 75 73.8 28.9 19.9 14.1 93.3 57 17.2 
Mg2+ (mg/L) 50 1.9 68.8 36.7 16.9 14.4 40.2 25.4 5.7 
Cl (mg/L) 250 3.8 56.2 14.1 11.1 3.9 83.4 15.7 16.7 
SO42− (mg/L) 250 50 22.1 12.5 55 17.6 12.9 
HCO3 (mg/L) – 229 497 309.2 67.8 128 409 295.9 62 
NO3 (mg/L) 45 0.2 7.8 2.1 2.71 0.2 10.8 2.35 3.09 
NO2 (mg/L) 0.003 0.008 0.003 0.001 0.180 0.031 0.056 
NH4+ (mg/L) – 0.02 0.78 0.11 0.18 0.02 0.12 0.04 0.02 
As (mg/L) 0.01 0.001 0.037 0.006 0.009 0.001 0.035 0.007 0.010 
Zn (mg/L) 0.1 0.002 1.340 0.099 0.287 0.002 0.690 0.103 0.171 
Fe (mg/L) 2.0 0.030 0.260 0.064 0.069 0.030 6.030 0.358 1.269 
Mn (mg/L) 0.4 0.0004 0.3400 0.0441 0.0869 0.0100 1.6400 0.1191 0.3478 
DGW (n = 23) 
T (°C) – 10.0 18.0 13.3 2.5 14.0 24.0 18.0 3.2 
pH 6.5–8.5 7.70 8.20 7.80 0.12 7.80 8.40 8.07 0.15 
EC (μS/cm) – 388 803 554 102 331 684 508 81 
TDS (mg/L) 500 242 457 323 61 210 491 343 76 
K+ (mg/L) – 0.05 1.12 0.6 0.3 0.58 4.72 2.2 1.08 
Na+ (mg/L) 50 5.2 86.2 30.6 24.1 17.4 113 43.5 26.4 
Ca2+ (mg/L) 75 65.1 34.9 22.3 15.9 95.4 55 17 
Mg2+ (mg/L) 50 1.4 54.7 30.9 16 4.8 32.4 23.5 6.8 
Cl (mg/L) 250 3.8 25.7 11.5 5.6 3.3 33.9 13 
SO42− (mg/L) 250 43 23.6 11.2 52 18.7 13.6 
HCO3 (mg/L) – 200 494 293.2 72.1 195 487 311 68.4 
NO3 (mg/L) 45 0.2 5.7 1.82 1.92 0.2 8.1 2.1 2.46 
NO2 (mg/L) 0.010 0.004 0.002 0.060 0.010 0.015 
NH4+ (mg/L) – 0.02 0.42 0.10 0.14 0.02 0.08 0.04 0.02 
As (mg/L) 0.01 0.001 0.014 0.003 0.004 0.001 0.079 0.011 0.019 
Zn (mg/L) 0.1 0.002 0.487 0.081 0.123 0.022 0.987 0.150 0.232 
Fe (mg/L) 2.0 0.030 0.360 0.087 0.101 0.030 1.010 0.160 0.264 
Mn (mg/L) 0.4 0.0100 0.3100 0.0517 0.0804 0.010 0.230 0.047 0.061 

SD, standard deviation.

As shown in Table 3, groundwater temperature ranges between 10.0 °C and 20.0 °C with an average of 13.8 °C for SGW and from 10 °C to 18 °C with an average of 13.3 °C for DGW during the pre-monsoon season. During the post-monsoon season it varies from 14.0 °C to 25.0 °C with an average of 17.3 °C for SGW and between 14 °C and 24 °C with an average of 18.0 °C for DGW. The temperature values of SGW and DGW are very similar in the same season, suggesting SGW and DGW maintain almost the same varying pace. The pH values are in the range of 7.6–8.4 with little variance for both SGW and DGW, indicating slightly alkaline condition. The EC values of SGW range from 468 μS/cm to 749 μ/cm with an average of 575 μS/cm during the pre-monsoon season, and are in the range of 430–860 μS/cm with an average of 537 μS/cm during the post-monsoon season. Those of DGW vary between 388 μS/cm and 803 μS/cm with an average of 554 μS/cm during the pre-monsoon season, and range from 331 μS/cm to 684 μS/cm with an average of 508 μS/cm during the post-monsoon season. This shows that both SGW and DGW are slightly diluted during the monsoon season due to the infiltration of local fresh precipitation or fresh surface water originating from upstream regions.

