Brian J. Morton Elizabeth Shay Eun Joo Cho July 13, 2005

1. Advanced Modeling System for Forecasting Regional Development, Travel Behavior, and the Spatial Pattern of Emissions Brian J. Morton Elizabeth Shay Eun Joo Cho July 13, 2005

2. UNC-CH/NCSU Project Team • Land use and travel behavior modeling • UNC-CH • NCSU • Emissions estimation • NCSU • Air quality modeling • UNC-CH

3. EPA STAR Grant • Regional Development, Population Trend, and Technology Change Impacts on Future Air Pollution Emissions • EPA’s interests • Ground level ozone and fine particulate matter • How locations of emissions might change in response to future land development patterns • Current tools used to estimate emissions do not capture long-term changes in regional development patterns • Long time frame: 50 years

4. Key Research Questions • How might regional development patterns, over 50 years, influence quantity and spatial pattern of emissions from transportation in Charlotte? • Could realistic development patterns reduce transportation emissions by 10-20% or more? • How would different development patterns affect quality of life? • Ozone and of fine particulate matter • Human exposure • Other indicators

5. Charlotte transportation system in 1940 Charlotte in 2050? Reasons for Selecting Charlotte • Growing metro area in North Carolina • Data-rich site • Recent travel survey • Designated 8-hour ozone nonattainment area • ReVA • SEQL • Future transit metropolis?

6. Integrated models—TRANUS Overview of Research Design • Development drivers • Market and non-market incentives and constraints on development characteristics and location • Land use model • Markets for land and for floor space • Travel behavior model • Motorized and nonmotorized modes • Vehicle emissions model • Engine load approach (same as EPA’s MOVES)

7. TRANUS

8. Activities-Land Use System Production costs Productive sectors Household sectors Floorspace Land Commodity flows Traveler flows Equilibrium pricesof land and floorspace Consumption ofland and floorspace Source: Modelistica, 2004

9. Transportation Model Vehicle ownership model Urban form -Mix of uses -Density -Infrastructure -Parking pricing -Regional access Trip generation Elastic trip generation Trip distribution Mode split Trips assignment Elastic mode split Probabilistic assignment

10. TAZ Transect for Describing Neighborhoods • TAZ Transect classifies neighborhoods based on: • Land use characteristics (density and use) • Transportation (street design and modes) • TAZ Transect provides a palette of neighborhoods for scenario assessment

11. Two Types of Neighborhood

12. Energy Factors Affecting Data From Driving Use Emission Rates Travel Forecasts Modes Speed Average Speed Micro - Emission Acceleration VMT scale Rate Select Road Grade Emissions Trans. Mode Estimation Context - Load Specific Meso - . . . Emissions Defaults scale Ambient Cond . Etc. Estimation Emissions Technology. Facility - Specific Vehicle Macro - Activity Etc. Driving Cycles Activity scale Knowledge (Real - World, Estimation Emissions Base On - Board Data) Emissions Estimation

13. Scenario Development: Two Approaches • Paint the landscape with new land uses and/or changes to the transportation system • Change market and non-market incentives and constraints on development, with or without transportation system changes

14. Multimodal travel forecasts sensitive to typology & exogenous factors Estimate emissions from on-road mobile sources Study area: Charlotte TAZ Transect Future locations of employment centers & residences Run air quality model Classify zones according to transect Run selected land use/transport forecasting model Estimate exposures Exogenous Factors: Population aging IPCC’s parameters Vehicle fleet mix Vehicle technology Translate scenarios into land market (change constraints, impose new tastes, etc.) & transportation system Identify future scenarios based on typology Summary of Modeling Approach

15. Expected Results and Benefits • State-of-the-art simulation model for investigating effects of development on spatial pattern and quantity of emissions from mobile sources • Scenario assessments for Charlotte • What proportion of area would have to be developed in a compact manner to reduce emissions by 10% or 15%? • Is a 20% emission reduction feasible with any reasonable forecast of market penetration of smart growth?

16. Analytical Innovations • TAZ Transect • Quantitative typology of land-use patterns at the neighborhood level (transportation analysis zone) • Tool for describing development scenarios • Land use model • Based on economic theory of how development occurs • TRANUS (applied in Europe and South America)

17. Additional Analytical Innovations • Travel behavior model • Travel options include bicycle and walking • Trip generation, destination choice, and modal choice are sensitive to attributes of built environment such as pedestrian friendliness • Vehicle emissions model • Detailed emissions profile for transit vehicles • Next generation emission factor model

18. Timeline of Major Analytical Tasks • 2005 • Obtain data • Construct land use and transportation models • 2006 • Construct baseline TAZ Transect • Refine land use and transportation models • Develop and analyze development scenarios • 2007 • Additional scenario analysis • Forecast air quality with Models3/Community Multiscale Air Quality modeling system

19. Working Together… • Already working together on data – thank you, thank you, thank you! • Additional ways of working together • Land use modeling • Transportation modeling • Developing scenarios • Evaluating scenarios • Others?

20. Contact Person and Web Site • Brian J. Morton, Ph.D., Project Manager bjmorton@unc.edu (919) 962-8847 Center for Urban and Regional Studies University of North Carolina at Chapel Hill • http://epastar.unc.edu/index.htm