Evidence map›Paper›PMID 35397022›Full record

ArticleEnvironmental science and pollution research international2022

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

Matilda Mali, Antonella Di Leo, Santina Giandomenico, Lucia Spada, Nicola Cardellicchio, Maria Calò, Alessandra Fedele, Luciana Ferraro, Alfonsa Milia, Monia Renzi and 4 more

Abstract read
In one paragraph

Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Matilda MaliDICATECh, Politecnico Di Bari, via Orabona, 4 I-70125, Bari, Italy. matilda.mali@poliba.it.ORCID http://orcid.org/0000-0002-2523-2807
Antonella Di LeoWater Research Institute, National Research Council, Taranto, Italy.
Santina GiandomenicoWater Research Institute, National Research Council, Taranto, Italy.
Lucia SpadaWater Research Institute, National Research Council, Taranto, Italy.
Nicola CardellicchioWater Research Institute, National Research Council, Taranto, Italy.
Maria CalòWater Research Institute, National Research Council, Taranto, Italy.
Alessandra FedeleWater Research Institute, National Research Council, Taranto, Italy.
Luciana FerraroInstitute of Marine Sciences, National Research Council, Naples, Italy.
Alfonsa MiliaInstitute of Marine Sciences, National Research Council, Naples, Italy.
Monia RenziDepartment of Life Science, L. Giorgieri, 10, 34127, Trieste, Italy.
Francesca MassaraTerna S.P.A. - Rete Elettrica Nazionale Roma - Viale Egidio Galbani, 70, Roma, Italy.
Tommaso GranataCESI S.P.a. - Centro Elettronico Sperimentale Italiano, Milano, Italy.
Letizia MoruzziCESI S.P.a. - Centro Elettronico Sperimentale Italiano, Milano, Italy.
Francesco Paolo BuonocuntoInstitute of Marine Sciences, National Research Council, Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Geologic SedimentsWater Pollutants, ChemicalEcosystemEnvironmental MonitoringItalyWater Pollutants, ChemicalComplex datasetContaminationGulf of NaplesHazard degreeMarine sedimentsMultivariate analyses

Identifiers

PMID35397022
PMCPMC9464125

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.