Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou 310058, China.
Unité de Recherche en Science du Sol, INRA, Orléans 45075, France.
Int J Environ Res Public Health. 2018 Apr 10;15(4):710. doi: 10.3390/ijerph15040710.
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.
评估重金属污染和划定污染区域是评估污染程度和确定经济有效的修复计划的基础。大多数现有研究都基于污染物的空间分布，但忽略了相关的不确定性。本研究在中国长江三角洲的一个沿海工业城市采集了 1040 个采样点的 8 种重金属浓度（Cr、Pb、Cd、Hg、Zn、Cu、Ni 和 Zn）。为了评估重金属污染程度，对每个表层样本（0-20cm）计算了单因子污染指数（PI）和内梅罗综合污染指数（NIPI）。普通克里金（OK）用于绘制重金属含量和 NIPI 的空间分布。然后，我们基于指示克里金（IK）产生的不确定性来划定复合重金属污染的范围。结果表明，所有 PI 和 NIPI 的平均值均处于安全水平。重金属在研究区的中部积累最多。基于 IK，计算了复合重金属污染的空间概率。中心核心城区的复合污染空间概率最高。发现概率为 0.6 是划定综合重金属污染污染区和非污染区的最佳概率阈值。基于不确定性的污染划定结果表明，假阴性误差区域的比例为 6.34%，而假阳性误差区域的比例为 0.86%。分类的准确率为 92.80%。这表明我们开发的方法是划定重金属污染的一种有效工具。
