Uncertainty assessment of mapping mercury contaminated soils of a rapidly industrializing city in the Yangtze River Delta of China using sequential indicator co-simulation |
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Authors: | Yongcun Zhao Xianghua Xu Weixia Sun Biao Huang Jeremy Landon Darilek Xuezheng Shi |
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Institution: | (1) State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China;(2) Department of Earth Sciences, Nanjing University, Nanjing, 210093, China |
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Abstract: | Accurate characterization of heavy-metal contaminated areas and quantification of the uncertainties inherent in spatial prediction
are crucial for risk assessment, soil remediation, and effective management recommendations. Topsoil samples (0–15 cm) (n = 547) were collected from the Zhangjiagang suburbs of China. The sequential indicator co-simulation (SIcS) method was applied
for incorporating the soft data derived from soil organic matter (SOM) to simulate Hg concentrations, map Hg contaminated
areas, and evaluate the associated uncertainties. High variability of Hg concentrations was observed in the study area. Total
Hg concentrations varied from 0.004 to 1.510 mg kg−1 and the coefficient of variation (CV) accounts for 70%. Distribution patterns of Hg were identified as higher Hg concentrations
occurred mainly at the southern part of the study area and relatively lower concentrations were found in north. The Hg contaminated
areas, identified using the Chinese Environmental Quality Standard for Soils critical values through SIcS, were limited and
distributed in the south where the SOM concentration is high, soil pH is low, and paddy soils are the dominant soil types.
The spatial correlations between Hg and SOM can be preserved by co-simulation and the realizations generated by SIcS represent
the possible spatial patterns of Hg concentrations without a smoothing effect. Once the Hg concentration critical limit is
given, SIcS can be used to map Hg contaminated areas and quantitatively assess the uncertainties inherent in the spatial prediction
by setting a given critical probability and calculating the joint probability of the obtained areas. |
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Keywords: | Heavy metal Mercury Spatial uncertainty Sequential indicator co-simulation |
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