Source apportionment for contaminated soils using multivariate statistical methods

Sonnia Parra, Manuel A. Bravo, Waldo Quiroz, Teresa Moreno, Angeliki Karanasiou, Oriol Font, Víctor Vidal, Francisco Cereceda-Balic

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


The application of statistical techniques for the recognition and identification of contamination sources has become an increasingly important tool. The chemical compositions of soil samples collected in the Puchuncaví Valley (Chile) provide a dataset suitable for the application of source apportionment techniques such as positive matrix factorization (PMF) and principal component analysis (PCA) with varimax rotation. PMF allowed the identification of the chemical profile and the relative contribution of three interpretable factors related to three contamination sources. Combining these results with a PCA analysis successfully showed that the main source of pollution emits Cu, Zn, As, Se, Mo, Sn, Sb and Pb. Therefore, the use of source profiles for contaminated soils shows much promise both for incorporating well-established knowledge about pollution sources and as a tool for incremental, exploratory data analysis.

Original languageEnglish
Pages (from-to)127-132
Number of pages6
JournalChemometrics and Intelligent Laboratory Systems
StatePublished - 15 Nov 2014


  • Emission sources
  • Positive matrix factorization
  • Soil contamination


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