Abstract

Natural and anthropogenic nitrate (NO3-N), nitrite (NO2-N) and ammonia (NH4-N) in groundwater represents vital environmental and health concern issue globally. Here, we present data and discuss sources of nitrogen compounds in the groundwater that accounts for two-thirds of the total water supply of the Haihe River Plain with a population of over 100 million. The spatial and temporal distribution of the nitrogen compounds (NO3-N, NO2-N, NH4-N) in the groundwater are linked to a variety of sources, such as fertilizers, domestic sewages, industrial wastewater and precipitation. About 12.64%, 53.90% and 16.73% of the investigated groundwater wells in the Haihe River Plain have NO3-N, NO2-N and NH4-N concentrations above permissible values for drinking water, respectively. Comprehensive actions such as changing farming methods, applying fertilizer at suitable times and appropriate irrigation pattern for the Haihe River Plain are required to reduce the nitrogen pollution in the future.

INTRODUCTION

Groundwater pollution is a growing concern everywhere in the world, especially from intensive human activities, including agriculture (Chen et al. 2007; Landon et al. 2011; Bonton et al. 2012) and industrial production (Farshad & Imandel 2003; Zakhem & Hafez 2015). The new established sub-capital of China (Xiong'an New Area), located in the Haihe River Plain (Figure 1). The annual average groundwater supply is about 20 billion m3, accounting for two-thirds of the total water supply. A large portion of groundwater is utilized in the Haihe River Plain for grain production with output reaching 109,370,000 tons in 2015, accounting for 22% of China.

Figure 1

Location map of the Haihe River Plain and samples.

Figure 1

Location map of the Haihe River Plain and samples.

Several studies reported groundwater nitrogen pollution which may threaten drinking water resources in the Haihe River Plain. Pollution sources of nitrogen compounds included septic waste (Gao et al. 2011), organic matter, animal manure and chemical fertilizer (Fang et al. 2015). Past research lacks many aspects in terms of spatial coverage, choice of pollution indices, effects on human health, comprehensive analysis (NO3-N, NO2-N, NH4-N) and possible sources of pollutants. To overcome some of these problems, a large spatial coverage of the Haihe River Plain was achieved here through seasonal analyses of groundwater from a large number of actively used wells in 2014. The data are used to provide information regarding the distribution levels, sources and environmental and health hazard impacts of the nitrogen compounds in the region.

MATERIALS AND METHODS

The Haihe River Plain (112°30′-119°30′ E, 34°46′-40°25′ N) has a total surface area of 136,189 km2 (Figure 1). The unique geology and geomorphology play an important role in controlling the movement and distribution of groundwater (Figure S1). The Quaternary deposits consist of sand, gravel and clay with the amount of gravel fraction decreasing from the Piedmont Plain to the Central Plains and into the Coastal Plain (Figure S1). The hydrogeological conditions in the region are strongly controlled by the geological elements where the groundwater level is lower in the middle and eastern parts (Figure S2). (Figures S1 and S2 are available with the online version of this paper.)

Groundwater samples were collected from 269 wells at a quarterly period in 2014. The sampling was performed after letting the well pump for a period of at least 1 h to avoid a stagnation effect. Total dissolved solids (TDS) and pH were determined in the field using a calibrated multi-parameter water quality detector (YSI6820). 2.5 L of water was collected from each well in tightly capped high-density polyethylene (HDPE) bottles. These samples were analysed for NO3-N, NO2-N, NH4-N, and MnO4 by continuous flowing analysis (AA3) and Cl by ion chromatograph (ICS-1100). The analyses were done following protocols and testing methods approved for industrial standards for quality control. For all water samples, ions equilibrium balance errors (IBE) were <10%, and most of them were <5%. The geostatistics module in ArcGIS10.2 was used for spatial analysis (Javad et al. 2016).

