Soil Heavy Metal Contamination and Risk Assessment Aroundthe Fenhe Reservoir, China

Hong Zhang • Guanglei Liu • Wei Shi •

Jinchang Li

Received: 21 November 2013 / Accepted: 21 May 2014

� Springer Science+Business Media New York 2014

Abstract Heavy metal contamination in the soil around a

water source is a particularly serious issue, because these

heavy metals can be transferred into the water source and

can pose significant human health risks through the con-

tamination of drinking water or farmland irrigation water.

In this paper, we collected surface soil samples from the

area surrounding the Fenhe Reservoir. The concentrations

of As, Cd, Cr, Cu, Hg, Ni, and Zn were determined and the

potential ecological risks posed by the heavy metals were

quantitatively evaluated. The primary inputs for As, Ni,

and Zn were natural sources, whereas the other elements

were derived from mainly anthropogenic sources. Hg dis-

plays more serious environmental impacts than the other

heavy metals. The upper reaches of the reservoir, located in

the northwest, display a higher potential ecological risk.

Keywords Heavy metals � Sources identification �Ecological risk � Spatial distribution

The contamination of urban and peri-urban soils by heavy

metals has received increasing public attention and cor-

relative surveys have been carried out in several munici-

palities (Birke and Rauch 2000; Rizo et al. 2013).

However, the contamination pattern in soils of water source

areas, especially in developing countries, remains inade-

quate, which is a particular problem because these heavy

metals can be transferred from the soil into reservoirs,

rivers, or underground water, which will pose a severe

threat to human health if it contaminates drinking water or

farmland irrigation water (Zahra et al. 2014; Suresh et al.

2012). Therefore, fully understanding (quantifying and

mapping) the spatial characteristics of soil contamination

by heavy metals in water source areas will facilitate

accurate risk assessment and planning of mitigation and/or

remediation (Lin 2002).

The Fenhe River, which is the second-largest tributary

of the Yellow River, possesses a length of 716 km and a

watershed area of 39, 000 km2, and flows through the

central and southern areas of the Shanxi Province of China.

The Fenhe Reservoir, located in the upper reaches of the

Fenhe River, is the largest reservoir and drinking water

source area in Shanxi Province. We conducted the present

study to survey soil heavy metal contamination around the

Fenhe Reservoir. The aims of this study are: (1) to deter-

mine and compare the concentrations of heavy metals in

soils surrounding the Fenhe Reservoir with those of other

areas; (2) to identify their possible sources; and (3) to

assess the potential ecological risks posed by these heavy

metals.

Materials and Methods

About 50 soil samples were collected around the Fenhe

Reservoir during April 2011. The detailed sampling loca-

tions are shown in Fig. 1. Each sample was a composite of

soil subsamples taken from the top 20 cm of 10 sites. At

each site, we obtained about 1 kg of soil using a stainless-

steel spade, and stored the samples in sealed polyethylene

bags. Site descriptions were registered at the time of

sampling to record the sample locations, elevations, land

use types and major environmental features.

H. Zhang (&)

College of Environmental Science and Resources, Shanxi

University, Taiyuan 030006, China

e-mail: zhanghong@sxu.edu.cn

H. Zhang � G. Liu � W. Shi � J. Li

Institute of Loess Plateau, Shanxi University, Taiyuan 030006,

China

123

Bull Environ Contam Toxicol

DOI 10.1007/s00128-014-1304-8

Each sample was air-dried, ground with agate mortar and

sieved to 200 mesh size and homogenized with cut sizes of

0.075 mm. All procedures of handling were carried out

without contacting any metals in order to avoid potential

cross-contamination of the samples. For analysis of Cr, Cu,

Zn, Ni, and Pb, samples were pressed into pellets having a

diameter of 3.1 cm under the pressure of 20 ton per cm2 and

then exposed to X-rays from a rhodium tube. The mea-

surements were carried out using a Rigaku ZSX 100e

wavelength dispersive X-ray fluorescence spectrometer. For

analysis of As and Hg, the soil samples were digested with

concentrated HNO3 and HCL in a microwave-accelerated

reaction system and were quantified using Atomic Fluores-

cence Spectrometer. For analysis of Cd, the soil samples

were digested with concentrated HF and H2SO4 in a

microwave-accelerated reaction system and were quantified

using graphite atomic absorption spectrometer.

Appropriate quality assurance procedures and precau-

tions were carried out to ensure reliability of the results.

