Assessment of the Condition of Soils before Planned Hard Coal Mining in Southern Poland: A Starting Point for Sustainable Management of Fossil Fuel Resources

Abstract

In Poland’s largest mining district, the Upper Silesian Coal Basin, there is a growing interest in resource development by small operators. Some concession areas are not yet directly affected by the mining industry. The objects of this research are two such areas and the goal is to determine a load of heavy metals (HM) in soils prior to mining projects and to assess the extent of their contamination at this stage. The metals studied were Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn, while HM contamination was assessed using the Contamination Factor (CF), Contamination Degree (CD), Pollution Load Index (PLI), and Geoaccumulation Index (I_geo). The Ecological Risk Potential Index (E_R) and Comprehensive Potential Ecological Risk Index (PERI) were also employed. The pre-mining areas are close to an area where mining was terminated before 2000. For this area, we performed the same set of analyses as for the pre-mining areas studied. HM concentration levels and pollution indices in post-mining areas are significantly higher than in pre-mining areas. The results obtained in the post-mining area give an idea of the expected type and scale of potential threat to soils from mining and can form the basis for monitoring environmental contamination in subsequent investment and operation phases, as well as help develop and implement timely methods to prevent the increase in heavy metal immission to soils during mining activities. We believe that the presented approach of assessing the condition of soils starting at the pre-mining stage can support the sustainable management of energy resources in the cases studied and elsewhere.

1. Introduction

Poland’s power industry is dominated by coal-fired power plants (>70%). To comply with EU environmental directives, domestic coal mining in the last 5 years was reduced by 26% [1] in favour of importing coal from outside the EU. Currently, the value of imports accounts for about 26% of the demand for this raw material. However, developable domestic coal reserves are huge, economic resources—64.7 million tons [1]. It is worth noting that Poland’s share of hard coal production in the EU is 96% [2]. This fact assumes importance, especially in the face of international political conflicts, resulting in cutting off sources of fuel import [3]. In Poland’s largest mining district, the Upper Silesian Coal Basin, there is a growing interest in resource development by small operators. Some concession areas are designated outside the boundaries of previously exploited coalfields. These sorts of pre-mining areas are not yet directly affected by the mining industry.

We all realise that the extraction of natural resources, on the one hand, is associated with economic benefits for national economies, but on the other hand, results in environmental pollution. Exploitation results in the degradation of the land surface, as well as air, groundwater, and soil pollution (e.g., [4,5]). Soil is a particularly sensitive element of the environment. In recent years, an important research problem was the determination of heavy metal (HM) loads in soils. The presence of HMs in the soil is the result of their natural occurrence in the parent rock as well as widespread anthropogenic activities. The extraction and processing of natural resources, as well as the burning of fossil fuels (e.g., coal), increases the emission of HM into the atmosphere, resulting in, among other things, their accumulation in the soil. Therefore, superficial soil layers up to 20–30 cm depth are subject to strong HM contamination. According to many researchers, the greatest threats to the environment, of all metals, are Cd, Cu, Cr, Pb, Ni, and Zn (e.g., [6,7,8]). In addition, research results show that there is severe soil contamination worldwide due to Pb and Cd, and only minor contamination related to Zn [6]. The amount of HM contamination is variable and depends on the type of anthropogenic activity and the size and timing of emissions (e.g., [9]).

Certain HM, viz: Cd, Cr, Cu, Mn, Ni, and Zn, show a special affinity for organic matter, including coal [10,11]. In addition, some of them—Cd, Mn, Pb, and Zn are associated with lead or iron sulfides, aluminosilicates, and carbonates accompanying coal deposits [11]. The environmental impact of historical and modern coal mining in various parts of the world was widely discussed by researchers [12,13,14,15,16,17,18,19,20,21,22,23].

When considering the impact of coal mining on the soil, it would be useful to be able to refer to the state of the environment before the period when mining began. We identified a noticeable lack of information on pollution loads for the “pre-mining” state. Only a few studies of the state of the environment before uranium mining can be found in the literature [24,25]. This state of the art mobilised us to (1) determine a load of heavy metals in soils prior to mining investments and (2) assess the degree of contamination at this stage. We assessed HM contamination of soil samples based on geochemical and ecotoxicity indicators widely used around the world for urbanised [26,27,28,29,30,31] mining [9,12,14,17,18,32] and processing sites [33], as well as landfills [13,34].

The objects of our detailed study were two areas not yet affected by coal mining. The metals studied were Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn, while heavy metal contamination was assessed using the Contamination Factor (CF), Contamination Degree (CD), Pollution Load Index (PLI), and Geoaccumulation Index (I_geo). Ecological Risk Potential Index (E_R) and Comprehensive Potential Ecological Risk Index (PERI) were also determined. What is more, these areas are in close proximity to an area where mining was terminated before 2000. For this post-mining area, we performed the same set of analyses and calculations as for the pre-mining areas studied.

We believe that our approach of assessing the condition of soils before mining investment can benefit the sustainable management of energy resources [3] in the cases studied and elsewhere.

