Advanced Modeling System for Forecasting Regional Development, Travel Behavior,
and the Spatial Pattern of Emissions
Through simulation modeling of land use, transportation, emissions, and air quality, this project will
determine whether regional development patterns, and market and non-market policy instruments to
influence such patterns, can significantly influence the spatial characteristics and quantity of emissions
that contribute to tropospheric ozone and fine particulate matter.  Our modeling system will have the
potential to create plausible North American emission inventories that are model ready, sufficient to
drive the Models3/Community Multi-scale Air Quality modeling system.

Objectives
The fundamental goal of our research is to rigorously test the hypothesis that alternative development
patterns, over a planning horizon of 50 years, can significantly influence the quantity and location of
direct and indirect emissions from mobile sources (and hence reduce the levels of tropospheric ozone
and fine particulate matter (PM)).  The development patterns of interest include the type of development
(transit-oriented and dense mixed-use developments, and those supportive of non-motorized transportation
modes for non-work trips, etc.) and its location (neo-traditional suburban, new urban core development,
redevelopment, etc.).

Key questions
Our research is motivated by several fundamental assumptions based in existing theory and knowledge.
These are:
• Transportation-related emissions form health-threatening tropospheric ozone and PM over multiple
  scales (local to continental), with mobile sources the greatest share
• Land development shapes travel behavior, such that aggregate travel activity may affect the location,
  quantity, temporal patterns, and speciation of emissions
• Behavioral research linking development and spatial distribution of emissions is sparse, and is
  complicated by design challenges and uncertainty

With this basis, we formulated key research questions:
• How do alternative development patterns, over a 50-year planning horizon, influence the quantity and
  location of direct and indirect emissions from mobile sources?
• How do such changes affect levels of tropospheric ozone and fine particulate matter?
• Can market and non-market policy instruments influene regional development, and thus emissions
  patterns, in desired directions?

Approach
The project team’s social scientists, physical scientists, and engineers will develop and apply a state-of-
the-art simulation model comprising the following modules: 1) a cross-sectional land-market equilibrium model;
2) a multimodal behavioral travel model which includes no-motorized modes, incorporates attributes of the built
environment, and is integrated with the land-use model; 3) a modal approach to estimating emissions based upon
the conceptual underpinnings of EPA’s Multi-Scale Motor Vehicle and Equipment Emissions Estimation System
(MOVES).  We will test our hypothesis with a case study of the Charlotte (NC) metropolitan area, where newly
acquired or developed data for all or our modules are available.  Our modeling system will forecast emissions
under various scenarios and quantify some of the uncertainty in the emissions estimates.  We will be able to
compare development scenarios on air pollutant concentrations and population exposures.

                                        
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Expected results
Our research will develop a general, objective method for exploring questions and hypotheses about the leverage
that smart-growth development patterns (and other forms of development) may have on the spatial characteristics
and quantity of direct and indirect emissions from mobile sources.  With our modeling system, we will explore
scenarios for land-use strategies and examine the potential of smart growth as a means for reducing emissions.  
We will determine whether a substantial (e.g., 20%) emissions reduction is feasible with any reasonable forecast
of the market penetration of smart growth.