Advertisement

Spatial Distribution and Source Identification of Loess Heavy Metal Pollution in Northern Baoji, China

  • Ling Han
  • Zhiheng LiuEmail author
  • Yuming Ning
  • Zhongyang Zhao
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 980)

Abstract

The spatial distribution of heavy metal pollution in loess is an essential prerequisite and scientific basis for detecting and evaluating the quality of loess ecosystem and the sustainable development of regional environment, but lack of research in special soil such as loess. Distribution characteristics and pollution sources of heavy metals in the northern loess area of Baoji is studied by means of geo-statistics and cluster analysis. The results showed that heavy metal pollution still existed in this area, and the pollution in Changqing town was obviously higher than the surrounding area. Consequently, different management strategies can be adopted in the loess area to reduce the contamination load of heavy metal, and attention should be paid to human activities, such as mining, transportation and gas emission, especially.

Keywords

Loess area Heavy metal pollution Geo-statistics analysis Cluster analysis GIS 

Notes

Acknowledgments

Thanks to the staff of Xi’an Center of China Geological Survey for the determination and inspection of heavy metal contents. This work was financially supported by the open fund for key laboratory of land and resources degenerate and unused land remediation, under Grant [SXDJ2017-7]; the 1:50, 000 geological mapping in the loess covered region of the map sheets: Caobizhen (I48E008021), Liangting (I48E008022), Zhaoxian (I48E008023), Qianyang (I48E009021), Fengxiang (I48E009022), & Yaojiagou (I48E009023) in Shaanxi Province, China, under Grant [DD-20160060].

References

  1. 1.
    Li, F., Cai, Y., Zhang, J.: Spatial characteristics, health risk assessment and sustainable management of heavy metals and metalloids in soils from Central China. Sustainability 10, 1–24 (2018)CrossRefGoogle Scholar
  2. 2.
    Giller, K.E., Mcgrath, S.P.: Pollution by toxic metals on agricultural soils. Nature 335(6192), 676 (1988)CrossRefGoogle Scholar
  3. 3.
    Rodrigues, S.M., Cruz, N., Coelho, C., et al.: Risk assessment for Cd, Cu, Pb and Zn in urban soils: chemical availability as the central concept. Environ. Pollut. 183(4), 234–242 (2013)CrossRefGoogle Scholar
  4. 4.
    Wang, Lujun, Fan, Shuanxi: Risk assessment of heavy metals in farmland soil in the outskirts of Baoji City. Chin. Agric. Sci. Bull. 31(3), 179–185 (2015). (in Chinese)Google Scholar
  5. 5.
    Ren, C.H., Xin-Wei, L.U., Wang, L.J., et al.: Human health risk related to pollution level of lead in dust around a lead-zinc plant in Changqing Town, Baoji City. Arid Zone Res. 29(1), 155–160 (2012). (in Chinese)Google Scholar
  6. 6.
    Wang, Lijun, Xinwei, Lu, Jing, Qi, et al.: Heavy metals pollution in soil around the lead-zinc smelting plant in Changqing Town of Baoji City, China. J. Agro-Environ. Sci. 31(2), 325–330 (2012). (in Chinese)Google Scholar
  7. 7.
    Shaheen, A., Iqbal, J.: Spatial distribution and mobility assessment of carcinogenic heavy metals in soil profiles using geostatistics and random forest, boruta algorithm. Sustainability 10(3), 799 (2018)CrossRefGoogle Scholar
  8. 8.
    Cortés, J.L., Bautista, F., Delgado, C., et al.: Spatial distribution of heavy metals in urban dust from Ensenada, Baja California, Mexico. Revista Chapingo Serie Ciencias Forestales Y Del Ambiente 23(1), 235–248 (2017)Google Scholar
  9. 9.
    Chen, J., Zhang, H., Liu, W., et al.: Spatial distribution patterns of ammonia-oxidizing archaea abundance in subtropical forests at early and late successional stages. Scientific Reports 5, 16587 (2015)CrossRefGoogle Scholar
  10. 10.
    Xie, Y., Chen, T., Lei, M., Yang, J., Guo, Q., Song, B., Zhou, X.: Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: accuracy and uncertainty analysis. Chemosphere 82(3), 468–476 (2011)CrossRefGoogle Scholar
  11. 11.
    Saito, H., Goovaerts, P.: Geostatistical interpolation of positively skewed and censored data in a dioxin-contaminated site. Environ. Sci. Technol. 34(19), 4228–4235 (2000)CrossRefGoogle Scholar
  12. 12.
    Fu, C., Zhang, H., Tu, C., et al.: Geostatistical interpolation of available copper in orchard soil as influenced by planting duration. Environ. Sci. Pollut. Res. 25, 52–63 (2018)CrossRefGoogle Scholar
  13. 13.
    Chen, T., Chang, Q., Liu, J., et al.: Identification of soil heavy metal sources and improvement in spatial mapping based on soil spectral information: a case study in northwest China. Sci. Total Environ. 565, 155–164 (2016)CrossRefGoogle Scholar
  14. 14.
    Huang, S., Tu, J., Jin, Y., et al.: Contamination assessment and source identification of heavy metals in river sediments in Nantong, Eastern China. Int J Environ Res 12(3), 1–17 (2018)CrossRefGoogle Scholar
  15. 15.
    Basatnia, N., Hossein, S.A., Rodrigo-Comino, J., et al.: Assessment of temporal and spatial water quality in international Gomishan Lagoon, Iran, using multivariate analysis. Environ. Monit. Assess. 190(5), 1–17 (2018)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Ling Han
    • 1
  • Zhiheng Liu
    • 1
    Email author
  • Yuming Ning
    • 1
  • Zhongyang Zhao
    • 1
  1. 1.Ministry of Land and Resources Key Laboratory of Degradation and Unused Land Remediation, School of Geology Engineering and GeomaticsChang’An UniversityXi’anChina

Personalised recommendations