Introduction

To maintain the soil ecological balance, the concentration of heavy metals such as Cr, Ni, Cd, Cu, Pb and As must be low. However, the concentration of these elements is increasing with the increase in anthropogenic activities (Arenas-Lago et al. 2013). Soil is a natural dynamic body essential for human life, and it should be taken into account due to its high potential for absorbing heavy and toxic metals (Blaser et al. 2000; Vesali Naseh et al. 2012). In recent decades, the soil pollution by heavy metals caused by industrialization and urbanization has received special attention (Belis et al. 2013; Liu et al. 2014; Huang et al. 2015; Wang et al. 2015). Heavy metals pollution in urban areas stems from different sources such as industrial activities, power stations, mines, fossil fuels combustion and wastes disposal (Krishna and Govil 2007; Wei and Yang 2010). In mining areas, the disposal of non-recyclable mineral wastes produced from mineral ore concentrates is responsible for soil contamination. Concentration of heavy metals in soil increases the potential of risk and adverse effects in soil ecosystems (Cui et al. 2004; Li et al. 2009a, b). Different enrichment calculation methods are used to assess the heavy metals pollution in soil (Farsad et al. 2011). Some of these methods are enrichment factor (EF), contamination factor, geo-accumulation index, pollution index (IPOLL) and level of pollution Ln (LP). EF indicates the enrichment of soil contamination compared to the pre-industrial soil in the same environment (Dias et al. 2014).

Chadormalu iron ore mine is located at the center of Iran, 180 km northeast of Yazd and 85 km north of Bafgh, with five production lines and annual capacity of 9 million tons of steel production through direct reduction method. The solid wastes area of Chadormalu contains heavy metals in an area of 2546 km2 6 km away from Chadormalu iron ore processing unit with a population of 4197 people. The population density in the mine is 1.65 per km2 (Fig. 1). Saghand village and Bahabad county, with distances of 40 km and 60 km, are the nearest and furthest residential places to the mine, respectively. Population densities in these areas are 15.8 and 3.37, respectively. The annual average wind speed is 52 km/h, and the annual average rain and snowfall is 107 mm in the area. The amount of heavy metals in solid wastes and their contamination were assessed in this study. The wind disperses the solid waste particles in the surrounding area, and a wide area of solid wastes actually provides an inactive ecosystem. The ways of preventing the dispersion of particles containing heavy metals, reducing the amount of heavy metals and providing a sustainable desert ecosystem have been considered in this study.

Fig. 1
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Soil and plant sampling locations at Chadormalu Tail Basin

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Materials and methods

Study area and sampling

Water is recovered for reuse from slurry-like mineral wastes from the ponds located at the southeast of Chadormalu. The remaining solids are dried over time. In order to create an ecological stable equilibrium, 25-cm-thick soil was poured on solid wastes to let the local winds disperse the seeds to grow wildflowers. The purpose of this study was to investigate the amount of waste material contaminants transferred into the soil and the role of wildflower in reducing soil contamination and also to assess the effects of anthropogenic and natural factors on soil contamination.

The soil and plant were taken from 20 different points and combined together. A total of 12 compound samples of soil and 12 compound samples of plant were obtained. Soil samples were dried in a dryer at 40 °C for 36 h (Mollazadeh et al. 2013).

Measurement of soil physicochemical properties

The particle size distribution of the samples was measured by sieve analysis. Using sieves and ASTM, soil particles were classified into slime (< 300 mic), sand (> 300 mic) and gravel (> 2 mm). Slime and plant roots were micronized by disk mill. Soil pH was measured in a solution with the soil/water ratio of 1:5. The suspension was left standing for a while and then its pH was measured by a pH meter. For organic matters in soil samples, the samples were heated in a muffle furnace at 450 °C for 4 h (Glasby and Szefer 1998) and then the loss on ignition (LOI) was measured. Moreover, the analytical grade laboratory chemicals were used to analyze the samples and the deionized water (conductivity ≤ 4 µs/cm) was employed to prepare solutions. About 2 g of soil samples and powdered plant roots were dissolved in 5 ml of normal hydrochloric acid (0.53 N) in a clean glass container, and the obtained mixture was digested using microwave digestion system. Finally, the extracted solutions were filtered through syringe filter (DISMIC–25HP PTFE, pore size = 0.45 µm) (Toyo Roshi Kaisha, Ltd, Tokyo, Japan) and stored in 50-ml polypropylene pipes (Nalgene New York) (Arenas-Lago et al. 2014).

