Evaluation and analysis of soil migration and distribution characteristics of heavy metals in iron tailings

Evaluation and analysis of soil migration and distribution characteristics of heavy metals in iron tailings

Journal of Cleaner Production 172 (2018) 475e480 Contents lists available at ScienceDirect Journal of Cleaner Production journal homepage: www.elsev...

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Journal of Cleaner Production 172 (2018) 475e480

Contents lists available at ScienceDirect

Journal of Cleaner Production journal homepage: www.elsevier.com/locate/jclepro

Evaluation and analysis of soil migration and distribution characteristics of heavy metals in iron tailings Xu Zhang a, 1, Huanhuan Yang b, 1, Zhaojie Cui a, * a b

School of Environmental Science and Engineering, Shandong University, Ji'nan 250100, China School of Life Science, Shandong University, Ji'nan 250100, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 21 January 2017 Received in revised form 23 September 2017 Accepted 29 September 2017

Migration and transformation trend of heavy metals have close relationship with soil safety. In this research, we aim to provide reliable basis for prevention and management of local soil contaminants. We choose Anshan tailings for field investigations and laboratory research, analyze vertical and horizontal migration characteristics of five heavy metals (Cu, Zn, Pb, Cd, and Cr) and the role of Amaranthus blitoides in tailings. According to Single factor contaminant index and Nemerow composite index, the five heavy metals condition different migration trend in the vertical direction (Cd > Zn > Cr > Pb > Cu) in the soil properties and threaten the groundwater of Anshan tailings. They had strong migration capability in horizontal direction resulting in surrounding pollution. The highest migration capability was found in Cr followed by Pb > Zn > Cd > Cu under specific climatic condition. Amaranthus blitoides as dominant species can grow well in harsh environment and can effectively remove heavy metals in mine tailings. © 2017 Elsevier Ltd. All rights reserved.

Keywords: Heavy metals Horizontal migration Risk assessment Vertical distribution

1. Introduction As an important subsystem, soil is usually considered as main stack area of various pollutants (Chibuike and Obiora, 2014). Polluted soil by heavy metals not only impairs physical and chemical properties, but also affects the soil organisms. Organisms have the ability to accumulate heavy metals through air, food, or water resources, finally to pose a threat to human health including hypophosphatemia, heart disease, liver damage, and neurotoxicity (Zoeteman et al., 1981). Heavy metals show great ecological significance because of high toxicity, persistence and bioaccumulation capacity. Although heavy metals contamination from an aquatic source shows negatively affect on organisms at all trophic level along the food chain (Tao et al., 2012), terrestrial organism reproductive success is reduced in the soil environment contaminated by heavy metals because chronic exposure can cause physiological abnormalities (Zhang et al., 2016). Therefore the pollution of heavy metal in soil greatly influences the health of ecosystem, and the study on heavy metals distribution mechanism has great significance (Oti et al., 2012). The content of heavy metals in tailings is influenced by many

* Corresponding author. E-mail address: [email protected] (Z. Cui). 1 Xu Zhang and Huanhuan Yang contributed equally to this work. https://doi.org/10.1016/j.jclepro.2017.09.277 0959-6526/© 2017 Elsevier Ltd. All rights reserved.

factors, including anthropogenic and lithogenic sources, the textual characteristic, organic matter content, mineralogical composition and depositional environment. Grain size is one of the essential factors influencing heavy metal contents in soil (Jung, 2008). Finegrained sediments often show high concentrations of heavy metals due to their greater surface to volume ratio and enrichment of organic matter and FeeMn oxides. The behavior of heavy metals in sediments is strongly dependent on redox gradients. The metal profiles are affected by sedimentary redox processes, which can be monitored by means of Mn and Fe concentrations (Vink, 2002). Iron is an important electron acceptor during early diagenesis and the reduction of iron plays a significant role in the cycling of heavy metals. Heavy metals show strong affinity with iron oxides in the environment, and the reduction of iron oxides has a direct influence on the cycling of heavy metals. The complexation of heavy metals with organic matter is important in the understanding of metal bioavailability and mobility in natural aquatic systems. Recent studies show phytoremediation is a safe and efficient way to handle heavy metal in soil (Kotrba et al., 2009). Phytoremediation inhabiting potentially polluted areas yields an assessment and protection of overall ecosystem health. Many of the current phytoremediation efforts rely on special hyperaccumulator, showing higher demand on soil quality. Local plants can withstand harsh environment and have the capability to accumulate heavy metal. Local wild-type is the best choice for in -


