People | Locations | Statistics |
---|---|---|
Naji, M. |
| |
Motta, Antonella |
| |
Aletan, Dirar |
| |
Mohamed, Tarek |
| |
Ertürk, Emre |
| |
Taccardi, Nicola |
| |
Kononenko, Denys |
| |
Petrov, R. H. | Madrid |
|
Alshaaer, Mazen | Brussels |
|
Bih, L. |
| |
Casati, R. |
| |
Muller, Hermance |
| |
Kočí, Jan | Prague |
|
Šuljagić, Marija |
| |
Kalteremidou, Kalliopi-Artemi | Brussels |
|
Azam, Siraj |
| |
Ospanova, Alyiya |
| |
Blanpain, Bart |
| |
Ali, M. A. |
| |
Popa, V. |
| |
Rančić, M. |
| |
Ollier, Nadège |
| |
Azevedo, Nuno Monteiro |
| |
Landes, Michael |
| |
Rignanese, Gian-Marco |
|
Lejon, Tore
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (5/5 displayed)
- 2017The influence of sediment properties and experimental variables on the efficiency of electrodialytic removal of metals from sedimentcitations
- 2016Degradation of oil products in a soil from a Russian Barents hot-spot during electrodialytic remediationcitations
- 2015Comparison of 2-compartment, 3-compartment and stack designs for electrodialytic removal of heavy metals from harbour sedimentscitations
- 2015Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sedimentscitations
- 2015Multivariate methods for evaluating the efficiency of electrodialytic removal of heavy metals from polluted harbour sedimentscitations
Places of action
Organizations | Location | People |
---|
article
Multivariate methods for evaluating the efficiency of electrodialytic removal of heavy metals from polluted harbour sediments
Abstract
Chemometrics was used to develop a multivariate model based on 46 previously reported electrodialytic remediation experiments (EDR) of five different harbour sediments. The model predicted final concentrations of Cd, Cu, Pb and Zn as a function of current density, remediation time, stirring rate, dry/wet sediment, cell set-up as well as sediment properties. Evaluation of the model showed that remediation time and current density had the highest comparative influence on the clean-up levels. Individual models for each heavy metal showed variance in the variable importance, indicating that the targeted heavy,metals were bound to different sediment fractions. Based on the results, a PLS model was used to design five new EDR experiments of a sixth sediment to achieve specified clean-up levels of Cu and Pb. The removal efficiencies were up to 82% for Cu and 87% for Pb and the targeted clean-up levels were met in four out of five experiments. The clean-up levels were better than predicted by the model, which could hence be used for predicting an approximate remediation strategy; the modelling power will however improve with more data included. (C) 2014 Elsevier B.V. All rights reserved.