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Journal of Resources and Ecology >

2023 , Vol. 14 >Issue 4: 683 - 691

DOI: https://doi.org/10.5814/j.issn.1674-764x.2023.04.001

Environmental Management of Mines

Assessment of Soil Heavy Metal Pollution in the Dump of a Western Inner Mongolian Coal Mine

  • LIU Ruiyao , 1, 2 ,
  • QIN Ru 3 ,
  • SI Qing 4 ,
  • XU Li , 1, 2, * ,
  • WANG Han 1 ,
  • CONG Longyu 1, 2 ,
  • LIU Zemeng 1, 2
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  • 1. College of Desert Control Science and Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China
  • 2. Key Laboratory of State Forest Administration for Desert Ecosystem Protection and Restoration, Hohhot 010018, China
  • 3. Qiongzhong County Environmental Protection Monitoring Station, Qiongzhong, Hainan 572931, China
  • 4. Ordos Forestry and Grassland Development Center, Ordos, Inner Mongolia 017000, China
*XU Li, E-mail:

LIU Ruiyao, E-mail:

Received date: 2022-08-10

  Accepted date: 2023-02-20

  Online published: 2023-07-14

Supported by

The Inner Mongolia Autonomous Region Science and Technology Major Project(2020ZD0020-2)

Key Research and Development Program of China(2017YFC0504402)

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Abstract

Exploring the status and sources of heavy metal pollution in the soil of the dump in Wuhai City, western Inner Mongolia, is of great significance. This study selected a sunny slope, a half-sunny slope and shady slope with plots of (A) Astragalus adsurgens + Agropyron desertorum + Elymus, (B) Caragana korshinskii+Astragalus adsurgens + Agropyron desertorum + Lolium, and (C) Medicago sativa + Artemisia ordosica+Astragalus adsurgens + Brassica juncea, and a naturally repaired slope for comparison, yielding a total of 10 types of sample plots. The soil heavy metal pollution levels and the potential ecological harm were assessed by the process of measuring the contents of seven heavy metal elements (As, Hg, Pb, Cr, Cd, Cu and Zn) in dump soil as a single factor pollution index, and then the comprehensive pollution index, potential ecological risk index and the mine soil heavy metal pollution sources were explored by correlation analysis and principal component analysis. The results showed three important aspects of the pollution levels, impacts and sources in this dump. (1) The heavy metal contents in Qifeng dump had little influence on the plant community composition type and no clear relationship with the slope direction, but the Cr content in the manually configured sample was significantly reduced compared with that in the naturally restored slope. The contents of Hg and Pb exceed their soil grade I standards, and Cd exceeds the National Grade II standard compared with the soil background values of Inner Mongolia. The As, Hg, Pb and Cd levels of the dump exceed their standards, so there is a certain degree of heavy metal accumulation in the soil of the dump. (2) The single factor pollution index in descending order is Cd > As > Pb > Cr > Hg > Cu > Zn, and all the dump samples are polluted by Cd. According to the Nemerow composite index, the heavy metals in the soil of the dump are at middlingor moderate pollution levels. The potential ecological risk index values of the individual heavy metals were in the order of Cd > As > Hg > Pb > Cr > Cu > Zn, so Cd was the most important potential ecological risk factor ranging from 108.650 to 180.600. The comprehensive potential ecological risk index ranged from 114.665 to 188.792, indicating that 50% of the plots were at slight or moderate potential ecological risks, respectively. According to the different evaluation methods, Qifeng dump is polluted by heavy metals, and the pollution degree and ecological risk associated with Cd are much higher than those of the other heavy metals. Therefore, timely control measures should be taken for Cd. (3) The correlation analysis and principal component analysis showed that Hg, Pb and Cd came from road coal dust diffusion and exhaust emissions, while Cu, Zn and Cr came from transportation and agricultural production activities, and As came from coal combustion pollution.

