# Risk Assessment and Source Apportionment of Heavy Metals in Soils from Handan City
## 3 Results and Discussion
### Source Apportionment of Heavy Metals
#### 3.4.4 Source Apportionment by PMF Model  
The PMF model was applied to determine the source categories and quantitatively calculate their contributions of soil heavy metals. Three sources were apportioned by the PMF model, and their factor profiles are presented in Figure 7. Residue analysis showed that most heavy metal values were between \(-3\) and \(3\). The fitting results of the observed concentrations and predicted concentrations are shown in Figure S1. The \(R^{2}\) values were greater than \(0.51\), indicating that the PMF model obtained reliable results and satisfied the research requirement. With the advancement of receptor modeling, together with the Geographic Information System, a visual analysis of the emission source contribution  
Figure 7: Factor profiles and source contributions of heavy metals by PMF model.  
is now possible. When identifying the sources of heavy metals, a study of the spatial relationship between different land-use types and pollution sources is vital. The spatial distributions of source contributions not only provides more detailed heavy-metal source information, it can also be conducive to obtaining reliable source apportionment results.  
Factor 1 accounted for 17.61% of the total contribution rate. Pb, Cd and Cu were the main loading elements, accounting for 80.84%, 66.65% and 51.10% of contributions, respectively. The spatial distribution of factor 1 is presented in Figure 8a. Factor 1 has a great influence on the west of the study area, Airport Road, South Ring Road, Fuhe North Street and Lianfang East Road, a source of traffic. According to the previous description, Pb, Cd, and Cu come from a traffic source, so factor 1 is the traffic source.  
Factor 2 comprised 28.62% of the total variance. The main loading elements were Cr and Ni, with a contribution of more than 70%. The distribution of factor 2 is presented in Figure 8b. The middle of the study area is highly affected by factor 2, and the content has no relationship with the industrial area and traffic roads. The source of Ni is related to the weathering process, and the source of Cr is parent material [29]. Therefore, factor 2 is identified as the natural source.  
Factor 3 was the largest of the three factors and made up 53.77% of the total contributions. Mn and Zn had a high load and accounted for 67.58% and 58.49% of the total, respectively. Cd was moderately loaded. The distribution of factor 3 is presented in Figure 8c, and the high-value area is located in the industrial area with the iron and steel group. Therefore, factor 3 can be classified as the industrial source.  
Overall, according to the results of spatial distribution, risk assessment and source apportionment, it is noteworthy that Cd was the heaviest pollutant metal in the study area. The spatial distribution of factor 1 and factor 3 with a high Cd concentration loading decreased from southwest to northeast. This indicated that the heavy metal pollution of soil, especially Cd, was typically associated with traffic activities or discharges from steel ammeter and manufacturing industries. As a typical heavy-industry city, the economic structure of Handan is dominated by heavy industry [55]. The Handan urban area is flatter, with less vegetation and bare soil. It is affected by industrial resuspended dust-bound heavy metals that accumulated in the topsoil.  
Given this, measures should be undertaken to alleviate the contamination. For instance, the capacity of industrials, including iron, steel, chemical, and heavy engineering industries needs to be reduced. The high capacity of industries has seriously hindered the sustainable development of this city. Furthermore, the promotion of pollution reduction, acceleration of economic structure transformation and promotion of ecological environmental protection are also effective ways to alleviate heavy-metal contamination.