Department of Soil Science, Khuzestan Science and Research Branch, Islamic Azad University, Ahvaz, Iran.
Department of Soil Sciences, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran.
Sci Rep. 2021 Apr 8;11(1):7806. doi: 10.1038/s41598-021-86937-1.
In this study, statistical analysis and spatial distribution were performed to compare raw data and centred log-ratio (clr) transformed data of three copper (Cu), lead (Pb), and zinc (Zn) potentially toxic elements (PTEs) concentration for 550 surface soil samples in Khuzestan plain. The results of both approaches showed that classical univariate analysis and compositional data analysis are essential to find the real structure of data and clarify its different aspects. Results also indicated that spatial distributions of raw data and clr-transformed data were completely different in three studied metals. Raw data necessarily shows the effects of anthropogenic activities and needs an additional evaluation of human health risk assessment for these three studied elements. Data obtained from clr-coefficient maps also demonstrated the role of geological processes in the distribution pattern of potentially toxic elements (PTEs). To improve the understanding of the implications for PTE pollution and consequences for human health, a RGB colour composite map was produce to identify the potential origin of PTEs from areas with higher than typical baseline concentrations.
在这项研究中，对 550 个表层土壤样本中的三种铜（Cu）、铅（Pb）和锌（Zn）潜在有毒元素（PTE）浓度的原始数据和中心对数比（clr）转换后的数据进行了统计分析和空间分布比较。两种方法的结果均表明，经典的单变量分析和组合数据分析对于发现数据的真实结构和阐明其不同方面是必不可少的。结果还表明，三种研究金属的原始数据和clr 转换后数据的空间分布完全不同。原始数据必然反映了人为活动的影响，需要对这三种研究元素的人体健康风险评估进行额外评估。clr 系数图获得的数据还表明了地质过程在潜在有毒元素（PTE）分布模式中的作用。为了更好地了解 PTE 污染的影响及其对人类健康的后果，生成了一个 RGB 彩色合成图，以确定高浓度 PTE 的潜在来源。
