The Science of the Total Environment 300 (2002) 229–243

Heavy metals in urban soils: a case study from the city of Palermo (Sicily), Italy Daniela Salvagio Mantaa, Massimo Angeloneb, Adriana Bellancaa,*, Rodolfo Neria, Mario Sprovieria a

Dipartimento di Chimica e Fisica della Terra (C.F.T.A), Universita` di Palermo, Via Archirafi 36, 90123-Palermo, Italy b ENEA, AMB TEIN CHIM, C.R. Casaccia, S.P. Anguillarese Km 1.200, 00060-Rome, Italy Received 25 January 2002; accepted 11 June 2002

Abstract Concentrations of V, Mn, Cd, Zn, Ni, Cr, Co, Cu, Pb, Hg and Sb were measured on 70 topsoil samples collected from green areas and parks in the city of Palermo (Sicily) in order to: (1) assess the distribution of these heavy metals in the urban environment; (2) discriminate natural and anthropic contributions; and (3) identify possible sources of pollution. Mineralogy, physico-chemical parameters, and major element contents of the topsoils were determined to highlight the influence of ‘natural’ features on the heavy metal concentrations and their distribution. Medians of Pb, Zn, Cu and Hg concentrations of the investigated urban soils are 202, 138, 63 and 0.68 mg kgy1, respectively. These values are higher, in some case by different orders of size, than those of unpolluted soils in Sicily that average 44, 122, 34 and 0.07 mg kgy1. An ensemble of basic and multivariate statistical analyses (cluster analysis and principal component analysis) was performed to reduce the multidimensional space of variables and samples, thus defining two sets of heavy metals as tracers of natural and anthropic influences. Results demonstrate that Pb, Zn, Cu, Sb and Hg can be inferred to be tracers of anthropic pollution, whereas Mn, Ni, Co, Cr, V and Cd were interpreted to be mainly inherited from parent materials. Maps of pollutant distribution were constructed for the whole urban area pointing to vehicle traffic as the main source of diffuse pollution and also showing the contribution of point sources of pollution to urban topsoils. 䊚 2002 Elsevier Science B.V. All rights reserved. Keywords: Urban soils; Heavy metals; Soil pollution; Geostatistics

1. Introduction Heavy metals in urban soils have been shown to be very useful tracers of environmental pollution (e.g. Davies and Houghton, 1984; Albasel and Cottenie, 1985; Burguera et al., 1988; Bacon et al., 1992; Kelly et al., 1996). *Corresponding author. Tel.: q39-091-6161574; fax: q39091-6168376. E-mail address: [email protected] (A. Bellanca).

Urban soils are known to have peculiar characteristics such as unpredictable layering, poor structure, and high concentrations of trace elements (Kabata-Pendias and Pendias, 1992; Tiller, 1992). They are the ‘recipients’ of large amounts of heavy metals from a variety of sources including industrial wastes, vehicle emissions, coal burning waste, and other activities. In areas where public gardens and parks are exposed to significant pollution

0048-9697/02/$ - see front matter 䊚 2002 Elsevier Science B.V. All rights reserved. PII: S 0 0 4 8 - 9 6 9 7 Ž 0 2 . 0 0 2 7 3 - 5

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levels, dust from the ground may have toxic effects as a consequence of inhalation or ingestion by humans, particularly children, which poses major health hazards (Culbard et al., 1988; Folinsbee, ´ 1993; Sanchez-Camazano et al., 1994). Furthermore, any contamination of urban soils could cause in turn groundwater contamination because metals of the polluted soils tend to be more mobile than those of unpolluted ones (Steinmann and Stille, 1997; Wilcke et al., 1998). Although a geographically widespread dataset has been generated from the analysis of urban soils, many from a single city (Farmer and Lyon, ´ 1977; Davies et al., 1987; Sanchez-Camazano et al., 1994, Strnad et al., 1994; Markus and McBratney, 1996) or from urban agglomerations within a country (Carey et al., 1980; Culbard et al., 1988; Tiller, 1992), some from Italy (Facchetti et al., 1982; Bini et al., 1984; Ferretti et al., 1991; Angelone et al., 1995, 1999) and none from Sicily, concentrations of some toxic elements (e.g. Hg, Sb and V) remain poorly documented. Mercury is one of the important pollutants and it is inferred to dramatically accumulate in different environments due to recent human activity. Most scientific papers deal with Hg contamination of waters or sediments, mainly as reflection of mining and smelting activities (Guerzoni et al., 1984; Covelli et al., 2001). Antimony and, to a certain extent, vanadium are inferred to potentially cause health problems when people are exposed to their relatively high levels. These metals have been increasingly entering the urban environment during recent years coming from industrial dust and burning fuel oils. In this study, we start with a general characterization of bulk mineralogy and geochemistry of topsoils from the city of Palermo. Then, the concentration data for 11 heavy metals (Pb, Hg, Cu, Cr, Zn, Sb, Mn, V, Co, Ni and Cd) are presented and discussed. In order to highlight the extent and severity of contamination, we take advantage of the availability of a dataset deriving from the analysis of ‘natural’ soils in Sicily (Bellanca et al., 1996; Palumbo et al., 2000). Basic and multivariate statistical procedures were used to identify heavy metal sources and discriminate natural and