2. Materials and Methods

2.1. Study Area

The study area (Figure 1) is located in southern Poland at the northeastern border of the Upper Silesian Coal Basin (USCB), the largest Polish coal district, and one of the largest basins in Europe. About 80% of the country’s hard coal reserves and 96% of active hard coal mines are located here [1]. The coal mining industry existed in the USCB area for more than 200 years. Initially, coal was mined by open-pit methods on outcrops of Carboniferous strata. Over time, deeper parts of the rock mass and more extensive areas were mined. Due to the growing interest in coal mining, new deposits of this resource are being sought. Recently, new reserves of it were documented. Based on the geological reconnaissance, new mines were proposed to be established in Jaworzno town (Figure 1), whose concession areas were delimited outside the boundaries of the previously exploited deposits. Such pre-mining areas, therefore, were not yet affected by the mining industry. The subject of our study is two such areas, pre-mining area 1, located in the northern part of the city, and pre-mining area 2, located in the eastern part of the city (Figure 1). To identify the foreseeable type and magnitude of the potential threat to the surface soil layer caused by mining, a neighbouring post-mining area where mining operations ceased before 2000 was included in the study. Pre-mining and post-mining areas were selected so that the results of the analyses can be compared. Similarities include the size of the area, the size of the potential resources (the scale of the project), and the depth of the coal seams (similar mining conditions). As can be seen in Figure 1, all three study areas are located in close proximity to each other, which should also translate into similar levels of soil contamination associated with pollution emitters operating in the area. At this point, it is worth noting that the main industries functioning in the study region are, in addition to coal mining, electricity generation, and mining and processing of Zn-Pb ores.

2.2. Materials

The study was conducted on soils (Podzols) sampled in the two pre- and in one post-mining sites. Topsoil, depth of 0–30 cm, was sampled at 17 locations: at 13 points in the pre-mining areas (5 in the area 1 and 8 in the area 2) and at 4 points in the post mining area. All soil samples, ca. 2 kg weight each, were collected with a small spade and stored in plastic sacks. The local sandy bedrock specimen was sampled to determine the HMs reference concentration/baseline levels (mg·kg⁻¹) in the study area, symbolised as C_B hereafter.

2.3. Analytical Methods

Analyses were preceded by soil samples oven drying at 105 °C to constant weight, sieving to 2 mm through a stainless steel sieve and milling into fine powder. To achieve the total contents of Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn, the soil and bedrock samples were digested wet in a closed system in a mixture of 6 cm³ of concentrated nitric acid (65% Suprapur), and 2 cm³ of hydrochloric acid (30% Suprapur). Digestion proceeded with the use of a Multiwave 3000 Microwave Digestion of Perkin Elmer, in two steps according to the program of mineralisation recommended by the equipment provider—power: 1400 W, recovery time: 5 min, hold 25 min in the first step, 10 min in the second, and fan speed: 1 in the first step and 3 in the second. After mineralisation, the samples were removed to measuring flasks (10 cm³) with a 1% solution of Suprapur nitric acid. The contents of the studied HM in the prepared solution were determined using an atomic emission spectrometer ICP-OES Optima 7300 Dual View Perkin Elmer. Each sample was analysed twice. If the results of these replications differ one from another by more than 5%, another two analyses of that sample were conducted.

2.4. Contamination Assessment Methods

Pollution indices were used to assess the state of pollution, such as Contamination Factor, CF; Contamination Degree, CD; Pollution Load Index, PLI; Geoaccumulation Index, I_geo; Potential Ecological Risk Factor, E_R, and Comprehensive Potential Ecological Risk Index, PERI.

The degree of soil pollution of a single element at each sampling point, Contamination Factor (CF), was calculated via the following equation [35]:

$$\mathrm{CF}=\frac{{\mathrm{C} }_{\mathrm{HM}}}{{ \mathrm{C}}_{\mathrm{B}}},$$

(1)

where C_HM means HM concentration in soil samples (mg·kg⁻¹) and C_B is the reference concentration/baseline level of HM in the soil in the study area (mg·kg⁻¹). CF allows for determining the amount of heavy metal contamination of the soil due to anthropogenic activities. The grading of CF is demonstrated in

Table 1. The adjusted grading standards of CF, CD, E_R, and PERI according to Håkonson [35].

CF Value	Pollution Level	CD Value	Pollution Level	ER Value	Risk Level	PERI Value	Risk Level
CF < 1	low	CD < 6	low	ER < 40	low	PERI < 150	low
1≤ CF < 3	moderate	6 ≤ CD < 12	moderate	40≤ ER < 80	moderate	150 ≤ PERI < 300	moderate
3 ≤ CF < 6	considerable	12 ≤ CD < 24	considerable	80 ≤ ER < 160	considerable	300 ≤ PERI < 600	high
CF ≥ 6	very high	CD ≥ 24	very high	160 ≤ ER < 320	high	PERI ≥ 600	severe
				ER ≥ 320	significantly high

.

