A decision-support system for sustainable urban metabolism in Europe

Urban metabolism components define the energy and material exchanges within a city and, therefore, can provide valuable information on the environmental quality of urban areas. Assessing the potential impact of urban planning alternatives on urban metabolism components (such as energy, water, carbon and pollutants fluxes) can provide a quantitative estimation of their sustainability performance. Urban metabolism impact assessment can, therefore, contribute to the identification of sustainable urban structures with regards, for example, to building types, materials and layout, as well as to location and capacity of transportation and infrastructural developments. In this way, it enables the formulation of planning and policy recommendations to promote efficient use of resources and enhance environmental quality in urban areas. The European FP7 project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) has developed a decision-support system (DSS) that systematically integrates urban metabolism components into impact assessment processes with the aim of accurately quantifying the potential effects of proposed planning interventions. The DSS enables integration of multiple spatial and non-spatial datasets (e.g. physical flows of energy and material with variables of social and economic change) in a systematic manner to obtain spatially defined assessment results and to thus inform planners and decision-makers. This multi-criteria approach also enables incorporation of stakeholders' perceptions in order to prioritise decisive assessment criteria. This paper describes the methodological framework used to develop the DSS and critically examines the results of its practical application in five European cities. - Highlights: ► Urban metabolism in sustainability assessment of planning alternatives. ► European FP7 project applied to 5 real life case studies across Europe. ► Decision support system enables incorporating scientific knowledge into planning. ► Scale, data availability and stakeholder representativeness limit its application.