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This paper proposes an approach to calculate the time series of cumulative carbon dioxide (CO 2 ) emissions between 1995 and 2014 based on industrial energy consumption data in three Eastern China jurisdictions in Shanghai, Jiangsu and Zhejiang during these two decades. Using the Hodrick-Prescott filter, the fluctuation components of the cumulative CO 2 -emission time-series data in the three provinces are obtained. Subsequently, a grey correlation-based change-point search algorithm is used to determine change-points in these data. Additionally, the CO 2 -emission time-series is divided into stages based on the change-points. The cycle characteristics of national energy policies, laws, and regulations are compared with those of the cumulative CO 2 -emission cycle of the three provinces to analyse the impact of energy policies on CO 2 emissions. This study shows that, although the industrial structure and trends in the CO 2 emission time-series data of the three provinces are different, their cumulative CO 2 -emission cycle remains the same from 1995 to 2014. The variation characteristics of the cumulative CO 2 emissions for each cycle during this period are well aligned with the stage characteristics of energy policies, laws, and regulations, indicating that energy policies play a consistent role in regulating such emissions. This study examines low-carbon production and sustainable energy development, and offers suggestions for issuing and perfecting energy policies, laws, and regulations, considering the indicators of energy consumption and CO 2 emissions. [ABSTRACT FROM AUTHOR]

Rapid urbanization has exerted substantial pressure on China’s energy system and contributed to climate change. To find the key drivers of urban residential energy consumption and CO 2 emissions, this paper uses an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model that employs city-level data to examine the influences of population scale, income level, population compactness and price on house-based residential energy consumption, energy-related CO 2 emissions and private vehicle ownership. The empirical results indicate that factors such as population scale, affluence, and population compactness can lead to increases in residential energy consumption and CO 2 emissions. In terms of transportation, income and population scale positively drive the growth of private vehicle ownership, while the fuel price negatively influences private vehicle ownership. Moreover, population scale is the most important factor in residential energy consumption and CO 2 emissions. Finally, policy recommendations are suggested for China’s urban development strategy and urban design and to encourage technology innovations that reduce residential energy consumption and CO 2 emissions. [ABSTRACT FROM AUTHOR]