Distribution of heavy metal contents of soils in an industrial area of Zibo, China

Shuai WANG, Hongqi WANG*, Yanguo TENG, Qingtao ZHOU College of Water Sciences Beijing Normal University

Beijing, China, 100875 *whongqi@126.com; bnuwsh@126.com

Abstract—A systematic soil sampling including 32 topsoil samples and 80 subsurface soil samples were collected to investigate the distribution of heavy metal (HM) contents of soils in an industrial area of Zibo, China. Both the total contents and water soluble contents of 6 HM (Cu, Pb, Cd, Cr, As, Hg) were analyzed to assess the enrichment and mobilization ability of the elements. The relative cumulative frequency (RCF) curve and robust statistical methods were used to distinguish anthropogenic influenced samples from background for these elements. Results showed that the baseline and background calculated in this study was close to the background of Shandong province. The upper limits of baseline and background were preferred for evaluation criterions to quality standards in China. Comparing of the baseline with background shows an accumulation of HM in the surface soils. The subsurface soils were less contaminated than top layers. The enrichment of Pb and Hg is significant in this area. The main accumulation area located at the surface soils around small chemical plants and sewage ditches in the area. The water available fractions of HM in surface soils were unusually higher than subsurface soils, indicating a potential risk for natural leaching. Decontamination of HM was needed in the polluted area.

Keywords-soil pollution; heavy metal; geochemical background; geochemical baseline;

I. INTRODUCTION Soils play an important role in maintaining the

environmental quality as they can act as both source and sink for pollutants [1]. Heavy metals (HM) are typical pollutants in soils in areas with extensive human activities. Main sources of HM in soils are industrial emissions, vehicle emissions, burning of fossil fuels and other activities [2, 3]. The HM in soils can directly enter human bodies by dust ingestion, dermal contact or breathing, therefore causing serious health problems [4]. Furthermore, any contamination of soils could cause in turn groundwater contamination because metals of the polluted soils tend to be more mobile than those of unpolluted ones [2, 5, 6].

Zibo is an important heavy industrial city in Shandong province of China. It has large scale industrials including petrochemical, mechanical, metalworking etc. The increasing development of economic and expanding population in the past decades caused serious environmental and health problems. For

example, the ground water resource in many districts was found to be contaminated by various pollutants [7].

In this study, two separate soil samplings including top soils and subsurface soils were performed in an industrial area of Zibo city to investigate the enrichment of typical HM in soils and the mobilization ability of the elements to groundwater.

II. MATERIALS AND METHODS

A. Study area descriptions The study area located between 36°30’-37°00’ north

latitude and 118°07’-118°29’ east longitude, with a total land area of more than 100km2 in Zibo city, Shandong province, east of China mainland. There are rock outcrops with low mountains and hills in the south. The depth of soil layer varies from nearly zero in the south to more than 100 meters in the north. The area lies on the east limb of Zibo syneline. The formations strike ENE-WSW and dip gently to NNW with an angle of 10. Aquifers are composed of fractured and karstified limestone and dolomite of Middle Ordovician. There is a large well field downstream.

The rapid increasing industry put extensive pressures on local environmental quality. Former studies in this area showed serious contaminations of soils and groundwater by organic matters. However, little information was known about the distribution of HM in this area.

B. Soil samples and chemical analyses The location of the sampling sites is shown in Fig. 1. Most

of them were chosen in or around the factories, sewage ditches and farmlands. A total of 32 topsoil samples (0-0.50m) and another 80 soil samples from deep stratum (0.5-15m) were collected in April 2007 and August 2007 respectively.

Composite samples of approximately 1 kg were obtained by mixing five subsamples within about 1 m2 in each sampling site. Stones and foreign objects were removed by hand, and the samples were air-dried and screened through a 2-mm sieve prior to analysis. Soil pH was measured in a 1: 5 (w/v) ratio of soil to water by a glass electrode. Particle size analysis was made using the pipette method. Water soluble fraction was extracted in a 1:20 (w/v) ratio of soil to water. Soil samples for

*Corresponding author Supported by National Natural Science Foundation of China (grant no.40772149)

978-1-4244-2902-8/09/$25.00 ©2009 IEEE 1

total contents of HM were digested with 60% perchloric acid, 40% hydrofluoric acid, concentrated nitric acid and concentrated hydrochloric acid [8]. Concentrations of Cu, Pb, Cd, Cr and As were analyzed by ICP-AES (ICAP-9000, Jarrell-ASH, USA) While concentrations of Hg were analyzed by HG-AFS (AFS930, Titan, China). For quality control, reagent blanks, replicates, and standard reference material were incorporated to detect contamination and assess precision and bias. The results showed no sign of contamination and revealed that the precision and bias of the analysis were generally below 10%.

