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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]

Based on energy and CO 2 emission efficiencies, this paper proposes a definition of the elasticity of the potential of emission reduction to energy saving ( E peres ), and measures the elasticity in China’s 30 provincial regions. Although E peres is a relative definition, it can be used (1) to measure the amount of reduced CO 2 emissions per unit fossil energy saving, (2) to reflect the effectiveness of fossil energy saving for CO 2 emission reduction in different regions, and (3) to provide decision-making criteria for selecting pathways for emission reductions in different regions. The results show that compared with energy saving, emission reduction is a more serious issue in China. This indicates that energy saving policies have been highly effective since their implementation during the 11th “Five-Year Plan”. With respect to provincial disparities, the emission reductions caused by fossil energy saving are not significant in Beijing, Shanghai, and Guangdong. Fujian province has significant E peres , indicating that emission reduction causing by fossil energy saving is effective. E peres has been increasing over time in Hunan and Hubei. Hainan’s E peres has remained less than 1, indicating that its emission-reduction effect of fossil energy saving is worse than in other provinces. Moreover, the elasticity of Eastern China is greater than that of Central China and Western China. This finding sheds light on pathway selection for energy saving and emission reduction in China: it would be more appropriate to encourage fossil energy saving in Eastern China, and to promote clean energy use (e.g., water electricity and solar energy) in Central China and Western China. [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]

Based on the two-level Logarithmic Mean Divisia Index (LMDI) method and Tapio index, this paper constructed an expanded decomposition model for decoupling elasticity and effort index of industrial carbon emissions, and further quantitatively analyzed the delinking indicators on industry growth and environmental pressures in Beijing–Tianjin–Hebei (BTH) economic band from 1996 to 2010. The results indicate that: (1) together with the rapid economic growth, industrial energy-related carbon emissions in BTH region rose from 44477.43 × 10 4 t in 1996 to 105602.33 × 10 4 t in 2006 and then declined to 64426.71 × 10 4 t in 2010, with an average annual growth rate of 2.94%. Our results also show that carbon emissions in BTH region were dominated by the secondary industry, which accounted for about 80% of total carbon emissions. (2) “Weak decoupling” was the main characteristic during the 9th Five-Year Plan period (1996–2000) and 11th Five-Year Plan period (2006–2010), particularly “strong decoupling” in 2007; while “weak coupling” was the main characteristic during the 10th Five-Year Plan period (2001–2005). (3) The rapid economic growth was the main factor responsible for industrial decoupling blocking. The energy structure and energy intensity made significant contributions to the industrial decoupling progress. The industrial structure effect had varied considerably over the years without showing a clear trend. [ABSTRACT FROM AUTHOR]

China is pursuing the development of low-carbon eco-cities to limit carbon dioxide and other greenhouse gases emissions; however, it is unclear what constitutes a low-carbon eco-city and how to evaluate it. The eco and low-carbon indicator tool for evaluating cities (ELITE cities) was developed by researchers at the Lawrence Berkeley National Laboratory in 2012 to evaluate cities’ performance by comparing them against benchmark performance goals as well as rank them against other cities in China. ELITE cities measures progress on 33 key indicators selected to represent priority issues within eight primary categories. An excel-based tool was then developed to package the key indicators, indicator benchmarks, explanation of indicators, point calculation functions and transparency-oriented data recording instructions. ELITE cities could be a useful and effective tool for local city government in defining the broad outlines of a low-carbon eco-city and assessing the progress of cities’ efforts towards this goal. ELITE cities can also be used by higher-level governments to assess city performance and discern best practices. This paper explains the general framework of the ELITE cities tool, the methods by which the indicators and indicator benchmarks were established, and a detailed guide on tool applications. [ABSTRACT FROM AUTHOR]

Since carbon emissions are considered to contribute the lion's share in global warming, extensive studies have been devoted to measuring the carbon emissions abatement cost in various ways. This paper derives the shadow prices of China's aggregate carbon emissions at provincial levels by using directional output distance function and Shephard output distance function. The empirical results indicate that the shadow prices estimated by the directional distance function with directional vector of (1,−1) are significantly higher than those estimated by Shephard distance function, which implies that the green production technology is very expensive for the developing country of China. In addition, the shadow prices of carbon emissions present a rising trend during the sample period, which implies that it is increasingly costly for China to regulate CO 2 emissions. Moreover, the shadow price is positively correlated with regional economic development levels. Generally, the shadow price of the high income regions is significantly bigger than that of low income regions. Therefore, China should promote regional scheme of carbon emissions reduction, such as regional carbon emissions trading scheme, to fulfill its ambitious target of carbon emissions reductions. [ABSTRACT FROM AUTHOR]