The estimation of the comprehensive contamination factor of surface layers in a particular sampling site, named Contamination Degree (CD), was quantified using a simple sum approach as follows [35]:

$$\mathrm{CD}={\displaystyle \sum }_{\mathrm{i}=1}^{\mathrm{i}=\mathrm{n}}\mathrm{CF},$$

(2)

with classification shown in Table 1.

The extent of HM pollution status in the studied soil samples was assessed by employing the Pollution Load Index (PLI) [36]. This indicator provides a simple way to compare the average soil quality in the region. The PLI is calculated by obtaining the n-root from the product of n-CFs that were achieved for all the metals, where n is the number of metals studied

$$\mathrm{PLI}=\sqrt[\mathrm{n}]{\left({\mathrm{CF}}_{\mathrm{HM}1}\times {\mathrm{CF}}_{\mathrm{HM}2}\dots .\times {\mathrm{CF}}_{\mathrm{HMn}}\right)}$$

(3)

The pollution level is classified based on their intensities on a scale presented in

Table 2. The classification of the pollution level of PLI and I_geo indices according to Zhang et al. [37].

PLI Value	Pollution Level	Class of Igeo Quality	Igeo Value	Pollution Level
PLI < 1	no pollution	0	Igeo < 0	uncontaminated
1 ≤ PLI < 2	moderate	1	0 ≤ Igeo < 1	uncontaminated to moderate
2 ≤ PLI < 3	moderate to high	2	1 ≤ Igeo < 2	moderate
3 ≤ PLI < 4	high	3	2 ≤ Igeo < 3	moderate to high
4 ≤ PLI < 5	very high	4	3 ≤ Igeo < 4	high
PLI ≥ 5	severe	5	4 ≤ Igeo < 5	high to extreme
		6	Igeo ≥ 5	extremely contaminated

, which was proposed by Zhang et al. [37].

The Geoaccumulation Index I_geo proposed by Müller [38] is a commonly used criterion for assessing HM contamination in soil in relation to the geochemical background. It is defined according to the equation:

$${\mathrm{I}}_{\mathrm{geo}}={\log }_2\left(\frac{{\mathrm{C}}_{\mathrm{HM}}}{1.5{ \mathrm{C}}_{\mathrm{B}}}\right),$$

(4)

where C_HM means HM concentration in soil samples (mg·kg⁻¹); C_B is the reference concentration/baseline level of HM in the soil in the study area (mg·kg⁻¹) and factor 1.5 is incorporated in the relationship to account for possible variation in background data due to lithogenic effect. The I_geo consists of seven grades or classes (Table 2). This index was applied along with the US Environmental Protection Agency (USEPA) as the recommended method for health risk assessment [14].

In addition to determining the level of heavy metal contamination in the soil, an ecological risk assessment was carried out, that is, an assessment of the negative impact that the theoretical presence of released substances, in our case HM, creates on all organisms in various ecosystems. For this purpose, the Potential Ecological Risk Index, E_R, and the Comprehensive Potential Ecological Risk Index, PERI, were calculated, and E_R index is expressed as follows [35]:

$${\mathrm{E}}_{\mathrm{R}}^{\mathrm{i}}={\mathrm{T}}_{\mathrm{r}}^{\mathrm{i}}\ast \mathrm{CF}$$

(5)

where ${\mathrm{E}}_{\mathrm{R}}^{\mathrm{i}}$ is the Potential Ecological Risk Index of metal i, and ${\mathrm{T}}_{\mathrm{r}}^{\mathrm{i}}$ is the biological toxic response factor of metal i, which is determined for Cd = 30, Cu = Ni = Pb = 5, Cr = 2, and Zn = 1. The Comprehensive Potential Ecological Risk Index, PERI, is easily calculated [35]:

$$\mathrm{PERI}={\displaystyle \sum }_{\mathrm{i}=1}^{\mathrm{i}=\mathrm{n}}{\mathrm{E}}_{\mathrm{R}}^{\mathrm{i}}.$$

(6)

3. Results and Discussion

3.1. Analysis of Heavy Metal Concentration

A summary of the results of the determination of total HM contents in pre-mining areas 1 and 2, and the post-mining area is shown in

Table 3. Statistics of heavy metals concentration in soil samples.

