Skip to main content

Advertisement

SpringerLink
Log in

Spatial distribution and ecological risk assessment of trace metals in urban soils in Wuhan, central China

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Surface soil samples from 467 sample sites were collected in urban area of Wuhan City in 2013, and total concentrations of five trace metals (Pb, Zn, Cu, Cr, and Cd) were measured. Multivariate and geostatistical analyses showed that concentrations of Pb, Zn, and Cu are higher along Yangtze River in the northern area of Wuhan, gradually decrease from city center to suburbs, and are mainly controlled by anthropogenic activities, while those of Cr and Cd are relatively spatially homogenous and mainly controlled by soil parent materials. Pb, Zn, Cu, and Cd have generally higher concentrations in roadsides, industrial areas, and residential areas than in school areas, greenbelts, and agricultural areas. Areas with higher road and population densities and longer urban construction history usually have higher trace metal concentrations. According to estimated results of the potential ecological risk index and Nemero synthesis pollution index, almost the whole urban area of Wuhan is facing considerable potential ecological risk caused by soil trace metals. These results reveal obvious trends of trace metal pollution, and an important impact of anthropogenic activities on the accumulation of trace metals in soil in Wuhan. Vehicular emission, industrial activities, and household wastes may be the three main sources for trace metal accumulation. Increasing vegetation cover may reduce this threat. It should be pointed out that Cd, which is strongly accumulated in soil, could be the largest soil pollution factor in Wuhan. Effective measures should be taken as soon as possible to deal with Cd enrichment, and other trace metals in soil should also be reduced, so as to protect human health in this important large city.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Anikwe, M. A. N., & Nwobodo, K. C. A. (2002). Long term effect of municipal waste disposal on soil properties and productivity of sites used for urban agriculture in Abakaliki, Nigeria. Bioresource Technology, 83(3), 241–250. doi:10.1016/s0960-8524(01)00154-7.

    Article  CAS  Google Scholar 

  • Atafar, Z., Mesdaghinia, A., Nouri, J., Homaee, M., Yunesian, M., Ahmadimoghaddam, M., et al. (2010). Effect of fertilizer application on soil heavy metal concentration. Environmental Monitoring and Assessment, 160(1–4), 83–89. doi:10.1007/s10661-008-0659-x.

    Article  CAS  Google Scholar 

  • Benhaddya, M., & Hadjel, M. (2014). Spatial distribution and contamination assessment of heavy metals in surface soils of Hassi Messaoud, Algeria. Environmental Earth Sciences, 71(3), 1473–1486. doi:10.1007/s12665-013-2552-3.

    Article  CAS  Google Scholar 

  • Birke, M., & Rauch, U. (2000). Urban Geochemistry: Investigations in the Berlin Metropolitan Area. Environmental Geochemistry and Health, 22(3), 233–248. doi:10.1023/a:1026554308673.

    Article  CAS  Google Scholar 

  • Bright, E. A., Rose, A. N., & Urban, M. L. (2013). LandScan 2013 Global Population Database. East View Information Services. O. R. N. Laboratory.

  • Cai, Q. Y., Mo, C. H., Li, H. Q., Lü, H. X., Zeng, Q. Y., Li, Y. W., et al. (2013). Heavy metal contamination of urban soils and dusts in Guangzhou, South China. Environmental Monitoring and Assessment, 185(2), 1095–1106. doi:10.1007/s10661-012-2617-x.

    Article  CAS  Google Scholar 

  • Chen, X. D., Lu, X. W., Li, L. Y., & Yang, G. (2013). Spatial distribution and contamination assessment of heavy metals in urban topsoil from inside the Xi'an second ringroad, NW China. Environmental Earth Sciences, 68(7), 1979–1988. doi:10.1007/s12665-012-1885-7.

    Article  CAS  Google Scholar 

  • China National Environmental Monitoring Centre. (1990). The background values of soil elements in China. Beijing: China Environmental Science Press.

