The Impact of Residential Density on Vehicle Usage and Energy Consumption

By T. Golob, David Brownstone. 2005

605 citations recorded by the source corpus.

Subfields: Renewable Energy, Sustainability and the Environment, Transportation

View Paper: https://www.semanticscholar.org/paper/319a0cb816f1193fc011d2af52dddd4c79a9eebc

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In Renewable Energy, Sustainability and the Environment

In Transportation

Citations in the corpus

The paradox of intensification (2011, methodology): “In the USA, where higher income groups generally prefer suburban living, there is a strong negative correlation between income and population density (Brownstone and Golob, 2009, Horning et al, 2008).”
A New Generalized Heterogeneous Data Model (GHDM) to Jointly Model Mixed Types of Dependent Variables (2015, background): “, 2012), as do households with many young active adults (Brownstone and Golob, 2009).”
Evolving Narratives of Low-Carbon Futures in Transportation (2016, background): “Similarly, a reasonable increase in population density in California would decrease fuel consumption by only 5.5% (Brownstone & Golob, 2009).”
Are compact cities environmentally friendly (2012, neutral): “ =  +  ( − ) with  6=  where  is given by (3) and  =  + ,  being the number of firms located in city  (with 1 + 2 = ).”
Beyond Technology: Demand-Side Solutions for Climate Change Mitigation (2016, background): “Modeling studies of California and England find a demand decrease of approximately 5% for reasonable compactification scenarios over the next 30 years (21, 40).”
Alternative Modeling Approaches Used for Examining Automobile Ownership: A Comprehensive Review (2014, methodology): “The methodological approaches applied to model car ownership range from simple linear regression to complex econometric formulations taking into account a rich set of covariates (Brownstone and Golob, 2009).”
A Meta-Analysis of Global Urban Land Expansion (2011, background): “The spatial form of cities, especially urban transportation infrastructure and residential density, affects travel demand [9], energy consumption [10], and automobile use [11].”
A discrete–continuous model of households’ vehicle choice and usage, with an application to the effects of residential density (2008, background): “Empirical studies have found that elements of urban spatial structure, particularly higher residential density, are associated with lower private vehicle utilization (Cervero and Kockelman 1991, Dunphy and Fisher 1996, and Golob and Brownstone 2005 etc.).”