Self organizing maps for analysis of polycyclic aromatic hydrocarbons 3-way data from spilled oils

In this paper, the application of a new method based on self-organizing maps (SOM; termed MOLMAP, molecular map of atom-level properties) to handle 3-way data generated in a monitoring environmental study is presented. The study comprised 50 polycyclic aromatic hydrocarbons (PAHs) analyzed in samples derived from the weathering of six oil products (four crude oils and two fuel oils) spilled under controlled conditions for about 4 months. MOLMAP yielded useful information on each mode of the data cube: weathering samples, spilled oil products, and PAHs. Thus, the different behaviors of the six oils were ascertained, along with their particular evolution on time, and their weathering patterns were studied in terms of the original PAHs. Thus, the two heaviest products (two fuel oils) were characterized by two neurons whose more relevant weights were associated to heavy PAHs, as C(1)-fluoranthene, C(2)-fluoranthene, benzo(ghi)perylene, and dibenz(ah)anthracene. The six spilled products were projected on different regions on both the MOLMAP-SOM and a subsequent principal components analysis (PCA) scatter plot, developed using the so-called MOLMAP-scores. Besides, it was possible to further differentiate between unweathered, or slightly weathered, samples and the most weathered ones. The more relevant PAHs characterizing those samples were assessed studying the weights of the neurons in which the samples got projected.