Journal of Environmental Sciences 19(2007) 50–54
Assessment and mapping of environmental quality in agricultural soils of
Zhejiang Province, China
CHENG Jie-liang1, SHI Zhou1,∗, ZHU You-wei2
1. Institute of Agricultural Remote Sensing and Information System, Zhejiang University, Hangzhou 310029, China.
2. Protection and Monitoring Station of Agricultural Environment, Bureau of Agriculture, Zhejiang Province, Hangzhou 310020, China
Received 14 December 2005; revised 31 March 2006; accepted 11 May 2006
Heavy metal concentrations in agricultural soils of Zhejiang Province were monitored to indicate the status of heavy metal
contamination and assess environmental quality of agricultural soils. A total of 908 soil samples were collected from 38 counties
in Zhejiang Province and eight heavy metal (Cd, Cr, Pb, Hg, Cu, Zn, Ni and As) concentrations had been evaluated in agricultural
soil. It was found 775 samples were unpolluted and 133 samples were slightly polluted and more respectively, that is approximately
14.65% agricultural soil samples had the heavy metal concentration above the threshold level in this province by means of Nemerow’s
synthetical pollution index method according to the second grade of Standards for Soil Environmental Quality of China (GB15618-
1995). Contamination of Cd was the highest, followed by Ni, As and Zn were lower correspondingly. Moreover, Inverse Distance
Weighted (IDW) interpolation method was used to make an assessment map of soil environmental quality based on the Nemerow’s
pollution index and the soil environmental quality was categorized into five grades. Moreover, ten indices were calculated as input
parameters for principal component analysis (PCA) and the principal components (PCs) were created to compare environmental quality
of different soils and regions. The results revealed that environmental quality of tea soils was better than that of paddy soils, vegetable
soils and fruit soils. This study indicated that GIS combined with multivariate statistical approaches proved to be effective and powerful
tool in the mapping of soil contamination distribution and the assessment of soil environmental quality on provincial scale, which is
beneficial to environmental protection and management decision-making by local government.
Key words: agricultural soil; heavy metals; soil environmental quality; Nemerow’s synthetical pollution index; multivariate analysis
As being a kind of non-renewable natural resources and
the foundation of human being’s subsistence and devel-
opment, soil serves many vital functions in our society,
particularly for food production. It is thus extremely im-
Deterioration of environment conditions and increasing
reliance on agrochemicals have led to a growing public
concern over the potential accumulation of heavy metals
and other contaminants in agricultural soils (Wong et al.,
2003; Nicholson et al., 2003). When heavy metals present
high concentration in agricultural soils, they are known
not only to affect the crops output and quality, but also
result in the further deterioration growth, morphology and
metabolism of micro-organisms in soils (Dietrich et al.,
1990; Muller, 1994; Giller et al., 1998), and adversely
affect agricultural production and water quality inevitably,
which could enhance the risk of metal contamination of
food chains (Frangi and Richard, 1997; Younas et al.,
Project supported by the National Natural Science Foundation of China
(No. 40001008) and the Science and Technology Project of Zhejiang
Province (No. 2004C32066). *Corresponding author.
1998; Mclaughlin et al., 1999).
Along with the developed coastal region of eastern
China, such as Zhejiang Province, a consequence of in-
dustrialization and urbanization have caused significant
impacts on the local environment because of lacking pollu-
tion controls. Zhejiang Province is located in the southern
wing of the Yangtze River Delta on the southeastern coast
of China and borders Shanghai City to the north. Zhejiang
is now a province of strong economy with industry as
the guiding sector and a large number of pollutants are
spreaded in the atmosphere: gaseous harmful materials,
solid materials and aerosols which contain organic as well
as inorganic harmful materials, toxic elements and heavy
metals contamination of agricultural soils has become
increasingly serious (Li et al., 1997; Chen et al., 1999).