	Concentration Ci (mg·kg−1)
Elements	Cd	Cr	Cu	Fe	Mn	Ni	Pb	Zn
Pre-mining areas
Pre-mining area 1
Range	0.18–3.34	2.31–103.62	0.71–31.29	1448.27– 12,891.97	24.62–108.11	1.21–35.89	7.53–76.47	24.44– 250.79
Average	0.96	21.23	6.56	4565.39	51.00	11.50	28.55	110.35
Median	1.05	7.70	5.79	3839.35	56.59	2.98	28.52	120.44
CV	66.22%	163.73%	90.58%	63.67%	36.47%	135.4%	55.91%	46.56%
Pre-mining area 2
Range	0.03–6.43	1.49–9.84	1.3–18.33	1056.29– 5276.38	17.82–131.85	1.17–6.29	3.85–232.38	9.5–361.34
Average	0.52	2.23	2.18	1388.03	22.51	1.49	25.77	36.71
Median	0.38	2.47	2.07	1383.47	24.82	1.59	19.67	34.67
CV	171.33%	65.10%	121.98%	53.84%	81.98%	60.36%	141.01%	139.72%
Post-mining area
Range	0.34–12.12	21.91–119.32	2.03–51.16	1398.64– 19,264.94	21.28–673.57	2.15–22.89	7.67–382.71	9.09– 1671.99
Average	2.55	67.09	16.49	7415.81	94.96	7.07	106.03	273.96
Median	2.25	62.33	11.52	6796.78	78.12	6.75	62.5	175.13
CV	104.43%	42.08%	81.91%	62.51%	115.79%	75.93%	97.33%	130.30%
Background value CB	0.03	1.73	0.46	1151.12	38.73	2.27	1.88	7.82

. The results show variation between pre-mining areas. Statistically significant differences between pre-mining areas were confirmed by t-test (p < 0.05). In pre-mining area 1, 2- to 3-fold higher concentrations of Cd, Cu, Fe, Mn, and Zn were observed than in pre-mining area 2. For Ni and Cr, the differences are 8- and 10-fold higher, at 11.50 mg·kg⁻¹ and 21.23 mg·kg⁻¹ for pre-mining area 1, and 1.49 mg·kg⁻¹ and 2.23 mg·kg⁻¹ for pre-mining area 2, respectively. Only the Pb levels in the soils of the two pre-mining areas have almost the same value. At this point, it should be noted that pre-mining area 1 is located near the former Solvay soda ash plant, which operated from 1885 to 1909 [39]. Soil tests performed at the site showed high levels of Cd, Cr, Pb, and Zn, and coke, burned during the production process, was identified as the source of contamination [40]. The highest metal concentrations were observed for the topsoil of the post-mining area. The average values here are (mg·kg⁻¹): 2.55 for Cd, 67.09 for Cr, 16.49 for Cu, 7415.81 for Fe, 94.96 for Mn, 7.07 for Ni, 106.03 for Pb and 273.96 for Zn (Table 3). The t-test performed (p < 0.05) confirmed statistically significant differences between post-mining area and pre-mining areas. HM contamination of topsoil in the abandoned mining area can be linked to the high average content of these elements in hard coal. The coals, found in the study area, are known to have high average contents of Cd, Cr, Pb, Zn, Hg, As, Rb, and V [41].

High concentrations of HMs in soils in areas of discontinued coal mining were reported in various parts of the world. RoyChowdhury et al. [20] report severe heavy metal contamination of soils at Tab-Simco coal mine in Illinois, with metal contents at (mg·kg⁻¹): 4 for Cd, 152 for Cr, 148 for Cu, 41,012 for Fe, 175 for Ni, 145 for Pb and 419 for Zn. The researchers concluded that the main source of contamination, in this case, was acidic leachate from mine drainage [20].

In all areas covered by our study, topsoil samples show a significant increase in HM concentration relative to C_B background values (Table 3). Exceptions were noted only for Mn and Ni in pre-mining area 2. The highest differences are in the post-mining area, indicating high HM accumulation in the soil. Similar observations were reported within China’s coalfields [16,42], as well as for soils around a waste rock dump [13]. This suggests that heavy metals accumulated in the soil as a result of anthropogenic activities. Table 3 also shows the CV coefficient of variation values; 94% of the results show a high level of variability (CV > 45%). The strong spatial fluctuation of HMs in post-mining topsoil may be a consequence of the high variability of trace element/heavy metal content in different types of coals, as pointed out by Wang et al. [11] and Smolinski et al. [41].

To verify the relationship between the metals studied, Pearson’s r correlation coefficient was calculated, and the results are summarised in

Table 4. Pearson correlation matrix for heavy metal in soil samples.

Pre-Mining Areas
Pre-Mining Area 1									Pre-Mining Area 2
	Cd	Cr	Cu	Fe	Mn	Ni	Pb	Zn		Cd	Cr	Cu	Fe	Mn	Ni	Pb	Zn
Cd	1								Cd	1
Cr	−0.22	1							Cr	−0.24	1
Cu	0.75	−0.22	1						Cu	0.80	−0.23	1
Fe	0.28	−0.26	0.52	1					Fe	0.50	−0.26	0.55	1
Mn	0.87	−0.07	0.75	0.57	1				Mn	0.90	−0.08	0.75	0.69	1
Ni	−0.09	−0.10	0.08	0.12	−0.01	1			Ni	−0.09	−0.12	0.08	0.20	−0.02	1
Pb	0.98	−0.23	0.68	0.33	0.89	−0.11	1		Pb	0.99	−0.24	0.71	0.50	0.91	−0.11	1
Zn	0.95	−0.05	0.66	0.41	0.92	−0.14	0.97	1	Zn	0.95	−0.05	0.68	0.56	0.93	−0.14	0.97	1
Post-mining area
	Cd	Cr	Cu	Fe	Mn	Ni	Pb	Zn
Cd	1
Cr	0.3	1
Cu	0.96	0.36	1
Fe	0.91	0.18	0.91	1
Mn	0.75	0.35	0.78	0.82	1
Ni	0.94	0.31	0.95	0.97	0.89	1
Pb	0.96	0.35	0.98	0.88	0.67	0.91	1
Zn	0.96	0.38	0.91	0.88	0.76	0.91	0.9	1

Bold numbers—correlation is significant at the 0.05 level.

