4.7 Article

Spatial distribution of heavy metal contamination and uncertainty-based human health risk in the aquatic environment using multivariate statistical method

期刊

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
卷 28, 期 18, 页码 22804-22822

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-020-12212-x

关键词

Heavy metals; Health risk; Multivariate statistical method; Uncertainty analysis; Decision-makers

资金

  1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences [WL2018003]
  2. Scientific and Technological Research Projects of Colleges and Universities in Hebei Province [QN2019054]
  3. Science Foundation of Hebei Normal University [L2019B36]
  4. Natural Science Foundation of Hebei Province [E2020202117]
  5. Science and Technology Project of Hebei Education Department [BJ2020019]
  6. Beijing-Tianjin-Hebei Collaborative Innovation Project of Tianjin Science and Technology Plan [19YFHBQY00050]
  7. Second Tibetan Plateau Scientific Expedition and Research Program (STEP) [2019QZKK1003]

向作者/读者索取更多资源

An evaluation framework was developed to identify the sources and health risks of heavy metal contamination in the North Canal of Fengtai District, China. The spatial distribution of heavy metals shows their impact on the aquatic environment. Recommended strategies were given to improve water environment quality.
Heavy metal contamination in the aquatic environment is one of the most serious health issues worldwide. In this study, an evaluation framework is developed to identify the sources and health risk of heavy metals (i.e., As, Hg, Cr, Cu, Zn, Pb, and Cd) contamination in the North Canal of Fengtai District, China, which is based on multiple approaches, including multivariate statistical method, health risk assessment, and uncertainty analysis. Spatial distribution of these heavy metals could exhibit their impact on the aquatic environment. Pearson's correlation analysis shows that a majority of the correlations between different heavy metals are not significant due to the differences in sources of heavy metals. Principal component analysis indicates that there are four principal components to explain 91.381% of the total variance. Moreover, health risk reveals that hazard quotient values are in low levels, ranging from 0.48 to 0.74, relative higher quotient levels could be observed in the northern section. The carcinogenic risk of Cd has exceeded the acceptable level in S1, S3, and S7. Sensitivity analysis ensures the reliability of health risk assessments. Furthermore, some specific recommendations are given to help decision-makers develop more comprehensive strategies for improving water environment quality.

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