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With important implications for global climate change mitigation, the development of a cap-and-trade emission trading scheme (ETS) in China is embedded in distinctive political, economic, and institutional contexts and has been attracting increasing attention in recent years. To offer a clear perspective on current research progress, this paper systematically reviews the recent literature on China’s ETS from three main aspects: mechanism design, policy and regional linkages, as well as impact assessment. The current research consensuses are summarized based upon detailed literature analyses and commentaries, and together with observations of international experience and China’s actual condition, the paper provides policy proposals for the development of China’s national ETS during 2016–2020. Finally, several important controversies in the current literature are discussed with regard to the practical demands of China’s ETS development. Five pressing topics that need to be further studied in the coming years are highlighted, including cap setting, allowance allocation among sectors and enterprises, carbon pricing, policy package and unified carbon market construction, as well as ex-ante and ex-post impact assessments. [ABSTRACT FROM AUTHOR]

As the largest carbon emissions source sector, electric power industry is undoubtedly a principal part of the carbon trading market in China. Aimed at researching the impact on power industry beyond establishing the national carbon trading market, a dynamic computable general equilibrium (CGE) model embedded with carbon trading block is introduced in this paper. Subsequently, we design 8 scenarios of which illustrate corresponding industry carbon emissions baselines and free quotas ratios. The main simulation results are as follows. The implementation of carbon emissions trading would bring a certain negative impact on the overall economy. Real GDP will be reduced by about 0.08%–0.52% in 2030. Though low free quotas ratio will cause a relatively high loss of GDP, this negative impact would be eliminated in the long run. In addition, carbon emissions trading would also promote the clean production of electricity. Indeed, the electric power industry would reach carbon emissions peak around 2020. Relative to scenarios without carbon trading, carbon emissions would reduce more than 1000 million tons in 2030 when industry carbon emissions baseline declines at an annual rate of 2%. Consequently, the carbon market can achieve a more significant reduction in carbon emissions with the influencing of quotas fully auctioned scenario. [ABSTRACT FROM AUTHOR]

Abstract Energy/emission intensity indicators measure the relationship between economic development and climate change. These intensity indicators are preferentially used in assessment criteria for mitigation goals in places such as China. This paper investigates the driving factors of changes in the national CO 2 emission intensity and their contributions to reductions at the sector level in China from 2002 to 2012 using multiplicative structural decomposition analysis (SDA) and attribution analysis. Both Leontief and Ghosh input-output models are used in the study. The empirical results indicate: 1) the energy intensity effect is the main driver that decreases the aggregate emission intensity from both the demand and supply sides; 2) structural effects, such as the energy structure effect and domestic Ghosh structure effect, promote the increase in aggregate emission intensity principally; and 3) to a large extent, sector "smelting and pressing of metals", "manufacture of non-metallic mineral products" and "chemical industry" are the top three sectors that contribute to the negative energy intensity effect. Ultimately, several discussions and conclusions associated with the empirical results, result stability and research extensibility are presented. Highlights • Both Leontief and Ghosh models were adopted to study China's CO 2 intensity. • Multiplicative decomposition was applied to study the intensity changes in 2002–2012. • Energy intensity effect was the major drivers to reduce China's emission intensity. • The structural effects as a whole contributed to the increase of emission intensity. • The domestic allocation structure can be adjusted and optimized preferentially. [ABSTRACT FROM AUTHOR]

As the largest carbon emitter and developing country in the world, China's rapid urbanization in recent decades plays a significant role in carbon emissions. However, there is still no consensus on whether urbanization process and carbon emission abatement in China can achieve a harmonious state. Based on the panel data of China's 30 provincial-level regions during 2001–2014, this paper uses the threshold regression model and the mediating effect model to investigate the effect and its mechanism of urbanization process on carbon emissions measured by three indicators: carbon emission scale, per capita carbon emissions, and carbon intensity. The results show that urbanization can contribute to declines in carbon emission scale, per capita carbon emissions, and carbon intensity. That is to say, urbanization can present an abatement effect on carbon emissions. However, such an abatement effect is diminishing with a deepening urbanization. Moreover, the relationship between urbanization and carbon emissions is mediated by four mediating variables, i.e., technological progress, industrial structure, energy consumption structure, and foreign direct investment. Therefore, a harmonious relationship between urbanization and carbon emission abatement can be achieved if policy-makers attempt to arouse the positive mediation roles of such factors when formulating relevant policies. [ABSTRACT FROM AUTHOR]

China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI , WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. [ABSTRACT FROM AUTHOR]

China is the largest emitter of carbon emissions in the world. In this paper, we present an Integrated Model of Economy and Climate (IMEC), an optimization model based on the input-output model. The model is designed to assess the tradeoff between emission deceleration and economic growth. Given that China's projected average growth rate will exceed 5% over the next two decades, we find that China may reach its peak CO 2 emissions levels by 2026. According to this scenario, China's carbon emissions will peak at 11.20 Gt in 2026 and will then decline to 10.84 Gt in 2030. Accordingly, approximately 22 Gt of CO 2 will be removed from 2015 to 2035 relative to the scenario wherein China's CO 2 emissions peak in 2030. While this earlier peaking of carbon emissions will result in a decline in China's GDP, several sectors, such as Machinery and Education, will benefit. In order to reach peak CO 2 emissions by 2026, China needs to reduce its annual GDP growth rate to less than 4.5% by 2030 and decrease energy and carbon intensity levels by 43% and 45%, respectively, from 2015 to 2030. [ABSTRACT FROM AUTHOR]