RESULTS AND DISCUSSION

Descriptive statistics

Data on TDS, Cl and MnO4 were used here to provide information about water salinity, seawater intrusion and oxidation potential of the groundwater. The complete seasonal results of the groundwater analyses are presented in Table S1. A summary of the data is presented in Table 1 which indicates TDS range of 168–4,775 mg/L, and places the groundwater in the fresh to brackish water. Using annual average distribution pattern, a few parts of the region show fresh drinkable water (TDS < 300 mg/L) while most of the central and coastal parts indicate rather high salinity water (Figure 2). The groundwater TDS seems also to depend on the seasons (Qin et al. 2013) where the northward extension of high salinity groundwater during winter moves further south and to the central part during spring through autumn (Figure S3). Variability in the Cl concentrations is rather large stretching from about 2 mg/L to 3,480 mg/L and the concentrations increase seawards (Figure 2 and Table 1). The seasonal Cl concentrations indicate some reduction in the high concentration zone during winter (Figure S4). The MnO4 distribution (0.5–51 mg/L) seems different from the other compounds (Figure 2) where high concentration occurs near to the seaside and is maintained through spring and autumn (Figure S5). (Table S1 and Figures S3-S5 are available with the online version of this paper.)

Table 1

Summary data of the chemical parameters in the investigated groundwater (mg/L)

TDSClMnO4NO3-NNO2-NNH4-N
Min 168 1.9 0.5 0.08 0.001 0.01 
Max 4,775 3,480 51 301.16 6.65 10.88 
Average 168 272.5 3.6 8.9 0.08 0.17 
Permissible limit 1,000a 250a 3a 20b 0.02b 0.2b 
TDSClMnO4NO3-NNO2-NNH4-N
Min 168 1.9 0.5 0.08 0.001 0.01 
Max 4,775 3,480 51 301.16 6.65 10.88 
Average 168 272.5 3.6 8.9 0.08 0.17 
Permissible limit 1,000a 250a 3a 20b 0.02b 0.2b 

aThe permissible limit is for drinking water according the World Health Organization (WHO 2011).

bThe permissible value is for drinking water according to the General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China.

Figure 2

Annual average concentrations of TDS, Cl and MnO4 in the investigated groundwater (seasonal data in Figures S4–S6, available with the online version of this paper).

Figure 2

Annual average concentrations of TDS, Cl and MnO4 in the investigated groundwater (seasonal data in Figures S4–S6, available with the online version of this paper).

The variability in the NO3-N is at 0.8–301 mg/L and that of NO2-N is at 0.001–6.65 mg/L while the NH4-N occurs at concentration of 0.1–10.9 mg/L (Figure 3 and Table 1). The seasonal distribution in these compounds seems unique to each of them with patches that contain high concentration seawards and at the southern tip of the region for the NO3-N (Figure S6). The NO2-N seasonal changes appear retaining high concentrations during winter compared to other seasons (Figure S7). The NH4-N concentrations show occurrence of high values during all seasons with slight difference in the distribution patterns (Figure S8). (Figures S6-S8 are available online.)

Figure 3

Annual average concentrations of dissolved nitrogen compounds in the investigated groundwater (seasonal data in Figures S7–S9, available with the online version of this paper).

Figure 3

Annual average concentrations of dissolved nitrogen compounds in the investigated groundwater (seasonal data in Figures S7–S9, available with the online version of this paper).

Liner correlation matrix of the whole data set (Table S2) shows that the most significant correlation for the nitrates is between NO3-N and MnO4, with R value = 0.63. The correlation coefficient between NO3-N and Cl is R = 0.46. The rest of the correlation values are <0.4. All of the p values are <0.01. The correlation coefficients between the different parameters and nitrogen compounds did not change significantly when each season data is treated separately (Table S2). Frequency histograms and probability plots (Figure S9) indicate mainly non-normal distribution of the nitrogen compounds and the rather limited range of significance within the t-test confidence range of >95%. (Table S2 and Figure S9 are available online.)

Variability in the distribution of the analyzed nitrogen compounds of the groundwater reflects complex influence of spatial and temporal factors that are related to sources of nitrogen, aquifer characteristics, landscape features, and seasons as discussed below.

Sources of nitrogen compounds

The Haihe River Plain represents the main production base of wheat and maize in China (Zhao et al. 2009) and high nitrogen chemical fertilizers are used. Although not a perfect match, the distribution patterns of nitrogen compounds (Figure 3) and of agricultural activity in the region (Figure 4) suggest potential effect of the fertilizers. Assuming that the nitrogen fertilizer was entirely converted to ammonia nitrogen, excluding volatile loss (Wang et al. 2012), then the nitrogen concentration in the groundwater can be calculated using follow formula (Lu et al. 2012): 
formula
(1)
where Nacf is agricultural chemical fertilizer nitrogen, F is amount of used fertilizer, Cacf is fertilizer nitrogen content, U is nitrogen fertilizer utilization rate, V is nitrogen volatilization rate, I is infiltration rate and α is the ratio of nitrogen infiltrated into the groundwater through the aeration zone.
Figure 4

Spatial data for the distribution of agricultural land and industrial units in the investigated area.

