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Journal of Environmental Science and Health, Part A Toxic/Hazardous Substances and Environmental Engineering
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Assessment of natural and anthropogenic factors on the distribution of chemical elements in soil from the Skopje region, North Macedonia Trajče Stafilov, Robert Šajn, Ružica Blaževska & Claudiu Tănăselia To cite this article: Trajče Stafilov, Robert Šajn, Ružica Blaževska & Claudiu Tănăselia (2022) Assessment of natural and anthropogenic factors on the distribution of chemical elements in soil from the Skopje region, North Macedonia, Journal of Environmental Science and Health, Part A, 57:5, 357-375, DOI: 10.1080/10934529.2022.2067444 To link to this article: https://doi.org/10.1080/10934529.2022.2067444
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JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH, PART A 2022, VOL. 57, NO. 5, 357–375 https://doi.org/10.1080/10934529.2022.2067444
Assessment of natural and anthropogenic factors on the distribution of chemical elements in soil from the Skopje region, North Macedonia Trajce Stafilova
, Robert Sajnb, Ruzica Blazevskaa, and Claudiu Tanaseliac
a
Institute of Chemistry, Faculty of Natural Sciences and Mathematics, Ss Cyril and Methodius University, Skopje, North Macedonia; Geological Survey of Slovenia, Ljubljana, Slovenia; cINCDO-INOE 2000 Research Institute for Analytical Instrumentation (ICIA), Cluj-Napoca, Romania b
ABSTRACT
ARTICLE HISTORY
The main objective of this study is to present the distribution of different chemical elements in soil samples from the Skopje region, North Macedonia. To determine the level of presence of chemical elements, soil samples are collected from a total of 60 locations. From each location, from an area of 5 5 km2 samples of soil are collected: topsoil (0–5 cm) and subsoil (20–30 cm). The soil samples were analyzed for 69 elements by using two instrumental methods: inductively coupled plasma-atomic emission spectrometry (ICP-AES) for macro-elements and inductively coupled plasma-mass spectrometry (ICP-MS) for trace elements. A factor analysis was applied to analyze the factors affecting the linear combination variables grouped at the same factor. Spatial distribution maps of each factor as well as distribution maps for the analyzed elements were prepared by universal kriging interpolation. It was found that the distribution of most elements follows the lithology of the examined area, except for some elements (Cd, Cu, Fe, Hg, Mn, Pb, and Zn) whose higher contents are found in the area of the city of Skopje as a result of urban and industrial activities (traffic, metal processing, fossil fuel combustion for heating).
Received 5 February 2022 Accepted 8 April 2022
Introduction The large concentration of the population in certain areas is accompanied by the presence of industry, transport, energy, or landfills of various waste materials, leading to the pollution of all environmental media: air, water, soil, flora, and fauna. In this regard, special attention should be paid to the pollution of the environment with potentially toxic elements (PTEs) that can originate from natural and anthropogenic sources. Natural sources of PTEs include lithogenic origin,[1] volcanic activity, evaporation from the see, while anthropogenic sources of pollution are increasing with rapid industrialization and modern lifestyles include car traffic, industrial plants for manufacturing and processing, power plants, commercial activities and waste disposal sites. PTEs can stay in the environment for hundreds of years.[2] Toxic elements and metals are commonly found as contaminants in soil, water, and food and are carried in the air. In recent years, environmental pollution with PTEs has been the basis for many studies.[3–12] The pollution with PTEs of soil, water, and air is an important part that should never be overlooked. The main cause of emission is anthropogenic sources, especially mining and metallurgical activities.[13–17] The emitted metals survive in the environment and the metal contamination that occurs as a result of ore mining persists for hundreds of years after mining has ceased.[13] CONTACT Trajce Stafilov [email protected] POB 162, 1000 Skopje, Macedonia ß 2022 Taylor & Francis Group, LLC
KEYWORDS
Soil; potentially toxic elements (PTE); spatial distribution; statistical analysis; Skopje region
On the base of our previously obtained data about the soil pollution from the city of Skopje, which occurred as a result of the emission of certain heavy metals (Cd, Cu, Zn, and Mn) from the metal industry, traffic, and urban activities,[18–21] the need arose to determine the distribution of various chemical elements in the wider area of the Skopje region. The obtained results for the content of the examined elements are statistically processed by multivariate factor analysis and cluster analysis to show the associations of chemical elements. Also, the spatial distribution maps are prepared for each of the analyzed elements.