Key words： open-pit mining area; waste dump of mine

Cite this article

LIU Ruiyao , QIN Ru , SI Qing , XU Li , WANG Han , CONG Longyu , LIU Zemeng . Assessment of Soil Heavy Metal Pollution in the Dump of a Western Inner Mongolian Coal Mine[J]. Journal of Resources and Ecology, 2023 , 14(4) : 683 -691 . DOI: 10.5814/j.issn.1674-764x.2023.04.001

1 Introduction

Mineral resources play an important role in the social and economic development of our country. Large-scale mining brings not only economic benefits but also a series of ecological and environmental problems (Hu, 2019), such as surface excavation, subsidence, occupation, vegetation destruction, soil heavy metals pollution and others (Lv and Lu, 2009). The stripped materials from open pit mining are concentrated and stacked to form a dump (Huang et al., 2007; Wang et al., 2018). Fly ash and waste residue in the dump contain refractory and toxic heavy metal components. Through the actions of wind and rain water leaching, heavy metals gradually migrate and pollute the surrounding soil (Chen et al., 2017; Wu et al., 2018). Preventing their entry into the soil is difficult, so they gradually migrate to plants and flow through the food chain to human beings, further affecting the whole ecosystem (Xu et al., 2007). With the improvement of society’s awareness of environmental protection, the problem of heavy metal pollution in mining area soil has become a major research focus. Many scholars at home and abroad have conducted a great deal of research on soil heavy metal pollution in mining areas. For example, Benhaddya and Hadjel (2014) found that heavy metal pollution has certain spatial distribution characteristics in Algeria, and that study provides a basis for the control of heavy metal pollution in similar areas. Bhuiyan (2010) found that the arable land around a mining area in Bangladesh was obviously polluted by heavy metals Mn, Zn, Pb and Ti. Li et al. (2007) considered that some human factors, dominated by mining activities, are the most important factors affecting the accumulation of heavy metals in soil. Li et al. (2021) found that the two mining areas in the study area are contaminated by heavy metal Cd and seriously polluted. Wang et al. (2020) found that there are no industrial activities in the study area other than mining activities, which indicates that the mining activities have led to the accumulation of heavy metals in the soil.
Wuhai City is a typical industrial city that is based on the development of coal resources and located at the eastern end of the northwestern arid desert area. Coal gangue and waste residue were filled in and flattened during reclamation in the Qifeng Open-pit Mine, which played a certain role in rehabilitating the land, but inevitably expanded the contact between the soil and the coal gangue, resulting in the gradual accumulation of heavy metals in the soil (Zhang, 2006). Qifeng Coal Mine is an open-pit mining operation, and the study area located in the main downwind direction, leading to coal dust diffusion in the production and coal transportation process, which can lead to the accumulation of heavy metals. Most research on the soil heavy metal pollution in mining areas in China is concentrated in the south. The soil nutrients and vegetation patterns in Inner Mongolia open pit mines are sometimes involved, but few studies on soil heavy metals in open pit mining sites in Inner Mongolia have been carried out. Based on this shortage of relevant research, the soil of Qifeng Open-pit Mine was selected as the research object, and the content characteristics of soil As, Hg, Pb, Cr, Cd, Cu and Zn in sunny, semi-sunny and shady slopes, with plots of (A) Astragalus adsurgens + Agropyron desertorum + Elymus, (B) Caragana korshinskii + Astragalus adsurgens + Agropyron desertorum + Lolium, and (C) sativa + Astragalus adsurgens + Brassica juncea were analyzed. Three indexes, the single factor pollution index, Nemero comprehensive pollution index and potential ecological risk index, were selected for pollution evaluation. On this basis, the possible sources of heavy metals were analyzed by correlation analysis and principal component analysis in order to provide a scientific basis for the treatment and ecological restoration of heavy metals in contaminated soils in local or similar mining areas.

2 Study area

Qifeng Open-pit Mine is located in the Hai Bo Wan area of Wuhai City with geographical coordinates of 39°38′21- 39°39′49N, 106°52′57-106°53′39E. Wuhai City has an arid climate and limited precipitation, so it belongs to the temperate arid continental monsoon climate. The annual average temperature is 9.3 ℃, the annual evaporation is 3289 mm, the annual precipitation is 159.88 mm, and the relative humidity is 41%. The main soil types are desert calcium soil and wind-sand soil. In order to realize the reclamation of mine vegetation, the waste soil, abandoned stone and gangue produced in the process of stripping during opencast mining are filled in and flattened. The surface of Qifeng Open-pit Mine is covered with a 30-40 cm layer of soil. On the one hand, the air is isolated in the dump to eliminate the risk of reburning, while on the other hand, the basic conditions for plant growth are created. In 2017, the reconstruction of vegetation in Qifeng was carried out to complete the greening of the slope and the restoration of the surrounding ecology over an area of 27 ha. The Qifeng dump land is barren, mostly sandy soil, with an overlay of about 40 cm. The total height of the tatal is about 252 m. The natural slope of the mountain is about 50°. The artificially planted vegetation on the slope of the dump is dominated by herbaceous plants, mainly shrubs and herbaceous vegetation such as Caragana korshinskii, Calligonum mongolicum, Artemisia ordosica, Agropyron desertorum, Astragalus adsurgens and others.

