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• W4379877978 abstract "From the signing of the United Nations Framework Convention on Climate Change in Rio de Janeiro in 1992 to the opening of a new round of climate talks in Bonn in 2018, climate change has been an international research focus for years The transport sector is the main consumer of fossil energy, and also the main source of CO2 emissions. According to the calculation of the IEA, CO2 emissions of the transport sector accounted for 25% of the total global CO2 emissions from fossil energy consumption in 2017. Since 1985, the average annual growth rate of transport energy consumption in China has been close to 8%, far higher than the average annual growth rate of the total energy consumption in the same period, which is 5.7%. With the surge in transport energy consumption, transport pollutant emissions are also growing rapidly. In the process of rapid motorization and urbanization, finding effective emission reduction policies for transport has been a problem. In addition, in China, there are significant differences in economic development, urbanization development, population distribution, industrialization and others among different regions, so the design of pollutant emission reduction policies should be implemented according to specific regional characteristics. Therefore, exploring the spatial difference characteristics of transport environmental efficiency (TEE) of provinces and regions in China, clarifying the spatial aggregation state of TEE, and identifying the influencing factors of transport emissions are of great significance for formulating differentiated transport emission reduction policies and promoting the construction of ecological civilization. The main contributions of this chapter are as follows: (1) At present, environmental efficiency is widely researched, but there is a lack of research on the transport sector. In this study, based on the actual situation of China and the comprehensive application of the international frontier theoretical and empirical method, a theoretical system is constructed to evaluate provincial TEE, which has great significance for improving the existing theory and methodology to evaluate regional environmental efficiency. (2) This study uses the epsilon-based measure (EBM) DEA model to measure TEE in 30 Chinese provinces from 2009 to 2016. This model can effectively solve the defects of CCR, BCC and SBM DEA models (Wu et al., 2019), which exhibits the potential for overestimation or underestimation of TEE (Yang et al., 2018). So we can get more accurate and scientific calculation results of provincial TEE. (3) The SDM method is used in this chapter, which contains spatial lags of the explained variable and explanatory variables and makes regression analysis more precise and reliable (Zhou et al., 2019), to explore how the influencing factors affect TEE, so as to provide the policy basis for decisions on transport emission reduction." @default.
• W4379877978 created "2023-06-09" @default.
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• W4379877978 date "2023-01-01" @default.
• W4379877978 modified "2023-09-27" @default.
• W4379877978 title "Transport Environmental Efficiency in China" @default.
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• W4379877978 doi "https://doi.org/10.1007/978-981-99-1055-7_11" @default.
• W4379877978 hasPublicationYear "2023" @default.
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