Effects of rural built environment on travel-related CO 2 emissions considering travel attitudes

Yibin Ao, Dujuan Yang, Chuan Chen, Yan Wang, 2019, in Transportation Research Part D

doi:10.1016/j.trd.2019.07.004
Location Sichuan, China
Population General
Sample size 1758
Factor analysis type exploratory factor analysis, unknown rotation
Stepwise regression no
Removal of insignificant variables no
Reviewed by NAH

Abstract

This study contributes to the understanding of the impacts of the rural built environment on travel-related CO2 emissions by considering the mediating effects of household car ownership, travel frequency, travel distance, and individual travel attitudes through structural equation modeling. The travel data were collected from an activity diary survey in rural Sichuan. Geographic information system technology, combined with on-site measurement, was used to obtain data on the built environment. After controlling the socio-demographic factors, the model results corroborate that all built environment variables had significant total effects on car ownership, travel distance, travel frequency, and travel emissions. Specifically, residents living in the village with more accessible markets, higher roads, and higher building density travel a shorter distance and emit less CO2. Meanwhile, residents living in the village with centralized living style and higher transit and destination accessibility travel less frequently but emit more CO2. Individual travel attitudes have a limited effect on travel behavior and CO2 emissions. This study suggests that planners and policymakers should consider shortening the distance between destination/transit and residential areas and increasing road and building densities. Moreover, promoting the construction of bicycling facilities and separate bicycle lanes to encourage rural residents to ride electric bicycles, bicycles, and motorcycles will reduce transport CO2 emission in Chinese rural areas. © 2019 Elsevier Ltd

Factors

Variable Pattern loading
There is no economic pressure to buy a car (Cost) 0.811
Variable Pattern loading
I often make reasonable arrangements to minimize the number of outings (Convenience) 0.726
For problems that can be resolved by the telephone or the Internet, they will not be resolved on site. (Other) 0.793
Variable Pattern loading
It is safe and environmentally friendly to ride motorcycles (Environmentalism) 0.523
The low cost of motorcycle purchase and use poses no economic burden at all (Cost) 0.771
Motorcycle parking is convenient (Convenience) 0.696
Variable Pattern loading
It is quick and easy to ride electric bicycles (Convenience) 0.769
It is safe and environmentally friendly to ride electric bicycles (Safety) 0.828
The low cost of electric bicycle purchase and use poses no economic burden at all (Cost) 0.591
Electric bicycle parking is convenient (Convenience) 0.586
Variable Pattern loading
Cycling exercises your body (Lifestyle) 0.762
Cycling is a low-carbon, environmentally friendly travel mode (Environmentalism) 0.767
Bicycle parking is convenient (Convenience) 0.738
The low cost of bicycle purchase and use poses no economic burden at all (Cost) 0.588
Quick and easy to walk (Convenience) 0.602
Walking exercises your body (Lifestyle) 0.742
Walking is a low-carbon and environmentally friendly travel mode (Environmentalism) 0.724
Variable Pattern loading
The price of gasoline affects my choice of travel mode (Cost) 0.739
Parking costs are high everywhere, and driving is not worthwhile (Cost) 0.754

Models

Source variable Target variable Effect p-value Effect type
respondent rides autobike use_cost -0.094 <0.1 direct_effect
income pro_Ab 0.151 <0.01 direct_effect
Number of convenient markets pro_Ab -0.873 <0.05 direct_effect
transit accessibility pro_Ab 0.542 <0.01 direct_effect
road density pro_Ab 0.28 <0.01 direct_effect
building density pro_Ab -1.05 <0.01 direct_effect
centralized living style pro_Ab 0.514 <0.05 direct_effect
destination accessibility pro_Ab 0.932 <0.01 direct_effect
male pro_Eb -0.098 <0.1 direct_effect
age pro_Eb 0.203 <0.01 direct_effect
respondent rides ebike pro_Eb 0.31 <0.01 direct_effect
respondent rides ebike less_out 0.129 <0.01 direct_effect
Number of convenient markets less_out -0.491 <0.1 direct_effect
building density less_out -0.415 <0.05 direct_effect
centralized living style less_out 0.388 <0.01 direct_effect
destination accessibility less_out 0.522 <0.01 direct_effect
respondent rides bicycle pro_wb 0.118 <0.1 direct_effect
Number of convenient markets pro_wb -0.268 <0.01 direct_effect
transit accessibility pro_wb -0.303 <0.01 direct_effect
road density pro_wb 0.138 <0.05 direct_effect
building density pro_wb 0.158 <0.01 direct_effect
male car -0.114 <0.05 direct_effect
age car 0.111 <0.05 direct_effect
income car 0.278 <0.01 direct_effect
driver's license car 0.262 <0.01 direct_effect
respondent rides autobike car -0.16 <0.01 direct_effect
respondent rides bicycle car 0.208 <0.01 direct_effect
Number of convenient markets car -1.359 <0.01 direct_effect
transit accessibility car 0.524 <0.01 direct_effect
road density car 0.223 <0.01 direct_effect
building density car 0.163 <0.01 direct_effect
centralized living style car 0.817 <0.01 direct_effect
destination accessibility car 1.114 <0.01 direct_effect
age Distance -0.117 <0.05 direct_effect
income Distance 0.119 <0.05 direct_effect
driver's license Distance 0.136 <0.05 direct_effect
Number of convenient markets Distance -0.645 <0.05 direct_effect
road density Distance -0.159 <0.01 direct_effect
building density Distance -0.432 >0.1 direct_effect
centralized living style Distance 0.308 <0.05 direct_effect
destination accessibility Distance 0.349 <0.1 direct_effect
driver's license Trips 0.108 <0.05 direct_effect
transit accessibility Trips -0.854 <0.01 direct_effect
road density Trips -0.269 <0.01 direct_effect
building density Trips 0.433 <0.01 direct_effect
centralized living style Trips -0.247 <0.01 direct_effect
destination accessibility Trips -0.515 <0.01 direct_effect
driver's license travel-related CO² emissions 0.135 <0.01 direct_effect
destination accessibility travel-related CO² emissions -0.059 <0.1 direct_effect
use_cost car -0.114 <0.05 direct_effect
pro_Ab Trips 0.073 <0.1 direct_effect
pro_Eb Trips 0.148 <0.01 direct_effect
car Trips 0.122 <0.05 direct_effect
use_cost travel-related CO² emissions -0.063 <0.05 direct_effect
car travel-related CO² emissions 0.081 <0.05 direct_effect
Distance travel-related CO² emissions 0.795 <0.01 direct_effect
Trips travel-related CO² emissions -0.146 <0.01 direct_effect

The Attitudes and Travel Database is produced with support from the Center for Teaching Old Models New Tricks at Arizona State University, a University Transportation Center sponsored by the US Department of Transportation through Grant No. 69A3551747116.

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