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situ ecological restoration. Amaranthus blitoides (Caryophyllales, Amaranthaceae, Amaranthus) is widely distributed in North America and Liaoning China. Amaranthus blitoides can tolerate harsh environment and effectively accumulate the heavy metal, showing great application prospects in - situ remediation (Río et al., 2002). Anshan city located in northeast of China engaged in development of mineral resources. Mining tailings and other wastes occupied a large area of the site, finally resulted in destruction of ecosystems in stacked field (Andrade et al., 2006). There was much heavy metal in tailings shown in Fig. 1. Large amount of toxic heavy metals released and migrated through surface runoff, airborne particulates. That had serious impact on the surroundings (Wang et al., 2007). In this study, we chose Anshan as sample area and employed phytoremediation to assay the migration of heavy metals in the vertical and horizontal direction to assess the environment pollution and discovery potential threat (Serrano et al., 2016). The main pollutants of heavy metal are Cu, Zn, Pb, Cd, and Cr and showing certain migration capability. Transportation area was prone to be secondary source of pollution. Monitoring and remediation are necessary for mine tailings. 2. Materials and methods 2.1. Sampling procedure In order to know the effects of heavy metals on deep soil and groundwater, we analyzed five typical heavy metal elements (Cu, Zn, Pb, Cd, and Cr) to study the migration of heavy metals in the vertical direction. Three one-meter profile were dug and divided into five 20 cm depth gradient from the surface to different depths (Rosling et al., 2003). Soil columns were collected from the mine tailings. Each column consisted of five distinct soil horizon which could be distinguished by their colour and found at the following depths: P1,0e20 cm; P2,20e40 cm; P3,40e60 cm; P4,60e80 cm; P5,80e100 cm. To ensure pure material of each layer, centered sample were collected. Soil samples were coded according to column and profile. According to the flow direction and the characteristics of the tailings, we set up ten sampling points to study migration rules in the horizontal direction. Also, we collected and identified the dominant species from local and sparse plants that grow in the tailings. The rhizosphere soil was tested to evaluate the role of plants in tailings and sought for plant species with heavy metal accumulation (Zhang et al., 2012). All samples were plugged into an auto-sealed polyethylene plastic bag and sealed with tape

immediately at site for lab analysis. In the lab, the sediment cores were divided into sub-samples at 2 cm intervals with knife under room conditions. Each sub-sample was immediately sealed in the plastic bag after squeezing out the air, and stored in the refrigerator at 4  C. Before analysis, the samples were dried at 25  C, ground with pestle and mortar until all particles passed through a 200 mesh nylon sieve. 2.2. Soil chemical analysis pH values were determined at a 1: 5 (soil: water, w/w) ratio using a digital ion meter (PXS-215, RIDAO Instrument Co., Ltd, China) (Qiang et al., 2006). Soil particle size was analyzed by malvern laser particle size analyzer (MS2000MU) (Uner et al., 2005). Soil porosity and water content of soil were referred to Determination of forest soil water – Physical properties (LY/T 1215-1999). Soil organic matter was measured using the Walkley and Black method (Walkley and Black, 1934). For each sample, approximately 3.00 g soil was digested in a high-pressure microwave system (XT-9900A, Xintuo Analytical Instruments Co., Ltd, China) (Fu et al., 2014). Before the digestion process, 5 mL of HNO3, 5 mL of HF, and 3 mL of HClO4 were mixed with the soil samples in a polytetrafluoroethylene vessel. After the microwave process, the vessel was taken out, uncovered, and heated to expel the acids until the residue was a viscous colorless or light yellow fluid. After adding 10 mL of deionized water, the crucible was then gently heated to dissolve the residues. 1 mL of HNO3 was added to the final solution and made up to 50 mL with deionized water. The concentrated solutions of HCl, HNO3, HF and HClO4 were used in the process. The concentration of heavy metals in the soil samples were determined by inductively coupled plasma - atomic emission spectrometry (ICP-AES) (Cui et al., 2017). 2.3. Data evaluation The single factor contaminant index and the Nemerow composite index were applied to assess heavy metal pollution (Bin et al., 2012). The formulas are as follows: Pi ¼ Ci/Si; PN ¼ {[(Ci/Si)max þ (Ci/Si)ave]/2}1/2 Ci is the measured concentration of pollutant i; Si is the background value or control land or standard values of pollutant i. Chinese background value (AM) (Li, 2014) is selected as Si. Multivariate statistical analysis was used to identify the relationship and the pollutant sources of different heavy metals. In this study, all statistical analysis in this paper was carried out using SPSS 12.0. The statistical differences in heavy metal concentrations among samples were determined using one-way ANOVA. 3. Results and discussion 3.1. Physical and chemical properties

Fig. 1. Study area in this research.

