Many reviewers have applied bibliometric analysis to conduct research on heavy metals (HMs) in Chinese soil and found that risk management decisions were biased to a certain extent due to case distribution difference and uncertainty. The previous methodologies were optimized integrating further uncertainty control and case identification in this study. A solid database was built, which included 779 cases published from 2009 to 2020. Based on the data features, the weight method was used to objectively shield extreme cases and normalize the concentrations. We conducted fuzzy eco- and health risk models via a triangular fuzzy number, and identified the risks from Pb, Cd, As, and Hg as the priority control metals. However, the national HMs risk had complex spatial heterogeneity and significant uncertainty. Thus, an "integrated risk grade criterion (IRGC)" was coupled with the risk threshold concentrations for the eco- and health risks to classify the each case. The cases above the moderate IRGC grade for Cd or Hg accounted for approximately 50%, and were mainly in the west and north of China, respectively. The high-grade areas were mostly in the south of China, including the Xijiang-Pearl River Basin and the Yangtze River Basin. It was demonstrated that warning health risks were likely a local question and that the ecological risks from Hg and Cd were considerable across China. By reviewing and summarizing the text information, high grades of soil Cd, Pb, and As were frequently reported in the villages associated with the mining industry, and certain soil Cd near suburban industrial complexes also caused warning health risks. Finally, this study proposed priority control objects for hierarchical risk management, including the identified heavy metals, areas, and pilot cities from multi-spatial scales.
Keywords: Heavy metals; Hierarchical risk management; Risk assessment; Soil; Uncertainty control.
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