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Abstract: The pulp and paper industry is one of the most energy-intensive industries worldwide. In 2007, it accounted for 5% of total global industrial energy consumption and 2% of direct industrial carbon dioxide (CO2) emissions. An energy audit is a primary step toward improving energy efficiency at the facility level. This paper describes a plant-wide energy audit aimed at identifying energy conservation and CO2 mitigation opportunities at a paper mill in Guangdong province, China. We describe the energy audit methods, relevant Chinese standards, methods of calculating energy and carbon indicators, baseline energy consumption and CO2 emissions of the audited paper mill, and nine energy-efficiency improvement opportunities identified by the audit. For each of the nine options, we evaluate the energy conservation and associated CO2 mitigation potential. The total technical energy conservation potential for these nine opportunities is 967.8terajoules (TJ), and the total CO2 mitigation potential is equal to 93,453tonnes CO2 annually, representing 14.4% and 14.7%, respectively, of the mill’s total energy consumption and CO2 emissions during the audit period. [Copyright &y& Elsevier]

Compared to cast-in-situ construction, prefabricated construction reduces the generation of construction waste; however, construction waste cannot be entirely eliminated through prefabrication and can be generated at each stage of its life cycle. This paper generates a system dynamics model, comprising two causal-loop diagrams and one stock-flow diagram, to simulate the effectiveness of policies on decarbonizing prefabricated concrete building waste. The model can predict the annual and total construction waste, along with the associated carbon emissions, under different policy scenarios in China by 2030. This paper focuses on prefabricated concrete buildings in China, with specific attention to the wastage of concrete, bricks, mortar, and metal. In single-factor scenario simulations, increasing landfilling fee is the most effective policy for waste decarbonization, potentially reducing carbon emissions by 31%. Increasing prefabrication rate and enhancing regulation degree at the design phase of prefabrication can directly reduce prefabricated building waste generation, subsequently resulting in an 18% and 7% carbon emissions reduction. Multi-factor scenario simulations demonstrate that the simultaneous application of all four policies is most effective, achieving a 44% reduction in carbon emissions. This research establishes a theoretical framework for prefabricated concrete building waste management and provides the Chinese government with practical insights on optimizing policies for waste decarbonization in the dynamic landscape of prefabrication. • This paper develops the prefabricated building waste generation and disposal systems. • The model predicts the construction waste and associated carbon emissions by 2030. • Raising landfill fee is an effective policy for decarbonizing construction waste by 31.06%. • Prefabrication rate reaching 100% can reduce 18.04% of carbon emissions from waste. • Applying all policies is most effective, achieving a 44.34% carbon emissions reduction. [ABSTRACT FROM AUTHOR]

Abstract China is under great pressure to reduce CO 2 emissions (CEs). Meanwhile, China's economy is more reliant on domestic consumption (particularly household consumption) than on exports. So, to achieve large-scale CEs' reduction for China, there is urgent need to study the CO 2 emissions from household consumption (CEs HC). Based on the environmentally extended Multiregional Input-Output model, this paper not only calculates both the direct CO 2 emissions from household consumption (DCEs-CH) and the indirect CO 2 emissions from household consumption （ICEs CH）at the provincial level in China, but also splits ICEs CH into domestic and foreign CEs. The findings of this paper are as follows: (1) between 2002 and 2012, CEs HC in China increased significantly, by 2.27 times, from 1306.17 Mt in 2002 to 2971.01 Mt in 2012. The CO 2 emissions from urban household consumption (CEs UHC) in China accounted for 75% of the total CEs HC in 2012. (2) The per capita CEs HC in China increased from 1.02 t/person in 2002 to 2.19 t/person in 2012. There was a prominent disparity in the total CEs and per capital CEs HC among the provinces in China. The per capita CEs HC were larger in provinces with a higher level of urbanization and higher per capita income. (3) The large-scale interprovincial transfer of ICEs caused by household consumption mainly occurred either within the Yangtze River Delta, the Pearl River Delta, and the Jing-Jin-Ji region or among these three regions. In addition, to service the household consumption, the energy-abundant provinces transferred a considerable amount of CEs to eastern coastal provinces. To achieve CEs' reduction, consumption-based strategies, such as lifestyle changes, should be required in parallel with strategies to reduce emission intensities on the producer side in China. Urban households should take more responsibility for the reduction of CEs in China. The interprovincial "Carbon leakage" should be taken into account when making policies for CEs' reduction in China. [ABSTRACT FROM AUTHOR]

