Accumulation and Distribution of Heavy Metals in agricultural soils, potential influe
Accumulation and Distribution of Heavy Metals in agricultural soils, 1
potential influenced by long-term Wastewater irrigation: A case
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study in Fangshan, Beijing
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HAN Ping a,b, WANG Ji-hua※a, XIAO Yuan-feng, PAN Li-gang a, MA Zhi-hong a , LU An-xiang a,
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(a Beijing Research Center for Agrifood Testing and Farmland Monitoring, Beijing 100097, P. R. China;
b College of agriculture and biotechnology, China Agricultural University, Beijing 100193, P. R .China)
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Abstract
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Concentration of 7 heavy metals in 269 topsoil samples were determined which collected from Shilou town of 9
Fangshan district in Beijing, and the data was analyzed by the single factor index and the Nemerow index for the 10
soil environment quality evaluation. The mean concentration of the heavy metals were 8.24 ± 1.42, 0.209 ± 0.07, 11
62.99 ±8.89, 0.133 ± 0.11, 25.29 ± 5.02, 23.91 ± 5.72 and 86.29 ± 28.13 mg kg-1 for As, Cd, Cr, Hg, Cu, Pb, and 12
Zn, respectively. Average concentration of As, Cd, Cr, Cu and Zn exceeded the background value of Beijing area.
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It was found that all heavy metals were not in normal distribution. The soil environment quality was evaluated by 14
single factor pollution index and Nemerow index of heavy metals. The order of single factor index was Cd, Zn, Hg, 15
Cu, Cr, Pb, As in decreasing. Average Nemerow index of soil was 0.918. This value was reached to the grade Ⅲ16
standard of soil environmental quality assessment classification.
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Keywords: Agricultural soil, Heavy metals, Distribution, Evaluation, Shilou town
Introduction
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Heavy metals accumulation in agricultural soils has become an important concern throughout the
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word due to the potential health impacts of consuming contaminated produce. Otherwise, soil 21
heavy metals have been a very useful indicator of environmental quality and been the subject of 22
much attention because of their peculiar characteristics (Yang, Mao et al. 2009). Human activities 23
such as industrial production, mining, transportation, wastewater irrigation, application of organic 24
fertilizer, chemical fertilizer and pesticides are potential source for heavy metals to enter agricultural soils (Yang QW, 2004; V outsa D, 1996; Li B, 2005; Yang J, 2005; Nicholson FA,
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2003). With the long-term application of wastewater to field, some heavy metals in soil have been accumulated (Xue ZJ, 2012). Previous studies have confirmed that wastewater irrigation is an
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important factor of the obvious accumulation of heavy metals in agricultural soils (Hu K L, et al., 29
2004; W.H. Liu, et al., 2005; Sardar khan, et al., 2008; K.K. Tiwari et al., 2011). Furthermore,
crops and vegetables can take up heavy metals by absorption from these contaminated soils.
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Heavy metals pollution in agricultural soil has serious negative influence on human health due to
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ingestion of food grain grown in contaminated soils (Khan et al., 2008; Zhu Y E et al., 2011).
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Heavy metals in agricultural soil of Beijing had indicated obvious accumulative trends (Li X X,
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et al., 2006,; Zheng Y M, et al., 2008; Huo X N, et al., 2009; Lu A X, et al., 2011). Fangshan
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district is an important agricultural products base of Beijing. There are several rivers run through
this district and these rivers were main water source of irrigation in the past. Dashi, Zhoukoudian, 36
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and Mapaoquan rivers flow across the Shilou town of Fangshan. In 1970s, industry wastewater
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and life sewage discharged into the rivers which brought serious pollution. The wastewater
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irrigation lasted approximately 20 years. The present study was selected in this agriculture field,
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which was a representative agricultural area of wastewater irrigation. The main objective of
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present studies is to investigate the accumulation and distribution of soil heavy metals in this area,
and evaluate the impact of long-term wastewater irrigation on accumulation of heavy metals in
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soil.
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Materials and Methods
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Study area
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The study was conducted in Shilou town of Fangshan district. Shilou town is located in southwest
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Beijing. It has a total area of 42.5 km2 which includes 22.65 km2 agricultural lands. Several rivers
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flow across the town, including Dashi, Zhoukoudian, and Mapaoquan rivers. The mean annual
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precipitation in the area is 655 mm with an uneven temporal distribution, of which 85% is
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concentrated during May and August each year. The region is classified as a warm-temperate and
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semi-humid zone with a continental monsoon climate. The main crops are winter wheat and maize
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in the town.
