Source apportionment of soil PTE in a northern industrial county using PMF model: Partitioning strategies and uncertainty analysis

• Published in: Environmental research Vol. 252; no. Pt 2; p. 118855
• Main Authors: Shi, Biling, Yang, Xiao, Liang, Tao, Liu, Siyan, Yan, Xiulan, Li, Junchun, Liu, Zhaoshu
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.07.2024
• Subjects: Agricultural soil PTE; agricultural soils; algorithms; China; Partitioning processing; population density; Positive matrix factorization; risk; Source apportionment; Spatial heterogeneity; spatial variation; species; toxicity; uncertainty; uncertainty analysis; China; Spatial heterogeneity; Source apportionment; Agricultural soil PTE; Partitioning processing; Positive matrix factorization
• ISSN: 0013-9351; 1096-0953; 1096-0953
• DOI: 10.1016/j.envres.2024.118855

Positive matrix factorization (PMF) has commonly been applied for source apportionment of potentially toxic elements (PTE) in agricultural soil, however, spatial heterogeneity of PTE significantly undermines the accuracy and reliability of PMF results. In this study, a representative industrial-agricultural hub in North China (Xuanhua district, Zhangjiakou City) was selected as the research subject, multiple partition processing (PP) strategies and uncertainty analyses were integrated to advance the PMF modeling and associated algorithm mechanisms were comparatively discussed. Specifically, we adopted three methods to split the research area into several subzones according to industrial density (PP-1), population density (PP-2), and the ecological risk index (PP-3) respectively, to rectify the spatial bias phenomenon of PTE concentrations and to achieve a more interpretable result. Our results indicated that the obvious enrichment of Cd, Pb, and Zn was found in the agricultural soil, with Hg and Cd accounted for 83.49% of the overall potential ecological risk. Combining proper PP with PMF can significantly improve the modelling accuracy. Uncertainty analysis showed that interval ratios of tracer species (Cd, Pb, Hg, and Zn) calculated by PP-3 were consistently lower than that of PP-1 and PP-2, indicating that PP-3 coupled PMF can afford the optimal modeling results. It suggested that natural sources, fertilizers and pesticides, atmosphere deposition, mining, and smelting were recognized as the major contributor for the soil PTE contamination. The contribution of anthropogenic activities, specifically fertilizers and pesticides, and atmosphere deposition, increased by 1.64% and 5.91% compared to PMF results. These findings demonstrate that integration of proper partitioning processing into PMF can effectively improve the accuracy of the model even at the case of soil PTE contamination with high heterogeneity, offering support to subsequently implement directional control strategies. [Display omitted] •The study underscores the utility of partitioning strategies and uncertainty analysis in source apportionment.•Partitioning processing based on RI has the lowest uncertainties.•PP PMF corrects the contribution of fertilizers, pesticides, and atmosphere deposition sources.