Sources apportionments of heavy metal(loid)s in soils based on positive matrix factorization (PMF) and lead isotope...

Accurately identifying the sources of heavy metal(loid) contamination in soil is essential for effective pollution control and risk management. This study examined 19 heavy metal(loid)s in soils from a typical rural area in Xiangtan County, Hunan Province-one of the most polluted regions in China-by combining geostatistical analysis, positive matrix factorization (PMF), and lead (Pb) isotopic fingerprinting. A total of 120 environmental samples, including 70 surface soils, were analyzed. PMF resolved four factors corresponding to parent material, irrigation-related inputs, atmospheric deposition, and agricultural activities. Farmland soils were mainly enriched in arsenic (As) and cadmium (Cd), while woodland soils were dominated by As and antimony (Sb). Irrigation was the primary source of Cd, whereas atmospheric deposition contributed substantially to Sb and Pb. Pb isotopic analysis provided post-model validation constraints. By comparing isotopic ratios predicted from PMF factor profiles with measured values, discrepancies were within ≤2.2 %. This quantitative isotopic validation integrated the PMF decomposition with geochemical evidence, reducing uncertainties in factor interpretation and enhancing the reliability of Pb and associated source apportionment. The integrated PMF-Pb isotope framework offers a transparent and reproducible approach for disentangling overlapping sources of soil contamination and provides actionable evidence to guide pollution control and remediation strategies in complex rural environments.