Decolorization enhancement of basic fuchsin by UV/H2O2 process: optimization and modeling using Box Behnken design.

IF 1.9 4区 环境科学与生态学 Q4 ENGINEERING, ENVIRONMENTAL
Nawel El Hanafi, Aida Zaabar, Farid Aoudjit, Hakim Lounici
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引用次数: 0

Abstract

The present work deals with the optimization of basic fuchsin dye removal from an aqueous solution using the ultraviolet UV/H2O2 process. Response Surface Modeling (RSM) based on Box-Behnken experimental design (BBD) was applied as a tool for the optimization of operating conditions such as initial dye concentration (10-50 ppm), hydrogen peroxide dosage (H2O2) (10-20 mM/L) and irradiation time (60-180 min), at pH = 7.4 under ultra-violet irradiation (254 nm and 25 W intensity). Chemical oxygen demand (COD abatement) was used as a response variable. The Box-Behnken Design can be employed to develop a mathematical model for predicting UV/H2O2 performance for COD abatement. COD abatement is sensitive to the concentration of hydrogen peroxide and irradiation time. Statistical analyses indicate a high correlation between observed and predicted values (R2 > 0.98). In the BBD predictions, the optimal conditions in the UV/H2O2 process for removing 99.3% of COD were found to be low levels of pollutant concentration (10 ppm), a high concentration of hydrogen peroxide dosage (20 mM/L), and an irradiation time of 80 min.

紫外线/H2O2 工艺对碱性品红的脱色增效:利用盒式贝肯设计进行优化和建模。
本研究涉及利用紫外线 UV/H2O2 工艺从水溶液中去除碱性染料的优化问题。在紫外线照射(254 纳米和 25 瓦强度)下,pH=7.4 条件下,应用基于方框-贝肯实验设计(BBD)的响应面建模(RSM)作为优化操作条件的工具,如初始染料浓度(10-50 ppm)、过氧化氢用量(H2O2)(10-20 mM/L)和照射时间(60-180 分钟)。化学需氧量(COD 减量)被用作响应变量。方框-贝肯设计(Box-Behnken Design)可用于建立一个数学模型,以预测紫外线/二氧化氢去除 COD 的性能。COD 消减量对过氧化氢浓度和辐照时间很敏感。统计分析表明,观测值和预测值之间具有很高的相关性(R2 > 0.98)。在 BBD 预测中,发现紫外线/H2O2 工艺去除 99.3% COD 的最佳条件是污染物浓度低(10 ppm)、过氧化氢用量浓度高(20 mM/L)和辐照时间为 80 分钟。
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来源期刊
CiteScore
4.10
自引率
4.80%
发文量
93
审稿时长
3.0 months
期刊介绍: 14 issues per year Abstracted/indexed in: BioSciences Information Service of Biological Abstracts (BIOSIS), CAB ABSTRACTS, CEABA, Chemical Abstracts & Chemical Safety NewsBase, Current Contents/Agriculture, Biology, and Environmental Sciences, Elsevier BIOBASE/Current Awareness in Biological Sciences, EMBASE/Excerpta Medica, Engineering Index/COMPENDEX PLUS, Environment Abstracts, Environmental Periodicals Bibliography & INIST-Pascal/CNRS, National Agriculture Library-AGRICOLA, NIOSHTIC & Pollution Abstracts, PubSCIENCE, Reference Update, Research Alert & Science Citation Index Expanded (SCIE), Water Resources Abstracts and Index Medicus/MEDLINE.
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