Multi-elemental Characterization of Soils in the Vicinity of Siderurgical Industry: Levels, Depth Migration and Toxic Risk

1. Introduction

Soil is a vital resource which provides essential support to humans and ecosystems. Industrial activities, such as metal smelting, steel production, mining, chemical industry and coal-fired power production, may cause soil quality degradation and serious pollution of environment with toxic trace elements which could negatively impact human health due to their accumulation, persistence and transfer in the compartments of the food chain [1,2,3,4,5]. The elemental analysis at trace level is an important analytical task in various laboratories and high precision techniques such as Instrumental Neutron Activation Analysis (INAA) [4,5,6,7,8,9,10], X-ray Fluorescence (XRF) [9,10,11,12,13,14] and inductively coupled plasma mass spectrometry (ICP-MS) [9,12,13,14,15] have shown to be powerful tools for multielemental analysis of a variety of environmental matrices, including soil and rock material, as well as for the assessment of mineralogical and geochemical features and spatio-temporal contamination trends of a certain region.

This work was aiming to apply INAA, XRF and ICP-MS in order to examine the soil multi-element load, level of soil pollution with Potential Contaminant Elements (PCEs) and their ecological impact around the largest integrated ferrous (iron and steel) metallurgical plant (ISP) in Romania located at Galati town — the biggest port on the maritime Danube — which is one of the most important integrated complexes in the South-East of Europe (Figure 1) [11,16,17], with a great potential of environmental contamination due to specific emissions from iron smelting, processing of ores, coal and auxiliary materials, agglomeration and sintering, minerals and scrap transportation, steelmaking, etc. [3,18,19,20]. The importance of the targeted region also derives from its closeness to the Danube River, the confluence of Danube with its main tributaries Siret and Prut Rivers, and proximity to the ecologically valuable natural sites and special protected areas in Romania, Republic of Moldova and Ukraine in the Lower Danube River and Black Sea basins [17,21,22]. The activity of this large ferrous metallurgical facility started in 1965, is continuing today, but in the last decade some of the units (blast furnaces, steelworks and mills) were closed and the slag dumping has stopped [23].

The aim of this paper was two-fold: 1) to study the soil mineralogy, the spatial and depth distribution pattern of 45 major and trace elements in soils belonging to several territorial-administrative units (TAU) of Galati (GL) and Braila (BR) counties in the South–East Development Region of Romania; and 2) to assess the ecotoxicological risk of PCEs in soils adjacent to siderurgical industry, which might produce serious health disorder.

The work was carried out as a continuation and extension of pollution and risk assessment of previous studies limited to soil contamination with heavy metals [4,10,11,16] and persistent organic pollutants (POPs) [17] in Galati industrial area and SE Romania in the period 2005-2009, and in connection with other projects implemented in the frame of international networks, focused on the determination of toxic compounds (heavy metals, radionuclides, POPs, pharmaceutics and endocrine disruptors) and assessment of ecological and human health risk in the Black Sea Basin [3,14,15,22,24].

2. Materials and Methods

2.1. Sampling and Sample Processing

Composite soil samples of about 1.5 kg were collected at nine sites around a large steel plant in SE Romania (Figure 1) from three different layers in the depth intervals: 0–5 cm, 5–20 cm and 20–30 cm. The samples labeled as G1 were taken from the village of Vadeni, Braila County, and the other samples (G2, G3, G4) from Galati County, from localities of Sendreni and Smardan TAUs and Galati town. A control sample (GC) was collected from Vanatori village, in the north part of Galati town (Figure 1). The site description is presented in Table 1.

The collected soil samples were prepared for various analyses at INPOLDE research center, Dunarea de Jos University of Galati, Romania, being cleaned from stones, vegetal material and other debris, dried at room temperature, then grounded and sieved to a granulation of 0.01 mm.

2.2. Analytical Techniques

Two non-destructive analytical techniques were used in this research, such as: epithermal neutron activation analysis (INAA) and X-ray fluorescence (XRF) analysis. The two analysis techniques were used to determine with high accuracy and precision the total concentrations of 44 major, minor and trace elements (INAA— Na, Mg, Al, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Co, Zn, As, Br, Rb, Sr, Zr, Nb, Mo, Sb, I, Cs, Ba, La, Ce, Nd, Sm, Eu, Tb, Dy, Tm, Yb, Hf, Ta, W, Au, Hg, Th and U; XRF—Cu, Pb, Sn, Y) in the soil samples taken around a large steel plant in SE Romania. For Cd analysis, the ICP-MS technique was employed.

