Source apportionment and ecological risk assessment of heavy metals in sediments of Dongping lake based on PCA-PMF model.

Accurately characterizing the spatial distribution of heavy metals in lake surface sediments, analyzing their sources, and identifying potential ecological risks are important scientific supports for lake ecosystem management. This study selected Dongping Lake, a typical inland shallow lake in the eastern region, as the research object. It systematically analyzed the distribution characteristics, source identification, and ecological risks of eight heavy metals (As, Zn, Cu, Ni, Cd, Hg, Pb, and Cr) in the sediments of Dongping Lake by employing a combination of statistical analysis, cluster analysis, principal component analysis (PCA), and positive matrix factorization (PMF) models, along with the enrichment factor method, geoaccumulation index method, and potential ecological risk assessment method. The results show that the concentrations of the eight heavy metals (As, Zn, Cu, Ni, Cd, Hg, Pb, and Cr) in the study area exhibit an overall improving trend, with significant spatial heterogeneity, and relatively higher concentrations in the central and southern regions. Through multivariate statistical analysis, three major sources of metal accumulation were identified: industrial and agricultural activities (As, Cu, Hg, Cd), traffic emissions (Zn, Ni, Pb), and natural geological background (Cr). Enrichment characteristics showed that Cd, As, and Hg were moderately to heavily enriched, and the potential ecological risk index (RI) indicated that Hg and Cd are the main risk factors, with contribution rates of 41.83% and 37.77%, respectively. The study revealed the dominant role of human activities in the accumulation of heavy metals in the sediments of Dongping Lake, providing a scientific basis for precise pollution control and ecological restoration in the watershed.