Abstract With the development of China's economy, the use of fossil energy has become more and more, resulting in increasing carbon emissions. CO 2 emissions have caused global warming, threatening humans and creatures on Earth. In order to effectively suppress the growth of carbon emissions, it is necessary to analyze the influencing factors of carbon emissions and apply them to predict carbon emissions. This paper presents sixteen potential influencing factors and uses grey relational analysis to identify the factors that have a strong correlation with carbon emissions. The principal component analysis (PCA) is used to extract the four principal components, which reduce the redundancy of the input data. The long short-term memory (LSTM) method is established to predict carbon emissions in China. We use back propagation neural network (BPNN) and Gaussian process regression (GPR) to compare LSTM method. The simulation results show that the prediction accuracy of carbon emissions based on LSTM is better than that of BPNN and GPR, indicating the effectiveness of PCA and LSTM in prediction of carbon emissions. Finally, this paper provides the theoretical basis for China to reduce carbon emissions by studying prediction of carbon emissions. Highlights • Grey correlation analysis is applied to identify factors associated with carbon emissions. • Principal components analysis is used to simplify input variables and obtain the main factors affecting carbon emissions. • The long short-term memory model is used for the first time to predict carbon emissions. • The direction of reducing carbon emissions in China is given by analyzing the prediction results. [ABSTRACT FROM AUTHOR]

Abstract Cities do play significant roles in tackling global environmental changes. Decoupling economic growth from environmental pressures is critical for global sustainable development, however, few studies pay attention to the decoupling analysis at city level. This paper conducts a comparative study of the decoupling performance of economic output from CO 2 emissions between Beijing and Shanghai, the top two cities in China. In this paper, the decoupling trends and the decoupling effects are explored from a sectoral perspective, by combining the Tapio decoupling elasticity and the logarithmic mean Divisia index (LMDI) model. The results show that Beijing and Shanghai both experienced weak decoupling in construction, expansive negative decoupling in transport, expansive coupling in trade, and weak decoupling in others over the period 2000–2015. Moreover, agriculture appeared strong decoupling in Beijing, and recessive decoupling in Shanghai; industry showed strong decoupling in Beijing, and weak decoupling in Shanghai. The decoupling effects showed different magnitudes and patterns in industrial sectors between Beijing and Shanghai. Overall, per-capita GDP and population growth inhibited the decoupling, while energy intensity, industrial share, energy mix accelerated the decoupling process. Highlights • The decoupling of sectoral economic output from carbon emissions in Beijing and Shanghai are investigated. • Beijing's industry enjoyed better decoupling performance than Shanghai's industry. • Transport should be put more emphasis in further decoupling efforts. • Energy intensity is crucial effect accelerating the decoupling process. [ABSTRACT FROM AUTHOR]

The five major power generation corporations dominate the power industry in China, and play vital roles in China's carbon trading scheme. Under this circumstance, this paper studies the allocation of carbon emission quotas to China's five major power generation corporations based on the fairness and efficiency principles, which proves the primary prerequisite for setting up the national carbon market. Specifically, a bi-level programming model is developed to optimally allocate carbon emission quotas to the corporations, and then a zero sum gains data envelopment analysis (ZSG-DEA) model is adopted to evaluate the efficiency of the allocation so as to adjust towards the optimal solution. The results indicate that power generation has significantly positive influence on the allocation of carbon emission quotas. Moreover, the difference between the sum of optimal carbon emissions and the sum of carbon quotas allocated is 1.431 billion tons, which implies that the emission reduction potential of the five major power generation corporations is tremendous. Finally, the bi-level model in this paper can well capture the context of China's power industry and provide effective results for the allocation of carbon quotas. [ABSTRACT FROM AUTHOR]

