## 3 Results
### Source Identification
#### 3.4.2 Principal Component Analysis (PCA)  
To identify and quantify the sources of the seven heavy metals in soil, PCA was used to further analyze the sources of heavy metals in soil more accurately. Firstly, the data were tested by KMO and Bartlett sphere, and the KMO value of the test result was 0.886. Therefore, the dataset was suitable for PCA. The analysis results are shown in Tables 6 and 7. The cumulative variance percentage contribution of the front three principal components is 87.137%, which basically represents the indicators of heavy metal in the study area. The variance contribution rate of the first principal component is 54.72%. The load values of Cu, Pb, Zn, Cd, and As are relatively large among the 7 elements, all of which are greater than 0.6. Meanwhile, they are significantly correlated with each other in the CA. Field investigation also found that they are high in the farmland soil near the mining area and along the road, and the mining of tin polymetallic ore produces a large number of tailings containing a certain amount of Cd, Pb, and Cu. The oxides and sulfides of the above elements may enter the environment through the weathering process and cause serious pollution to the surrounding soil [34; 35]. Therefore, it is speculated that the first principal component is enriched by the influence of tailings accumulation, mining, and transportation. The contribution rate of PC2 (the second principal component) is 17.82%, and the highest load value is Ni. Ni has a significant positive correlation with Cu, but not with other elements. It is speculated that it may be related to sewage irrigation, pesticides, and soil-forming parent materials. The load value of Cr is the highest in the third principal component, with a contribution rate of 14.60%. The correlation between Cr and the other six elements is not significant. It is considered that Cr is related to the soil-forming parent materials.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Components**} & \multicolumn{3}{c}{**Extraction Sums of Squared Loadings**} & \multicolumn{3}{c}{**Rotation Sums of Squared Loadings**} \\ \cline{2-7}  & **Eigenvalues** & **\% of Variance** & **Cumulative \%** & **Eigenvalues** & **\% of Variance** & **Cumulative \%** \\ \hline PC1 & 3.943 & 56.327 & 56.327 & 3.83 & 54.720 & 54.720 \\ PC2 & 1.233 & 17.619 & 73.946 & 1.247 & 17.816 & 72.536 \\ PC3 & 0.923 & 13.191 & 87.137 & 1.022 & 14.601 & 87.137 \\ PC4 & 0.379 & 5.414 & 92.552 & & & \\ \hline \hline \end{tabular}
\end{table}
Table 6: Total variance explained and component matrices for heavy metals.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Item** & **Cr** & **Ni** & **Cu** & **Zn** & **Cd** & **Pb** & **As** &
\begin{tabular}{c} **Organic** \\ **Matter** \\ \end{tabular} & **pH** & **Eh** \\ \hline Cr & \(1\) & & & & & & & & \\ Ni & 0.113 & \(1\) & & & & & & \\ Cu & 0.148 & 0.358 ** & \(1\) & & & & & \\ Zn & 0.174 & 0.086 & 0.712 ** & \(1\) & & & & \\ Cd & 0.160 & \(-\)0.570 * & 0.631 ** & 0.964 ** & \(1\) & & & \\ Pb & 0.037 & \(-\)0.058 & 0.633 ** & 0.758 ** & 0.785 ** & \(1\) & & \\ As & 0.072 & \(-\)0.047 & 0.596 ** & 0.815 ** & 0.831 ** & 0.839 ** & \(1\) & \\ organic matter & \(-\)0.560 ** & \(-\)0.338 ** & 0.129 & 0.301 & 0.211 & 0.266 ** & 0.385 ** & \(1\) & \\ pH & \(-\)0.083 & 0.369 ** & 0.443 ** & 0.547 ** & 0.628 ** & 0.518 ** & 0.512 ** & 0.248 & \(1\) \\ Eh & 0.132 & \(-\)0.338 ** & \(-\)0.449 ** & \(-\)0.507 ** & \(-\)0.581 ** & \(-\)0.482 ** & \(-\)0.498 ** & \(-\)0.206 & \(-\)0.945 ** & \(1\) \\ \hline \hline \end{tabular}
\end{table}
Table 5: Correlation coefficients among heavy metals, pH, Eh, and organic matter.