    Google Scholar 

  • Gong, M., Wu, L., Bi, X. Y., Ren, L. M., Wang, L., Ma, Z. D., et al. (2010). Assessing heavy-metal contamination and sources by GIS-based approach and multivariate analysis of urban–rural topsoils in Wuhan, central China. Environmental Geochemistry and Health, 32(1), 59–72.

    Article  CAS  Google Scholar 

  • Guo, G. H., Wu, F. C., Xie, F. Z., & Zhang, R. Q. (2012). Spatial distribution and pollution assessment of heavy metals in urban soils from southwest China. Journal of Environmental Sciences, 24(3), 410–418. doi:10.1016/S1001-0742(11)60762-6.

    Article  CAS  Google Scholar 

  • Gupta, S., Satpati, S., Nayek, S., & Garai, D. (2010). Effect of wastewater irrigation on vegetables in relation to bioaccumulation of heavy metals and biochemical changes. Environmental Monitoring and Assessment, 165(1–4), 169–177. doi:10.1007/s10661-009-0936-3.

    Article  CAS  Google Scholar 

  • Hakanson, L. (1980). An ecological risk index for aquatic pollution control.a sedimentological approach. Water Research, 14(8), 975. doi:10.1016/0043-1354(80)90143-8.

    Article  Google Scholar 

  • Helmreich, B., Hilliges, R., Schriewer, A., & Horn, H. (2010). Runoff pollutants of a highly trafficked urban road - correlation analysis and seasonal influences. Chemosphere, 80(9), 991–997. doi:10.1016/j.chemosphere.2010.05.037.

    Article  CAS  Google Scholar 

  • Jiang, J. H., Xu, Y. H., & Peng, H. (2014). Distribution and speciation of heavy metals in sediments from Donghu Lake, Wuhan, China. Fresenius Environmental Bulletin, 23(2A), 502–507.

    CAS  Google Scholar 

  • Johansson, C., Norman, M., & Burman, L. (2009). Road traffic emission factors for heavy metals. Atmospheric Environment, 43(31), 4681–4688. doi:10.1016/j.atmosenv.2008.10.024.

    Article  CAS  Google Scholar 

  • Lin, Y. P., Teng, T. P., & Chang, T. K. (2002). Multivariate analysis of soil heavy metal pollution and landscape pattern in Changhua county in Taiwan. Landscape and Urban Planning, 62(1), 19–35. doi:10.1016/S0169-2046(02)00094-4.

    Article  Google Scholar 

  • Liu, H. L., Li, L. Q., Yin, C. Q., & Shan, B. Q. (2008). Fraction distribution and risk assessment of heavy metals in sediments of Moshui Lake. Journal of Environmental Sciences, 20(04), 390–397.

    Article  CAS  Google Scholar 

  • Liu, C. L., Yu, R. L., & Duan, D. Z. (2014). Spatial-temporal structure of capacity fractal about urban–rural road network in Wuhan Metropolitan Area (in Chinese). Geographical Research, 33(4), 777–788.

    Google Scholar 

  • Ljung, K., Otabbong, E., & Selinus, O. (2006). Natural and anthropogenic metal inputs to soils in urban Uppsala, Sweden. Environmental Geochemistry and Health, 28(4), 353–364. doi:10.1007/s10653-005-9031-z.

    Article  CAS  Google Scholar 

  • Ma, Z. D., Zhang, D. C., Bi, X. Y., Liu, G. Q., Ren, L. M., & Quan, H. L. (2005). Origin of cadmium high-value zones along the Yangtze River and Hanjiang River in Wuhan, Hubei, China (in Chinese). Geological Bulletin of China, 24(8), 740–743.

    CAS  Google Scholar 

  • Mahanta, M., & Bhattacharyya, K. (2011). Total concentrations, fractionation and mobility of heavy metals in soils of urban area of Guwahati, India. Environmental Monitoring and Assessment, 173(1–4), 221–240. doi:10.1007/s10661-010-1383-x.

