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

Year 2024, Volume: 26 Issue: 1, 41 - 52, 19.01.2024
https://doi.org/10.25092/baunfbed.1328496

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.

References

  • İbiş, M., Bir Yonga levha fabrikasında ham madde kaynaklarının optimizasyonu ve üretim koşullarının teknolojik yönden incelenmesi, Yüksek Lisans Tezi, Düzce Üniversitesi, Fen Bilimleri Enstitüsü, Düzce, (2018).
  • Göktaş O., Alma, H., Erdil, Z.Y., Günsel U., Özen, E. ve Dican, Ö., Ege bölgesi bağ budama artıklarının yonga levha endüstrisinde değerlendirilmesi, TÜBİTAK TOVAG Proje, Ankara, (2008).
  • Ozmetin, E., Süt endüstrisi atıksularının kimyasal arıtımının yanıt yüzey yöntemi ile optimizasyonu, Journal of the Institute of Science and Technology, 9, 4, 1968–1976, (2019).
  • Wang, J.P., Chen, Y.Z., Ge, X.W. and Yu, H.Q., Optimization of coagulation–flocculation process for a paper-recycling wastewater treatment using response surface methodology, Colloids and Surfaces A: Physicochemical and Engineering Aspects, 302, 1, 204–210, (2007 )
  • Singh, B. and Kumar, P., Pre-treatment of petroleum refinery wastewater by coagulation and flocculation using mixed coagulant: Optimization of process parameters using response surface methodology (RSM), Journal of Water Process Engineering, 36, 101317, 1-17, (2020).
  • Kamali, M. and Khodaparast, Z., Review on recent developments on pulp and paper mill wastewater treatment, Ecotoxicology and Environmental Safety, 114, 326–342, (2015).
  • El-taweel, R.M., Mohamed, N., Alrefaey, K.A., Husien, H., Aziz, A.B., Salim A.I., Mostafa, N,G., Said, L,A., Fahim, I.S. and Radwan, A.G., A review of coagulation explaining its definition, mechanism, coagulant types, and optimization models; RSM, and ANN, Current Research Green Sustainable Chemistry, 6, 100358, 1-23, (2023).
  • Igwegbe, C.A., Ighalo, J.O., Iwuozor, K.O., Onukwuli, O.D., Okoye, P.U. and Al-Rawajfeh, A.E., Prediction and optimisation of coagulation-flocculation process for turbidity removal from aquaculture effluent using Garcinia kola extract: Response surface and artificial neural network methods, Cleaner Chemical Engineering, 4, 100076, 1-11, (2022).
  • Gaayda, J.E., Rachid, Y., Titchou, F.E., Barra, I., Hsini, A., Yap, P.S., Oh, W.D., Swanson, C., Hamdani, M. and Akbour, R.A., Optimizing removal of chromium (VI) ions from water by coagulation process using central composite design: Effectiveness of grape seed as a green coagulant, Seperation and Purification Technology, 307, 122805, 1-15, (2023).
  • Korkmaz, M., Özmetin, E., Süzen, Y., Çalgan, E. ve Özmetin, C., A new adsorbent (aluminum modified talc) for phosphate removal from alkaline solutions and optimization of data by central composite design, Desalination Water Treatment, 245, 178–190, (2022).
  • Myers, R.H., Montgomery, D.C., Vining, G.G., Borror, C.M. and Kowalski, S.M., Response Surface Methodology: A Retrospective and Literature Survey, Journal of Quality Technology, 36, 1, 53–77, (2004).
  • Süzen, Y. and Ozmetin, C., Removal of reactive black 5 dye using fenton oxidation from aqueous solutions and optimization of response surface methodology, Desalination Water Treatment, 172, 106–114, (2019).
  • Baş, D. and Boyacı, İ.H., Modeling and optimization I: Usability of response surface methodology, Journal of Food Engineering, 78, 3, 836–845, (2007).
  • Karaoğlan, A.D., Demir, M.M. and Çarkacı, M.M., Minimization of pres time at particleboard production, Pamukkale University Journal Engineering Science, 24, 4, 658–664, (2018).
  • Volkan, N. ve Ozmetin, E., Maxilon Blue GRL boyar maddesinin illit kil minerali ile gideriminin optimizasyonu, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 10, 1, 216–232, (2022).
  • Márquez-Montes, R.A., Orozco-Mena, R.E., Camacho-Dávila, A.A., Pérez-Vega, S., Collins-Martínez, V.H. and Ramos-Sánchez, V.H., Optimization of the electrooxidation of aqueous ammonium sulfite for hydrogen production at near-neutral pH using response surface methodology, International Journal of Hydrogen Energy, 45, 27, 13821–13831, (2020).
  • Arslan Alaton, I., Tureli, G. and Olmez Hanci, T., Treatment of azo dye production wastewaters using Photo-Fenton-like advanced oxidation processes: Optimization by response surface methodology, Journal of Photochemistry and Photobiolgy A: Chemistry, 202, 2–3, 142–153, (2009).
  • Özmetin, E., Yaşar, Y. ve Karaoğlan, A.D., Pirinç kabuğu ile metilen mavisi gideriminin optimizasyonu, III. Fiziksel Kimya Günleri, Balıkesir, (2012).
  • Katip, A., Pestisit endüstrisi atıksularının koagülasyon/flokülasyon prosesi ile geri kazanımının değerlendirilmesi, Doğal Afetler ve Çevre Dergisi, 90, 224, 94–100, (2018).
  • WEF, A.A., Standard methods for the examination of water and wastewater, 19th Edition, Washington DC., (1995).
  • Bashir, M.J.K., Aziz, H.A., Yusoff, M.S. and Adlan, M.N., Application of response surface methodology (RSM) for optimization of ammoniacal nitrogen removal from semi-aerobic landfill leachate using ion exchange resin, Desalination, 254, 1, 154–161, (2010).
  • Beyan, S.M., Prabhu, S.V., Sissay, T.T. and Getahun, A.A., Sugarcane bagasse based activated carbon preparation and its adsorption efficacy on removal of BOD and COD from textile effluents: RSM based modeling, optimization and kinetic aspects, Bioresource Technology Reports, 14, 100664, (2021).
  • Arami-Niya, A., Wan Daud, W.M.A., Mjalli, F.S., Abnisa, F. and Shafeeyan, M.S., Production of microporous palm shell based activated carbon for methane adsorption: Modeling and optimization using response surface methodology, Chemical Engineering Research and Design, 90, 6, 776–784, (2012).
  • Ghafari, S., Aziz, H.A. and Bashir, M.J.K., The use of poly-aluminum chloride and alum for the treatment of partially stabilized leachate: A comparative study, Desalination, 257, 1, 110–116, (2010).