Fig. 1. Map of the Palermo city (Sicily) with location of sampling sites of topsoils (solid circles), calcarenitic bedrocks (open squares), and cemented detritus (solid square).

anthropic contributions as well as point and nonpoint sources of contamination. 2. Materials and sampling strategy A total of 70 non-stratified topsoil samples (depths0–10 cm) were collected from green areas and public parks within the city of Palermo (Fig. 1). Sampling sites were selected where the last human perturbations go back to at least 10 years ago and where chemicals (such as fertilizers, pesticides) and sewage sludges have not been used. To avoid effects due to the differential uptake of metals by vegetation, sampling was carried out where plants with superficial roots are not present. At each sampling point, three sub-samples, with a 20=20 cm surface, were taken and then mixed to obtain a bulk sample. Such a sampling strategy was adopted in order to reduce the possibility of random influence of urban waste not clearly visible. All the samples were collected with a stainless steel spatula and kept in PVC packages, at room temperature, for not more than 12 h before starting analytical procedures.

D.S. Manta et al. / The Science of the Total Environment 300 (2002) 229–243

Soils in the city of Palermo are developed on Pleistocene calcarenites or recent alluvial sediments derived from the erosion of calcareous mountains surrounding the city. Locally, the soils have received in the past some contribution from Terra Rossa soils of the neighboring country. To define the lithologic imprint on the geochemical composition of the urban soils, five calcarenite samples were collected from different sites in Palermo and from the Monte Gallo hill (NW of the city); one sample of cemented detritus was taken from the Favorita Park (Fig. 1). 3. Analytical methods The soil samples were air-dried for approximately 24 h and sieved through a 2-mm sieve. The samples were analyzed for pH, cation exchange capacity (CEC) and organic matter contents. Values of pH were measured in H2O and in 1 M KCl solution with a soilysolution ratio of 1:25, using a Metrohn 691 with a glass electrode AC 9101. CEC was determined in a 10% Ba(CH3COO)xH2O and 0.1 N MgSO4 extracting solutions (Gazzetta Ufficiale, 1992). Organic matter contents were determined by soil ignition at a temperature of 450 8C (Allen et al., 1974). Soil mineralogy was investigated by powder Xray diffraction (XRD, Philips PW1729 apparatus) using CuKa radiation filtered by Ni. The relative proportions of minerals were determined according to methods and data of Schultz (1964), Barahona et al. (1982). CaCO3 contents were measured by means of a classic gas-volumetric technique as reported in Husselmann (1966). The major element concentrations were determined by X-ray fluorescence spectrometry (XRF, Philips PW1400 apparatus), on bulk-sample pressed, boric-acid backed pellets. X-Ray counts were converted into concentrations by a computer program based on the matrix correction method according to Franzini et al. (1975). The accuracy of determinations was checked by using certified reference materials. Analytical errors were below 1% for Si, Al, Na, below 3% for Ti, K, Fe, Ca and below 10% for Mg and P.

231

‘Pseudo-total metal contents’ were obtained by digesting soil samples with aqua regia in bombs using a microwave oven (CEM MSD 2000 equipment). The term ‘pseudo-total’ accounts for the aqua regia digestion not completely destroying silicates. This method is widely used in environmental geochemistry studies and recommended by the National Government regulation. Mn, Cr, Ni, Co, Cu, Zn, Pb and Cd concentrations were measured by atomic absorption spectrophotometry coupled with a graphite furnace (GF-AAS) using a 5100 Perkin–Elmer instrument. The elements Sb and V were determined by inductively coupled plasma mass spectrometry (ICP-MS) using an ELAN 6000 Perkin–Elmer. All calibration standards were prepared in the same acid matrix used for the soil samples. Caution was used in preparing and analyzing samples to minimize contamination from air, glassware and reagents, which were all of Suprapur quality. Replicated measures of international reference materials (IAEA SOIL 5 and SOIL 7), reagent blanks, and duplicated soil samples (approx. 20% of the total number of soil samples was used for this purpose) randomly selected from the set of available samples were used to assess contamination and precision. The analytical precision, measured as relative standard deviation, was routinely between 5 and 6%, and never higher than 10%. Mercury concentrations were determined by Direct Mercury Analyzer-80 (DMA-80). Accuracy of analyses was checked using an international soil standard (Best-1) and duplicate samples. The quality control gave good precision (S.D.-5%) for all samples. 4. Results and discussion 4.1. Physico-chemical parameters The main physico-chemical parameters determined for urban topsoils from Palermo include: (i) organic matter contents ranging from 3 to 25%, with most values approximately 6%; (ii) values of pH ranging in a narrow interval (7.2–8.3), which suggests neutral to sub-alkaline conditions for all the topsoils; and (iii) cation exchange capacity (CEC) showing a very broad interval of variation,

