Reducing energy use and emissions through innovative technologies and community designs.

Khattak, Asad J.; Wang, Xin · 2016 · ROSA P / United States. Dept. of Transportation. Research and Special Programs Administration

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Summary

This report evaluates strategies to reduce transportation energy consumption and greenhouse gas emissions through the integration of smart growth land-use policies, intelligent transportation systems (ITS), and alternative fuel vehicles. Motivated by the transportation sector’s status as the second-largest source of U.S. greenhouse gas emissions, the study aims to quantify the impacts of these strategies at both regional and individual levels. The research seeks to determine which combinations of growth management and technology adoption most effectively enhance sustainability, specifically targeting reductions in carbon dioxide (CO2) and local pollutants. The methodology employs a comprehensive modeling, simulation, and visualization framework that integrates macroscopic travel demand models with microscopic emissions analysis. At the macro-level, the authors analyzed behavioral data from the 2009 National Household Travel Survey (NHTS) and Virginia Add-on surveys, covering over 15,000 households. They utilized Heckman sample selection models to account for the conditional nature of driving decisions and emissions. Regional analyses were conducted using TransCAD for the Hampton Roads, Virginia area, comparing smart growth and transit-oriented development (TOD) scenarios against business-as-usual trends. At the micro-level, the study leveraged large-scale GPS trajectory data, including 51,371 trips from Atlanta, Georgia, to analyze instantaneous driving decisions such as acceleration and braking. Additionally, hierarchical models were applied to assess the travel patterns of early alternative fuel vehicle adopters. Key findings indicate that smart growth strategies are significantly associated with emission reductions. Households residing in mixed-use neighborhoods with high network connectivity produced approximately 9% lower tailpipe CO2 emissions compared to those in conventional developments. The study also identified that driving volatility, characterized by hard braking and acceleration, varies significantly by demographic factors and trip attributes, directly impacting energy use. Comparative analyses of four metropolitan areas revealed distinct regional driving profiles influenced by local development density and road network structures. Furthermore, the research demonstrated that providing eco-friendly route information and alerts for aggressive driving can effectively modify traveler behavior, leading to smoother driving styles and reduced fuel consumption. The significance of this work lies in its provision of empirical evidence linking specific land-use and technology strategies to measurable environmental outcomes. By bridging macroscopic planning tools with microscopic behavioral data, the study offers planners and policymakers robust analytical building blocks for evaluating sustainable urban development. The findings support the implementation of compact growth strategies and ITS applications, such as eco-routing and driver alerts, as viable methods for achieving state and national emission reduction goals. This integrated approach enhances the scientific understanding of how behavioral changes and infrastructure design jointly contribute to livable, sustainable communities.

Key finding

Households residing in mixed land use neighborhoods with good network connections produced approximately 9 percent less carbon dioxide emissions than those in conventional developments.

Methodology

dataset

Sample size: 15213

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• exposure measurement
• urban rural setting
• eco driving
• speed choice

Information type

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• Empirical Findings: observational prevalence
• Methodological Resource: dataset resource
• Theoretical Contribution: computational model