To achieve the Chinese government's CO 2 emissions reduction target and build a carbon trading market in the Pearl River Delta (PRD) region, an initial allocation of CO 2 emissions quotas among cities in this region is fundamental. Different from the previous CO 2 emissions quotas allocation methods, this paper uses the maximum deviation method (MDM) to allocate CO 2 emissions quotas in the PRD region by taking the imbalanced development of different cities into consideration. Three principles including equality (represented by a population indicator), efficiency (represented by a GDP indicator) and feasibility (represented by a historical CO 2 emissions indicator) are considered in the method. The results reveal that the allocations derived by the MDM are more balanced than those derived using either single indicator approach or the information entropy method, and more closer to the development targets of Guangdong province. The more balanced allocations will be conducive to stimulating the development of under-developed cities and narrowing the gap between developed and under-developed cities, thus help to achieve the sustainable development in the PRD region. This paper helps to enrich the emissions quotas allocation methods and provides a new equitable method for policy makers to allocate emissions quotas under imbalanced development circumstances. [ABSTRACT FROM AUTHOR]

The metallurgy industry plays a very important role in China's economic growth. Due to its energy concentration, the energy consumption of the industry accounts for a large proportion of China's total energy consumption, and thus contributes to carbon emissions. Whether the metallurgy industry can successfully reduce emissions is related to the future of China's carbon emissions targets. In this paper, the logarithmic mean Divisia index model is used to analyze the change in China's carbon dioxide emissions from 1991 to 2014. The empirical results show that there are three main factors affecting the carbon dioxide emissions of China's metallurgy industry. The three factors are labor productivity, energy intensity and industry size. In addition, we further analyzed the deep motivation of carbon dioxide emissions in the industry, and calculated the future emission reduction potentials. Lastly, according to the empirical results, the paper proposes policy recommendations for the future emission reduction of China's metallurgy industry. [ABSTRACT FROM AUTHOR]

Ecological sustainability of the Chinese economy is vital for China as well as for the world. By integrating environmental input-output analysis, emergy theory, and a complex network model into one framework, this paper explores Chinese sectoral ecological sustainability with the most recent 2012 input-output table. The results show that there are significant differences in emergy intensities among sectors. The non-metal mining sector is the most emergy-intensive sector at 6.06E+17 sej/10000 Yuan, followed by the metal mining sector. Additionally, output connections have a positive impact on the emergy yield ratio, input connections exert a negative impact on the emergy yield ratio, and PageRank centrality has a positive effect on the environmental loading ratio. This paper updates the Chinese sectoral emergy assessment, identifies key sectors in the Chinese ecological network, and analyzes the impact of network indicators on sectoral emergy performance. These analyses will be useful in updating the guide for adjusting industrial structure in China. [ABSTRACT FROM AUTHOR]

Traditional energy planning methods are mostly related to newly-built area. However, in most already-built regions, the existing district energy systems (DESs) need to be ameliorated due to insufficient capacity and low efficiency. This paper investigates the methodology of expansion planning, which can offer planners a viable way to expand existing DESs. The term “expansion” aims to increase the supply capacity of the energy forms, e.g., steam, hot water and electricity, which cannot be accessed from national or urban energy supply network, and meanwhile increase energy utilization efficiency and cut CO 2 emission. Three parts of the methodology, including problem analysis in current DESs, demand side analysis and the existing DES expansion, are introduced in this paper. New concepts of load structure and evaluation system of the whole district are proposed in this methodology. A case analysis of Ningbo Hi-Tech District, China is conducted to shed light on the application of this method. [ABSTRACT FROM AUTHOR]