Material and methods Study area description and generalized geology Skopje Region is one of the largest regions in North Macedonia (Figure 1). It is surrounded by the mountains Zeden, Ivanje (Matka) and Suva Gora in the west, Skopska Crna Gora in the north, Gradistanska Mountain in the east and northeast, Golesnica on the southeast and Kitka, Karadzica and Vodno, i.e. the massif of Mokra mountain to the south (Figure 1b). The valley stretches from northwest to southeast. The highest point of the investigated region is on Jakupica mountain (2,450 m) while the bottom of the Skopje valley is at a height of 225 to 340 m (Figure 2a). The region of Skopje is located between 21 100 and 21 300 east
Institute of Chemistry, Faculty of Natural Sciences and Mathematics, Ss Cyril and Methodius University,
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Figure 1. Location of the study area in North Macedonia (a) and its topographic map (b).
longitude and 41 500 and 42 100 north latitude. The altitude in the city center is 240 m. The Skopje Region covers 1812 km2 with about 600,000 inhabitants.[22] The Skopje region is dominated by hard rocks ranging in age from the Proterozoic to the Mesozoic. The widespread Skopje region consists of Neogene sediments and Quaternary alluvial deposits. Along the Vardar valley, which crosses the region from Northeast to Southwest, these rocks are overlain by Neogene to Pliocene lake sediments and Quaternary, mostly alluvial terrace sediments.[23] The Quaternary sediments of layers of gravel, sand, and clay. As can be seen on the geological map of the Skopje region (Figure 2b), the dominant geological formations are Paleogene and Mesozoic flysch in the northern and southeastern parts of the region, Quaternary alluvial and Neogene sediments in the central part of the Skopje valley, Proterozoic, Mesozoic, and Paleozoic carbonates in the western part, Proterozoic gneisses, and shales in the southern part, as well as the appearance of igneous rocks in the northwestern and southeastern part of the region.[18,20] From a pedological point of view, the composition of soil from the Skopje Valley was determined by Filipovski et al.[24] The following major soil types have been found to be present: regosol, vertisol, cambisol and fluvisol. Generally, it is composed of the following substances: humus, soil with fine particles and fine-grained sand of medium consistency and dark brown; finegrained clay, fine-grained and coarse-grained sand and gravel and organic impurities with medium consistency and brown color; fine to coarse gravel with sandy, medium consistency with the presence of quartz dust and variable percentage of granules and light reddish and brown.
Soil sampling and preparation Samples of topsoils in the investigated area were collected according to the European guidelines and also according to our experience.[16,21,25,26] The study area (1812 km2) was covered by the same sampling grid of 5 5 km as used for the preparation of the Geochemical Atlas of Macedonia [23] (Figure 2a,b). Altogether 120 soil samples were collected from 60 locations. To distinguish eventual anthropogenic pollution at the surface from the natural geochemical composition at deeper layers, samples from two intervals were collected, topsoil (0–5 cm) and subsoil (20–30 cm). To obtain representative composite samples, five subsamples from each location on a square plot of 10 10 m were collected. The soil samples brought to the laboratory were cleaned from plant material and stones and then homogenized and dried at room temperature. Subsequently, they were passed through a 2 mm sieve and ground in a porcelain mortar until reaching a final particle size below 125 lm. For the digestion of soil samples, open wet digestion with a mixture of acids was applied (HNO3, HF, HClO4, and HCl according to ISO Standard (ISO 14869–1:2001).[27] Instrumentation All samples were analyzed by ICP-AES (Varian, model 715ES) for the elements with high contents (Ag, Al, B, Ba, Ca, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, Pb, Sr, V, and Zn).[28] Trace elements (As, Au, Be, Bi, Br, Cd, Ce, Co, Cs, Dy, Er, Eu, Ga, Gd, Ge, Hf, Hg, Ho, I, In, Ir, La, Lu, Mo, Nb, Nd, Os, Pd, Pr, Pt, Rb, Re, Rh, Ru, Sb, Sc, Se, Sm, Sn, Ta, Tb, Te, Ti, Tl, Tm, W, Y, and Zr) were analyzed by ICP-MS
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Figure 2. Elevation map with soil sampling locations and simplified geological map of the Skopje Region.
