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Published online 1 May 2008
Published in J Environ Qual 37:780-787 (2008)
DOI: 10.2134/jeq2007.0154
© 2008 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
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TECHNICAL REPORTS

Ecological Risk Assessment

Spatial Distributions and Potential Risk Analysis of Total Soil Selenium in Guangdong Province, China

H. H. Zhanga,b,c, Z. F. Wua,c,*, C. L. Yanga, B. Xiab, D. R. Xub and H. X. Yuana

a Guangdong Inst. of Eco-environmental and Soil Sciences, 510650, Guangzhou, China
b CAS Key Lab. of Marginal Sea Geology, Guangzhou Inst. of Geochemistry, Chinese Academy of Sciences, 510640, China
c State Key Lab. of Soil and Sustainable Agriculture, Inst. of Soil Science, Chinese Academy of Sciences, 210008, Nanjing, China

* Corresponding author (hhzhang{at}soil.cn; zfwu{at}soil.cn).

Received for publication March 27, 2007.

   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 Materials and Methods
 Results and Discussion
 REFERENCES
 
A total of 260 soil profiles were examined to investigate the spatial distribution of total soil selenium (Se) in Guangdong province, China. In the investigated area, the soil Se concentrations follow an approximately lognormal distribution. The soil Se geometric mean concentration of 0.23 mg kg–1 is higher than that of Chinese soils; however, Se concentration varies over the study area. The baseline concentration of 0.13 to 0.41 mg kg–1 indicates that the soil Se concentration is mostly in the range of deficiency to medium level for surface soils in Guangdong province. In A-, B-, and C-horizon, soil Se spatial distribution is correlated with the nature of the parent material, with high Se concentration mainly located in limestone and sandshale areas and low Se concentration associated with purple shale and granite areas. The spatial distribution pattern of soil Se concentrations suggests that potential Se deficiency may be an issue for human health in this province. Moreover, due to soil degradation and erosion, calculated soil Se exported into surrounding waters could reach approximately 23,000 kg yr–1 in the study area.

Abbreviations: GM, geometric mean • GSD, geometric standard deviation


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
Materials and Methods
 Results and Discussion
 REFERENCES
 
SELENIUM (Se) is usually described as a dispersed element in nature. It is present in soils, rocks, water, and biota. It occurs naturally in soils and waters due to chemical weathering of Se-containing minerals and as a contamination in many areas of industrial activity, such as coal combustion, smelting, and fertilizer production.

Many Se-poisoning episodes, induced by Se excess, have been reported in differently investigated areas, such as the Kesterson National Wildlife Refuge in California (Presser, 1994; Presser et al., 1994) and the Enshi district in China (Yang et al., 1983; Fordyce et al., 2000). In contrast, Se deficiency has been confirmed to be associated with heart failure (Ge et al., 1983; Fleming et al., 1982), muscle pain (Van Rij et al., 1981), some cancers (Ip and Ganther, 1994; Cech et al., 1984), and many other diseases (Burk, 1994). Therefore, the acceptable intake level estimated by Yang and Xia (1995) ranges between a minimum dietary Se requirement (17 µg d–1) and a maximum safe Se intake (600 µg d–1).

Due to the threat to human and ecological health, many studies have been conducted on Se speciation and geochemical processes. These investigations focused for instance on Se deposits (Wen et al., 2006), flue gas (Yan et al., 2001), agricultural drainage water (Zhang et al., 1999) and sediments (Zawislanski et al., 2003), Se transport between waters and sediments (Tokunaga et al., 1997; Fujita et al., 2005), and Se removal methods from agricultural drainage water (Lin and Terry, 2003). Little attention has been paid to the spatial distribution of soil Se concentrations on the regional scale for anticipating and preventing Se problems.

In Guangdong province, the limestone and sandshale were formed predominantly during the early Carboniferous period to early Permian period due to the large-scale sea invasion. In that period, the biological enrichment was the primary reason for the high Se content in the limestone and sandshale. During the Cenozoic period, the landform was uplifted by tectonic movements, and igneous rocks intruded and cut through the limestone and sandshale along the regional faults. In this period, hydrothermal activities were intensive and frequently induced by regional magmation. The Se-containing minerals were the products of the low-temperature hydrothermal metasomatic process (GSGIO,1993). The soil and water loss due to intensive physical and chemical weathering and damaged vegetation are serious issues in Guangdong province. The soil erosion areas reach up to about 7376 km2, accounting for 4.2% of the total area (GSGIO,1993). Therefore, the investigation of spatial distribution is of importance to reveal the geochemical behaviors of soil Se and to evaluate the influence of soil Se on the quality of surrounding environments. The present study was conducted (i) to identify controlling factors that determined the spatial distribution of soil Se concentration and (ii) to discuss the potential human and ecological risk in Guangdong province.