Innovative emission reduction technologies combined with optimized processes can effectively reduce the environmental pressure in the iron and steel industry (ISI). Identifying and comparatively analyzing the carbon emissions (CE) from steel productions is conducive to achieving China's ambitious carbon reduction targets. In this paper, we investigated two innovative routes: the shaft furnace-induction furnace-basic oxygen furnace route (SF-IF-BOF) and shaft furnace-electric smelting furnace-basic oxygen furnace route (SF-ESF-BOF), alongside two traditional routes: the blast furnace-BOF route (BF-BOF) and SF-electric arc furnace route (SF-ESF). The analysis was based on a functional unit of 1000 kg of crude steel (CS). By establishing the mass and energy balance models and decision criteria, 12 typical smelting scenarios for these routes were analyzed and compared in terms of materials consumption and CE. The results showed that increasing the proportion of scrap was beneficial for reducing CE. Under the condition of a 50% scrap ratio, the CE of the SF-IF-BOF, SF-ESF-BOF, BF-BOF, and SF-EAF routes were 768, 823, 946, and 870 kg, respectively. The SF-IF-BOF route displayed the most significant advantage of CE reduction. In addition, by using 100% zero-carbon electricity substitution, the SF-EAF route exhibited the greatest CE reduction effect of 41% (from 870 to 510 kg/t). While deploying 100% biomass fuels to replace coal, the CE of the BF-BOF route reduced by 80%. Finally, after introducing biomass fuels and zero-carbon electricity, the CE of the SF-IF-BOF route was minimized to a significantly low 13 kg/t (from 768), nearing zero CE. This research is expected to provide a novel solution for further CE reduction in the future of ISI, contributing to environmental sustainability and carbon reduction goals. • Suggestions for solutions to reduce CO2 emissions in the steel industry are provided. • Emissions of the SF-IF-BOF and SF-ESF-BOF compared to the BF-BOF and DRI-EAF routes. • DRI is considered to be generated using COG zero reforming process. • Using zero-C electricity and biomass can reduce CO2 emissions for the steel industry. [ABSTRACT FROM AUTHOR]

Substituting renewable energy for coal power under the carbon neutrality goal is an inevitable path for power system transformation, while the high share of renewable energy leads to a rapid rise in system flexibility demand. Currently, coal-fired power is still one of the most economical and reliable large-scale flexible resources in China. Therefore, the issue of how to mitigate the conflict between cleanliness and flexibility for coal-fired power is urgent to be solved. Accordingly, this paper established an optimization framework for the retirement and technology adoption of coal-fired power units with high spatial-temporal resolution, and the regional carbon emission budget is estimated from a top-down perspective. Secondly, a dynamic carbon quota allocation method considering technological innovation and adoption is proposed. The carbon trading cost of the units is evaluated from a bottom-up perspective, to realize the interaction between the obligatory policy constraints of the top-level target and the flexible incentives of the market mechanism. Finally, the empirical analysis was conducted in the Beijing-Tianjin-Hebei region of China. The optimal solution achieved by proposed method results in a substantial 27% reduction in total costs while keeping the increase in carbon emissions below 3%. By analyzing the dynamic evolution path of coal and the scale of diffusion of multi-type technologies, the differences in the roles coal power assuming at various stages of decarbonization are discussed. The robustness of the model and the validity of the proposed method were verified by comparing the dynamic/static carbon quota allocation. Overall, this study provides an effective optimization model for investigating the low-carbon technology adoption timing for coal power in Beijing-Tianjin-Hebei region, and offers valuable insights for other coal-dominated emerging economies seeking for power system transformation roadmap in the forthcoming net-zero carbon age. • A decision-making optimization model of CCPs low-carbon technology is proposed. • A dynamic CET system with upper-lower layer interaction is introduced. • The proposed dynamic CET system results in 27% reduction in total costs. • The high-resolution data of coal power in Beijing-Tianjin-Hebei region are used. • The strategy to solve the conflict between cleanliness and flexibility is given. [ABSTRACT FROM AUTHOR]

Mitigating greenhouse gas emissions is a significant global challenge, and precise prediction of carbon emissions holds the utmost importance for China to attain its dual carbon goal. To overcome the limitations of existing studies using a single forecasting method, based on quadratic exponential smoothing, multiple linear regression, and Gaussian process regression models, this paper constructs a carbon emission combination forecasting model with the generalized induced ordered weighted average (GIOWA) operator and analyzes carbon emission reduction performance. Empirical testing utilizing China's carbon emission data from 1980 to 2020 reveals the following findings: (1) The GIOWA combination forecasting model significantly enhances the accuracy of carbon emission forecasts, with an average accuracy exceeding 99.5% over the sample period, surpassing various single forecasting methods. (2) The carbon emission reduction target can be achieved under three different scenarios of low, average, and high GDP growth rates. Specifically, under the low growth rate scenario, China can achieve a 60% reduction in carbon intensity by 2025 and a 65% reduction by 2030. This study offers valuable decision support for the development of effective carbon reduction policies. [ABSTRACT FROM AUTHOR]

