Faculty of Applied Sciences

Abstract Nitrification at a full-scale activated sludge plant treating municipal wastewater was monitored over a period of 237 days. A combination of fluorescent in situ hybridiza-tion (FISH) and quantitative real-time polymerase chain reac-tion (qPCR) were used for identifying and quantifying the dominant nitrifiers in the plant. Adaptive neuro-fuzzy infer-ence system (ANFIS), Pearson’s correlation coefficient, and quadratic models were employed in evaluating the plant oper-ational conditions that influence the nitrification performance. The ammonia-oxidizing bacteria (AOB) abundance was with-in the range of 1.55 × 108–1.65 × 1010 copies L−1, while Nitrobacter spp. and Nitrospira spp. were 9.32 × 109–1.40 × 1011 copies L− 1 and 2.39 × 109 –3.76 × 1010 copies L−1, respectively. Specific nitrification rate (qN)was significantly affected by temperature (r 0.726, p 0.002), hy-draulic retention time (HRT) (r −0.651, p 0.009), and ammo-nia loading rate (ALR) (r 0.571, p 0.026). Additionally, AOB was considerably influenced by HRT (r −0.741, p 0.002) and temperature (r 0.517, p 0.048), while HRT negatively impact-ed Nitrospira spp. (r −0.627, p 0.012). A quadratic combina-tion of HRT and food-to-microorganism (F/M) ratio also im-pacted qN (r2 0.50), AOB (r2 0.61), and Nitrospira spp. (r2 0.72), while Nitrobacter spp. was considerably influenced by a polynomial function of F/M ratio and temperature (r2 0.49). The study demonstrated that ANFIS could be used as a tool to describe the factors influencing nitrification process at full-scale wastewater treatment plants.

Seasonal 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.

Faculty of Applied Sciences

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