3 Research methods

3.1 Sample collection and treatment

On the basis of detailed field investigations, soil samples were collected in June 2021. The sunny slope, semi-sunny slope and shady slope were selected as control plots, with an Astragalus adsurgens + Agropyron desertorum + Elymus plot, a Caragana korshinskii + Astragalus adsurgens + Agropyron desertorum + Lolium plot, and a sativa + Astragalus adsurgens + Brassica juncea plot; and naturally repaired slopes were selected as control plots according to the plant community configuration and slope direction. The basic characteristics of the sample plots are shown in Table 1. In order to eliminate the differences in soil properties caused by the overlying soil, the thin surface soil was removed as much as possible in order to remove the plant root systems. The 0-20 cm soil samples were randomly collected according to the “S” type 5-point method. First, the sampling position was determined, and a sample was collected at the first sampling site. Four additional sampling sites were then selected within the surrounding 20 m range, and the five resulting soil samples were mixed into one sample. Soil samples of about 1 kg were kept sealed and transported to the laboratory. The soil samples were naturally air-dried in the laboratory, the plant root systems were removed, and the sample was passed through a mm screen and ground.
Table1 Basic characterstics of the sample sites
Sample plot number Plant community allocation Slope direction Latitude and longitude
A1 A. adsurgens+A. desertorum+Elymus Sunny slope 106°52′44.44″E, 39°38′50.67″N
A2 A. adsurgens+A. desertorum+Elymus Semi-sunny slope 106°52′46.88″E, 39°39′3.44″N
A3 A. adsurgens+A. desertorum+Elymus Overcast slope 106°52′53.64″E, 39°39′6.39″N
B1 C. korshinskii+A. adsurgens+A. desertorum+Lolium Sunny slope 106°52′45.31″E, 39°38′50.42″N
B2 C. korshinskii+A. adsurgens+A. desertorum+Lolium Semi-sunny slope 106°52′46.91″E, 39°39′2.72″N
B3 C. korshinskii+A. adsurgens+A. desertorum+Lolium Overcast slope 106°52′54.57″E, 39°39′7.54″N
C1 M. sativa+A. ordosica+A. adsurgens+B. juncea Sunny slope 106°52′49.30″E, 39°38′53.05″N
C2 M. sativa+A. ordosica+A. adsurgens+B. juncea Semi-sunny slope 106°52′48.29″E, 39°38′59.97″N
C3 M. sativa+A. ordosica+A. adsurgens+B. juncea Overcast slope 106°52′54.24″E, 39°39′3.74″N
CK Halogeton arachnoideus +Grubovia dasyphylla Natural restoration of slope 106°52′57.91″E, 39°39′5.04″N
The contents of heavy metals were determined by the Inner Mongolia Agriculture Animal Husbandry and Fisheries Biological Experiment Center. As and Hg were determined by atomic fluorescence spectrophotometry; Pb and Cd were determined by graphite atomic absorption spectrophotometry; and Cu, Zn and Cr were determined by flame atomic absorption spectrophotometry.