    Article  CAS  Google Scholar 

  • Meza-Figueroa, D., De la O-Villanueva, M., & De la Parra, M. L. (2007). Heavy metal distribution in dust from elementary schools in Hermosillo, Sonora, México. Atmospheric Environment, 41(2), 276–288. doi:10.1016/j.atmosenv.2006.08.034.

    Article  CAS  Google Scholar 

  • Odewande, A., & Abimbola, A. (2008). Contamination indices and heavy metal concentrations in urban soil of Ibadan metropolis, southwestern Nigeria. Environmental Geochemistry and Health, 30(3), 243–254. doi:10.1007/s10653-007-9112-2.

    Article  CAS  Google Scholar 

  • Peng, C., Ouyang, Z., Wang, M., Chen, W., Li, X., & Crittenden, J. C. (2013). Assessing the combined risks of PAHs and metals in urban soils by urbanization indicators. Environmental Pollution, 178, 426–432. doi:10.1016/j.envpol.2013.03.058.

    Article  CAS  Google Scholar 

  • Qu, M. K., Li, W. D., Zhang, C. R., Wang, S. Q., Yang, Y., & He, L. Y. (2013). Source apportionment of heavy metals in soils using multivariate statistics and geostatistics. Pedosphere, 23(4), 437–444. doi:10.1016/S1002-0160(13)60036-3.

    Article  Google Scholar 

  • Qu, M. K., Li, W. D., & Zhang, C. R. (2014). Spatial distribution and uncertainty assessment of potential ecological risks of heavy metals in soil using sequential gaussian simulation. Human and Ecological Risk Assessment, 20(3), 764–778. doi:10.1080/10807039.2013.770352.

    Article  CAS  Google Scholar 

  • Rizo, O. D., Castillo, F. E., López, J. O. A., & Merlo, M. H. (2011). Assessment of heavy metal pollution in urban soils of Havana City, Cuba. Bulletin of Environmental Contamination and Toxicology, 87(6), 414–419. doi:10.1007/s00128-011-0378-9.

    Article  CAS  Google Scholar 

  • Rose, N., Cowie, C., Gillett, R., & Marks, G. B. (2009). Weighted road density: A simple way of assigning traffic-related air pollution exposure. Atmospheric Environment, 43(32), 5009–5014. doi:10.1016/j.atmosenv.2009.06.049.

    Article  CAS  Google Scholar 

  • Salonen, V.-P., & Korkka-Niemi, K. (2007). Influence of parent sediments on the concentration of heavy metals in urban and suburban soils in Turku, Finland. Applied Geochemistry, 22(5), 906–918. doi:10.1016/j.apgeochem.2007.02.003.

    Article  CAS  Google Scholar 

  • Shi, G., Chen, Z., Xu, S., Zhang, J., Wang, L., Bi, C., et al. (2008). Potentially toxic metal contamination of urban soils and roadside dust in Shanghai, China. Environmental Pollution, 156(2), 251–260. doi:10.1016/j.envpol.2008.02.027.

    Article  CAS  Google Scholar 

  • State Environmental Protection Administration of China (1995). Environmental quality standard for soils.

  • Wei, B. G., Jiang, F. Q., Li, X. M., & Mu, S. Y. (2009). Spatial distribution and contamination assessment of heavy metals in urban road dusts from Urumqi, NW China. Microchemical Journal, 93(2), 147–152. doi:10.1016/j.microc.2009.06.001.

    Article  CAS  Google Scholar 

  • Wu, C. M., Tsai, H. T., Yang, K. H., & Wen, J. C. (2012). How reliable is X-ray fluorescence (XRF) measurement for different metals in soil contamination? Environmental Forensics, 13(2), 110–121. doi:10.1080/15275922.2012.676603.

    Article  CAS  Google Scholar 

  • Wuhan bureau of statistics. (2012). 2012 Wuhan statistical yearbook. Beijing: China Statistics Press.

