## 3 Results and Discussion
### Source and Pollution Degree of Heavy Metals in Soil
#### 3.3.2 Source Analysis of PMF Model  
By using constraints, PMF can obtain results that no sample can have significantly negative source contributions. The uncertainty caused by modeling error, random error, and rotational ambiguity can be avoided by the bootstrap (BS), displacement (DISP), and the BS-DISP [25]. The data was processed through 100 iterations to identify the smallest and most stable Q (robust). After multiple attempts, it was finally determined that the Q (robust) was the smallest when factor 4 was used. Most of the residuals were in the \([-3,3]\) interval, indicating an ideal modeling. Results from PMF analysis were shown in Figure 6. Factor 1 was dominated by Cr (79.9%) and Ni (53.3%), followed by Cu (27.2%), Zn (7.9%), Pb (4.4%), and As (1.4%). Studies have shown that the Cr and Ni in the topsoil are mainly affected by the natural background [26; 27]. There is a positive correlation between Cr and Ni (Table 3), indicating that they have similar origins. The CV of Cr and Ni was 0.51 and 0.44 (Table 1), respectively, indicating that their variation is relatively small and was less affected by human activities. Therefore, Cr and Ni mainly come from natural sources and are affected by soil-forming parental materials. In contrast, Cu, Zn, Pb, and As are partly from natural sources. Factor 1 can be interpreted as a natural source. The contribution rate of factor 2 was 85%, 29.9%, 23.1%, 3.8%, and 0.5% for Pb, Zn, Cu, Cr, and As, respectively. Pb mainly contributed by factor 1 constituted the most significant potential ecological risk in the soils of the study area. Pb is usually present in natural soils,  
Figure 5: Two-dimensional ordination of CCA of soil heavy metal contents and soil physicochemical properties. and the content of Pb increases significantly with the continuous industrial modernization (e.g., mining, steel processing, coal combustion, and lead-acid battery production) [28]. Pb and Zn in the soil were enriched in the non-ferrous metal slag field in the study area through rainwater erosion and atmospheric deposition [29; 30; 31; 32]. Transportations are also an important source of soil Pb and Zn. National Highway 108 traverses the entire study area from north to south. Brake pad wear, lubricating oil loss, tire wear, and corrosion of automobile parts can result in the enrichment of Pb and Zn in soil [33]. Therefore, factor 2 can be used as a mixed source for industry and transportation. Factor 3 had high contribution to the As (90.0%), while its contribution to Cu (17.2%), Cr (16.3%), Ni (13.6%), and Pb (5.2%) was relatively low. The main anthropogenic sources of As include mining activities, metal smelting, pesticides, and fertilizers. In particular, the use of As-containing pesticides, As-containing feed additives in pig and poultry farming, and manure from poultry for land fertilization may lead to soil contamination in large areas of agricultural land [34; 35]. High As pollution was located in the north of the study area (Figure 2), which is far from the slag field. The land use types were mainly forest land (sites# 29-31), dry land (sites# 46-49), and garden land (sites# 61-63). The vegetation coverage in this study area is low, and the application of As-containing pesticides and fertilizers in dryland and garden land leads to an increase in As content. Thus, factor 3 can be defined as an agricultural source. The main loading elements of factor 4 were Zn, Ni, and Cu. The contribution rates of factor 4 for Zn, Ni, and Cu were 62.2%, 33.1%, and 32.5%, respectively, followed by 8.1% for As and 5.4% for Pb. Lima River flows through the study area from north to south (Figure 1). A large amount of wastewater containing Zn, Ni, Cu, As, and Pb was produced near the non-ferrous metal slag field and discharged into the Lima River. Under the influence of the dry-hot valley, soil erosion is serious, and soil heavy metals are easily accumulated in the lower reaches of the Lima River.