**Quality of Peri-Urban Soil Developed from Ore-Bearing Carbonates: Heavy Metal Levels and Source Apportionment Assessed Using Pollution Indices**

#### **Katarzyna Sutkowska 1, \*, Leslaw Teper 1 , Tomasz Czech 2 , Tomasz Hulok 1 , Michał Olszak 1 and Jan Zogala 1**


Received: 20 November 2020; Accepted: 16 December 2020; Published: 19 December 2020

**Abstract:** Pollution indices are used to assess the influence of the bedrock as a natural source of heavy-metal (*HM*), and anthropogenic pollution from ore mining in soils developed from ore-bearing carbonates. The research was conducted in two areas differing in geological setting and type of land use in the Upper Silesia Industrial Region, Southern Poland. Physical properties such as pH, total sulfur, total carbon and total organic carbon values, as well as total Zn, Pb, and Cd contents (ICP-OES) for 39 topsoil samples were measured. Contamination factor (*C<sup>f</sup>* ), degree of contamination (*Cdeg*), pollution load index (*PLI*) and geoaccumulation index (*Igeo*), were used to determine the deterioration of topsoil due to *HM* pollution. The *HM* content exceeded geochemical background levels by 2.5–18.1 times. Very high to moderate topsoil contamination was determined. In a shallow historical mining zone, the relative influence of particular *HM* was found to be in the order of Pb > Cd > Zn and, in a deep mining zone, Zn > Cd > Pb. In the topsoil developed over shallow ore bodies, the *HM* content was mainly (60%) due to naturally occurring *HM*. In the area of deeply buried ore bodies, 90% of the *HM* load was related to anthropogenic sources. Zn, Pb and Cd vertical distributions and the patterns of topsoil pollution differ in terms of types of mined ores, mining methods and times elapsed since mining ceased. Pollution indices are an efficient tool for distinguishing soil anthropogenic pollution and geogenic contamination.

**Keywords:** pollution indices; heavy metals; soil contamination; geogenic and anthropogenic origin

### **1. Introduction**

Heavy metals (*HM*) in the environment originate from geological, industrial, agricultural, atmospheric, and waste sources. Soil is one of the most important environmental components at risk of *HM* contamination as a result of anthropogenic activities. A high concentration of *HM*s and metalloids (Zn, Pb, Cd, As, Tl, etc.) can be found in and around active and abandoned mines or smelting plants [1–3] due to the emission and dispersion of pollutants into air [4,5], water [6,7], soil [8–17], plants [4,18–22], and fauna [23,24]. The global average concentration of *HM*s in soils varies for Zn (10–300 mg·kg −1 ), Pb (10–150 mg·kg −1 ) and Cd (0.06 mg·kg −1 ) [25]. In general, the *HM* concentrations in soils are increasing over time, and the highest concentrations are observed in industrial cities, due to traffic, power plants, and other industrial activities [25]. Soil contains baseline or background

concentrations of *HM*. The *HM* content is determined by the composition of the parent rock material from which the soil is derived.

The effective assessment of soil *HM* contamination is an important global issue [10,25–29]. Indicators for the geochemical assessment of the soil environment include contamination factor (*C<sup>f</sup>* ), degree of contamination (*Cdeg*), pollution load index (*PLI*), and geoaccumulation index (*Igeo*). These indicators enable the estimation of environmental risk and soil degradation due to accumulation of *HM*s [28–30]. Moreover, they facilitate differentiation between the accumulation of *HM*s produced by natural processes and anthropogenic activities (e.g., [31]). Essential to any assessment of the degree of soil contamination is the selection of an appropriate reference value. Although this issue has already been widely discussed [26,32–36], there is still a lack of unambiguous methodological findings.

The aim of the current study is to assess the quality of soil developed from Zn-Pb ore-bearing carbonates, in terms of (1) the influence of the bedrock, as a natural/geogenic source of *HM*s, and (2) anthropogenic pollution from ore mining and processing. We attempted a source apportionment of *HM*s (Zn, Pb, Cd) based on the pollution indices and using the local/on-site geochemical background. The research was carried out on the topsoil layers that are usually expected to accumulate trace elements of anthropogenic origin.

The main novelty of our work consists in taking into account data linking the indices to a broader geological context and mining history which has scarcely been published. We compare two areas located in the same Zn-Pb MVT-type deposit, which differ in terms of types of mined ores, ore-body depth, mining method and the time of mining cessation. The presented approach can be applied to the analyses of environmental risk and *HM* source apportionment in the abandoned mining sites worldwide.

#### **2. Study Area**

Two areas located in the north-east part of the Upper Silesia Basin (Figure 2) in the Dlugoszyn and Wilkoszyn Synclines in Jaworzno City were chosen for the study. Both synclines belong to the superior synclinorial structure with an NW-NE trending axis resulting from the Alpine orogenic movements. The inclination of the rock layers varies from 4◦ to 15◦ NW in the Dlugoszyn Syncline, and from 4◦ to 20◦ SE in the North-West limb of the Wilkoszyn Syncline. These tectonic structures comprise the Middle Triassic carbonate formation, which is composed of dolomites, limestones, and marls. The carbonate rock profile is partially altered due to the epigenetic fluid flow resulting in dolomitisation [37]. The Zn-Pb mineralisation followed the dolomitisation episode, which developed the ore-bearing dolomites with Zn-Pb ore deposits [38]. The Zn-Pb ore deposits in the area belong to the stratabound type. The ore minerals (galena, sphalerite, pyrite, marcasite, and secondary nonsulfides) form bodies of varying horizontal- and vertical extension ranging from several tens of centimetres up to several tens of meters. They consist of metasomatic-, dispersed- and cavity-filling-ores, the latter including crusted-, veined-, drusy- and breccia varieties [39]. Most of the ore bodies have a typical tabular form concordant with the rock bedding. The boundaries between the ore-bearing dolomites and the host carbonate rocks are rarely defined, but more commonly form a broad transition zone into weakly mineralized dolostones.

