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Open AccessArticle

Heavy Metal Pollution Delineation Based on Uncertainty in a Coastal Industrial City in the Yangtze River Delta, China

by Bifeng Hu 1,2,3,4, Ruiying Zhao 1, Songchao Chen 3,5, Yue Zhou 1, Bin Jin 6, Yan Li 7,* and Zhou Shi 1
1
Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou 310058, China
2
Unité de Recherche en Science du Sol, INRA, Orléans 45075, France
3
InfoSol, INRA, US 1106, Orléans F-4075, France
4
Sciences de la Terre et de l’Univers, Orléans University, Orleans 45067, France
5
Unité Mixte de Rercherche (UMR) Sol Agro et hydrosystème Spatialisation (SAS), INRA, Agrocampus Ouest, Rennes 35042, France
6
Ningbo Agricultural Food Safety Management Station, Ningbo 315000, China
7
Institute of Land Science and Property, School of Public Affairs, Zhejiang University, Hangzhou 310058, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2018, 15(4), 710; https://doi.org/10.3390/ijerph15040710
Received: 14 March 2018 / Revised: 31 March 2018 / Accepted: 3 April 2018 / Published: 10 April 2018
(This article belongs to the Special Issue Soil Pollution and Remediation)
Assessing heavy metal pollution and delineating pollution are the bases for evaluating pollution and determining a cost-effective remediation plan. Most existing studies are based on the spatial distribution of pollutants but ignore related uncertainty. In this study, eight heavy-metal concentrations (Cr, Pb, Cd, Hg, Zn, Cu, Ni, and Zn) were collected at 1040 sampling sites in a coastal industrial city in the Yangtze River Delta, China. The single pollution index (PI) and Nemerow integrated pollution index (NIPI) were calculated for every surface sample (0–20 cm) to assess the degree of heavy metal pollution. Ordinary kriging (OK) was used to map the spatial distribution of heavy metals content and NIPI. Then, we delineated composite heavy metal contamination based on the uncertainty produced by indicator kriging (IK). The results showed that mean values of all PIs and NIPIs were at safe levels. Heavy metals were most accumulated in the central portion of the study area. Based on IK, the spatial probability of composite heavy metal pollution was computed. The probability of composite contamination in the central core urban area was highest. A probability of 0.6 was found as the optimum probability threshold to delineate polluted areas from unpolluted areas for integrative heavy metal contamination. Results of pollution delineation based on uncertainty showed the proportion of false negative error areas was 6.34%, while the proportion of false positive error areas was 0.86%. The accuracy of the classification was 92.80%. This indicated the method we developed is a valuable tool for delineating heavy metal pollution. View Full-Text
Keywords: soil heavy metal pollution; indicator kriging (IK); Nemerow integrated pollution index (NIPI); uncertainty; pollution area definition soil heavy metal pollution; indicator kriging (IK); Nemerow integrated pollution index (NIPI); uncertainty; pollution area definition
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MDPI and ACS Style

Hu, B.; Zhao, R.; Chen, S.; Zhou, Y.; Jin, B.; Li, Y.; Shi, Z. Heavy Metal Pollution Delineation Based on Uncertainty in a Coastal Industrial City in the Yangtze River Delta, China. Int. J. Environ. Res. Public Health 2018, 15, 710.

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