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from 5 to 56 meqy100 g, with a mean value of 26 meqy100 g comparable to that of soils from temperate regions (Wilcke et al., 1998). CaCO3 contents of the analyzed soils vary from 7 to 67%, with an average value of 32% and lowest percentages for the Favorita Park samples. 4.2. Soil mineralogy The topsoil mineralogy is dominated by carbonates (calcite and dolomite), alumino-silicates (clay minerals and feldspars) and quartz. Most samples are characterized by high contents of carbonate phases ()50%) while the soils from the Favorita Park (FP) are dominated by silicate phases (mainly clay minerals and quartz). 4.3. Major element composition The bulk-soil major element composition of most samples is defined by CaOqMgO ranging from 15 to 65%, SiO2 varying between 25 and 60%, and Al2O3qFe2O3 ranging from 7 to 35%. Samples of the Favorita Park exhibit higher concentrations of SiO2, with a mean value of 60%. The investigated soils show chemical imprints of both calcarenite bedrocks and local Terra Rossa soils. This may be accounted for urban soils of Palermo received in the past some contribution from Terra Rossa soils and supports the utilization of heavy metal concentrations of these soils as background levels to estimate urban soil contamination. 4.4. ‘Pseudo-total’ metal contents Concentrations of Hg, Pb, Zn, Cu, Cd, Cr, Co, Ni, V, Sb and Mn in urban soils and bedrocks of Palermo are listed in Table 1 together with median values, standard deviations and variability ranges. Median values are given for the sites where more samples were analyzed. Because of its anomalously high heavy metal contents, sample PF11 was considered as an outlier of the total dataset. For comparison mean values for natural soils of Sicily (Bellanca et al., 1996; Palumbo et al., 2000) and ranges of variability of the same metals for unpolluted soils estimated at world scale by Fergusson

(1990), Kabata-Pendias and Pendias (1992) are reported in the same table. The results demonstrate a general enrichment of heavy metals in the topsoils with respect to bedrocks. Mercury, Pb, Zn, Cu and Sb concentrations are higher for topsoils compared to their levels in unpolluted soils (at a world-scale) and in natural soils of Sicily. High concentrations coupled with high standard deviation values suggest anthropogenic sources for these elements. Generally, the recorded V levels are similar to those reported for unpolluted soils, although some samples seem to be anomalously enriched in this element. Cobalt, Cr, Ni and Mn concentrations exhibit generally low levels, close to those reported for unpolluted soils. Moreover, these metals display quite homogeneous distributions across the city and therefore lower standard deviations, thus suggesting a major natural (i.e. indigenous lithologic) source. Cd and Mn values in the analyzed samples are comparable to the higher terms reported for natural soils worldwide (Table 1). High Cd and Mn concentrations (greater than 1 and 500 mg kgy1, respectively) were measured in some soils from the Favorita Park and other green areas of the city. However, it is noteworthy that these values agree with those of natural soils in Sicily and that of the FP rock sample collected in the Favorita Park. Compared to average concentrations in urban soils in the world (Table 2), the median values of Pb in the analyzed soils are much lower than those reported for samples from some large andyor industrialized cities (i.e. Boston, central Madrid, central London), but they are similar to those measured in smaller cities (i.e. Hamburg, Glasgow) and residential areas of London (London Borough). Copper, Cr, Co, Zn, V and Ni concentrations are generally similar to those reported for other cities, while Mn contents are generally higher. Records for Hg and Sb levels in urban soils are scarce in the literature. Inter-element relationships provide interesting information on heavy metal sources and pathways. Pb is best correlated with Hg (r 2s0.7) and well with Zn, Cu and Sb (r 2s0.6), which could indi-

Table 1 Concentrations (mg kgy1) of heavy metals in topsoils and bedrocks from the urban area of Palermo listed together with median values, upper and lower quartiles, and standard deviations Pb

Zn

Cu

Cd

Cr

Co

Ni

V

Sb

Mn

Soils (ppm) VT1 VT2 VT3 VT4 VT5 VT6 VT7 VT8 VT9 VT10 VT11 VT12 VB1 VB2 VB3 PI1 PI2 PI 3 PI4 OB1 OB2 OB3 OB4 OB5 OB6 OB7 OB8 VM1 VM2 VM3 VM4 VM5 VM6 VM7 VM8 PD V.Mare Ucc XIII Vitt

1.00 1.57 0.76 0.37 1.10 1.48 0.61 0.72 0.62 0.11 1.16 0.08 2.70 3.74 2.40 1.23 1.57 2.45 1.71 1.40 1.70 6.96 0.64 3.90 0.93 0.40 2.14 0.96 0.82 0.34 0.51 0.63 0.94 0.83 0.72 0.74 2.72 1.00 0.62