3.2 Evaluation methods

Three methods from the Soil Environmental Quality Agricultural Land Pollution Risk Control Standard (GB15618- 2018), i.e., the single factor index method, Neimero comprehensive pollution index method and potential ecological risk index method, were used to evaluate the soil heavy metal pollution levels and potential ecological harm in the dump.
(1) Single factor index method
The single factor index method is designed to evaluate the pollution degree of one single heavy metal factor using the ratio between the measured value and the standard value. Therefore, it can directly characterize the accumulation degree of a single heavy metal element.
Pi=Ci /Si
In the formula, Pi is the heavy metal pollution index of item i; Ci is the measured value of heavy metal elements in item i; and Si is the standard value for the evaluation of heavy metal elements in item i. The evaluation standard values selected for each metal are shown in Table 2.
Table 2 Agricultural land pollution risk screening values (GB15618-2018)
Evaluation indicators As Hg Pb Cr Cd Cu Zn
Evaluation criteria (mg kg-1) 25 3.4 170 250 0.6 100 300
(2) Nemero comprehensive pollution index method
The Nemero comprehensive pollution index method can more comprehensively reflect the average pollution level of heavy metal elements in soil (Jiang et al., 2019).
${{P}_{N}}=\sqrt{\left[ \left( \frac{{{C}_{i}}}{{{S}_{i}}} \right)ma{{x}^{2}}+\left( \frac{{{C}_{i}}}{{{S}_{i}}} \right)av{{e}^{2}} \right]/2}$
In the formula, PN is the Nemero pollution index; $\left( \frac{{{C}_{i}}}{{{S}_{i}}} \right)ma{{x}^{2}}$ is the maximum value of each heavy metal pollution index; and $\left( \frac{{{C}_{i}}}{{{S}_{i}}} \right)av{{e}^{2}}$ is the arithmetic average of each heavy metal pollution index.
(3) Potential ecological risk index method
This method was developed in 1980 by Sweden’s most famous geochemist, Hakanson (1980). Using the environmental ecological effects, toxicology and heavy metal content factors, the evaluation of heavy metal pollution using this method is more focused on toxicology, so it evaluates the potential ecological risk of heavy metals in soil.
$RI=\underset{i=1}{\overset{n}{\mathop \sum }}\,E_{r}^{i}$;$~E_{r}^{i}=T_{r}^{i}\times {{P}_{i}}$;$~{{P}_{i}}={{C}_{i}}/{{S}_{i}}$
In the formula, RI is the comprehensive potential risk index of all of the heavy metals measured; n is the total number of heavy metals measured, and n=7 in this study; $E_{r}^{i}$ is the potential risk parameter of heavy metal i; $T_{r}^{i}$ is a biological toxicity parameter of some heavy metals, and according to the standardized toxicity coefficients of heavy metals established by Hakanson, the corresponding toxicity coefficients of heavy metals for this study are: Cr=2, Ni=5, Cu=5, Zn=1, Pb=5, As=10, Hg=40, and Cd=30; and Pi is the first heavy metal pollution index. The classification criteria of heavy metal pollution in soil are shown in Table 3.
Table 3 Classification standards of soil heavy metal pollution levels
Single factor index method Nemero comprehensive pollution index Potential ecological risk index
Pi Class of pollution level PN Class of pollution level $E^{i}_{r}$ Single factor risk RI Ecological risk index
Pi≤1 Clean PN≤0.7 Clean ≤40 Slight ≤150 Slight
1<Pi≤2 Slightly polluted 0.7<PN≤1 Warning line 41-80 Medium 151-300 Medium
2<Pi≤3 Moderately polluted 1<PN≤2 Slightly polluted 81-159 Relatively high 301-599 Relatively high
Pi>3 Heavily polluted 2<PN≤3 Moderately polluted 160-319 High ≥600 High
PN>3 Heavily polluted ≥320 Extremely high

3.3 Data analysis and processing

The correlation and principal component analyses of heavy metals in soil were carried out using SPSS software, and the sources of the heavy metals were analyzed.

