GreenSTEP Statewide Transportation Greenhouse Gas Model Cutting Carbs Conference December 3, 2008 Brian Gregor ODOT Transportation Planning Analysis Unit.

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Presentation transcript:

GreenSTEP Statewide Transportation Greenhouse Gas Model Cutting Carbs Conference December 3, 2008 Brian Gregor ODOT Transportation Planning Analysis Unit

What are models?

3 We Are All Modelers Highway Expansion Sprawl More Travel Any time that logic is used to predict the consequences of decisions, a model is used to structure the reasoning process. Most often that is a mental model. Whatever shall we do?

4 Conflicts Arise from Differences in Mental Models Highway Expansion Sprawl More Travel Highway Expansion More Travel Sprawl You’re wrong! No You Are!

5 Formal Models are Needed for Analyzing Complex Systems Well structured models: Can account for many complex interactions Maintain logical consistency in addressing interactions Provide a more complete accounting of effects Allow policies to be tested in a reasonable amount of time Help to resolve conflicts between differing points of view

6 Steps in Model Development Process Design –Define model scope, structure, and components Estimation –Use data to develop mathematical functions and algorithms for model components Calibration –Adjust function parameters and algorithms to match observed values (e.g. % zero vehicle households) Validation –Check that overall model behavior is reasonable Models are complex, and may be difficult to understand, but should not be black boxes.

What is GreenSTEP

8 GreenSTEP Model Greenhouse gas State Transportation Emissions Planning Model Why develop GreenSTEP –The OGWC needs to be able to analyze the effects of transportation and land use strategies for reducing GHG emissions statewide. –Existing land use and transportation models can’t be used to do the required analysis on a statewide basis in the time available. Statewide scope of analysis required A wide range of factors need to be analyzed Run-time issues

9 GreenSTEP Model Requirements Develop statewide forecasts of GHG emissions from transportation sources in response to various policy approaches and other factors (e.g. fuel prices). Be responsive to regional differences including differences between metropolitan areas, other urban areas and rural areas. –Is not a substitute for the use of metropolitan transportation and land use models for regional planning Run relatively quickly so that a number of iterations of scenario development and testing can occur.

10 Factors for Model to Address Demographic changes Relative amounts of development occurring in urban and rural areas Metropolitan and other urban area densities and urban form Amounts of metropolitan area public transit service Highway capacity Vehicle fuel efficiency Electric vehicles Fuel prices Other vehicle pricing Demand management Congestion effects Vehicle operation and maintenance Carbon content of fuels – including well to wheels impacts CO 2 production from electrical power generation

Model Structure

12 GreenSTEP Model Structure Population Projection by Age Cohort (OEA County Forecasts) Create Synthetic Households by County to Represent Population Projection Number of persons by age Income Calculate Population Densities and Urban Mixed-Use Characteristics where Households are Located Urban Growth Boundary Expansion Rates Average Fleet MPG by Type Primary EV Driving Range and Proportion of VMT in Range to be EV Calculate Vehicle Fleet Characteristics: Vehicle ages, types by income Average MPG Gas and diesel proportions Proportion of Mileage that is EV Rate of Transit Revenue Mile Growth Rate of Freeway Lane- Mile Growth Household Age Structure Model Household Income Model Proportions of Growth Occurring in Metropolitan, Other Urban, and Rural Areas Calculate Freeway and Public Transit Supply Levels Census Tract Density Model Models of Age and Type of Vehicle by Income Group Model of Daily Miles Driven by Vehicle by Population Density Calculate Vehicle Ownership Vehicle Ownership Model State Average Per Capita Income Growth Calculate Annual Household VMT Household DVMT Models - Metropolitan Area -Other Urban and Rural Urban Mixed-Use Model Urban Mixed-Use Assumptions

13 Demand Management Assumptions Demand Adjustment Factors Calculate Demand Management Adjusted VMT Electric Power Cost Assumptions VMT Tax Policy Assumptions Fuel Lifecycle Carbon Content CO2 Production per KWH Household DVMT Models - Metropolitan Area -Other Urban and Rural Vehicle Ownership Model Calculate Household Travel Cost Increase Over 2000 Levels and Adjust Household Income Fuel Cost Assumptions Recalculate Vehicle Ownership Based on Adjusted Household Income Recalculate Annual Household VMT Based on Adjusted Household Income Public Transit VMT Calculated from Revenue Miles ( above ) Calculate Fuel Consumption, Electric Power Consumption, and Greenhouse Gas Emissions Average Fleet MPG and MPKwh ( calculated above ) Vehicle Fleet MPG & MPKwh Statewide Population Projection Truck VMT Model Calculate Truck VMT State Average Per Capita income Growth Vehicle Maintenance & Operations Assumptions

Model Sensitivity Testing

15 Test of Model Sensitivity to Land Use and Transportation Inputs

16 Test of Model Sensitivity to Land Use and Transportation Inputs Approximate density of Los Angeles Approximate density of Atlanta

17 Test of Model Sensitivity to Land Use and Transportation Inputs Approximate freeway supply of New York Approximate freeway supply of Houston Approximate freeway supply of Minneapolis

18 Test of Model Sensitivity to Land Use and Transportation Inputs Approximate transit supply of Miami Approximate transit supply of Detroit Approximate transit supply of Seattle

19 Test of Model Sensitivity to Land Use and Transportation Inputs No places are urban mixed-use All places are urban mixed-use

20 Test of Model Sensitivity to Land Use and Transportation Inputs

21

22 Conclusions GreenSTEP can be used to evaluate a large number of different policies and other factors on GHG emissions: land use, transportation, prices, vehicle characteristics, fuels, etc. GreenSTEP evaluates interactions between factors: e.g. density -> vehicle ownership -> vehicle travel GreenSTEP includes new modeling components that we will be able to combine with other models, statewide and urban for modeling GHG emissions.