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With rising income and the emergence of modern shopping centers in urban China, shopping trips by private car becomes more and more common, leading to higher carbon emissions in the transport sector. Encouraging car owners to shift transport mode from private car to public transport could achieve significant emissions reductions. This study estimat...
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Context 1
... this section, we analyze the two primary modes of transport (private car and public transport) with regard to their carbon emissions. On average, shoppers travel 9.3 km and produce 426.9 g of carbon emissions. The weekend figure is 451.7 g which is 13% higher than the weekday figure. Carbon emissions per shopper are higher at the weekends because more people drive and travel longer distances (10.2 km; 21% higher than weekdays). Figure 4 shows the average carbon emissions of private cars and public transport. Private car emissions are 5 times higher than those of public transport. On weekends, carbon emissions from cars increase to 1230.5 g, which are 5.6 times higher than public ...
Context 2
... emissions per shopper are higher at the weekends because more people drive and travel longer distances (10.2 km; 21% higher than weekdays). Figure 4 shows the average carbon emissions of private cars and public transport. Private car emissions are 5 times higher than those of public transport. ...
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Citations
... Based on the literature review of the factors influencing carbon emissions in Section 2.1, 11 relevant factors were identified. In addition, SO 2 emissions are considered to be closely related to greenhouse gas emissions [53]; with the improvement of living standards, the number of private cars has increased significantly and the carbon emissions of private trips are five times higher than those of public transportation [54]. Based on this, this study included SO 2 emissions and civil vehicle ownership in the analysis and finally aggregated and identified 13 influencing factors related to carbon emissions as candidates. ...
Driven by China’s peak carbon emissions and carbon neutrality goals, each region should choose a suitable local implementation path according to local conditions, so it is of great significance to mine and analyze the critical influencing factors of regional carbon emissions. Therefore, this paper integrates grey relation analysis (GRA) and an improved STIRPAT model and selects the Yangtze River Delta region of China as the research object to analyze the factors affecting carbon emissions in four provinces in the region. Firstly, it uses the IPCC method to calculate the energy carbon emissions of each province. Secondly, according to the existing research, the relevant influencing factors of carbon emissions are sorted and summarized as candidate sets and this paper uses GRA to calculate the correlation degree of the above candidate sets. On this basis, this paper combines with the characteristics of the improved STIRPAT model to determine the index selection criteria and filter out the critical factors of each province. Thirdly, an improved STIRPAT model is constructed for each province to explore the influence of critical factors and analyze the influencing factors of carbon emissions in detail. The empirical results show that during the period from 2005 to 2019, the carbon emissions of the four provinces in the Yangtze River Delta are significantly different in structure and trend. At the same time, the critical influencing factors of each province are different and the influence of the same factor on different regions is significantly different. Finally, the policy suggestions for the provinces to achieve their peak carbon emissions and carbon neutrality goals are precisely tailored to the different carbon emission influencing factors.
... Zegras and Srinivasan (2006) point out the fall in share of passenger trips in public transport in China despite growth in the number of public transit vehicles. Private vehicle ownership in China is reportedly rising and use of public transport is simultaneously declining (Li et al., 2015;Mu and de Jong, 2012). In India, on the other hand, a sizeable section of population still does not own automobiles and relies a great deal on use of public transport (Goel and Mohan, 2020). ...
... Other socioeconomic factors, such as employment, level of education also act as important determinants of public transport use. Li et al. (2015) conducted a study in Brisbane, Australia and conclude that regions with low socioeconomic status, determined by ownership of house, employment, educational status and income, have high transportation cost of public transport. ...
Purpose
Using primary survey data from an urban area in Global North, this study aims to examine the impact of sociodemographic factors on perception of usefulness of public transport and the importance of safety in preferring private modes of transport over public.
Design/methodology/approach
The study uses stratified random sampling technique to collect data on travel behavior and socioeconomic characteristics. Descriptive statistics complemented with bivariate probit model and seemingly unrelated bivariate probit model is implemented on the data obtained.
