4.7 Article

Spatial distribution and health risk assessment of toxic metals associated with receptor population density in street dust: a case study of Xiandao District, Changsha, Middle China

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 22, Issue 9, Pages 6732-6742

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-014-3753-3

Keywords

Street dust; Metals; Health risk assessment; Geostatistics; Receptor population density

Funding

  1. National Natural Science Foundation of China [51178172, 51039001, 51378190]
  2. Chinese Ministry of Education [113049A]
  3. Research Fund for the Program for Changjiang Scholars and Innovative Research Team in University [IRT-13R17]

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Spatial characteristics of the properties (dust organic material and pH), concentrations, and enrichment levels of toxic metals (Ni, Hg, Mn and As) in street dust from Xiandao District (Middle China) were investigated. Method of incorporating receptor population density into noncarcinogenic health risk assessment based on local land use map and geostatistics was developed to identify their priority pollutants/regions of concern. Mean enrichment factors of studied metals decreased in the order of Hg a parts per thousand As > Mn > Ni. For noncarcinogenic effects, the exposure pathway which resulted in the highest levels of exposure risk for children and adults was ingestion except Hg (inhalation of vapors), followed by dermal contact and inhalation. Hazard indexes (HIs) for As, Hg, Mn, and Ni to children and adults revealed the following order: As > Hg > Mn > Ni. Mean HI for As exceeded safe level (1) for children, and the maximum HI (0.99) for Hg was most approached the safe level. Priority regions of concern were indentified in A region at each residential population density and the areas of B at high and moderate residential population density for As and the high residential density area within A region for Hg, respectively. The developed method was proved useful due to its improvement on previous study for making the priority areas of environmental management spatially hierarchical and thus reducing the probability of excessive environmental management.

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