The TDS values of SGW are in the range of 253–429 mg/L with an average of 336 mg/L and a standard deviation of 55 mg/L during the pre-monsoon season, and vary from 286 mg/L to 574 mg/L with an average of 363 mg/L and a standard deviation of 68 mg/L during the post-monsoon season. For DGW, the TDS values vary from 242 mg/L to 457 mg/L with an average of 323 mg/L and a standard deviation of 61 mg/L during the pre-monsoon season, and between 210 mg/L and 491 mg/L with an average of 343 mg/L and a standard deviation of 76 mg/L during the post-monsoon season. All SGW and DGW samples are within the TDS values' narrow range below 600 mg/L and small standard deviation. The abundance of cations during the pre-monsoon season is in the following order: Mg2+>Na+>Ca2+>K+ for SGW and Ca2+>Mg2+>Na+>K+ for DGW. The order changes to Ca2+>Na+>Mg2+>K+ for both SGW and DGW during the post-monsoon season. Bicarbonate is the dominant anion, followed by sulfate and chloride in both SGW and DGW, and shows almost no seasonal variation.

The concentration of nitrate, nitrite, and ammonia during the pre-monsoon is in the range of 0.2–7.8 mg/L, 0.003–0.008 mg/L, 0.02–0.78 mg/L, respectively, for SGW, and 0.2–5.7 mg/L, 0–0.010 mg/L, 0.02–0.78 mg/L, respectively, for DGW. During the post-monsoon it is in the range of 0.2–10.8 mg/L, 0–0.180 mg/L, 0.02–0.12 mg/L, respectively, for SGW, and 0.2–8.1 mg/L, 0–0.060 mg/L, 0.02–0.08 mg/L, respectively, for DGW. The nitrogen pollutants are all within permissible limits. The concentration of nitrate and nitrite in both SGW and DGW show a slight increase trend from pre-monsoon to post-monsoon season (Table 3), indicating that the infiltrating surface water carried nitrate/nitrite pollutants into shallow aquifers and deep aquifers during the monsoon. The ammonia concentration in SGW and DGW is presenting a decreasing trend from pre-monsoon to post-monsoon season. This may be as the result of reaction between ammonia and oxygen brought in by infiltrated surface water.

The heavy metal concentrations range from 0.001 mg/L for elements like As up to 6.03 mg/L for Fe (Table 3). Based on the WHO Drinking Water Quality standard, the maximum concentrations of As and Zn are greater than the permissible limits (0.01 mg/L for As and 0.1 mg/L for Zn) for both SGW and DGW in all seasons. For Fe and Mn, only SGW collected in the post-monsoon season has maximum concentrations exceeding the permissible limits (2.0 mg/L for Fe and 0.4 mg/L for Mn) of WHO. The mean values of As, Zn, Fe, Mn of SGW and DGW in all seasons are far less than the permissible limits. All the heavy metals' mean contents increased from pre- to post-monsoon season. This is because the infiltrated water brought pollutants downwards during the monsoon season.

To determine the hydrochemical facies of groundwater, the Piper trilinear diagram has been adopted in this study. Generally, the diamond-shaped field of a Piper diagram can be divided into four parts representing four basic groundwater facies: (1) HCO3-Ca·Mg; (2) HCO3-Na; (3) SO4·Cl-Na; (4) SO4·Cl-Ca·Mg. All groundwater samples sampled from shallow and deep aquifers during the pre- and post-monsoon season are plotted in Figure 3. It shows that HCO3-Ca·Mg is the dominant hydrochemical facies for both SGW and DGW, followed by HCO3-Na. Figure 3 shows that about 95% of SGW samples and 93% of DGW samples are classified to HCO3-Ca·Mg type; only 5% of SGW samples and 7% of DGW samples are identified as HCO3-Na. The hydrochemical facies of both SGW and DGW are with almost no change before or after the monsoon (Figure 3).

Figure 3

Piper diagram for both shallow and deep groundwater.

Figure 3

Piper diagram for both shallow and deep groundwater.