The commercial sector is one of the key sectors in China’s economic transformation and carbon emissions control. This paper applies VAR and STIRPAT models to investigate the major influencing factors of CO 2 emissions in China’s commercial sector over the period 1980–2014. According to the empirical results, per capita GDP, urbanization and energy structure have positive effects on CO 2 emissions while energy intensity has negative effect on CO 2 emissions in the long term. Besides, per capita GDP ranks as the most important driving factors of CO 2 in China’s commercial sector, followed by urbanization, energy structure and energy intensity in that order. This paper argues that reducing energy intensity and improving energy structure are the means to realize CO 2 emission reductions in the commercial sector in the short and long term, respectively. Besides, this paper forecasts that CO 2 emissions in China’s commercial sector will be 1942 Mt by 2030, which is huge and about half of the CO 2 emissions of the European Union in 2014. The findings have important implications for policy-makers to enact CO 2 emission reduction policies. [ABSTRACT FROM AUTHOR]

A carbon reduction labelling scheme is an effective policy tool for motivating enterprises or organizations to reduce their life-cycle-based carbon emissions to benefit the environment. This paper uses system dynamics to model enterprises' compliance with a combined government policy instrument for a carbon reduction labelling scheme, that is, government subsidies and economic sanctions. A case study of paper enterprises in China is provided to demonstrate the application of the proposed model in which two optional technological plans to reduce the enterprises' carbon emissions are examined. The technological plans are categorized as a low-cost and high-cost plan. The simulation results show that both the technological plans are vulnerable to the combined policy making, and the high-cost plan shows superior environmental performance for carbon emissions reduction. However, the enterprises are more inclined to choose the low-cost plan because of superior economic performance. The study offers insights to help enterprises select optimal actions on carbon emissions reduction and to inform government of possible sustainable policy design to promote low-carbon development. The model limitations are discussed as a basis for further improvements in low-carbon development. [ABSTRACT FROM AUTHOR]

E-commerce has emerged through digital platforms and Internet construction as an important way to achieve low-carbon development in China. To evaluate the mitigation effect of e-commerce, this paper conducts a quasi-natural experiment in terms of the pilot policy of national e-commerce demonstration cities (NEDC) to explore the changes in CO 2 emissions of 270 cities from 2004 to 2017 in China. We also check the asymmetry, mechanism effects and heterogeneity. The results show that the treated cities reduce CO 2 emissions by 4.1% due to the NEDC pilot policy compared to the untreated cities. The estimated results pass the parallel trend test, robustness tests, and the Goodman-Bacon decomposition. Moreover, the NEDC pilot policy increases the CO 2 emissions of treated cities by promoting economic growth (scale effect), and decreases the carbon emissions of treated cities by upgrading the industrial structure (structural effect) and increasing the technological innovation level (technical effect). Furthermore, the CO 2 mitigation effects of the NEDC pilot policy are significantly concentrated in the higher quantiles. Finally, the NEDC pilot policy has significantly negative effects on CO 2 emissions in "postage-free regions," southern China, and cities with large e-commerce sales. The results of this paper provide theoretical and practical references for China to achieve low-carbon development. • Evaluating the impact of pilot policies of national e-commerce demonstration cities (NEDC) on carbon emissions in China. • The NEDC pilot policy reduces carbon emissions of treated cities by 4.1%. • The NEDC pilot policy reduces carbon emissions through structural and technical effects. • The emission-reduction effects are significant at the higher quantiles. • The impact of the NEDC pilot policy on carbon emissions is obviously heterogeneous. [ABSTRACT FROM AUTHOR]

China has set an ambitious national determined contributions target to peak CO 2 emissions by 2030 and aims to be carbon neutral by 2060. One of China's top energy consumers and CO 2 contributors, the steel industry accounts for 13% of the country's total consumption and 15% of CO 2 emissions. In response to the present global warming trend, there is an urgent need to cut energy consumption and CO 2 emissions to promote low-carbon growth. This paper attempts to provide a detailed analysis of the steel industry's CO 2 emission reduction path to carbon neutrality. Further efforts in terms of industrial structure, material efficiency, energy efficiency, and low- or zero-carbon technologies are required to achieve a low-carbon transition. Given that decarbonization is a significant priority in the steel industry in many countries, this study focuses on the goals and technological paths of low-carbon emissions projects to optimize existing technology priorities and propose development directions. Deep decarbonization is also projected to be achieved by combining CCUS and hydrogen metallurgy technologies. The steel industry requires collaborative efforts to standardize CO 2 emission accounting methodologies and establish a carbon trading system to strengthen carbon emission management. • The steel industry is one of the key contributors to carbon neutrality which needs to accelerate decarbonization. • Reducing energy consumption and CO 2 emissions to keep up with the current global warming trend are reviewed. • This paper selects low-carbon emission projects to optimize current technology priorities and provide development directions. • Policy recommendations and next steps for low-carbon transition are given. [ABSTRACT FROM AUTHOR]

