INPUT CHARACTERIZATION OF SEDIMENTARY ORGANIC CONTAMINANTS AND MOLECULAR MARKERS IN THE NORTHWESTERN MEDITERRANEAN SEA BY EXPLORATORY DATA-ANALYSIS

Citation
Jsi. Salau et al., INPUT CHARACTERIZATION OF SEDIMENTARY ORGANIC CONTAMINANTS AND MOLECULAR MARKERS IN THE NORTHWESTERN MEDITERRANEAN SEA BY EXPLORATORY DATA-ANALYSIS, Environmental science & technology, 31(12), 1997, pp. 3482-3490
Citations number
38
Categorie Soggetti
Environmental Sciences","Engineering, Environmental
ISSN journal
0013936X
Volume
31
Issue
12
Year of publication
1997
Pages
3482 - 3490
Database
ISI
SICI code
0013-936X(1997)31:12<3482:ICOSOC>2.0.ZU;2-6
Abstract
Deposition zones of the NW Mediterranean were characterized according to the source of organic pollutants (i.e., UCM, PAHs, PCBs, DDTs) and lipidic compounds (i.e., alkanes and sterols) identified in surface se diments (31 samples) by principal component analysis (PCA) and hierarc hical cluster analysis (HCA). Score plots of the two main principal co mponents showed a cluster comprising the off-shore Barcelona and Rhone prodelta samples corresponding to the most polluted samples, while th e remaining samples were clustered together. Loading plots revealed th at most of the compounds were present in the first component except be nzo[ghi]fluoranthene, the major DDT metabolites (i.e., DDE and DDD), a nd perylene, which was probably of diagenetic origin. In order to defi ne further the cluster containing the most samples, a second data base that excluded the Rhone and offshore Barcelona samples was constructe d. Score plot of the two principal components showed that three differ ent depositional environments could be clearly defined, namely the Gul f of Lions, the Ebro prodelta, and the deep sea basin. Similar cluster ing was confirmed by HCA. The loading plots enabled riverine-transport ed compounds such as n-alkanes, PCBs, DDTs, sterols, and perylene (fir st component) to be distinguished from pyrolytic PAHs (second componen t). Furthermore, in order to obtain an apportionment of the inputs rec eived to each station, a recently developed factor analysis multivaria te curve resolution (MCR) method based on the alternating least square s (ALS) positive factorization of a data matrix was carried out for th e first time on marine sediment samples. The ALS positive matrix facto rization method enabled the apportionment of the environmental source of the main components of the compounds in the area of study.