Modeling and optimizing the removal of cadmium by

Artificial Neural Networks Response Surface Methodology (RSM) modeling phytoremediation sewage sludge

Journal

International journal of phytoremediation
ISSN: 1549-7879
Titre abrégé: Int J Phytoremediation
Pays: United States
ID NLM: 101136878

Informations de publication

Date de publication:
2020
Historique:
pubmed: 30 5 2020
medline: 24 9 2020
entrez: 30 5 2020
Statut: ppublish

Résumé

The study was aimed to model and optimize the removal of cadmium from contaminated post-industrial soil via

Identifiants

pubmed: 32466658
doi: 10.1080/15226514.2020.1768513
doi:

Substances chimiques

Sewage 0
Soil 0
Soil Pollutants 0
Cadmium 00BH33GNGH

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1321-1330

Auteurs

Marta Jaskulak (M)

Faculty of Infrastructure and Environment, Institute of Environmental Engineering, Czestochowa University of Technology, Czestochowa, Poland.
Laboratory of Civil Engineering and Environment (LGCgE), Environmental Axis, University of Lille, Lille, France.

Anna Grobelak (A)

Faculty of Infrastructure and Environment, Institute of Environmental Engineering, Czestochowa University of Technology, Czestochowa, Poland.

Franck Vandenbulcke (F)

Laboratory of Civil Engineering and Environment (LGCgE), Environmental Axis, University of Lille, Lille, France.

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Classifications MeSH