Spatial Distribution Characteristics and Source Analysis of Heavy Metals in Soil of a Lead Plant in Sanmenxia

被引:2
|
作者
Lu X.-H. [1 ]
Yu F.-Z. [1 ]
Fan Y.-M. [1 ]
Yang Y. [1 ]
机构
[1] School of Earth Sciences and Engineering, Hohai University, Nanjing
来源
Huanjing Kexue/Environmental Science | 2023年 / 44卷 / 03期
关键词
geostatistics; positive matrix factorization (PMF) model; soil heavy metals; source analysis; spatial distribution;
D O I
10.13227/j.hjkx.202205052
中图分类号
学科分类号
摘要
At present, a large-scale relocation of industrial enterprises is taking place in major cities in China, and a large number of contaminated relocation sites are being generated, among which the heavy metal pollution is particularly serious. In order to analyze the pollution status, spatial distribution, and sources of heavy metals in the soil of a lead factory in Sanmenxia, the spatial variation and distribution characteristics of heavy metals in the soil were analyzed using geostatistics, and the main sources of heavy metals in the soil were analyzed using a PMF model. The results showed that the average values of As, Cd, Cu, Pb, Hg, and Ni in the soil far exceeded the background values of the soil environment in Henan province; the contents of As, Cd, Pb, and Hg exceeded the screening values of soil pollution risk; and the contents of As, Pb, and Hg exceeded the control values of soil pollution risk. The high-value area was located on the northern part of the slag yard; the Cr, Ni, and Cd high-value area was located in the north and south of the slag yard; the high-value As area was located in the slag yard between the southern area and the living quarters; the Cu and Pb high-value area was relatively scattered, mainly concentrated in the central part of the raw material storage area and furnace area; and Ni and Cd and Cu and Pb had the same spatial distribution characteristics. Based on the PMF model, it can be seen that there were three main sources of the seven heavy metals, and Cd was mainly from waste residue accumulation, with a contributing rate of 87. 60%. Cu, Pb, and Hg were mainly soil parent material, with contribution rates of 92. 50%, 75. 20%, and 95. 40%, respectively. Cr, Ni, and As were mainly raw material dust exhaust gas sources, with contribution rates of 80. 80%, 83. 30%, and 62. 00%, respectively. © 2023 Science Press. All rights reserved.
引用
收藏
页码:1646 / 1656
页数:10
相关论文
共 27 条
  • [1] Zhang C S, Zhang S, He J B., Spatial distribution characteristics of heavy metals in the sediments of Changjiang river system-Geostatistics method [J], Acta Geographica Sinica, 52, 2, pp. 184-192, (1997)
  • [2] Pang W P, Qin F X, Lyu Y C, Et al., Chemical speciations of heavy metals and their risk assessment in agricultural soils in a coal mining area from Xingren County, Guizhou Province, China, Chinese Journal of Applied Ecology, 27, 5, pp. 1468-1478, (2016)
  • [3] Burgess T M, Webster R., Optimal interpolation and isarithmic mapping of soil properties. II. Block kriging, European Journal of Soil Science, 31, 2, pp. 333-341, (1980)
  • [4] Chen J F, Fang H D, Wu J J, Et al., Distribution and source apportionment of heavy metals in farmland soils using PMF and lead isotopic composition, Journal of Agro-Environment Science, 38, 5, pp. 1026-1035, (2019)
  • [5] Chen Y L, Weng L P, Ma J, Et al., Review on the last ten years of research on source identification of heavy metal pollution in soils, Journal of Agro-Environment Science, 38, 10, pp. 2219-2238, (2019)
  • [6] Ding Y L, Liao M, Fang Z P, Et al., Impact of newly build lead-acid battery agglomeration area on the surrounding soil environment: a study based on the spatial characteristics of heavy metals, Environmental Science, 40, 9, pp. 4244-4252, (2019)
  • [7] Li Y, Shi Z, Xu J M, Et al., Utilization and perspective of geostatistics in soil sciences, Journal of Soil and Water Conservation, 17, 1, pp. 178-182, (2003)
  • [8] Huang Y, Guo Q R, Ren H, Et al., Application and perspective of geostatistics in the study on soil heavy metals, Ecology and Environment, 13, 4, pp. 681-684, (2004)
  • [9] Xie L T, Pan J J, Bai H R, Et al., GIS-based spatial distribution and risk assessment of heavy metals in farmland soils: a case study of a town of Jiangning, Nanjing, Acta Pedologica Sinica, 57, 2, pp. 316-325, (2020)
  • [10] Cerar S, Mezga K, Zibret G, Et al., Comparison of prediction methods for oxygen-18 isotope composition in shallow groundwater, Science of the Total Environment, 631-632, pp. 358-368, (2018)