Determinants of CO2 emissions from household daily travel in Beijing, China: Individual travel characteristic perspectives

Examining the Uneven Distribution of Household Travel Carbon Emissions Within and Across Neighborhoods: The Case of Beijing

“…Household income is another factor that generally promotes higher HTCEs, and has a significant coefficient in Model 1. This finding agrees with the results of other studies (e.g., Ko et al., 2011; Qin and Han, 2013; Wang and Liu, ). Moreover, this study shows that the interaction between household income and HTCEs varies according to family income group and neighborhood type (Figure ).…”

“…Numerous studies have demonstrated the unevenness of territorial-based TCEs at the national, regional and city levels (Scholl, Schipper, and Kiang, 1996;Greening et al, 1997;Duro and Padilla, 2006). A number of recent studies have focused on TCE variations at the household and individual levels (Brand and Boardman, 2008;Susilo and Stead, 2009;Brand and Preston, 2010;Ko et al, 2011;Qin and Han, 2013;Ma et al, 2015;Wang and Liu, 2015). These population-based TCE variations have been demonstrated by a variety of methods, including the varying coefficient, cumulative percentage curve, Gini coefficient and distribution rule methods (Duro and Padilla, 2006).…”

“…Second, individual residential variations (e.g., location, population density, land use, and transport accessibility) promote interpersonal travel behavior and TCEs differences. Residents living in traditional high-density, mixed land-use neighborhoods are likely to drive less and thus emit fewer TCEs (Cervero and Duncan, 2003;Grazi, van den Bergh, and van Ommeren, 2008;Chatman, 2009;Druckman and Jackson, 2009;Cao, 2010;Hong and Goodchild, 2014;Ma et al, 2015;Wang and Liu, 2015). In addition, individual travel behaviors are significantly influenced by travel preference and self-selection when making residential and travel decisions.…”

Life-cycle private-cost-based competitiveness analysis of electric vehicles in China considering the intangible cost of traffic policies

“…The energy consumption of the transportation sector accounts for 20% of the total energy consumption in China [1] and is responsible for 8% of the total GHG emissions nationwide [2]. Because this ratio would be significantly higher in large cities and has become the primary cause of pollution haze [3], the reduction of GHG emissions in the transportation sector is a top priority of the government [4,5]. Because battery electric vehicles (BEVs) produce zero emissions during operation, they have been considered a most promising means of mobility toward reducing the GHG emissions of the transportation sector in the future.…”

Contribution of the transport sector to climate change mitigation: Insights from a global passenger transport model coupled with a computable general equilibrium model

“…Because the continuing growth in traffic activities could outweigh all mitigation measures unless transport emissions can be strongly decoupled from gross domestic product (GDP) growth, decarbonizing the transport sector will be more challenging than for other sectors [4,5]. It has been proposed that transport-related GHG emissions are bound up with economic development, technological change, travel behavior, transport policy, and energy efficiency improvements [2,[6][7][8][9][10][11]. Therefore, the key factors influencing global passenger transport, including travel mode and technological details, need to be taken into account to estimate long-term transport-related GHG emission pathways.…”