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Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
Published on: October 16, 2018
Spatial distribution, risk assessment, and source apportionment of soil heavy metals in a karst county based on grid
Zhaoxin Hu1, Zeyan Wu1, Weiqun Luo1
1Institute of Karst Geology, Chinese Academy of Geological Sciences, Guilin 541004, China; Pingguo Guangxi, Karst Ecosystem, National Observation and Research Station/Pingguo Baise, Karst Ecosystem, Guangxi Observation and Research Station, Pingguo 531406, China; Key Laboratory of Karst Dynamics, Ministry of Natural Resources & Guangxi/International Research Centre on Karst under the Auspices of United Nations Educational, Scientific and Cultural Organization, Guilin 541004, China.
Abstract:
Soil in karst areas commonly exhibits characteristics of heavy metal enrichment. Accurate identification of soil heavy metal distribution, risks, and sources are crucial for preventing soil heavy metal pollution in karst areas. In this study, 2467 topsoil samples (0-20 cm) and 620 subsoil samples (150-200 cm) were collected using a grid-based sampling method in Tianyang County. Statistics, geo-statistics, correlation analysis, principal component analysis, and the absolute principal component-multiple linear regression model were utilized to analyze the content, spatial distribution and sources of heavy metals. The geo-accumulation index and the potential ecological risk index were employed to assess the ecological risks of heavy metals in the topsoil, with the subsoil content as baseline. The results showed that the study area's soil exhibited high heavy metal content, significantly exceeding Chinese background values. The content of heavy metals in the karst area's soil was notably higher than that in the non-karst area. The fitted semi-variogram models and the spatial distribution map revealed that the heavy metals' content was generally dominated by the geological background. As, Cr, Cu, Hg, Ni, Pb, and Zn displayed low levels of pollution in the topsoil and posed low ecological risk, with over 90 % of samples classified as unpolluted and low risk. Cd exhibited high levels of pollution and ecological risks, with 52.28 % of samples classified as polluted and 60.81 % classified as moderate to high risk. For Hg, despite only 6.94 % of samples showing polluted, the ecological risks were not negligible, with 40.65 % of samples in moderate to high risk. Natural source and anthropogenic source contribute to the heavy metals on average by 81.49 % and 18.51 %, respectively. This study provides a reference for the risk assessment of soil heavy metals, and its findings offer valuable scientific insights for the prevention of heavy metal pollution in the study area.
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