Consumer Travel Behaviors and Transport Carbon Emissions: A Comparative Study of Commercial Centers in Shenyang, China

Li, Jing; Lo, Kevin; Zhang, Pingyu; Guo, Meng

doi:10.3390/en9100765

Cited by 10 publications

(7 citation statements)

References 43 publications

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“…Commercial services have been greatly improved, with retail sales of consumer goods reaching 363.61 billion RMB in 2015. Eight typical commercial centers were selected as our field sites based on their location characteristics and types of retail present [ 57 ]. Middle Street and Taiyuan Street are two municipal commercial centers at the city center, with a large business circle covering the entire municipality of Shenyang, and even extending to surrounding cities.…”

Section: Methodsmentioning

confidence: 99%

Do Socio-Economic Characteristics Affect Travel Behavior? A Comparative Study of Low-Carbon and Non-Low-Carbon Shopping Travel in Shenyang City, China

Guo

2018

IJERPH

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Choices regarding mode of travel have an evident effect on environment pollutants and public health. This paper makes a significant contribution by examining the differences between low-carbon and non-low-carbon travel mode choices during shopping trips, and how socio-economic characteristics impact individual travel behavior based on data gathered from a questionnaire conducted in Shenyang, China. The study found that, firstly, low-carbon travel modes were more common than non-low-carbon travel modes for shopping, and the average travel distance by non-low-carbon modes was a little longer than that of low-carbon modes. Secondly, suburban and wholesale specialized commercial centers attracted more residents travelling longer distances by non-low carbon modes, especially private car, compared to regional commercial centers in inner city areas. Thirdly, strong relationships between car ownership, gender, monthly income, and travel mode choices were identified in a binary logistic regression model. This study thus highlights the importance of sustainable transportation policies to advocate low-carbon travel modes and reduce carbon emissions.

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Section: Methodsmentioning

confidence: 99%

Do Socio-Economic Characteristics Affect Travel Behavior? A Comparative Study of Low-Carbon and Non-Low-Carbon Shopping Travel in Shenyang City, China

Guo

2018

IJERPH

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“…They further established that innovation and infrastructure development with an increased absorptive capacity could help lessen the carbon intensity of China and the US. Li et al [26] found that the average CO 2 emissions of suburban commercial centers were 6.94% and 26.92%, which are higher than those of urban commercial centers. The CO 2 emissions of wholesale centers were nearly three times less than those of the inner-city commercial centers.…”

Section: Impact Of Transport Energymentioning

confidence: 99%

Energy Efficiency in Transportation along with the Belt and Road Countries

et al. 2020

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China’s huge investment in the “belt and road initiative” (BRI) may have helped improve the economic level of participating countries, but it may also be accompanied by a substantial increase in greenhouse gas (GHG) emissions. The BRI corridors aim to bring regional stability and prosperity. In such efforts, energy efficiency due to increased transport has been overlooked in the recent literature. This paper employed a data envelopment analysis of the slack-based measurement (SBM) for bad output to assess the transport energy efficiency of 19 countries under the BRI economic corridors. By using the most cited transport-related input variables, such as vehicles, labor, motor oil, jet fuel, and natural gas, this study first analyzes the transport energy efficiency by first assuming the output variables individually and then takes two years as a pre- and post-BRI case by considering the aggregated output model. The results show an increase in economic activity but a decline in transport energy efficiency in terms of consumption and emissions.

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“…where i represents the travel mode; ECO 2 is the estimated CO 2 emissions (g); F i is the average fuel consumption rate of the travel mode i (m 3 /100 km or L/100 km); ρ is the fuel density (kg/m 3 ); D is the travel distance (km); EF is the carbon emissions factor of fuel (t CO 2 /1000 Nm 3 or t CO 2 /t) and AC is the estimated transport capacity (Li et al, 2016). Carbon emissions for rail transit are demonstrated as follows:…”

Section: Model 231 Co 2 Emissions Modelmentioning

confidence: 99%

“…where p represents the travel mode; ECO 2 is the estimated CO 2 emissions (g); C is the average power consumption (kWh/100 km); D is the travel distance (km); EF is the carbon emissions factor of power (kg/kWh) and AC is the estimated transport capacity (Li et al, 2016).…”

Section: Model 231 Co 2 Emissions Modelmentioning

confidence: 99%

“…The results regarding the relationship between individual socio-economic characteristics and shoppers' travel mode choices may be beneficial in developing important policy measures for curbing the sharply increasing car ownership rates in developing countries, including sales control, fuel taxes, parking regulations, the rationing of car usage, and congestion pricing (Etminani-Ghasrodashti and Ardeshiri, 2016;Li et al, 2016). This should be coupled with technological measures through the development of new cleaner fuel and fuel efficient vehicles for reducing the adverse effects of pollution in cities in a context of relatively high car ownership and use (Andong and Sajor, 2015).…”

Section: Individual Socio-economic Characteristics and Transport Carbmentioning

confidence: 99%

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Relationship between built environment, socio-economic factors and carbon emissions from shopping trip in Shenyang City, China

Zhang

et al. 2017

Chin. Geogr. Sci.

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Promoting active travel behavior and decreasing transport-related carbon dioxide (CO 2) emissions have become a priority in many Chinese cities experiencing rapid urban sprawl and greater automobile dependence. However, there are few studies that holistically examine the physical and social factors associated with travel CO 2 emissions. Using a survey of 1525 shoppers conducted in Shenyang, China, this study estimated shopping-related travel CO 2 emissions and examined how the built environment and individual socioeconomic characteristics contribute to shopping travel behavior and associated CO 2 emissions. We found that, firstly, private car trips generate nearly eight times more carbon emissions than shopping trips using public transport, on average. Second, there was significant spatial autocorrelation with CO 2 emissions per trip, and the highest carbon emissions were clustered in the inner suburbs and between the first and second circumferential roads. Third, shopping travel CO 2 emissions per trip were negatively correlated with several built environment features including population density, the quantity of public transport stations, road density, and shop density. They were also found to be significantly related to the individual socioeconomic characteristics of car ownership, employment status, and education level using a multinomial logistic regression model. These empirical findings have important policy implications, assisting in the development of measures that contribute to the sustainability of urban transportation and meet carbon mitigation targets.

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Consumer Travel Behaviors and Transport Carbon Emissions: A Comparative Study of Commercial Centers in Shenyang, China

Cited by 10 publications

References 43 publications

Do Socio-Economic Characteristics Affect Travel Behavior? A Comparative Study of Low-Carbon and Non-Low-Carbon Shopping Travel in Shenyang City, China

Do Socio-Economic Characteristics Affect Travel Behavior? A Comparative Study of Low-Carbon and Non-Low-Carbon Shopping Travel in Shenyang City, China

Energy Efficiency in Transportation along with the Belt and Road Countries

Relationship between built environment, socio-economic factors and carbon emissions from shopping trip in Shenyang City, China

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