Sumala Tirumalachetty^a, ^b,
Kara M. Kockelman^b,
Brice G. Nichols^b,
^a Sabre Holdings, Bangalore, India
^b Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, United States


Highlights

•We developed a microsimulation forecast of demographic and firmographic attributes of Austin, TX.
•GHG emissions and household energy demand estimates for 2030 are compared under five scenarios.
•This microsimulation framework can track location and travel behaviors for a mid-size U.S. region.
•This work provides useful insights into future energy demands and policy decisions for communities.


Keywords
Land use modeling; Urban system forecasting; Microsimulation; Energy consumption; Greenhouse gas emissions; Travel demand modeling



Abstract
Policymakers, planners, engineers, and others seek effective ways to anticipate and manage greenhouse gas (GHG) emissions for a sustainable future. Here, a microsimulation model was developed to demonstrate how one can forecast Austin’s demographic and firmographic attributes over time, using a variety of national and local, aggregate and disaggregate data sets. Year 2030 household energy demands and GHG emissions estimates are compared under five different land use and transport policy scenarios. Application of an urban growth boundary provided the lowest increase in overall vehicle miles traveled (VMT) and GHG emissions, while network additions resulted in the highest rates of increase. Average energy consumption per household are estimated to fall over time (by 11–19% depending on the scenario), but the region’s overall energy consumption is estimated to increase dramatically – by nearly 88% in terms of home energy consumption (in the base scenario) and 108% in the transport sector, relative to the 2005 base-year scenario. Such increases are considerably higher than proposed GHG targets, presenting a serious energy and emissions challenge for Austin as well as other U.S. regions.



Article Outline
1. Background
2. Model development and data description
2.1. The region
2.2. Overview of modeling framework
2.3. Policy scenarios

3. Results
3.1. Location choices
3.2. Vehicle choices
3.3. Vehicle miles traveled and GHG emissions
3.4. Household energy demand
3.5. Per capita emissions

4. Summary and conclusions
Acknowledgements
References


Figures
   

Fig. 1.

Overall simulation framework.


Fig. 2.

The Austin region (Travis, Williamson and Hays Counties).


Fig. 3.

Illustration of Austin’s example urban growth boundary, I-35 Corridor and SH 130 Corridor.


Fig. 4.

2030 Household densities across 4 scenarios.


Fig. 5.

VMT by fuel economy class in 2030 across scenarios.



Tables

Table 1. Summary of modules in the simulation framework.

Table 2. Vehicle fleet composition estimates in 2030 by scenario.

Table 3. Network VMT, greenhouse gas emissions, V/C ratios and speeds in 2030.

Table 4. Household energy demand and GHG emissions over time, by scenario.

Table 5. Year 2030 per capita carbon emissions forecasts.