Two-dimensional empirical mode decomposition of heavy metal spatial variation in agricultural soils, Southeast China.
The distribution of heavy metals in agricultural soils is affected by various anthropogenic activities and environmental factors occurring at different spatial scales. This paper introduced the two-dimensional empirical mode decomposition (2D-EMD) to separate the spatial variability in soil heavy metals into different scales. Geostatistics and multivariate analysis were also utilized to quantify their spatial structure and identify their potential influencing factors. The study was conducted in an arable land in southeastern China where 260 surface soil samples were collected and measured for total contents of cadmium (Cdtotal), mercury (Hgtotal), and sulfur (TS); pH; and soil organic carbon content (SOC). The results showed that both Cdtotaland Hgtotalhad high coefficients of variation. The overall variation in all five soil variables was separated into three intrinsic mode functions (IMFs) and spatial residues. All three IMFs had short-range spatial correlations (1-8 km), while the spatial residues had moderate-large spatial ranges (13-39 km). IMF1 of Cdtotalwas strongly correlated with IMF1 of SOC and TS, which was consistent with the principal component analysis. This indicated that IMF1 of Cdtotalrepresented local variations which were influenced by agricultural activities. IMFs of Hgtotalshowed clustered distributions in the study area, with IMF1 and IMF2 of Hgtotalcorrelated in one principal component, and IMF3 of Hgtotaland IMF3 of soil pH in another component. This indicated that all three IMFs of Hgtotalmight be influenced by different industrial activities or different pathways of the same industrial activities. The residues of Cdtotaland Hgtotal, representing the regional trends, only accounted for 26% of the total variance, whereas IMF1 contributed about half of the total variance. It can be concluded that agricultural activities and industrial activities were the dominant contributors of the overall variations in Cdtotaland Hgtotalin the study area, respectively.
Department of Agricultural Resources and Environment, Nanjing University of Information Science and Technology, Nanjing, 210044, China. wchf1680@163.com.|Faculty of Agriculture and Environment, The University of Sydney, Sydney, NSW, 2006, Australia. wchf1680@163.com.
Chunfa
C
Wu
School of Biological, Earth and Environmental Sciences, UNSW Australia, Sydney, NSW, 2052, Australia.
Jingyi
J
Huang
Faculty of Agriculture and Environment, The University of Sydney, Sydney, NSW, 2006, Australia.
Budiman
B
Minasny
Department of Agricultural Resources and Environment, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
Hao
H
Zhu
D000383:Agriculture; D002104:Cadmium / Q000032:analysis*; D002681:China; D004784:Environmental Monitoring / Q000379:methods; D007221:Industry; D008628:Mercury / Q000032:analysis*; D019216:Metals, Heavy / Q000032:analysis; D015999:Multivariate Analysis; D025341:Principal Component Analysis; D012987:Soil / Q000737:chemistry*; D012989:Soil Pollutants / Q000032:analysis*
D019216:Metals, Heavy; D012987:Soil; D012989:Soil Pollutants; D002104:Cadmium; D008628:Mercury
Heavy metal; Influence factor; Intrinsic mode functions; Scale; Spatial variation