4 Results and analysis

4.1 Heavy metal contents in soils of vegetation communities with different slope orientations

Table 4 shows the data for the soil contents of 7 heavy metals (As, Hg, Pb, Cr, Cd, Cu and Zn) in 10 sample sites of the Qifeng Open-pit Mine drainage site, and the results indicate that the different vegetation communities are not significantly different. The A plot shows that the contents of As, Cd, Cu and Zn in the sunny slope were higher than those in other slope directions, while Pb accumulated more in the shady slope and Cr accumulated in the semi-sunny slope. The contents of Hg, Pb, Cd, Cu and Zn in the B plot showed trends of sunny slope > semi-sunny slope > shady slope, while As accumulated to a greater extent in the semi-sunny slope. Except for the accumulation of Zn on the sunny slope, there were no significant differences in the contents of other heavy metal elements among the different slope directions in the C plot. Generally speaking, the contents of heavy metals in soil had little effect on plant community composition and no clear relationship with the slope direction. Compared with the natural restoration slope, the Cr content of the artificialrestoration slope clearly decreased, but the contents of other heavy metal elements were not different.
Table 4 Soil heavy metal contents (Unit: mg kg-1)
Plot As Hg Pb Cr Cd Cu Zn
A1 13.980 0.219 36.290 25.120 2.941 1.360 1.373
A2 10.500 0.113 32.950 30.870 2.173 1.361 0.519
A3 10.760 0.237 44.520 18.380 2.646 0.512 0.871
B1 9.800 0.243 39.720 21.370 3.612 1.219 4.019
B2 15.130 0.156 38.470 25.500 3.064 0.722 0.964
B3 14.880 0.096 28.220 34.310 2.232 0.301 0.820
C1 13.910 0.151 29.480 33.270 3.171 1.535 7.276
C2 13.730 0.162 33.530 36.370 3.055 1.128 3.437
C3 15.300 0.143 30.090 39.780 2.463 1.061 1.716
CK 11.420 0.174 36.830 34.220 2.859 0.966 1.922
Average value 12.941 0.169 35.010 29.919 2.822 1.017 2.292
Background value① 6.3 0.03 15 36.5 0.04 12.9 48.6
Grade I standard② 15 0.15 35 90 0.2 35 100
Grade II standard③ 25 1.0 350 250 1.0 100 300

Note: ① indicates soil background value in Inner Mongolia Autonomous region; ② indicates soil environmental quality grade I standard (GB15618- 2018); ③ indicates soil environmental quality grade II standard (GB15618-2018), and the corresponding values at soil pH > 7.5 are shown.

The average contents of heavy metals in soil were in the following order: Pb > Cr > As > Cd > Zn > Cu > Hg. The levels of As, Hg, Pb and Cd were 2.05, 5.63, 2.33 and 70.55 times higher than their Inner Mongolia soil background values, respectively, so Cd exceeded the standard the most severely. These results showed that the soil was polluted by Cd, Hg, Pb and As to varying degrees. The Hg and Pb contents surpassed the soil environmental quality grade I standard, while the Cd content exceeded the soil environmental quality grade II standard.

