Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments

Using multivariate design and modelling, the optimal conditions for electrodialytic remediation (EDR) of heavy metals were determined for polluted harbour sediments from Hammerfest harbour located in the geographic Arctic region of Norway. The comparative importance of the variables, current density...

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Main Authors: Pedersen, Kristine B., Lejon, Tore, Ottosen, Lisbeth M., Jensen, Pernille E.
Format: Dataset
Language:unknown
Published: Taylor & Francis 2015
Subjects:
Online Access:https://dx.doi.org/10.6084/m9.figshare.1332438.v2
https://tandf.figshare.com/articles/dataset/Screening_of_variable_importance_for_optimizing_electrodialytic_remediation_of_heavy_metals_from_polluted_harbour_sediments/1332438/2
id ftdatacite:10.6084/m9.figshare.1332438.v2
record_format openpolar
spelling ftdatacite:10.6084/m9.figshare.1332438.v2 2023-05-15T15:08:39+02:00 Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments Pedersen, Kristine B. Lejon, Tore Ottosen, Lisbeth M. Jensen, Pernille E. 2015 https://dx.doi.org/10.6084/m9.figshare.1332438.v2 https://tandf.figshare.com/articles/dataset/Screening_of_variable_importance_for_optimizing_electrodialytic_remediation_of_heavy_metals_from_polluted_harbour_sediments/1332438/2 unknown Taylor & Francis https://dx.doi.org/10.1080/09593330.2015.1028470 https://dx.doi.org/10.6084/m9.figshare.1332438 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY Biological Sciences Sociology FOS Sociology Ecology FOS Biological sciences Chemistry Earth and Environmental Sciences Cell Biology dataset Dataset 2015 ftdatacite https://doi.org/10.6084/m9.figshare.1332438.v2 https://doi.org/10.1080/09593330.2015.1028470 https://doi.org/10.6084/m9.figshare.1332438 2021-11-05T12:55:41Z Using multivariate design and modelling, the optimal conditions for electrodialytic remediation (EDR) of heavy metals were determined for polluted harbour sediments from Hammerfest harbour located in the geographic Arctic region of Norway. The comparative importance of the variables, current density, remediation time, light/no light, the liquid–solid ratio and stirring rate of the sediment suspension, was determined in 15 laboratory-scale EDR experiments by projection to latent structures (PLS). The relation between the X matrix (experimental variables) and the Y matrix (removal efficiencies) was computed and variable importance in the projection was used to assess the influence of the experimental variables. Current density and remediation time proved to have the highest influence on the remediation of the heavy metals Cr, Cu, Ni, Pb and Zn in the studied experimental domain. In addition, it was shown that excluding the acidification time improved the PLS model, indicating the importance of applying a limited experimental domain that covers the removal phases of each heavy metal in the specific sediment. Based on PLS modelling, the optimal conditions for remediating the Hammerfest sediment were determined; operating in the experimental domain of 0.5–0.8 mA/cm 2 and a remediation time after acidification of 450–570 h met acceptable levels according to Norwegian sediment quality guidelines. Dataset Arctic Hammerfest DataCite Metadata Store (German National Library of Science and Technology) Arctic Norway The ''Y'' ENVELOPE(-112.453,-112.453,57.591,57.591)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Biological Sciences
Sociology
FOS Sociology
Ecology
FOS Biological sciences
Chemistry
Earth and Environmental Sciences
Cell Biology
spellingShingle Biological Sciences
Sociology
FOS Sociology
Ecology
FOS Biological sciences
Chemistry
Earth and Environmental Sciences
Cell Biology
Pedersen, Kristine B.
Lejon, Tore
Ottosen, Lisbeth M.
Jensen, Pernille E.
Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments
topic_facet Biological Sciences
Sociology
FOS Sociology
Ecology
FOS Biological sciences
Chemistry
Earth and Environmental Sciences
Cell Biology
description Using multivariate design and modelling, the optimal conditions for electrodialytic remediation (EDR) of heavy metals were determined for polluted harbour sediments from Hammerfest harbour located in the geographic Arctic region of Norway. The comparative importance of the variables, current density, remediation time, light/no light, the liquid–solid ratio and stirring rate of the sediment suspension, was determined in 15 laboratory-scale EDR experiments by projection to latent structures (PLS). The relation between the X matrix (experimental variables) and the Y matrix (removal efficiencies) was computed and variable importance in the projection was used to assess the influence of the experimental variables. Current density and remediation time proved to have the highest influence on the remediation of the heavy metals Cr, Cu, Ni, Pb and Zn in the studied experimental domain. In addition, it was shown that excluding the acidification time improved the PLS model, indicating the importance of applying a limited experimental domain that covers the removal phases of each heavy metal in the specific sediment. Based on PLS modelling, the optimal conditions for remediating the Hammerfest sediment were determined; operating in the experimental domain of 0.5–0.8 mA/cm 2 and a remediation time after acidification of 450–570 h met acceptable levels according to Norwegian sediment quality guidelines.
format Dataset
author Pedersen, Kristine B.
Lejon, Tore
Ottosen, Lisbeth M.
Jensen, Pernille E.
author_facet Pedersen, Kristine B.
Lejon, Tore
Ottosen, Lisbeth M.
Jensen, Pernille E.
author_sort Pedersen, Kristine B.
title Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments
title_short Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments
title_full Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments
title_fullStr Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments
title_full_unstemmed Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments
title_sort screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments
publisher Taylor & Francis
publishDate 2015
url https://dx.doi.org/10.6084/m9.figshare.1332438.v2
https://tandf.figshare.com/articles/dataset/Screening_of_variable_importance_for_optimizing_electrodialytic_remediation_of_heavy_metals_from_polluted_harbour_sediments/1332438/2
long_lat ENVELOPE(-112.453,-112.453,57.591,57.591)
geographic Arctic
Norway
The ''Y''
geographic_facet Arctic
Norway
The ''Y''
genre Arctic
Hammerfest
genre_facet Arctic
Hammerfest
op_relation https://dx.doi.org/10.1080/09593330.2015.1028470
https://dx.doi.org/10.6084/m9.figshare.1332438
op_rights Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.6084/m9.figshare.1332438.v2
https://doi.org/10.1080/09593330.2015.1028470
https://doi.org/10.6084/m9.figshare.1332438
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