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Three consulting teams conducted independent modelling projects for three different wastewater treatment plants ranging in size from approximately 113,800 m(3)/d (30 mgd) to 530,000 m(3)/d (140 mgd), in different parts of the world (USA and Finland). The plants have different treatment objectives ranging from nitrification and partial denitrification (nitrate plus nitrite <8.7 mg/L) to enhanced nutrient removal (total nitrogen <3 mg/L, total phosphorus <0.3 mg/L). Commonly-used models were applied in the case studies, including ASM3 (using the GPS-X simulator), New General (using GPS-X), Dold (using BioWin), and a variation of the Dold model methanol degradation capabilities (NGmeth within GPS-X). The authors compare and contrast the modelling approaches taken, including calibration and validation approaches, sensitivity analyses, and the application of results to full-scale studies, designs and operations. Despite several differences between the approaches, there are many similarities which are discussed in light of the IWA draft uniform protocol for activated sludge modelling. The authors also discuss current modelling limitations and offer suggestions to improve the state of the art.

Using an interactive multiobjective optimization method called NIMBUS and an approximation method called PAINT, preferable solutions to a five-objective problem of operating a wastewater treatment plant are found. The decision maker giving preference information is an expert in wastewater treatment plant design at the engineering company Pöyry Finland Ltd. The wastewater treatment problem is computationally expensive and requires running a simulator to evaluate the values of the objective functions. This often leads to problems with interactive methods as the decision maker may get frustrated while waiting for new solutions to be computed. Thus, a newly developed PAINT method is used to speed up the iterations of the NIMBUS method. The PAINT method interpolates between a given set of Pareto optimal outcomes and constructs a computationally inexpensive mixed integer linear surrogate problem for the original wastewater treatment problem. With the mixed integer surrogate problem, the time required from the decision maker is comparatively short. In addition, a new IND-NIMBUS ® PAINT module is developed to allow the smooth interoperability of the NIMBUS method and the PAINT method.