4.2 Heavy metal pollution in soils of different vegetation communities

Based on the agricultural land pollution risk screening value (GB15618-2018) and the contents of As, Hg, Pb, Cr, Cd, Cu and Zn in the soils of different dump sites, the values for the single factor index, Nimeluo index, pollution index and potential ecological risk index of heavy metals in the 10 dump site plots were calculated.
(1) Single factor and Nemero comprehensive pollution index evaluations
Table 5 shows the results of the soil heavy metal pollution index and Nemero comprehensive index for the ten sample sites in the dump. Compared with the classification standards of soil heavy metal pollution levels (Table 3), the order of the single factor pollution index is Cd > As > Pb > Cr > Hg > Cu > Zn. All 10 plots in the dump were polluted by Cd, and all of the plots with values greater than 3 reached the level of severe pollution. The single pollution index values of the other six heavy metal elements did not exceed 1, so they were at the clean level. For the PN, the soil heavy metal pollution levels of the dump are in the moderate and severe pollution levels, because Wuhai City is a city that relies on coal. Many open pit mining sites, coal washing plants and coking plants are congregated, and the dump is in the downwind direction of the mining area. In addition, there are transportation routes on the west side of the dump, so some coal and stripped material will be scattered in the long-term transportation process, and the soil will be polluted by heavy metals under the action of wind erosion, dust drift, leaching and other processes. Combined with the contents of heavy metals in soil and the pollution index values, clearly the main contributing factor of heavy metal pollution in the dump soil is Cd. The B3 and C3 plots were only moderately polluted, while the remaining plots were heavily polluted. The most serious comprehensive pollution index value of 4.312 was in the B1 plot.
Table 5 Soil heavy metal pollution index
Plot PAs PHg PPb PCr PCd PCu PZn PN Class of pollution
A1 0.559 0.064 0.213 0.100 4.902 0.014 0.005 3.520 Heavily polluted
A2 0.420 0.033 0.194 0.123 3.622 0.014 0.002 3.518 Heavily polluted
A3 0.430 0.070 0.262 0.074 4.410 0.005 0.003 3.163 Heavily polluted
B1 0.392 0.071 0.234 0.085 6.020 0.012 0.013 4.312 Heavily polluted
B2 0.605 0.046 0.226 0.102 5.107 0.007 0.003 3.663 Heavily polluted
B3 0.595 0.028 0.166 0.137 3.720 0.003 0.003 2.672 Moderately polluted
C1 0.556 0.044 0.173 0.133 5.285 0.015 0.024 3.790 Heavily polluted
C2 0.549 0.048 0.197 0.145 5.092 0.011 0.011 3.652 Heavily polluted
C3 0.612 0.042 0.177 0.159 4.105 0.011 0.006 2.948 Moderately polluted
CK 0.457 0.051 0.217 0.137 4.765 0.010 0.007 3.417 Heavily polluted
Average value 0.534 0.050 0.206 0.120 4.703 0.030 0.008 3.374
(2) Evaluation of the potential ecological risk index of heavy metals in the soil
Table 6 shows the statistical results of the single potential ecological risk index and the comprehensive potential ecological risk index for the seven heavy metals in the dump according to Hakanson’s potential ecological risk classification standard. Comparing these data with Table 3, the classification criteria of soil heavy metal pollution, shows that the average potential ecological risk index of the individual heavy metals in the dump is Cd > As > Hg > Pb > Cr > Cu > Zn. Among them, the values for Cd were between 108.650 and 180.600, so it was the most important potential ecological risk factor, and 10% of the plots were at high potential ecological risks be while 90% of the plots were at high potential ecological risks. and the other six heavy metals had E values that are less than 40, which shows only slight potential ecological risk. The potential ecological risk index value range was 114.665-188.792, with an average value of 134.837. Four plots were at slight potential ecological risk and six were at medium potential ecological risk.
Table 6 Potential ecological risk index of soil heavy metals
Plot EAs EHg EPb ECr ECd ECu EZn RI Ecological risk index
A1 5.592 2.576 1.067 0.201 147.050 0.068 0.005 157.559 Medium
A2 3.400 1.329 0.969 0.247 108.650 0.068 0.002 114.665 Slight
A3 4.304 2.788 1.309 0.147 132.300 0.026 0.003 140.877 Slight
B1 3.920 2.859 1.168 0.171 180.600 0.061 0.013 188.792 Medium
B2 6.052 1.835 1.131 0.204 153.200 0.036 0.003 164.862 Medium
B3 5.952 1.129 0.830 0.274 111.600 0.015 0.003 119.804 Slight
C1 5.564 1.776 0.867 0.266 158.550 0.077 0.024 167.125 Medium
C2 5.492 1.906 0.986 0.291 152.750 0.056 0.011 161.493 Medium
C3 6.120 1.682 0.885 0.318 123.150 0.053 0.006 132.214 Slight
CK 4.568 2.047 1.083 0.274 142.950 0.048 0.007 150.977 Medium
Average value 5.336 1.993 1.030 0.290 141.080 0.151 0.008 134.837 Slight
To sum up, different evaluation methods have obtained almost the same results. Qifeng dump is polluted by heavy metals, and the serious ecological risk of Cd pollution is high, so Cd elements should be controlled as soon as possible.

4.3 Analysis of heavy metal sources in the soils of different vegetation communities

(1) Correlation analysis of heavy metals
Correlation analysis can be used to determine the similarity of the sources of different heavy metals in soil, so it is widely used in soil heavy metal source analysis (Yang and Ji, 2015). Some studies have shown significant correlations between the contents of different heavy metal elements in soil, which indicates that there is often a homologous relationship or compound pollution relationship between the heavy metals; while in other cases the correlation is low, suggesting that the sources of one element in the region are inconsistent with the sources of the other elements (Feng et al., 2020).
According to the results of the correlation analysis of heavy metal contents in soil in this study (Table 7), As was not significantly correlated with the other heavy metals, Hg was positively correlated with Pb, Cd was positively correlated with Hg and Zn, and Pb was negatively correlated with Cr, but the other combinations were not significantly correlated (P>0.05). This indicates that the source of soil As is different from the other heavy metal sources, Pb and Hg have the same source, Cd and Hg have similar sources, and Cr has no homology with either Hg or Pb.
Table 7 Correlation coefficients of soil heavy metal contents
Elements As Hg Pb Cr Cd Cu Zn
As 1
Hg -0.314 1
Pb -0.460 0.814** 1
Cr 0.438 -0.714* -0.845** 1
Cd -0.090 0.650* 0.384 -0.366 1
Cu -0.027 0.130 -0.197 0.645 0.379 1
Zn 0.082 0.133 -0.254 0.556 0.640* 0.573 1

Note: ** indicates that the correlation coefficient is significant at the 0.01 level, and * indicates that the correlation coefficient is significant at the 0.05 level.