The instrumental neutron activation analysis (INAA) analytical technique was applied at REGATA installation of the IBR-2M reactor within the Frank Laboratory of Neutron Physics (FLNP), of Joint Institute for Nuclear Research (JINR) Dubna, Russian Federation. Several channels of the IBR-2M reactor were used, which allowed the irradiation of the samples with thermal and epithermal neutrons. Soil samples weighing around 100 mg, together with certified reference materials, were wrapped in polyethylene bags and aluminium foils for the short and long-term irradiation, respectively, according to the analytical scheme described in other work [7,25,26,27,28]. The induced radioactivity in the samples was measured with the aid of gamma spectrometric chains equipped with automatic switch system for soil and standard material samples [7,25]. The gamma spectra were processed using the software developed at JINR [26] and the analysis was performed based on the radionuclides formed in the samples during activation with neutrons with various energies, listed in [5,6,7,25].

For the application of XRF spectrometric analysis with energy dispersion the prepared samples were put in specific capsules coated with a Myler foil. The encapsulated samples were irradiated for 120 seconds using a portable Genius XRF spectrometer manufactured by Skyray Instruments Inc., equipped with a large area and detector with Be window and an excitation source of 40 kV / 100µA miniature X-ray tube with an Ag-target [14,23].

ICP-MS was applied for cadmium determination with the aid of an Agilent 7700Χ ICP-MS spectrometer from the International Hellenic University (IHU), Kavala, Greece, a partner laboratory of INPOLDE center in the frame of MONITOX network [24], as described in a previous study [14].

2.3. Depth Migration, Contamination and Toxic Risk Indices

In order to qualitatively assess the degree of migration/mobility in soil of the determined chemical elements, the depth migration index (DMI) was calculated for each element using the Eq. (1), adapted by us after [29,30], for all the depths from which samples were taken (from 0 to 30 cm):

$$\mathrm{DMI} ={\sum }_{\mathrm{i}=1}^{\mathrm{n}}\left(\frac{{\mathrm{c}}_{\mathrm{i}}}{{\mathrm{c}}_{\mathrm{T}}}\right){\mathrm{D}}_{\mathrm{i}}$$

(1)

where n=3 represents the number of layers from which the samples were taken, c_i is the value of the chemical element concentration in each sampled layer i, ${\mathrm{c}}_{\mathrm{T}}=\sum _{i=1}^n{c}_i$ is the sum of the values of the chemical element concentrations from all the depths of the sampled layers, and D_i is the depth (in cm) of the lower limit of each sampled layer (5, 20 or 30 cm). The value of this index ranges from 1 (if the element accumulated entirely in the first cm) to 30 (if the element accumulated entirely between 29 and 30 cm). The migration/mobility potential is classified into four categories, labelled as: A (DMI<5) — very low; B (5<DMI<10) — moderate; C (10<DMI<20) — high; D (DMI>20) — very high [16,30].

Contamination factor (CF) for an individual chemical element is defined by Eq. (2) as the ratio of each element concentration in the soil sample to the element concentration in background soil [31]:

$$\mathrm{CF}=\frac{{\mathrm{c}}_{\mathrm{sample}}}{{\mathrm{c}}_{\mathrm{background}}}$$

(2)

where c_sample and c_background are the measured concentration and the background concentration value of metal i, respectively. The contamination classification of soils using this index is: CF < 1 – low; 1 ≤ CF < 3 – moderate; 3 ≤ CF < 6 – considerable; CF ≥ 6 – very high [2,31,32,33,34].

To evaluate the pollution levels of various contaminants specific to a site, the site Pollution Load Index (PLI) was employed, utilizing Eq. (3) as introduced by Tomlinson et al. (1980) [35]. This equation involves computing the nth root of the product of the highest individual contamination factors ${\mathrm{CF}}^{\mathrm{i}}$, calculated for specific metals (PCEs) which might result from siderurgical industry activity (n=number of elements/ contamination factors). In this work we considered n=13 PCEs, chosen from those specified in the Romanian legislation [36] and probably to be emitted during the iron and steel making and steel products manufacturing processes, e.g. Hg, Cd, As, Pb, Cu, Co, Ni, Cr, Mn, Zn, Fe, V and Sb. The site PLI categories are the following: PLI≤1– unpolluted (Background Pollution); PLI ≥1– polluted.