. A significant positive correlation (for p < 0.05) was found in the pre-mining 1 and pre-mining 2 areas between (r values are given in parentheses, respectively): Cd vs. Cu (r = 0.75 and r = 0.80), Mn (r = 0.87 and r = 0.90), Pb (r = 0.98 and r = 0.99), Zn (r = 0.95 and r = 0.95); Cu vs. Fe (r = 0.52 and r = 0. 55), Mn (r = 0.75 and r = 0.75), Pb (r = 0.68 and r = 0.71), Zn (r = 0.66 and r = 0.68); Fe vs. Mn (r = 0.57 and r = 0.69); and Pb vs. Zn (r = 0.97 and r = 0.97). In the case of the post-mining area, a strong positive correlation was found between all studied elements except Cr. The strong correlation between the studied parameters indicates their common origin. This allows us to assume that the mobilisation of elements occurred from similar sources and that they migrated together in the studied geoenvironment.

It is important to be aware that the information provided on the basis of total HM content in soil is limited [19] and useful mainly for identifying the source of pollution and determining the level of possible environmental pollution [43]. Currently, many studies are focused on determining the relationship between total metal concentrations in soil and their bioavailability [19,44,45]. The mobility, bioavailability, or eco-toxicity of HMs depends on the properties of the soils and on the structure and other physicochemical characteristics of the contaminating material, not on the total concentration of HMs.

3.2. Indices of Pollution

3.2.1. Pre-Mining Areas

The Contamination Factor, CF, was used to assess the enrichment of soil in HM. The results are shown in

Table 5. Indices of pollution for the studied soil.

Sample Point			Contamination Factor (CF)								CD	PLI	Geoaccumulation Index (Igeo)								Potential Ecological Risk Index (ER)								PERI
Pre-mining area			Cd	Cr	Cu	Fe	Mn	Ni	Pb	Zn			Cd	Cr	Cu	Fe	Mn	Ni	Pb	Zn	Cd	Cr	Cu	Fe	Mn	Ni	Pb	Zn
	Pre-mining area 1	S1	48.5	3.2	27.7	2.9	1.4	1.6	19.4	16.4	121.1	1.8	5.0	1.1	4.2	1.0	−0.1	0.1	3.7	3.4	1455.2	6.4	138.5	2.9	1725.6	8.0	96.8	16.4	1725.6
		S2	15.3	4.7	7.8	2.3	1.0	10.5	9.1	7.4	58.2	1.7	3.3	1.7	2.4	0.6	−0.5	2.8	2.6	2.3	457.8	9.5	38.9	2.3	615.1	52.7	45.5	7.4	615.1
		S3	31.9	5.4	18.9	7.9	1.5	6.7	15.6	15.5	103.4	1.8	4.4	1.9	3.7	2.4	0.0	2.2	3.4	3.4	955.8	10.9	94.6	7.9	1197.7	33.3	78.2	15.5	1197.7
		S4	15.8	52.5	5.9	1.7	1.0	0.7	8.1	12.2	98.0	1.8	3.4	5.1	2.0	0.2	−0.6	−1.1	2.4	3.0	472.7	105.1	29.7	1.7	666.4	3.5	40.5	12.2	666.4
		S5	64.6	3.5	9.5	3.4	1.7	1.1	29.6	23.8	137.2	1.8	5.4	1.2	2.7	1.2	0.2	−0.5	4.3	4.0	1938.1	7.1	47.5	3.4	2174.6	5.3	147.8	23.8	2174.6
	Pre-mining area 2	Q1	20.9	1.7	5.3	1.2	0.5	0.6	16.1	5.1	51.4	1.6	3.8	0.1	1.8	−0.3	−1.5	−1.4	3.4	1.8	628.3	3.3	26.3	1.2	748.2	2.8	80.5	5.1	748.2
		Q2	1.5	1.3	2.8	1.2	0.5	0.7	2.2	1.3	11.5	1.4	0.0	−0.2	0.9	−0.3	−1.6	−1.1	0.5	−0.2	45.4	2.6	14.2	1.2	79.5	3.5	10.8	1.3	79.5
		Q3	7.9	1.2	3.2	1.2	0.5	0.8	6.8	2.4	24.0	1.5	2.4	−0.3	1.1	−0.3	−1.6	−1.0	2.2	0.7	238.1	2.4	16.2	1.2	298.5	3.8	34.0	2.4	298.5
		Q4	24.2	1.0	4.9	1.1	0.5	0.6	14.0	5.9	52.2	1.6	4.0	−0.7	1.7	−0.5	−1.5	−1.4	3.2	2.0	724.9	1.9	24.6	1.1	831.9	2.9	70.1	5.9	831.9
		Q5	57.9	2.0	10.2	1.6	0.8	0.7	49.3	12.3	134.8	1.8	5.3	0.4	2.8	0.1	−0.9	−1.0	5.0	3.0	1736.0	3.9	51.2	1.6	2055.9	3.7	246.4	12.3	2055.9
		Q6	10.5	1.1	3.6	1.0	0.5	0.5	8.6	3.1	28.9	1.5	2.8	−0.5	1.3	−0.6	−1.6	−1.5	2.5	1.0	315.8	2.1	17.9	1.0	386.1	2.7	43.0	3.1	386.1
		Q7	10.8	1.2	4.3	1.2	0.7	0.7	7.9	4.1	30.9	1.5	2.8	−0.4	1.5	−0.3	−1.2	−1.1	2.4	1.4	323.2	2.3	21.6	1.2	396.3	3.5	39.7	4.1	396.3
		Q8	5.5	1.1	3.6	1.1	0.6	0.7	4.8	3.3	20.7	1.5	1.9	−0.5	1.2	−0.4	−1.2	−1.1	1.7	1.1	166.3	2.1	17.8	1.1	218.6	3.5	23.9	3.3	218.6
Post-mining area		N1	110.1	43.2	39.4	7.1	3.6	3.7	57.0	53.4	317.4	2.1	6.2	4.8	4.7	2.2	1.2	1.3	5.2	5.2	3302.7	86.5	197.0	7.1	3.6	18.5	284.8	53.4	3953.6
		N2	76.2	50.4	42.5	5.3	1.9	2.9	75.0	43.1	297.3	2.0	5.7	5.1	4.8	1.8	0.4	0.9	5.6	4.8	2287.3	100.8	212.6	5.3	1.9	14.3	375.1	43.1	3040.4
		N3	118.3	32.0	47.3	7.1	2.1	3.7	81.0	29.4	320.9	2.1	6.3	4.4	5.0	2.3	0.5	1.3	5.8	4.3	3547.9	64.0	236.3	7.1	2.1	18.4	405.0	29.4	4310.3
		N4	37.2	29.8	15.5	6.3	2.1	2.2	15.5	14.4	123.0	1.8	4.6	4.3	3.4	2.1	0.5	0.6	3.4	3.3	1115.4	59.6	77.3	6.3	2.1	11.2	77.4	14.4	1363.7