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

Year 2024, Volume: 26 Issue: 1, 41 - 52, 19.01.2024
https://doi.org/10.25092/baunfbed.1328496

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.

References

  • İbiş, M., Bir Yonga levha fabrikasında ham madde kaynaklarının optimizasyonu ve üretim koşullarının teknolojik yönden incelenmesi, Yüksek Lisans Tezi, Düzce Üniversitesi, Fen Bilimleri Enstitüsü, Düzce, (2018).
  • Göktaş O., Alma, H., Erdil, Z.Y., Günsel U., Özen, E. ve Dican, Ö., Ege bölgesi bağ budama artıklarının yonga levha endüstrisinde değerlendirilmesi, TÜBİTAK TOVAG Proje, Ankara, (2008).
  • Ozmetin, E., Süt endüstrisi atıksularının kimyasal arıtımının yanıt yüzey yöntemi ile optimizasyonu, Journal of the Institute of Science and Technology, 9, 4, 1968–1976, (2019).
  • Wang, J.P., Chen, Y.Z., Ge, X.W. and Yu, H.Q., Optimization of coagulation–flocculation process for a paper-recycling wastewater treatment using response surface methodology, Colloids and Surfaces A: Physicochemical and Engineering Aspects, 302, 1, 204–210, (2007 )
  • Singh, B. and Kumar, P., Pre-treatment of petroleum refinery wastewater by coagulation and flocculation using mixed coagulant: Optimization of process parameters using response surface methodology (RSM), Journal of Water Process Engineering, 36, 101317, 1-17, (2020).
  • Kamali, M. and Khodaparast, Z., Review on recent developments on pulp and paper mill wastewater treatment, Ecotoxicology and Environmental Safety, 114, 326–342, (2015).
  • El-taweel, R.M., Mohamed, N., Alrefaey, K.A., Husien, H., Aziz, A.B., Salim A.I., Mostafa, N,G., Said, L,A., Fahim, I.S. and Radwan, A.G., A review of coagulation explaining its definition, mechanism, coagulant types, and optimization models; RSM, and ANN, Current Research Green Sustainable Chemistry, 6, 100358, 1-23, (2023).
  • Igwegbe, C.A., Ighalo, J.O., Iwuozor, K.O., Onukwuli, O.D., Okoye, P.U. and Al-Rawajfeh, A.E., Prediction and optimisation of coagulation-flocculation process for turbidity removal from aquaculture effluent using Garcinia kola extract: Response surface and artificial neural network methods, Cleaner Chemical Engineering, 4, 100076, 1-11, (2022).
  • Gaayda, J.E., Rachid, Y., Titchou, F.E., Barra, I., Hsini, A., Yap, P.S., Oh, W.D., Swanson, C., Hamdani, M. and Akbour, R.A., Optimizing removal of chromium (VI) ions from water by coagulation process using central composite design: Effectiveness of grape seed as a green coagulant, Seperation and Purification Technology, 307, 122805, 1-15, (2023).
  • Korkmaz, M., Özmetin, E., Süzen, Y., Çalgan, E. ve Özmetin, C., A new adsorbent (aluminum modified talc) for phosphate removal from alkaline solutions and optimization of data by central composite design, Desalination Water Treatment, 245, 178–190, (2022).
  • Myers, R.H., Montgomery, D.C., Vining, G.G., Borror, C.M. and Kowalski, S.M., Response Surface Methodology: A Retrospective and Literature Survey, Journal of Quality Technology, 36, 1, 53–77, (2004).
