Data · dataset · 2015
Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments
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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.
Description
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.
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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.
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- Repository landing page tandf.figshare.com/articles/dataset/Screening_of_variable_importance_for_optimizi… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.1332438 ↗
DOI / persistent id · from DataCite
Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
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- IsSupplementTo 10.1080/09593330.2015.1028470 doi.org/10.1080/09593330.2015.1028470 ↗
publication · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.1332438 ↗
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- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.1332438 ↗
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Topics
- Stated by source
- Biological sciences · Sociology
- From keywords
- Chemistry · Life Sciences · Social Science
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.1332438 | 14 d ago | JSON v1 |
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|---|---|---|---|
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| concepts[field].fos:biological-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:sociology | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].local:field:chemistry | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Chemistry'] |
| concepts[field].local:field:life-sciences | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Biological Sciences'] |
| concepts[field].local:field:social-science | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Sociology'] |
| created_date | source · DataCite | connector:datacite@1.0.0 | |
| description | source · DataCite | connector:datacite@1.0.0 | /data/attributes/descriptions |
| license | source · DataCite | connector:datacite@1.0.0 | /data/attributes/rightsList |
| publication_date | source · DataCite | connector:datacite@1.0.0 | /data/attributes/dates |
| title | source · DataCite | connector:datacite@1.0.0 | /data/attributes/titles/0/title |
| updated_date | source · DataCite | connector:datacite@1.0.0 |