and Figure 2a,b. Pre-mining area 1 is characterised by considerable and very high soil contamination with Cd, Cr, Cu, Pb, and Zn, and low to moderate contamination due to the presence of Mn and Ni. The largest contributions to pollution, in descending order, are: Cd, Pb, Zn > Cu > Cr > Fe > Mn > Ni. The situation is slightly different in the pre-mining area 2. Very high and considerable contamination of Cu, Pb, and Zn is reported here, while the content of other HM affects moderate and low contamination of topsoil. Moreover, the order of decreasing CF values for individual heavy metals is as follows: Cu > Cd, Pb > Zn > Cr, Fe > Ni, and Mn.

The Contamination Degree, CD, calculated for pre-mining region 1 reaches values ranging from 58.2 to 137.2 (Table 5). This indicates that the total impact of the metals studied in the topsoil is very high (cf. Table 1 and Table 5). The situation is slightly more favourable in pre-mining region 2. CD ranges from 11.5 to 134.8, and only at five measurement points (75% of the population) values exceeded 24 (see Table 5). In the remaining locations, the degree of topsoil contamination is moderate to considerable.

A more comprehensive PLI index, which is calculated based on CF, was used to assess the soil load of HM. The PLI index allows a comparison of the level of contamination by an individually selected group of metals. In both pre-mining areas, PLI values range from 1 to 2 (Table 5). This shows that a moderate total level of metal contamination was obtained for all sampling points: Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn, despite very high CF values.

The level of soil enrichment in HM from anthropogenic sources was calculated based on the Geoaccumulation Index (I_geo). The results are shown in Table 5 and Figure 2c,d. Analysis of I_geo levels in the soil of pre-mining area 1 allows us to conclude that the predominant heavy metals causing high to extreme levels of contamination (Classes 5 and 6) are Cd (such levels were identified in 60% of sampling points) and Cr, Cu, and Pb (in 20% of sampling points). Moderate to high and high contaminations (Classes 3 and 4) refer to pollution with Zn, Cu, Pb, Cd, and Ni. The percentages of Class 3 and Class 4 at each sampling point are 100, 80, 80, 40, and 40%, respectively. Of the elements tested, only Mn, completely, and Ni and Fe, partially, do not cause topsoil contamination. In the case of pre-mining area 2, we observe that 12.5% and 25% of all measurement points, respectively, due to the presence of lead and cadmium, belong to pollution Classes 5 and 6 (high to extreme and extreme pollution levels). High and moderate to a high level of contamination (Classes 3 and 4) was assigned to 62.5, 50, 25, and 12.5% of the sample population due to the presence of Pb, Cd, Zn, and Cu, respectively. Moderate topsoil contamination is influenced by Cu and Zn, for which 75% and 37.5% of the samples tested reached Class 2. The magnitudes of I_geo marked for Fe, Mn, and Ni indicate the absence of contamination of the topsoil with these metals (Class 0). The above considerations allow us to infer the geogenic origin of Fe, Mn, and Ni, while the sources of Cd, Cr, Cu, Pb, and Zn are to be found in anthropogenic activities.

