The use of principal component analysis (PCA) for soil heavy metals characterization provides useful information for decision making and policies regarding the potential sources of soil contamination. However, the concentration of heavy metal pollutants is spatially heterogeneous. Accounting for such spatial heterogeneity in soil heavy metal pollutants will improve our understanding with respect to the distribution of the most influential soil heavy metal pollutants. In this study, geographically weighted principal component analysis (GWPCA) was used to describe the spatial heterogeneity and connectivity of soil heavy metals in Kumasi, Ghana. The results from the conventional PCA revealed that three principal components cumulatively accounted for 86% of the total variation in the soil heavy metals in the study area. These components were largely dominated by Fe and Zn. The results from the GWPCA showed that the soil heavy metals are spatially heterogeneous and that the use of PCA disregards this considerable variation. This spatial heterogeneity was confirmed by the spatial maps constructed from the geographically weighted correlations among the variables. After accounting for the spatial heterogeneity, the proportion of variance explained by the three geographically weighted principal components ranged between 85% and 89%. The first three identified GWPC were largely dominated by Fe, Zn and As, respectively. The location of the study area where these variables are dominated provides information for remediation.

中文翻译：

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地理加权主成分分析用于表征加纳库马西土壤重金属的空间异质性和连通性


使用主成分分析 (PCA) 进行土壤重金属表征可为有关土壤污染潜在来源的决策和政策提供有用的信息。然而，重金属污染物的浓度存在空间异质性。解释土壤重金属污染物的这种空间异质性将提高我们对最有影响力的土壤重金属污染物分布的理解。本研究采用地理加权主成分分析（GWPCA）来描述加纳库马西土壤重金属的空间异质性和连通性。常规主成分分析结果显示，3个主成分累计占研究区土壤重金属总变异的86%。这些成分主要以 Fe 和 Zn 为主。 GWPCA 的结果表明，土壤重金属在空间上存在异质性，PCA 的使用忽略了这种相当大的变化。这种空间异质性通过变量之间的地理加权相关性构建的空间图得到了证实。考虑空间异质性后，三个地理加权主成分解释的方差比例在 85% 至 89% 之间。前三个确定的 GWPC 分别主要以铁、锌和砷为主。这些变量占主导地位的研究区域的位置为修复提供了信息。