Figure 4

Spatial data for the distribution of agricultural land and industrial units in the investigated area.

The amount of chemical fertilizer used in the Haihe River Plain during 2015 at 837.7 × 104 t (Zhao et al. 2015) with an average nitrogen content of 35% (Gao et al. 2009) was considered. Estimates of nitrogen fertilizer utilization and nitrogen volatilization rates were approximately 40% (Ju et al. 2009) and 36% (Wang et al. 2014a, 2014b), respectively. Variation range in infiltration rate was estimated to between 0.06 and 0.3 and is considered here at 0.18 (Cao et al. 2013). The amount of nitrogen produced from the fertilizer application during 2015 is estimated at 12.6 × 104t. When the nitrogen entered the groundwater through the aeration zone, part of it will be adsorbed to particles and according to studies carried out in the Haihe Plain, about 20% of the nitrogen may infiltrate into the groundwater (Min et al. 2015). Therefore, the amount of nitrogen in groundwater sourced from fertilizer is estimated at 2.52 × 104 t in 2015. The amount of chemical fertilizer applied by most farmers in the Haihe River Plain exceeds 200 kg/hm2 and may reach 500 kg/hm2 in a winter wheat and summer maize rotation system (Zhao et al. 2015). An estimate of ratio for the nitrogen, phosphorus and potassium fertilizers is about 5:3:1. The high amounts of nitrogen fertilizers far exceeded the nutrient consumption of crops in the same season. In addition, the loss of farmland nitrate nitrogen with runoff was relatively small (Zhou et al. 2011) that results in increasing content of nitrate and consequently infiltration into groundwater.

Haihe River Plain has 411 industrial enterprises including paper, leather, chemical fertilizer, agricultural and sideline products. The pollutants discharged from these enterprises mainly include organic matter, ammonia nitrogen and total nitrogen. Although the spatial distribution of these industrial pollution sources cover most of the investigated region (Figure 4), there seems some match with respect to the nitrogen compounds in the groundwater (Figure 3). In particular, the high NH4-N and NO3-N in the south most tip of the region agrees with high numbers of the industrial enterprises there. In order to estimate the amount of nitrogen discharged from the industrial wastewater, we used only the data from wastewater treatment plants (WWTPs) discharges and applying the nitrogen removal rate Equation (2) below (Lu et al. 2012). 
formula
(2)
where Niww is industrial wastewater nitrogen concentration, W is industrial wastewater nitrogen amount before treatment, R is the removal efficiency of nitrogen after treatment. The amount of nitrogen emission from the industrial enterprises in the Haihe River Plain is estimated at approximately 5.2 × 104t in 2014 (China Environmental Statistics Yearbook 2015). A modified anaerobic-anoxic-oxic (A2/O) process was adopted for nitrogen removal from WWTPs in the study area that resulted in 80.7% removal efficiency (R) of nitrogen according to the pollution census (Qiu et al. 2010). Consequently, the amount of nitrogen emitted from industrial wastewater is estimated at 0.18 × 104t y−1 using the equation above, which is about 70 times less than what is produced from the fertilizers. The nitrogen was released into the river or in the wild and infiltration ratio of 20% reaching the groundwater was estimated and results in 0.036 × 104t of nitrogen in 2015 from industrial wastewater.
The nitrogen discharge from the domestic sewages was estimated as the product of both urban and rural population average nitrogen consumption per capita. Sewage from the urban domestic treatment network are discharged into rivers and fields after treatment. Rural domestic sewage is often directly discharged without treatment. The amount of nitrogen discharge from domestic sewage is estimated using a combination of both population segments (urban and rural) following Equation (3) (Lu et al. 2012): 
formula
(3)
where Nds is domestic sewage nitrogen, Purban is urban population, Durban is nitrogen emission per capita by urban inhabitants, Rr is nitrogen removal rate, Prural is rural population, Drural is nitrogen consumption per capita in rural, M is the proportion of nitrogen in rural manure to farmland. The nitrogen emission per capita by urban inhabitants of China was approximately 4.77 kg y−1 (Wei et al. 2008). The nitrogen removal rate by the various sewage treatment systems in China ranged from 40 to 70% (Qiu et al. 2010) and we adopted an average reported value for nitrogen removal rate of 60%. The nitrogen consumption per capita in rural China is approximated at 4.31 kg y−1 (Wei et al. 2008) and the proportion of nitrogen in rural manure to farmland is about 60% (Wei et al. 2008). These values resulted in an estimated amount of nitrogen discharge from domestic sewages at 3.5 × 104t y−1, which is about 4 times less than that produced from the agricultural chemical fertilizer. Using a 20% infiltrated nitrogen into groundwater, the amount of 0.7 × 104t nitrogen in 2015 reached the groundwater from domestic sewage.

