The concentrations of Cd, Pb and Zn in these riparian wetlands are significantly lower than those in Guangzhou city riverine sediment. It is apparently attributed to the decrease of disturbances by industrial or municipal activities because the sampling sites in our study mostly located in the rural area. Whereas compared with the mudflat in PRE, Cr and Pb are generally higher in our study and the other metals were obvious lower than those concentrations in mudflat [22]. It may imply the increase of accumulations of Cr and Pb occurred in recent years.
In order to further identify the relationships between different metals and its corresponding origins, principal component analysis (PCA) and cluster analysis (CA) are conducted in our study. PCA and CA could provide some indications for association of heavy metals and give some information about the origins of contamination [39].
The results of PCA reflect that Cd, Cr, Cu, Ni, Pb and Zn are dominated by two principal components which accounted for 83.4% of the total variance explains. As shown in Table 3, Cd and Pb are associated with the high values in the first component whereas Cr, Cu and Ni are greater in the second component. The concentrations of Zn are simultaneously controlled by both first and second component although the first component was more important. Many previous studies have proved that good associations of different metals indicated similar sources of pollution [17,18,40].
The concentrations of Cd, Pb and Zn in these riparian wetlands are significantly lower than those in Guangzhou city riverine sediment. It is apparently attributed to the decrease of disturbances by industrial or municipal activities because the sampling sites in our study mostly located in the rural area. Whereas compared with the mudflat in PRE, Cr and Pb are generally higher in our study and the other metals were obvious lower than those concentrations in mudflat [22]. It may imply the increase of accumulations of Cr and Pb occurred in recent years. In order to further identify the relationships between different metals and its corresponding origins, principal component analysis (PCA) and cluster analysis (CA) are conducted in our study. PCA and CA could provide some indications for association of heavy metals and give some information about the origins of contamination [39]. The results of PCA reflect that Cd, Cr, Cu, Ni, Pb and Zn are dominated by two principal components which accounted for 83.4% of the total variance explains. As shown in Table 3, Cd and Pb are associated with the high values in the first component whereas Cr, Cu and Ni are greater in the second component. The concentrations of Zn are simultaneously controlled by both first and second component although the first component was more important. Many previous studies have proved that good associations of different metals indicated similar sources of pollution [17,18,40].
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