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Soil sampling and chemical analysis
A total of 269 topsoil samples (0-20cm depth) were collected from the agricultural area of Shilou
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town in September 2010 (Fig. 1). The distribution and number of soil sampling sites were
determined based on land use patterns and plots area. An intensive investigation was conducted
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in the area alongside rivers. The soil sampling sites were mainly distributed in the fields which
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planted wheat and corn. The location of sampling sites were recorded by global positioning
system (GPS). 60 61
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63 Fig. 1 Distribution of samples sites in study area
64 Each soil sample comprised five sub-samples obtained randomly from a 10 m × 10 m grid in 65 each sampling point using a wood spade. Approximately 1.0 kg of the soil samples were taken and 66 mixed thoroughly. The soil samples were air-dried and then passed through a 2.0 mm sieve, and 67 then digested with HNO 3, HCl, and H 2O 2 (USEPA, 1996). Copper, lead, zinc and chromium 68 concentrations were analyzed by a flame atomic absorption spectroscopy (FAAS). Cadmium 69 concentrations were analyzed using graphite furnace AAS. The samples were digested with 70 HNO 3:HCl (10 ml, 1:1 v/v) at 100 °C for 2 h (Lacerda et al., 2004). The total concentrations of As 71 and Hg were determined by atomic fluorescence spectrometry (Titan AFS 830, China). Standard 72 reference material (GSS-1 soil) obtained from Center of National Standard Reference Material of 73 China, was used as quality assurance and quality control (QA/QC) procedures. Triplicates were 74 made for all samples. 75 Statistical treatment
76 Descriptive statistical, Shapiro-Wilk test, partial correlation analysis, cluster analysis (CA) and 77 Principal component analysis (PCA) were carried out using SPSS software. A Shapiro-Wilk test 78 was employed for the distribution test of soil heavy metals. PCA and CA was used to interpret the
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Dashi River
Rivers
Agricultural area
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Soil sampling sites Beijing
Zhoukoudian River
Mapaoquan River
relations between heavy metals in geochemical processes. Geochemical maps of heavy metals
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were obtained using the extension of geostatistical analyst of geography information system (GIS) 82
software (Arc GIS, version 9.3).
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Results and Discussion
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Heavy metal concentrations in agricultural soils
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The descriptive statistics of the soil heavy metals in the agricultural soils of Shilou town were 87
presented in Table 2. The mean values of the heavy metals were 8.24 ± 1.42, 0.209 ± 0.07, 62.99 ±8.89, 0.133 ± 0.11, 25.29 ± 5.02, 23.91 ± 5.72 and 86.29 ± 28.13 mg kg-1 for As, Cd, Cr, Hg, Cu,
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Pb, and Zn, respectively. The application of the S-W test confirmed that all heavy metals contents 90
in the soils were not normally distributed.
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With an exception of soil Pb and Hg, the mean concentration of all the heavy metals exceeded 92
Beijing area background value, as shown by Chen et al (Chen T B, 2004). The mean concentration 93
of Hg also exceeded China background value (CNEMC, 1990). This result suggested soils of the 94
study area had a slight contamination of heavy metals. According to the Chinese Environmental 95
Quality Standard for Soils (State Environmental Protection Administration of China, 1995), the 96
Class 1 values of heavy metal concentrations in soil for agricultural products and human heath are 97
15, 0.2, 90, 0.15, 35, 35, and 100 mg kg-1 for As, Cd, Cr, Hg, Cu, Pb, and Zn, respectively, and the 98
Class 2 values of heavy metal concentrations in soil for agricultural products and human heath are 99
25, 0.6, 250, 1.0, 100, 350, and 300 mg kg-1 for As, Cd, Cr, Cu, Hg, Pb, and Zn, respectively. Only 100
the mean concentration of Cd exceeded Class 1 of environmental standard. Maximum 101
concentration of all heavy metals were lower than Class 2 of environmental standard. The 102
maximum concentration of Zn was 296.1 mg kg-1, which was closed to Class 2 of environmental 103
standard of Zn.