It is not only the level of contaminants that is important for assessing the condition of the soil, but also their potential impact on the biotic environment. The potential ecological risk of HM based on their toxicity was assessed using the Individual Potential Ecological Risk Index, E_R, and the Comprehensive Potential Ecological Risk Index, PERI. The results of the E_R evaluation of HM in topsoil are presented numerically (Table 5) and graphically (Figure 2e,f). All sampling points of pre-mining areas 1 and 2 show low ecological risk potential associated with the presence of Fe, Mn, Ni, and Zn. Additionally, the presence of Cr, except at point S4, shows no potential for increased ecological risk. Moderate risk levels were found for Cd (Q2), Cu (S5, Q5), and Pb (S2, S3, S4, Q4, and Q6). The considerable and high ecological risk was found due to the presence of Cu and Pb at two (S1, S3) and four (S1, S5, Q1, and Q5) locations, respectively. The most dangerous appears to be the situation related to the occurrence of Cd. The highest, significantly high, potential level of ecological threat was reached at 9 (5 in pre-mining area 1 and 4 in pre-mining area 2) sites out of 13 surveyed. Based on the E_R index values, the following ranking of potential environmental risk of metals was obtained: Cd > Pb > Cu > Cr, Ni > Fe, Mn, Zn, and Cd > Pb > Cu > Cr, Fe, Mn, Ni, and Zn, for pre-mining 1 and pre-mining 2, respectively.

The values of the, E_R directly affect the magnitude of the PERI. The PERI values calculated for pre-mining area 1 (Table 5) range from 615.1 to 2174.6 (average value of 1275.9), this means that the area is characterised by severe ecological risk potential. At all sampling points, PERI exceeded the value of 600. Significantly lower values, ranging from 79.5 to 2055.9 (average value of 626.9), were obtained for pre-mining area 2. Here we observe low (Q2), moderate (Q3 and Q8), high (Q6 and Q7), and severe (Q4 and Q5) comprehensive potential ecological risk.

The above-described assessment of soil condition at selected pre-mining sites shows that even before mining, there can be moderate and sometimes even significant enrichment in heavy metals, viz: Cd, Cu, Pb, and Zn. Their source should be sought in earlier anthropogenic activities (operations of soda ash plants near pre-mining area 1) or immission from modern sources. The enrichment in Cd, Pb, and Zn may also be related to the historical mining and processing of Zn-Pb ores that took place in the vicinity of the study areas [44,46,47,48]. The Cr, Fe, Mn, and Ni present in the soils of pre-mining area 2 appear originate only from natural sources, I_geo < 0.

3.2.2. Post-Mining Area

To recognise what effect mining activities have on topsoil, the area of the historical coal mine (cf. Figure 1) was investigated. CF calculations show that all samples in the post-mining area are very high (CF ≥ 6) contaminated with Cd, Cr, Cu, Fe (except N2), Pb, and Zn (Table 5 and Figure 2g). Mn and Ni pollution is at moderate to significant levels. No CF < 0 was found at any of the surveyed sites. Due to the decreasing CF values for individual heavy metals, they can be ranked as follows: Cd > Cr, Cu, Pb, and Zn > Fe > Ni > Mn.

The very high level of HM contamination was confirmed by the values of the CD index, which, for all topsoil samples studied, significantly exceed 24 (see Table 1 and Table 5). Despite the high values of CF and CD, the level of contamination load, determined by the PLI value, does not appear to be high. PLI was found to be in the range of 1.8 to 2.1 (compare Table 2 and Table 5). Thus, we are dealing here with a moderate and moderate to high pollution load (see Table 2).

In the case of the Geoaccumulation Index, I_geo, the distribution of values is no longer so clear-cut (see Table 2 and Figure 2). All of the topsoil samples tested, due to the concentration of Cd and Cr, were classified as high to extremely and extremely contaminated (Classes 5 and 6); 75% of the topsoil samples were placed in the same class due to the level of Cu, Pb, and Zn content. Only in the N4 site are Cu, Pb, and Zn influenced by high contamination (Class 4). In all samples, Fe represents moderate to high and moderate contamination (Classes 2 and 3). In contrast, Mn and Ni either do not affect topsoil pollution or have a moderate effect (grades 1 and 2).