The areas selected for the study vary in terms of the geological setting. In the Dlugoszyn area (see point 1 in Figures 1 and 2), the ore-bearing dolomites occur near the surface (0–1 m), while in the Wilkoszyn syncline (see point 2 in Figures 1 and 2) the ore bodies occur at a depth of 20 to 90 m. The relatively shallow occurrence of ore mineralisation favours the development of mining. There is evidence of outcrop and underground Zn-Pb ore mining and smelting from the 12th [40] to the 20th century. The shallow ore exploitation in the Dlugoszyn area was completed at the end of the 19th century, while the deep mines and processing plants in the Wilkoszyn area were abandoned in the middle of the 20th century [41,42]. There is evidence of the historical mining and industrial activity in the landscape of the town [43]. Local ore mining left its mark on natural habitats impacting air [44], water [45,46] and soil [2,3,47–49] quality and imposing imprints onto flora [50,51] and fauna [52,53].

**Figure 1.** Schematic geological cross-section of the study area showing location of ore bodies, without Quaternary sediments (after [54]).

50°14′19.2″ N – **Figure 2.** Geological context of the study area, without Quaternary sediments (after [54]).

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#### 19°14′30″ E – **3. Material and Analytical Methods**

50°14′19.2″ N 19°14′30″ E

50°14′58.5″ N –

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50°14′58.5″ N – To investigate the relationship between the ore-bearing bedrock and content of *HM*s (Zn, Pb, and Cd) in the soils (mostly skeletal Rendzic Leptosol), 15 soil profiles were studied (Figure 3). We tried to select homogenous soil profiles. Each soil profile was divided into separate horizons, providing 54 soil samples. Only the topsoil layers (up to 30 cm depth), characterised by the highest concentrations of *HM*, were considered further; these are represented by 39 soil samples in Table 1. Moreover, bedrock specimens (from each study area) were sampled and analysed to evaluate the local/natural chemical pedogenic enrichment.

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**Table 1.** Geochemical properties of the topsoil samples. D—Dlugoszyn area, W—Wilkoszyn area.

Prior to the analysis, the soil samples were oven-dried at 105 ◦C to constant weight, sieved to 2 mm through a stainless-steel sieve, and milled into a fine powder, while the bedrock samples were crushed and ground. The soil pH was determined using a 1:5 (g:mL) ratio of soil and 1 M KCl solution, with pH meter ELMETRON CP-315 m. The concentration of total carbon (TC), total organic carbon (TOC), and total sulfur (TS) were determined using an Eltra CS-530 IR-analyser with a TIC module. In order to determine the total content of Zn, Pb, and Cd, the soil and rock samples were wet digested in a closed system in a mixture of 6 cm<sup>3</sup> of concentrated nitric acid (65% Suprapur), and 2 cm<sup>3</sup> of hydrochloric acid (30% Suprapur). Digestion proceeded with the use of a Perkin Elmer Multiwave 3000 Microwave Digestion, in two steps according to the program of mineralisation recommended by the manufacturer—power: 1400 W, recovery time: 5 min, hold: 25 min in the first step, 10 min in the second, fan speed: 1 in the first step, 3 in the second. After mineralisation, the samples were transferred to measuring flasks (10 cm<sup>3</sup> ) with a 1% solution of Suprapur nitric acid. The *HM* content

in the prepared solution was determined using an atomic emission spectrometer ICP-OES Optima 7300 Dual View Perkin Elmer. Each sample was analysed twice. The quality control procedure was performed using internal laboratory standard for soil material. The percentage recovery for observed elements ranged from 86.5% to 100% (Supplementary Materials Table S1). The ICP-OES analyses were performed at the Department of Agricultural and Environmental Chemistry, University of Agriculture in Krakow.

**Figure 3.** Characteristic examples of studied soil profiles in elevated- (profile D5) and buried (profile W3) ore-bearing dolomitic areas (photographs: T. Hulok).

X'Pert (X'Celerator). Kα 2θ 2θ The phase composition was provided by X-ray diffraction (XRD). The analyses were performed on powdered samples using a PANalytical X'Pert Pro MPD (multipurpose diffractometer) powered by a Philips PW3040/60 X-ray generator and fitted with a 1D silicon strip detector (X'Celerator). The measurements were performed using Co Kα-radiation with a wavelength of 0.1789010 nm, an acceleration voltage of 40 kV, a current of 40 mA, and with 0.02 ◦ 2θ step sizes between the angles of 5◦ and 70 ◦ 2θ and a 300 s measurement time per step. The data obtained were processed using HighScore+ software and the ICSD database and PDF4+ ICDD database. All XRD analyses were performed at the Institute of Earth Sciences, Faculty of Natural Sciences, University of Silesia, Sosnowiec.

Håkonson's

#### **4. Soil Pollution Assessment**

The concentration of *HM*s in the soil is related either to the natural abundance if they come from parent rocks or the anthropogenic load if they come from mining- and processing activities. The distinction between the background of the site level and the pollution load is essential to determine the nature of any anomaly, especially in industrial areas such as the selected study area.

The *HM* contamination in the soil samples is evaluated by applying the *C<sup>f</sup>* , *Cdeg*, *PLI*, and *Igeo*.

The *C<sup>f</sup>* is employed to determine the degree of soil pollution with a particular potentially toxic element. The calculation of this factor follows Håkonson's [55] definition (Equation (1)):

$$\mathcal{C}\_f = \frac{\mathcal{C}\_{\text{HM}}}{\mathcal{C}\_B} , \tag{1}$$

where *CHM* is the *HM* concentration in soil samples (mg·kg−<sup>1</sup> ) and *C<sup>B</sup>* is reference concentration of *HM*s in soil in the study area (mg·kg−<sup>1</sup> ). According to Håkonson [55], four contamination categories can be distinguished: *C<sup>f</sup>* < 1, low; 1 < *C<sup>f</sup>* < 3, moderate; 3 < *C<sup>f</sup>* < 6, considerable; and *C<sup>f</sup>* > 6, very high contamination.