$${\mathrm{P}\mathrm{L}\mathrm{I}=\left({\mathrm{CF}}^1{ \times \mathrm{CF}}^2 {\times \dots \dots \dots . \times \mathrm{CF}}^{\mathrm{n}}\right)}^{1/n}$$

(3)

Similar to the definition of the site PLI and classification, a Regional Pollution Load Index (RPLI) is defined in this work with the aid of Eq. 4, as the mth root of the product of the individual site average PLIs [35], calculated for the m=9 industrial sites (except for the control site GC) in Galati ISP area,

$${\mathrm{R}\mathrm{P}\mathrm{L}\mathrm{I}=\left({\mathrm{PLI}}^1{ \times \mathrm{PLI}}^2{\times \dots \dots \dots . \times \mathrm{PLI}}^{\mathrm{m}}\right)}^{1/\mathrm{m}}$$

(4)

Ecological risk factor ($E_r^i$) for an element i is defined with the aid of the Eq. (5):

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

(5)

where the toxic response factors ($T_r^i$) for the selected toxic trace elements are the following: Hg–40, Cd–30, As–10, Pb–5, Cu–5, Co–5, Ni–5, Cr–2, Mn–1, Zn–1, as indicated in the literature studies [2,31,32,33,34,37,38]. The risk classification using this individual ecotoxicological index is: $E_r^i$ < 40 – low potential ecological risk; 40 ≤ $E_r^i$ < 80 – moderate potential ecological risk; 80 ≤ $E_r^i$ < 160 – considerable potential ecological risk; 160 ≤ $E_r^i$ < 320 – high potential ecological risk; $E_r^i$ ≥ 320 – very high potential ecological risk [32].

The risk index RI is the sum of calculated ecological risk factors corresponding to all n=10 hazardous elements analyzed, according to Eq. (6):

$$\mathrm{R}\mathrm{I}={\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{E}}_{\mathrm{r}}^{\mathrm{i}}$$

(6)

The risk classification using this complex ecotoxicological index is: RI < 90 – low; 90 ≤ RI < 180 – moderate; 180 ≤ RI < 360 – strong; 360 ≤ RI < 720 – very strong; RI ≥ 720 – highly strong [32].

2.4. Mapping and Statistical Data Analysis

Principal Component Analysis (PCA) and Cluster Analysis (CA) – i.e. Joining or Tree Clustering – were applied to examine the relationship among the sampling sites and elemental load for each soil layer. The inputs consisted of 45 variables representing the concentrations for all 45 chemical elements which were determined in soils collected from nine industrial sites surrounding the enterprise and one control site (GC).

The experimental data concerning the spatial distribution of RI as well as PLI values for selected PCEs in all three investigated soil layers were organized in a geospatial data base, further processed ArcMap 10.4 Spatial Analyst [39]. This permitted generating six maps representing the spatial distribution of both RI and site PLI indices.

Due to the fact that the sampling points did not follow a regular network, the entire considered area was decomposed in Thiessen – Voronoi polygons [40,41]. In this case, an inverse distance weighting algorithm [42,43] gave the best results. Due to a reduced number of sampling points and in the absence of a confident data concerning the distribution function of PLI values, the nonparametric ANOVA Tukey, Man-Whitney, Dunnett post hoc as well as the Spearman correlation were used to calculate the probabilities the PLI distributions corresponding to the considered three layers are closer.

Further, the Discriminant Analysis (DA) [44] was used to evidentiate at which extent the PLI values of each layer are correlated.

PAST 4.1 [45], TIBCO^® Data Science / Statistica™ 10 [46], and OriginLab^® OriginPro^TM 2021 [47] were used for statistical data analysis, and MS Excel 2019 was employed for experimental data processing and graphing.

3. Results and Discussion

3.1. Concentrations of Elements in Industrial Soils

The results obtained by the combined analytical methods INAA, XRF and ICP-MS highlighted the existence of 45 elements in soils. Figure 2 shows the spatial and depth wise distribution of the element concentrations and Table 2 presents the concentration ranges and average of values obtained in this paper, along with the limits allowed by Romanian norms for trace elements in soil (normal values, low alert and intervention for sensitive use of soil, and high alert and intervention for less sensitive use of soil) [36] and literature data for Earth’s crust composition [48].

From Figure 2 it can be seen that the highest concentrations of most of the trace elements occur in sites G.2.2. G2.3 and G3.2 which are the closest to the industrial complex, as well as in the location G1.1, situated in the predominant wind direction, trend similar with previous findings for the same industrial area [11,16].

