Tools to support a model-based methodology for emission/immission and benefit/cost/risk analysis of wastewater systems that considers uncertainty

被引:49
|
作者
Benedetti, Lorenzo [1 ]
Bixio, Davide [2 ]
Claeys, Filip [1 ]
Vanrolleghem, Peter A. [1 ,3 ]
机构
[1] Univ Ghent, Dept Appl Math Biomet & Proc Control, BIOMATH, B-9000 Ghent, Belgium
[2] Aquafin NV, Dept Technol, B-2630 Aartselaar, Belgium
[3] Univ Laval, Dept Genie Civil, ModelEAU, Ste Foy, PQ G1K 7P4, Canada
关键词
wastewater treatment plant design; cost-benefit analysis; risk; modelling and simulation; software tools; grid computing;
D O I
10.1016/j.envsoft.2008.01.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper presents a set of tools developed to support an innovative methodology to design and upgrade wastewater treatment systems in a probabilistic way. For the first step, data reconstruction, two different tools were developed, one for situations where data are available and another one where no data are available. The second step, modelling and simulation, implied the development of a new simulation platform and of distributed computation software to deal with the simulation load generated by the third step, uncertainty analysis, with Monte Carlo simulations of the system over one year, important dynamics and stiff behaviour. For the fourth step, evaluation of alternatives, the evaluator tool processes the results of the simulations and plots the relevant information regarding the robustness of the process against input and parameters uncertainties, as well as concentration-duration curves for the risk of non-compliance with effluent and receiving water quality limits. This paper illustrates the merits of these tools to make the innovative methodology of practical interest. The design practice should move from conventional procedures suited for the relatively fixed context of emission limits, to more advanced, transparent and cost-effective procedures appropriate to cope with the flexibility and complexity introduced by integrated water management approaches. (c) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1082 / 1091
页数:10
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