   Materials and Methods
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and Methods
Results and Discussion
 REFERENCES
 
Study Area
Guangdong province is located in South China (Fig. 1A ), between 20°10' to 31'N and 109°41' to 117°17'E. The area is characterized by a subtropical monsoon climate and has an average annual precipitation of 1336 mm and average annual evaporation of 1100 mm. The annual average temperature is 18.7 to 23.4°C, and there are on average 1828 h of sunshine annually. From north to south, the landscape changes from mountain to plateau to flood plain. The hilly area is up to about 60% of the total area. Regional faults running NNE or NE are the main geological features and cut through the regional limestone and sandshale areas (Fig. 1B). Granite is the most common parent material for soils, accounting for more than 40% of soils in the Guangdong area. Limestone and sandshale occupy about 40% of the total area. Basalt parent material is located in the Leizhou Peninsula (Fig. 1B).


Figure 1
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  		Fig. 1. Location of Guangdong Province, China (A), geological sketch indicating the distribution of parent rocks (B), and sampling locations (C). Number 1 is the Beijiang River, 2 is the Xijiang River, 3 is the Dongjiang River, 4 is the Huanjiang River, and 5 is the Jianjiang River.

 
The Guangdong soil profile is the typical Al-enriched weathering profile and is the product of the latest stage of weathering. Because of the intensive eluviation and illuviation in the hydrothermal condition in the investigated area, the soil profiles are deficient in soluble salt, alkali metal, and alkali-earth metal but are rich in Fe and Al oxides and H+ (Lan et al., 2003). Therefore, the average pH value in Guangdong soil profiles is acidic in nature. Acid rain is also an important factor affecting the pH value of the soil in this area (Larssen and Carmichael, 2000). As a result, in the study area Se is predominantly present in the form of selenite in soils and forms undissolved compounds with Fe-oxide and Al-oxide (Wang and Wei, 1995).

Field Sampling
Soil samples used in this study were collected from the locations shown in Fig. 1C. The sampling points in each area were selected on flat terrain. A-, B-, and C-horizon soil samples were taken from 260 soil profiles at depths of 0 to 20, 20 to 40, and 40 to 120 cm, respectively. Each soil profile was 1.5 m long, 0.8 m wide, and 1.2 m deep. The soil samples, free of plant roots, were air-dried, crushed, and divided into two portions. One portion was sieved through a 20-mesh nylon screen (1-mm aperture size) for analysis of soil properties and stored at room temperature (25°C). The second portion was passed through a 200-mesh nylon sieve before the acid digest procedure.

Chemical Analyses
Subsamples of 0.5 g of soil were precisely weighed and digested using hot, concentrated HNO3 and 30% H2O2 for 24 h. The residue was refluxed using hot 6 mol L–1 HCl and washed several times with HCl. Supernatant solutions were passed through a 0.45-µm seive. Total Se was determined using hydride generation atomic absorption spectroscopy (Zawislanski and Zavarin, 1996; Zawislanski et al., 2001). The recovered soil Se concentration of the National Research Center for GeoAnalysis soil standard reference materials (ESS-4, Beijing, China; standard value: 0.072 mg kg–1) was 0.079 mg kg–1 (n = 32). The analytic precision was <5% for total soil Se.

The pH of soil was measured in a suspension of equilibrating 10 g of soil and 25 mL of deionized water (Chinese National Standard Agency, 1988). The soil organic matter content was measured using the potassium bichromate oxidation process (Yu and Wang, 1988). Soil clay and sand contents are based on wet and dry sieving techniques and pipette method (Gee and Bauder, 1986).

Statistical Analyses
All soil Se concentrations are presented on a dry-matter basis. These values are transformed to logarithms (base 10) because they have positive-skewed frequency distributions (Table 1 ). The log-transformed data fit an approximately normal distribution (Fig. 2 ); therefore, the geometric mean (GM) and geometric standard deviations (GSD) are used to represent the central tendency and variations of the data. Baseline concentrations of Se are defined as the range between GM/GSD2 and GM x GSD2. This range includes 95% of the samples (Dudka et al., 1995).


