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Regulators and engineers are faced with a great deal of uncertainty in the process of permitting and designing activated sludge treatment plants. To account for this uncertainty, regulators sometimes establish effluent limits based on combinations of worst-case conditions that may seldom, if ever, occur. Design engineers employ generous safety factors to compensate for uncertainties in the design process. The cumulative result of these layers of conservatism may be an over-designed activated sludge treatment plant, a luxury that the wastewater treatment industry can ill afford in an engineering environment in which stakeholders increasingly demand reliable low-cost protection of surface water quality. In other cases, failure to account for uncertainty can result in under-performance when unexpected conditions arise. Regulators and engineers require better tools to manage uncertainty in order to build cost-effective treatment plants that reliably protect surface water quality.

In this paper, a design methodology for activated sludge treatment plants that explicitly considers water quality effects and uncertainty in design variables and parameters is presented. The Monte Carlo method is used to propagate uncertainty through the design equations. The approach is implemented on a spreadsheet using a desk-top computer. This approach allows a plant design to be tested for literally thousands of operating conditions in a matter of minutes. The method is applicable to a wide range of water quality and activated sludge process models. A hypothetical example is used to illustrate the method and to make comparisons with conventional design procedures. In the example tested, the main difference was that the Monte Carlo based method resulted in a smaller aeration basin compared to a conventional design approach.
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Document Type: Research Article

Publication date: 2000-01-01

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