Table S1 the Assessment Criteria for Enrichment Factor (EF) Used in This Study

Table S1 The assessment criteria for Enrichment factor (EF) used in this study

EF / Degree of enrichment
< 1 / No enrichment
< 3 / Minor enrichment
3–5 / Moderate enrichment
5–10 / Moderately severe enrichment
10–25 / Severe enrichment
25–50 / Very severe enrichment
50 / Extremely severe enrichment

Table S2 The Shapiro-Wilk test results on statistical distribution of heavy metals concentrations

Heavy metals / DF / Initial data / Logarithmically transformed
Statistic / Prob<W / Statistic / Prob<W
Cr / 276 / 0.874 / 0.000 / 0.983 / 0.002
Cu / 276 / 0.693 / 0.000 / 0.948 / 0.000
Fe / 276 / 0.956 / 0.000 / 0.991 / 0.088
Mn / 276 / 0.962 / 0.000 / 0.988 / 0.018
Pb / 276 / 0.805 / 0.000 / 0.971 / 0.000
V / 276 / 0.822 / 0.000 / 0.917 / 0.000
Zn / 276 / 0.819 / 0.000 / 0.991 / 0.088

Table S3 Heavy metal concentrations in street dust from different cities in China and other countries (mg·kg−1)

Cr / Cu / Fe / Mn / Pb / V / Zn / Reference
Beijing, China / 69.33–84.7 / 63.73–107.7 / —a / 564.12 / 50.79–201.82 / — / 219.2–238.6 / (Xiang et al. 2010; Tang et al. 2012; Du et al. 2013; Xin et al. 2015)
Shanghai, China / 145 / 216 / — / — / 259 / — / 895 / (Zhang et al. 2013)
Nanjing, China / 67.15 / 101.7 / 2.641% / 573.9 / 71.95 / 40.65 / 297.8 / (Li et al. 2014)
Xi’an, China / 149.2–159.7b / 70.8–74.2 / 558.3–565.4 / 176.2–180.9 / 67.6 / 461.5–462.6 / (Chen et al. 2014; Lu et al. 2014)
Baoji, China / 126.7 / 123.2 / 804.2 / 433.2 / 88.9 / 715.3 / (Lu et al. 2010)
Tianjin, China / 121.41 / 100.62 / — / — / 61.48 / — / — / (Hu et al. 2016)
Huludao (Zinc smelting district), China / — / 264.4 / — / — / 533.2 / — / 5271 / (Zheng et al. 2010)
Shantou (E-waste recycling area), China / 69.71 / — / — / 693.74 / 589.74 / — / — / (Yekeen et al. 2016)
Shenyang (Tiexi old industrial zone), China / — / 158.0 / — / — / 140.0 / — / 361.55 / (Ren et al. 2015)
Suzhou (Polymetallic ore mining areas), China / 25.7 / 104.8 / — / — / 262.2 / — / 376.9 / (Ma et al. 2015)
Murcia, Spain / — / 130 / — / — / 123 / — / 377 / (Acosta et al. 2014)
Al-Qunfudah, Kingdom of Saudi Arabia / — / 40 / 22092 / 175 / 26 / — / 47 / (Harb et al. 2015)
Shiraz, Iran / 67.16 / 136.34 / 20254.6 / 438.5 / 115.71 / — / 403.46 / (Keshavarzi et al. 2015)
Hassi Messaoud (Oilfield area), Algeria / — / 83.63 / — / 579.41 / 288.00 / — / 293.33 / (Benhaddya et al. 2016)
Thessaloniki, Greece / 104.90 / 662.30 / 21300 / 336.40 / 209.00 / — / 452.80 / (Bourliva et al. 2016)
Gyumri, Armenia / 68.337 / 43.688 / — / — / 77.274 / — / 158.309 / (Sahakyan et al. 2016)
Maha Sarakham, Thailand / — / 13.37 / — / — / 13.12 / — / 58.02 / (Ma and Singhirunnusorn 2012)

a No data.

b Range of mean values.

Table S4 Pearson correlation coefficients (r) between the selected heavy metals

Cr / Cu / Fe / Mn / Pb / V / Zn
Cr / 1
Cu / 0.016 / 1
Fe / 0.230** / 0.230** / 1
Mn / 0.269** / 0.155** / 0.548** / 1
Pb / 0.303** / 0.275** / 0.415** / 0.275** / 1
V / 0.103 / 0.488** / 0.412** / 0.305** / 0.458** / 1
Zn / 0.292** / 0.232** / 0.536** / 0.226** / 0.546** / 0.381** / 1

** Correlation is significant at the 0.01 level (two-tailed).

Table S5 Rotated component matrix of heavy metals in street dust of Suzhou

Parameter / Component
1 / 2 / 3 / 4
Cr / 0.192 / −0.015 / 0.141 / 0.956
Cu / 0.070 / 0.916 / 0.037 / 0.011
Fe / 0.529 / 0.116 / 0.716 / −0.025
Mn / 0.029 / 0.135 / 0.915 / 0.194
Pb / 0.742 / 0.29 / 0.097 / 0.238
V / 0.370 / 0.711 / 0.253 / −0.022
Zn / 0.881 / 0.098 / 0.15 / 0.092
Initial eigenvalue / 2.995 / 1.146 / 0.880 / 0.719
Percentage of variance (%) / 42.78 / 16.37 / 12.57 / 10.28
Cumulative percentage (%) / 42.78 / 59.15 / 71.73 / 82.00

Fig. S1 Classification of heavy metals in groups obtained using Ward’s clustering method (z-score-standardized)

Fig. S2 3D plot of PCA loadings for the studied HMs

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