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  		Table 1. Summary statistic of the data for 260 soil profiles in Guangdong Province.

 

Figure 2
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  		Fig. 2. Distribution frequency of selenium concentration in A-, B-, and C-horizon soils in Guangdong Province, China. Left: original data; right: log10-transformed data.

 
The semivariogram is half of the expected squared difference between paired data values z(x) and z(x + h) to the lag distance h, by which locations are separated (Webster and Olive, 2000):

Formula
The semivariogram can be calculated by the following equation:

Formula
where z(xi) is the value of the variable z at location of xi, h is the lag distance, and N(h) is the number of pairs of sample points separated by h.

The experimental semivariogram calculated for several lag distances is generally fitted with a theoretical model, such as spherical or nugget effect models. The spherical model is probably the most commonly used transition model. This model has linear behavior at the origin and then reaches a plateau (Sill value). The nugget effect model is used to model a discontinuity at the origin (Zhang, 2004). These models provide information about the structure of the spatial variation and input parameters for the following spatial interpolation performed using ordinary kriging. For the low-density and background sampling, the ordinary kriging estimate can be thought of as an optimally weighted average of the data. It provides a best linear unbiased prediction of spatial distribution (Cressie, 1991).

In the present study, the log-transformed data were used to calculate their semivariograms using the software package VARIOWIN 2.2. The semivariogram obtained can better fit the spherical model combined with the nugget effect model (Fig. 3 ). The Spatial interpolation and contour maps were produced using the software of Surfer (Golden Software, Inc., Version 8.00).


Figure 3
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  		Fig. 3. Semivariograms of selenium concentration in A-, B-, and C-horizon in Guangdong Province, China, obtained by spherical model.

 

   Results and Discussion
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and Methods
 Results and Discussion
REFERENCES
 
Baseline Concentration of Surface Soil Selenium
Natural background concentration can be defined as the ambient concentration of chemicals in soils without human influence (Gough, 1993). It is generally difficult to establish the true natural background level in soils because of long-range transport and precipitation of contaminants. Accordingly, a baseline concentration can be used to represent element concentrations specific for a given region and time period but does not always represent a true background concentration (Kabata-Pendias and Pendias, 1992; Salminen and Tarvainen, 1997).

The present results show that the Se concentration in A-horizon soil varies from 0.03 to 1.42 mg kg–1 (Table 1). The geometric mean of 0.23 mg kg–1 is greater than that in Se-deficiency areas, such as 0.028 mg kg–1 in California soils (Bradford et al., 1996), 0.01 mg kg–1 in Florida soils (Chen et al., 1999), 0.145 mg kg–1 in Poland soils (Budka, 1993), and is close to 0.21 mg kg–1 in Chinese soils (Wang and Wei, 1995) but lower than 0.26 mg kg–1 in USA soils (Shacklette and Boerngen, 1984) and 0.4 mg kg–1 in worldwide soils (Bowen, 1979). The upper baseline concentration of 0.41 is higher than that of 0.23 mg kg–1 in California (Bradford et al., 1996) and 0.30 mg kg–1 in Poland (Budka, 1993), lower than that of 1.11 mg kg–1 in Florida (Chen et al., 1999) and 0.99 mg kg–1 in Chinese soils (Wang and Wei, 1995), and much lower than the Geological Survey (USGS) upper limit of 1.4 mg kg–1 in western USA soils (Presser et al., 1994).

Log-transformed Se concentrations follow a linear trend when plotted on a normal probability plot, and almost all data points fall into the range between the lower bound and the upper bound in the 95% confidence interval (Fig. 4 ). This suggests that the data can be assumed to be sampled from a single population after log transformation. It also suggests that Se levels in most of the soils were not significantly affected by anthropogenic influences, or, if they were, that it was the result of a nonpoint source. Thus, the data are suited to estimate current Se baseline concentrations in the surface soils in Guangdong province. Accordingly, in the investigated area, the present baseline concentration can better express the range of Se background concentrations because the distorting effects of a few high concentrations have been minimized by using a log-transformation (Budka, 1993; Chen et al., 1999). The baseline concentration range (0.13–0.41 mg kg–1) also indicates that the Se concentrations of approximately 95% of soil samples are in the range of deficiency (0.125 mg kg–1) to medium level (0.40 mg kg–1) as reported by Tan et al. (2002).