Groundwater suitability

Irrigation purpose

EC is important in classifying irrigation water since it is a measure of the total salinity of groundwater. Irrigation water with higher EC may result in a saline soil which has a hard texture and low permeability (Patel et al. 2016). According to the EC criteria for irrigation water quality (Table 1), most samples for SGW and DGW in both pre- and post-monsoon season have EC values in the range of 250–750 μS/cm (Figure 4), implying good quality for irrigation; only one SGW sample collected in the post-monsoon season and one DGW sample collected during the pre-monsoon season have an EC value slightly above 750 μS/cm (Figure 4), indicating acceptable quality for irrigation.

Figure 4

USSL diagram for groundwater of pre- and post-monsoon.

Figure 4

USSL diagram for groundwater of pre- and post-monsoon.

SAR is an ideal index to assess the possibility of sodium/alkali hazard because it is a measure of soil capacity to adsorb sodium from irrigation water. Irrigation water with higher SAR value is able to destroy the soil structure by cation exchange reaction between sodium in water and calcium (or magnesium) in soil. The SAR values of SGW range from 0.17 to 5.19 with an average of 1.01 in pre-monsoon, and between 0.37 and 4.16 with an average of 1.10 in post-monsoon season. Those of DGW are in the range of 0.16–4.96 (mean 1.03) in pre-monsoon and 0.51–6.36 (mean 1.39) in post-monsoon season. All SGW and DGW samples fall in the excellent category in pre- and post-monsoon seasons.

United States Salinity Laboratory (USSL) classification was introduced to further determine the irrigation suitability of groundwater. EC and SAR are taken as the salinity and alkalinity hazard, respectively, in the USSL diagram. As shown in Figure 4, the majority of the samples fall in the C2S1 category of medium salinity and low alkalinity water, indicating suitability for all plants under good drainage conditions. Only two samples (one SGW sample and one DGW sample) belong to C3S1 category, which represents water with high salinity hazard and low alkalinity hazard. Proper drainage should be undertaken otherwise their usage for irrigation would be dangerous for soil.

Sodium is an important parameter to determine the suitability of water for irrigation purposes due to its potential threat to soil permeability. Sodium percent (%Na) is used to express the sodium content in groundwater. As shown in the Wilcox diagram (Figure 5), most of the SGW samples (95.45%) fall in the excellent to good category for irrigation, and 2.27% and 2.27% belong to good to permissible, permissible to suitable categories, respectively. For DGW, 93.48, 4.35, and 2.17% of the collected samples belong to excellent to good, good to permissible, permissible to suitable categories for irrigation, respectively. All SGW and DGW in the study area are permissible for irrigation in terms of %Na.

Figure 5

Wilcox diagram (%Na versus EC) demonstrating irrigation water quality.

Figure 5

Wilcox diagram (%Na versus EC) demonstrating irrigation water quality.

Permeability, an essential physical property of soil, may be affected by long-term irrigation. The potential risk of long-term irrigation of a certain water can be determined by PI. The PI values of SGW samples vary from 39.32 to 110.86 with an average of 61.11 in pre-monsoon and between 36.02 and 90.66 with an average of 57.37 in post-monsoon season. That of DGW samples are in the range of 33.88–117.45 (mean 62.59) in pre-monsoon and 45.03–113.18 (mean 62.33) in post-monsoon season. According to the classification of irrigation water based on permeability developed by Doneen (1964), 27.27, 70.45, 2.27% of SGW samples fall in Class-I, Class-II, Class-III categories, respectively; 28.26, 65.22, 6.52% of DGW samples belong to Class-I (good), Class-II (suitable), Class-III categories (unsuitable), respectively (Figure 6). This implies the majority of SGW (97.73%) and DGW (93.48%) in the study area are suitable for long-term irrigation without noticeable variation.

Figure 6

Classification of irrigation water based on permeability.

Figure 6

Classification of irrigation water based on permeability.

Overall, all groundwater in the study area, regardless the depth, in both pre- and post-monsoon seasons are suitable for irrigation with nearly no salinity and sodium hazards if proper drainage measures are undertaken. The majority of SGW and DGW are suitable for long-term irrigation and would not destroy the soil permeability, while 2.27% of SGW samples (one in pre-monsoon) and 6.52% of DGW samples (two in pre-monsoon and one in post-monsoon) have high PI values and potentially threaten the soil property when used for long-term agricultural irrigation.

