Yazar "Dogan, Selim" seçeneğine göre listele

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    Removal of sulphate from landfill leachate by crystallization
    (Korean Soc Environmental Engineers, 2019) Aygün, Ahmet; Dogan, Selim; Argun, Mehmet Emin; Ates, Havva
    The present study explores the applicability of response surface methodology (RSM) in conjunction with central composite design (CCD) matrix to statistically optimize ettringite crystallization process for the removal of sulphate from landfill leachate. A three factor-five coded level CCD with 20 runs, was performed to estimate the best fitted model. The RSM results indicated that the fitted quadratic regression model could be appropriate to predict sulfate removal efficiency. The pH was identified as the most dominant parameter affecting sulphate removal. 61.6% of maximum sulphate removal efficiency was obtained at pH of 11.06 for a 1.87 of Ca/SO4 and 0.51 of Al/SO4 molar ratios. The operating cost for ettringite crystallization at optimized conditions was calculated to be 0.52 $/m(3 ). The significance of independent variables and their interactions were tested by analysis of variance. Scanning electron microscope (SEM) and SEM coupled with energy dispersive X-Ray spectroscopy results confirmed the formation of ettringite crystal and were used to describe its morphology features.
  • Küçük Resim
    Öğe
    STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATE
    (Brazilian Soc Chemical Eng, 2018) Aygün, Ahmet; Dogan, Selim; Argun, Mehmet Emin
    In the present study, experiments were conducted to optimize sulfate removal efficiency with ettringite precipitation from landfill leachate using Response Surface Methodology (RSM) and Central Composite Design (CCD). The statistical analysis of the results showed that the operating parameters such as molar rates of Ca/SO4 and Al/SO4, and pH had a significant effect on sulfate removal efficiency. Aluminum hydroxide and calcium hydroxide were used for external sources of aluminum and calcium. The goodness of the model was checked by different criteria including the coefficient of determination (R-2 = 0.94), p value (<0.0001), adequate precision (14.78), and coefficient of variance (7.30). The RSM results indicated that the fitted model could be appropriate to predict sulfate removal efficiency. A 55.7% maximum sulfate removal efficiency was obtained at pH 11.95 for 2.29 Ca/SO4 and 0.74 Al/SO4 molar ratios. Sulfate inhibition effects on treatment methods such as the anaerobic process decreased with increasing COD/SO4 ratio from 14:1 to 25:1 by ettringite precipitation.