249 256 319 261 267 398 186 248 239 178 243 150 356 423 392 283 277 366 328 228 295 279 140 443 140 137 206 205 192 184 269 224 239 225 253 169 228

200 156 318 128 150 264 104 156 184 134 136 68 149 137 133 161 139 144 135 165 123 107 85 245 84 67 138 129 143 130 85 83 122 144 187 89 190

109 87 86 48 74 71 61 57 56 45 78 23 108 106 93 92 81 109 102 99 82 64 43 110 12 10 29 104 121 48 34 30 76 76 164 16 105

0.53 0.62 1.86 0.66 0.68 0.81 0.62 1.31 0.68 0.81 0.65 0.52 0.50 0.43 0.48 0.87 0.78 0.68 0.60 0.44 0.48 0.44 0.40 0.95 0.35 0.27 0.44 0.88 0.81 0.89 0.53 0.56 1.26 0.94 1.85 0.50 0.90

34 27 28 19 29 39 18 33 29 15 29 14 24 16 24 40 46 30 30 36 20 13 26 29 14 13 18 43 44 31 15 12 42 40 15 100 52

4.4 5.1 4.2 2.3 4.0 5.7 2.5 4.5 3.4 1.5 4.1 1.9 2.6 3.2 3.4 4.3 5.1 4.1 4.5 3.7 3.1 2.4 3.6 2.3 1.8 5.2 3.4 6.9 6.1 4.6 3.9 2.6 8.3 6.7 7.3 2.9 7.5

16.0 14.9 15.5 18.3 17.7 25.3 12.0 19.5 18.1 9.1 17.6 8.8 11.5 12.0 15.3 20.1 19.2 16.1 12.7 13.6 11.2 7.3 12.6 11.1 7.5 7.7 11.8 20.3 21.6 17.9 10.5 7.0 23.0 24.6 24.0 7.8 19.9

57 50 48 35 62 62 38 60 52 21 58 31 32 27 39 66 65 63 50 39 36 30 45 26 28 27 42 80 79 65 38 28 89 81 73 30 54

3.4 4.7 4.5 4.5 3.1 3.3 2.1 2.9 3.6 2.0 2.1 1.2 3.8 3.3 3.1 3.1 3 2.9 4.1 4.0 2.2 1.9 1.3 3.5 1.3 1.2 2.0 2.2 2.1 1.8 1.8 1.5 2.3 2.6 2.8 1.2 7.6

403 416 429 329 519 564 312 494 358 142 544 256 360 379 412 514 638 557 519 263 447 283 492 443 296 268 383 648 628 434 322 251 801 716 705 299 550

181

191

108

0.80

70

11.7

32.4

98

4.0

850

233

Hg

D.S. Manta et al. / The Science of the Total Environment 300 (2002) 229–243

Sample

234

Table 1 (Continued) Sample

Pb

Zn

0.22

103

167

Magn Camp Nisc Tuk U.Ita 1 U.Ita 2 Ziino Mor D.Bosco Praga Pall Garib1 Garib2 Garib3 Gasp PF1 PF2 PF3 PF4 PF5 PF6 PF7 PF8 PF9 PF10 PF11 PF12 PF13 PF14

0.05 0.80 0.17 0.59 0.62 0.86 0.34 1.00 0.27 0.09 0.29 4.46 3.79 1.49 0.21 0.11 0.12 0.09 0.12 0.08 0.28 0.21 0.04 0.13 0.31 56.00 0.20 0.29 0.07

149 138 121 199 281 198

Min Max Media SD

Brun

Bedrocks PF rock 5M.Gallo 9C.Pisani 11V.Tasca 14P.Sturzo 10F.Oreto

Cu

Cd

Cr

Co

65

1.30

89

14.8

335 136 76 137 384 204

57 51 37 71 344 113

1.20 1.40 0.60 0.60 1.00 0.89

52 71 24 48 31 30

227 95 169 119 682 406 355 85 89 159 140 57 68 126 81 60 103 157 2516 85 147 165

227 100 105 138 433 176 192 139 99 100 115 142 84 146 98 52 89 87 203 147 170 126

59 42 53 47 304 104 108 42 48 37 45 50 33 68 37 25 43 39 207 55 84 51

0.80 0.70 0.60 0.80 0.80 0.60 0.56 0.70 0.76 0.54 1.28 1.62 0.53 1.45 0.60 0.37 0.97 0.62 3.80 1.26 1.28 0.59

