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Modeling and forecasting household energy consumption and related CO2 emissions integrating UrbanSim and transportation models: an Atlanta BeltLine case study

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  • Dantong Wang
  • Chun Yuan

Abstract

Reducing energy consumption and controlling greenhouse gas emissions are key challenges for urban residents. Because urban areas are complex and dynamic, affected by many driving factors in terms of growth, development, and demographics, urban planners and policy makers need a sophisticated understanding of how residential lifestyle, transportation behavior, land-use changes, and land-use policies affect residential energy consumption and associated CO2 emissions. This study presents an approach to modeling and simulating future household energy consumption and CO2 emissions over a 30-year planning period, using an energy-consumption regression approach based on the UrbanSim model. Outputs from UrbanSim for a baseline scenario are compared with those from a no-transportation-demand model and an Atlanta BeltLine scenario. The results indicate that incorporation of a travel demand model can make the simulation more reasonable and that the BeltLine project holds potential for curbing energy consumption and CO2 emissions.

Suggested Citation

  • Dantong Wang & Chun Yuan, 2018. "Modeling and forecasting household energy consumption and related CO2 emissions integrating UrbanSim and transportation models: an Atlanta BeltLine case study," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(4), pages 448-462, May.
  • Handle: RePEc:taf:transp:v:41:y:2018:i:4:p:448-462
    DOI: 10.1080/03081060.2018.1453917
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