Neighborhood-scale urban form, travel behavior, and CO₂ emissions in Beijing: implications for low-carbon urban planning

ABSTRACT

With an increasing awareness of global climate change, the effect of urban spatial organization, at both city and neighborhood scales, on urban CO₂ emission reduction has attracted much scholarly and practical attention. Using Beijing as a case study, this article examines the extent to which neighborhood-scale urban form may contribute to reduction of travel-related CO₂ emissions in the context of rapid urbanization and spatial transformation. We derive complete travel-activity records of 1,048 residents from an activity diary survey conducted in 2007. Analysis using structural equation models finds that residents living in a neighborhood with higher land use mix, public transit accessibility, and more pedestrian-friendly street design tend to travel in a “low-carbon” manner and emit less CO₂ in daily travel, even controlling for residential and travel preferences. This article offers empirical evidence that sheds light on debates about policy measures to facilitate China’s transition toward sustainable and low-carbon urban development.

KEYWORDS:

• Urban form
• travel behavior
• CO₂ emission
• structural equation model (SEM)
• Beijing

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. In London, ground transportation is responsible for 22% of the city’s total CO₂ emissions, or 44% if aviation is included (Greater London Authority, 2007). Transportation also contributes nearly 40% of the energy-related CO₂ emissions in Portland (City of Portland Bureau of Planning and Sustainability, 2009).

2. The energy experts we interviewed indicate that this estimation remains an ongoing research but it has not yet produced final results. The report published by Lvyuan Company can be found at: http://wenku.baidu.com/view/ad60fee79b89680203d825fc.html.

3. In other words, if one resident drives 10 km in a day, his/her total travel-related CO₂ emissions would be 1.786 kg, whereas the total CO₂ emissions from daily travel would be 738 g or 91 g if the resident chooses public transportation. CO₂ emissions for walking or bicycle are zero.

4. The total effect is the total of direct and indirect effects from a “cause” variable to an “outcome” variable. To take the subway accessibility variable as an example, as seen in Table 5, the total effect of subway accessibility on travel modal choices is 0.046, which equals the total of its direct effect (0.012) and indirect effect (0.024). The indirect effect is the effect of a “cause” variable on an “outcome” variable through an intermediate variable. For instance, living in a neighborhood with a nearby subway station indirectly increases the probability of using a low-carbon travel mode by 2.4%, through the intermediate effects of travel distance and number of trips (i.e. 0.024 = 0.405 × 0.023 + (−0.268) × (−0.053), see Figure 3.

Additional information

Funding

This research was partially sponsored by the National Natural Science Foundation of China (Grant Nos. [41571153], [41529101], and [41571144]).