Reactive Black 5 Removal with Ozone on Lab-scale and Modeling

Sarı B., Güney H., Türkeş S., Keskinkan O.

OZONE : SCIENCE & ENGINEERING, cilt.45, sa.1, ss.50-64, 2022 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 45 Sayı: 1
  • Basım Tarihi: 2022
  • Dergi Adı: OZONE : SCIENCE & ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Chemical Abstracts Core, Communication Abstracts, Compendex, Environment Index, INSPEC, Metadex, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.50-64
  • Çukurova Üniversitesi Adresli: Evet

Özet

This study investigates modeling the ozone removal of the Reactive Black 5 (RB5) dye from an aqueous solution using a combination of nonlinear regression (NLR), multiple linear regression (MLR), and Intrinsically multiple linear regression (IMLR) models. Lack of use and evaluation of the IMLR method in estimating RB5 removal by ozonation attract attention. Experimental data were used in the R Core Team software for the development of the models and estimate of RB5 removal by ozone. The effects of variables such as pH, contact time, initial dye concentration, and applied ozone dosage on RB5 removal by ozone were investigated. Maximum 92% RB5 removal rate was obtained at pH 8, 60 min contact time, 100 mg/L initial RB5 concentration, and applied ozone dosage of 66 mgO3/L. Under these conditions, the amount of specific ozone consumption was 0.678 gO3/gRB5. In order to compare the models, coefficient of determination (R2) and mean square error (MSE) were utilized as reliability and precision criteria. The best R2 and MSE values for the IMLR model were calculated as 0.8940 and 0.098, respectively. To determine the appropriate model and coefficients, analysis of variance (ANOVA), and t-test were used, respectively. Whether the model is within the confidence interval was determined by the significance value (p) and the variation was <5% for the IMLR model. As a result, it was found that the best method for modeling RB5 removal from aqueous solution by ozone was the IMLR method. Detailed explanations on results were introduced in the study.