Multivariate tools to investigate the spatial contaminant distribution in a highly anthropized area (Gulf of Naples, Italy)

Abstract

The Gulf of Naples located in a high anthropized coastal area is subjected to an infrastructural intervention for the installation of a submarine power pipeline. In order to evaluate the distribution of contaminants in the seafloor sediments, a preliminary study has been conducted in the area using multivariate techniques. The statistic approach was performed to gain insights on the occurrence of organic and inorganic contaminants within the area, aiming to identify the relevant hot spots. Three geographical sub-areas influenced by different contaminant association were recognized: Torre Annunziata (TA), Capri (CA), and middle offshore (MO). TA and CA resulted marked by a severe contamination pattern due to anthropogenic pressures. In addition, the influence of the depositional basin in governing the contamination trend has been pointed out. The supervised technique PLS_DA resulted to be a powerful tool in addressing the complexity of the huge dataset acquired during the marine survey, highlighting the main trends in the variability of quality indicators, orienting thus the deeper investigations during follow-up monitoring activities.

Grain size, nutrients and heavy metals analysis to evaluate natural vs anthropogenic sources in the sea environment (Naples Bay, Eastern Tyrrhenian Sea)

“…A positive correlation of the TOC concentration versus the finest grain size fractions (clay and/or silt) is also verified, as can be inferred by the Pearson coefficients TOC vs fine grain size (clay and silt) (Table S2). The close association of the two components can be explained by (1) the capacity of the finest particles to hinder the diffusion of the oxygen into the sediments, that induce the preservation of organic matter, and (2) the adsorption of organic particles onto the charged surfaces of the clay minerals [16,11,8,15].…”

Identification of the Contamination Sources by PCBs Using Multivariate Analyses: The Case Study of the Annaba Bay (Algeria) Basin

“…HCA is a complementary technique of PCA. The combination of these statistical techniques is considered useful for obtaining information about the existing site clusters with similar pollution characteristics and for identifying the sources of contamination [48,63]. Specifically, the PCA enabled us to identify the PCBs that contribute most to the contamination of the Gulf basin.…”

Improved identification of pollution source attribution by using PAH ratios combined with multivariate statistics

“…Sixteen EPA PAHs were considered: naphthalene (Naph), anthracene (Ant), phenanthrene (Phen), acenaphthene (Ace), acenaphthylene (Acy), fluorene (Flu), fluoranthene (Flt), pyrene (Py), chrysene (Chr), benz(a)anthracene (BaA), benzo(a)pyrene (BaP), benzo(b)fluoranthene (B(b)F), benzo(k)fluoranthene (B(k)F), dibenzo(a,h)anthracene (DB(ah)A), benzo(g,h,i)perylene (B(ghi)P), and indeno(1,2,3-c,d)pyrene (IP). After specific clean-up 41 , 42 PAHs were determined by gas chromatography coupled to mass spectrometry (GC–MS) 43 . The recovery rates, validated with spiked samples, ranged from 50% to Naph to 90% for Chr.…”