Drinking purposes

To understand the suitability of groundwater quality for drinking purposes, physicochemical parameters of groundwater were assessed with the drinking water standards set by WHO (2011).

The pH values of groundwater, regardless the depth, in the study area are within the permissible limits (6.5–8.5) of WHO standards at all sites (Table 3). The average values of pH in the pre- and post-monsoon seasons are 7.78 and 8.07, respectively, for SGW; and for DGW are 7.80 and 8.07, respectively. EC is a representation of the ionized substance content in groundwater (Jain & Vaid 2018). The EC values of groundwater at all sampled sites and depths are below 1,500 μS/cm (Table 3), indicating fresh water according to the groundwater classification based on EC (fresh: <1,500 μS/cm; brackish: 1,500–3,000 μS/cm; saline: >3,000 μS/cm) (Xiao et al. 2017a).

TDS is another comprehensive representative index of dissolved ions in groundwater. Almost all groundwater samples (except one post-monsoon SGW sample) collected from both pre- and post-monsoon seasons have TDS values less than the permissible limit of 500 mg/L of the WHO (2011) standard (Table 3), implying suitability for drinking purposes in terms of dissolved substances' content. All soluble cations and anions except sodium are less than the maximum permissible limits of the WHO standard, suggesting suitability for drinking purposes with regards to these individual ions. Especially, nitrogen parameters (including nitrate, nitrite, and ammonia), which are sensitive to anthropogenic pollutants, in both SGW and DGW are far less than the permissible limits of the WHO standard, suggesting groundwater in the study area has good quality without significant anthropogenic influence. The average values of sodium in both shallow and deep groundwater during all (pre- and post-monsoon) seasons are within the permissible limits (50 mg/L). Samples with sodium concentration exceeding the maximum WHO permissible limit of 50 mg/L, accounts for 18.18% (pre-monsoon) and 27.27% (post-monsoon) of SGW samples with the maximum values of 104 mg/L and 116 mg/L, respectively. For DGW, 21.74% (pre-monsoon) and 34.78% (post-monsoon) of collected samples were found to exceed the maximum permissible limit with the maximum values of 86.2 mg/L and 113 mg/L, respectively.

To further understand the comprehensive quality of groundwater for drinking purposes, the EWQI was applied in the present study. The EWQI values of SGW range from 39.54 to 65.77 with an average of 50.05 in pre-monsoon, and vary between 37.86 and 71.35 with an average of 46.50. Those of DGW are in the range of 32.17–57.66 with the mean of 44.41 in the pre-monsoon, and 32.27–59.08 with the mean of 46.28 in the pre-monsoon season. According to the EWQI classification criteria (Table 2), 54.55% and 72.73% of SGW samples collected in pre- and post-monsoon season, respectively, are of excellent quality (Rank 1) for drinking purposes, and others have good quality (Rank 2). About 82.61 and 73.91% of DGW samples obtained in pre- and post-monsoon season, respectively, have excellent quality (Rank 1) for drinking purposes, and others are of good quality (Rank 2) (Figure 7). Overall, groundwater, regardless the depth, in the study area is suitable for drinking and domestic purposes. This is very similar to the deep confined groundwater quality of southeastern Beijing plain, which has virtually not been influenced by anthropogenic activities and evaporation (Gu et al. 2018). The shallow groundwater in this study area has a much better quality than that in the southeastern Beijing plain (the downstream area). This is ascribed to the greater groundwater depth (almost no evaporation) and less reclaimed water/wastewater used for irrigation historically in the study area (Zhai et al. 2015; Gu et al. 2017a, 2018; Xiao et al. 2017a).

Figure 7

Bivariate diagram of entropy-weighted water quality index (EWQI) versus EC.

Figure 7

Bivariate diagram of entropy-weighted water quality index (EWQI) versus EC.

Health risk assessment

Higher concentrations of NO3-N, NH4-N and heavy metals (such as As, Zn, Fe, Mn) in drinking water may pose serious health hazards to human beings (Li et al. 2019). In the present study, the non-carcinogenic risk due to ingestion of nitrogen (NO3-N, NH4-N) and heavy metals (As, Zn, Fe, Mn) through drinking water was assessed for children and adults.

