Assessing Soil Quality of Pb‐Zn Smelting Sites by a Two‐Step MDS‐Based Model

Heavy metals (HMs) emitted from the smelting process accumulate in soil, reducing soil quality and subsequently affecting human health. Estimating the extent of land degradation and analyzing the limiting factors of soil quality are essential to facilitate soil management and ecological restoration at smelting sites. This study aims to select the most effective indicators to construct a streamlined minimum data set (MDS) for soils of Pb‐Zn smelting sites and analyze the crucial factors affecting soil quality. Two Pb‐Zn smelting sites, Zhuzhou (ZZ) and Jiyuan (JY), are selected as research areas. The MDS for ZZ and JY is constructed, respectively, to obtain their concatenation of integrated indicators, after which the MDS model is further employed to de‐redundancy to screen for streamlined assessment indicators (SAI) of the contaminated soils. The soil quality index (SQI) based on SAI was calculated, and the accuracy was verified using linear/nonlinear fitting and root‐mean‐square error (RMSE). The selected SAI sets (Pb, sand, Ni, urease activity, and Shannon‐function index) can better represent the individual total data set (TDS) of ZZ and JY with R 2 > 0.7 and RMSE ≈ 0. The average scores of SQI‐SAI of ZZ and JY were 0.578 and 0.669, indicating that soils at the two sites were heavily and moderately degraded, respectively. The low SQI was caused by the high contents of Pb and Ni, which possibly affected soil quality by reducing soil fertility and productivity. This study provides a practical, time‐saving, and economical method for soil quantitative evaluation of smelting sites.