Modeling a policy making framework for urban sustainability: Incorporating system dynamics into the Ecological Footprint |
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| Institution: | 1. State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China;2. Beijing Engineering Research Center for Watershed Environmental Restoration & Integrated Ecological Regulation, School of Environment, Beijing Normal University, Beijing 100875, China;3. Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan, Canada;1. State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing, 100875, China;2. Department of Western Development, The National Development and Reform Commission, No. 38, Yuetan South Street, Xicheng District, Beijing, 100824, China;1. State Key Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing 100875, China;2. Department of Development and Planning, Danish Centre for Environmental Assessment, Aalborg University, Rendsburggade 14, 9000 Aalborg, Denmark;1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Hui Long Guan, Chang Ping District, Beijing 102206, China;2. School of Economics and Management, North China Electric Power University, Hui Long Guan, Chang Ping District, Beijing 102206, China;3. School of Economics and Management, Beihang University, Xueyuan Road, Haidian District, Beijing 100191, China |
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| Abstract: | The Ecological Footprint (EF) is a powerful tool to advance the science of sustainability. However, the static snapshot of EF accounting is not designed to make projections of future sustainability consequences, which fails to elicit policy implications from a dynamic, temporally explicit perspective. This work attempts to incorporate system dynamics (SD) into EF to develop a dynamic EF forecasting framework, and provide a platform to support policy making for urban sustainability improvement. SD is firstly adopted to model the dynamics and interactions of EF driving forces, and then incorporated into the EF framework by correlating system drivers to EF-related consumption categories, embodied EF is finally calculated using the compound-based method. Based on different policy feasibility and sustainability targets, four policy scenarios are designed to explore future sustainability prospects and formulate integrated policies which would attain that sustainability scenario. The modeling procedure is applied to a case study area to illustrate how it works, and policy making for urban sustainability can hopefully be supported using this developed framework in the near future. |
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