Statistical data of the soil properties are shown in Table 1. Soil particles are mainly consist of sand, 19.2% medium sand, 43.5% fine sand and 3.68% 3.68% clay, with low water holding capacity (Chen et al., 2006). Particle size determines the migration of particles in runoff erosion process, small particle size causes great erosion rate (Zamani and Mahmoodabadi, 2013). The pH values demonstrate that the soil in the study area is saline alkali soil (Richards, 1968). Soil porosity in tailings is much lower than normal range of soil (55%e75%). Low soil permeability seriously affects respiration of

X. Zhang et al. / Journal of Cleaner Production 172 (2018) 475e480


Table 1 Physical and chemical properties of Anshan tailings.

pH Water content of soil (%) Organic matter (%) Soil porosity (%) Medium Particle-D50 (um) Specific surface area (m2/g)





Normal value

8.32 1.55 1.04 36.92 110.77 0.128

8.98 2.31 1.26 52.44 173.20 0.174

8.65 1.93 1.15 44.68 141.985 0.151

0.33 0.38 0.11 7.76 31.215 0.023

Alkaline soil pH 7.5e8.5 Drought < 15% Barren < 1.5% 55%e75% / /

plant and microbe. There is few plants in tailings mainly because of low water content (1.93%) and little organic matter (1.15%). Some organic matter have large cation exchange capacity and are prone to exchange on the particle surface and form an organic wrapped layer with heavy metals, which can absorb and complexate heavy metals, thereby fixing heavy metals. The interaction of organic matter with heavy metal has great influence on the behavior of heavy metal in soil (Egli et al., 2010). Anshan tailings with little organic matter may aggravate the migration of heavy metals. 3.2. Total heavy metal concentrations The mean values of total heavy metal concentrations show that the mean order of their abundance was: Zn (33 mg/kg), Cr (29 mg/ kg), Cu (20 mg/kg), Pb (9.5 mg/kg), Ni (6.0 mg/kg), Co (<5 mg/kg), Cd (0.066 mg/kg), Hg (0.003 mg/kg). The background value (AM) of Liaoning Province, China and the Grade II criteria of the Chinese environmental quality standard for soil were used for further research (Li et al., 2015). None of the concentrations of the heavy metals for each soil sample exceeded the Grade II criteria. However, the mean values of heavy metal in this study are relatively higher or close to the background values, which indicates notable enrichment of these metal contaminants in the tailings soil. So we chose top four elements Zn, Cr, Cu and Pb for risk assessment. Taking into account the high toxicity with low content, Cd was incorporated into the study. This finding suggests a potential risk to soil environmental quality from these heavy metal contaminants, and further monitoring and management are required to avoid additional pollution.

complicated rules with the increasing depth, which indicates physical and chemical properties of soil may significantly affect the migration of the two heavy metals (Slavich et al., 2013). Zn, Pb and Cr showed similar rules, the concentrations declined (0e40 cm) after rising (40e80 cm) and then declined (80e100 cm), which might be related to properties and forms of the three heavy metals. According to the proportion, capability of migration was obviously different. Zn, Cr and Pb had stronger capability of migration compared with the proportion of Cu. When the depth was over one meter, migration ability decreased. Heavy metals have strong capability to be absorbed onto clay minerals. Sediments having high content of clay minerals often lead to low redox potential environment, thus have markedly decreased oxygen exchange ability compared to the coarse sediments. Heavy metal can migrate together with the course particles in the sediment (Zafra et al., 2011). Acid rain in Liaoning, china mainly caused by sulfuric acid type-based has great impact on heavy metal in the soil. Acid rain not only exacerbate migration of heavy metal, but also result in activating heavy metal in soil, finally cause serious toxic effects in water (Zhang et al., 2017). Considering strong permeability and poor adsorption capacity of tailings soil, groundwater is prone to be polluted, so heavy metals of tailings should be monitored and properly handled (Rashed, 2010). As shown in Fig. 2, through the single factor of five heavy metals and composite index analysis of the five profiles, five heavy metals had different toxic effect and caused deep soil pollution. Migration of Cu and Pb impacted on deep soil seriously and made major contribution to PN because of high concentrations. Concentration of Cd was low, but slight change of Cd had a remarkable affect on soil pollution. P4 was seriously polluted (PN of P4 was highest), indicating that heavy metals had migrated downward significantly

3.3. Vertical distribution of heavy metals The vertical distribution patterns of heavy metals (Cu, Zn, Pb, Cd and Cr) in tailings are shown in Table 2. From the top of the profiles to the bottom, the highest concentrations of Cu, Zn, Pb, Cd and Cr generally appear in the range of 40e80 cm. These elements generally decrease with increasing depth below 80 cm. This finding suggests that Cu, Zn, Pb, Cd and Cr are enriched along with increasing depth of soil and showing a fluctuating and downward tendency from the top to the bottom of the soil profiles, finally to impact on ecological security of different profile in soil (Luo et al., 2010). Five heavy metals exhibited downward trend of migration, but with different migration rules. Cu and Cd conditioned

Fig. 2. Vertical distribution of pollution index.