0.04 56.00 1.85 6.73

57 2516 253 302

52 433 151 71

10 344 77 56

0.01 0.02 0.01 0.02 0.03 0.01

35 47 41 34 30 37

71 11 9 15 15 13

19 17 13 12 17 13

Ni

V

Sb

Mn

36.3

107

2.4

1241

11.0 12.6 5.2 12.0 7.0 7.2

26.8 28.6 15.6 23.6 17.6 16.6

73 84 43 63 43 41

4.5 3.3 4.0 6.3 7.8 4.6

833 1098 330 1046 508 820

34 40 72 46 51 33 34 79 58 38 49 45 61 58 34 50 25 58 58 56 50 51

5.5 7.2 14.4 9.0 6.8 4.2 4.1 12.1 10.2 7.4 10.1 13.5 8.2 11.9 8.1 10.0 11.5 5.0 13.6 9.6 12.5 8.2

18.3 35.9 22.4 20.0 11.8 10.3 12.7 32.7 28.6 22.3 22.6 38.6 23.2 32.3 17.7 16.6 23.4 13.7 38.3 26.3 29.1 23.5

35 54 124 64 34 30 25 98 88 51 74 99 71 92 52 60 72 37 97 103 96 74

4.5 3.4 2.5 3.6 15.7 5.6 6.6 2.8 3.1 3.4 2.2 1.2 1.4 4.3 1.7 1.1 1.7 2.9 27.5 2.3 4.4 4.0

478 543 1163 680 524 360 335 779 807 526 784 1056 558 772 643 156 871 252 1259 730 949 578

0.27 3.80 0.84 0.51

12 100 39 19

1.5 14.8 6.5 3.6

7.0 38.6 19.1 8.0

21 124 58 25

1.1 27.5 3.7 3.6

142 1259 566 263

1.62 0.25 0.23 0.22 0.15 0.21

103 16 11 36 40 39

7.7 1.4 1.4 1.5 2.1 2.2

19.7 4.5 2.8 4.9 4.9 4.2

53 35 32 33 28 28

0.6 0.5 0.5 0.6 0.5 0.6

578 55 66 200 106 311

D.S. Manta et al. / The Science of the Total Environment 300 (2002) 229–243

Hg

Table 1 (Continued) Sample

Pb

Zn

Cu

Cd

Cr

Co

Ni

V

Sb

Mn

Hg

Pb

Zn

Cu

Cd

Cr

Co

Ni

V

Sb

Mn

0.80 2.95 1.74 2.26 0.72 0.74 3.25 0.16 56.00 0.74 2.72 0.62 0.22 0.05 0.80 0.17 0.59 1.00 0.27 0.09 0.29 0.21

250 390 314 234 224 239 481 109 2516 169 228 181 103 149 138 121 199 227 95 169 119 85

167 140 145 127 128 294 267 114 203 89 190 191 167 335 136 76 137 227 100 105 138 139

66 102 96 56 82 229 172 47 207 16 105 108 65 57 51 37 71 59 42 53 47 42

0.81 0.47 0.73 0.47 0.96 0.95 0.65 0.90 3.80 0.50 0.90 0.80 1.30 1.20 1.40 0.60 0.60 0.80 0.70 0.60 0.80 0.70

26 21 37 21 30 31 39 51 58 100 52 70 89 52 71 24 48 34 40 72 46 79

3.6 3.1 4.5 3.2 5.8 7.1 5.0 9.9 13.6 2.9 7.5 11.7 14.8 11.0 12.6 5.2 12.0 5.5 7.2 14.4 9.0 12.1

16.1 12.9 17.0 10.4 18.6 17.1 11.6 25.0 38.3 7.8 19.9 32.4 36.3 26.8 28.6 15.6 23.6 18.3 35.9 22.4 20.0 32.7

48 33 61 34 67 42 30 76 97 30 54 98 107 73 84 43 63 35 54 124 64 98

3.1 3.4 3.3 2.2 2.1 6.2 9.3 2.6 27.5 1.2 7.6 4.0 2.4 4.5 3.3 4.0 6.3 4.5 3.4 2.5 3.6 2.8

397 384 557 359 563 664 406 676 1259 299 550 850 1241 833 1098 330 1046 478 543 1163 680 779

Median Minimum Maximum Lower quartile Upper quartile Std. Dev.

0.68 0.04 6.96 0.22 1.40 1.26

202 57 682 140 269 111

138 52 433 104 167 71

63 10 344 43 99 54

0.68 0.27 1.86 0.54 0.90 0.35

34 12 100 25 50 19

5.2 1.5 14.8 3.7 8.3 3.5

17.8 7.0 38.6 12.6 23.4 7.7

54 21 124 37 73 24

3.0 1.1 15.7 2.1 4.0 2.1

519 142 1241 360 716 250

Bedrocks Bedrocks (6) Median Minimum Maximum Lower quartile

0.02 0.02 0.01 0.03 0.01

37 36 30 47 34

22 14 9 71 11

15 15 12 19 13

0.45 0.23 0.15 1.62 0.21

41 38 11 103 16

2.7 1.8 1.4 7.7 1.4

6.8 4.7 2.8 19.7 4.2

35 33 28 53 28

0.6 0.6 0.5 0.6 0.5

219 153 55 578 66

Sample (mg kgy1) Topsoils VT (12) VB (3) PI (4) OB (8) VM (8) U Ita (2) Garib (3) FP (14) FP11 PD V Mare XIII Vitt Brun Magn Camp Nisc Tuk Mor D Bosco Praga Pall Gasp