measurements on a SCIEX Perkin Elmer Elan DRC II (Canada) inductively coupled plasma mass spectrometer with quadruple and single detector setup.[29] Quality control is checked by the recovery for the investigated elements ranging from 98.2% to 100.8%. The quality control was also performed by the analysis of certified reference soil and geological samples: soil sample JSAC 0401 (The Japan Society for Analytical Chemistry) and rock CRM samples undersaturated igneous rock SARM 3 NIM-L Lujaurite (SA Bureau of Standards, Pretoria, S. Africa), rock NCS DC71306 (GBW07114) (China National Analysis Center). It has been determined that the obtained values are within the standard deviation of the certified reference materials. Data processing Data analysis and the production of maps were performed on a Statistica (ver. 13), Autodesk Map (ver.2008), QGIS (ver. 3.10), and Surfer (ver. 13) software. All field observations, analytical data, and measurements were introduced into the data matrix. Parametric and nonparametric statistical methods were used for data analysis. Box-Cox transformations were used to acquire normal distributions. Multivariate R-mode factor analysis was used to reveal associations of the chemical elements.[30] From numerous
variables, the factor analysis (FA) derives a smaller number of new, synthetic variables. The factors contain significant information about the original variables, and they may have certain meanings. Factor analysis was performed on variables standardized to a mean of zero and one unit of standard deviation.[31] As a measure of similarity between variables, the product-moment correlation coefficient (r) was applied. For orthogonal rotation, the varimax method was used. Multivariate cluster analysis was also applied to determine the significance of the factor analysis and the stability of the new synthetic variables, that is, associations of elements.[31] Cluster analysis was used with a similar aim as factor analysis, in case high values for the loadings of certain variables were not acquired. In such case is applied the data processing method based on a matrix of remoteness (distances) or nearness (similarities). How the dependence between the variables will be expressed, will depend on the use of a single or several dimensions. To establish the dependence among a series of variables in a multidimensional system, the Euclidean distance matrix is most commonly used. The universal kriging method with linear variogram interpolation was applied for the construction of the areal distribution maps of the analyzed elements and the obtained factor scores. Seven classes of the following percentile values were selected: 0–10, 10–25, 25–40, 40–60, 60–75, 75–90, and 90–100.