  • Süzen, Y. and Ozmetin, C., Removal of reactive black 5 dye using fenton oxidation from aqueous solutions and optimization of response surface methodology, Desalination Water Treatment, 172, 106–114, (2019).
  • Baş, D. and Boyacı, İ.H., Modeling and optimization I: Usability of response surface methodology, Journal of Food Engineering, 78, 3, 836–845, (2007).
  • Karaoğlan, A.D., Demir, M.M. and Çarkacı, M.M., Minimization of pres time at particleboard production, Pamukkale University Journal Engineering Science, 24, 4, 658–664, (2018).
  • Volkan, N. ve Ozmetin, E., Maxilon Blue GRL boyar maddesinin illit kil minerali ile gideriminin optimizasyonu, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 10, 1, 216–232, (2022).
  • Márquez-Montes, R.A., Orozco-Mena, R.E., Camacho-Dávila, A.A., Pérez-Vega, S., Collins-Martínez, V.H. and Ramos-Sánchez, V.H., Optimization of the electrooxidation of aqueous ammonium sulfite for hydrogen production at near-neutral pH using response surface methodology, International Journal of Hydrogen Energy, 45, 27, 13821–13831, (2020).
  • Arslan Alaton, I., Tureli, G. and Olmez Hanci, T., Treatment of azo dye production wastewaters using Photo-Fenton-like advanced oxidation processes: Optimization by response surface methodology, Journal of Photochemistry and Photobiolgy A: Chemistry, 202, 2–3, 142–153, (2009).
  • Özmetin, E., Yaşar, Y. ve Karaoğlan, A.D., Pirinç kabuğu ile metilen mavisi gideriminin optimizasyonu, III. Fiziksel Kimya Günleri, Balıkesir, (2012).
  • Katip, A., Pestisit endüstrisi atıksularının koagülasyon/flokülasyon prosesi ile geri kazanımının değerlendirilmesi, Doğal Afetler ve Çevre Dergisi, 90, 224, 94–100, (2018).
  • WEF, A.A., Standard methods for the examination of water and wastewater, 19th Edition, Washington DC., (1995).
  • Bashir, M.J.K., Aziz, H.A., Yusoff, M.S. and Adlan, M.N., Application of response surface methodology (RSM) for optimization of ammoniacal nitrogen removal from semi-aerobic landfill leachate using ion exchange resin, Desalination, 254, 1, 154–161, (2010).
  • Beyan, S.M., Prabhu, S.V., Sissay, T.T. and Getahun, A.A., Sugarcane bagasse based activated carbon preparation and its adsorption efficacy on removal of BOD and COD from textile effluents: RSM based modeling, optimization and kinetic aspects, Bioresource Technology Reports, 14, 100664, (2021).
  • Arami-Niya, A., Wan Daud, W.M.A., Mjalli, F.S., Abnisa, F. and Shafeeyan, M.S., Production of microporous palm shell based activated carbon for methane adsorption: Modeling and optimization using response surface methodology, Chemical Engineering Research and Design, 90, 6, 776–784, (2012).
  • Ghafari, S., Aziz, H.A. and Bashir, M.J.K., The use of poly-aluminum chloride and alum for the treatment of partially stabilized leachate: A comparative study, Desalination, 257, 1, 110–116, (2010).
There are 24 citations in total.