Double distilled deionized water was used throughout the

study. Reagents blank determinations were used to correct

the instrument readings. Standard reference soil (GSS-

11\10\14) obtained from the China National Center for

Standard Materials were used for validation of the analyt-

ical procedure. Table 1 shows the analytical limits of

detection and relative standard deviation (RSD) of each

heavy metal.

Many factors can influence the concentrations of heavy

metals in soil and their impacts upon ecosystems. Principal

components analysis (PCA) has been widely used to

identify the sources of soil pollutants (Mico et al. 2006;

Gurhan and Semiha 2008). In the present study, we per-

formed PCA using SPSS 13.0 for Windows.

The potential ecological risks posed by the heavy metals

were quantitatively evaluated using Hakanson’s method

(1980; Muge et al. 2013). These risk indices are calculated

as follows:

Eir ¼ Ti

r �Ci

s

Cin

ð1Þ

RI ¼Xn

i¼1

Eir ð2Þ

where Eir is the potential ecological risk index of an indi-

vidual metal i; Tir is the toxic-response index for heavy

metals i, Hakanson (1980) suggested that appropriate Tir

values for As, Cd, Cr, Cu, Hg, Ni, and Zn were 10, 30, 2, 5,

40, 5, and 1, respectively. Cis is the measured concentration

of metal i at sampling sites s, Cin is the background value

(BGV) of heavy metal i in the research area. RI is the

potential ecological risk index that results from the com-

bination of multiple metals. The higher the E and RI are,

the higher the risk is. Table 2 summarizes the potential

ecological risk indices and corresponding risk grades.

Results and Discussion

Table 3 summarizes the results of heavy metal concentra-

tions in soils in the research area. The median was selected

as a representative of central tendency because the data

does not require a normal distribution. We have provided

Fig. 1 Location of the study

area and sampling sites

Table 1 The limits of detection and RSD of each heavy metal

Heavy metal Limits of detection (mg kg-1) RSD (%)

As 0.42 3.09

Cd 0.029 6.64

Cr 5 3.25

Cu 1 5.54

Hg 0.003 1.80

Ni 2 3.73

Zn 2 1.62

Bull Environ Contam Toxicol

123

the Grade I and Grade II values in the Chinese Environ-

mental Quality Standard for Soil as well as the soil BGV

for the Taiyuan Basin in Table 3. In the Chinese standard,

Grade I levels represent the average natural background

levels for uncontaminated soil of China, and Grade II

levels represent the levels at which a pollutant is hazardous

to agricultural production and human health.

The concentrations of heavy metals in the research area

are lower than the Grade I and Grade II criteria, suggesting

that the soils of the research area has not been contami-

nated related to the average natural background levels of

heavy metals in soils of China and were currently not

hazardous to agricultural production and human health.

However, Cr and Hg displayed relatively higher mean

concentrations than the corresponding background levels

for soil in the Taiyuan Basin, suggesting that both elements

were more likely to be affected by anthropogenic sources.

The coefficients of variation (CV) values were all relatively

small for the seven elements, suggesting that these

elements were derived predominantly from natural sources

or from dispersed anthropogenic sources.

In this study, the concentrations of heavy metals of soils

in this research area were in the approximate order of

magnitude when compared with those in other areas of

China (Table 4). The concentrations of heavy metals in

different research areas were various, which may be

attributed to the different natural background and human

activities.

PCA was applied here to identify the sources of soil

pollutants. The results of the efficiency of the method are

indicated in Table 5. It can be seen that the first 4 factors

explain over 86.61 % of the total variation. The first PC,

which explained 37.15 % of the total variance, was

strongly and positively related to As, Ni, and Zn. As, Ni,

and Zn showed significant correlations and their mean

concentrations were comparable to the corresponding

background levels in the research area. Therefore, it seems

reasonable to infer that PC1 is related to natural sources at

Table 2 Indices and grades of

potential ecological riskIndices Low Moderate High Very high Extremely high

E E \ 40 40 B E \ 80 80 B E \ 160 160 B E \ 320 E C 320

RI RI \ 150 150 B RI \ 300 300 B RI \ 600 RI C 600

Table 3 Descriptive statistics of heavy metal concentrations in soils in the research area