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Table 1. Descriptive statistics for the content of the elements in topsoil (0–5 cm) and subsoil (20–30 cm), n ¼ 120. Element Ag Al As B Ba Be Br Ca Cd Ce Co Cr Cs Cu Dy Er Eu Fe Ga Gd Ge Hf Hg Ho K La Li Lu Mg Mn Mo Na Nb Nd Ni P Pb Pd Pr Rb Rh Sb Sc Sm Sn Sr Ta Tb Ti Tl Tm V W Y Yb Zn Zr
X
Md
Min
2.7 2.7 38 14 250 4.0 20 4.5 4.1 48 35 89 4.8 30 3.6 1.8 1.2 2.7 24 4.9 0.84 1.3 60 0.67 0.87 22 19 0.25 0.92 700 1.2 0.44 19 22 81 530 120 0.92 5.7 100 26 1.7 20 4.6 7.6 68 1.1 0.68 0.74 0.48 0.25 70 2.0 18 1.6 740 71
2.0 2.6 25 14 240 3.4 15 2.9 0.43 41 28 74 3.8 24 3.0 1.6 1.1 2.6 23 4.4 0.60 1.0 33 0.56 0.83 19 16 0.22 0.83 670 0.98 0.36 17 19 62 500 28 0.76 4.8 84 20 0.78 12 4.2 3.3 59 0.97 0.60 0.61 0.37 0.22 64 1.6 15 1.4 86 59
1.0 0.48 7.7 4.0 80 0.005 0.005 0.37 0.005 8.7 3.0 7.8 0.005 5.2 0.32 0.13 0.13 0.52 1.6 0.57 0.058 0.11 5.0 0.059 0.39 3.1 8.0 0.015 0.052 290 0.005 0.063 3.7 3.4 5.7 160 5.0 0.14 0.92 7.7 5.0 0.085 2.0 0.55 0.005 8.6 0.050 0.069 0.11 0.050 0.017 11 0.035 3.6 0.095 40 23
Unit mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg % mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg
Max
S
A
E
X
Md
Min
2.4 1.6 36 7.8 98 3.4 18 4.8 25 33 26 65 3.6 39 2.4 1.3 0.67 0.94 9.6 3.1 0.85 0.94 56 0.46 0.31 16 8.5 0.17 0.60 290 1.2 0.30 7.8 15 110 300 640 0.59 3.7 66 23 5.7 29 3.0 22 37 0.73 0.44 0.43 0.53 0.18 33 2.0 10 1.1 4600 38
4.14 1.16 2.25 1.59 1.06 2.07 2.06 2.17 7.45 1.53 2.91 2.22 1.63 6.52 1.08 1.20 0.79 0.16 0.29 0.91 3.59 1.84 0.52 1.13 1.11 2.08 1.28 1.33 1.20 1.42 4.34 0.96 0.96 1.16 5.81 1.59 7.71 1.84 1.24 1.72 2.85 7.40 5.55 0.98 7.02 1.88 1.34 0.96 1.71 2.28 1.19 1.00 4.26 0.92 1.28 7.71 1.80
20.86 1.55 5.45 4.00 2.52 8.24 4.65 5.69 55.64 2.67 12.03 6.38 3.68 46.82 0.93 1.36 0.25 0.12 0.10 0.39 15.94 4.72 1.33 1.06 1.76 5.63 1.26 1.84 1.29 2.57 25.02 0.07 1.38 1.12 39.08 3.64 59.67 3.66 1.43 4.05 10.12 55.14 35.47 0.56 51.07 5.98 2.72 0.51 3.99 7.39 1.33 1.32 25.08 0.22 1.66 59.59 5.12
2.9 2.7 35 14 250 4.1 17 4.7 1.4 51 33 95 5.3 26 3.6 1.8 1.2 2.7 26 5.1 0.73 1.3 71 0.68 0.87 24 21 0.25 0.96 660 1.1 0.42 21 24 86 510 54 0.91 6.1 110 22 1.1 18 4.9 5.0 65 1.0 0.70 0.80 0.46 0.25 69 1.8 20 1.6 300 82
2.2 2.4 27 13 240 3.7 15 2.8 0.38 41 29 81 4.0 24 3.3 1.6 1.1 2.8 24 4.4 0.60 1.1 41 0.60 0.85 20 18 0.21 0.86 660 1.1 0.35 18 20 65 440 27 0.75 5.0 91 15 0.90 16 3.9 3.3 59 0.96 0.64 0.69 0.34 0.22 68 1.6 17 1.5 82 74
1.1 0.55 0.050 4.5 72 0.005 0.005 0.18 0.005 0.32 0.12 10 0.057 5.5 0.011 0.005 0.005 0.67 0.15 0.016 0.005 0.005 5.0 0.005 0.38 0.12 7.3 0.005 0.098 240 0.005 0.076 0.16 0.11 7.2 120 5.0 0.050 0.034 1.1 5.0 0.005 0.050 0.050 0.005 6.7 0.050 0.005 0.006 0.050 0.005 13 0.005 0.14 0.005 35 0.63