The estimation of the degree of total contamination of surface layers in a particular core or sampling site was proposed by Håkanson [55] as a sum of the *C<sup>f</sup>* for each sample, or *Cdeg* (Equation (2)):

$$\mathbb{C}\_{\text{deg}} = \sum\_{i=1}^{i=n} \mathbb{C}\_{f'} \tag{2}$$

The classification of the *Cdeg* in sediments is as follows [55]: *Cdeg* < 6, low; 6 < *Cdeg* < 12, moderate; 12 < *Cdeg* < 24, considerable; and *Cdeg* > 24, high.

The status of the *HM* pollution in the studied soils is assessed through the *PLI* [56]. The *PLI* is calculated by obtaining the *n*-root from the product of *n*- *C<sup>f</sup>* s for all the *HM*s, where n is the number of *HM*s studied (Equation (3)):

$$PLI = \sqrt[n]{\left(\text{CF}\_{\text{HM1}} \times \text{CF}\_{\text{HM2}} \dots \times \text{CF}\_{\text{HMn}}\right)} \tag{3}$$

A *PLI* value < 1 indicates minimal or no metal pollution, a *PLI* = 1 indicates that the level of pollutants is equal to the baseline content of *HM*, whereas *PLI* > 1 means that there is pollution and the value indicates the severity of the pollution. For the latter case, Zhang et al. [57] classify soils into the following five categories: 1 < *PLI* < 2, moderately; 2 < *PLI* < 3, moderately to highly; 3 < *PLI* < 4, highly 4 < *PLI* < 5, very highly; and *PLI* > 5, extremely polluted.

The *Igeo* proposed by Müller [58] is a common criterion to evaluate the *HM* pollution in sediments/soil. It is defined as follows (Equation (4)):

$$I\_{\rm geo} = \log\_2\left(\frac{\mathcal{C}\_{\rm HM}}{1.5\,\mathcal{C}\_B}\right) \tag{4}$$

where *<sup>C</sup>HM* is the *HM* concentration in soil samples (mg·kg−<sup>1</sup> ); *C<sup>B</sup>* is reference concentration of *HM*s in the soil in the study area (mg·kg−<sup>1</sup> ), and factor 1.5 is incorporated in the relationship to account for possible variation in background data due to the lithogenic effect. Müller [58] distinguished seven classes of soil quality based on *HM* enrichment: Class 0–*Igeo* < 0, uncontaminated; Class 1–0 < *Igeo* < 1, uncontaminated to moderately; Class 2–1 < *Igeo* < 2, moderately; Class 3–2 < *Igeo* < 3, moderately to highly; Class 4–3 < *Igeo* < 4, highly; Class 5–4 < *Igeo* < 5, highly to extremely; Class 6–*Igeo* > 5, extremely contaminated. *Igeo* Class 0 suggests the lack of contamination, while the highest Class 6 shows the extreme enrichment of the *HM*s relative to background values.

The above reference concentration, symbolised as *CB*, depends on the local natural conditions, and differs widely from one geologic unit to another. The metal background depends on the

composition of the parent rock from which the soil was derived [13]. Thus, use of Clark values or off-site reference methods are obviously not appropriate, especially in assessing weakly contaminated sites [34]. The on-site reference value is more specific and sensitive in the case of trace-element soil contamination [33]. Because of the bedrock of ore-bearing dolomites in the research area, we decided to use the *HM* content in the carbonate bedrock (Table 2) as a local reference value. In addition, three more off-site reference values (Table 2) were applied to further define the role played by different sources in the topsoil contamination detected.


**Table 2.** HM concentrations in topsoil samples and baseline CB values (mg·kg−<sup>1</sup> dry weight).

#### **5. Results and Discussion**

The pH values of the soil in the Dlugoszyn area (Table 1) fluctuate between 4.26 and 7.24 (median 6.57), while in the Wilkoszyn area, the pH varies from 6.01 to 7.6 (median 6.77), indicating that the examined soil samples are extremely acidic to slightly alkaline, but mostly neutral. Generally, the pH value decreases with depth. The TOC values obtained for the soil range from 0.2% to 23.12% (median 1.72%) in the Dlugoszyn area and from 0.68% to 13.84% (median 2.04%) in the second study area, while TS varies from 0 to 0.14% (median 0.01%) and 0.01 to 0.12% (median 0.02%), in the two study areas, respectively (Table 1). Both parameters diminish with depth. The TOC levels observed are characteristic for rendzina skeletal soils.

The concentrations of Zn, Pb, and Cd in the soil differ significantly between the elevated (Dlugoszyn) and buried (Wilkoszyn) ore-bearing dolomite areas (Table 2). The Dlugoszyn soil samples contain 68–3329 mg·kg <sup>−</sup><sup>1</sup> d.m. of Zn, 18–1877 mg·kg <sup>−</sup><sup>1</sup> d.m. of Pb, and 0.31–37.58 mg·kg <sup>−</sup><sup>1</sup> d.m. of Cd, with weighted arithmetic means 1351 mg·kg <sup>−</sup><sup>1</sup> d.m., 550 mg kg <sup>−</sup><sup>1</sup> d.m., and 13.01 mg·kg <sup>−</sup><sup>1</sup> d.m., respectively. The pollution load of the same elements in the Wilkoszyn area ranges as follows: 480–3077 mg .kg <sup>−</sup><sup>1</sup> d.m. for Zn, 118–1035 mg·kg <sup>−</sup><sup>1</sup> d.m. for Pb, and 2.34–27.66 mg·kg <sup>−</sup><sup>1</sup> d.m. for Cd, with weighted arithmetic means 1549 mg .kg <sup>−</sup><sup>1</sup> d.m., 410 mg·kg <sup>−</sup><sup>1</sup> d.m., and 10.43 mg·kg <sup>−</sup><sup>1</sup> d.m., respectively. For the soil derived from ore-bearing dolomites occurring close to the surface in the Dlugoszyn area, the mean concentrations of the studied metals exceed 2.5-, 9- and 3.8-fold of the Zn, Pb, and Cd content in bedrock, respectively. For the soil developed in the Wilkoszyn area from deeper ore-bearing dolomites, the mean values calculated are 18.1- (for Zn), 5.1- (for Pb), and 8.6-fold (for Cd) higher than the baseline level (compare Table 2), indicating intensive soil contamination in both study areas.

