Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/42283
Title: Analysis of Ni, Cr, Cu, Pb and Cd in marine bioindicators using mixed-micelles with microwave assisted micellar extraction and GF-AAS
Authors: Hernández-Martínez, A. M.
Padrón-Sanz, C.
Torres-Padrón, M. E. 
Sosa-Ferrera Z. 
Santana-Rodríguez, J. J. 
UNESCO Clasification: 251002 Oceanografía química
Keywords: Cloud-Point Extraction
Atomic-Absorption-Spectrometry
Icp-Ms Determination
Heavy-Metals
Mytilus-Galloprovincialis, et al
Issue Date: 2016
Journal: Analytical Methods 
Abstract: A new method has been developed for the extraction and determination of the heavy metals Ni, Cu, Cr, Pb, and Cd in mussels (Mytilus galloprovincialis) and polychaetes (Nereis diversicolor), using biodegradable mixed-micelles (SDS and Triton X-100) as the extractant, and GF-AAS analysis. This method proves to be effective in the extraction of metals from this type of matrix by employing only mixed-micelles as the extractant, without the addition of chelating agents or any other reagents to enhance the efficiency of the method. The proposed method has shown satisfactory recovery percentages for all the metals under study in both cases: 83-110% for Mytilus galloprovincialis and 72-106% for Nereis diversicolor, good linearity and reproducibility (with RSDs lower than 4.6% and 3.24%, respectively), as well as detection limits ranging from 0.02 to 0.05 μg g-1 for Mytilus galloprovincialis and from 0.003 to 0.04 μg g-1 for Nereis diversicolor. The results obtained for the optimized method were compared with those obtained using MAE/GF-AAS (ISO 11047:1998) analysis. This method has been applied to the Certified Reference Material ERM-CE 278K, as well as to other species of bivalves (Donax trunculus and Cerastoderma edule) and polychaetes (Lumbrineris latreilli and Marphysa sanguinea), with satisfactory results.
URI: http://hdl.handle.net/10553/42283
ISSN: 1759-9660
DOI: 10.1039/c6ay01913g
Source: Analytical Methods [ISSN 1759-9660], v. 8 (39), p. 7141-7149
URL: https://api.elsevier.com/content/abstract/scopus_id/84991071489
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