The Yangtze River Delta (YRD) is China’s largest urban agglomeration with a rapid urbanization process. This paper analyzes the dynamic relationship between urbanization rate, energy intensity, GDP per capita, and population with CO2 emissions in YRD over 1990–2011 based on the extended STIRPAT model, impulse response function, and variance decomposition. A support vector machine model was constructed to further predict the scenarios of YRD’s CO2 emissions from 2015–2020. The results show that YRD’s CO2 emissions continuously increased during the sample period and are predicted to increase over 2015–2020. Energy intensity is the most influential factor, both in the short and long term, and the total population contributes the least. However, the influencing magnitude of energy intensity tends to decrease in the long term. The increase of urbanization rate is still accompanied by the increase of CO2 emissions in YRD, but an inverted-U shape relationship between them may exist in the long term. The contribution of GDP per capita to CO2 emissions is higher than the population and urbanization rate, and its contribution rate for CO2 emissions is growing. The Kuznets curve does not exist in the current YRD.

Electric Vehicles (EVs) have the potential to solve the problems associated with the use of internal combustion engines (ICEs), such as air pollution and security of energy supply. This paper addresses the question about how EVs in China can achieve system innovation. Recognizing that the system innovation of EVs is essentially a transition involving co-evolution of many elements including technology and society, this paper adopts multilevel perspective (MLP). The drivers and barriers for the system innovation of EVs in China are identified. Based on the analysis combined with the theories on social-technical pathways, this paper describes the possible ways that transition to EVs may take place from the short-term, medium-term and long-term perspectives.

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