• Energy Research

With the rapid economic development of the Xinjiang Uygur Autonomous Region, the area’s transport sector has witnessed significant growth, which in turn has led to a large increase in carbon dioxide emissions. As such, calculating of the carbon footprint of Xinjiang’s transportation sector and probing the driving factors of carbon dioxide emissions are of great significance to the region’s energy conservation and environmental protection. This paper provides an account of the growth in the carbon emissions of Xinjiang’s transportation sector during the period from 1989 to 2012. We also analyze the transportation sector’s trends and historical evolution. Combined with the STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model and ridge regression, this study further quantitatively analyzes the factors that influence the carbon emissions of Xinjiang’s transportation sector. The results indicate the following: (1) the total carbon emissions and per capita carbon emissions of Xinjiang’s transportation sector both continued to rise rapidly during this period; their average annual growth rates were 10.8% and 9.1%, respectively; (2) the carbon emissions of the transportation sector come mainly from the consumption of diesel and gasoline, which accounted for an average of 36.2% and 2.6% of carbon emissions, respectively; in addition, the overall carbon emission intensity of the transportation sector showed an “S”-pattern trend within the study period; (3) population density plays a dominant role in increasing carbon dioxide emissions. Population is then followed by per capita GDP and, finally, energy intensity. Cargo turnover has a more significant potential impact on and role in emission reduction than do private vehicles. This is because road freight is the primary form of transportation used across Xinjiang, and this form of transportation has low energy efficiency. These findings have important implications for future efforts to reduce the growth of transportation-based carbon dioxide emissions in Xinjiang and for any effort to construct low-carbon and sustainable environments.

Coal consumption and carbon dioxide emissions from coal combustion in China are attracting increasing attention worldwide. Between 1990 and 2013, the coal consumption in Shandong Province increased by approximately 5.29 times. Meanwhile, the proportion of coal consumption of Shandong Province to China rose from 7.6% to 10.8%, and to the world, it rose from 1.8% to 5.5%. Identifying the drivers of coal consumption in Shandong Province is vital for developing effective environmental policies. This paper uses the Vector Autoregression model to analyze the influencing factors of coal consumption in Shandong Province. The results show that industrialization plays a dominant role in increasing coal consumption. Conversely, coal efficiency is the key factor to curtailing coal consumption. Although there is a rebound effect of coal efficiency in the short term, from a long-term perspective, coal efficiency will reduce coal consumption gradually. Both economic growth and urbanization have a significant effect on coal consumption in Shandong Province. In addition, the substitution effect of oil to coal has not yet met expectations. These findings are important for relevant authorities in Shandong in developing appropriate policies to halt the growth of coal consumption.

With China’s rapid economic growth, energy-related CO2 emissions have experienced a dramatic increase. Quantification of energy-related CO2 emissions that occur in China is of serious concern for the policy makers to make efficient environmental policies without damaging the economic growth. Examining 33 productive sectors in China, this paper combined the extended “Kaya identity” and “IPAT model” with the Log-Mean Divisia Index Method (LMDI) to analyze the contribution of various factors driving of energy-related CO2 emissions in China during 1995–2009. Empirical results show that the main obstacle that hinders China’s transition to a green energy economy is the economic structure characterized by high carbon emissions. In contrast, the increased proportion of renewable energy sources (RES) and the improvement of energy efficiency play a more important role in reducing carbon emissions. Moreover, the power sector has a pivotal position in CO2 emissions reduction, primarily because of the expansion of electricity consumption. These findings suggest that policies and measures should be considered for various industrial sectors to maximize the energy efficiency potential. In addition, optimizing the industrial structure is more urgent than adjusting the energy structure for China.

The United States of America is not only an important energy consuming country, but also in the dominant position of energy for many years. As one of the two largest emitters, the US has always been trying to register a decline in energy-related CO2. In order to make a further analysis of the phenomenon, we choose a new decoupling analysis with the multilevel logarithmic mean Divisia index (LMDI) method. This study examined the contribution of factors influencing energy-related carbon emissions in the United States of America during 1990–2014, quantitatively analyzed decoupling indicators of economic development and environmental situations. As is indicated in the results, economy development and activities have a significant effect in increasing carbon emission, however, measures of energy optimization such as the improvement of energy efficiency has played a crucial role in inhibiting the carbon dioxide emission. Furthermore, as is indicated in decoupling relationship, “relative decoupling” and “no decoupling” are the main states during the examined period. In order to better investigate the long-run equilibrium relationship between total carbon dioxide emissions of each effect and the relationship between CO2 emissions and economic growth, on the basis of a static decomposition analysis, we applied a dynamic analysis method-cointegration test. At last, recommendations and improvement measures aiming at the related issues were put forward.

Rapid economic growth in Northwest China has been accompanied by a dramatic increase in carbon emissions. Based on the two-level Logarithmic Mean Divisia Index (LMDI) method, this study decomposes changes in energy-related carbon emissions in Northwest China during 1995–2012 from the regional and provincial perspectives. Further, by constructing an expanded decomposition model of the decoupling index, this paper quantitatively analyzes delinking indicators of economic activity and environmental pressure in Northwest China. The results indicate that: (1) at both regional and provincial levels, economic activity effects play a crucial role in increasing carbon emissions, whereas improvements of energy efficiency appear as the main factor in curbing carbon missions; (2) the significance of influencing factors of CO2 emissions varies across provinces. The role of economic activity in Shannxi is more pronounced compared to that of the other four provinces, as well as the role of population in Xinjiang; (3) when the decoupling relationship is considered, “relative decoupling” and “no decoupling” are the main characteristics under investigation during the examined period. Whereas “strong decoupling” was only identified in 2007 and 2009; (4) the current extensive pattern of economic growth in Northwest China poses a serious threat to the decoupling process. Furthermore, the coal-based energy structure also hinders the decoupling process. According to these results, some policy recommendations are proposed.