    Google Scholar 

  • Wuhan bureau of statistics (2013). The Wuhan Statistical Bulletin of National Economic and Social Development. http://www.whtj.gov.cn/details.aspx?id=2180. Accessed 21 May 2014.

  • Xia, X. H., Chen, X., Liu, R. M., & Liu, H. (2011). Heavy metals in urban soils with various types of land use in Beijing, China. Journal of Hazardous Materials, 186(2–3), 2043–2050. doi:10.1016/j.jhazmat.2010.12.104.

    Article  CAS  Google Scholar 

  • Yang, Z. F., Wang, Y., Shen, Z. Y., Niu, J. F., & Tang, Z. W. (2009). Distribution and speciation of heavy metals in sediments from the mainstream, tributaries, and lakes of the Yangtze River catchment of Wuhan, China. Journal of Hazardous Materials, 166(2–3), 1186–1194. doi:10.1016/j.jhazmat.2008.12.034.

    Article  CAS  Google Scholar 

  • Yang, X. F., Xiong, B. X., & Yang, M. S. (2010). Relationships among heavy metals and organic matter in sediment cores from Lake Nanhu, an Urban Lake in Wuhan, China. Journal of Freshwater Ecology, 25(2), 243–249. doi:10.1080/02705060.2010.9665074.

    Article  CAS  Google Scholar 

  • Yang, T., Zeng, Q. L., Liu, Z. F., & Liu, Q. S. (2011). Magnetic properties of the road dusts from two parks in Wuhan city, China: implications for mapping urban environment. Environmental Monitoring and Assessment, 177(1–4), 637–648. doi:10.1007/s10661-010-1662-6.

    Article  CAS  Google Scholar 

  • Yang, J., Meng, X. Z., Duan, Y. P., Liu, L. Z., Chen, L., & Cheng, H. F. (2014). Spatial distributions and sources of heavy metals in sediment from public park in Shanghai, the Yangtze River Delta. Applied Geochemistry, 44, 54–60. doi:10.1016/j.apgeochem.2013.08.007.

    Article  CAS  Google Scholar 

  • Zhao, J. H., Li, H. Y., Gong, X., Du, W. M., & Hu, R. F. (2011). Study of soil organic carbon content in some typical functional areas, Wuhan City (in Chinese). Journal of Anhui Agricultural Sciences, 39(6), 3409–3410,3415.

    Google Scholar 

  • Zheng, N., Wang, Q. C., Zhang, X. W., Zheng, D. M., Zhang, Z. S., & Zhang, S. Q. (2007). Population health risk due to dietary intake of heavy metals in the industrial area of Huludao city, China. Science of the Total Environment, 387(1–3), 96–104. doi:10.1016/j.scitotenv.2007.07.044.

    Article  CAS  Google Scholar 

  • Zibret, G. (2012). Impact of dust filter installation in ironworks and construction on brownfield area on the toxic metal concentration in street and house dust (Celje, Slovenia). Ambio, 41(3), 292–301. doi:10.1007/s13280-011-0188-7.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The research was supported by National Natural Science Foundation of China (Grant No. 41101193), and the Fundamental Research Funds for National Universities (Grant No. 2662014PY062). Opinions in the paper do not constitute an endorsement or approval by the funding agencies and only reflect the personal views of the authors.

Author information

Authors and Affiliations

  1. Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtze River), Ministry of Agriculture, College of Resources and Environment, Huazhong Agricultural University, Wuhan, 430070, China

    Chutian Zhang, Yong Yang, Ruoxi Zhang, Yang Mei, Xiangsen Liao & Yingying Liu

  2. Department of Geography and Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, CT, 06269, USA

    Weidong Li & Chuanrong Zhang

Authors
  1. Chutian Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weidong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chuanrong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ruoxi Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yang Mei
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Xiangsen Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yingying Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yong Yang.

