Dataset for: Multivariate analyses and human health assessments of heavy metals for the surface water quality in the Xiangjiang River Basin, China
Posted on 24.01.2022 - 15:13 by Wiley Admin
The pollution by heavy metals in river water is becoming a major subject of global drinking water concern, and the Xiangjiang River is one of the most heavily polluted rivers in China. Water samples were collected from 17 sites spanning the entire Xiangjiang watershed from 2005 to 2016 to investigate spatial-temporal distributions and potential human health risks related to 8 metal pollutants (As, Cd, Hg, Cr, Cu, Pb, Zn, and Se). The results of spatial-temporal distribution analyses proved that most metals were below the guideline limits for the majority of the time. However, the hazard index (HQ) and carcinogenic risk (CR) analyses indicated that As and Cr facilitated a potential risk of cancer, although noncarcinogenic heavy metals in general and carcinogenic risk declined year by year. A nonparametric seasonal Mann–Kendall's test revealed that there were notable decreasing trends in As, Cd, Zn, Cu, Cr and Pb for most sites, whereas Se and Hg significantly increased in some areas over the targeted 12 years. The results of principal component analysis (PCA) agreed with dual hierarchical cluster analysis (DHCA) in the identification of pollution sources, the results of which are as follows: 1) As, Cd, Pb, Hg, and Zn were mainly derived from anthropogenic activities and the smelting industry; 2) Cr and Cu mainly originated from agricultural or industrial activities; and 3) Se was predominantly from natural erosion. This research will be conducive to optimizing the distribution of water monitoring stations and drafting remediation strategies pertaining to the protection of public health in metal-polluted areas.
CITE THIS COLLECTION
Jiang, Dongyi; Wang, Yunyuan; Zhou, Sangyang; Long, Zhe; Liao, Qi; Yang, Jinqin; et al. (2022): Dataset for: Multivariate analyses and human health assessments of heavy metals for the surface water quality in the Xiangjiang River Basin, China. Wiley. Collection. https://doi.org/10.6084/m9.figshare.c.5807264.v1
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