Topsoil (0–5 cm) 17 7.6 170 45 630 20 88 26 190 170 170 350 19 310 11 5.8 2.9 4.9 47 13 5.4 5.2 170 2.1 1.9 88 44 0.82 2.9 1700 8.8 1.2 43 64 860 1700 5000 2.9 17 370 120 44 210 13 170 240 3.8 1.9 2.5 2.9 0.82 170 14 46 5.3 36000 230
Max
S
A
E
2.90 0.91 4.05 0.66 1.21 1.13 1.03 2.22 4.52 1.34 2.01 2.10 3.63 1.89 1.29 1.33 1.13 0.15 0.52 1.23 1.39 1.55 1.81 1.34 1.03 1.96 1.36 1.46 1.30 1.02 0.66 1.38 1.41 1.23 6.00 1.42 5.65 1.15 1.24 1.13 1.45 2.18 2.05 1.19 2.34 2.41 0.55 1.26 1.70 1.48 1.38 0.59 1.02 1.22 1.43 5.74 1.89
10.52 0.73 21.67 0.32 3.64 1.33 0.94 5.90 22.36 1.99 6.79 6.25 18.40 5.88 2.05 2.23 1.45 0.50 1.07 1.71 2.54 2.64 4.61 2.23 1.57 5.26 1.81 2.67 1.45 2.62 0.60 1.60 2.93 1.56 41.46 2.51 35.61 2.01 1.59 1.28 1.51 5.86 5.96 1.39 6.89 9.80 0.24 1.90 3.95 1.90 2.49 0.72 1.01 1.94 2.59 35.67 4.66
Subsoil (20–30 cm) 13 7.7 260 27 630 14 55 27 23 190 130 350 31 84 13 6.9 3.9 5.2 54 18 2.3 4.6 410 2.6 1.9 95 53 0.92 2.7 1600 2.9 1.3 52 83 920 1700 810 3.1 21 270 81 4.8 83 17 27 250 2.5 2.5 2.5 2.0 0.97 150 5.9 64 6.1 7100 280
2.0 1.6 38 5.3 94 3.4 14 5.1 3.8 38 23 65 4.7 14 2.7 1.4 0.81 0.90 10 3.7 0.43 1.0 81 0.52 0.31 18 9.3 0.19 0.56 230 0.66 0.29 10 17 120 310 110 0.61 4.3 57 19 0.91 15 3.6 5.0 38 0.63 0.51 0.49 0.49 0.19 29 1.3 13 1.2 1000 54
Abbreviations: X, arithmetical average; Md, median; Min, minimum; Max, maximum; º, standard deviation; A, skewness; ð, kurtosis.
Results and discussion As a result of the analysis of soil samples, data were obtained on the content of a total of 68 elements from which 19 elements present in higher content were analyzed by ICP-AES (Ag, Al, B, Ba, Ca, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, Pb, Sr, V, and Zn) and 49 trace elements by ICPMS (As, Au, Be, Bi, Br, Cd, Ce, Co, Cs, Dy, Er, Eu, Ga, Gd, Ge, Hf, Hg, Ho, I, In, Ir, La, Lu, Mo, Nb, Nd, Os, Pd, Pr, Pt, Rb, Re, Rh, Ru, Sb, Sc, Se, Sm, Sn, Ta, Tb, Te, Ti, Tl,
Tm, W, Y, and Zr). The descriptive statistics for the content of the elements in topsoil and subsoil samples are presented in Table 1. The values for Al, Ca, Fe, K, Mg, Na, and Ti are given in %, values for Hg and Rh in mg/kg, while the values for the content for the remaining elements are given in mg/ kg. The content of Au, Bi, I, In, Ir, Os, Pt, Re, Ru, Se, and Te are not shown in the table because they are bellow the detction limit of the analytical technique. Basic descriptive statistics were used for the statistical processing of the values obtained from this study. The
JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH, PART A