The main crystalline phases in the topsoil are in the 79.5–84 wt.% (Table 3) represented by quartz (Figure 4). Goethite is abundant, especially in the Wilkoszyn area (11.5 wt.%). The large concentration of dolomite (3–5%), and some calcite (to 0.5 wt.%) were also detected. The K-feldspars (microcline and orthoclase), albite, plagioclases, and kaolinite occur there as the accessory minerals. The low-crystalline goethite (7.16Å in Figure 4), is accompanied by amorphous iron oxides or sulfides (marcasite, hematite—2.695 Å) and/or iron oxide/hydroxide. Additionally, the pyroxene (augite-diopside) or spinel Zn-Al-Fe family phases were documented by diffraction peak 4.675 Å.


**Table 3.** Semiquantitative mineralogical analysis of XRD results.

— — — — — **Figure 4.** XRD patterns of topsoil from D-Dlugoszyn (red line) and W-Wilkoszyn (blue line) area. Symbol explanations: C—calcite, D—dolomite, F—feldspars, G—goethite, Q—quartz.

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On the basis of the trace-element contents of the sampled soil, the natural concentration and the contamination from anthropogenic sources cannot be distinguished. To assess the degree of anthropogenic influence on the soils, the selected pollution indices (*C<sup>f</sup>* , *Cdeg*, *PLI*, and *Igeo*) were calculated.

The *C<sup>f</sup>* was calculated for each soil sample relative to the bedrock value for both study areas (Table 2). The *C<sup>f</sup>* of Zn, Pb, and Cd in the Dlugoszyn area is in the range of 1.0–6.0, 2.8–30.6, and 2.1–9.6, with a mean value of 2.4, 9.1, and 3.8, respectively (Table 4). This indicates considerable to very high (80% of results for Pb) and moderate to considerable (100% for Zn and 80% for Cd) topsoil contamination level (Table 5). In the Wilkoszyn area, *C<sup>f</sup>* has values of 6.9–35.8, 1.1–6.1 and 1.9–22.6 for Zn, Pb, and Cd, respectively, with a mean value of 14.8, 4.1, and 7.0, respectively (Table 4). Such *C<sup>f</sup>* levels point to considerable to very high contamination degree with Zn (100% of results) and Cd (90%), and moderate to considerable pollution with Pb (80%) (Table 5).


**Table 4.** Assessment of *HM* pollution indices in studied topsoil in relation to the local carbonate bedrock in the D-Dlugoszyn and W-Wilkoszyn areas as a background value.

In bold—strongly contaminated.

The *Cdeg* index determines the degree of overall contamination of a particular sample in the study areas. Based on the *Cdeg* (see Tables 4 and 5), 80% of the calculated values for the Dlugoszyn samples are recognised as moderately contaminated, while 20% are very highly contaminated. In the Wilkoszyn samples, 60% indicate very high (30%) and moderate (10%) pollution of the topsoil (Table 5).

The PLI indicates deterioration of the soil quality due to metal pollution. In the current study, the PLI obtained for the Dlugoszyn samples indicates moderate (20% of results), moderate to high (40%), high (20%) and extreme (20%) topsoil pollution (Table 5), with values ranging from 1.8 to 12.1, and mean equal to 4.3 (Table 4). In the Wilkoszyn samples, the PLI values range from 1.9 to 16.5, with a mean of 7.2 (Table 4) pointing to extremely (70% of results), very high (20%), and moderately (10%) polluted topsoil (Table 5).

The pollution indices indicate the moderately to extremely high level of topsoil contamination and reveal a difference in the level of topsoil contamination between the study areas (Table 5).


**Table 5.** Percentage of class distribution of topsoil pollution for indices considered. D—Dlugoszyn area, W—Wilkoszyn area.

The Igeo ranges from −0.6 to 2.0 for Zn, with a mean value of 0.4; 0.9 to 4.3 for Pb, with a mean value of 1.9, and 0.5 to 2.7 for Cd, with a mean value of 1.1 in the Dlugoszyn area (Table 4). The values of Igeo for *HM*s decrease in the sequence Pb > Cd > Zn. The results classify the area as highly polluted with Pb and moderately polluted with Zn and Cd (Table 5). In contrast, in the Wilkoszyn area, the Igeo varies widely from 1.2–4.6 for Zn, with mean value 3.0; −0.5–2.0 for Pb, with mean value 1.3 and 0.3–3.9 for Cd, with mean value 1.8 (Table 4). The *HM* pollution follows the order Zn > Cd > Pb. Using Igeo, we can determine the potential source of pollution. The Igeo values obtained for the elevated ore-bearing dolomites in the Dlugoszyn area indicate mainly baseline levels of pollution for Zn and Cd, as 80% Zn and 80% Cd belong to Classes 0 and 1. The only exception is pollution with Pb (see Table 5). Most of the Zn and Cd are derived from geogenic sources, and most of the Pb (80%) is derived from anthropogenic sources. As such, in the Dlugoszyn area, the deterioration in soil quality is due to Pb. In the Wilkoszyn area, with buried ore-bearing dolomites, moderate to heavy pollution by Pb and Cd is observed, as 80% Pb and 90% Cd belong to Class 2 and 3 (Table 5). Heavy to extreme pollution by Zn is identified, as 70% Zn belongs to Class 4 and 5 (Table 5). Based on these results and the fact that concentrations of *HM*s decrease with depth, the *HM*s in the topsoil of the Wilkoszyn location is of anthropogenic origin. The graphical model of *HM* immissions into the topsoil of the Dlugoszyn and Wilkoszyn areas is presented in the Figure 5, while the complete set of soil profiles studied is put into the Supplementary Materials (Figure S1).

When calculating pollution indices, the selection of an appropriate reference value is an important and complicated issue. Opinions about the best value to use are divided. Some researchers favour the trace-element contents in the deeper soil horizon [32,36,62] or the average values in soil from the study area [30,63] as correct. Others consider the trace-element contents in the bedrock [64,65] as best. The accuracy and sensitivity of the on-site reference value in identifying trace-element soil contamination was evaluated by Desaules [33]. The specific geological setting of both study areas forced us to calculate the selected pollution indices with reference to the bedrock.

