Article ID: | iaor20023687 |
Country: | United States |
Volume: | 43 |
Issue: | 7 |
Start Page Number: | 265 |
End Page Number: | 270 |
Publication Date: | Jan 2001 |
Journal: | Water Science and Technology |
Authors: | Lambert A.J.D., Balkema A.J., Preisig H.A., Otterpohl R., Weijers S.R. |
Keywords: | artificial intelligence: decision support |
To enable decision makers to select sustainable wastewater treatment systems, insight into the sustainability of a wide variety of systems should be provided in a transparent way leaving room for adaptation and interpretation according to the local situation. To provide this insight a structured methodology comparing wastewater treatment systems with respect to sustainability is defined. Similar to life cycle assessment (LCA) three phases can be distinguished: (1) goal and scope definition, (2) inventory analysis, and (3) optimisation and results. In the goal and scope definition we set the system boundaries to include most of the water cycle and part of the food cycle. Furthermore, we defined a multi-disciplinary set of sustainability indicators including technical, economic, environmental, and socio-cultural aspects. In the inventory analysis these sustainability indicators are quantified using simple static models of wastewater unit operations. Selection of unit operations results in a model of a complete wastewater treatment system. In the optimisation phase the decision maker can weigh the different sustainability indicators and select sustainable options through integer programming.