Yonga levha endüstrisi atık sularının kimyasal ön arıtımı ve yanıt yüzey yöntemi ile optimizasyonu

Abstract

Bu çalışmada yonga levha atık suyunun koagülasyon/flokülasyon yöntemiyle kimyasal ön arıtılabilirliği incelenmiştir. Çalışmada kullanılan parametreler ve seviyeleri Yanıt Yüzey Yöntemi (YYY) kullanılarak tasarlanmış ve sonuçlar optimize edilerek model denklemleri türetilmiştir. Çalışma kapsamında; koagülant olarak Flo30, flokülant olarak ise anyonik patates nişastası (APN, %1) kullanılmıştır. Bağımsız değişkenler olarak; başlangıç pH’sı (5-8), Flo30 koagülant dozu (6-12 ml/L), APN dozu (10-30 ml/L); bağımlı değişkenler olarak kimyasal oksijen ihtiyacı (KOİ,%), askıda katı madde (AKM,%) ve renk giderim verimleri (%) seçilmiştir. Her bir bağımlı değişkenin giderimini maksimum yapan şartlar ayrı ayrı belirlenmiş ve bu şartlarda doğrulama deneyleri yapılmıştır. Maksimum giderim şartlarında KOİ, AKM ve renk giderim verimleri sırasıyla; %56,83, %96,46, %83,2 olarak bulunmuştur. Elde edilen modellerin R2 değerleri ise sırası ile 0,9501, 0,9666 ve 0,9377 olmuştur. Yonga levha atık sularının ön arıtımında kimyasal arıtımın etkili bir metot olduğu belirlenmiştir.

Keywords

• Yonga levha atık suyu
• koagülasyon
• flokülasyon
• optimizasyon

Chemical pretreatment of particle board industry wastewater and optimization by response surface method

Abstract

In this study, the chemical pre-treatment of particle board waste water by coagulation/flocculation method was investigated. The parameters and levels used in the study were designed using the Response Surface Method (RSM), and the model equations were derived by optimizing the results. In the scope of the study; Flo30 was used as coagulant and anionic potato starch (APN, 1%) was used as flocculant. As independent variables; initial pH (5-8), Flo30 coagulant dose (6-12 ml/L), APN dose (10-30 ml/L); Chemical oxygen demand (COD,%), total suspended solids (TSS,%) and color removal efficiencies (%) were chosen as dependent variables. The conditions that maximize the removal of each dependent variable were determined separately and validation experiments were carried out under these conditions. Under maximum removal conditions, the COD, TSS and color removal efficiencies are respectively; It was found as 56.83%, 96.46%, 83.2%. The R2 values of the models obtained were 0.9501, 0.9666 and 0.9377, respectively. It has been determined that chemical treatment is an effective method in the pre-treatment of particleboard wastewater.

Keywords

• Particleboard wastewater
• coagulation
• flocculation
• optimization.

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