Ozonlama ile çeşitli model tekstil boyalarından KOİ ve TOK giderimi: Box-Behnken yaklaşımı

Bu çalışmada bir ileri oksidasyon süreci olan ozonlama kullanılarak çeşitli sentetik atık sularından KOİ ve TOK giderimleri incelenmiştir. Deneylerin planlanmasında bir tür cevap yüzey metodu olan Box Behnken tasarımından (BBT) yararlanılmıştır. İşletme parametreleri olarak ozon dozu (OD, mg/L), reaksiyon süresi (RS, dk) ve başlangıç boya konsantrasyonu (BBK, mg/L) belirlenmiştir. %90’ın üzerinde KOİ ve %80’in üzerinde TOK giderimi, ozonlamanın sentetik atık suların arıtımında etkili bir süreç tipi olduğunu göstermiştir. Son olarak çoklu doğrusal olmayan regresyon (ÇDOR) ile modelleme, ilaveten optimizasyon ile validasyon çalışmaları gerçekleştirilmiştir. Türetilen ÇDOR modellerinin yanıt değişkenlerini tahmin edebilme gücü %99 olarak belirlenmiştir. 24 mg/L OD, 40 dk RS ve 10 mg/L BBK şartları BBT-optimize işletme şartları olarak belirlenmiştir. Bu şartlarda tüm sentetik atık sulardan yaklaşık %95 KOİ ve %85 TOK giderimi öngörülmüştür. Optimize şartlardaki validasyon deneylerinde elde edilen sonuçlar bu tahminsel değerleri doğrulamıştır. Tahminsel ve deneysel sonuçlar arasındaki büyük uyum BBT’nin optimizasyondaki doğruluğunu ve başarısını ortaya koymuştur.

Anahtar Kelimeler:

Tekstil boyaları, Ozonlama, CYM, Ampirik modelleme, Optimizasyon

Removal of COD and TOC from various model textile dyes by ozonation: Box-Behnken approach

In this study, the removal of COD and TOC from various synthetic effluents was investigated using ozonation as an advanced oxidation process. Box Behnken design (BBD) as a kind of response surface methodology was used in planning the experiments. Ozone dose (OD, mg/L), reaction time (RT, min), and initial dye concentration (IDC, mg/L) were determined as the operating parameters. Removal of COD over 90% and TOC over 80% showed that ozonation was an effective process type in the treatment of synthetic effluents. Finally, modeling by multiple non-linear regression (MNLR), additionally optimization and validation studies were performed. The power of the proposed MNLR models for predicting response variables was determined as 99%. OD of 24 mg/L, RS of 40 min, and IDC of 10 mg/L were determined as BBD-optimized operating conditions. Under these conditions, COD of 95% and TOC of 85% removal from all synthetic effluents were approximately predicted. The results obtained from the validation experiments that were performed at optimized condition confirmed these predicted values. Good accordance between predictive and experimental results demonstrated the accuracy and success of BBT in optimization.

Keywords:

Textile dyes, Ozonation, RSM, Empirical modeling, Optimization,

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