Compared with norms stipulated by Romanian law [36], the concentration values obtained in this work for several PCEs (Table 2) – As, Ba, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb and Zn – exceed the normal levels, while in the case of Ba, Cr, Pb and V the alert levels are surpassed. With the exception of Al, Ba, Co, K, Mg, Na Sc, Sr and Y, all other major and trace elements are present in the investigated soils in concentrations higher than the Upper Continental Crust (UCC) values [48].

The variation of the depth migration index DMI of identified chemical elements for each sampling location is illustrated in Figure 3.

It can be noticed a tendency for element mobilization in the deeper layers of soil, most of the sites being characterized by high (class C) and very high (class D) vertical migration potential; the urban site G4.1. is differing from other locations as being classified with very high migration potential of trace elements, trend also visible in Figure 2 as the elemental levels in the first soil layer are lower than in the second and third layers of this sublocation.

The results for PCA and CA of elemental concentrations are presented in Figures S1 and S2 – Supplementary Material, respectively, for 10 cases (soil sampling sites – 9 industrial sites around Galati integrated siderurgical plant and 1 control site) and 45 variables (concentrations of chemical elements).

PCA results modeled on the basis of the first two most significant principal components (PC1, PC2) specified in Figure S1 are depicted in Figure 4. The PCA shows that as the depth increases the sites are better grouped, with the exception of sites G4.1 for the depth 0-5 cm, respectively G1.1 for the depths 5-20 cm and 20-30 cm. In all cases, it is noticed that the control site GC is distant from the main group, as expected. Similar results were found by applying CA for sites clustering (Figure S2 – Supplementary Material).

3.2. Soil Mineralogy

In assessing the origin of the soil mineral component, the incompatible trace elements such as Sc, Co, Zr, rare earth elements (REE), Hf, or Th are very useful [5,8,13]. In this regard, felsic rocks are depleted in Sc but enriched in Th and light REE, while the mafic rocks appear enriched in Sc, Cr, Co, Ni and heavy REE [49]. On this subject, the Sc mass fraction in felsic rocks is less than 20 mg/kg, but exceeds 20-40 mg/kg in mafic rocks so that Sc is one of the most appropriate proxies for such kind of studies [50]. In the case of investigated soils, Sc mass fraction was of 9.8 ± 2 mg/kg. In this regard, the discriminating bi-plot Th/Co vs. La/Sc (Figure 5 a) [51] points with clarity towards a felsic origin of the mineralogy of investigated soil. The presence and distribution of Sc, Zr and Th in the investigated material permitted inferred the past processes that shaped the current situation. Indeed, the mineral zircon due to an extreme resilience to abrasion explained by its hardness on Mohs scale greater than 7.5, showed to be extremely resilient during recycling, so that the higher the Zr mass fraction, the larger the sedimentary material sorting and recycling [52].

In this case, the biplot Th/Sc vs. Zr/Sc showed a relatively reduced recycling when compared with the Dobrogea loess (Figure 5 b) [53], fact explained by the predominance of clastic material in considered soils. More information concerning the affinities of mineral constituents of the soil with the other mineral systems can be furnished, by reciprocal distribution of Sc, La and Th of La and Th [54]. In this regard, both discriminating La-Sc-Th ternary (Figure 5 c) and La vs. Th biplot (Figure 5 d) showed a good correlation between soil inorganic, mineral, component and the Upper Continental Crust (UCC) [48,54] and the North American Shale Composite (NASC) [55].

In the case of Sc-La-Th ternary diagram (Figure 5 c) , all the experimental points corresponding to Galati soils form a cluster around UCC [48,54] and NASC [55], suggesting a composition consisting of clay, silt or gravels from mixed sources. At its turn, the La vs Th bi-plot (Figure 5 d) shows a good correlation between these incompatible elements of which ratio of 3.3 ± 0.35 is close to the UCC one of 2.95 [54] or the NASC value of 2.65 [55]. For this approach to the UCC [48,54] and NASC [55] also pleads the obtained La/Sm mass fractions ratio of 5.47 ± 0.17, close to UCC value of 6.6 [48] and NASC of 5.7 [55].

3.3. Soil Contamination and Ecotoxicological Risk

The second aim of this study consisted of a detailed investigation of 13 PCEs distribution around the Galati integrated steel plant (ISP) given its status of potential contamination source. Accordingly, based on the mass fractions of V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Hg, Sb and Pb determined in soil cores covering the 0-5, 5-20 and 20-30 depth layers, the corresponding PLI (series PLI-13 in Figure 6) was calculated for each sampling point and each layer as one of the most representative contamination index (Figure 6). In the calculations of Contamination Factors (CF) (Table A1, Appendix A), the UCC element concentrations [48] were considered as background values.

