## 3 Results
### Comparison of Different Cleaning Methods
#### 3.2.3 Principal Component Analysis of Four Heavy Metals in Three Plant Species  
According to the results of the principal component analysis (Table 3), the cumulative variance contribution of the first two principal components reached 91.17%, so the first two principal components were deemed sufficient to explain the original data. The loadings of Cu, Cd, and Zn in principal component 1 (PC1) were greater than 0.86, and the loading of Mn in principal component 2 (PC2) was larger than 0.876 (Table 4). \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multicolumn{13}{c}{**Chinese Juniper**} & \multicolumn{5}{c}{**Dragon Juniper**} & \multicolumn{5}{c}{**Cedar**} \\ \hline  & \(C_{w}\) & \(P_{w}\) & \(C_{e}\) & \(P_{e}\) & \(C_{w}\) & \(P_{w}\) & \(C_{e}\) & \(P_{e}\) & \(C_{w}\) & \(P_{w}\) & \(C_{e}\) & \(P_{e}\) \\  & **(\(\mathbf{\mu g\cdot g^{-1}}\))** & **(\%)** & **(\(\mathbf{\mu g\cdot g^{-1}}\))** & **(\%)** & **(\(\mathbf{\mu g\cdot g^{-1}}\))** & **(\%)** & **(\(\mathbf{\mu g\cdot g^{-1}}\))** & **(\%)** & **(\(\mathbf{\mu g\cdot g^{-1}}\))** & **(\%)** & **(\(\mathbf{\mu g\cdot g^{-1}}\))** & **(\%)** & **(\(\mathbf{\mu g\cdot g^{-1}}\))** & **(\%)** \\ \hline Cu & 7.01 & 34.45 & 8.58 & 42.16 & 5.18 & 27.95 & 6.99 & 37.72 & 3.29 & 15.68 & 6.90 & 32.89 \\ Mn & 6.10 & 10.54 & 9.31 & 16.08 & 1.98 & 5.36 & 6.60 & 17.88 & 4.55 & 14.96 & 6.50 & 21.37 \\ Cd & 3.39 & 58.35 & 4.16 & 71.60 & 2.73 & 41.87 & 3.98 & 61.04 & 1.71 & 30.59 & 2.16 & 38.64 \\ Zn & 8.49 & 21.45 & 11.24 & 28.40 & 6.24 & 17.82 & 9.38 & 26.79 & 3.23 & 10.54 & 5.33 & 17.40 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Differences in content (\(\mathbf{\mu g\cdot g^{-1}}\)) and percentages (%) between the two cleaning methods for different plants. \(C_{w}\): water-eluted fraction; \(P_{w}\): percentage of elution for water-washing treatment; \(C_{e}\): ethanol-eluted fraction; \(P_{e}\): percentage of elution for ethanol-washing treatment. Figure 2: Heavy metal contents in needles of the three plants under different treatments. Different letters represent significant differences among the three types of needles under the same treatment for the same heavy metal content (\(p<0.05\)). UW: without washing; WW: water washing; EW: ethanol washing. For PC1 (Figure 3), the two washing methods and unwashed treatment were distinct from each other, showing a trend of UW > WW > EW. There was no significant difference between the three methods for PC2 (Figure 3). It was presumed that PC1 represents the heavy metals that were effectively cleaned off and PC2 represents the heavy metals for which cleaning was averagely effective. PC1 was mainly copper, cadmium, and zinc, and PC2 was mainly manganese. This means that the cleaning was more effective for Cu, Cd, and Zn, while the effect was not as obvious for Mn as it was for the other three elements. For PC2, the trend in the manganese content of the three plants was Chinese juniper > dragon juniper > cedar. The composite score model was calculated according to Tables 3 and 4 [22]  
\[\text{Y}=0.254\text{ Cu}+0.442\text{ Mn}+0.255\text{ Cd}+0.481\text{ Zn}. \tag{6}\]  
The coefficients corresponding to each indicator in the model are the weights of each indicator. It can be seen that the contents of the four heavy metals in the three plants were in the order of Zn > Mn > Cd > Cu. \begin{table}
\begin{tabular}{c c c} \hline \hline  & \multicolumn{2}{c}{**Initial Eigenvalues**} \\ \cline{2-3}
**Component** & **Total** & **\% of Variance** & **Cumulative \%** \\ \hline
1 & 2.43 & 60.85 & 60.85 \\
2 & 1.21 & 30.31 & 91.17 \\
3 & 0.24 & 6.06 & 97.23 \\
4 & 0.11 & 2.77 & 100.00 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Total variance explained. Figure 3: Principal component analysis scores for the three plant species. \begin{table}
\begin{tabular}{c c c} \hline \hline  & \multicolumn{2}{c}{**Component**} \\ \cline{2-3}  & **1** & **2** \\ \hline Cu & 0.864 & 0.381 \\ Mn & 0.414 & 0.876 \\ Cd & 0.880 & 0.401 \\ Zn & 0.861 & 0.371 \\ \hline \hline \end{tabular}
\end{table}