In summary, among the anthropogenic nitrogen sources (agricultural chemical fertilizer, industrial wastewater and domestic sewage), the application of agricultural chemical fertilizer represents the most significant source of nitrogen pollution in the Haihe River Plain (Figure 5). Another signature of the fertilizers-induced nitrogen is the source apportion of the different nitrogen compounds as illustrated by the frequency and probability diagrams (Figure S9). The data indicate rather non-normal distribution for nitrogen compounds that implies un-equilibrium conditions created by the variable sources (anthropogenic and natural). Factor analysis was used here to define correlated grouping of comparable variables, natural and/or anthropogenic (Figure S10, available online). Factor loading is used to show which variables load into each factor (Love et al. 2004). Despite the relatively far from normal distribution shown by the data, factor analysis can indicate approximate relationship between the parameters. The data reveal comparable trends for TDS and Cl thus suggest linking to mainly common sources, which can be mainly a mixture of natural (aquifer and seawater) and anthropogenic ones. The nitrogen compounds and MnO4 show attributes of load and trends supporting source apportions that is likely dominated by anthropogenic additives such as fertilizers. The rather separated trends of NH4-N and NO3-N (Figure S10) suggest supply of these nitrogen forms under different temporal and/or chemical conditions. The relatively higher amount of NO3-N in the seasonal pattern (Figure S6) compared to NH4-N in the southern part of the region points out differential nitrogen compounds discharge from industrial wastewater as the cause of the rather separate trend in the factor analysis data (Figure S10).

Figure 5

Estimated total amounts of nitrogen provide to the groundwater by the different anthropogenic practices and precipitation.

Figure 5

Estimated total amounts of nitrogen provide to the groundwater by the different anthropogenic practices and precipitation.

Another mixed natural and anthropogenic source of nitrogen is from precipitation. The concentration of nitrogen oxides in North China, including Haihe River Plain is relatively high compared to the global distribution, and is still increasing rapidly (Richter et al. 2005). The nitrogen annual deposition rate in the Haihe River Plain was estimated at about 4,700 kg N km−2 (Gao et al. 2014). Then, the atmospheric nitrogen contribution to groundwater is estimated as (Lu et al. 2012): 
formula
(4)
where Ndep is atmospheric nitrogen deposition, A is area of Haihe River Plain, I is infiltration rate and α is the ratio of nitrogen infiltrated into the groundwater through the aeration zone. The estimate results in about 0.16 × 104t of nitrogen from precipitation which is comparable to that supplied by domestic water, but still about one-quarter of the fertilizers portion polluting the groundwater (Figure 5).

Regional comparison

In most areas nitrogen fertilizer and household livestock or poultry appear to be the most common pollution source (Zhao et al. 2008). Nitrate concentration in the Hetao Irrigation District shows much higher NO3-N in the fertilized compared to the non-fertilized area (Feng et al. 2003). The groundwater NO3-N content was different among different land use types in the Chao Lake watershed, Anhui province. This pattern was proven to be related to effects of seasons and amount of fertilizer applied (Wang et al. 2014a, 2014b). In the central Sichuan basin, NO3-N concentration was greatest in the rainy season (Chen et al. 2006) which was likely related to that fertilizer's nitrogen stored in the soil infiltrates with the rain into the groundwater. The urbanization rate and sewage treatment rate in the study area were higher than other parts of China (China Statistics Yearbook 2015), leading to a possible less impact of domestic sewage on the groundwater in the Haihe River Plain (Figure S11, available online).