obtained values are within the average range, from which it can be determined that the presence of the investigated elements in the soil samples reflects the lithology of the area [20,21] with small deviations in the central part of the city of Skopje with the anthropogenic influence visible by increasing the content of some elements (Cd, Cu, Fe, Hg, Mn, Pb, and Zn). Most of the analyzed elements are within the limits of Dutch soil standards, but some elements exceed these values. The order of the distribution of contents of the major elements (Al, Ca, Fe, K, Mg, Na, and Ti) were in the following ranges: 0.48–7.6% Al; 0.37–26% Ca; 0.52–4.9% Fe; 0.39–1.9% K; 0.05–2.9% Mg, 0.062–1.2% Na and 0.11–2.5% Ti for topsoil (0-5 cm) and 0.55–7.7% Al; 0.18–27% Ca; 0.67–5.2% Fe; 0.38–1.9 K; 0.098–2.7% Mg, 0.076–1.3% Na, and 0.006–2.5% Ti for bottom soil (20-30 cm). The content of major elements is most frequently a result of the dominant geological formations of the area: Neogene clastic sediments, Paleozoic sandstone, and magmatic rocks.[18,20] The ratio of the contents between the topsoil and the subsoil is presented in Supplementary materials (Table 2) and no significant differences were found. The ratio changes from 0.88 for Ag to 1.27 for Rh, which shows the absence of noticeable influence of eventual anthropogenic activities. A comparative analysis of the contents of the analyzed elements in topsoils from the Skopje Region and the soil from the city of Skopje (urban zone), soil from Macedonia [21,23] and Europe [26] is given in Table 3. It was found that the contents of many elements are different in soil from the Skopje region compared with those from Macedonian soil as well as with the European soil (Table 3) showing their dependence of the specific lithogenic origin of the rocks in the separate sub-regions. It is important to note that, except in the case of Ba, Co and Ni, the element contents found in soil samples of the Skopje region are below the target values given in The New Dutchlist https://www.esdat.net/environmental%20standards/dutch/annexs_i2000dutch%20environmental%20standards.pdf), while in some parts of the region some of the elements exceeded the target values (As, Cd, Cr, Cu, Pb, and Zn) or even the action values (As, Cd, Ni, Pb, and Zn) which is due to the lithogenic origin of these elements in soil from the Vardar tectonic zone [21,23] or due to the anthropogenic activities in the city of Skopje.[18,20] From the comparison of the contents of the investigated elements in the soils of the Skopje Region with those of the urban zone of the city of Skopje [18,20] it can be noticed that the urban activities in the city, as well as the industrial activities, lead to increased contents, especially of Cd, Cu, Fe, Hg, Mn, Pb, and Zn. The factor analyses were performed separaterly for the major elements (analyzed by ICP-AES) and trace elements (analyzed by ICP-MS). In the first factor analysis, the following 19 major elements were included: Ag, Al, B, Ba, Ca, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, Pb, Sr, V, and Zn after preparation of the correlation matrix of these elements (Tables 4 and 5). Four elements (Ag, B, Li, Na, and P) were eliminated from further analysis because they had low shares of communality. The total communality of the factors was
