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

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.

Linking ecosystem services and circuit theory to identify priority conservation and restoration areas from an ecological network perspective.

The Yellow River basin has been experiencing ecosystem fragmentation, conversion, and degradation. The ecological security pattern (ESP) can provide a systematic and holistic perspective for specific action planning to maintain ecosystem structural, functional stability, and its connectivity. Thus, this study focused on Sanmenxia, one of the most representative cities of the Yellow River basin, to construct an integrated ESP to provide evidence-based support for ecological conservation and restoration. We adopted four main steps, including measuring the importance of multiple ecosystem services, identifying ecological sources, constructing the ecological resistance surface, and linking the MCR model and circuit theory to identify the optimal path, optimal width, and key nodes of ecological corridors. Overall, we identified various ecological conservation and restoration priority areas in Sanmenxia, including 3593.08 km2 of ecosystem service hotspots, 28 corridors, 105 pinch points, and 73 barriers, and we highlighted multiple priority actions. This study provides an effective starting point for the future identification of ecological priorities at the regional or river basin scale.