The values of the Potential Ecological Risk Index, E_R, calculated for the post-mining area, confirmed serious topsoil contamination. The highest E_R values were obtained for Cd, Pb, and Cu (Table 5 and Figure 2i). Moderate to considerable risk is observed for Cr and Zn. Only for Fe, Mn, and Ni were low (1.9–3.6) E_R index values obtained. The ranking of HM, in terms of potential ecological risk, is as follows: Cd > Pb > Cu > Cr > Zn > Fe, Mn, and Ni. Due to the significantly high E_R values for cadmium, the PERI index values should also be classified as severe (PERI ≥ 600).

Enrichment in heavy metals (Cd, Cr, Cu, Pb, and Zn) in the soils of mining-affected areas is observed worldwide [13,16,17,18,20,22,23,42] and persists for a long time in the environment. In Illinois, at the site of the abandoned Tab-Simco coal mine, high contamination of Fe, Zn, Ni, Cr, Cu, Pb, and Cd was reported, with average metal contents corresponding to (mg·kg⁻¹), respectively: 41,012; 419; 175; 152; 148; 145, and 4 [20]. Most of these values are significantly higher than those observed for the post-mining area in Jaworzno. Soil contamination is also reported in reclaimed mining areas. An example of such kind is the post-mining area at Xinzhuangzi in China, restored coal-mining terrain used as cultivated land, where high Cd, Cr, Zn, Ni, and Pb concentrations, as well as high I_geo values for Cr (Classes 1 to 3) and Cd (Classes 2 to 5), are still observed [16]. Additionally in eastern India, around an open-cast coal mine, high levels of contamination with mercury, arsenic, and cadmium, as well as high comprehensive potential ecological risk index PERI (from 497.5 to 595.3), are noted [22].

In areas affected by coal mining, the strongest ecological risk, of all heavy metals, is mostly attributed to cadmium [13,18,23]. This is also reflected in our observations (Table 5 and Figure 2e,f,i).

On the other hand, there are places in the world where coal mining is yet to cause serious soil contamination. Guo et al. [32] report little or no contamination of topsoil by As, Hg, Cu, Pb, Zn, Cr, Ni, and Cd in the Hunchun Basin in northeastern China. Moderate contamination was observed there for only 26 of the 310 samples tested due to the presence of Hg, and for two and three samples, respectively, due to high Cr and Cd contents. Based on the I_geo index values (most < 0), Li et al. [14] find that coal mining in China appears to have the least impact on environmental pollution among 72 other mining areas.

4. Conclusions

To our knowledge, the presented approach of assessing the state of soil contamination prior to coal mining and comparing it with the state of contamination in a nearby post-mining area is novel, at least in Poland. A set of contamination indicators: CF, CD, PLI, I_geo, E_R, and PERI used to assess soil condition showed significant variation in the impact of Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn. The content of HMs in the soil is much higher than in the parent rock (background value C_B), except for the concentration of Mn and Ni in pre-mining area 2. The magnitude of metal contamination, CF, and the degree of contamination, CD, for most metals (Cd, Cr, Cu, Pb, and Zn) showed moderate to strong pollution in areas not affected by mining. Despite the relatively high CF values, a moderate level of contamination load, PLI (2 < PLI < 1) was observed in the pre-mining topsoils studied. The sources of the most soil-polluting metals, viz: Cd, Cr, Cu, Pb, and Zn, in pre-mining areas, should be attributed to anthropogenic activities (I_geo > 1), while for Fe, Mn, and Ni, the most likely sources are geogenic (0< I_geo < 1). Of all the metals tested, only cadmium poses a significantly high potential ecological risk, E_R, and Pb and Cu were classified as elements with a high risk of toxicity. The extreme comprehensive potential ecological risk (PERI ≥ 600) obtained for pre-mining area 1 reflects the high E_R values received due to the presence of Cd. In the case of pre-mining area 2, low to moderate ecological hazard potential was observed.

Analyses conducted in the neighbouring post-mining area give an idea of the expected type and scale of potential danger to soils from the planned mining activity. HM concentration levels and values of pollution indices in post-mining areas are significantly higher than in pre-mining areas. The very high level of HM contamination was confirmed there by the values of the CF and CD indexes. In the case of the I_geo, all of the topsoil samples tested were classified as high to extremely and extremely contaminated due to the concentration of Cd and Cr.

In addition, our research shows that in industrial areas, soil contamination can occur before mining activities take place. Thus, when assessing the state of the soil after mining, it is necessary to take into account its condition before the development. This approach makes it possible to determine the impact of coal mining itself on the state of the soil environment in human-altered terrains.

The results obtained can form the basis for monitoring environmental contamination in subsequent investment and operation phases, as well as help develop and implement timely methods to prevent the increase in heavy metal immission to soils during mining, coal processing, and transportation. We are convinced that our approach of assessing the condition of soils starting at the pre-mining stage can support the sustainable management of energy resources in the cases studied and elsewhere.