Spatial Heterogeneity Analysis of Soil Heavy Metals in Chongqing City Based on Different Interpolation Methods

Abstract Heavy metal pollution in urban soil is an important indicator of environmental pollution, which is of great significance to the sustainable development of cities. Choosing the best interpolation method can accurately reflect the distribution characteristics and pollution characteristics of heavy metals in soil, which is conducive to effective management and implementation of protection strategies. In this study, the grid sampling with a depth of 40cm was carried out in the whole study area based on the principle of uniform sampling, and the characteristics of As, Cu and Mn elements in the soil of the main urban area of Chongqing were investigated. The interpolation accuracy and difference of results of four interpolation methods, namely ordinary Kriging (OK), inverse distance weighting (IDW), local polynomial (LPI) and radial basis function (RBF), were analyzed and compared. The results showed that the average values of As (5.802 mg kg -1 ), Cu (23.992 mg kg -1 ) and Mn (573.316 mg kg -1 ) in the soil of the study area were lower than the background values of heavy metals in Chongqing. Coefficient of variation showed that As (55.71%), Cu (35.73%) and Mn (32.21%) all belonged to moderate variation. The parameters of semi-variance function theory model show that Cu element belongs to moderate spatial correlation, and As and Mn element have strong spatial correlation. The spatial distribution of the three elements was further predicted by using OK method, IDW method, LPI method and RBF method, which showed that LPI and OK method had strong smoothing effect and could not reflect the information of local point source pollution, while the interpolation results of IDW method and RBF method greatly retained the maximum and minimum information of element content, which reflected the necessity of using different methods when studying the spatial distribution of soil properties.