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Table 2. Concentration ratios (FO) of the average contents (Box-Cox transformed) in topsoil versus subsoil. Element Ag Al As B Ba Be Br Ca Cd Ce Co Cr Cs Cu Dy Er Eu Fe Ga Gd Ge Hf Hg Ho K La Li Lu Mg Mn Mo Na Nb Nd Ni P Pb Pd Pr Rb Rh Sb Sc Sm Sn Sr Ta Tb Ti Tl Tm V W Y Yb Zn r
Unit mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg % mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg
FO T F R Topsoil Subsoil (T/B) (test) Sign (ratio) Sign (T/B) Sign 2.0 2.3 0.88 1.55 NS 1.12 NS 0.71 2.4 2.4 1.02 0.21 NS 1.12 NS 0.77 29 26 1.10 0.61 NS 1.18 NS 0.70 13 13 1.01 0.12 NS 1.74 NS 0.66 240 240 0.99 0.16 NS 1.10 NS 0.94 3.1 3.1 1.00 0.01 NS 1.09 NS 0.43 16 13 1.20 0.90 NS 1.15 NS 0.25 NS 2.9 3.0 0.97 0.14 NS 1.03 NS 0.92 0.31 0.25 1.25 0.53 NS 1.03 NS 0.62 42 43 0.98 0.13 NS 1.46 NS 0.65 31 29 1.08 0.55 NS 1.16 NS 0.60 75 81 0.93 0.58 NS 1.03 NS 0.88 4.0 4.4 0.91 0.61 NS 1.05 NS 0.70 23 23 1.01 0.13 NS 1.28 NS 0.87 3.1 3.0 1.03 0.21 NS 1.36 NS 0.68 1.5 1.5 1.01 0.10 NS 1.28 NS 0.67 1.1 1.1 0.99 0.07 NS 1.41 NS 0.69 2.7 2.7 0.99 0.12 NS 1.08 NS 0.88 24 25 0.95 0.67 NS 1.08 NS 0.46 4.4 4.4 1.00 0.04 NS 1.42 NS 0.68 0.67 0.63 1.07 0.46 NS 1.28 NS 0.24 NS 1.1 1.1 1.00 0.00 NS 1.32 NS 0.49 31 35 0.90 0.40 NS 1.07 NS 0.45 0.57 0.55 1.04 0.25 NS 1.34 NS 0.68 0.82 0.82 1.00 0.03 NS 1.06 NS 0.84 19 20 0.95 0.34 NS 1.41 NS 0.61 17 19 0.92 1.09 NS 1.02 NS 0.88 0.21 0.20 1.04 0.25 NS 1.19 NS 0.63 0.80 0.86 0.93 0.59 NS 1.29 NS 0.87 650 620 1.05 0.72 NS 1.15 NS 0.78 0.99 0.95 1.04 0.26 NS 1.30 NS 0.50 0.36 0.34 1.03 0.26 NS 1.10 NS 0.95 18 19 0.93 0.81 NS 1.63 NS 0.37 20 20 0.97 0.21 NS 1.44 NS 0.64 57 61 0.93 0.44 NS 1.01 NS 0.90 460 440 1.06 0.5 9 NS 1.23 NS 0.95 29 27 1.08 0.55 NS 1.03 NS 0.58 0.82 0.77 1.05 0.41 NS 1.50 NS 0.36 5.0 5.2 0.96 0.26 NS 1.42 NS 0.64 91 97 0.94 0.50 NS 1.15 NS 0.65 20 15 1.27 1.48 NS 1.26 NS 0.36 0.83 0.83 1.00 0.02 NS 1.17 NS 0.56 14 13 1.05 0.29 NS 1.17 NS 0.71 4.0 4.1 0.98 0.15 NS 1.40 NS 0.66 3.7 3.4 1.10 0.40 NS 1.18 NS 0.57 61 59 1.05 0.47 NS 1.03 NS 0.88 0.96 0.89 1.08 0.55 NS 1.04 NS 0.51 0.60 0.59 1.01 0.09 NS 1.38 NS 0.68 0.68 0.72 0.95 0.45 NS 1.43 NS 0.61 0.27 0.26 1.03 0.12 NS 1.01 NS 0.51 0.21 0.21 1.03 0.20 NS 1.21 NS 0.66 66 66 1.01 0.09 NS 1.15 NS 0.85 1.6 1.5 1.07 0.37 NS 1.06 NS 0.44 16 18 0.92 0.63 NS 1.51 NS 0.68 1.4 1.3 1.05 0.33 NS 1.27 NS 0.66 86 81 1.06 0.72 NS 1.17 NS 0.94 65 72 0.91 0.84 NS 1.94 NS 0.50