The permissible limits of nitrogen and other compounds in drinking water set by the Chinese Quality Supervision and the World Health Organization (WHO 2011) are shown in Table 1. There are 12.64%, 53.90% and 16.73% wells in the Haihe River Plain, showing values above the permissible values of NO3-N, NO2-N and NH4-N, respectively. The relatively greater than permissible values of NO2-N (>50%) in the groundwater suggest that many of the wells produce water which is not suitable for direct drinking.

CONCLUSION

The results presented here indicate that nitrogen compounds, NO3-N, NO2-N and NH4-N, in the groundwater of the Haihe River Plain were mainly derived from excessive use of fertilizers during agricultural production. The excessive concentration of NO2-N was the highest, which indicates that the Haihe River Plain groundwater nitrogen pollution is still ongoing. The Xiong'an Area, the sub-capital of China, is presently located in zones where the level of permissible limits for nitrogen compounds has been exceeded. Remediation actions, such as changing farming methods, applying fertilizer at suitable times and appropriate irrigation pattern, will result in reducing infiltration of the nitrogen compounds into the groundwater and thus create a more sustainable and less polluted environment.

ACKNOWLEDGEMENTS

This work was supported by the Public Welfare Industry Research Funds (Grant No. 201501008), Ministry of Water Resources of People's Republic of China.