Since a survey of soil heavy metal contents might sup-
ply some fundamental information for the environmental
planning, extensive investigations of agricultural soils have
been carried out in some countries and regions in recent
years (Elsokkary et al., 1995; Burn et al., 1998; Abollino
et al., 2002; Adamo et al., 2003) and some works (Li et
al., 2001; Wang, 2002; Wang et al., 2003; Zhang and Ke,
2004) also have been carried out to evaluate the heavy
No. 1 Assessment and mapping of environmental quality in agricultural soils of Zhejiang Province, China51
metal contamination of some cities or drainage areas in
China, however, there is a few detailed and systematically
study have been undertaken to investigate the heavy metal
contents in agricultural soil on a provincial scale in China.
The present study was carried out as a part of the agro-
geology environment investigation in Zhejiang Province.
The objectives of this study were to (1) indicate the status
of heavy metal contamination; (2) assess and map the
environmental quality in agricultural soils of Zhejiang
1 Materials and methods
1.1 Soil sampling and analysis
A total of 908 soil samples were collected from 38 coun-
ties in Zhejiang Province (Fig.1). Among these samples,
303 were from fruit land, 261 from paddy field, 136 from
tea garden and 208 from vegetable land, respectively. A
Trimble Pro-XR Global Positioning System (GPS, Trim-
ble, USA), operated in differential mode with real-time
GPS corrections, was used to locate each sampling point
to within ± 5 m. Composite soil samples were taken from
each of these sampling points. Using quincunx-sampling
method, 5 soil cores were collected to a depth of 20 cm in
a 25-m rectangle of each grid node, and then bulked to give
a composite sample.
Soil samples were air-dried at 30°C and sieved through
a 2-mm polyethylene sieve. After digestion with a mixed
acid of aqua fortis, nitric acid (HNO3), fluorin acid (HF)
and chlorine acid (HClO4), heavy metal contents were de-
termined according to the national standard methodologies
(NSPRC, 1995). Concentrations of Cd, Pb, Cu, Cr, Ni and
Zn were determined using an inductively coupled plasma-
mass spectrometry (ICP-MS; POEMS 3, Thermo Electron,
USA). Applying atomic spectro-fluorophotometer (AFS,
XGY-1011A, IGGE, China) to detect the concentrations
of As, Hg. Standard reference material, GSS-1 soil was
obtained from the Institute of Geophysical and Geochem-
ical Prospecting, Department of Geology and Minerals
of China, was used as quality assurance measure for the
analyses of total heavy metals and incorporated during the
Fig. 1 Location map of soil samples in Zhejiang Province.
1.2 Data analysis
Nemerow’s synthetical pollution index was applied to
assess soil environmental quality in previous study (Liu et
al., 2004). In the present study, this method was utilized for
the degree of soil environmental pollution and integrative
assessment of soil environmental quality, the Standards
Soil Environmental Quality (GB15618-1995) was used as
soil quality assessment criteria. Its equation is as follows:
Pn is the Nemerow’s synthetical pollution index, Pi
is the pollution index of the ith heavy metal, Ci is the
measured concentration of the ith heavy metal, Siis the
required standard of the ith heavy metal, ¯Pi and maxPi
is the average and the maximum value of the pollution
indices of all heavy metals respectively.
The Nemerow’s synthetical pollution index Pnfor all the
soil sampling points was calculated to show the relative
magnitudes of soil pollution. Higher value for Pnindicates
more serious pollution. According to GB15618-1995, soil
environmental quality was classified into 5 grades from
Nemerow’s synthetical pollution index. The classification
criterions are presented in Table 1.
Table 1 Classification criterions for polluted index of soil
Slightly polluted domain
Moderately polluted domain
Seriously polluted domain
Inverse distance weighted (IDW) interpolation method
is based on a basic principle of geography, that things close
to one another are more alike. IDW is often used to create
a continuous surface from sampled point values. Using
Spatial Analyst Module of ArcGIS software (ESRI, 2001),
in current study, the assessment map of soil environmental
quality was generated from all sampled points with Ne-
merow’s synthetical pollution index.
Moreover, in order to investigate the soil environmen-
tal quality of different districts and primary elements
in the agricultural soil, all the data were evaluated by
means of principle component analysis (PCA). PCA was
a multivariate analysis technique used to describe the in-
terrelationships among many correlated variables in terms
of a few underlying factors (Werner et al., 2003).