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**Figure 5.** Graphical model of anthropogenic (red arrows) and geogenic (green arrows) *HM* immissions into the topsoil of the D-Dlugoszyn and W-Wilkoszyn areas.

– – – – We also take off-site reference values defined as the median for topsoil in (1) the Cracow-Silesia region [60], (2) S Poland [59] and (3) Europe [61] into consideration. Outcomes of these examination are listed in Tables 6–8. In applying the off-site reference values to topsoil in the area where shallow ore-bearing dolomites occur (the Dlugoszyn area), a significantly higher degree of contamination is observed. Additionally, anthropogenic sources are mainly responsible for the *HM* presence in the soil. The percentage of class distribution shows (Tables 6–8) that 80–100% of *Igeo* values belong to classes 2–6. The only exception refers to Pb when the S Poland median value is used. In the case of deeper situated Zn-Pb mineralization (the Wilkoszyn area), comparable results were obtained using the off-site and on-site reference values. Significant differences were noted when the reference value for European topsoil was considered. Using the latter reference value, the extremely high soil contamination (*C<sup>f</sup>* , *Cdeg*) here is attributed mainly to human activity (*Igeo*; see Table 8). In our opinion, and especially in the case where the ore-bearing dolomite is near surface, use of the local reference value to assess topsoil contamination provides more reliable results than use of off-site reference values.


**Table 6.** Assessment of *HM* pollution indices in studied topsoil in relation to the median for topsoil in the Cracow-Silesia region as a background value [60].

In bold—strongly contaminated.


**Table 7.** Assessment of *HM* pollution indices in studied topsoil in relation to the median for topsoil in S Poland as a background value [59].

In bold—strongly contaminated.

**Table 8.** Assessment of *HM* pollution indices in studied topsoil in relation to the median for European topsoil as a background value [61].


In bold—strongly contaminated.

Diatta et al. [9] observed similar results, with significantly high *HM* levels in soils impacted by the Miasteczko Slaskie Zn smelter, in part of the Upper Silesia Industrial Region. The mean Zn, Pb, and Cd contents in mg.kg−<sup>1</sup> reported are 1062.97, 781.91, and 12.32, respectively. Using the off-site reference value to *Igeo*, *C<sup>f</sup>* , and *Cdeg* calculations, extremely high contamination was observed for Zn, Cd, and Pb, in ascending order [9]. Our findings differ slightly in terms of the influence of particular *HM*s. In our opinion, the difference between the orders of pollutant intensity acquired for individual sites resulted primarily from the local industrial land use and the kind of reference value.

The historical mining of Zn-Pb ores in the Dlugoszyn area was based on the dominant mineral, galena (Pb sulfide), which occurs in shallow ore bodies which are easily recognised. Moreover, Pb has a relatively low melting point, allowing for ease of processing [41]. As such, ore mining in the area started in the early medieval period and resulted in the most severe Pb pollution in the Dlugoszyn topsoil. The levels of Zn and Cd are derived from the metal-rich bedrock.

The very high Zn and Pb contamination observed in the Wilkoszyn area probably results from the 20th century underground Zn-Pb ore mining and processing, when galena, Zn sulfides, and nonsulfides were mined and processed in the area. As such, it seems probable that recent industrial operations are a principal cause of the high levels of Zn and Pb accumulated in the Wilkoszyn topsoil.

Generally, soil samples from arable fields and home gardens across the Upper Silesia Industrial Region are characterised by high levels of toxic *HM*s. This is reflected in the *HM* concentrations in locally cultivated vegetables, which are well above the permissible levels [11]. Both study areas are used as peri-urban agricultural lands. The very high topsoil *HM* levels reported in this paper are not as harmful due to the pH value (Table 1) observed in studied soil. The *HM*s are regarded as highly soluble and more toxic in an acidic soil environment [66,67].

#### **6. Conclusions**

The application of various pollution indices (*C<sup>f</sup>* , *Cdeg*, *PLI*, and *Igeo*) and the local background value *C<sup>B</sup>* enable the detection of Zn, Pb, and Cd pollution in soils. Depending on the index used, we determined very high to considerable (according to the classification proposed by [55]) topsoil contamination. The influence intensity of particular metals differs between studied areas. In the case of shallow historical mining (the Dlugoszyn area), it follows the order Pb > Cd > Zn, while in the place of deep mining and processing (the Wilkoszyn area) it decreases in the sequence Zn > Cd > Pb. With the geo-accumulation index, it is possible to discriminate between natural and anthropogenic *HM*s in the soils developed over the ore-bearing formation in the two areas. Based on *Igeo* values, we consider that the *HM* content in the topsoil developed over the shallowly occurring ore bodies in dolomites (the Dlugoszyn area) is mainly (60%) connected with the natural presence of metals. In the Wilkoszyn area where ore bodies are more deeply buried, 90% of the *HM* load is related to anthropogenic sources. An accurate assessment of soil quality, based on *HM* content, is possible only with the combined use of various pollution indices.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2075-163X/10/12/1140/s1, Table S1. Zn, Pb, Cd content mg. kg−<sup>1</sup> d. m. determined in the internal laboratory standard for soil material (n = 20), Figure S1. The complete set of soil profiles for D-Dlugoszyn and W-Wilkoszyn areas.

**Author Contributions:** Conceptualization: K.S., L.T.; Methodology: K.S.; Investigation: K.S., T.C., T.H., M.O., J.Z.; Formal analysis: K.S.; Resources: T.C.; Writing—original draft: K.S.; Writing—review & editing: L.T.; Funding acquisition: L.T.; Supervision: L.T.; Data curation and Visualization: K.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study was funded by the University of Silesia, Institute of Earth Sciences (WNP/INOZ/2020\_ZB32).