The assessment results for children and adults are presented in Table 4. The maximum hazard quotient (HQ) of NO3-N, NH4-N, Zn, Fe, Mn of all SGW and DGW samples in the study area for children and adults is less than the permissible limit (HQ = 1), indicating that nitrogen (NO3-N, NH4-N), Zn, Fe, Mn would not pose non-carcinogenic risks to human health individually. The As hazard quotient of some SGW and DGW samples are found to exceed the permissible limit (HQ = 1) regarding children and adults, implying that As in SGW and DGW at some local scales may pose non-carcinogenic risk to children and adults. The HI values suggest that, overall, potential non-carcinogenic risks posed by multiple contaminants may exist at some sampling sites for SGW and DGW sampled during both pre- and post-monsoon seasons. The overall potential non-carcinogenic risk for children is higher than that for adults. Similar studies have been conducted in many regions and have also found that children are at greater risk than adults (Su et al. 2013; Wu & Sun 2016).

Table 4

Statistics of health risk assessment results for children and adults through drinking water intake

Pre-monsoon (Mean ± SD)
Post-monsoon (Mean ± SD)
ChildrenAdultsChildrenAdults
SGW (n = 22) 
HQNO3-N 4.95 × 10−2 ± 6.39 × 10−2 2.31 × 10−2 ± 2.98 × 10−2 8.85 × 10−2 ± 1.16 × 10−1 2.58 × 10−2 ± 3.40 × 10−2 
HQNH4-N 4.17 × 10−3 ± 7.04 × 10−3 1.95 × 10−3 ± 3.28 × 10−3 1.64 × 10−3 ± 9.67 × 10−4 7.67 × 10−4 ± 4.51 × 10−4 
HQAs 7.95 × 10−1 ± 1.17 × 100 3.71 × 10−1 ± 5.46 × 10−1 8.46 × 10−1 ± 1.31 × 100 3.95 × 10−1 ± 6.09 × 10−1 
HQZn 1.25 × 10−2 ± 3.61 × 10−2 5.83 × 10−3 ± 1.68 × 10−2 1.29 × 10−2 ± 2.15 × 10−2 6.04 × 10−3 ± 1.01 × 10−2 
HQFe 3.45 × 10−3 ± 3.73 × 10−3 1.61 × 10−3 ± 1.74 × 10−3 1.93 × 10−2 ± 6.84 × 10−2 9.00 × 10−3 ± 3.19 × 10−2 
HQMn 1.19 × 10−2 ± 2.34 × 10−2 5.55 × 10−3 ± 1.09 × 10−2 3.21 × 10−2 ± 9.37 × 10−2 1.50 × 10−2 ± 4.37 × 10−2 
HI 8.76 × 10−1 ± 1.15 × 100 8.74 × 10−1 ± 5.38 × 10−1 1.00 × 100 ± 1.27 × 100 4.51 × 10−1 ± 6.01 × 10−1 
DGW (n = 23) 
HQNO3-N 4.29 × 10−2 ± 4.54 × 10−2 2.00 × 10−2 ± 2.12 × 10−2 4.95 × 10−2 ± 5.81 × 10−2 2.31 × 10−2 ± 2.71 × 10−2 
HQNH4-N 3.97 × 10−3 ± 5.34 × 10−3 1.85 × 10−3 ± 2.49 × 10−3 1.45 × 10−3 ± 6.12 × 10−4 6.79 × 10−4 ± 2.86 × 10−4 