The coefficients of variation (CV) values for all the soil heavy metals were between 14.1 and 104
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82.7, belonged to medium variation. The CV value was least for soil Cr, which showed that the
soil Cr was relatively homogeneous across the study area. The high coefficient of variation of Hg 106
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concentration accounted for the strong variability.
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Table 2 Descriptive statistics of soil heavy metals in Shilou town a (n=269) 110
Metal Concentrations (mg kg-1)
CV(%) Skewness Kurtosis S-W
Background
value b
(mg kg-1)
Environmental
Standard c
(mg kg-1) Range Mean S.D. Class1 Class2
As 4.64~12.20 8.24 1.42 17.2 -0.478 0.191 0.001 7.81 ± 3.22 15 25 Cd 0.083~0.489 0.209 0.07 32.5 0.444 0.595 0.000 0.119 ± 0.112 0.2 0.6 Cr 29.8~112.7 62.99 8.89 14.1 3.666 0.758 0.000 29.8 ± 9.29 90 250 Hg 0.014~0.744 0.133 0.11 82.7 10.783 2.987 0.000 0.080 0.15 1.0 Cu 18.8~62.4 25.29 5.02 19.8 13.248 2.670 0.000 18.7 ± 6.33 35 100 Pb 9.7~43.1 23.91 5.72 23.9 -0.111 0.486 0.000 24.6 ± 5.08 35 350 Zn 57.0~296.1 86.29 28.13 32.6 19.688 3.724 0.000 57.5 ± 16.3 100 300
a S.D. means standard deviation; CV mean coefficient of variation
b Chen et al. 2004. Mean ± S.D; CNEMC.1990.
c SEPA 1995. Class 1 is the natural backgroun
d level; class 2 is for th
e need o
f agricultural production and human health
Correlation coefficient analysis
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Correlation coefficient shows the linear relationship between heavy metals. The relationship
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between heavy metals can provide important information on heavy metal sources(Manta et al.,
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2002). The partial correlation coefficients and their significance levels (p<0.05; p<0.01) between all
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the variable are presented (shown in table 3). As, Pb, Cr and Cd were not significantly correlated
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with Hg. Strong negative correlations were observed between As and Zn, Pb, Cd. The same
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phenomena were also observed between Pb and Cr, Cr and Cd. Except for the relations listed
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above, positive correlations excited between each other of 7 heavy metals, observed between As
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and Cu, Cr, Hg and Cu, Zn, Cu and Zn, Pb, Cr, Cd, Zn and Pb, Cr, Cd, Pb and Cd. The results
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suggested that accumulation of these heavy metals except for As may originate from a common
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pollution source.
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Table 3 Correlation matrix of heavy metals
As Hg Cu Zn Pb Cr Cd As 1.000
Hg -0.077 1.000
Cu 0.245**0.133* 1.000
Zn -0.285**0.339**0.415** 1.000
Pb -0.207**-0.093 0.293**0.160** 1.000
Cr 0.325**0.093 0.139*0.198**-0.292** 1.000
Cd -0.255**0.100 0.356**0.272**0.557**-0.301** 1.000
Partial correlation analyses were used.*p<0.05, n=269; **p<0.01, n=269;(two-tailed)
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Multivariate analysis results
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PCA and CA can be used to identify the sources of heavy metals contamination in soil. The CA 131
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Fig 2 Dendrogram of the cluster analysis based on the correlation coefficients using the furthest
neighbour linkage method
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The results of the PCA are presented in table 4. The Eigenvalues of the third extracted components 142
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were all greater than 1.0. Therefore, the original variables could be reduced to 3 factors, 144
accounting for over 70% of the total variance. As shown in table 3, As had the main loading in 145
factor 3, Hg, Cr and Cu was mainly distributed in factor 2, Cd, Cu, and Zn were strongly 146
associated with the first component (factor 1) with high values.
