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The transportation sector is the main energy consumer and carbon emitter in China. To accurately evaluate the dynamic changes in the energy-carbon performance of the sector and to propose alternatives for sustainable development, this paper proposes an approach incorporating the meta-frontier method, global benchmark technology, and non-radial directional distance function. Using this approach, the paper proposes a new definition, named the global meta-frontier non-radial Malmquist energy-carbon performance index (GMNMECPI). GMNMECPI can be decomposed into technical efficiency change (EC), best-practice gap change (BPC), and technology gap change (TGC). This new method was then used to estimate the dynamic changes of energy-carbon performance in China's transportation sector from 2006 to 2015. The paper also identifies the effect of current policies. The empirical results show that the energy-carbon performance of China's transportation sector decreased annually by 1.636% during the study period. This reduction was mainly caused by a significant technology lag in the central area while primarily influenced by deterioration in efficiency in both the east and west. There is a distinct heterogeneity in technology across China's three areas. Based on the findings, the paper closes with policy implications. [ABSTRACT FROM AUTHOR]

This paper explores China's strategies for addressing climate change on the industrial level. Focusing on six energy-intensive industries, this paper applies gray relational analysis theory to the affecting factors to CO emissions of each industry after calculating each industry's CO emissions during 2001-2010. Further research based on GM(1, 1) model is conducted to forecast the trend of the factors, the energy consumption and each industry's CO emissions during the 12th Five-Year Plan period. As a breakthrough in previous conclusions, energy consumption structure was divided into the respective proportion of coal, oil, natural gas and electricity in the primary energy consumption, with which industrial output and energy intensity are combined to analyze each of their impacts on the energy-intensive industries. It turns out that all the factors' impacts on emissions of the six major energy-intensive industries are significant, despite their differentiated extents. It is worth noting that, contrary to previous findings, industrial output is not the leading affecting factor to CO emissions of the energy-intensive industries compared with the proportion of coal and electricity in the primary energy consumption. The GM(1, 1) forecast results of energy consumption and CO emissions by the end of 2015 show that coal and electricity will remain a large proportion in primary energy consumption. This research may shed some light on China's adjustment of energy structure under the pressure of addressing climate change and hence provide decision support for the acceleration of renewable energy utilization in the industrial departments. [ABSTRACT FROM AUTHOR]

A reduction in the CO2 emission intensity (ton per gross domestic product) from a base year to a target year with different rates of reduction in each individual year can yield different cumulative CO2 emissions over time, which could have different effects on the climate. In this paper, an indicator is proposed to measure the extent to which the cumulative CO2 emissions are generated by a specific reduction trajectory of CO2 emission intensity, especially for emerging economies with a relatively higher economic growth rate. The proposed indicator is important for less-developed countries and regions in which economic growth is heavily reliant on energy and in which significant potential exists for improvement of energy efficiency. The indicator is applied to evaluate the CO2 emission reduction performance in China's 12th Five-Year Plan period, and the result is not encouraging, especially when the likely gap between the energy conservation goals and temperature goals is further examined. Mitigation goals should be set by considering not only the performance in the final year, but also the reduction in cumulative emissions over the evaluation period. [ABSTRACT FROM AUTHOR]

Considering the significance and importance of urban sustainability in China and China's history of rapid urbanisation and industrialisation, this paper aims to incorporate the investigation of climate change and air pollution in urban sustainability research in China through a driver-pressure-state-impact-response model. The model has 12 indices: population, enterprise, registered vehicles, energy consumption, emissions and concentrations of carbon dioxide and sulfur dioxide, land use change, annual temperature, tropical nights and reforestation were selected. It was used in the analysis of 14 cities in the Liaoning Province. The results show that the model is an effective tool for urban sustainability research, allowing for the investigation of interactions of climate change and air pollution and contributing to the body of knowledge by aiding generation of realistic and practical measures. [ABSTRACT FROM AUTHOR]

The Chinese government committed to reduce its national CO 2 emissions intensity by 40–45% until 2020 in response to climate change. This paper quantitatively evaluates the performance of CO 2 emissions reduction over the period 2005–2020 from the historical and prospective perspectives by using a combination of decomposition analysis and scenario analysis, aiming to provide suggestions about how to achieve the target in key emissions reduction fields. Unlike traditional index decomposition methods, this paper incorporates the total energy conversion efficiency effect into the model, and further decomposes it into a final energy mix effect and a final energy conversion efficiency effect by a multilevel decomposition procedure, allowing to measure the contributions of primary energy structure low-carbonization, the final energy mix electrification, and the energy conversion efficiency improvement. The results show that the carbon intensity could decline over the period 2005–2020 by 47.8%, 50.9%, 48.0%, 44.5% and 47.5% in the Business as Usual, S1, S2, S3 and S4 scenarios, respectively. This shows that the 40–45% target is very likely to be achieved. The final energy intensity effect is always the most important driving factor, causing carbon intensity to decrease by 24.0% and 22.1%, again respectively, from 2005–2012 to 2012–2020. Moreover, the energy conversion effect was another major driver during 2005–2012. The Chinese government needs to make more efforts to adjust the industrial structure, which could cause carbon intensity to decrease by 3.6% during 2012–2020, and to adjust the primary energy mix, which could cause carbon intensity to decrease by 7.1% during 2012–2020. [ABSTRACT FROM AUTHOR]

