## 3 Results
### Identification of the Sources of HMs in Sediments  
In recent years, the PMF model, recognized as a typical receptor model and an effective approach for pollutant source apportionment, has gained widespread application [20,44,47,48]. An analysis of HM sources in sediments from the YRB using the PMF model revealed that the average concentrations of seven HMs at 44 sample points in the study area were all above the detection limit. The number of runs was set to the system-recommended 20 times, with the factor number ranging from 3 to 6. Calculations were performed by selecting random initial iteration numbers. When the factor number was 3, the Q\({}_{\rm Robust}\)/Q\({}_{\rm True}\) reached the minimum convergence value, and the source apportionment model for the seven HMs exhibited a normal distribution. The fitting R\({}^{2}\) value was higher than 0.8, effectively elucidating the pollution source information. The results of the model run are shown in  
Figure 4: Statistical results of single-factor evaluation of HMs in sediments.  
Figure 6a. The results of HM pollution sources in the YRB obtained through PMF model analysis are presented in Figure 6b,c.  
Figure 5: Distribution characteristics of the _PLI_.  
Figure 6: Source apportionment of HMs using the PMF model. (**a**) PMF Source apportionment model. (**b**) Contribution rates of various HMs. (**c**) Contribution rates of various factors.  
liquids containing HMs like copper and zinc are generated. Furthermore, certain chemical enterprises produce wastewater or residues containing HMs such as copper and zinc during production. If these wastes are improperly handled, they may enter river environments and accumulate in sediments [51; 52]. Therefore, Factor 1 represents a traffic-industrial source, explaining 32.47% of the HM sources in the sediments.  
Factor 2 accounted for 44.87% of the HM sources in the sediments, with high loadings of As (67.35%), Cr (66.02%), Ni (65.92%), and Cd (40.13%). Factor 3 explained 22.66% of the HM sources in the sediments, primarily due to the high loading of Cd (59.87%). The sediments in the study area showed moderate variation in Ni content and high variation in As content (Table S3), indicating that both elements are significantly influenced by human activities. Pollution assessment results also revealed severe As contamination in the sediments within the study area. Studies have shown that coal combustion, industrial activities, and weathering of soil-forming parent materials are the primary sources of Ni in soils [53; 54], while As mainly originates from fossil fuel combustion, wastewater emissions from coal-fired power plants, and smelters [55]. Continuous wastewater discharges from smelters and coal-fired power plants inevitably lead to increased As and Ni concentrations in river sediments [56]. Additionally, previous studies have indicated that the enrichment of Ni and Cr in soil environments is associated with the weathering of rock parent materials and coal combustion emissions, whereas the accumulation of Cr and Cd is closely related to long-term agricultural practices, such as the application of phosphate fertilizers, insecticides, pesticides, and organic fertilizers. Therefore, it can be inferred that Factor 2 represents an agricultural-industrial source, while Factor 3 represents an industrial source, explaining 44.87% and 22.66%, respectively, of the HM sources in the sediments.