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Chemometric Assessment of Soil Pollution and Pollution Source Apportionment for an Industrially Impacted Region around a Non-Ferrous Metal Smelter in Bulgaria

机译:保加利亚有色金属冶炼厂周围工业影响区的土壤污染和污染源分配的化学计量学评估

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摘要

The present study deals with the assessment of pollution caused by a large industrial facility using multivariate statistical methods. The primary goal is to classify specific pollution sources and to apportion their involvement in the formation of the total concentration of the chemical parameters being monitored. This aim is accomplished by intelligent data analysis based on cluster analysis, principal component analysis and principal component regression analysis. Five latent factors are found to explain over 80% of the total variance of the system being conditionally named “organic”, “non-ferrous smelter”, “acidic”, “secondary anthropogenic contribution” and “natural” factor. The apportionment models designate the contribution of the identified sources quantitatively and help in the interpretation of risk assessment and management actions. Since the study takes into account pollution uptake from soil to a cabbage plant, the data interpretation could help in introducing biomonitoring aspects of the assessment. The chemometric expertise helps in revealing hidden relationships between the objects and the variables involved to achieve a better understanding of specific pollution events in the soil of a severely industrially impacted region.
机译:本研究使用多元统计方法处理由大型工业设施引起的污染评估。主要目标是对特定的污染源进行分类,并分摊它们对所监测化学参数总浓度的形成的影响。该目标是通过基于聚类分析,主成分分析和主成分回归分析的智能数据分析来实现的。发现五个潜在因素可以解释系统总变化的80%以上,这些有条件地称为“有机”,“有色金属冶炼厂”,“酸性”,“次要人为贡献”和“自然”因素。分配模型定量地确定已识别来源的贡献,并有助于解释风险评估和管理措施。由于该研究考虑了从土壤到卷心菜植物的污染吸收,因此数据解释可以帮助引入评估的生物监测方面。化学计量学的专业知识有助于揭示物体与所涉及变量之间的隐藏关系,以更好地了解受严重工业影响区域土壤中的特定污染事件。

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