Locality Villa Trabia Villa Bonanno P.zza Indipendenza Orto Botanico Villa Malfitano Unita` d’Italia Villa Garibaldi Favorita Park Favorita Park Parco d’Orleans Villa a Mare XIII Vittime Brunelleschi Magnolie Camporeale Villa Niscemi Tukory Morello Don Bosco Praga-Belgio Pallavicino De Gasperi

D.S. Manta et al. / The Science of the Total Environment 300 (2002) 229–243

Hg

235

236

Table 1 (Continued) Sample Upper quartile Std. Dev.

Hg

Pb

0.02 0.01

41 6

0.066 0.05y0.1

44 22y44

Zn 15 24

Cu

Cd

Cr

Co

17 3

0.25 0.58

40 33

2.2 2.5

34 13y24

1.3 0.37y0.78

83 12y83

4.5y12

Ni 4.9 6.3

V

Sb

Mn

35 9

0.6 0.1

311 200

18y67

0.3y0.9

Unpolluted soils * **

Mean values of different natural soils of Sicily (Bellanca et al., 1996; Palumbo et al., 2000). Mean ranges calculated to the world scale (Fergusson, 1990; Kabata-Pendias and Pendias, 1992).

**

12y34

1728 270y525 D.S. Manta et al. / The Science of the Total Environment 300 (2002) 229–243

*

122 45y100

D.S. Manta et al. / The Science of the Total Environment 300 (2002) 229–243

237

Table 2 Average heavy metal concentrations (mg kgy1) in urban soils from different cities in the world City

Hg

Pb

Rome 330.8 Pittsburg 0.51 398 Boston 800 Warsaw 57 Hamburg 218.2 Salamanca 53.1 ˜ Coruna 309 Central Madrid 621 Madrid 161 Bangkok 47.8 Aberdeen 94.4 Birmingham 570 Glasgow 216 Central London 647 Greater London 250 Outer London 322 London boroughs 294 London 294 Hong Kong 93.4 Hong Kong 100 Hong Kong 89.9 Manila 213.6

Zn

Cu

Cd

Cr

Co

Ni

V

Sb Mn

0.31 1.2 166 516

31 0.73 146.6 2.0 0.53 60 0.3

32 95.4

210 118 58.4

71.7 41.7 0.29 27

74.7 26.4 23.9

207

97

0.53

183 183 168 93.9 58.8 440

49 73 24.8 27.5 16.1 98.7

1.0 1.0 2.18 1.89 0.94 0.57 114

206

39

5.1

11

cate common contamination sources for these metals. Cr shows good correlation with Co, Ni, V and Mn (r 2s0.6–0.7). These four metals exhibit excellent correlations with SiO2, Al2O3 and Fe2O3 (r 2s0.8–0.9), suggesting their strong affinities for alumino–silicate phases and Fe-oxides of the soils. Chromium is significantly correlated with these major oxides but not as well as with Co, Ni and V. Cadmium is positively correlated with Co, Ni, V and major oxides (r 2s0.5), but a better correlation with Mn (r 2s0.6) reflects its affinity for soil Mn-phases. Heavy metal concentrations do not correlate with pH, CEC and organic matter contents. Owing to the narrow range of pH (7.2–8.3) measured in the samples, this parameter has limited importance on the heavy metal distribution, substantially limiting their mobility because of the neutral-subalkaline environment. 4.5. Enrichment factors (EFs) Heavy metal enrichment factors (EFs) for the soil samples were calculated by assuming as geo-

12 62.5 28

6.42 14.1 30 24.8 6.4 14.9

20.9

337 750 3 437 340 286

1999

Reference Angelone et al. (1995) Carey et al. (1980) Spittler and Feder (1979) Czarnowska (1980) Lux (1986) ´ Sanchez-Camazano et al. (1994) Cal-Prieto et al. (2001) Pellicer (1985) De Miguel et al. (1998) Wilcke et al. (1998) Paterson et al. (1996) Department of the Environment (1982) Gibson and Farmer (1986) Rundle and Duggan (1980) Rundle and Duggan (1980) Davies et al. (1979) Culbard et al. (1988) Thornton (1991) Li et al. (2001) Wong et al. (1996) Chen et al. (1997) Pfeiffer et al. (1988)

chemical background concentrations of natural soils in Sicily reported in Table 1. Thus, EFs element concentration in urban soilyelement concentration in average natural soil. The EF values for Co, V and Sb were calculated as concentration ratios between the soil and average bedrock (Table 1). Most significant results are represented in Fig. 2. Consistent with indications of inter-element relationships, EFs are generally less than 1 for Ni, Mn, Cr and Cd, which suggests a natural source for these elements in the studied soils. On the other hand, the urban soils contain much higher Pb, Zn, Cu and Hg concentrations when compared to natural soils and have high EFs confirming an important role of the anthropogenic pollution. In particular, Pb is enriched on average by 5–10 times and Hg exhibits EF values as high as 35. Cobalt and V are slightly to moderately enriched in topsoils with respect to bedrocks (2.3 and 1.6, respectively), suggesting a ‘natural’ concentration of these metals during weathering andyor pedogenesis processes. For Sb, high EFs (Fig. 2)

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Fig. 2. Enrichment factors for some metals in topsoil samples with respect to natural soils in Sicily (Hg, Pb and Zn) and bedrocks (Sb). Data used in calculating EFs are those of Table 1.

