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Open Access Publications from the University of California

Transportation Module of Global Change Assessment Model (GCAM): Model Documentation- Version 1.0

  • Author(s): Mishra, Gouri S.
  • Kyle, Page
  • Teter, Jacob
  • Morrison, Geoffrey M.
  • Kim, Son H.
  • Yeh, Sonia
  • et al.

This publication provides methodological detail on the new GCAM Transportation Module and contains the following: (1) Descriptions of the new transportation module in GCAM (2) Details about the data sources and methodology adopted to estimate the exogeneous input parameters (3) A summary of the region-specific transportation data for base year (2005) (4) Comparisons of these estimates across regions and modes. (5) Highlights of the uncertainty and shortcomings in our estimates The project broadly encompasses the following four refinements to the transportation sector of GCAM: 1) Increased resolution to include the full spectrum of sub-modes and technologies available in passenger and frieght transport; 2) Refined estimates of input parameters so as to better represent real-world heterogeneity in a way consistent with the latest literature on transportation; 3) Refined estimates of base year (2005) estimates of transportation demand, and disaggregation of IEA energy estimates between modes and size classes; 4) Included the non-motorized modes of walking and biking. The above refinements will not only allow us to develop better estimates of transportation energy demand and emissions, but will also enable modeling of the impact of policies that induce behavioral change and switching to different size classes within a single fuel type. Existing literature on long-term forecasts of transportation energy demand and emissions have focused on the role of advanced low-emission vehicle technologies and low-carbon energy carriers in achieving climate change goals. In GCAM, modeling the impact of policies in the form of varying levels of carbon prices has, to date, been restricted to consumer choices for different modes (e.g. rail versus personal car) and different vehicle technologies (e.g. internal combustion engine vehicles versus electric vehicle). A more detailed representation of the transportation sector – including various size classes of vehicles -- will allow us to estimate the potential for downsizing in the case of private modes (large LDV to midsize or compact LDVs), transfer to public modes (rail and bus) or to non-motorized transport (walking and biking), and adoption of energy efficient “new” modes like the electric-bikes, which have seen rapid adoption in China and other developing countries. This project aims to better represent the heterogeneity and flexibility in the transport system to allow the modeling of a broader range of transport policy intruments including subsidies to public transit, government incentives for alternative technology, transportation fuel taxes, and public investments to increase the speed, service frequency/availability, and comfort of public and nonmotorized modes.

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