Kim Sung-Min, Choi Yosoon
Energy Resources Institute, Pukyong National University, Busan 48513, Korea.
Department of Energy Resources Engineering, Pukyong National University, Busan 48513, Korea.
Int J Environ Res Public Health. 2017 Jun 18;14(6):654. doi: 10.3390/ijerph14060654.
To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a -score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF) analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES) data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and -scores: high content with a high -score (HH), high content with a low -score (HL), low content with a high -score (LH), and low content with a low -score (LL). The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1-4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required.
为制定适当措施防止废弃矿区的土壤污染，有必要了解土壤中潜在有毒微量元素（PTEs）的空间变化。为了进行有效的土壤采样，本研究采用热点分析，该方法基于Getis-Ord Gi*统计量计算z分数，以识别具有统计学意义的热点样本。要构成具有统计学意义的热点，高值特征周围还应环绕其他高值特征。利用成本和时间效益相对较高的便携式X射线荧光（PXRF）分析，从釜山废弃矿山获取了足够的输入数据，并用于热点分析。为校准精度相对较低的PXRF数据，利用电感耦合等离子体原子发射光谱法（ICP-AES）数据对PXRF分析数据进行转换。釜山废弃矿山经转换的PXRF数据根据其归一化含量和z分数分为四组：高含量高z分数（HH）、高含量低z分数（HL）、低含量高z分数（LH）和低含量低z分数（LL）。HL和LH情况可能是由于测量误差所致。对于这些可疑样本周围的区域或重要热点区域，需要进行额外或补充调查。土壤采样按照四个阶段的程序进行，其中采用热点分析和建议的分组分类方法来支持下一阶段采样计划的制定。总体而言，在第1至4阶段分别对30、50、80和100个样本进行了调查和分析。本案例研究中实施的方法可在实地用于评估具有统计学意义的土壤污染，并识别需要进行额外调查的区域。