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Fig. 3. Hierarchical clustering results (dendrogram) of the heavy metal concentrations in topsoil samples of the Palermo city.

together with a wide range of values hint at an anthropic nature of most of the metal. 4.6. Hierarchical clustering analysis In order to discriminate distinct groups of heavy metals as tracers of natural or anthropic source, an explorative hierarchical cluster analysis was performed on the available dataset. The obtained results (Fig. 3) enabled the identification of two main groups of elements, clustered at level of similarity 4, discriminating V, Ni, Mn, Co, Cr and Cd (Group I) from Cu, Zn, Sb, Pb and Hg (Group II). This result is consistent with elemental relationships indicating that the metals of Group I strongly correlate with the alumino-silicate phases, thus supporting a natural origin for these elements, and is also suggested by their relatively low concentration values and relatively low standard deviations. In accordance with EF data, Group II includes metals dominated by an anthropic input. 4.7. Spatial distribution of pollutant metals and factors controlling contamination Distribution patterns of the main pollutant metals in the whole urban area of Palermo are visualized by a set of concentration maps obtained by processing data in Table 1 with the Surfer program (Fig. 4).

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Lead, Zn, Sb and Hg show similar spatial distributions highlighting two significantly polluted zones corresponding to: (i) the historical center of the city (lower-right side of the maps), open to heavy vehicle traffic; and (ii) green areas close to the crossing of major urban traffic axes (central part of the maps). The spatial distribution of these elements suggests the dominant role of vehicle traffic as pollutant source. However, it is important to take into account additional point sources of contamination such as gas industries for all metals, chemical laboratories for Hg, and fireworks for Sb. A moderate pollution is recorded in the Favorita Park area (top center in Fig. 4) where the vehicle traffic is generally declining and vegetation barriers play an important protective role for the soils. However, it is worth noting that very high concentration values of heavy metals were recorded for a sample from this park (FP11, see Table 1) and that these anomalous data were discarded in the course of statistical treatments. The severe contamination of this zone is related to the activity of a firing range, located some years ago in this area. Finally, we must consider that the chemical composition of topsoils in Palermo might have been affected by the use of garden fertilizers. In fact, the analyzed soils contain P2O5 levels, ranging between 0.22 and 1.34, consistently higher than those of natural soils in Sicily (P2O5 from 0.04 to 0.35; Bellanca et al., 1996; Palumbo et al., 2000). Owing to the significant correlations between P2O5 and Hg, Pb, Zn and Cu (r 2s0.5– 0.6), the enhanced levels of P2O5 are attributed to fertilizer applications. 4.8. PCA and statistical evaluation of anthropic pollution To reduce the high dimensionality of the sampleyvariable space, a principal component analysis (PCA) was applied to the available dataset of heavy metals. Normal distribution of each metal was previously checked, since the PCA procedures are based on linear combinations of the variables and their correlations. The obtained Factors were rotated using a varimax normalized algorithm, which allows an easier interpretation of the prin-

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Fig. 4. Maps of Hg, Zn, Pb, and Sb distribution (values in mg kgy1) in the urban area of Palermo (scale 1:100 000).

cipal component loadings and the maximization of the variance explained by the extracted factors. Two principal components were extracted from the available dataset, explaining a total variance of approximately 71% (Table 3). In Table 3 and Fig. 5, the factor loadings for the two extracted factors are reported allowing an easy interpretation of the master variables. Factor I is dominated by Co, Ni, V, Cr and Mn. Based

on earlier discussions suggesting that the distribution of these elements is mainly controlled by natural materials, the first factor can be inferred as a ‘lithogenic factor’. Factor II loaded by Hg, Pb, Zn, Cu and Sb can be identified as a tracer of anthropic pollution. Cadmium shows high values in F I, but it is also represented in F II. An explanation for this may be that the distribution of Cd is affected by both lithogenic and anthropogen-

D.S. Manta et al. / The Science of the Total Environment 300 (2002) 229–243 Table 3 Values of two extracted factor loadings for the studied heavy metals; values of dominant elements in each factor reported in bold

Hg Pb Zn Cu Cd Cr Co Ni V Sb Mn Expl. Var.

