A Master of Science thesis in Chemical Engineering by Awais Zaka entitled, “Pharmaceutical wastewater treatment using graphene oxide derivatives”, submitted in December 2019. Thesis advisor is Dr. Taleb H. Ibrahim. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).
The rising problem of pharmaceutical contamination in different water bodies calls for a swift action in the treatment and removal of these emerging pollutants from water using advanced methods. Adsorption is employed as a primary treatment method for treating water containing Diclofenac sodium, Aspirin and Paracetamol (Acetaminophen). Two graphene oxide-based adsorbents namely, reduced graphene oxide magnetite (RGOM) and graphene oxide nickel ferrite (GONF) were used for the adsorption process. Batch experiments were conducted to find the optimum conditions such as contact time, adsorption dosage, pH of the solution, temperature and initial concentration. These optimum values were then used to perform a number of experiments in order to fit isotherm models such as Langmuir, Freundlich and Temkin model. Pseudo-first and pseudo-second order kinetic models were also used to fit the kinetic data. Thermodynamic properties such as change in Gibbs free energy, enthalpy and entropy were then calculated to get further insight of the adsorption process. RGOM showed better results with the removal efficiency of more than 90% for the above-mentioned pharmaceuticals. The removal efficiency of GONF to remove Diclofenac sodium, Aspirin and Paracetamol was around 20%, 40% and 65% respectively. Reusability of both RGOM and GONF was studied for economic aspects of their applicability. Based on its better performance, RGOM was also used to study continuous fixed-bed adsorption of all three pharmaceuticals and the effect of flow rate of contaminated water and the bed depth of adsorbent in the column was studied. The adsorption data was fitted using different continuous adsorption models to obtain adsorption parameters.