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

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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

unc ch ncsu project team
UNC-CH/NCSU Project Team
  • Land use and travel behavior modeling
    • UNC-CH
    • NCSU
  • Emissions estimation
    • NCSU
  • Air quality modeling
    • UNC-CH
epa star grant
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
key research questions
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
reasons for selecting charlotte

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?
overview of research design

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)
activities land use system
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

transportation model
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

taz transect for describing neighborhoods
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
emissions estimation

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
scenario development two approaches
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
summary of modeling approach

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
expected results and benefits
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?
analytical innovations
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)
additional analytical innovations
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
timeline of major analytical tasks
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
working together
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?
contact person and web site
Contact Person and Web Site
  • Brian J. Morton, Ph.D., Project Manager

[email protected]

(919) 962-8847

Center for Urban and Regional Studies

University of North Carolina at Chapel Hill

  • http://epastar.unc.edu/index.htm
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