The study area, the city of Xuzhou, is located in the north western part of Jiangsu, one of the provinces of China, the geographical position being 33˚43¢N to 34˚58¢N, 116˚22¢E to 118˚40¢E.

Surface soils (0 - 20 cm) were collected within the city of Xuzhou in 2010. Figure 1 shows the sampling sites. In total, 167 soil samples were collected; each consisting

of three subsamples collected from the surrounding area of each site (within 1 m²). All of the samples were freeze-dried and sieved to <2 mm after removing stones and residual roots, then stored in desiccators.

One 0.2 g aliquot was completely dissolved with HNO₃ (5 ml), HF (5 ml) and HClO₄ (3 ml) acid mixture for around 5 h on a hot plate and refluxed with the acid mixture if the sample was only partly dissolved. The residue was solubilized with 2% HNO₃ and diluted to volume. All reagents and acids (Fuchen, Shanghai) were suprapure or pro-analysis quality. Zn, Pb, Fe, Mn, Cu, Cd, Sr, Ba Cr, Ni and Mo concentrations were measured by inductively coupled plasma—mass spectrometry (ICPMS, Bruker 820-MS, Germany).

All glassand plastic-wares were soaked overnight in a 10% nitric acid solution and rinsed thoroughly with deionized water before use. Precision and accuracy for HM concentrations were determined using certified reference materials (CRMs). Two soil samples (ESS-3, GSBZ50013-88 and ESS-4, GSBZ500014-88)) certified by the China Institute for Environmental Reference Materials (IERM) and a solution sample (GSB04-1767- 2004) certified by the China National Centre of Analysis and Testing for Nonferrous Metals and Electronic Materials (NCATN) were used.

Magnetic susceptibility (c, 10^{−8 m3}/kg) was measured using a dual-frequency (470 and 4700 Hz) Bartington Instruments MS2 susceptibility meter.

The analytical results were compiled to form a multielemental database using SPSS 16.0 (Statistical Product and Service Solutions, SPSS Inc., USA). Statistical analyses including factor analysis (FA), cluster analysis (CA) and Pearson correlation analysis were performed using SPSS statistical software. In the FA, Varimax with Kaiser normalization was used as the rotation method in the analysis. Since the elemental concentrations varied greatly among the heavy metals, the raw data were standarded before the execution of clustering in CA. The data were standardized to the Z score (with a mean of 0 and a standard variation of 1) and then classified with the clustering method [20].

Table 1 presents summary statistics for the analyzed metals in all of the studied samples. In general, the concentrations of heavy metals were in wide ranges, which are typical in urban soils [20]. Compared with their levels [21] in natural soils of China also shown in Table 1, these metals investigated exhibited a slight build-up in Xuzhou topsoils. The median concentrations of Ba exceeded the target values recommended by the Dutch Ministry of Housing, Spatial Planning and Environment and those of Cu and Zn were close to the target values [22].

The spatial distribution of heavy metals in soils was analysed using the program SURFER 8 (Golden Software Inc.). The metal concentrations were first interpolated with the Kriging method. The spatial distribution of

Table 1. Summary stastistics of metal concentrations (mg/kg) and specific susceptibility (c, 10⁻⁸ m³/kg) in Xuzhou urban topsoils and the guideline values (n = 167).

^aMean values of different natural soils of China [21]; ^bValues of dutch soil guidelines [22]; ^cBackground value [15].

Table 2. Values of two extracted factor loadings for the studied heavy metals. Values of dominant elements in each factor reported in bold.

Extraction method: principal component analysis; Rotation method: varimax with Kaiser normalization. Rotation converged in 3 iterations.

heavy metals in this study area is shown in Figure 3. Similar spatial distribution patterns of Pb, Fe, Zn, to a lesser extent, Cu, Cd, Sr and Mn, indicated that their highest concentrations were found in central and northern parts of the urban area. On the other hand, similar distribution patterns were found for Cr, Ni, and Mo.

In agreement to FA and CA results, the spatial distribution analysis suggests that the increase of Pb, Fe, Cu, Cd and Zn probably came from a common anthropogenic source. Previous studies have demonstrated that Zn, Pb and Cu in Xuzhou urban topsoils were principally from traffic emissions [1].

The spatial distribution of Cr, Ni and Mo suggests that their distribution pattern could be mainly controlled by parent material.

Table 1 also shows the median value of specific susceptibility in studied area is 157 × 10^{−8 m3}/kg, ranging from 37 × 10^{−8 m3}/kg to 1554 × 10^{−8 m3}/kg. The mean value of specific susceptibility is significantly higher than its local background value. The spatial distributipn map of specific susceptibility are presented in Figure 4 as well. Similar spatial distribution patterns of between Pb, Zn and c were observed in the map.

To examine the relationships between the heavy metals and mass specific susceptibility, a correlation table (Pearson coefficients) has been established (Table 3). The Pb, Zn and Fe show strongly significant correlations with magnetic susceptibility (r > 0.7 and p < 0.01), and Cu, Cd, Mn, Sr and Ba, on the other hand, show a weak correlation with magnetic susceptibility (r < 0.7 and p < 0.01). Of these metals, Cr, Ni and Mo show no significant correlations to the specific susceptibility. As expected, common presence of some heavy metals from the anthropogenic emissions accounts for the significant correlations between the magnetic susceptibility and these metals in the urban topsoil. Our study suggests that simple, rapid, and nondestructive magnetic measurements could provide useful information about some heavy metal pollution in Xuzhou urban topsoils.