(2) Principal component analysis of heavy metals in soil
Principal component analysis (PCA) takes the contents of heavy metals in soil as the original variable. By calculating and reducing the number of original variables, the data are concentrated and extracted, and then the sources of heavy metal pollution can be judged (Huang and Gui, 2017). In Table 8, the cumulative variance contribution rate of the first three principal components was 89.437%, indicating that these three principal components could reflect most of the information for all seven kinds of heavy metals. Of the three components, the contribution rate of the first principal component variance was 44.927%, which mainly reflected the composition information of Hg, Pb and Cd, while the variance contribution rate of the second principal component was 29.985%. The load coefficients of Cr, Cu and Zn were 0.790, 0.782 and 0.921, respectively, which were higher than those of the other elements, indicating that the sources of Cr, Cu and Zn in soil might be the same. The contribution rate of the third principal component variance was 14.524%, and the largest load coefficient was that of As.
Table 8 Load factors extracted by principal component analysis
Heavy metal Factor load
PC1 PC2 PC3
As -0.519 0.140 0.798
Hg 0.928 0.085 0.156
Pb 0.904 -0.350 0.066
Cr -0.878 0.790 -0.046
Cd 0.639 0.636 0.334
Cu 0.104 0.782 -0.480
Zn 0.084 0.921 0.080
E 3.145 2.099 1.017
P (%) 44.927 29.985 14.524
C (%) 44.927 74.913 89.437

Note: E is the eigenvalue, P is the variance contribution rate, and C is the cumulative variance contribution rate.

The development and utilization of coal resources in Wuhai City has made great contributions to the rapid development of the social economy, but at the same time, it has destroyed the vegetation and made the soil properties of the mining area and the surrounding soil quite different. Heavy metals have been carried by waste water, waste residue, coal gangue and coal mine dust from open pit mining through wind and hydraulic migration and settlement.
The Cd level in the sample site exceeds the local soil background value, which may be due to the accumulation of soil Cd in the vicinity of the mining area and at the side of the transportation route. Many studies on Hg have shown that coal combustion and transportation (Liu et al., 2019) can lead to Hg pollution and accumulation (Fang et al., 2015). Mining and transportation activities are frequent in mining areas, and the large amount of traffic and motor vehicle exhaust is the main source of Pb. Guo et al. (2011) also found that the accumulation and pollution of heavy metals in the roadside soil of the transportation lines in mining areas is caused by ore and coal dust under the action of wind and water. Therefore, PC1 represents the artificial source of road coal dust diffusion and exhaust pollution.
The main sources of Zn are considered to be engine lubricating oil combustion, and tire and body wear. Zn and Cu are often added to automobile tires and radiators (Han et al., 2015; Li et al., 2019), so the contents of Zn and Cu will increase to a certain extent due to transportation activity (Vander et al., 2007). These conclusions are consistent with those of Yao et al. (2013). The study area is located in an arid area with little annual precipitation. In the process of vegetation reclamation in the dump, irrigation and fertilization will be carried out, and the chemical fertilizer contains a large amount of Cr elements (Jiao, 2012). Therefore, Cr may come from these agricultural production activities (Huang and Gui, 2017), and Cu is also found in pesticides and fertilizers. Therefore, PC2 represents pollution from transport and agricultural production activities.
Some studies (Wei et al., 2012) have shown that As is highly volatile in coal carbon (Guo et al., 2006). This leads to the pollution of As elements in the study area, and suggests that the important source of As elements is coal combustion (Huang and Tian, 2013). Therefore, PC3 represents coal combustion pollution.
When a given heavy metal element has a certain amount of load on different principal components, that element can be considered to have those two principal components as sources. For example, Cd has a considerable loading on the first and second principal components. Cd also exists in phosphate fertilizer, as an impurity in phosphate rock, and it enters the soil through the application of phosphate fertilizer. Therefore, it is likely that the Cd in the dump soil in this study represents the comprehensive accumulation from the coal dust from mining activities and coal transportation, as well as the application of chemical fertilizer.