Details

Primary Language Turkish
Subjects Environmental Engineering (Other)
Journal Section Research Articles
Authors

Yeliz Süzen 0000-0003-4059-4643

Ahmet Günay 0000-0001-9499-9932

Early Pub Date January 6, 2024
Publication Date January 19, 2024
Submission Date July 17, 2023
Published in Issue Year 2024 Volume: 26 Issue: 1

Cite

APA Süzen, Y., & Günay, A. (2024). Yonga levha endüstrisi atık sularının kimyasal ön arıtımı ve yanıt yüzey yöntemi ile optimizasyonu. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 26(1), 41-52. https://doi.org/10.25092/baunfbed.1328496
AMA Süzen Y, Günay A. Yonga levha endüstrisi atık sularının kimyasal ön arıtımı ve yanıt yüzey yöntemi ile optimizasyonu. BAUN Fen. Bil. Enst. Dergisi. January 2024;26(1):41-52. doi:10.25092/baunfbed.1328496
Chicago Süzen, Yeliz, and Ahmet Günay. “Yonga Levha endüstrisi atık sularının Kimyasal ön arıtımı Ve yanıt yüzey yöntemi Ile Optimizasyonu”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 26, no. 1 (January 2024): 41-52. https://doi.org/10.25092/baunfbed.1328496.
EndNote Süzen Y, Günay A (January 1, 2024) Yonga levha endüstrisi atık sularının kimyasal ön arıtımı ve yanıt yüzey yöntemi ile optimizasyonu. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 26 1 41–52.
IEEE Y. Süzen and A. Günay, “Yonga levha endüstrisi atık sularının kimyasal ön arıtımı ve yanıt yüzey yöntemi ile optimizasyonu”, BAUN Fen. Bil. Enst. Dergisi, vol. 26, no. 1, pp. 41–52, 2024, doi: 10.25092/baunfbed.1328496.
ISNAD Süzen, Yeliz - Günay, Ahmet. “Yonga Levha endüstrisi atık sularının Kimyasal ön arıtımı Ve yanıt yüzey yöntemi Ile Optimizasyonu”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 26/1 (January 2024), 41-52. https://doi.org/10.25092/baunfbed.1328496.
JAMA Süzen Y, Günay A. Yonga levha endüstrisi atık sularının kimyasal ön arıtımı ve yanıt yüzey yöntemi ile optimizasyonu. BAUN Fen. Bil. Enst. Dergisi. 2024;26:41–52.
MLA Süzen, Yeliz and Ahmet Günay. “Yonga Levha endüstrisi atık sularının Kimyasal ön arıtımı Ve yanıt yüzey yöntemi Ile Optimizasyonu”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 26, no. 1, 2024, pp. 41-52, doi:10.25092/baunfbed.1328496.
Vancouver Süzen Y, Günay A. Yonga levha endüstrisi atık sularının kimyasal ön arıtımı ve yanıt yüzey yöntemi ile optimizasyonu. BAUN Fen. Bil. Enst. Dergisi. 2024;26(1):41-52.