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Proper operation of municipal wastewater treatment plants is important in producing an effluent which meets quality requirements of regulatory agencies and in minimizing detrimental effects on the environment. This paper examined plant dynamics and modeling techniques with emphasis placed on the digital computing technology of Artificial Neural Networks (ANN). A backpropagation model was developed to model the municipal wastewater treatment plant at Ardiya, Kuwait City, Kuwait. Results obtained prove that Neural Networks present a versatile tool in modeling full-scale operational wastewater treatment plants and provide an alternative methodology for predicting the performance of treatment plants. The overall suspended solids (TSS) and organic pollutants (BOD) removal efficiencies achieved at Ardiya plant over a period of 16 months were 94.6 and 97.3 percent, respectively. Plant performance was adequately predicted using the backpropagation ANN model. The correlation coefficients between the predicted and actual effluent data using the best model was 0.72 for TSS compared to 0.74 for BOD. The best ANN structure does not necessarily mean the most number of hidden layers.

Laboratory experiments were conducted at room temperature (20-25 degrees C) using four identical filter columns made of Plexiglas, each of 1 m height and 15 cm internal diameter, packed with granular media of 70 cm depth. Each filter was operated at a constant filtration rate, thus four rates were tested in the range of 2-15 m(3) m(-2) d(-1). Mono-media (sand) and dual-media (sand and anthracite) were tested and three types of municipal wastewaters, namely raw, primary and secondary-treated effluents were applied. The results obtained indicate that considerable improvements in effluent quality could be attained by tertiary sand filtration. Removal of solids, organics and bacteria was not significantly affected by the increase in filtration rate from 2 to 15 m(3) m(-2) d(-1). The highest removal efficiency was obtained at low filtration rate of 2 m(3) m(-2) d(-1), but higher filtration rates achieved acceptable removal efficiencies and provided effluents of good quality to satisfy the irrigation water quality standards. Since the conventional sand filters in wastewater treatment plants operate at a rate in the range of 2-5 m(3) m(-2) d(-1), utilization of high rate filtration is advantageous and would result in significant cost savings. However, with high filtration rates the filters require more frequent backwashing. Dual-media filters achieved 50% reductions in BOD suggesting that filtration could be used to treat primary effluents in emergency cases.

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This paper evaluates the effluent treatment plant of a slaughterhouse in Hawalli City, Kuwait processing 1100 heads of livestock a day. Results indicated that the proposed process effectively reduces pollution potential of slaughterhouse wastewater. Influent Chemical Oxygen Demand (COD) ranged from 3335 to 7580 mg L(-1), of which approximately 30% were in the form of suspended solids (SS). Removal efficiency was 77% for soluble COD and 82% for insoluble COD, at a volumetric load of 1.8 kg COD m(-3) d(-1). Values obtained for the biokinetic coefficients, floc uptake (FU), substrate removal efficiency (SRE), specific reaction rate (RR), maximum reaction rate (Rm) and Yield (Y) of the contact tank were higher than the range of values reported for other continuously fed activated sludge systems. In contrast to the contact tank, the aeration basin biokinetic coefficients were within the range of values reported. Contact process testing demonstrated that controlling solid recirculation to maintain a contact loading of about 120-150 mg COD g(-1) VSS in the contact tank generally resulted in high SRE. RR, Rm, and also in good settleability as indicated by SVIs being consistently below 150 mL g(-1). In the other hand, higher contact loadings of more than 150 mg COD g(-1) VSS. resulted in a significant deterioration in SRE, RR, Rm, and SVIs.

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