5 Discussion

There are no obvious differences in the contents of heavy metals among the different vegetation allocation types or the downward slopes in the Qifeng Open-pit Mine. The results showed that the main reason for the differences in the heavy metal contents in soil was the soil matrix itself. Based on the contents of Cr, Zn and Cu in the dump, they are not considered to be significant pollutants, which is consistent with Liu et al. (2016). The research in Huaidong Coalfield Opencast Mining Area indicated the same situation. The average contents of Hg and Pb exceeded their soil grade I standards, Cd exceeded its soil grade II standard, and compared with the soil background values of Inner Mongolia, As, Hg, Pb and Cd exceeded their standards. In the worst case, Cd was 70.55 times the soil background value of Inner Mongolia. Therefore, there was a certain degree of heavy metal accumulation in the soil of the dump, so the situation of heavy metal pollution in dump is not optimistic. The pollution degree and ecological risk of Cd were much higher than those of the other heavy metals. The local government and related units should pay attention to the control of Cd elements and strengthen the prevention of pollution by the other elements. In an analysis of heavy metals in the soil of Luling Mine, Zhang et al. (2014) considered that Zn comes from traffic pollution sources. Wei et al. (2012) found that As released from coal combustion is an important channel for spreading As pollution, while Huang and Gui (2017) considered that Cr and Zn may come from the pollution of transportation and agricultural production activities. Liu et al. (2019) indicated that Pb, Cu, As and Cr may come from the wind erosion of coal and gangue in mining areas and coal dust in the process of transportation. Liu et al. (2016) and Yao et al. (2013) found a strong correlation between Zn and Cu. The analyses in this study indicate that Hg, Pb, and Cd come from road coal dust diffusion and exhaust emission, while Cu, Zn, and Cr come from transportation and agricultural production activities, and As comes from coal combustion pollution.

6 Conclusions

(1) The content of heavy metals in the soil of the Qifeng Open-pit Mine has little effect on plant community composition type and no clear relationship with the slope direction. Compared with natural restoration slopes, the content of Cr in the artificial reconstructed vegetation plot was clearly reduced, but there were no differences in the other heavy metal elements. The average contents of Hg and Pb exceeded their soil grade I standards, and Cd exceeded its soil grade II standard. Compared with the soil background values of Inner Mongolia, As, Hg, Pb and Cd exceeded their standards, and they were 2.05, 5.63, 2.33 and 70.55 times of the soil background values of Inner Mongolia, respectively.
(2) The single factor pollution index of heavy metals in the dump soil was in the order of Cd > As > Pb > Cr > Hg > Cu > Zn. The discharge site was clearly polluted by Cd, but the other six heavy metal elements were in their “clean” level ranges. The Nemero comprehensive index indicated that the soil heavy metal pollution level of the dump site is at the middling and moderate pollution level. The average potential ecological risk index values of the individual heavy metals were in the following order: Cd > As > Hg > Pb > Cr > Cu > Zn. In this case, Cd was between 108.650 and 180.600, so it was the most important potential ecological risk factor. The comprehensive potential ecological risk index value was between 114.665 and 188.792, with five plots in the slight potential ecological risk category and five others in the moderate potential ecological risk category. The different evaluation methods show that Qifeng dump is polluted by heavy metals. The pollution degree and ecological risk of Cd are much higher than those of the other heavy metals. Therefore, Cd should be controlled as soon as possible.
(3) Wuhai City is a mining city, with open pit mines, coal washing plant accumulation and coal gangue and coal debris travelling through wind and hydraulic processes, gradually transporting pollution to the surrounding soil. The results of the correlation analysis and principal component analysis show that human activities are the main reasons for the enrichment of heavy metals. Specifically, Hg, Pb, and Cd come from road coal dust diffusion and exhaust emission, while Cu, Zn, and Cr come from transportation and agricultural production activities, and As comes from coal combustion pollution.

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