Ten indices, including Pnx, Pnn, Pxx, first quantile (Q1),
third quantile (Q3), 90% quantile (Q0.9), minimum (Min),
maximum (Max), percentage of above the precaution (P1)
52 CHENG Jie-liang et al. Vol. 19
and percentage of above the allowed limits (P2), were cal-
culated respectively as input parameters for PCA method.
Pnxis the average of the Nemerow’s synthetical pollu-
tion index for all assessing samples. Pnnand Pxxare given
by Eq.(3) and Eq.(4), respectively.
where Pnj is the Nemerow’s synthetical pollution index
at the jth sampling point, and Max(Pnj) and¯Pnj is the
maximum and average value of the Nemerow’s synthetical
pollution index for all samples.
Where P is the pollution indices for one heavy metal at
a sampling point (Eq.(2)), m is the number of soil heavy
metal; n is the number of the assessing soil samples.
Q1, Q3and Q0.9are statistical results according to the
Nemerow’s synthetical pollution index of soil samples in
each district. P1 is the percentage of soil samples with
Pn?0.7 and P2is the percentage of soil samples with Pn>1
of the whole assessing samples, respectively. A new set
of uncorrelated variables called the principal components
(PCs) are created from ten above indices using PCA
method to analyze the primary pollutants to soils.
2 Results and discussion
2.1 Heavy metal concentrations in agricultural soils
Descriptive statistics of concentration of eight heavy
metals (Cd, Cr,Pb, Hg, Cu, Zn, Ni and As) are summarized
in Table 2. Based on the Standards for Soil Environmental
Quality of China (NSPRC, 1995), the allowed values for
these heavy metals are listed in Table 2 when soil pH value
was more than 6.5 and less than 7.5, and the average value
for soil pH in this study was 6.78, which just fell in this
scope. As shown in the table, the average concentrations
of Cd, Cr, Pb, Hg, Cu, Zn, Ni and As were all below
the allowed values of above-mentioned standards. With
respect to the total percentage (T1) of above this allowed
limits, contamination of Cd was the highest, which reached
10.72%, followed by Ni, Hg, Pb, Cu and Cr, contamination
of As and Zn was the lowest, which were 1.82% and
1.04%, respectively. Large coefficient of variation (CV) of
Hg, Ni and Cd in all soils, which reached 89.06%, 83.66%
and 80.9% respectively, implied a great heterogeneity
in soils. Otherwise, the variance of Cr was relatively
smoother due to its lowest CV value.
An attempt had been made to compare the content of
heavy metals given by general soil survey of Zhejiang
Province which had been investigated in the 1980s (Table
3), the maximum and minimum values of these eight heavy
metals were higher in the present study. Moreover, the
heavy metal contents, except Hg and As, were generally
above the contents of the survey in the 1980s, which
indicated increased concentrations of these heavy metals
during the past two decades. It was noteworthy that the
maximum of Pb (348.3 mg/kg) and Ni (410.1 mg/kg)
were three times higher than that in the 1980s. The
contamination of Pb probably due to the exhaust emissions
from vehicle, industrial like metal smeltery and wastewater
irrigation, which with a high content of Pb. However,
the high content of Ni might be due to parent rock of
the province consisted of alluvial deposit of the Yangtze
River which contains high Ni only next to the lime rock
(Zhejiang Province of General Survey on Soil, 1994).
2.2 Spatial distribution of heavy metal contamination
in Zhejiang Province
The assessment map of soil environmental quality is
illustrated in Fig.2, which created from the Nemerow’s
synthetical pollution indices of all soil sampling points
using the Inverse Distance Weighted interpolation method.
It should be noticed that the interpolated surface were only
generated in 38 counties where soil sampling points were
collected. As shown in Fig.2, up to 88.96% of the whole
study area belonged to the safety domain, whereas only
0.53% area was moderately polluted and more. Summa-
rized with the whole 908 samples, 503 samples were in the
safety domain in which the soils were considered as unpol-
luted, 272 samples were located in the precaution domain
in which heavy metals were accumulated in agricultural
soils but below the allowed limits, 105 samples were
slightly polluted, 14 samples were moderately polluted and
14 samples were seriously polluted, respectively. In other
words, most of the agricultural soils of Zhejiang Province
was not contaminated with these heavy metals.