**Acknowledgments:** This study was undertaken in the framework of the activities of the University of Silesia in Katowice and was funded by the University of Silesia, Institute of Earth Sciences (WNP/INOZ/2020\_ZB32). We wish to thank Tomasz Krzykawski from the University of Silesia in Katowice for his assistance with XRD analysis. We are grateful to Pádhraig S. Kennan from University College Dublin for valuable remarks and suggestions. Two anonymous reviewers are thanked for improving the quality of the paper.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


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## *Article* **Feasibility of a Chemical Washing Method for Treating Soil Enriched with Fluorine Derived from Mica**

**Dong-Jun Baek 1 , Ye-Eun Kim <sup>2</sup> , Moon-Young Jung 2 , Hye-On Yoon <sup>3</sup> and Jinsung An 1,2, \***


**\*** Correspondence: jsan@semyung.ac.kr; Tel.: +82-43-649-1335; Fax: +82-43-649-1779

**Abstract:** High levels of fluorine in soil may pose health risks and require remediation. In this study, the feasibility of using a practical chemical washing method for the removal of fluorine from an enriched soil was evaluated. The chemical washing procedures were optimized through experimental analyses of various washing solutions and washing conditions (i.e., washing solution concentration, solid–liquid ratio, agitation speed, and reaction time). Additionally, the effects of techniques for improving the washing efficiency, such as ultrasonic washing, aeration, and multistage washing, were evaluated. Herein, among all applied methodologies, the maximum washing efficiency achieved for the total fluorine present in soil was only 6.2%, which indicated that chemical washing was inefficient in remediating this particular soil. Further sequential extraction analysis showed that the fluorine in this soil was present in a chemically stable form (residual fraction), possibly because of the presence of mica minerals. It was demonstrated that chemical washing may not be effective for remediating soils containing such chemically stable forms of fluorine. In these cases, other physical-based remediation technologies or risk management approaches may be more suitable.

**Keywords:** natural fluorine-enriched soil; natural sources; soil remediation; chemical extraction resistance; low washing efficiency

#### **1. Introduction**

Fluorine, an element with atomic number 9, has high electronegativity and thus can readily react with other elements, such as Fe, Al, and Ca. Therefore, fluorine mostly exists as compounds in the natural state, and it is difficult to find fluorine in natural settings as a single element [1,2]. Human activities (e.g., fertilizer use, coal use, and aluminum and steel industrial activities) have resulted in the accumulation of fluorine in soil. Coal combustion releases hydrogen fluoride (HF), silicon tetrafluoride (SiF4), and carbon tetrafluoride (CF4), which can be accumulated in the soil environment [3,4]. Moreover, fluorine levels in soil can be elevated by fluorine-containing rocks (natural origin) [5,6]. Studies have shown that fluorine-containing mica, fluorite (CaF2), and apatite can contribute to the accumulation of fluorine in soil and groundwater through weathering [5–12].

High intake of fluorine is known to cause dental fluorosis, skeletal fluorosis, and osteoporosis [13–15]. The World Health Organization (WHO) [16] has reported that the intake and inhalation of fluorine may cause cancer, such as osteosarcomas and bone tumors. Therefore, the concentration of fluorine in soil must be properly managed.

Chemical washing has been widely used as a treatment method for soil contaminated with metals and metalloids [17–24]. The chemical washing process can be implemented within a short period of time compared to solidification and stabilization technologies, and this means that it may be possible to reuse the site quickly. For soil contaminated with

**Citation:** Baek, D.-J.; Kim, Y.-E.; Jung, M.-Y.; Yoon, H.-O.; An, J. Feasibility of a Chemical Washing Method for Treating Soil Enriched with Fluorine Derived from Mica. *Minerals* **2021**, *11*, 134. https://doi.org/10.3390/ min11020134

Academic Editor: Ana Romero-Freire Received: 1 December 2020 Accepted: 26 January 2021 Published: 29 January 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

As, Cd, Cu, Cr, Pb, and Zn, removal efficiencies between 56% and 100% were achieved with various washing solutions such as HCl, ethylenediaminetetraacetic acid (EDTA), phosphoric acid, sulfuric acid, and FeCl<sup>3</sup> (Table 1). Chemical washing with 3 M HCl was also performed on fluorine-contaminated soil near a chemical plant, and a removal efficiency of 97% was observed [17]. The application of the chemical washing technique to treat natural fluorine-enriched soil has not been previously studied.

**Table 1.** Chemical washing conditions and efficiencies for the metals, metalloids, and fluorine-contaminated soils reported in previous studies.


In this study, the feasibility of using a chemical washing method to remediate natural fluorine-enriched soil was evaluated. The soil at the target site requires specialized treatment because the fluorine concentration exceeds the soil contamination criterion of South Korea (Area 2: 400 mg/kg, "Area 2" refers to locations containing forests, warehouse sites, etc.) [18], and treatment needs to be completed within a relatively short period of time because the site is located in an urban area. The applicability of various washing solutions and washing conditions (i.e., washing solution concentration, solid–liquid ratio, agitation speed, and reaction time), which have been used previously for chemical washing of heavy metal-contaminated soil, was examined. In addition, the effects of techniques for improving the washing efficiency, such as ultrasonic washing, aeration, and multi-stage washing, were evaluated. X-ray diffraction (XRD) analysis and sequential extraction were performed on the target sample to obtain a better understanding of the nature of fluorine within the soil.

#### **2. Materials and Methods**

#### *2.1. Soil Preparation and the Determination of Its Characteristics*

In this study, natural fluorine-enriched soil was collected from Seoul (latitude: 37◦29′23", longitude: 127◦00′03"), a mega city. Topsoil with a depth of 30 cm or less was collected, airdried at room temperature, and sifted through a 2-mm sieve; then, the pH, organic matter content (Walkley–Black method), cation exchange capacity (ammonium acetate method), and iron/aluminum/manganese oxide content (dithionite–citrate system buffered with sodium bicarbonate (DCB) method) of the soil were measured [26–29]. Additionally, pellets with a diameter of 34 mm (prepared by compressing soil samples to enable X-ray analysis on a flat surface) were fabricated and subjected to X-ray fluorescence analysis (S8 Tiger, Bruker, Billerica, MA, USA) under vacuum conditions at an output of 40 mA and 40 V. Based on these data, the main components (Si, Al, Fe, Ca, Na, K, Mg, Ti, P, and S) of the soil samples were determined. The types of crystalline minerals in the soil samples were identified through XRD analysis (D8 ADVANCE, Bruker, Billerica, MA, USA). This analysis was conducted with a 2theta range of 3–90◦ , step of 0.02, scan speed of 0.5 s/step, and wavelength of Cu kα1 = 1.5418 Å at a generator output of 40 kV and 40 mA.

