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Updated: Mar 23, 2026

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil
Published on: September 1, 2020
An exploration of spatial human health risk assessment of soil toxic metals under different land uses using
Jin-Hui Huang1, Wen-Chu Liu1, Guang-Ming Zeng1
1College of Environmental Science and Engineering, Hunan University, Changsha 410082, China; Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, China.
Abstract:
A modified method was proposed which integrates the spatial patterns of toxic metals simulated by sequential indicator simulation, different exposure models and local current land uses extracted by remote-sensing software into a dose-response model for human health risk assessment of toxic metals. A total of 156 soil samples with a various land uses containing farm land (F1-F25), forest land (W1-W12) and residential land (U1-U15) were collected in a grid pattern throughout Xiandao District (XDD), Hunan Province, China. The total Cr and Pb in topsoil were analyzed. Compared with Hunan soil background values, the elevated concentrations of Cr were mainly located in the east of XDD, and the elevated concentrations of Pb were scattered in the areas around F1, F6, F8, F13, F14, U5, U14, W2 and W11. For non-carcinogenic effects, the hazard index (HI) of Cr and Pb overall the XDD did not exceed the accepted level to adults. While to children, Cr and Pb exhibited HI higher than the accepted level around some areas. The assessment results indicated Cr and Pb should be regarded as the priority pollutants of concern in XDD. The first priority areas of concern were identified in region A with a high probability (>0.95) of risk in excess of the accepted level for Cr and Pb. The areas with probability of risk between 0.85 and 0.95 in region A were identified to be the secondary priority areas for Cr and Pb. The modified method was proved useful due to its improvement on previous studies and calculating a more realistic human health risk, thus reducing the probability of excessive environmental management.
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