HQAs 3.94 × 10−1 ± 5.19 × 10−1 1.84 × 10−1 ± 2.42 × 10−1 1.32 × 100 ± 2.36 × 100 6.17 × 10−1 ± 1.10 × 100 
HQZn 1.02 × 10−2 ± 1.55 × 10−2 4.78 × 10−3 ± 7.22 × 10−3 1.89 × 10−2 ± 2.92 × 10−2 8.81 × 10−3 ± 1.36 × 10−2 
HQFe 4.69 × 10−3 ± 5.46 × 10−3 2.19 × 10−3 ± 2.55 × 10−3 8.60 × 10−3 ± 1.42 × 10−2 4.01 × 10−3 ± 6.65 × 10−3 
HQMn 1.39 × 10−2 ± 2.17 × 10−2 6.51 × 10−3 ± 1.01 × 10−2 1.25 × 10−2 ± 1.63 × 10−2 5.85 × 10−3 ± 7.63 × 10−3 
HI 8.15 × 10−1 ± 5.40 × 10−1 3.80 × 10−1 ± 2.52 × 10−1 1.76 × 100 ± 2.37 × 100 8.22 × 10−1 ± 1.11 × 100 
Pre-monsoon (Mean ± SD)
Post-monsoon (Mean ± SD)
ChildrenAdultsChildrenAdults
SGW (n = 22) 
HQNO3-N 4.95 × 10−2 ± 6.39 × 10−2 2.31 × 10−2 ± 2.98 × 10−2 8.85 × 10−2 ± 1.16 × 10−1 2.58 × 10−2 ± 3.40 × 10−2 
HQNH4-N 4.17 × 10−3 ± 7.04 × 10−3 1.95 × 10−3 ± 3.28 × 10−3 1.64 × 10−3 ± 9.67 × 10−4 7.67 × 10−4 ± 4.51 × 10−4 
HQAs 7.95 × 10−1 ± 1.17 × 100 3.71 × 10−1 ± 5.46 × 10−1 8.46 × 10−1 ± 1.31 × 100 3.95 × 10−1 ± 6.09 × 10−1 
HQZn 1.25 × 10−2 ± 3.61 × 10−2 5.83 × 10−3 ± 1.68 × 10−2 1.29 × 10−2 ± 2.15 × 10−2 6.04 × 10−3 ± 1.01 × 10−2 
HQFe 3.45 × 10−3 ± 3.73 × 10−3 1.61 × 10−3 ± 1.74 × 10−3 1.93 × 10−2 ± 6.84 × 10−2 9.00 × 10−3 ± 3.19 × 10−2 
HQMn 1.19 × 10−2 ± 2.34 × 10−2 5.55 × 10−3 ± 1.09 × 10−2 3.21 × 10−2 ± 9.37 × 10−2 1.50 × 10−2 ± 4.37 × 10−2 
HI 8.76 × 10−1 ± 1.15 × 100 8.74 × 10−1 ± 5.38 × 10−1 1.00 × 100 ± 1.27 × 100 4.51 × 10−1 ± 6.01 × 10−1 
DGW (n = 23) 
HQNO3-N 4.29 × 10−2 ± 4.54 × 10−2 2.00 × 10−2 ± 2.12 × 10−2 4.95 × 10−2 ± 5.81 × 10−2 2.31 × 10−2 ± 2.71 × 10−2 
HQNH4-N 3.97 × 10−3 ± 5.34 × 10−3 1.85 × 10−3 ± 2.49 × 10−3 1.45 × 10−3 ± 6.12 × 10−4 6.79 × 10−4 ± 2.86 × 10−4 
HQAs 3.94 × 10−1 ± 5.19 × 10−1 1.84 × 10−1 ± 2.42 × 10−1 1.32 × 100 ± 2.36 × 100 6.17 × 10−1 ± 1.10 × 100 
HQZn 1.02 × 10−2 ± 1.55 × 10−2 4.78 × 10−3 ± 7.22 × 10−3 1.89 × 10−2 ± 2.92 × 10−2 8.81 × 10−3 ± 1.36 × 10−2 
HQFe 4.69 × 10−3 ± 5.46 × 10−3 2.19 × 10−3 ± 2.55 × 10−3 8.60 × 10−3 ± 1.42 × 10−2 4.01 × 10−3 ± 6.65 × 10−3 
HQMn 1.39 × 10−2 ± 2.17 × 10−2 6.51 × 10−3 ± 1.01 × 10−2 1.25 × 10−2 ± 1.63 × 10−2 5.85 × 10−3 ± 7.63 × 10−3 
HI 8.15 × 10−1 ± 5.40 × 10−1 3.80 × 10−1 ± 2.52 × 10−1 1.76 × 100 ± 2.37 × 100 8.22 × 10−1 ± 1.11 × 100 