Meanwhile, wet sieving was also performed for soil samples of 2 mm or less to analyze the fluorine concentration by particle size. The sizes of the sieves used were 0.5, 0.15, and 0.075 mm, and the composition ratio was calculated by measuring the dry weight after sieving.

Finally, mica, which was estimated to be the main fluorine-containing mineral in the target soil, was manually collected from the gravel (>2 mm). Then, it was pulverized and the fluorine content was measured using the alkali fusion method described in Section 2.3.

#### *2.2. Chemical Washing Procedures for Natural Fluorine-Enriched Soil*

To determine optimal conditions for the chemical washing method used on the natural fluorine-enriched soil, experiments were performed by varying the washing solution type, washing solution concentration, ratio between the soil sample and the washing solution (g:mL), agitation speed, and reaction time. Furthermore, changes in washing efficiency due to aeration, ultrasonic irradiation, and multi-stage washing were also evaluated. First, to determine the optimal washing solution, 1 M solutions of sulfuric acid (H2SO4), phosphoric acid (H3PO4), sodium hydroxide (NaOH), potassium hydroxide (KOH), oxalic acid (H2C2O4), nitric acid (HNO3), perchloric acid (HClO4), and hydrochloric acid (HCl) were mixed with the soil samples at a solid–liquid ratio of 1:5 (g:mL), and the amount of fluorine eluted was evaluated after a reaction time of 60 min at an agitation speed of 200 rpm. Washing experiments were performed while the washing solution concentration was varied from 1 to 2 and 2.5 M, solid–liquid ratio (g:mL) from 1:2 to 1:3 and 1:5, agitation speed from 100 to 150 and 200 rpm, and reaction time from 10 to 30, 60, 120, and 240 min. In addition, the amount of fluorine eluted was evaluated after aeration and ultrasonic irradiation for 10, 30, and 60 min and two to four cycles of multi-stage (repeated) washing. After chemical washing experiments were carried out under each condition, solid–liquid separation was performed using a 0.45-µm Gelman hydrophilic polypropylene (GHP) syringe filter (Pall, Port Washington, NY, USA). The fluorine concentration in the filtrate was then measured using a fluoride ion electrode (F001502, ISTEK, Seoul, Korea) after mixing the filtrate with total ionic strength adjustment buffer (TISAB) at a 1:1 ratio. The washing efficiency was calculated as the ratio of the fluorine concentration in the washing solution (i.e., the filtrate) (unit: mg/kg) to the total fluorine concentration in soil (unit: mg/kg).

#### *2.3. Determination of the Total Fluorine Concentration in Soil*

The alkali fusion method was used to measure the total fluorine concentration in soil [30]. For this procedure, 0.5 g of the dried soil sample was placed in a nickel crucible, and 6 mL of 16 M NaOH was injected. The crucible was placed in a dryer at 150 ◦C for 1 h and then in a furnace at 300 ◦C. The temperature was increased to 600 ◦C, and the reaction was allowed to proceed for 30 min. Approximately 10 mL of distilled water was

then added to the residue in the nickel crucible, and the pH was adjusted between 8 and 9 with concentrated HCl. After transferring the sample to a volumetric flask and adding distilled water to reach 100 mL, the solution was filtered through Whatman No. 40 filter paper. After mixing the filtrate and TISAB at a ratio of 1:1, the concentration of fluoride ions in the filtrate was measured using the fluoride ion electrode, and these data were used to determine the fluorine concentration in soil.

Furthermore, the accuracy of the method for analyzing the fluorine concentration in soil was assessed using GSP-2 and NIM-G, which are certified reference materials (CRMs). The fluorine content was 3000 mg-F/kg-soil for GSP-2 and 4200 mg-F/kg-soil for NIM-G.

#### *2.4. Sequential Extraction Procedures for Fluorine in Soil*

Sequential extraction was performed to understand the binding pattern between soil components and fluorine. Fluorine was divided into a water-soluble fraction (F1), exchangeable fraction (F2), Mn and Fe oxide bound fraction (F3), organic matter bound fraction (F4), and residual fraction (F5) (Table 2). In step 1, 2.5 g of the dried soil sample and 25 mL of the extractant were mixed [31,32]. After centrifugation, the precipitates and 25 mL of each extractant were mixed in steps 2 to 4. For the analysis in step 5, the alkali fusion method described in Section 2.3 was used. For the separation of the extractant and the soil sample, centrifugation (1580R, Labogene, Seoul, Korea) was performed for 15 min at 2357 *g* [33].

**Table 2.** Sequential extraction procedures for fluorine-enriched soil (following Yi et al. [32] with some modifications).


<sup>a</sup> Cited from Davison et al. [34]. <sup>b</sup> 0.02 M HNO<sup>3</sup> 3 mL + 30% H2O<sup>2</sup> 10 mL and ammonium acetate 12 mL [35].

#### **3. Results**

#### *3.1. Characteristics of Fluorine-Natural Enriched Soil*

Table 3 shows the fluorine concentration for various soil particle sizes. The properties of the natural fluorine-enriched soil used in this study are presented in Tables A1 and A2. The total fluorine concentration in the soil samples (<2 mm) was found to be 1078 ± 178 mg/kg, which exceeds the soil contamination criterion of Korea (Area 2: 400 mg/kg) [25]. Thus, these data confirmed that an appropriate remediation technique was required for this natural fluorine-enriched soil. The soil sample with a particle size of 0.15 mm or less exhibited 1.5 times higher fluorine concentration than the total soil sample (i.e., particle size of 2 mm or less). Because pollutants introduced to soil from external sources are easily adsorbed on the surface of silt or clay particles with a large specific surface area, the concentration of heavy metals increases as the particle size of soil decreases [36,37]. Despite the above finding, the distribution of fluorine concentrations was relatively homogeneous in this study (i.e., no significant differences were observed for the different soil particle sizes). This indicated that the pollutants adsorbed on soil particles were not introduced from the outside but were possibly of natural origin (from minerals).