Figure 4
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  		Fig. 4. Lognormal probability plot for total selenium concentration in surface soils (A-horizon soil) in Guangdong Province, China.

 
Correlations with Soil Properties
Geochemical behavior of Se in soils is affected by soil pH, amounts of clay minerals, organic matter, and other factors (Lakin, 1972; Weres et al., 1989; Masscheleyn et al., 1990; Peng et al., 1995; Jayaweera and James, 1996; Zawislanski and Zavarin, 1996).

Our results show that linear trends between total Se concentrations and soil clay and organic matter contents were mostly not significant in this province (Table 2 ). This phenomenon may be correlated with the low average soil organic matter (27.5 g kg–1) in A-horizon soil and the different adsorptive capacities of clay minerals developed on the different parent materials. In granite areas, the soils generally showed a lower average Se content of 0.18 mg kg–1, compared with 0.26 mg kg–1 in the limestone areas and 0.25 mg kg–1 in the sandshale areas (Wang and Wei, 1995). However, in granite areas, abundant kaolinite with a small amount of vermiculite was the dominant clay mineral (Lan et al., 2003). In contrast, there is abundant vermiculite and a small amount of kaolinite in limestone and sandshale areas (GSGIO, 1993). Because kaolinite has more significant absorptive capacity to soil selenite than vermiculite (Wang and Wei, 1995), the present results suggest that there is a strong adsorption of selenite in low-Se areas and a weak adsorption in high-Se areas. This difference may mask or modify the correlation between soil Se concentrations and soil clay contents to a certain extent.


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  		Table 2. Pearson correlations between selenium contents and some soil properties.

 
From A-horizon to C-horizon, soil pH has significant negative correlations of –0.396, –0.329, and –0.194 with the Se concentration, respectively (Table 2). In acid soil conditions, Se is mainly present in the form of selenite (Se4+) with a greater affinity for iron and aluminum oxide in soils, which make them largely unavailable to plants and animals (Mikkelsen et al., 1989; McNeal and Balistrieri, 1989). The present correlation between soil pH and total Se concentration suggests that there may be a higher Se loss in relative high soil pH areas than that in low pH areas; that is, soil Se developed on the limestone areas may be more easily released than Se present in granite areas.

Spatial Distributions of Soil Selenium Contents
The spatial distribution of the soil Se concentrations as estimated by ordinary kriging is mapped in Fig. 5 for A-, B-, and C-horizon soils. The A-horizon reflects the complex interplay between atmosphere, biosphere, and lithosphere. The B-horizon can be used to study the influence of soil forming process, and the C-horizon represents the composition of the lithosphere at each sample site and thus reflects the geogenic background (Reimann et al., 2001).


Figure 5
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  		Fig. 5. Spatial distributions of selenium concentrations in A-, B-, and C-horizon soils in Guangdong Province, China. Red line areas (<0.125 mg kg–1): selenium deficiency areas; yellow line areas (0.125–0.175 mg kg–1): selenium marginal areas; green line areas (0.175–0.4 mg kg–1): selenium medium areas; outer areas of green line (>0.4 mg kg–1): selenium adequate areas.

 
Wang and Wei (1995) summarized 4095 soil samples in China and pointed out that the background concentration of soil Se was primarily influenced by the parent materials. In the present study, contours of soil Se concentrations display similar spatial distribution patterns in soil profiles (Fig. 5A–C). Moreover, there are significant correlations between Se contents in different horizons (r = 0.747 for A/B, 0.720 for B/C, and 0.578 for A/C) (Fig. 6 ). It also indicates that in A-, B-, and C-horizon soil, Se spatial distribution is correlated with the nature of parent material with high Se concentration mainly located in limestone and sandshale areas and that low Se concentration is correlated with purple shale and granite areas (Fig. 5 and see Fig. 1B), which further confirms that the spatial distribution of soil Se is controlled by properties of regional parent materials rather than anthropogenic Se inputs.


Figure 6
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  		Fig. 6. Scatter diagrams showing correlation for soil selenium in A-, B-, and C-horizon soils

 
Vertical variation of total Se concentrations in soil profiles generally follows the order B-horizon > C-horizon > A-horizon (Table 1). This phenomenon may be attributed to the following reasons: (i) A low average organic matter content in the A horizon (27.5 g kg–1) cannot act as a natural biogeochemical barrier that suppresses the percolation of Se with the seepage water, (ii) intensive eluviations induce the upper soil Se transfer to the B-horizon, and (iii) the strong adsorption of Se onto iron and aluminum oxide and clay minerals in the B-horizon suppress the downward transfer of soil Se to C-horizon soils. As a result, soil Se in the B-horizon has much higher spatial continuity than that in A- and B-horizon soils (Fig. 3 and 5).

