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Evaluation of seasonal impacts on nitrifiers and nitrification performance of a full-scale activated sludge system

dc.contributor.advisorBux, Faizal
dc.contributor.advisorSheena Kumari, S.K.
dc.contributor.authorAwolusi, Oluyemi Olatunjien_US
dc.date.accessioned2016-11-10T06:24:45Z
dc.date.available2016-11-10T06:24:45Z
dc.date.issued2016
dc.descriptionSubmitted in complete fulfillment for the degree of Doctor of Philosophy (Biotechnology), Durban University of Technology, Durban, South Africa, 2016.en_US
dc.description.abstractSeasonal nitrification breakdown is a major problem in wastewater treatment plants which makes it difficult for the plant operators to meet discharge limits. The present study focused on understanding the seasonal impact of environmental and operational parameters on nitrifiers and nitrification, in a biological nutrient removal wastewater treatment works situated in the midlands of KwaZulu Natal. Composite sludge samples (from the aeration tank), influent and effluent water samples were collected twice a month for 237 days. A combination of fluorescent in-situ hybridization, polymerase chain reaction (PCR)-clone library, quantitative polymerase chain reaction (qPCR) were employed for characterizing and quantifying the dominant nitrifiers in the plant. In order to have more insight into the activated sludge community structure, pyrosequencing was used in profiling the amoA locus of ammonia oxidizing bacteria (AOB) community whilst Illumina sequencing was used in characterising the plant’s total bacterial community. The nonlinear effect of operating parameters and environmental conditions on nitrification was also investigated using an adaptive neuro-fuzzy inference system (ANFIS), Pearson’s correlation coefficient and quadratic models. The plant operated with higher MLSS of 6157±783 mg/L during the first phase (winter) whilst it was 4728±1282 mg/L in summer. The temperature recorded in the aeration tanks ranged from 14.2oC to 25.1oC during the period. The average ammonia removal during winter was 60.0±18% whereas it was 83±13% during summer and this was found to correlate with temperature (r = 0.7671; P = 0.0008). A significant correlation was also found between the AOB (amoA gene) copy numbers and temperature in the reactors (α= 0.05; P=0.05), with the lowest AOB abundance recorded during winter. Sanger sequencing analysis indicated that the dominant nitrifiers were Nitrosomonas spp. Nitrobacter spp. and Nitrospira spp. Pyrosequencing revealed significant differences in the AOB population which was 6 times higher during summer compared to winter. The AOB sequences related to uncultured bacterium and uncultured AOB also showed an increase of 133% and 360% respectively when the season changed from winter to summer. This study suggests that vast population of novel, ecologically significant AOB species, which remain unexploited, still inhabit the complex activated sludge communities. Based on ANFIS model, AOB increased during summer season, when temperature was 1.4-fold higher than winter (r 0.517, p 0.048), and HRT decreased by 31% as a result of rainfall (r - 0.741, p 0.002). Food: microorganism ratio (F/M) and HRT formed the optimal combination of two inputs affecting the plant’s specific nitrification (qN), and their quadratic equation showed r2-value of 0.50. This study has significantly contributed towards understanding the complex relationship between the microbial population dynamics, wastewater composition and nitrification performance in a full-scale treatment plant situated in the subtropical region. This is the first study applying ANFIS technique to describe the nitrification performance at a full-scale WWTP, subjected to dynamic operational parameters. The study also demonstrated the successful application of ANFIS for determining and ranking the impact of various operating parameters on plant’s nitrification performance, which could not be achieved by the conventional spearman correlation due to the non-linearity of the interactions during wastewater treatment. Moreover, this study also represents the first-time amoA gene targeted pyrosequencing of AOB in a full-scale activated sludge is being done.en_US
dc.description.levelDen_US
dc.format.extent196 pen_US
dc.identifier.doihttps://doi.org/10.51415/10321/1722
dc.identifier.other662629
dc.identifier.urihttp://hdl.handle.net/10321/1722
dc.language.isoenen_US
dc.subjectamoAen_US
dc.subjectNitrifiersen_US
dc.subjectNGSen_US
dc.subjectIlluminaen_US
dc.subjectPyrosequencingen_US
dc.subjectAdaptive neuro-fuzzy inference systemen_US
dc.subjectSAORen_US
dc.subjectSNFRen_US
dc.subjectqPCRen_US
dc.subjectActivated sludgeen_US
dc.subject.lcshSewage--Purification--Activated sludge processen_US
dc.subject.lcshNitrifying bacteriaen_US
dc.subject.lcshNitrificationen_US
dc.subject.lcshSewage--Purification--South Africa--KwaZulu-Natalen_US
dc.subject.lcshWater treatment plants--South Africa--KwaZulu-Natalen_US
dc.titleEvaluation of seasonal impacts on nitrifiers and nitrification performance of a full-scale activated sludge systemen_US
dc.typeThesisen_US
local.sdgSDG06

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