Evaluating the dynamic impacts of urban form on transportation and environmental outcomes in US cities

Abstract

Previous urban sprawl studies have typically taken a cross-sectional approach without examining how sprawling urban areas are performing over time. Longitudinal studies of individual or household travel behavior and built-environment preference have made some progress in this direction, but very few studies have explored the longitudinal interaction of urban form with transportation and environmental outcomes. This study begins to fill this gap by evaluating the transportation and environmental impact dynamics of several key dimensions of urban sprawl: density, land use mix, centrality, and street connectivity. The central hypothesis is that while the built environment is durable and development patterns change slowly, the impacts of urban sprawl are dynamic rather than static and are accelerated in more sprawling cities relative to less sprawling cities. To test this hypothesis, a panel dataset of 7 years (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007) was developed for 60 Metropolitan Statistical Areas of the US and a hybrid modeling framework that incorporates fixed and random effects is applied to evaluate different transportation and environmental outcomes over time. We found that the influence of urban centrality or the strength of urban subcenters on the travel pattern of commuters and transit users is dynamic. This suggests that people living in cities with stronger centers drive less and use public transportation more over time. For environmental outcomes, we found that cities with higher density have experienced a significant decrease in ambient ozone and PM 2.5 concentrations after controlling city-specific variables.

Impact of Population Density on PM2.5 Concentrations: A Case Study in Shanghai, China

“…Previous studies have used multifarious research strategies to estimate the influence of built environment attributes on air pollution [29,[65][66][67]. Given that administrative divisions do not constrain the diffusion of PM 2.5 , we expect significant spatial dependency between adjacent regions, which violates the independent distribution assumption of the error term in OLS estimation.…”

The Impacts of Urban Air Pollution Emission Density on Air Pollutant Concentration Based on a Panel Model

“…Previous studies related to urban structure examined the relationship of air quality with urban sprawl, compact, and indicators (e.g., density, distance network, and complexity). They focused on explaining the relationship with linear pollution sources (cars, roads, and traffic volume) associated with traffic among various air pollution sources in cities [8,[21][22][23][24][25]. Consequently, it is necessary to comprehensively consider the structural characteristics of the various air pollution sources affecting the air pollution concentration in urban areas.…”

Low-Carbon Transportation Oriented Urban Spatial Structure: Theory, Model and Case Study

“…The evidence suggests that the influence of urban spatial structure on transport-related energy consumption and emissions is profound. Urban sprawl will significantly increase the commuting time [35]. Travisi et al used a mobility impact index (IMPACT) based on commuting data on 739 Italian cities and empirically proved that sprawl contributes to move job opportunities to peripheral areas and the congestion virtually follows jobs to the periphery and increases travel demand [36].…”