Findings
The study finds that women, unmarried individuals, the youngest age group, least educated individuals and those who are working are expected to finding public transport more useful as compared to their respective counterparts. Despite finding the mode most useful, women are more likely to find it unsafe to travel.
Research limitations/implications
The study calls attention to not only dealing with the infrastructural changes in system but also with those attached insecurities which limit its use.
Originality/value
To the best of our knowledge, this is the first time a comprehensive evaluation of the demands and challenges for transportation services faced by different segments of the society is carried out in this section of the developing world.
... Transportation modes (e.g., walking, bus, metro and private car) induced by physical shopping are categorized by distance (SD). CO 2 emission intensities (g/person·km) for transport modes are adopted from a previous study (Li et al., 2015). CO 2 emissions induced by offline shopping were calculated with the following equation: ...
... From our data and analysis, we found that residents with monthly incomes of less than 2000 CNY, 2000-3000 CNY and 3000-5000 CNY were 0.421 times, 0.522 times and 0.588 times more likely to choose non-low-carbon modes during shopping trips, respectively, than residents with monthly income higher than 5000 CNY. Along with rising personal disposable incomes and an expanding middle class buying private cars as soon as they can afford to, private automobile ownership and usage are increasing, while public transport usage has almost universally declined in China in the past decades [76,77]. ...
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.
... While there are some studies on the interaction between shopping and transportation, they are primarily trip based: e.g. trip generation for shopping purposes (Department for Transport, 2016), mode choice for shopping trips (Ibrahim, 2005), effects of congestion charge on shopping trips (Schmocker et al., 2006) or reduction in carbon emissions from shopping trips (Li et al., 2015). There are planning guidelines and regulations in most developed and many developing countries, which regulate the quantity of parking to be made available in a new shopping facility (e.g. in the UK, USA). ...
Shopping and retail trade play an important role in the economy, yet shopping activities and associated on-street parking and disruptions to traffic could substantially contribute to congestion in the megacities of the developing and emerging countries. This research investigates and quantifies the effects of shopping and related road-side frictions and disruptions on congestion in a city. We make use of minute by minute GPS tracking data of vehicles and a unique policy of different shopping closure days in different areas of the city, which allows the separation of shopping related congestion effects from commute and other effects. Results show that average speed increased by 18.5% on weekdays when shopping centres were closed. The differences in speed in the different zones can also be qualitatively related with the density of shopping centres in those zones.
... In addition, most studies only focus on travel behavior and CO 2 emissions from commuting [25,[37][38][39]. There is still much to learn concerning the effect of environmental factors on daily travel for non-work purposes, especially shopping trips [40,41]. Therefore, our study contributes to the existing studies on China's sustainable transport by comparing transport mode choice and its impacts on CO 2 ...
... Shenyang is the capital city of Liaoning Province and the largest city in northeast China [41,42]. It includes nine districts: Heping, Shenhe, Dadong, Huanggu, Tiexi, Sujiatun, Hunnan, Yuhong and Shenbei, with a total area of 3471 km 2 and a total population of 5.3 million. ...
Shifting toward sustainable daily travel will play a significant role in the future of sustainable development and the lowering of carbon emissions. This study provides an in-depth comparison of transport mode choice and corresponding CO2 emissions between private cars and public transport used for shopping trips based on individual data from a travel survey conducted in Shenyang, China. The analysis found that bus travel accounted for the majority of motorized transportation. Public transport users were closely distributed along the bus or metro lines, and aggregated private car users were mainly clustered within the second circumferential road. Furthermore, average per trip emissions for private car travel were 8-fold that of public transport. Binary logistic regression modeling was employed to examine factors that were related to the choice between private car and public transport, and the results indicated that car ownership and gender were the most important factors in explaining the preference of car driving. Age and per capita monthly income were negatively correlated with car driving. In addition, there were also negative impacts associated to the built environment factors of access to the closest metro stations and the number of bus stops near the residence on car driving. This study is vital to formulate more effective transportation policy measures in the future development for a sustainable low-carbon city. DOWNLOAD HISTORY | This article has been downloaded 775 times in Digital Commons before migrating into this platform.
