This study evaluated the application of magnetised powdered activated carbons and biochars, in the removal of typical pollutants encountered in refinery and other wastewaters. Phenol, pharmaceuticals and heavy metals were chosen as representatives of priority pollutants, organic micropollutants and metals. In the sorption of the organics, there existed a strong correlation (Pearson correlation R up to 0.9990) between isotherm models’ capacity parameters and sorbents’ capacity influencing properties. In the case of the metals, the sorbents’ capacities are not dependent upon surface area and micropore volume. In some instances, the biochars have on the average about 20.45% higher uptake of the metals than the activated carbons. A general decrease in phenol uptake on the biochars with increase in pH was recorded, due to electrostatic repulsion between like charged surface and sorbates. For the activated carbons, peak phenol sorption was found within the vicinity of the pKa and point of zero charge when there is maximum electrostatic attraction between the opposite charged surface and sorbates. For the micropollutants, ibuprofen was negatively affected by an increase in pH while diclofenac sorption was not sensitive to changes in pH. Sorption of metals was found to increase with an increase in pH. Synthetic wastewater (SWW) did not have a significant impact on the sorption of the phenol and heavy metals. In the case of phenol, the highest impact, an average of just 6.15% for all sorbents was recorded. For the micropollutants, according to the linear model, there is, on the other hand, about 92 and 96% less uptake of diclofenac and ibuprofen respectively due to competition. Finally, in an equimolar solution, due to its high solubility, Zn2+ was outcompeted by Cu2+ and Pb2+ for binding to available sorption sites.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:724692 |
| Date | January 2017 |
| Creators | Sani, Badruddeen Saulawa |
| Publisher | University of Newcastle upon Tyne |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10443/3595 |
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