Studying the characteristics, trends, and evolution of carbon emissions in agricultural related sectors is of great significance for rational formulation of carbon emission reduction policies. However, as an important carbon emission reduction policy, carbon tax has been controversial over whether or not it should be levied on China. Based on this consideration, this paper takes China's agricultural related sectors as an example and analyzes the degree of carbon tax on macro-environment, macroeconomy, and agricultural sectors during the period 2020–2050 by constructing a 3EAD-CGE (economy-energy-environmental-agricultural-dynamics Computable General Equilibrium) model. The results show that: (1) carbon tax has a time effect, specifically, the short-term effect is better than the long-term. (2) If the incremental rate of carbon tax is carried out alone, it will exert a great influence on the macroeconomy as well as on most of the agricultural related sectors. (3) If a carbon tax is introduced at the same time as indirect taxes are cut (proportionally), the policy will exert a negative impact on agriculture-related sectors that are subsidized. However, the policy will have a positive impact on those nonsubsidized sectors. Finally, based on the results, we put forward some suggestions that are more suitable for the introduction of a carbon tax in China's agricultural-related sectors. [ABSTRACT FROM AUTHOR]

Based on the apparent energy consumption data, a systematic and comprehensive city-level total carbon accounting approach was established and applied in Guangzhou, China. A newly extended LMDI method based on the Kaya identity was adopted to examine the main drivers for the carbon emissions increments both at the industrial sector and the residential sector. Research results are listed as follow: (1) Carbon emissions embodied in the imported electricity played a significant important role in emissions mitigation in Guangzhou. (2) The influences and impacts of various driving factors on industrial and residential carbon emissions are different in the three different development periods, namely, the 10th five-year plan period (2003–2005), the 11th five-year plan period (2005–2010), and the 12th five-year plan period (2010–2013). The main reasons underlying these influencing mechanisms were different policy measures announced by the central and local government during the different five-year plan periods. (3) The affluence effect (g-effect) was the dominant positive effect in driving emissions increase, while the energy intensity effect of production (e-effect-Production), the economic structure effect (s-effect) and the carbon intensity effect of production (f-effect-Production) were the main contributing factors suppressing emissions growth at the industrial sector. (4) The affluence effect of urban (g-effect-AUI) was the most dominant positive driving factor on emissions increment, while the energy intensity effect of urban (e-effect-Urban) played the most important role in curbing emissions growth at the residential sector. [ABSTRACT FROM AUTHOR]

Nighttime Light (NTL) has been widely used as a proxy of many socio-environmental issues. However, the limited range of sensor radiance of NTL prevents its further application and estimation accuracy. To improve the performance, we developed an improved Vegetation Adjusted Nighttime light Urban Index (VANUI) through fusing multi-year NTL with population density, the Normalized Difference Vegetation Index and water body data and applied it to fine-scaled carbon emission analysis in China. The results proved that our proposed index could reflect more spatial variation of human activities. It is also prominent in reducing the carbon modeling error at the inter-city level and distinguishing the emission heterogeneity at the intra-city level. Between 1995 and 2013, CO2 emissions increased significantly in China, but were distributed unevenly in space with high density emissions mainly located in metropolitan areas and provincial capitals. In addition to Beijing-Tianjin-Hebei, the Yangzi River Delta and the Pearl River Delta, the Shandong Peninsula has become a new emission hotspot that needs special attention in carbon mitigation. The improved VANUI and its application to the carbon emission issue not only broadened our understanding of the spatiotemporal dynamics of fine-scaled CO2 emission, but also provided implications for low-carbon and sustainable development plans. [ABSTRACT FROM AUTHOR]

Secondary organic carbon (SOC) formation and its effects on human health require better understanding in Chinese megacities characterized by a severe particulate pollution and robust economic reform. This study investigated organic carbon (OC) and elemental carbon (EC) in PM2.5 and PM0.25 collected 8-20 March 2012. Samples were collected inside and outside a classroom in a middle school at Xi'an. On average, OC and EC accounted for 20%-30% of the particulate matter (PM) mass concentration. By applying the EC-tracer method, SOC's contribution to OC in both PM size fractions was demonstrated. The observed changes in SOC:OC ratios can be attributed to variations in the primary production processes, the photochemical reactions, the intensity of free radicals, and the meteorological conditions. Total carbon (TC) source apportionment by formula derivation showed that coal combustion, motor vehicle exhaust, and secondary formation were the major sources of carbonaceous aerosol. Coal combustion appeared to be the largest contributor to TC (50%), followed by motor vehicle exhaust (25%) and SOC (18%) in both size fractions. [ABSTRACT FROM AUTHOR]

China has achieved notable success in developing its economy with approximate 10 percent average annual GDP growth over the last two decades. At the same time, energy consumption and CO2 emissions almost doubled every five years, which led China to be the world top emitter in 2007. In response, China's government has put forward a carbon mitigation target of 40%-45% reduction of CO2 emission intensity by 2020. To better understand the potential for success or failure of such a policy, it is essential to assess different driving forces such as population, lifestyle and technology and their associated CO2 emissions. This study confirms that increase of affluence has been the main driving force for China's CO2 emissions since the late 1970s, which outweighs reductions achieved through technical progress. Meanwhile, the contribution of population growth to CO2 emissions was relatively small. We also found a huge disparity between urban and rural households in terms of changes of lifestyle and consumption patterns. Lifestyles in urban China are beginning to resemble Western lifestyles, and approaching their level of CO2 emissions. Therefore, in addition to the apparent inefficiencies in terms of production technologies there is also a lot of room for improvement on the consumption side especially in interaction of current infrastructure investments and future consumption. [ABSTRACT FROM AUTHOR]