{"title":"Phenolic Compound Removal from Olive Mill Wastewater by Sulfate Radical SR/AOP: RSM-CCD Optimization","authors":"Hamida Iboukhoulef, Abdeltif Amrane","doi":"10.1002/ceat.70085","DOIUrl":null,"url":null,"abstract":"<p>Olive mill wastewater (OMW) is rich in organic pollutants, particularly phenolic compounds (PC). Persulfate (PS)-based advanced oxidation processes have emerged as effective treatment methods. This study focused on optimizing PC removal using a catalytic Fenton-like process. A Plackett–Burman design was applied to screen key variables: PS and copper concentrations, reaction time, temperature, and initial pH. A central composite design with response surface methodology was then used to refine the process. The resulting second-order polynomial model showed excellent fit with experimental data. Under optimal conditions, a maximum PC removal efficiency of 62.09 % was achieved.</p>","PeriodicalId":10083,"journal":{"name":"Chemical Engineering & Technology","volume":"48 7","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemical Engineering & Technology","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ceat.70085","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Olive mill wastewater (OMW) is rich in organic pollutants, particularly phenolic compounds (PC). Persulfate (PS)-based advanced oxidation processes have emerged as effective treatment methods. This study focused on optimizing PC removal using a catalytic Fenton-like process. A Plackett–Burman design was applied to screen key variables: PS and copper concentrations, reaction time, temperature, and initial pH. A central composite design with response surface methodology was then used to refine the process. The resulting second-order polynomial model showed excellent fit with experimental data. Under optimal conditions, a maximum PC removal efficiency of 62.09 % was achieved.
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