Integrating Climate Change Considerations Into MPO Long Range Transportation Forecasting

In the last few years, there is an increasing number of scientific evidences supporting the hypothesis that emissions of greenhouse gas (GHG) into the atmosphere is contributing to changes in the earth's climate with many detrimental effects that are already taking place. A consensus toward the need for actions for the reduction of GHG has grown among the public and elected officials. In the United States, a major source of GHG emissions is Carbon dioxide (CO2) emissions from personal vehicles and trucks. The amount of CO2 emissions from mobile sources is tied directly to the amount of fuel consumed, which is then tied to the total Vehicle Miles Traveled (VMT). In order to devise effective multimodal transportation policies and financial programs for VMT reduction (i.e., reduction in CO2 emissions) in a metropolitan area, a travel demand forecasting model with sufficient spatial and temporal resolution is needed to generate traffic forecasts to be used as inputs to air quality models such as EPA's MOBILE 6 or MOVES model. It is noted that MOVES, which will replace MOBILE 6 as the next generation mobile source emission model, require traffic volume forecasts with spatial and temporal details that exceed what the current travel demand models can produce. The two Metropolitan Planning Organizations (MPO) in Alaska are Anchorage Metropolitan Area Transportation Solutions (AMATS) and Fairbanks Metropolitan Area Transportation System (FMATS). Each of them maintains a travel demand forecasting model for the purpose of long-range transportation plan updates. This study proposes to use the two MPO models as the case studies to first examine the inefficiencies of the two models in terms of meeting data requirements for MOVES. The inadequacies for the two models to address the effectiveness of reflecting GHG reduction policies will also be examined. Effective methods to address the models' inefficiencies will then be researched and developed. The newly improved models will be validated and calibrated with most current observed data. The models will be tested with a forecasting scenario to demonstrate their capability to reflect the effectiveness of GHG emission reduction of proposed transportation measures.


  • English


  • Status: Completed
  • Contract Numbers:


    309042 / G00003238

  • Sponsor Organizations:

    Alaska University Transportation Center

    University of Alaska, Fairbanks
    P.O. Box 755900
    Fairbanks, AK  United States  99775-5900
  • Project Managers:

    Lee, Ming

  • Performing Organizations:

    Alaska University Transportation Center

    University of Alaska, Fairbanks
    P.O. Box 755900
    Fairbanks, AK  United States  99775-5900
  • Principal Investigators:

    Lee, Ming

  • Start Date: 20090801
  • Expected Completion Date: 0
  • Actual Completion Date: 20110731
  • Source Data: RiP Project 22616

Subject/Index Terms

Filing Info

  • Accession Number: 01462058
  • Record Type: Research project
  • Source Agency: Alaska University Transportation Center
  • Contract Numbers: DTRT06-G-0011, 309042 / G00003238
  • Files: UTC, RiP
  • Created Date: Jan 3 2013 1:57PM