C. Statistical analysis Data were log-transformed before further treatment.

Cumulative frequency distribution was performed by the Microsoft Office Excel for Windows. Robust estimation, Kolmogorov-Smirnov (K-S) test and Shapiro-Wilk (W) test were performed by the SAS system for Windows.

III. RESULTS AND DISCUSSION

A. Geochemical background of study area In order to perform a critical identification of anthropogenic

pollution, the geochemical background or geochemical baseline is needed. Geochemical background is the content in trace elements that a soil presents without the influence of human activity [9]. As no virgin ecosystems exist [10], the concept of geochemical baseline is accepted by many researchers. Geochemical baseline is defined as the level of trace elements in soils that are not under the direct influence of humans, therefore it would be the sum of the geochemical background plus a small quantity due to diffuse contamination [9-11]. It provides the means to distinguish between the natural origin and the anthropogenic origin of the trace element in the environmental compartment [12-14].

Geochemical baseline, by its definition, is limited for surface layers. Due to the different geochemical processes experienced between the surface and subsurface layers, it is not appropriate to apply the geochemical baseline to subsurface soils. In this context, the item geochemical background is used for subsurface environment.

A widely applied method to obtain geochemical background or baseline is relative cumulative frequency (RCF) technique. This technique does not require any assumption concerning the distribution function and simply applies the curves of the individual elements to display the RCF linearly. The first turning point of the curve in the high values can therefore be defined as the upper limit of any background data collective [15-16]. This method is of high performance for detecting outliers from background ranges. The values below the limit represent the background range. Fig.2 shows the RCF curves for all the elements. There are points with extremely high concentrations for each element, especially for Pb and Hg. The concentrations of Hg in top soils obviously deviated from that in deep soils due to its high volatility. The baseline and background of the A-horizon and C-horizon soils were determined separately.

The K–S test and W test were applied to test the normal distribution for both raw and log-transformed data after removing outliers. Table 1 shows the results of normal distribution test for C-horizon layer. In this case, only the concentrations of Cu and Hg fitted log-normal distribution well at the significance of 0.05 for the two tests. In fact, it is very common for geochemical data sets to deviate from gauss distributions [9, 15, 17-18]. There were many evitable errors involved in sampling, sample preparing and analysis [18].

An alternative way for estimating background is exploratory data analysis and robust statistics. Reimann recommended the usage of box-plots and median±2MAD (median absolute deviation) for estimating the location and range of the background [17, 19-20]. To make a validation of the results of the RCF, the MAD method was used here, as shown in Table 2. We can see that the ranges of background or baseline calculated by the two methods are much identical.

In addition, the background of Shandong province and the quality standard for soil in China are also provided as a comparison (Table 2). The baselines predicted in this study are very close to the backgrounds of Shandong soils. The upper limits of background and baseline for the six elements are preferred as evaluation criterions to the quality standard. A critical observation in Table 2 reveals that the baselines for A-horizon soils usually have a wider range than that of C-horizon soils. This shows an accumulation of HM in the surface.

Figure 1. Location of the samples sites

TABLE I. TEST OF NORMAL DISTRIBUTION FOR RAW AND LOG-TRANSFORMED DATA

Elements Count K–S test* W test Sig. a Sig. b Sig. a Sig. b

Cu 75 >0.10 >0.20 0.253 0.712 Pb 75 <0.01 <0.01 0.002 0.001 Cd 75 <0.01 <0.01 0.001 0.004 Cr 77 <0.01 <0.01 0.016 0.000 As 79 <0.01 <0.01 0.001 0.139 Hg 78 <0.01 >0.20 0.000 0.401

*Lilliefors significance correction

a Significance calculated from raw data

b Significance calculated from log-transformed data

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Figure 2. Relative cumulative frequency curves for six elements in top soils (star) and subsurface soils (circle)