China, as the world's largest emitter, intends to achieve the peaking of carbon dioxide (CO) emissions around 2030 and to make best efforts to peak early to mitigate global change. Under this strategy, a dynamic, recursive computable general equilibrium (CGE) model is used to analyze the economy, energy, and environment impact of CO emission reduction policy based on 17 scenarios in China: carbon tax, emission trading scheme (ETS), and the mixed policy in different price level, in order to find out which kind of emission reduction strategy is more feasible. The results show that CO emission in 2030 will be reduced with the implementation of tax, ETS and mixed policy, by 10-13 %, 12-14 %, and 18-28 %, respectively. From 2016 to 2030, China can reduce 18,338-24,156 Mt CO through the implementation of mixed policy. Furthermore, relative to single policy, mixed policy has stronger effects on primary energy consumption cut, by 738-1124 Mtoe or 18-28 %, which will make CO emissions reach a peak before 2030 and the peak emission is not greater than 12 billion tons which is in line with the reduction demand in China. Thus, the mixed policy is the most effective strategy so that mixed policy is recommended to parties included in Annex I in United Nations Framework Convention on Climate Change Kyoto Protocol and other countries with large potential of emission reduction, while ETS is suggested to countries with low carbon emissions per capita which can balance economic development and CO mitigation. [ABSTRACT FROM AUTHOR]

Accurately understanding the real situation of China’s carbon emissions at the provincial level is not only crucial for realizing carbon mitigation in China, but also of great importance for tackling climate change on a global scale. This paper uses detailed energy consumption data subdivided within each fuel type and sector-specific emission factors, to calculate both direct and indirect energy-related CO 2 emissions for China’s provinces, and offers provincially-targeted policy proposals on emission reductions. The results uncover large divergences in calculation of provincial CO 2 emissions between production-based and consumption-based accounting approaches. Considering the large amount of interprovincial CO 2 emission transfers embodied in secondary energy deployment, the consumption-based accounting performs better in reflecting the actual features and responsibilities of carbon emissions in the provinces of China. From the consumption perspective, Shandong, Hebei, Jiangsu, Inner Mongolia, Guangdong, Henan, Liaoning and Shanxi contributed to the majority of China’s carbon emission growth during the period of 1996–2013, while Xinjiang, Sichuan, Anhui, Tianjin and Hunan were playing an increasingly important role. These two groups of provinces should be regarded as the key regions for national emissions abatement. Meanwhile, the energy industry was the top sectoral contributor to CO 2 emissions growth in most provinces, while service and household sectors made increasingly significant impacts on driving up provincial emissions. Together with ongoing efforts in the energy sector, the mitigation of CO 2 emissions in service and household sectors deserves much more attention, especially in the transportation and urban household sectors. Furthermore, the temporal trends of carbon emissions in various provinces, as well as their factor and sectoral driving forces, varied greatly with each other. Therefore, each of the provinces should formulate emission reduction policies according to their own situation, and target the key driving factors and sectors of carbon emissions at the current stage or in the near future. [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]

Climate change which is induced from energy consumption and CO 2 emissions has got people's attention; hence, many strategies and ways are being adopted to mitigate CO 2 emissions. Energy substitution is crucial to the promotion of energy conservation and CO 2 emissions reduction. The purpose of this paper is to estimate both inter-factor and inter-fuel substitution in China's iron & steel industry during the period 1985–2011. Empirical results show several conclusions for China's iron & steel industry: (1) own-price elasticity of energy is negative, so increase in energy price will reduce energy input; (2) energy and capital, and energy and labor are substitutes, and the substitution in energy/capital is relatively stronger; (3) though coal, oil and electricity are also substitutes, the substitution effect is not so obvious because of pricing distortions in China. The driving forces of energy efficiency change are further discussed and the results show that technology progress is the key factor determining energy intensity. Therefore, market-oriented reforms in terms of energy prices, improvement in energy substitution (including inter-factor and inter-fuel substation) and promotion of energy saving technologies are important means for ensuring future energy conservation and CO 2 emissions reduction practices in China's iron & steel sector. [ABSTRACT FROM AUTHOR]

The 2015 Paris climate change negotiations represents the most ambitious worldwide effort to date to combat climate change. As the largest energy consumer and carbon emitter, China pledges 60–65% cut in carbon intensity below 2005 levels by 2030. To accelerate China's climate efforts, China has also committed to cap its primary energy use at 4.8 billion tons of coal equivalent in 2020. This paper proposes an equitable and efficient scheme to disaggregate this national goal among provinces. A three-step disaggregation procedure is proposed which takes into account the initial allocation, national redistribution and inter-provincial adjustment. First, this study allocates the incremental energy quota, taking 2010 as the base year. Second, part of the energy quota is set aside by the central government for redistribution purposes, while an incremental energy quota index comprising equity and efficiency criteria is used for initial allocation among provinces. Finally, historical efforts and inter-provincial energy flows are considered for inter-provincial adjustment. This disaggregation scheme is flexible and can be easily extended to allocation and management of other resource and environmental targets. The empirical findings can assist decision-makers in identifying which provinces are likely to over-consume the energy quota relative to the proposed allocation and which provinces are likely to perform better in energy conservation. Moreover, the results show that the energy cap set for 2020 is unachievable without further action. Market-based instruments, such as an energy allowance trading market, are strongly recommended to achieve the energy use target in an equitable and cost-effective manner. [ABSTRACT FROM AUTHOR]