Table 2 Concentration of heavy metals in vertical direction. (mg/kg)






(AM) P1 P2 P3 P4 P5

22.6 29.67 12.66 30.33 11.67 15.75

74.2 15.42 ± 2.85 5.33 ± 1.28 16.92 ± 3.11 78.25 ± 9.43 19.08 ± 3.79

26 10.33 ± 1.97 8.75 ± 1.12 30.92 ± 4.34 39.66 ± 8.56 9.50 ± 2.28

0.097 0.031 0.037 0.028 0.128 0.051

61 26.51 19.58 27.75 29.42 25.17

± ± ± ± ±

3.62 3.41 4.98 2.05 2.77

± ± ± ± ±

0.005 0.008 0.006 0.024 0.011

Total ± ± ± ± ±

4.63 3.31 6.05 3.17 2.93

81.947 46.37 105.945 159.126 69.551


X. Zhang et al. / Journal of Cleaner Production 172 (2018) 475e480

Table 3 Concentration of heavy metals in horizontal direction.










(AM) 1 2 3 4 5 6 7 8 9 10

22.6 23.67 ± 4.02 11.08 ± 1.43 13.58 ± 1.91 8.21 ± 1.48 11.08 ± 1.66 8.50 ± 0.94 8.21 ± 1.43 7.26 ± 0.79 13.92 ± 2.16 12.67 ± 1.51

74.2 27.08 15.66 11.75 14.58 12.25 13.42 14.42 14.83 18.67 56.50

26 7.14 ± 1.01 3.18 ± 0.55 5.56 ± 0.88 0.79 ± 0.12 3.96 ± 0.55 5.56 ± 0.92 3.97 ± 0.52 4.76 ± 0.73 8.75 ± 1.02 23.20 ± 2.78

0.097 0.068 0.007 0.004 0.078 0.031 0.024 0.026 0.023 0.011 0.042

61 27.92 14.29 21.64 18.59 21.33 21.30 21.70 20.08 26.17 30.92

± ± ± ± ± ± ± ± ± ±

3.79 2.13 1.27 1.65 1.68 2.11 1.87 1.53 2.39 7.58

within 1 m depth. Migration trend decreased beyond 1 meter but still impacted on deep soil. Migration ability decreased when depth was more than 1 m. Considering the huge amount of heavy metals in tailings, vertical migration could impact the deep soil and contaminate groundwater. PN increased obviously from P2 to P3 due to high concentration and strong migration capability of Pb and Cu. Cd migrated dramatically from P3 to P4. Concentration of Cd was lowest but effect of Cd was significant because of high toxic effect. Trend of PN was consistent with total amount of heavy metals, showing a positive correlation (R ¼ 0.914) but not exactly the same. These results indicate that some trace concentration of heavy metals had huge influence on environmental safety (Massadeh et al., 2008).

± ± ± ± ± ± ± ± ± ±

0.009 0.001 0.001 0.008 0.004 0.002 0.002 0.003 0.001 0.006

Total ± ± ± ± ± ± ± ± ± ±

3.74 2.15 2.68 2.16 3.81 2.88 3.04 2.49 3.17 4.42

85.877 44.217 52.536 42.247 48.653 48.799 48.3157 46.956 67.512 123.327

metals, these three elements appeared to be stable under anaerobic conditions but labile under aerobic conditions. Cr was the most mobile element, whereas Cu was the least mobile element. Heavy metals show strong affinity with iron oxides in the environment, especially in iron tailing, the reduction of iron oxides has great impact on migration of heavy metals (Ermakov et al., 2016). Heavy metal can be transported together with redox-sensitive elements and enriched near the sedimentewater interface. Both particle size and depositional effect can influence the variations in heavy metals concentrations in migration process. As shown in Fig. 3, Migration of Cr and Cu made higher contribution to PN because of high concentrations. Pollution index of Zn and Pb were lower. 9th and 10th point located in Transportation area, were polluted seriously. Pollution index was found highest in