Potential Risk Analysis of Total Soil Selenium
The biological function of Se shows a dual character because of the narrow Se content ranging between toxic and deficient concentrations in animals. Therefore, for preventing related endemic diseases, strict dietary requirements and a safe range of dietary intakes of Se have been established, such as a minimum dietary Se requirement (17 µg d–1), adequate dietary Se requirement (40 µg d–1), safe dietary Se intake (400 µg d–1), and maximum safe Se intake (600 µg d–1) (Yang and Xia, 1995). However, most of the research effort is generally performed after Se problems happen rather than anticipating and preventing them (Lemly, 2002).

Generally, soil Se is the primary source of human food Se. Many researches in different areas of China have showed that the Se concentrations in grains are significantly correlated with the total Se concentrations in surface soils (Zhu and Zheng, 2001; Cao et al., 2001; Tan et al., 2002). Tan (1989) and Tan et al. (2002) investigated the distribution of topsoil Se in China and its relationship to Keshan disease (KSD) and Kashin-back disease (KBD) induced by Se deficiency and reported that the total Se concentrations in topsoil of KSD/KBD-affected areas were below 0.125 mg kg–1. The marginal concentration was 0.125 to 0.175 mg kg–1 (Tan, 1989; Wang and Wei, 1995; Tan et al., 2002). As a result, these values can be considered as the reference threshold for the risk assessment of potential Se deficiency. Accordingly, in surface soils total Se is divided into Se deficiency level (<0.125 mg kg–1), Se marginal level (0.125–0.175 mg kg–1), Se medium level (0.175–0.4 mg kg–1), and Se adequate level (>0.4 mg kg–1).

The present results show that soil Se geometric mean concentration of 0.23 mg kg–1 is higher than that of Chinese soils (Wang and Wei, 1995); however, Se concentration varied in the study area. The baseline concentration of 0.13 to 0.41 mg kg–1 suggests that the soil Se concentration may be mostly in the range of deficiency to medium level. In surface soils, the Se spatial distribution indicates that several Se-deficient areas (red line areas: <0.125 mg kg–1) are scattered throughout the province, and other areas may fall within the range of potential Se deficiency (Fig. 5; yellow line areas: 0.125–0.175 mg kg–1). Due to the specific soil characteristics of this area, only a limited part of the Se is likely to be phytoavailable because of the lower water-soluble Se content (Jayaweera and James, 1996) and intensive eluviations in Guangdong acid soils. Therefore, in these areas, supplement Se in the diet may be a valid method to prevent the potential Se deficiency, in particular in rural areas where the inhabitants obtain food (such as grain and vegetables) only from local soils.

The Se movement export takes place constantly from surface soil degradation and erosion. Its products are being transported into ground and surface water. As a rough estimate, the soil area of Guangdong province is about 147,000 km2 and has an average soil density of about 1 g cm–3 (GSGIO, 1993). Annual soil erosion yield is about 1 x 1011 kg and is mainly distributed along Hanjiang, Beijiang, Dongjiang, and Jianjiang water bodies (Zhang et al., 1994). According to these data, due to soil degradation and erosion, soil Se exported into surrounding waters could reach approximately 23,000 kg yr–1. This may be the reason that in the Pearl River estuary the concentrations of dissolved Se are slightly enriched as compared with pristine rivers (Yao et al., 2006).


   ACKNOWLEDGMENTS
 
We thank two reviewers for their very useful comments that improved the quality of this manuscript. This work was partly funded by National Natural Science Foundation of China (No. 40571164), the CAS Key Laboratory of Marginal Sea Geology (MSGL07-19 and MSGL06-18), the Technologies R & D Program of Guangdong Province (No. 2004B32501004), and the State Key Laboratory of Soil and Sustainable Agriculture (0751010006).


   NOTES
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 NOTES
ABSTRACT
 INTRODUCTION
 Materials and Methods
 Results and Discussion
 REFERENCES
 
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   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and Methods
 Results and Discussion
 REFERENCES
 




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