2.3 Environmental quality assessment of agricultural
The percentage of the heavy metals above the allowable
limits (T1) in various soil categories were summarized
Table 2 Heavy metal concentrations of agricultural soils in Zhejiang Province (mg/kg)
CV: coefficient variation; T1: the total percentage above allowed values; the letters of A, B, C, D represent paddy field, dry land, agricultural land,
orchard land, respectively.
No. 1Assessment and mapping of environmental quality in agricultural soils of Zhejiang Province, China 53
Table 3 Heavy metal contents of topsoil (0–20 cm) in 1980s (mg/kg)
Heavy metalRange MedianMean SD
in Table 4. T1value in tea soils descended in the order:
Ni>Cr=Cu>Pb>Cd=As>Zn>Hg. Nevertheless, orders of
vegetable soils, paddy soils and fruit soils were: Hg>Cd
Cr and Cd>Pb>Hg>Ni>Cr>As>Zn>Cu, respectively. T1
value of Cd was placed first rank in fruit soils and second
rank in vegetable and paddy soils among the eight metals.
was apparently influenced by human activities, such as
spent litter, Cd-containing phosphorus fertilizers and pesti-
cides, which contain high content of Cd (Chen et al.,1997).
Moreover, ten indices and the PCs scoring of four soil
categories were calculated in Tables 5 and 6. As shown
in the sorting of PCA analysis, environmental quality of
tea soils was better than the other three types of soil,
because majority of the tea soils in Zhejiang Province
was located in mountain area with a good environmental
conditions and lower human impacts. Paddy soils were
worse in environmental quality than others, which might
originate form extensive agricultural practices, such as
applications of pesticides, animal manures and fertilizers.
It was confirmed by P1 value in Table 5, that 65.9%
of paddy soil samples belonged to precaution domain
(0.7<Pn?1.0 ) according to GB15618-1995 (Table 1).
Fig. 2 Assessing map of soil environmental quality of Zhejiang Province.
The agricultural soils in Zhejiang Province had a trend
of increasing heavy metal concentration compared with
previous survey result, which possibly attributed to atmo-
using of fertilizer and pesticide and might be relate to the
parent rock. This research indicated that environmental
quality of agricultural soils in Zhejiang Province had
degenerated compared with that in the 1980s, which would
pollute the food and harm human health to some extent.
By utilizing the Nemerow’s synthetical pollution in-
dex, coupled with Inverse Distance Weighted interpolation
method, the agricultural soil environmental quality was
assessed. It revealed that 775 samples were in the safety
Table 4 Percentage of the allowed limits (T1) for four soil categories
Soil categorySamplesCd (%) Cr (%)Pb (%) Hg (%) Cu (%)Zn (%)Ni (%)As (%)
Table 5 Value of ten indices for PCA evaluation of four soil categories
Table 6 Percentage of above allowed limits for the four soil categories
Z1: scoring of the first principle component ; Z2: scoring of the second principle component; Z3: scoring of the third principle component; Zm: synthetical
scoring of principle component.
54CHENG Jie-liang et al. Vol. 19
domain and 133 samples were slightly polluted and more
respectively, which about 14.65% of soil samples had the
heavy metal concentration above the threshold levels in
whole province, contamination of Cd was the highest,
while the contamination of As and Zn was lower. Accord-
ing to the assessment map of soil environmental quality, up
to 88.96% of the whole study area was belonged to safety
domain, whereas only 0.53% area was moderately polluted
From the results of PCA analysis, it was clearly shown
that lower concentrations of heavy metal in the tea soils
compared with those of the vegetable soils, fruit soils and
paddy soils. It was possibly subjected to the least impact
of anthropogenic sources of heavy metals, furthermore,
higher concentrations of heavy metals in the paddy soils
were strongly influenced by high usage of agrochemicals
and differences in cultivation method (Gimeno-Garcfa et
al., 1996). The results demonstrated that it was necessary
to control heavy metal contamination of agricultural soils,
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