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Table 3 Total variance explained and component matrixes for heavy metals
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153 154 155
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158 159 160 161
162 Spatial distribution of soil heavy metals
163 GIS software can be used to produce spatial distribution maps. In the present study, the 164 concentration of As, Cd, Cr, Hg, Cu, Pb, and Zn were interpolated using kriging. Figs. 2 showed 165 the spatial distribution of 7 heavy metals. The spatial distribution of As and Cr showed that the 166 high contour were at the southwest of the town. The distribution of Cd and Pb showed a similar 167 pattern. Their concentrations decreased from the east to the west. The highest concentrations were 168 found in the northeast, which were distributed in the west side of Dashi river. Similar spatial 169 distribution pattern of Hg and Zn were showed in the geochemical maps. 170
171 Their highest concentrations were distributed on the both side of upstream Mapaoquan river. 172 The highest concentrations of Cu mainly were distributed in the southeast. 173 174 175 176 177 178 179 180 181 182 183 184 185 186
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188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218
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Fig. 3 Spatial distribution of topsoil heavy metals 225
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Component Matrix a
Component
1 2 3
As -.440 .430 .656
Hg .239 .469 -.553
Cu .526 .572 .461
Zn .586 .532 -.354
Pb .730 -.258 .353
Cr -.329 .742 .017
Cd .827 -.126 .162
Extraction Method: Principal Component
Analysis.
a. 3 components extracted.
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229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270
Rotated Component Matrix a
Component
1 2 3
As -.149 -.322 .826 Hg -.104 .755 -.047 Cu .595 .304 .609 Zn .284 .818 .054 Pb .838 -.080 -.123 Cr -.383 .331 .635 Cd .819 .167 -.164 Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.
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A total of 269 soil samples were collected from the agricultural area of 22.65km2. It suggested that
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it had 1 soil samples in the approximately 0.29 km2. In soil sampling process, number and position
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of soil samples were based on land use patterns and plots area. Through consultation with the local
farmers, soils intensive sampling was to carried out in the some farmland, which had used sewage 279
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for irrigation. It is ensured that soil samples were representative.
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In the study area, the mean concentration of all heavy metals with an exception of Pb exceeded
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the background value of environment, and part of soil samples was located in the slight pollution
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grade. In 2008, Zheng et al. (2008) investigated the As, Cd, Cu, Cr, Pb and Zn contents in the
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Beijing area. Compared with their result, the concentration of Cd, Cu, Cr, and Zn were larger in
our result. It suggested that the soil heavy metals had been accumulation in Shilou town. By 285
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evaluation of the soil environment quality, 29.74 % of soil samples were located in the slight
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pollution grade, which implied crop has been polluted. Proportion of Cd Single factor index which
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exceeded grade Ⅱ was largest (50.56%) in all soil heavy metals. For soil quality Nemerow index,
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effect of Cd and Hg were notability. Cd is an environmental toxin and has a biological half-life of
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greater than 10 years in humans. High level of Cd exposure can affect kidney or lung functions
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(Friberg et al, 1986). Accumulation and pollution of Cd in agriculture soil came from inorganic
fertilizer (Nicholoson, et al., 2003). It was estimated that the phosphate application of human 292
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activities accounted for 54% to 58% in the contribution of soil accumulation of Cd (He, 1998). It
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suggested that fertilizer supervision and effective use was necessary for controlling pollution of
Cd in the study area. Proportion of Hg Single factor index which exceeded grade Ⅱ was 23.05%. 295
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Sources of Hg in the soil include mother rock, atmospheric deposition, wastewater irrigation,
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pesticide, and fertilizer. Atmospheric deposition is typically considered as the main source of Hg
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in soils (Jin et al., 2008). It indicated that controlling of Hg pollution is necessary in the study
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area.
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In summary, mean of all samples soil quality Nemerow index had been approximated to grade
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Ⅲ(slight pollution). It must be to control soil heavy metals pollution and ward off anthropogenic 302
contamination of agricultural products.
CONCLUSION
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This investigation of soil samples from Shilou town in Beijing demonstrated that the mean 304
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concentration of the soil heavy metals As, Cd, Cu, Cr, Hg and Zn exceeded the background value 306
of Beijing area. And it revealed a clear accumulation of Cd, Hg and Zn. By evaluation of the soil 307
environment quality, it was indicated that 29.74 % of soil samples were located in the slight 308
pollution grade, 61.71 % of soil samples were located in “Fire line” pollution grade, and only 309
8.55 % of soil samples were in the safety grade. The mean of all samples soil quality Nemerow
index was 0.918, which had been approximated grade Ⅲ(slight pollution). The study indicated 310
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that more attention should be paid to controlling heavy metal pollution in agricultural soils in 312
Beijing.
Acknowledgements
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The work was supported by the National Science and Technology to support the scheme subject: 315
“Research & development on instruments of direction measuring and dynamic monitoring for 316
village environment (2012BAJ24B02)”
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