Heavy metal Median Minimum Maximum SD CV Grade I Grade II BGV

As 10.7 4.1 12.8 1.3 12.50 15 25 10.2

Cd 0.114 0.050 0.155 0.025 23.36 0.2 0.8 0.1

Cr 75.4 52.2 87.7 5.7 7.57 90 250 65.1

Cu 21.8 14.4 32.9 3.3 14.93 35 100 21.5

Hg 0.041 0.022 0.095 0.017 36.96 0.15 1.5 0.03

Ni 26.6 22.3 33.4 2.5 9.11 40 100 28.2

Zn 60.6 41.0 84.4 6.5 10.64 100 300 61.6

All concentrations were given in unit of mg kg-1 of dry weight

SD standard deviation, CV coefficient of variation (%), Grade I the average BGV of soil heavy metals of China (SEPA 2008), Grade II the value

of soil heavy metals in China for protecting agricultural production and human health (SEPA 2008), BGV background value of soil heavy metals

in the Taiyuan Basin (Wang et al. 2008)

Table 4 Heavy metals

concentrations (mg kg-1) in

different soil samples in China

– Means data not available

Sample site Number As Cd Cr Cu Hg Ni Zn References

Around the Fenhe

Reservoir, Taiyuan

50 10.7 0.114 75.4 21.8 0.041 26.6 60.6 This study

Roadside, Beijing 80 8.1 0.215 61.9 29.7 – 26.7 92.1 Chen et al.

(2010)

Suburban areas, Tianjin 86 9.5 0.49 101 67 0.97 – 100.6 Shi et al.

(2010)

Industrial district,

Shenyang

93 17.56 0.54 65.1 71.1 0.33 – 182.0 Li et al.

(2013)

Bull Environ Contam Toxicol

123

the regional scale. The second PC, which explained

24.59 % of the total variance, demonstrated high positive

factor loadings for Cu and Hg. Previous studies showed

that Cu and Hg are typically anthropogenically influenced

(McMartin et al. 2002). PC3 and PC4 accounted for

13.48 % and 11.39 % of the total variance, and showed

strong positive loadings for Cr and Cd, respectively, which

can be identified as another tracer of anthropogenic pol-

lution sources.

The potential ecological risk factors E for each metal

and the RI for all seven heavy metals combined of the

research area were summarized in Table 6. The results

show that the highest concentrations of Hg present a con-

siderably higher potential ecological risk than any other

elements, and that Cd poses a moderate potential ecologi-

cal risk. In contrast, As, Cr, Cu, Ni, and Zn pose a low

potential ecological risk. The differences result from the

fact that the ‘toxic-response’ factors for Cd and Hg are

higher than those for other elements. On the other hand, Hg

concentrations in soils in the study area are elevated, but

not dramatically; for example, the maximum concentration

of Hg is only 3.2 times the BGV for the study area (and the

ratios are even\1 when compared with the Grade I criteria

in Table 3). Based on the potential ecological risk factors

for all metals combined (RI), the minimum, mean, and

maximum potential ecological risk grades are low, low,

and moderate, respectively, which can be mainly attributed

to the fact that the study area is located far from any

metropolitan areas and does not support any heavy indus-

trial operations.

In order to indicate the spatial distribution of potential

ecological risk of heavy metals in the research area, we

mapped the distribution of RI by using of GIS-based Kri-

ging interpolation methods. The results were shown in

Fig. 2 and suggested that the northwestern part of the study

area exhibits a moderate potential ecological risk, whereas

other areas except local spots present mainly a relatively

low potential ecological risk. This should be a cause for

concern for the local government because the soils in the

area, located in the upper reaches of the Fenhe Reservoir,

can easily contaminate the reservoir through particulate

deposition by wind and precipitation.

The soils surrounding the Fenhe Reservoir are mostly

lightly polluted by heavy metals, since none of the seven

analyzed elements in any of our samples exceeded the

Grade I criteria that represent the natural background levels

for uncontaminated soil in China or the Grade II criteria

that were established to protect agricultural production and

human health. The concentrations of heavy metals in the

research area were in the approximate order of magnitude

comparing with those in other areas of China. The con-

centrations of As, Ni, and Zn were mainly affected by

natural sources and the concentrations of Cd, Cr, Cu, and

Fig. 2 Spatial distribution of RI in soils in the research area

Table 5 PCA results with first 4 factors

Heavy

metals

PC 1

(37.15 %)

PC 2

(24.59 %)

PC 3

(13.48 %)

PC 4

(11.39 %)

As 0.760 -0.379 0.264 0.216

Cd 0.108 -0.059 0.041 0.989

Cr 0.216 -0.029 0.931 0.045

Cu 0.512 0.635 -0.389 0.001

Hg -0.060 0.937 0.047 -0.067

Ni 0.913 0.014 0.027 0.105

Zn 0.815 0.260 0.182 -0.025

Table 6 Potential ecological

risk indices (E) for each metal

and the risk index (RI) for soil

heavy metals in the research

area

Heavy

metals

Toxic-response index

(Tir)

E RI

Min. Mean Max. Min. Mean Max.

