Residential density and transportation emissions: Examining the connection by addressing spatial autocorrelation and self-selection

Jinhyun Hong, Qing Shen

Research output: Contribution to journalArticlepeer-review

46 Scopus citations

Abstract

This paper examines the effect of residential density on CO2 equivalent from automobile using more specific emission factors based on vehicle and trip characteristics, and by addressing problems of spatial autocorrelation and self-selection. Drawing on the 2006 Puget Sound Regional Council Household Activity Survey data, the 2005 parcel and building database, the 2000 US Census data, and emission factors estimated using the Motor Vehicle Emission Simulator, we analyze the influence of residential density on road-based transportation emissions. In addition, a Bayesian multilevel model with spatial random effects and instrumental variables is employed to control for spatial autocorrelation and self-selection. The results indicate that the effect of residential density on transportation emissions is influenced by spatial correlation and self-selection. Our results still show, however, that increasing residential density leads to a significant reduction in transportation emissions.

Original languageEnglish
Pages (from-to)75-79
Number of pages5
JournalTransportation Research Part D: Transport and Environment
Volume22
DOIs
StatePublished - Jul 2013

Keywords

  • Confounding by location
  • Residential density
  • Self-selection
  • Transportation emissions

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