Premium
A 10‐year survey of trace metals in sediments using self‐organizing maps
Author(s) -
Besada Victoria,
Quelle Cristina,
Andrade José Manuel,
Gutiérrez Noemí,
GómezCarracedo María Paz,
Schultze Fernando
Publication year - 2014
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.2615
Subject(s) - principal component analysis , trace (psycholinguistics) , matrix (chemical analysis) , cube (algebra) , heavy metals , pollution , environmental chemistry , environmental science , mineralogy , computer science , chemistry , mathematics , statistics , combinatorics , chromatography , philosophy , linguistics , ecology , biology
Self‐organizing maps (SOMs) (in particular, Matrix reOrganization Layout to Map Analytical Patterns (MOLMAP)) were used to unravel the main patterns in a three‐way dataset after a preliminary unfolding of the cube. Eleven sites of the ría of Vigo (NW of Spain) were monitored during the last decade (from 2000 to 2010) to assess pollution trends in this area. Twelve trace metals (Hg, Pb, Cd, Cu, Zn, Cr, As, Li, Fe, Al, Ni and Mn), the total organic carbon and the percentage of fine particles were measured. Results from MOLMAP, the SOM‐based approach, were compared to those of three established alternatives: parallel factor analysis, matrix‐augmented principal component analysis and generalized Procrustes rotation, the latter two employing unfolding as well. MOLMAP showed the best capabilities to differentiate groups of samples. The spatial and temporal trends, as well as the analytical variables causing them, were almost the same for all methods, which confirms MOLMAP as a simple and reliable methodology to treat three‐way environmental datasets. Copyright © 2014 John Wiley & Sons, Ltd.