Multivariate geostatistical analyses of heavy metals in soils: spatial multi-scale variations in Wulian, Eastern China.

Jianshu Lv, Yang Liu, Zulu Zhang, Bin Dai
Author Information
  1. Jianshu Lv: The Key Laboratory of Coast and Island Development of Ministry of Education, School of Geographic and Oceanographic Sciences, Nanjing University, 163 Xianlin Avenue, Nanjing 210023, China; Geological Survey of Canada (Atlantic), Bedford Institute of Oceanography, Dartmouth, Canada B2Y 4A2. Electronic address: lvjianshu@126.com.
  2. Yang Liu: State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China.
  3. Zulu Zhang: College of Population, Resource and Environment, Shandong Normal University, Jinan 250014, China.
  4. Bin Dai: The Key Laboratory of Coast and Island Development of Ministry of Education, School of Geographic and Oceanographic Sciences, Nanjing University, 163 Xianlin Avenue, Nanjing 210023, China.

Abstract

The objective of this study was to examine spatial multi-scale variability of six heavy metals (Cd, Cr, Cu, Ni, Pb and Zn) in relation to environmental factors in Wulian, Eastern China. Factorial kriging analysis (FKA) was applied to a data set consisting of 432 topsoils. We found that most of the heavy metal contents in soils did not exceed the guideline values of Environmental Quality Standard for Soils (EQSS) in China. Through linear model of coregionalization (LMC) fitting, spatial variation in six heavy metals could be grouped into one nugget effect, and two sphere structures with ranges of 6km (local scale) and 14km (regional scale). Spatial correlations among six heavy metals depended on local or regional scales. The high correlations between Cr, Ni and among Cd, Cu, Pb, Zn were found regardless of the spatial scale, while correlations of Cr and Ni with other four metals decreased with increasing spatial scale. Spatial variation of Cr and Ni was related to parent material at both local and regional scales, and was derived from natural sources. Mining activity was observed to affect the spatial variation of Cd, Cu, Pb and Zn at local scale, while parent material dominated spatial variation of those metals at regional scale. However, agricultural practices and human activity in urban area did not alter spatial variation of heavy metals in soils. It could be concluded that human influence on heavy metals variation was noted on local scale, and parent material had greater influence on spatial variation of heavy metals at both local and regional scales.

Keywords

MeSH Term

Agriculture
China
Environmental Monitoring
Linear Models
Metals, Heavy
Mining
Multivariate Analysis
Soil
Soil Pollutants
Spatial Analysis

Chemicals

Metals, Heavy
Soil
Soil Pollutants

Word Cloud

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