Instrumental analysis and quality control

Inductively coupled plasma mass spectrometry (ICP-MS-HP4500) was used to determine heavy metals contents in soil and plant. In order to prepare the calibration curve, 10 ppb solution of Y, Ce, Tl and Li was used. The calibration range for all the elements was 0.1 to 50.0 ppb, and this level was used for all of them. The mother solution (100 ppm) was from Merck and Chem Lab Companies. These solutions covered a wide range of metals. The results of heavy metals analysis in soil and plant are provided in Table 1.

Table 1 Metal contents in soils and plants from Tail Basin
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Data calculation

Enrichment factors (EF)

The enrichment factor (EF) is a tool for differentiating between the heavy metals from anthropogenic activities and those from natural source. The concentration of immobile element in the sample and the reference sample was used in calculating EF. Knowing that Sc and Al are often considered to be immobile in soil, Al was considered immobile in this study. EF is calculated using Eq. 1:

$$ {\text{EF}} = \left( {C_{\rm{M}} /C_{\rm{Al}} } \right){\text{Sample}}/\left( {C_{\rm{M}} /C_{\rm{Al}} } \right){\text{STD}} $$
(1)

where (CM/CAl) sample is the ratio of heavy metals concentration (CM) to aluminum concentration in soil and (CM/CAl) STD is the same ratio in the pre-industrial or standard sample.

The EF value of 1 for all samples places them in a non-contaminated range. EF values of < 2, 2–4, 4–16, 16–32 and > 32, respectively, indicate no contamination, low contamination, moderate contamination, high contamination and very high contamination (Table 2).

Table 2 Terminologies for contamination classes on single and integrated indices
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Contamination factor (C if )

Contamination factor (Cif) is the ratio between the metal content in soil (Cm) and the standard concentration levels as suggested by Hakanson (1980) and can be calculated by Eq. 2.

$$ \left( {C_{\text{STD}} } \right)C_{f}^{i} = \frac{\rm{Cm}}{\text{CSTD}} $$
(2)

The degree of contamination is classified as: low contamination (Cif < 1), moderate contamination (1–3), considerable contamination (3–6) and very high contamination (Cif ≥ 6) (Rashed 2010) (Table 3).

Table 3 Hakanson contamination classes
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Transfer factor (TF)

Transfer factor indicates the movement of contaminant from the soil to the plant as presented by Eq. 3.

$$ {\text{TF}} = \frac{{C_{\text{M}} }}{{C_{\text{P}} }} $$
(3)

where CM is the concentration of metal in soil and CP is the concentration of metal in plant.

Geo-accumulation Index (I geo)

Igeo is used to assess the metal contaminant in sediments and soils by comparing the analyzed concentration of metals with pre-industrial levels. Igeo proposed by Muller (1969) is calculated using Eq. 4.

$$ I_{\text{geo}} = {\text{Log}}_{2} \frac{\text{Cm}}{{1.5 C_{\text{STD}} }} $$
(4)

where CM and CSTD are the concentrations of metal in current and pre-industrial soil samples, respectively, factor 1.5 is used to eliminate possible variations in reference values and to eliminate anthropogenic effects. The geo-accumulation index (Igeo) was defined as: Igeo ≤ 0.42 (unpolluted), 0.42 < Igeo ≤ 1.42 (less polluted), 1.42 < Igeo ≤ 3.42 (moderately polluted), 3.42 < Igeo ≤ 4.42 (strongly polluted) and Igeo > 4.42 (extremely polluted). The geo-accumulation index (Igeo) is classified into 6 classes (Table 4).

Table 4 Muller contamination classes
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Pollution index (I POLL)

IPOLL index indicates the degree of metal contamination which can be calculated by Eq. 5 (Karbassi et al. 2008).

$$ I_{\text{POLL}} = {\text{Log}}_{2} \frac{\text{Cm}}{{1.5 C_{\text{STD}} }} $$
(5)

where CM and CSTD are the concentrations of metal in current and pre-industrial soil samples, respectively. Classification of IPOLL is the same as that of Igeo.

Modified contamination degree (mcd)

Modified contamination degree (mcd) is a modified form of the Hankanson equation for calculating the overall degree of contamination at a given site. Contamination degree is the final index for estimating soil contamination in terms of the presence of various elements and can be calculated by Eq. 6.

$$ {\text{mcd}} = \frac{{\mathop \sum \nolimits_{i = 1}^{n} C_{f}^{i} }}{n} $$
(6)

where Cif is the contamination factor for each element and n is the total number of the analyzed elements. Modified contamination degree is classified as: mcd < 1.5 (no contamination), 1.5 ≤ mcd < 2 (low contamination), 2 ≤ mcd < 4 (moderate contamination), 4 ≤ mcd < 22 (high contamination) and mcd ≥ 22 (extreme contamination).