... However, these studies on CO 2 emissions largely focused on people's intra-urban shopping trips and overlooked human trips for other purposes. Li et al. (2015) studied China's low-carbon transportation from two aspects, namely, private cars and public transport. The quantitative comparison of CO 2 emissions for shopping trips showed that emissions produced by private cars are five times higher than those by public transport and emissions on weekends are higher than emissions on weekdays. ...
... For example, convenient public transport facilities (e.g., bus and subway) should be constructed around residential and working places. Previous studies also demonstrate that CO 2 emission intensity of taxi is far higher that of bus and subway (Ma et al., 2011;Chai et al., 2012;Li et al., 2015). Hence, taking bus or subway rather than taxi is one efficient way to facilitate urban sustainable development. ...
Traffic-related carbon dioxide (CO2) emissions have become a major problem in cities. Especially, the CO2 emissions induced by taxis account for a high proportion in total CO2 emissions. The availability of taxi trajectory data presents new opportunities for addressing CO2 emissions induced by taxis. Few previous studies have analyzed the impact of human trips on CO2 emissions. This paper investigates trip-related CO2 emission patterns based on individuals' travel behavior using taxi trajectory data. First, we propose a trip purpose inference method that takes into account the spatiotemporal attractiveness of POIs to divide human trips into different types. Further, we reveal the spatiotemporal patterns of CO2 emissions from various types of trips, including temporal regularity and periodicity as well as spatial distribution of “black areas”. Finally, comparative analysis of CO2 emissions for different kinds of trips based on trip behavior is conducted using three variables, namely trip distance, trip duration and trip speed. This study is helpful for us to understand how to make travel and cities more sustainable through modifying people's trip behaviors or taxi trips.
... With economic and social development, retailing in China has entered a phase of rapid growth, especially with regard to the emergence of large-scale commercial centers, and many cities are transforming or have transformed from producing cities to consuming cities [28]. With an increasingly affluent middle class buying cars as soon as they can afford to, Chinese cities are also becoming increasingly congested with automobiles [29]. According to the China Statistical Yearbook, the number of small private passenger cars nationwide has increased from 10.8 million to 105.9 million from 2005 to 2014 (an annual growth rate of 31.1%). ...
... Technological measures and policies can reduce carbon emissions to a certain extent. Nevertheless, policymakers in China can realize their low-carbon agenda by optimizing urban form, ensuring safety and comfort of low-carbon public transport modes (in particular, subway-based mass transit systems), investing in basic transport infrastructure, connecting city centers to suburban areas, developing sustainable transport intervention (e.g., parking regulations, vehicle and fuel taxes, and congestion taxes), and promoting low carbon consumption behaviors, all of which crucially influence shoppers' choice of travel mode [29,52]. ...
Current literature highlights the role of commercial centers in cities in generating shopping trips and transport carbon emissions. However, the influence of the characteristics of commercial centers on consumer travel behavior and transport carbon emissions is not well understood. This study addresses this knowledge gap by examining shopping trips to eight commercial centers in Shenyang, China, and the CO2 emissions of these trips. We found that the locations and types of commercial centers strongly influence CO2 emissions. CO2 emissions per trip to commercial centers in the suburbs of Shenyang were on average 6.94% and 26.92% higher than those to commercial centers in the urban core and the inner city, respectively. CO2 emissions induced by wholesale centers were nearly three times higher than the lowest CO2 emissions of commercial centers in the inner city. These empirical results enhance our understanding of shopping-related transport carbon emissions and highlight the importance of optimizing urban space structure, in particular, the layout of commercial centers.