78%. Four geogenic factor associations (Factors) were identified. From the obtained factors groups, it can be concluded that the distribution of the elements actually occurs as a result of both geogenic and anthropogenic distribution. The dendrogram of the distances among the individual elements obtained by the application of the multivariate cluster analysis is presented in Figure 3. Similar results were achieved by the application of multivariate factor analysis. All of the obtained factors correspond to the four obtained clusters. The only difference is observed in the cluster that
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Table 3. Comparison of the median, minimal, and maximal values of the content of the analyzed elements in topsoil from Skopje Region with soil from the city of Skopje, North Macedonia, and Europe. Dutchlist Element Ag Al As B Ba Be Br Ca Cd Ce Co Cr Cs Cu Dy Er Eu Fe Ga Gd Ge Hf Hg Ho K La Li Lu Mg Mn Mo Na Nb Nd Ni P Pb Pd Pr Rb Rh Sb Sc Sm Sn Sr Ta Tb Ti Tl Tm V W Y Yb Zn Zr
Unit mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg % mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg % mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg
Skopje Region (this work)
Target
Action
29
55
200
625
0.8
12
20 100
240 380
36
190
10
200
35
210
85
530
140
720
Md 2.0 2.6 25 14 240 3.4 15 2.9 0.43 41 28 74 3.8 24 3.0 1.6 1.1 2.6 23 4.4 0.60 1.0 33 0.56 0.83 19 16 0.22 0.83 670 0.98 0.36 17 19 62 500 28 0.76 4.8 84 20 0.78 12 4.2 3.3 59 0.97 0.60 0.61 0.37 0.22 64 1.6 15 1.4 86 59
Min–Max 1.0–17 0.48–7.6 7.7–170 4.0–45 80–630 0.005–20 0.005–88 0.18–27 0.005–23 0.32–190 0.12–130 10–350 0.057–31 5.5–84 0.011–13 0.005–6.9 0.005–3.9 0.67–5.2 0.15–54 0.016–18 0.005–2.3 0.005–4.6 5.0–170 0.005–2.6 0.38–1.9 0.12–95 7.3–53 0.005–0.92 0.098–2.7 240–1600 0.005–0.60 0.063–1.2 3.7–43 3.4–64 5.7–860 160–1700 5.0–5000 0.14–2.9 0.92–17 7.7–370 5.0–120 0.085–44 2.0–210 0.55–13 0.005–170 8.6–240 0.050–3.8 0.069–1.9 0.11–2.5 0.050–2.0 0.017–0.82 11–170 0.035–14 3.6–46 0.095–5.3 40–36000 23–230
City of Skopje[18] Md 2.7 3.8 12 – 300 5.1 19 4.8 0.54 52 38 100 4.0 33 3.3 1.6 1.2 3.1 26 4.9 0.84 0.88 130 0.60 1.2 26 – 0.20 1.2 720 1.5 0.53 22 25 86 – 51 1.1 0.12 110 25 1.2 24 4.8 4.8 91 0.70 0.65 0.88 0.19 0.22 – 1.3 24 1.3 100 75
Min–Max 0.1–29 0.86–6.6 0.050–68 – 49–2000 0.005–18 0.005–120 0.42–26 0.050–77 0.025–250 0.12–130 42–350 0.005–19 7.3–590 0.005–9.4 0.005–4.7 0.005–3.3 1.1–5.2 0.005–79 0.005–12 0.005–5.4 0.005–3.7 5–6100 0.005–1.8 0.37–2.7 0.05–120 – 0.005–0.64 0.29–2.3 340–5600 0.05–310 0.085–6.0 0.05–74 0.013–71 24–320 – 5.0–2900 0.050–4.9 0.005–0.95 0.05–430 5.0–180 0.005–42 0.050–91 0.050–14 0.005–150 3.0–540 0.050–2.3 0.005–1.7 0.001–2.8 0.050–10 0.005–0.65 – 0.005–5.5 0.014–79 0.005–4.2 23–18000 0.005–340
Macedonia[23] Md – 1.3 10 – 430 2.0 – 1.3 0.30 56 17 88 – 28 – – – 3.5 – – – 1.0 – – 1.9 25 26 – 0.94 900 0.90 1.3 11 – 46 620 32 – – 86 – 0.80 12 – 2.6 140 0.70 – 0.34 0.70 – 89 1.3 18 – 83 35
Min–Max – 0.05–35 1.0–720 – 6–2900