Aygün, AhmetDogan, SelimArgun, Mehmet EminAtes, Havva2021-03-202021-03-2020191226-10252005-968Xhttp://doi.org/10.4491/eer.2017.179https://hdl.handle.net/20.500.12885/659The 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.eninfo:eu-repo/semantics/openAccessEttringite crystallizationLeachateResponse surface methodology (RSM)Scanning electron microscope (SEM)Sulphate removalArticle10.4491/eer.2017.1792412430WOS:000463210100003Q4Q2