Land use policies and transport emissions: Modeling the impact of trip speed, vehicle characteristics and residential location

Hong, Jinhyun; Goodchild, Anne

doi:10.1016/j.trd.2013.10.011

Cited by 62 publications

(39 citation statements)

References 2 publications

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“…In addition, people living in neighborhoods where many jobs are located tend to generate fewer transportation emissions, mainly due to the short commuting trips. These results are consistent with previous land usetransportation emissions analyses (Hong and Goodchild 2014;Stone, 2007) and support the claim of smart growth, implying the usefulness of land-use policy.…”

Section: Discussionsupporting

confidence: 91%

“…VMT is highly correlated with the fuel consumption and transportation emissions, thus the above finding supports the potential use of land-use policies to reduce transportation emissions. Moreover, some studies examined the direct relationship between land-use factors and transportation emissions while controlling for other influential factors such as socio-demographics and vehicle characteristics, and found their significant associations (Frank, Stone, and Bachman 2000;Barla et al 2010;Hong and Goodchild 2014;Lee and Lee 2014). Even though previous findings provide useful implications to planners and policy makers, most of results are limited because they do not consider a potential non-linear relationship between the built environment and transportation emissions.…”

Section: Introductionmentioning

confidence: 99%

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Non-linear influences of the built environment on transportation emissions: Focusing on densities

Hong

2015

JTLU

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Compact development is often recommended to reduce auto-dependency thereby decreasing related energy consumptions and transportation emissions. However, there could be a non-linear relationship between density and transportation emissions because of a possible non-linear association between density and vehicle miles travelled (VMT); low travel speed due to congestion; and the relationship between neighborhood characteristics and vehicle characteristics (e.g., vehicle type and age). In addition, the self-selection issue can exist in the land use-transportation emissions analysis because transportation emissions are often estimated based on travel behavior. Using the 2006 Puget Sound Regional Council (PSRC) Household Activity survey, the follow-up stated preference survey, the Motor Vehicle Emission Simulator (MOVES) data, and the GIS network data, this study investigates the non-linear effects of densities on CO 2 equivalent (CO 2 e) emissions with the consideration of self-selection. Specifically, quadratic forms of population and employment densities, different population density group indicators, and attitudinal factors are employed in the regression models. The results indicate that people living in denser neighborhoods tend to generate fewer CO 2 e emissions. However, this effect becomes insignificant as population density reaches a certain level.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Non-linear influences of the built environment on transportation emissions: Focusing on densities

Hong

2015

JTLU

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“…The spatial autocorrelation is also proven to exist in accidents that happen on suburban highways [55]. Moreover, the relationship between transport emissions and land use is estimated and the CAR model is found to be effective in representing the spatial autocorrelation [27]. Most statistical models ignoring the spatial autocorrelation could lead to misunderstanding the role played by the built environment in car ownership and use.…”

Section: Spatial Effects In City Contextmentioning

confidence: 99%

“…Second, few prior studies exploring the impacts of the built environment on car dependency take into account spatial autocorrelation, which might lead to misunderstanding the role the built environment plays. The spatial autocorrelation, which has been studied in spatial economics by several approaches and proven to create an effect on travel behavior [26][27][28], is still rarely considered in existing studies.…”

Section: Introductionmentioning

confidence: 99%

Application of Bayesian Multilevel Models Using Small and Medium Size City in China: The Case of Changchun

et al. 2018

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Concerns about transportation energy consumption and emissions force urban planners and policy makers to pay more attention to the effects of car ownership and use on the environment in China. However, few studies have investigated the relationship between the built environment and car ownership and use in China, especially in mid-sized and small cities. This study uses Changchun, China as a case study and examines the potential impacts of the built environment and socio-demographics on car ownership and use for commuting simultaneously using Bayesian multilevel binary logistic models. Furthermore, the spatial autocorrelation of car ownership and use is recognized across traffic analysis zones (TAZs), which are specifically represented by the conditional autoregressive (CAR) model. The estimated results indicate that socio-demographic characteristics have significant effects on car ownership and use. Moreover, the built environment measured at the TAZ level still shows a significant association with other factors controlled. Specifically, it suggests that denser residential density, compact land use, better transit services and street connectivity can reduce car dependency more effectively. This study provides new insights into how the built environment influences the car ownership and use, which can be useful for urban planners and policy makers to develop strategies for reducing car dependency.

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“…This environment problem is being studied using a holistic approach to understand the influence of land use on transportation emissions in urban and suburban areas (Hong and Goodchild 2014;Monzón et al 2007). Urban transport solutions, behind the inherent efficiency requisites, must be improved to raise the quality of life and the cities environment (Yigitcanlar et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Traffic air pollution monitoring based on an air–water pollutants deposition device

Silva

Pinho

Nurusman

2014

Int. J. Environ. Sci. Technol.

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An air water surface sampler device was developed and used to evaluate the atmosphere deposition due to the urban traffic air pollution in the business center of a mid-sized city. The indicator adopted to assess the cumulative air pollutant deposition in the surface of the device was the electric conductivity that was measured on a regular basis during the experiment. Additionally, a digital camera was used to count the passing traffic in the road of the study site. Water samples were also taken from the device reservoir, and dissolved metal concentrations (copper, iron and zinc) and acidity/alkalinity were determined in the laboratory. The obtained results were compiled and analyzed in order to evaluate the performance of the device and the relation between the atmospheric deposition and the traffic activity under different meteorological conditions. The research successfully proved that the device was able to evaluate the impact of pollutant emissions related to city traffic. It was also proved that electric conductivity can be used as an indicator to evaluate the cumulative deposition of air pollutants from road traffic. A significant correlation (Spearman's rank) between the accumulated traffic and electric conductivity (dry period: . = 0.991626 and wet period: . = 0.810526) was observed.

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Land use policies and transport emissions: Modeling the impact of trip speed, vehicle characteristics and residential location

Cited by 62 publications

References 2 publications

Non-linear influences of the built environment on transportation emissions: Focusing on densities

Non-linear influences of the built environment on transportation emissions: Focusing on densities

Application of Bayesian Multilevel Models Using Small and Medium Size City in China: The Case of Changchun

Traffic air pollution monitoring based on an air–water pollutants deposition device

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