REFERENCES

REFERENCES
Bonton
A.
,
Bouchard
C.
,
Rouleau
A.
,
Rodriguez
M. J.
&
Therrien
R.
2012
Calibration and validation of an integrated nitrate transport model within a well capture zone
.
Journal of Contaminant Hydrology
128
(
1–4
),
1
18
.
Cao
G.
,
Zheng
C.
,
Scanlon
B. R.
,
Liu
J.
&
Li
W.
2013
Use of flow modeling to assess sustainability of groundwater resources in the North China Plain
.
Water Resources Research
49
(
1
),
159
175
.
Chen
K. L.
,
Zhu
X. D.
,
Zhu
B.
,
Wang
X. H.
&
Cai
B. C.
2006
Temporal and spatial variation of NO3-N pollution in groundwater in small watershed of central Sichuan Basin
.
Journal of Agro-Environment Science
25
(
4
),
1060
1064
(in Chinese)
.
Chen
J.
,
Taniguchi
M.
,
Liu
G.
,
Miyaoka
K.
,
Onodera
S. I.
&
Tokunaga
T.
2007
Nitrate pollution of groundwater in the Yellow River delta, China
.
Hydrogeology Journal
15
(
8
),
1605
1614
.
Fang
J. J.
,
Zhou
A. G.
,
Ma
C. M.
,
Liu
C. F.
&
Gan
Y. Q.
2015
Evaluation of nitrate source in groundwater of southern part of North China Plain based on multi-isotope
.
Journal of Central South University
22
(
2
),
610
618
.
Farshad
A. A.
&
Imandel
K.
2003
An assessment of groundwater nitrate and nitrite levels in the industrial sites in the west of Tehran
.
Journal of School of Public Health & Institute of Public Health Research
1
(
2
),
109
118
.
Feng
Z.
,
Wang
X.
,
Feng
Z.
,
Liu
H.
&
Li
Y.
2003
Influence of autumn irrigation on soil N leaching loss of different farmlands in Hetao irrigation district, China
.
Acta Ecologica Sinica
23
(
10
),
2027
2032
.
Gao
W.
,
Jin
J. Y.
,
He
P.
,
Li
S. T.
,
Zhu
J. H.
&
Li
M. Y.
2009
Optimum fertilization effect on maize yield, nutrient uptake, and utilization in Northern China
.
Better Crops with Plant Food
93
(
2
),
18
20
.
Gao
T.
,
Pang
H.
,
Zhang
J.
,
Zhang
H.
&
Zhou
J.
2011
Migration and transformation rule of nitrogen in vadose zone and groundwater: a case of Hebei Plain
.
Environmental Microbiology
11
(
10
),
2649
2659
.
Gao
W.
,
Howarth
R. W.
,
Hong
B.
,
Swaney
D. P.
&
Guo
H. C.
2014
Estimating net anthropogenic nitrogen inputs (NANI) in the Lake Dianchi basin of China
.
Biogeosciences Discussions
11
(
3
),
4577
4586
.
Javad
S.
,
Leila
E.
&
Mahmood
S.
2016
Spatial variation modeling of groundwater electrical conductivity using geostatistics and GIS
.
Modeling Earth Systems and Environment
2016
(
2
),
1
10
.
Ju
X. T.
,
Xing
G. X.
,
Chen
X. P.
,
Zhang
S. L.
,
Zhang
L. J.
&
Liu
X. J.
2009
Reducing environmental risk by improving n management in intensive Chinese agricultural systems
.
Proceedings of the National Academy of Sciences of the United States of America
106
(
9
),
1
6
.
Lu
Y.
,
He
J. T.
,
Wang
J. J.
,
Liu
L. Y.
&
Zhang
X. L.
2012
Groundwater pollution sources identification and grading in Beijing Plain
.
Environmental Science
33
(
5
),
1526
1531
.
Chinese
.
Love
D.
,
Hallbauer
D.
,
Amos
A.
&
Hranova
R.
2004
Factor analysis as a tool in groundwater quality management: two southern African case studies
.
Physics & Chemistry of the Earth Parts A/B/C
29
(
15–18
),
1135
1143
.
National Bureau of Statistics of the People's Republic of China
2015
China Environmental Statistics Yearbook 2015
.
China Statistics Press
,
Beijing
,
China
.
National Bureau of Statistics of the People's Republic of China
2015
China Statistics Yearbook 2015
.
China Statistics Press
,
Beijing
,
China
.
Qin
R. G.
,
Wu
Y. Q.
,
Xu
Z. G.
,
Xie
D.
&
Zhang
C.
2013
Assessing the Impact of Natural and Anthropogenic Activities on Groundwater Quality in Coastal Alluvial Aquifers of the Lower Liaohe River Plain, NE China
.
Qiu
Y.
,
Shi
H.
&
He
M.
2010
Nitrogen and phosphorous removal in municipal wastewater treatment plants in China: a review
.
International Journal of Chemical Engineering
2010
,
1
10
.
Richter
A.
,
Burrows
J. P.
,
Nüss
H.
,
Granier
C.
&
Niemeier
U.
2005
Increase in tropospheric nitrogen dioxide over China observed from space
.
Nature
437
(
7055
),
129
132
.
Wang
J.
,
He
J. T.
,
Liu
Y. M.
&
Jiang
L.
2014a
Multivariate statistical analysis for characteristics of reclaimed water quality in reception basin of Chaobai River
.
Environmental Science & Technology
37
(
6
),
171
177
.
Wang
Q. S.
,
Gu
Y.
&
Sun
D. B.
2014b
Spatial and seasonal variations of nitrate-N concentration in groundwater within Chao Lake watershed
.
Acta Ecologica Sinica
34
(
15
),
4372
4379
.
Wei
J.
,
Ma
L.
,
Lu
G.
,
Ma
W. Q.
,
Li
J. H.
&
Zhao
L.
2008
The influence of urbanization on nitrogen flow and recycling utilization in food consumption system of China
.
Acta Ecologica Sinica
28
(
3
),
1016
1025
(in Chinese)
.
World Health Organization (WHO)
2011
Guidelines for Drinking-Water Quality
, 4th edn.
WHO Press, Geneva, Switzerland
, p.
541
.
Zhao
X. F.
,
Yang
L.
,
Shi
Q.
,
Ma
Y.
,
Zhang
Y.
&
Chen
L.
2008
Nitrate pollution in groundwater for drinking and its affecting factors in Hailun, northeast China
.
Environmental Science
1
(
11
),
2993
2998
.
Zhao
R. F.
,
Chen
X. P.
&
Zhang
F. S.
2009
Nitrogen cycling and balance in winter-wheat-summer-maize rotation system in northern China plain
.
Acta Pedologica Sinica
46
(
4
),
684
697
.
Zhao
L.
,
Li
Y.
,
Jiang
F.
,
Wang
H.
,
Ren
S.
&
Liu
Y.
2015
Comparative advantage for the areas irrigated with underground blue water in North China Plain
.
Water Policy
17
(
6
),
114
126
.

Supplementary data