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Operational parameters optimization for remediation of crude oil-polluted water in floating treatment wetlands using response surface methodology

Rehman, Khadeeja; Arslan, Muhammad; Müller, Jochen A. ORCID iD icon 1; Saeed, Muhammad; Anwar, Samina; Islam, Ejazul; Imran, Asma; Amin, Imran; Mustafa, Tanveer; Iqbal, Samina; Afzal, Muhammad
1 Institut für Biologische Grenzflächen (IBG), Karlsruher Institut für Technologie (KIT)

Abstract:

The application of floating treatment wetlands (FTWs) is an innovative nature-based solution for the remediation of polluted water. The rational improvement of water treatment via FTWs is typically based on multifactorial experiments which are labor-intensive and time-consuming. Here, we used the response surface methodology (RSM) for the optimization of FTW’s operational parameters for the remediation of water polluted by crude oil. The central composite design (CCD) of RSM was used to generate the experimental layout for testing the effect of the variables hydrocarbon, nutrient, and surfactant concentrations, aeration, and retention time on the hydrocarbon removal in 50 different FTW test systems planted with the common reed, Phragmites australis. The results from these FTW were used to formulate a mathematical model in which the computational data strongly correlated with the experimental results. The operational parameters were further optimized via modeling prediction plus experimental validation in test FTW systems. In the FTW with optimized parameters, there was a 95% attenuation of the hydrocarbon concentration, which was very close to the 98% attenuation predicted by the model. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000143852
Veröffentlicht am 18.03.2022
Originalveröffentlichung
DOI: 10.1038/s41598-022-08517-1
Scopus
Zitationen: 11
Web of Science
Zitationen: 9
Dimensions
Zitationen: 14
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Biologische Grenzflächen (IBG)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 12.2022
Sprache Englisch
Identifikator ISSN: 2045-2322
KITopen-ID: 1000143852
HGF-Programm 43.33.11 (POF IV, LK 01) Adaptive and Bioinstructive Materials Systems
Erschienen in Scientific Reports
Verlag Nature Research
Band 12
Heft 1
Seiten Article: 4566
Vorab online veröffentlicht am 16.03.2022
Nachgewiesen in Dimensions
Web of Science
Scopus
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