Based on the average values of 9 site PLIs, a regional index RPLI of 1.20 was calculated for the metallurgical industrial area of Galati, SE Romania, emphasizing a polluted zone (RPLI >1).

Comparing the PLI values for 13 PCEs with PLI calculated for all 45 identified elements (series PLI-45 in Figure 6), it can be stated that the using of pollutant elements gives rise to relative higher PLI than in the case of considering the elements present at near baseline levels [35], suggesting a real deterioration of soil quality in a region, which is a correct approach.

Final results showing the PLI distribution for each sampling point, including the remote one GC, are illustrated by the violin diagram reproduced in Figure 7a. Here it can be remarked that for all three soil layers, the reference one appears less contaminated, fact sustained by PLI values varying between 0.45 and 0.78, i.e. lower than the threshold equal to one necessary to prove a local contamination.

To deepen the study of local contamination we have performed a DA of the PLI values by considering the sampling point as cases and the mass fractions of each of the 13 contaminating elements as variables. The result is reproduced in Figure 7b by a Root 2 vs. Root 1 biplot. This graph shows with clarity the presence of two distinct clusters, one consisting of a partial superposition of the 0-5 and 5-20 cm points and the other one containing only the 20-30 cm data. In our opinion, this graph suggests that the contamination process is spread onto the 0-20 cm layer while the third layer, between 20 and 30 cm, seems less affected.

This observation is confirmed also by several-samples ANOVA Tukey, Mann-Whitney (Table 3a) and Dunnett post hoc tests, as well as Spearman rank correlation (Table 3b) which showed a certain degree of similitude only between the 0-5 and 5-20 cm layers.

Another peculiarity can be remarked by analyzing the spatial distribution of PLI corresponding to each of the considered soil layers and illustrated by the maps in Figure 8 (a-c). Here it can be observed that the maximum contamination corresponds to two well evidenced maxima in the sites G2.2 (close to the slag dump) and G3.2 (at the north gate of the enterprise, close to iron scrap deposit, lime factory, steel plant and plate products mills), for which the PLI reaches closer values of 1.55 and 1.51, respectively, for the 0-5 cm layer, closely followed by the G2.3 site (at the south gate of the enterprise, close to agglomeration, sintering and coking plants, blast furnaces and ironmaking facilities) with a PLI value of 1.46. With the depth, these areas enlarge in the second layer (5-20 cm) until they merge in the third layer (20-30 cm), while the maximum PLI values decrease to 1.41 in all three places in the second layer, and 1.10, 1.15, and 1.18, respectively, in the third layer. In our opinion, this finding illustrates a 3D diffusion of contaminating elements into soil starting from the two hotspots better evidenced in Figure 8a.

Three maps were generated representing the spatial distribution of the risk index RI for each soil layer (Figure 8 d-f), calculated in Table 4 for 10 selected PCEs based on the individual ecotoxicological factors $E_r^i$.

The RI distribution maps highlight the depth diffusion trend of hazardous elements shown by the PLI maps (Figure 8 a-c).

The obtained values for the individual ecotoxicological factors $E_r^i$ and the risk factors RI (Table 4) show that highly ecological risk in the identified industrial hot spots is due to Cd and Hg.

4. Conclusions

The current study aimed to bring new insights on the quality of soils in the neighborhood of a large siderurgical complex located in Galati, SE region of Romania, regarding the compositional scheme, spatial and depth migration of 45 chemical elements (metals, radioelements, rare earth elements and other trace elements), contamination trends, mineral assemblage, ecotoxicological risk of selected potential contaminant elements and regional contamination level due to industrial activity related to ferrous metallurgy.

Our results obtained for the concentrations and environmental and safety risk indices of elements of concern demonstrate a present pollution of surface layer of soils adjacent to siderurgical industry, although the industrial production and activity had been restrained in the last decade, and a vertical migration of most of the analyzed elements in deeper soil layers.

The geochemical and contamination features suggest a similarity with results obtained in previous surveys performed in Galati industrial area, regarding the location of the impacted sites in dependence of the distance from the enterprise and dominant direction of wind. Our results could constitute a useful database for further investigations in the area and elaboration of land management strategies and exploitation of terrains, as well as decommissioning of the slag dump territory and valorization of metallic materials in various purposes.