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    It was aimed to precisely investigate the coagulation properties of graphene oxide (GO) as a novel coagulant for turbidity removal from water. For this purpose, the process was simulated through response surface methodology (RSM) to determine the effect of the preselected independent factors (pH, GO dosage, and initial turbidity) and their interaction effects on the process. Based on the results, increased turbidity removal efficiencies were obtained as pH decreased from 10 to 3. Besides, increase of GO dosage within the test range (2.5-30 mg/L) was highly beneficial for enhancing the process performance. However, a slight overdosing of GO was observed for dosages of more than 20 mg/L under pH values of less than about 4. For initial turbidity with test range of 25-300 NTU, there was an optimum range (approximately 120-200 NTU) out of which the removal efficiency declined. According to the results of the analysis of variance (ANOVA), pH and GO dosage, orderly, had the strongest individual effect on the process performance. The most significant interaction effect was also observed between pH and GO dosage. The optimal coagulation conditions with GO dosage of 4.0 mg/L, pH of 3.0, and initial turbidity of 193.34 NTU led to a turbidity removal efficiency of about 98.3%, which was in good agreement with RSM results. Under basic pH levels, the sweeping effect was recognized as the main coagulation mechanism occurred between the negatively surface charged particles of GO and soil. However, according to zeta potential (ZP) analysis results, under acidic pH conditions in addition to the sweep coagulation, the electric double layer compression, and the subsequent ZP reduction also contributed significantly to the process. Scanning electron microscopy (SEM) images showed that the layered structure of GO particles provided an appropriate platform on which the flocs were formed.


    Nazila Rezania, Maryam Hasani Zonoozi, Motahareh Saadatpour. Coagulation-flocculation of turbid water using graphene oxide: simulation through response surface methodology and process characterization. Environmental science and pollution research international. 2021 Mar;28(12):14812-14827

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    PMID: 33216297

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