NDLI: Cyclic influences on the heavy metal chronology in a Central Mediterranean area (Palermo Gulf, Italy)

Content Provider	Springer Nature Link
Author	Basile, Salvatore Brai, Maria Rizzo, Salvatore Spanò, Marco Tranchina, Luigi
Copyright Year	2010
Abstract	The evaluation of long-term heavy metal concentrations in the Gulf of Palermo (Italy) has been carried out in order to investigate how changes of pollution levels in the last 50 years can be reflected in marine sediments. Measurements of Cr, Cu, Hg, Pb, and Zn concentrations were performed on dated fractions of a sediment core. Time series analysis has allowed to obtain information on the chronology of the heavy metal pollution of the area and to identify seasonal components and trends.Heavy metal concentrations in the <63 μm fraction of core sections were obtained by Atomic Absorption Spectrophotometry, after wet sieving, drying, and digestion procedures. Dating of sediment core had been previously achieved by excess $^{210}$Pb method. A methodological approach based on the time series analysis was used in order to investigate the presence of heavy metal cyclic variations and to outline the trend of each pollutant. A spectral analysis was performed on concentration data to investigate the presence of seasonal components. The additive component model, widely used to estimate seasonal and long-term behavior, was chosen for the time series analysis. R statistical software and advanced toolkits have been used.Sediment core has been found to provide information for years from 1959 to 2004. Time series analysis results showed the presence of statistically significant cycles, of about 10.3, 7.2, and 4.8 years. Seasonal components of heavy metals concentrations and well known cycles have been compared. In particular, correlations with seasonal components of Sun Spot Number Cycle, Multivariate ENSO Index, and Winter North Atlantic Oscillation Index have been investigated. Moreover, the presence of trends in heavy metal concentration data has been highlighted.Time series analysis on the concentrations of heavy metals from a dated sediment core sampled in the Palermo Gulf (Italy) has been carried out. Cyclical pattern over a time of about 50 years have been identified thanks to spectral analysis. Statistically significant cycles have been detected, showing how metal concentrations in sediments also depend on natural cycles. Seasonal and trend components have been extracted, through time series decomposition by the LOESS procedures. Seasonal components of our data and of natural cycles show a good agreement in terms of series correlations. Sediment core, on a local scale and with good reliability, records the dynamics of heavy metal pollution of the area, also allowing comparisons on a much larger scale.
Starting Page	174
Ending Page	184
Page Count	11
File Format	PDF
ISSN	14390108
Journal	Journal of Soils and Sediments
Volume Number	11
Issue Number	1
e-ISSN	16147480
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-11-10
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Heavy metals emissions Heavy metals trends Marine environment Mediterranean area Time-series analysis Environmental Physics Environment Soil Science & Conservation
Content Type	Text
Resource Type	Article
Subject	Stratigraphy Earth-Surface Processes

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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