3.4. Horizontal distribution of heavy metals As shown in Table 3, concentration of five heavy metals is closely related to the position of each sampling point. From the 1st to 8th sampling points, concentration of heavy metals decrease with increasing distance from the tailings, however, decreasing trend is not obvious. Concentration of heavy metals is high in the 9th and 10th sampling points. 10th point is close to transport road. 10th point becomes a new source of pollution due to the falling tailings from trailer (Licsk et al., 1999). Five heavy metals had certain capability of migration, but the migration rules were quite different. Migration capability of Cu and Cd was poor, which was positively correlated with the distance. Cr showed strong migration capability within a certain distance. Zn and Pb showed stronger migration capability and complex regulation which might be related to soil properties (Matos et al., 2001). After investigation, the trailer took no protective measures easily leading to fall. So the trailers need to be modified and covered. As revealed by Table 3, Cr, Pb and Zn were easier to mobilize and release under varied reducing conditions. Meanwhile, compared with other heavy

Fig. 4. Bioremediation efficiency of Amaranthus blitoides, Kochia scoparia and S. nigrum.

Fig. 3. Horizontal distribution of pollution index.

X. Zhang et al. / Journal of Cleaner Production 172 (2018) 475e480

Tailings area followed by Transportation > Fringe. The mine tailings was the pollution source of heavy metals released to the environment. Five heavy metals had similar migration rules from 1st to 8th sampling point. Total concentration and PN decreased with increasing distance. However, total concentration of heavy metals of 4th point was low, but the PN was high because of increasing concentration of Cd. Low concentration of Cd has significant toxic effects (Miao et al., 2005). Curve of total concentration and PN was inconsistent (R ¼ 0.563) which indicated that trace concentration of heavy metal with high toxicity seriously polluted the environment and can't be ignored in pollution assessment. Considering the huge amount of heavy metals in tailings, horizontal migration could pollute surroundings (Zhao et al.). 3.5. Role of local plant in tailings Soil of tailings has bad physical and chemical properties with high pH and little organic matter. It is not conducive to plant growth. The dominant species in Anshan tailings is Amaranthus blitoides, which grows on barren-drought sandy soil. As wild type, Amaranthus blitoides has strong vitality and well adapts to local conditions (Sibony and Rubin, 2010). Amaranthus blitoides, Kochia scoparia and S. nigrum was used for phytoremediation in Anshan mine tailings. Pb, Zn, Cu and Cr, heavy metal elements with higher concentrations, was selected and tested in bioremediation analysis. Previous research showed that Kochia scoparia and S. nigrum can tolerate terrible environmental condition and has good effect on removal of heavy metal. As shown in Fig. 4, Amaranthus blitoides, Kochia scoparia and S. nigrum showed similar regularity of remediation. Remediation effect was increased with the time consuming. Remediation efficiency tend to be stable when reach to the saturation of hyperaccumulation. Amaranthus blitoides showed better removal rate on heavy metal than Kochia scoparia and S. nigrum. Amaranthus blitoides can accumulate and effectively remove the heavy metals in soil. The highest removal rate was found in Pb followed by Cu > Zn > Cr. Amaranthus blitoides can be applied to heavy metal removal and ecological restoration saline soil of Iron tailings (Sibony and Rubin, 2003). 4. Conclusions Anshan tailings polluted by heavy metal had become source of pollution. We couldn't accurately assess the contamination degree and migration capability rarely based on concentration because of toxicity differences. Although concentration is low, some kinds of heavy metals with high toxicity seriously polluted the environment. Therefore it is more valuable to apply pollution index for assessment. In this research, the mean concentrations of heavy metals were Zn (33 mg/kg), Cr (29 mg/kg), Cu (20 mg/kg), Pb (9.5 mg/kg), Ni (6.0 mg/kg), Co (<5 mg/kg), Cd (0.066 mg/kg), Hg (0.003 mg/kg). The migration and distribution of heavy metals (Cu, Zn, Pb, Cd, and Cr) were chosen for investigation and further research by measuring concentrations and toxicity of each element. Five main pollutants (Cu, Zn, Pb, Cd, and Cr) with certain migration capability pose a threat to groundwater and surroundings. The study found that contamination of the tailings and transportation area was serious. Regular monitoring and ecological restoration are necessary for tailings. Amaranthus blitoides can effectively remove the heavy metals and can be used for situ - phytoremediation. The transformation characteristics of heavy metals in Amaranthus blitoides need to be comprehensively research in the future. Acknowledgments This research was funded by Ministry of Science and Technology


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