Abstract

The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) was recently proposed by the Chinese government for socioeconomic–political–environmental development. As one of the most important parts for the development of the GBA, the transportation sector has become a nonnegligible consumer of energy and source of emission. Therefore, vehicle energy consumption and related emissions in the GBA must be evaluated. However, an effective framework for accurately estimating the real-time transportation performance, vehicle energy consumption and emission in large urban areas is still lacking. This study aims to develop a novel method for examining the regional integration and the spatial connection that affect vehicle emission via crowdsourced traffic data and an emission model. The novelty of this study is that it explores the acquisition of large-scale and real-time data as well as the calculation of corresponding energy consumption and environmental impact. Based on the analysis of transportation in GBA, it is found that the vehicle energy consumption and emission on the expressway are nearly half as that on the other urban roads. Moreover, a significant difference exists in vehicle energy consumption and emission between passenger cars and medium-duty trucks. Regarding transportation performance, vehicle energy consumption and emissions, they are closely related to departure time. It is also found that most of the adjacent cities tend to have high vehicle energy consumption and emission. The contribution of the Hong Kong–Zhuhai–Macao Bridge to transportation from Hong Kong, Macao and Zhuhai is different. Hong Kong benefits most from the bridge in terms of traffic energy efficiency. This study would be valuable to both researchers and practitioners. It helps researchers apply a large dataset in replicating real-world travel, energy consumption and emission pattern at a large scale. Policymakers and practitioners would benefit from developing effective strategies for the sustainable development of the GBA.

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