Factor I

Factor II

y0.43 y0.40 0.21 0.09 0.68 0.71 0.92 0.91 0.91 0.14 0.91

0.62 0.83 0.87 0.88 0.27 y0.10 y0.14 y0.12 y0.18 0.94 0.01

45%

26%

ic control. Addition of Terra Rossa soils to urban soils in Palermo could be responsible for enhanced Cd levels due to the presence in the Terra Rossa of Cd-enriched Fe–Mn nodules (Palumbo et al., 2001), which accounts for the strong correlation of Cd with Mn. On the other hand, a few sites with strong positive Cd anomalies are expression of an additional influence of pollutant sources. Conceptually, Factor II condenses the information of the heavy metals as tracers of anthropic pollution. The calculated scores of Factor II were plotted on the map of the urban area of Palermo (Fig. 5) to gather an ‘average image’ of the anthropic pollution in the city. This map indicates the occurrence of a diffuse pollution related to anthropic activity with a good correspondence of peaks of metal contaminations and sites of major deposition of atmospheric particles generated primarily from traffic. Such an urban distribution map can be used for direct comparison with thematic maps and database (e.g. topographic, geological, etc.) using Geographical Information System (GIS) software.

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background levels have been correctly interpreted and established. Topsoil samples from green areas in the city of Palermo show Pb, Zn, Cu, Sb and Hg concentrations higher than those of natural soils in Sicily and comparable to those recorded in other important European cities. Based on the whole dataset these metals are inferred to derive from anthropogenic sources, whereas Co, Ni, V, Cr and Mn distributions are mainly controlled by lithogenic inputs. Except for a few anomalously high Cd values that are an expression of the influence of pollutant sources, relatively high levels of cadmium in the investigated soils were interpreted to reflect a natural enrichment by weathering and pedogenesis processes. Results of combined multivariate statistical analyses and the distribution patterns of the pollutant metals suggested that vehicle traffic represents the most important pollutant source for the studied urban environment. Plotting PCA results on the map of the city can be used to advantage in investigating urban soil pollution and its potential deleterious effect, especially when used for direct comparison with thematic maps and database by GIS software.

5. Conclusions The data obtained in this study demonstrate that the heavy metal concentrations of urban soils can be used as powerful geochemical tracers for monitoring the impact of human activity, provided that

Fig. 5. Map of the estimated ‘average pollution’ in the city of Palermo (scale 1:100 000).

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Acknowledgments We would like to thank the management of the ‘Assessorato al Centro Storico’ of Palermo city and that of the ‘Ente Gestore Riserva Naturale Monte Pallegrino’ for authorizing soil sampling in different sites. We are grateful to the management ` of the Serveis Cientificotecnics of Barcelona University (UB) and in particular to Dr A. Padro (Technical Staff) for all facilities concerning the ICP-MS analyses. Thanks are also due to thank Prof. C. Dazzi (Palermo University) for facilities relative to chemico-physical parameters of topsoil samples. We thank H.W. Mielke and an anonymous referee for reviewing an earlier version of the paper. This research was supported by the following grants to AB: CNR-99.00636.CT05; MIUREx quota 60%. References Albasel N, Cottenie A. Heavy metal contamination near major highways, industrial and urban areas in Belgian Grassland. Water Air Soil Pollut 1985;24:103 –109. Allen S, Grimshaw HM, Parkinson JA, Quarmby C. Chemical analysis of ecological materials. Oxford: Blackwell, 1974. (521 pp). Angelone M, Corrado T, Dowgiallo G. Lead and cadmium distribution in urban soil and plants in the city of Rome: a preliminary study. Proceedings of the Third International Conference on the Biogeochemistry of Trace Elements 1995. p. 23 –24. Angelone M, Cavaliere A, Dowgiallo G. Mercury levels in natural soils and two plant species (spartium junceum l. and avena sativa l.) in Latium (central Italy). Proceedings of the Fifth International Conference on the Biogeochemistry of Trace Elements 1999. p. 540 –541. Bacon JR, Berrow ML, Shand CA. Isotopic composition as an indicator of origin of lead accumulations in surface soils. Int J Environ Anal Chem 1992;46:71 –76. Barahona E, Huertas F, Pozzuoli A, Linares J. Mineralogia e genesi dei sedimenti della provincia di Granata (Spagna). Miner Petrogr Acta 1982;26:61 –90. Bellanca A, Hauser S, Neri R, Palumbo B. Mineralogy and geochemistry of Terra Rossa soils, western Sicily: insights into heavy metal fractionation and mobility. Sci Total Environ 1996;193:57 –67. Bini C, Ferretti O, Chiara E, Gragnani R. Distribuzione e circolazione degli elementi in traccia nei suoli. Suoli della Regione Puglia. Rend Soc Ital Miner Petrol 1984;39:281 – 296. Burguera JL, Burguera M, Rondon C. Lead in roadside soils of Merida City, Venezuela. Sci Total Environ 1988;77:45 – 49.

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