**Table 3.** Particle size distribution of the soil sample and the corresponding total fluorine concentrations.

#### *3.2. Chemical Washing Efficiency*

The soil samples were mixed with 1 M solutions of H2SO4, H3PO4, NaOH, KOH, H2C2O4, HNO3, HClO4, and HCl at a solid–liquid ratio of 1:5 (g:mL). For each mixture, the reaction was allowed to proceed for 1 h at an agitation speed of 200 rpm, but the washing efficiency remained as low as 0.6–3.0% (Table 4).

**Table 4.** Chemical washing efficiencies when using various washing solutions.


To improve the washing efficiency, various conditions (i.e., washing solution fixed to HCl, washing solution concentration (1–2.5 M), solid–liquid ratio (1:2–1:5), agitation speed (100–200 rpm), reaction time (10–240 min), aeration (10–60 min), ultrasonic washing (10–60 min), and multi-stage washing (1–4 times)) were tested. The washing efficiency, however, did not exceed 6.2% (Table 5).

According to a previous study [17], a 97% removal efficiency was achieved when chemical washing was performed for 1 h under conditions of 200 rpm and 20 ◦C at a solid–liquid ratio of 1:5 (g:mL) using 3 M HCl (Table 1); these results are markedly different from the results of this study.

#### *3.3. Origin of Fluorine in Soil*

To analyze the causes of the significantly low washing efficiency obtained in this research, even though chemical washing conditions similar to those applied in previous research on soil contaminated with heavy metals and fluorine of an artificial origin were maintained (Table 1), XRD analysis and sequential extraction were performed on the target sample.


**Table 5.** Chemical washing efficiencies when applying various washing conditions.

#### 3.3.1. X-Ray Diffraction Analysis

Figure 1 shows the XRD analysis results. Peaks of biotite, phlogopite, muscovite, and lepidolite, which belong to mica, were detected in the soil sample data. It is known that mica can contain fluorine as a result of the substitution of hydroxide ions (OH– ) and fluoride ions (F– ) [4–11]. Based on the XRD analysis results, gravel-sized fragments rich in mica were manually collected from the > 2 mm sifted soil sample in which a large amount of mica was detected. Then, the mineral samples obtained were pulverized and subjected to fluorine concentration analysis and XRD analysis.

The XRD analysis results for the minerals that were estimated to be mica exhibited peaks of biotite, phlogopite, lepidolite, and muscovite (Figure 1) that were more prominent than those in the above results [38,39], and a fluorine concentration of 2647 mg/kg was measured (the fluorine concentration in the soil sample with a size of 2 mm or less from the same soil was 1078 mg/kg). This finding indicated that fluorine was possibly present in the soil sample (with a size of 2 mm or less) as result of the fragmentation of mica minerals.

#### 3.3.2. Sequential Extraction Results

Table 6 shows the fluorine sequential extraction results for the target soil sample. The residual fraction (F5) amounted to 99.2–99.6%, thus confirming that most of the fluorine was present in soil in a chemically stable form. When the sample, obtained by manually collecting mica minerals with a size of 2 mm or higher and pulverizing them, was subjected to fluorine sequential extraction using the same method, the residual fraction (F5) was found to be 99.8%, which was similar to the value obtained for the soil sample.

As confirmed in Section 3.3.1, the target soil sample represents a case in which fluorine of a natural origin (mica) is present and has accumulated above the soil environmental criterion. In such a case, fluorine is present in a chemically stable form because it exists

as minerals. This appears to have contributed to the significantly low efficiencies for the chemical washing procedures tested.

**Figure 1.** X-ray diffraction analysis results for (**a**) the soil sample and (**b**) mica selected manually from the gravel (>2 mm).


**Table 6.** Sequential extraction results for the soil sample and mica selected from gravel.

#### **4. Conclusions**

In this study, the applicability of chemical washing was evaluated for the treatment of a soil containing high levels of fluorine that originated from mica. This soil exceeded the soil environmental criterion for the region. Various conditions (washing solution type, washing solution concentration, solid–liquid ratio, agitation speed, reaction time, aeration, ultrasonic washing, and multi-stage washing), similar to those of the general washing method for soil contaminated with heavy metals and the washing method previously applied to soil contaminated with fluorine of an artificial origin (near a chemical plant, where a 97% washing efficiency was achieved) [17], were tested; however, from all methodologies applied, the maximum washing efficiency achieved in our study for natural fluorineenriched soil was 6.2%. The sequential extraction results showed that approximately 99% of the fluorine was present as a residual fraction, thus indicating that it occurred in the soil in a chemically stable form, possibly because of the presence of the fragmented mica minerals. This may have contributed to the low washing efficiency. Consequently, treating this soil enriched with fluorine of a natural origin (mica) using general chemical washing methods is not feasible. Therefore, it is recommended that physical separation technology be applied or other approaches be used to manage potential human health and/or ecological risks.

**Author Contributions:** Conceptualization, M.-Y.J. and J.A.; methodology, J.A.; software, D.-J.B.; validation, D.-J.B., Y.-E.K., and H.-O.Y.; formal analysis, D.-J.B. and Y.-E.K.; investigation, D.-J.B. and Y.-E.K.; resources, H.-O.Y.; data curation, D.-J.B.; writing—original draft preparation, D.-J.B. and J.A.; writing—review and editing, J.A.; visualization, D.-J.B.; supervision, J.A.; project administration, M.-Y.J. and J.A.; funding acquisition, J.A. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the Korea Ministry of Environment (MOE) as Waste to Energy-Recycling Human Resource Development Project, and the Geo–Advanced Innovation Action (GAIA) project (Grant No. 2013000530001) of the Korea Environmental Industry & Technology Institute (KEITI).

**Data Availability Statement:** Data is contained within the article and Appendix A.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Appendix A**


**Table A1.** Composition of the major elements in the soil samples determined using an X-ray fluorescence spectrometer.

**Table A2.** Characteristics of the soil samples used in this study.


#### **References**

