İçme suyu arıtma tesisi atık çamuru üzerine metilen mavisi adsorpsiyonu ve yapay sinir ağları ile modellenmesi
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Date
2020-08-11
Authors
Öztürk, Nurcan
Şentürk, Hasan Basri
Gündoğdu, Ali
Duran, Celal
Journal Title
Journal ISSN
Volume Title
Publisher
Bursa Uludağ Üniversitesi
Abstract
Bu çalışmada içme suyu arıtma tesislerinde arıtım aşamaları sonucu oluşan İçme Suyu Arıtma Tesisi Atık Çamurunun (İSATAÇ), atık sularda organik kökenli bir kirletici (boyar madde) olan Metilen Mavisinin uzaklaştırılmasında adsorban olarak kullanılabilirliği araştırılmıştır. Adsorpsiyon çalışmalarında kullanılan İSATAÇ fiziksel ya da kimyasal ön işleme tabi tutulmamıştır. Öncelikle İSATAÇ’ın nem, yoğunluk, uçucu madde, sabit karbon, kül tayini yanı sıra elementel, SEM, FT-IR, XRD, XRF ve TGA/DTA analiz gibi çeşitli analitik işlemlerle karakterize edilmiştir. Sonrasında adsorpsiyon deneyleri kesikli sistemle gerçekleştirilmiş ve İSATAÇ’ın sulu çözeltiden bu kirletici türü uzaklaştırma potansiyeli denge, kinetik ve termodinamik parametreler açısından incelenmiştir. Metilen mavisinin uzaklaştırılmasında Langmuir izoterm modelinden elde edilen maksimum adsorplama kapasitesi 62,50 mg g-1 olarak tespit edilmiştir. Bazı deneysel parametrelerin İSATAÇ üzerinde Metilen Mavisi adsorpsiyonuna etkileri göz önüne alınarak Yapay Sinir Ağı (YSA) modeli geliştirilmiş ve İSATAÇ’ın atık sulardan organik kirleticilerin uzaklaştırılmasında kullanılabileceği sonucuna varılmıştır.
In this work, it was investigated usability of Drinking Water Treatment Sludge (DWTS), obtained as end product at the end of treatment stages, as an adsorbent for removal of Methylene Blue, the organic pollutant (dyestuff), present in wastewaters. DWTS used for the adsorption experiments were not subjected to physical or chemical pre-treatment. Firstly, DWTS was characterized employing various analytical procedures including determination of moisture, density, volatiles, fixed carbon, ash, as well as elemental, SEM, FT-IR, XRD, XRF and TGA/DTA analysis. Then, adsorption experiments were carried out in a batch system and DWTS’s removal potential of the pollutant specie from aqueous solution was investigated in terms of equilibrium, kinetics and thermodynamics. DWTS’s maximum adsorption capacity obtained from Langmuir model for Methylene Blue was 62.50 mg g-1. Artificial Neural Network (ANN) model was developed considering the effects of certain experimental parameters for adsorption of Methylene Blue on DWTS and it was concluded that DWTS can be used to remove organic pollutants from wastewaters.
In this work, it was investigated usability of Drinking Water Treatment Sludge (DWTS), obtained as end product at the end of treatment stages, as an adsorbent for removal of Methylene Blue, the organic pollutant (dyestuff), present in wastewaters. DWTS used for the adsorption experiments were not subjected to physical or chemical pre-treatment. Firstly, DWTS was characterized employing various analytical procedures including determination of moisture, density, volatiles, fixed carbon, ash, as well as elemental, SEM, FT-IR, XRD, XRF and TGA/DTA analysis. Then, adsorption experiments were carried out in a batch system and DWTS’s removal potential of the pollutant specie from aqueous solution was investigated in terms of equilibrium, kinetics and thermodynamics. DWTS’s maximum adsorption capacity obtained from Langmuir model for Methylene Blue was 62.50 mg g-1. Artificial Neural Network (ANN) model was developed considering the effects of certain experimental parameters for adsorption of Methylene Blue on DWTS and it was concluded that DWTS can be used to remove organic pollutants from wastewaters.
Description
Keywords
Metilen mavisi, Adsopsiyon, Yapay sinir ağları, Methylene blue, Adsorption, Artificial neural network
Citation
Öztürk, N. vd. (2020). "İçme suyu arıtma tesisi atık çamuru üzerine metilen mavisi adsorpsiyonu ve yapay sinir ağları ile modellenmesi". Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, 25(2), 1083-1104.