As 10 4.07 10.18 12.57 82.69

low

116.35

low

180.51

moderateCd 30 14.91 31.99 46.50

Cr 2 1.50 2.17 2.52

Cu 5 3.34 5.13 7.65

Hg 40 29.33 61.09 126.67

Ni 5 3.96 4.79 5.92

Zn 1 0.67 0.99 1.37

Bull Environ Contam Toxicol

123

Hg were mainly controlled by various anthropogenic

sources. The potential ecological risks posed by Hg were

considerably higher than those for any other elements. The

northwestern parts of the study area are at a moderate

potential ecological risk, based on the multi-metal risk

index (RI). To conclude, the results of our study highlight

the influence of human activities, particularly agricultural

activities, on heavy metal levels in soils surrounding the

Fenhe Reservoir and the potential ecological risks posed by

these pollutants. This may thereby provide a basis for

developing soil quality policies for the region.

Acknowledgments This work was financially supported by the

National Natural Science Foundation of China under Grant 41271513.

References

Birke M, Rauch U (2000) Urban geochemistry: investigations in the

Berlin metropolitan area. Environ Geochem Health 22(3):233–248

Chen X, Xia XH, Zhao Y, Zhang P (2010) Heavy metal concentra-

tions in roadside soils and correlation with urban traffic in

Beijing, China. J Hazard Mater 181:640–646

Gurhan YM, Semiha I (2008) Multivariate analyses to determine the

origin of potentially harmful heavy metals in beach and dune

sediments from Kizkalesi coast, Turkey. Bull Environ Contam

Toxicol 81(1):57–68

Hakanson L (1980) An ecological risk index for aquatic pollution

control: a sedimentological approach. Water Res 14(8):975–1001

Li XY, Liu LJ, Wang YG et al (2013) Heavy metal contamination of

urban soil in an old industrial city in Northeast China. Geoderma

192:50–58

Lin Y (2002) Multivariate geostatistical methods to identify and map

spatial variations of soil heavy metals. Environ Geol 42(1):1–10

McMartin I, Henderson P, Plouffe A, Knight R (2002) Comparison of

Cu–Hg–Ni–Pb concentration in soils adjacent to anthropogenic

point sources: examples from four Canadian sites. Geochem

Explor Environ Anal 2(1):57–73

Mico C, Recatala L, Peris M, Sanchez J (2006) Assessing heavy metal

sources in agricultural soil of an European Mediterranean area

by multivariate analysis. Chemosphere 65(5):863–872

Muge A, Filiz K, Muhammet D, Tolga GL (2013) Heavy metal

concentrations in surficial and core sediments from Izmir bay: an

assessment of contamination and comparison against sediment

quality benchmarks. Bull Environ Contam Toxicol 91(1):69–75

Rizo OD, Morell DF, Lopez JOA et al (2013) Spatial distribution and

contamination assessment of heavy metals in urban topsoils from

Las Tunas city, Cuba. Bull Environ Contam Toxicol 91(1):29–35

SEPA (State Environmental Protection Administration of China)

(2008) Environmental quality standard for soils, GB15618-2008

Shi RG, Lv JG, Cai YM et al (2010) Levels, spatial distribution and

possible sources of heavy metals contamination of suburban soils

in Tianjin, China. Bull Environ Contam Toxicol 85(3):287–290

Suresh G, Sutharsan P, Ramasamy V, Venkatachalapathy R (2012)

Assessment of spatial distribution and potential ecological risk

of the heavy metals in relation to granulometric contents of

Veeranam lake sediments, India. Ecotoxicol Environ Saf

84:117–124

Wang XJ, Lai JQ, Kong H et al (2008) Analysis of the geochemical

distribution characteristics of heavy metal elements in soil in

Taiyuan basin and Taiyuan city (in Chinese). Earth Environ

36(1):72–80

Zahra A, Hashmi MZ, Malik RN, Ahmed Z (2014) Enrichment and

geo-accumulation of heavy metals and risk assessment of

sediments of the Kurang Nallah—feeding tributary of the Rawal

Lake reservoir, Pakistan. Sci Total Environ 470–471:925–933

Bull Environ Contam Toxicol

123