TABLE II. GEOCHEMICAL BASELINE AND BACKGROUND IN THE STUDY AREA AND THE REFERENCE BACKGROUND IN OTHER STUDIES

Elements Baseline of A-horizon Background of C-horizon Quality Standard for soil [8]

location a Range b Range c location a Range b Range c Cu 23.3(21.7) 12.8-43.8 0.0-47.0 21.3(22.6) 15.5-29.4 15.7-28.6 35 Pb 30.9(24.3) 11.6-40.4 8.5-53.2 32.8(22.9) 14.0-42.0 24.5-41.2 35 Cd 0.084(0.079) 0.059-0.132 0.043-0.125 0.100(0.074) 0.075-0.150 0.071-0.129 0.20 Cr 60.9(65.2) 29.4-99.5 30.8-91.0 60.9(67.9) 29.5-86.5 33.4.6-83.6 90 As 10.3(8.7) 7.5-18.7 6.2-14.4 10.6(9.0) 4.5-18.8 3.5-17.7 15 Hg 0.062(0.016) 0.014-0.123 0.000-0.165 0.013(0.011) 0.002-0.090 0.002-0.082 0.150

a The value in the bracket is the baseline of Shandong province [21]

b Estimated by the method of relative cumulative frequency

c. Estimated by the method of Median±2MAD (normalized MAD)[19-20]

B. Enrichment of HM in soils With the upper limit of baseline and background as the

pollution evaluation criterion, it is found that 12.5%, 31.2%, 9.4%, 6.2%, 15.6%, 31.2% of the A-horizon soils and 3.8%, 12.5%, 5%, 1.3%, 2.5%, 3.8% of the C-horizon soils were polluted with Cu, Pb, Cd, Cr, As and Hg respectively. So the anthropogenic pollution in surface soils is worse than that in subsurface soils. Among the six elements, Pb and Hg were the main pollutants.

The anthropogenic influenced samples were further examined for depths and locations. It was found that more than 60% of the pollution happened in surface soil. However, some deep soils about 2.5 meters below the surface were also found to be polluted seriously. The polluted soils located around sewage ditches from machinery plants and scattered chemical plants. It can be concluded that the deep soils are relatively less influenced by human activities except for the contaminated fields. However, there is obvious accumulation of HM in the top soils. As stated above, this will make a direct health problem to the local people’s health, especially for children.

C. Mobilization ability of HM In soils Although total analysis may give information concerning

possible enrichment of HM in the soils, it is the chemical form of a metal in the soil that determines its mobilization capacity and behavior in the environment [22]. Sequential extraction is considered useful for evaluating mobility and bioavailability of HM in soils [23]. The water soluble fractions of the HM were studied in this study to examine their mobilization ability.

In natural conditions, the main state of HM in soils is residual [24]. Fig.3 shows the variety of water soluble fraction of Cu for all the samples with sample depth. The figures for other elements are similar to Fig.3. It is obvious that the water soluble fraction in top soils is rather high compared to deep soils, indicating a potential leaching risk to subsurface soil and groundwater. Combined with Fig.1, it can be found that all these soils come from small chemical factories who disposed waste water improperly to the soil.

The water soluble content of HM in soils is affected by many factors, such as pH and Eh. The pH values of those soils with high soluble HM were examined to be very abnormal, i.e.

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10.24, 2.57, 2.22, 10.30, 2.96 or 8.92. This low or high pH values may increase the solubility of HM. Therefore the mobilization ability of HM in anthropogenic influenced soils was much stronger than that in natural soils. The soils with high water soluble fraction of HM need to be stabilized or cleaned up.

Figure 3. Variety of water soluble fraction of Cu with soil depth

IV. CONCLUSIONS The geochemical baseline and background of HM in the

industrial area was determined by RCF technique and robust statistics. The result was close to the background of Shandong province and there is an evident accumulation of HM in the top soils. With the upper limits of the baseline and background as evaluation criterions, the top soil layer is found to be anthropogenic polluted more serious than the subsurface layer. The main HM pollutants in this area were Pb and Hg. The water available fractions of HM in some top soils were unusually high coincide with abnormal pH values, therefore posing a potential leaching risk for subsurface environment. The main pollution area located at surface soils around small chemical plants and sewage ditches in the region. Following cleaning actions and monitoring works are needed in this polluted area.

ACKNOWLEDGMENT The authors are grateful to Li Guanghe, Zhang Yinghua

and Han Wei for their guides and efforts during outdoor investigation. The authors also thank the well field bureau for supplying data and fund for the study.

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