Pollution level (LP)

Considering the specific characteristics of the soil samples taken from the iron ore tailing pond, Cif, Igeo, IPOLL and mcd cannot provide reliable results because of their restricted range and high concentrations of elements. Therefore, it was decided to develop an index based on math principles and simulation using the data obtained from TF and IPOLL to be applicable to all types of soil from other mines and to similar projects, with the capability to assess high concentrations of contamination. The new index was named level of pollution, Ln (LP), and it was presented as an equation in Neperian logarithm form (Eq. 7):

$$ {\text{Ln }}\left( {\text{LP}} \right) = 0.0519 \times {\text{TF}} + 0.6931 \times I_{\text{POLL}} {-} \, 0.163 $$
(7)

Classification of pollution level (LP) is: Ln (LP) < 1 (no contamination), 1 ≤ Ln (LP) < 2 (low contamination), 4 ≤ Ln (LP) < 6 (high contamination) and Ln (LP) > 6 (extreme contamination).

Statistical analysis

The data were analyzed using SPSS 2014 (SPSS, ASA), and cluster analysis was used for soil and plant separately and in compound. In this study, cluster analysis has been widely used to analyze the data and the relationship between the metal contents of soil and plant.

Results and discussion

Metal contents in soil and plant samples are provided. The LOI range in soil samples is in the range of 10% to 13%. Some studies indicated that the organic content in the soils from Iran was less than 5% (Saeedi and Karbassi 2006). Therefore, the high value of organic contents in the soil can be attributed to the high level of BOD (Saeedi and Karbassi 2006; Karbassi et al. 2008; Parvaresh et al. 2011; Mollazadeh et al. 2013). High concentration of Ca (about 6%) can be related to the presence of lime in the soil. The percentile of anthropogenic and natural metal contents has been shown in Table 5.

Table 5 Percentile of lithogenous and anthropogenic portion of metals in soil from Tail Basin
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Percentile of lithogenous portion

Ti (100%) > Al (99.95%) > Fe (99.93%) > Cr (99.89%) > V (99.88%) > Sc (99.85%) > Zn (99.77%) > Cu (99.54%) > Co (99.28%) > Mn (98.80%) > Ca (97.14%) > Mo (89.19%)

Percentile of anthropogenic portion

Mo (10.81%) > Ca (2.86%) > Mn (1.20%) > Co (0.72%) > Cu (0.46%) > Zn (0.23%) > Sc (0.15%) > V (0.12%) > Cr (0.11%) > Fe (0.07%) > Al (0.05%) > Ti (0%)

This chemical partitioning shows that MO and Ca are derived from anthropogenic sources. Some studies show that about 10% of each metal component can be originated from anthropogenic source (10% of the total metal content is representative of the anthropogenic portion) (Saeedi and Karbassi 2006; Karbassi et al. 2008). Therefore, in this study, the anthropogenic portions of Mo, Ca, Mn and Al are considered to be normal. The calculated indices values for metals are shown in Table 6. The restricted range of IPOLL, Igeo and EF made them inappropriate to be used for the analysis of the data obtained in this study. The plant root absorbed water, minerals and food. TF values in Table 7 show the importance of plant in absorbing heavy metals from soil. They also showed no anthropogenic pollution, implying that the pollution was naturally formed with no intervention of human activities.

Table 6 Pollution intensity in soils from Tail Basin
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Table 7 Transfer factor in soils and plants from Tail Basin
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Cluster analysis identified a positive correlation among the metal components in soil samples (Fig. 2). Most of this correlation is related to Fe, Co, Cr, Pb, Al, Sc and Ca. Fe, Co and Cr, Pb portions also have the same behavior. Cluster analysis of soil and plant showed a positive correlation among Fe, Co, Al, Sc, Ti and As (Fig. 3). The interaction of these elements in soil and plant revealed the important role of plant in reducing the pollution. Cluster analysis also showed that Fe, Cr, Pb, Mo, Co, As, Mn and Al were interdependent in the plant (Fig. 4).

Fig. 2
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Dendrogram of cluster analysis for soil of Tail Basin

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Fig. 3
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Dendrogram of cluster analysis for soil and plant of Tail Basin

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Fig. 4
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Dendrogram of cluster analysis for plant of Tail Basin

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Conclusion

Solid wastes from iron ore operations have resulted in vast areas of dried tailing ponds during the last two decades. The results of this study showed that pouring soil on these ponds and the growth of wildflowers on them prevented the spread of contamination. Plant played an important role in heavy metals uptake. Considering this restriction, all the data were placed in no pollution range. Therefore, a new index called Ln (Lp) was developed and used as a solution. The obtained results revealed that all the studied elements, except for cobalt with low pollution, were in the range of no pollution. For Igeo, IPOLL and EF indices, all the elements were in the range of no pollution. Modified degree of contamination also showed no contamination.