Location, Vehicle Miles of Travel, and the Environment: A Chicago Case Study

Reduction of greenhouse gas emissions from personal vehicles, accountable for 62% of U.S. transportation emissions, requires strategies sensitive to the relationship between drivers and urban spaces. This research explores the hypothesis that urban location significantly impacts this relationship by analyzing recent vehicle miles of travel (VMT) data from a Chicago household travel survey. The goal is to take this understanding and devise strategies to reduce both VMT and greenhouse gas emissions.;Regional household data were aggregated to probe spatial profiles of VMT, energy consumption, and greenhouse gas emissions for interesting patterns. Scenarios tests for reducing driving/emissions included calculating savings from fleet substitution and application of future fuel economy standards. The feasibility of shifting drivers to train for work commutes considering proximity of households and work destinations to rail stations was also tested. Finally, market segmentation techniques and canonical correspondence analysis (CCA) were used to investigate household heterogeneity and suburban driving, respectively, as they relate to the local impact of demographic, urban-form, and employment variables. Both statistical techniques have not been previously used for VMT analysis.;VMT on the city's fringe exceeded that of the city center; higher fringe energy consumption/emission values resulted from extensive driving and low-efficiency vehicle use. Scenario tests revealed possible consumption/emission savings of up to 48% from application of future European fuel economy standards. Up to 71% of the work trips originating from homes within 1 mile of stations also terminated at destinations within 1 mile, 61% of these being automobile trips, signaling the potential for mode shift. Shifting these trips could reduce all energy associated with driven work commutes by 24%. Market segmentation revealed that Chicago's North side was associated with higher residential density and less driving than the South side, a region of greater employment and dispersed rail stations. The result cemented how simple distance from the city center inadequately predicted driving behavior. CCA revealed that residential density predominantly influenced low driving (as compared to other driving segments), all other urban-form variables and agrarian employment impacted high driving, and demographics influenced moderate driving, which was associated with the majority of suburbs. Knowledge of these local behavioral variations will yield more effective, targeted policy for reducing driving.