Supplementary material.

To investigate the characteristics of soil heavy metal pollution in the Manghe River watershed, a typical industrial and mining complex area in the Yellow River Basin, concentrations of Hg, Cr, Cu, Ni, Pb, Zn, Cd, and pH were measured in 121 topsoil samples (0–20 cm) collected from the study area. Geostatistical methods were employed to analyze the spatial distribution patterns of heavy metals. The pollution status was assessed using the pollution load index (PLI), while correlation analysis, principal component analysis (PCA), and a positive matrix factorization (PMF) model were applied to identify the sources of heavy metals. The results indicated that: (1) The concentrations of Hg, As, Ni, Cu, Pb, Zn, and Cd exceeded their respective background values, with Hg, Pb and Cd reaching 3.52, 4.85, and 46.4 times of the background levels, respectively.(2) Different elements exhibited distinct spatial distribution and diffusion patterns, revealing their respective sources and influencing factors. (3) The overall PLI was 0.785, reflecting a mild pollution level across the region, while industrial and mining lands exhibited severe pollution (PLI = 4.3). The relative contribution of each heavy metal to the pollution load was ranked as follows: Cd (30.35)> Pb (4.76)> Hg (3.62)> Zn (2.18)> As (1.77)> Cu (1.53). (4) Principal component analysis categorized the sources of heavy metals into anthropogenic activities and natural origins. Further analysis using the PMF model delineated four specific sources: coal combustion (10.87%), natural and agricultural contributions (27.37%), transportation and agricultural actives (26.81%), and industrial emissions (34.95%). Finally, the study identified the following feasible strategies for controlling heavy metal pollution: blocking and remediating industrial pollution sources; treating agricultural non-point source pollution through biological methods; and substituting traditional transportation sources with new energy alternatives. This research could support decision-making processes related to the prevention and control of heavy metal pollution in the study area, as well as regional sustainable development.

为探究黄河流域典型工矿复合区——蟒河流域的土壤重金属污染特征，本研究于研究区采集121件0–20 cm表层土壤样品，测定了Hg、Cr、Cu、Ni、Pb、Zn、Cd浓度及土壤pH值。采用地统计学方法分析重金属的空间分布格局；以污染负荷指数（pollution load index, PLI）评估区域污染现状；通过相关性分析、主成分分析（principal component analysis, PCA）及正矩阵因子分解（positive matrix factorization, PMF）模型解析重金属来源。研究结果表明：(1) Hg、As、Ni、Cu、Pb、Zn及Cd的浓度均超出当地背景值，其中Hg、Pb、Cd分别为背景水平的3.52、4.85及46.4倍；(2) 不同重金属元素呈现各异的空间分布与扩散特征，反映出其各自的来源与影响因素；(3) 区域整体污染负荷指数（PLI）为0.785，整体处于轻度污染水平，而工矿用地的PLI达4.3，属于重度污染。各重金属对污染负荷的相对贡献排序为：Cd（30.35%）> Pb（4.76%）> Hg（3.62%）> Zn（2.18%）> As（1.77%）> Cu（1.53%）；(4) 主成分分析将重金属来源划分为人为活动与自然成因两类；进一步通过PMF模型解析出4类具体来源：燃煤燃烧（10.87%）、自然与农业输入（27.37%）、交通与农业活动（26.81%）及工业排放（34.95%）。最后，本研究提出了针对性的重金属污染防控策略：阻断并修复工业污染源、采用生物手段治理农业面源污染、以新能源替代传统交通燃料。本研究可为研究区重金属污染防控决策及区域可持续发展提供支撑。