Detection of dominant factors and interactions of spatial heterogeneity of soil heavy metals in northern Chengdu Plain, western China

• Published in: Arabian journal of geosciences Vol. 15; no. 7
• Main Authors: Wang, Guangjie, Peng, Wenfu, Zhang, Dongmei, Luo, Yanmei
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01-04-2022; Springer Nature B.V
• Subjects: Anthropogenic factors; Chromium; Copper; Earth and Environmental Science; Earth science; Earth Sciences; Geographic information systems; Geographical information systems; Geomorphology; Heavy metals; Heterogeneity; Human influences; Information systems; Kriging interpolation; Land pollution; Land use; Lead; Metal concentrations; Metals; Moisture content; Moisture effects; Nickel; Organic matter; Original Paper; Patchiness; Phosphates; Pollution; Remote sensing; Soil; Soil moisture; Soil pollution; Soil types; Soils; Spatial heterogeneity; Statistical analysis; Statistical methods; Water content; Zinc; China; Spatial heterogeneity; Soil heavy metals; Ground accumulation index; Geographic detector; Chengdu Plain
• ISSN: 1866-7511; 1866-7538
• DOI: 10.1007/s12517-022-09603-4

Several studies have examined the role of changes in the natural and anthropogenic factors of soil heavy metals; however, the causes of spatial heterogeneity of soil heavy metals remains to be understood. To study heavy metals in soil, we collected a total of 134 soil samples from diverse land-use types; whereby we measured the concentrations of six metals (Cr, Ni, Cu, Zn, As, and Pb). Herein, we used Kriging interpolation methods in a geographic information system (GIS) and geo-accumulation index to map the distribution and evaluate the pollution of heavy metals in soil. We applied geographic detector models, a new spatial statistical method, to determine how the dominant factors and interactions led to spatial heterogeneity of heavy metal variations in soil, in the northern Chengdu Plain in western China. The results indicated that the overall pollution of heavy metals in soil was relatively light, with Cr, Ni, Cu, Zn, As, and Pb in soil reaching 5.37%, 22.15%, 22.82%, 17.45%, 4.70%, and 27.52%, respectively. We observed that heavy metals in soil demonstrated significant spatial heterogeneity, with high Cr and Ni contents in the central region and low in the south and north; Cu was high and widely distributed in the western parts, exceeding the background value; Zn was high in the north and west, and low in the east, covering a wide area with significantly high contents; As was high in the west and central parts, and low in the north, south, and east; Pb was high in the north and central parts, and low in the south. The results revealed that the dominant factors affecting the spatial heterogeneity of Cr in soil were moisture content, available phosphate, and distance to factory; the explanatory power was 31.52%, 25.77%, and 10.71%, respectively. Moisture content, organic matter, and available phosphate most significantly influenced Cu and Pb in soil, with explanatory powers of 13.11%, 8.20%, 3.21%, 10.55%, 10.49%, and 11.87%, respectively. The available phosphate, moisture content, and soil type can explain the spatial heterogeneity of Zn in soil, with explanatory powers of 31.52%, 2 5.77%, and 10.71%, respectively; whereas the dominant factors affecting the spatial heterogeneity of As in soil were soil type, slope, and geomorphic type, with explanatory powers of 16.11%, 6.68%, and 6.40%, respectively. Moisture content, soil type, and GDP had the greatest influence on Ni in soil, with explanatory powers of 1.4%, 0.77%, and 0.62%, respectively. This study suggests that the interactions among impact factors mutually and non-linearly enhance the impact of a single factor on the spatial heterogeneity of soil heavy metals. Our research highlights that the geodetector method is an effective approach to disentangle the complicated driving factors and reveal the optimum characteristics and ranges of each factor, further contributing to our understanding of the spatial heterogeneity of soil heavy metals and the driving mechanisms. Our results are useful for providing theoretical contributions and practical references to accelerate the formulation of land pollution management policies.