Appendices

Appendix 1:Data quality verification

A dataset of a previous study (Qu et al. 2014), kindly provided by Qu et al., was used for data quality verification of ICP-AES and XRF measurements in this paper. Considering the high spatial variability of trace metals, data points located within the Wuhan Donghu High-tech Development Park, which was the region of the previous study, were extracted. Concentrations of Pb, Zn, Cu, Cr, and Cd by ICP-AES and XRF in this paper were compared to the previous study based on the independent sample t test method. Results listed in Table 5 show that concentrations of Pb, Zn, and Cr by ICP-AES and Pb and Zn by XRF in this study well match those in the previous study (p > 0.05), while concentrations of Cu and Cd by ICP-AES and Cr by XRF are significantly different from those in the previous study (p < 0.05). But, the range of Cd contents is comparable with results by Qu et al. (2013) and Yang et al. (2009). The above results indicate that concentrations of Pb, Zn, Cr, and Cd in this study could be trusted, while the significant difference between Cu contents in this study and the previous study may be caused by the high coefficient of variation of Cu (see the “Trace metal concentrations in urban soils” section).

Table 5 Summary statistics and results of two independent sample t tests of soil trace metal concentrations (mg/kg) by different methods
Full size table

Appendix 2: XRF data transformation

To integrate trace metal data obtained by ICP-AES and XRF, regression models were established based on the pairwise concentrations of Pb, Zn, Cu, and Cr in the training samples (no Cd data by XRF).

Shown as Fig. 8, concentrations of Pb, Zn, and Cu obtained by XRF had significantly positive relationship with the corresponding ICP-AES measurements; the coefficient of correlation were 0.915, 0.946, and 0.808 for Pb, Zn, and Cu, respectively. XRF measurements fitted fairly well with the ICP-AES measurements for Pb, Zn, and Cu, and the R 2 values were 0.842, 0.895, and 0.675, respectively. On the contrary, Cr by XRF showed no significant relationship with that by ICP-AES, with a quite low R 2 value of 0.027. Wu et al. (2012) also found that XRF measurements of Pb, Zn, Ni, and Cu are highly reliable and agrees well with the ICP-AES experiments, while Cr and Cd by XRF show poor accuracy. Before transformation, BDLs of XRF were examined. A total of 107 BDLs for Pb, 2 BDLs for Zn, and 151 BDLs for Cu were excluded from the dataset. Since XRF-measured Cr was not accurate and no XRF measurement of Cd was higher than the detection limit, XRF measurements of Cr and Cd were abandoned and only ICP measurements of these two elements were used in further analysis. Although 50 % of the detection limit may be used as the substitution in cases where concentrations were BDLs (Zibret 2012), taking this substitution into account would bring about big errors when establishing regression models and performing the transformations. Therefore, in the data transformation stage, ICP measurements of Pb, Zn, Cu, Cr, and Cd were reserved at the training sample points, and XRF measurements of Pb, Zn, and Cu that were higher than detection limit were transformed using the regression models at other data points. The distributions of available data points for Pb, Zn, Cu, Cr, and Cd can be found in Fig. 9.

Fig. 8
figure 8

Quantitative relationships between concentrations of Pb, Zn, Cu, and Cr (mg/kg) obtained by ICP-AES and XRF. Dash lines represent the 1:1 line and the solid lines represent the regression lines. Regression models, corresponding R 2 values, and coefficient of correlation are also presented in this figure

Full size image
Fig. 9
figure 9

Sampling sites used for analysis of Pb, Zn, Cu, Cr, and Cd. IZ, RS, RA, SA, AA, and GB refer to industrial zone, roadside, residential area, school area, agricultural area, and greenbelt, respectively. The two black ring lines represent the 1st Ring Road and the 3rd Ring Road of Wuhan City, respectively

Full size image

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, C., Yang, Y., Li, W. et al. Spatial distribution and ecological risk assessment of trace metals in urban soils in Wuhan, central China. Environ Monit Assess 187, 556 (2015). https://doi.org/10.1007/s10661-015-4762-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-015-4762-5

Keywords

Search

Navigation