Abstract
Trace elements have been widely used for classification (of variables and of samples) and source apportionment studies, but the comparison and combination of the two is uncommon in previous works. In this paper, the grouping of trace elements, clustering of samples, and source identification were merged for an integrated understanding of the origin and distribution of trace elements in western Philippine Sea sediments. The grouping and clustering studies were implemented by a nonlinear clustering method called a self-organizing map (SOM), and the source identification was accomplished by a nontraditional factor analysis method called positive matrix factorization (PMF). Through visualization and clustering techniques, the SOM simultaneously classified a database of 26 trace elements into four groups of trace elements and five clusters of samples. Each sample cluster occupies a certain geographic area and is characterized by high concentrations of trace elements that are classified within one or two groups. Five potential sources were identified by PMF, representing the land mass of Taiwan Island, anthropogenic emissions from Taiwan, nutrient exportation from the South China Sea, mineral attachment in the deep ocean, and biogenetic components and riverine inputs from the Luzon Islands. The spatial distributions of the sample clusters are comparable to the ranges of high contributions from the five sources distinguished by PMF. This conclusion was further supported by displaying the PMF outputs on the SOM plane. Furthermore, a corresponding relationship was observed between every factor profile and every trace element group. Our work tests the consistency of the classification (of the trace elements and of the samples) and source identification and improves the application of multiperspective methodology in environmental studies.
Published Version
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