Abstract
Anthropogenic activities could result in increasing concentrations of heavy metals in soil and deteriorating in soil environmental quality. Topsoil samples from a typical industrial area, Shiting River Valley, Sichuan, Southwest China, were collected and determined for the concentrations of Cu, Zn, Cr, Cd, As, and Hg. The mean concentrations of these metals were lower than the national threshold values, but were slightly higher than their corresponding background values, indicating enrichment of these metals in soils in the valley, especially for Cu, Zn, and Hg. The topsoils in this area demonstrated moderate pollution and low potential ecological risk. Principal component analysis coupled with cluster analysis was applied to analyze the data and identified possible sources of these heavy metals; the results showed that soil Cd, Hg, As, Cu, and Zn were predominantly controlled by human activities, whereas Cr was mainly from the parent material. The spatial distribution of the heavy metals varied distinctly and was closely correlated to local anthropogenic activities. Furthermore, the concentrations of heavy metals in the industrial land demonstrated relatively higher levels than those of other land use patterns. Soil metal concentrations decreased with the distance increase from the traffic highway (0–1.0 km) and water system (0–2.0 km). Additionally, soil properties, especially pH and soil organic matter, were found to be important factors in the distribution and composition of metals.
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Acknowledgements
The authors acknowledge the funding provided by the Projects of Sci-Tech Support, Sichuan, China (No. 2014NZ0044), and the Projects of National Sci-Tech Support, China (2012BAD14B18-2), for carrying out this research. We wish to thank Ping Yao, Chuer Zhang, Yue Chen, Rui Ma, Yijun Wang, and Yaru Cao of Sichuan Agricultural University, for supporting the investigation and research work.
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Wang, G., Zhang, S., Xiao, L. et al. Heavy metals in soils from a typical industrial area in Sichuan, China: spatial distribution, source identification, and ecological risk assessment. Environ Sci Pollut Res 24, 16618–16630 (2017). https://doi.org/10.1007/s11356-017-9288-7
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DOI: https://doi.org/10.1007/s11356-017-9288-7