Spatial distributions of HI for children and adults are shown in Figure 8. Overall, the spatial distribution of high HI values of SGW are basically consistent with that of DGW in both pre- and post-monsoon seasons. For SGW, the high HI values for children and adults in both seasons are mainly distributed in the southwestern area and a small local area in the central study area. It can be seen from Figure 8(a)–8(d) that the area with potential non-carcinogenic risk (HI ≥ 1) for children is larger than that for adults and higher HI values for children are observed in these potential non-carcinogenic risk areas when compared with that for adults. The area of potential non-carcinogenic risk areas (HI ≥ 1) and their HI values show no significant change for children from the pre- to post-monsoon season, but present an obvious decrease for adults. This may be due to the dilution of recharging surface water and precipitation. For DGW in pre-monsoon season (Figure 8(e) and 8(f)), the area with potential non-carcinogenic risk (HI ≥ 1) is smaller in comparison to that of SGW (Figure 8(a) and 8(b)), but shows a significant increase from the pre-monsoon to post-monsoon season (Figure 8(e)8(h)). The values of HI for both children and adults also present an obvious increase from the pre- to post-monsoon season. This may be caused by the infiltration of pollutants in the monsoon. As aforementioned, the HQ of As pollutant for children and adults is found to exceed the permissible limit (HQ = 1) in some local areas. Therefore, groundwater should be treated properly with regards to As if used for long-term drinking purposes.

Figure 8

Spatial distribution of HI of: (a) SGW in pre-monsoon for children; (b) SGW in pre-monsoon for adults; (c) SGW in post-monsoon for children; (d) SGW in post-monsoon for adults; (e) DGW in pre-monsoon for children; (f) DGW in pre-monsoon for adults; (g) DGW in post-monsoon for children; (h) DGW in post-monsoon for adults.

Figure 8

Spatial distribution of HI of: (a) SGW in pre-monsoon for children; (b) SGW in pre-monsoon for adults; (c) SGW in post-monsoon for children; (d) SGW in post-monsoon for adults; (e) DGW in pre-monsoon for children; (f) DGW in pre-monsoon for adults; (g) DGW in post-monsoon for children; (h) DGW in post-monsoon for adults.

CONCLUSIONS

Groundwater is the primary water resource for various purposes in arid and semiarid regions throughout the world. This paper reported the quality and human health risk of groundwater in a rapid urbanization area of the North China Plain. The main findings are as follows.

Groundwater in both shallow phreatic aquifers and deep confined aquifers is slightly alkaline in nature with TDS less than 600 mg/L. The hydrogeochemical facies of groundwater are dominantly HCO3-Ca·Mg type, followed by HCO3-Na type. The EC values show a decreasing trend from pre- to post-monsoon for both shallow and deep groundwater as the result of dilution by the infiltrating fresher water during the monsoon season. All groundwater, regardless the depth, in both pre- and post-monsoon is suitable for drinking purposes and irrigation with almost no salinity and sodium hazards if proper drainage measures are undertaken. The majority of shallow and deep groundwater in all seasons is suitable for long-term irrigation except for several groundwater samples with high PI values which may potentially threaten soil properties.

The overall potential non-carcinogenic risk for children is higher than that for adults in terms of the non-carcinogenic risk due to ingestion of nitrogen (NO3-N, NH4-N) and heavy metals (As, Zn, Fe, Mn) through drinking water. The spatial distribution of high non-carcinogenic risk of shallow groundwater is basically consistent with that of deep groundwater in both pre- and post-monsoon seasons. High non-carcinogenic risk is mainly distributed in the southwestern area and a small local area in the central study area for children and adults in both seasons. The overall potential non-carcinogenic risk (HI) for both children and adults posed by multi-pollutants present an obvious increase from the pre- to post-monsoon season as the results of infiltration of pollutants in the monsoon season. Special attention should be paid to the As since its hazard quotient value exceeds the permissible limit (HQ = 1) in some local areas for both children and adults. Therefore, groundwater should be treated properly with regards to As if used for long-term drinking purposes in the high As content areas.

ACKNOWLEDGEMENTS

This research was supported by the Fundamental Research Funds for the Central Universities (2682019CX14; 2019MS028), the National Basic Resources Survey Program of China (2017FY100405), and China Geological Survey (DD20160238).

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