Sustained increase in Chinese household income has exerted positive impact on the consumption of goods and services. This paper aims to analyze the unequal impacts of household consumption across different income households on the whole CO 2 emissions, by utilizing a semi-closed input-output model and hypothetical extraction method. The semi-closed input-output model moves household consumption activities into the intermediate use along with dividing urban and rural households to several groups by their income levels, and the hypothetical extraction method (HEM) is used to estimate the reductions of CO 2 emissions relative to total emissions after extracting the consumption of each household group. The results show that: (1) the impact on CO 2 emissions generated by urban households’ consumption are 1.8 times as much as that of rural ones; (2) excluding consumption of higher-income households from the economy would cause greater CO 2 emission reductions than lower ones. Specifically, urban highest-income households have the most relative reductions of CO 2 emissions, which are −12.2% in 2007 and -13.8% in 2012, while for rural highest-income households are −5.1% in 2007 and -5.1% in 2012. And urban and rural highest-income households are respectively 3.8 and 1.8 times on the relative reductions of the lowest-income ones; (3) the relative reductions of household CO 2 emissions from food sectors is the most, while from residence sectors is the least. Based on the above conclusions, this paper puts forward consumption-based policy implications. [ABSTRACT FROM AUTHOR]

The significant carbon emissions generated by China's sludge treatment industry cannot be ignored. However, with only a few recent well-executed studies on carbon emission reduction in the sludge treatment field, the literature awaits a more comprehensive assessment and prediction whether the sludge treatment industry can achieve the dual-carbon target. This article aims to fill this gap, holistically examining the carbon emission reduction potential in the industry. Using the moving average method and IPCC method, the projected carbon emission value of sludge treatment in China from 2021 to 2030 indicates a total net carbon emission of 0.3 million tons by 2030. This suggests that the sludge treatment industry is on track to meet the carbon peak target, leaving surplus carbon quotas or credits available to assist other industries for carbon emissions reductions. The study also finds that only incineration and composting demonstrate the potential to be able to partially offset carbon emissions through resource utilization in certain stages or processes. Therefore, the current sludge treatment methods do not yield comprehensive emission reduction effects and cannot provide sufficient contribution to China's dual carbon goals. To address this issue, the paper explores a new scheme that focuses on improving the sludge treatment process. The scheme comparative analysis reveals that, even with all sludge treatment methods optimized, the total net carbon emissions of the industry could only be reduced to 0.058 million tons. This reduction falls short of significantly mitigating carbon emissions to achieve the carbon neutrality goal. Therefore, industries unable to achieve substantial net carbon reduction may need to explore alternative measures, such as carbon sinks, to ultimately attain carbon neutrality. [ABSTRACT FROM AUTHOR]

Towards the target of carbon neutrality, the need for deep decarbonization in iron and steel industry is increasingly recognized. Existing studies rarely mention the effects of collaboration with its source industries for carbon emission reduction in ISI. Furthermore, the fundamental laws of CO 2 emission reduction capacity with cost change of source substitutions for various steel production routes under market economics are unclear. To avoid the blind substitution of clean sources for meeting the urgent requirements for decarbonization in China's steel industry, which may result in increased carbon emissions and uneconomical carbon reduction from a lifecycle perspective. This paper integrates the production and utilization processes of source resources into the steel production process, establishes coupling models of carbon and value flows for four main types of steel production routes, and aims to quantitatively analyze the specific CO 2 emission reduction potential and costs. Three economic market development scenarios from 2021 to 2060 are set, and the marginal carbon prices of various source substitutions are determined. Subsequently, decarbonization pathways with the goal of minimizing production costs are developed. Finally. The future resource demand and the carbon emission reduction contributions of source industries collaborated are predicted. The results show that (1) about 81.7–89.9 % of CO 2 emissions could be reduced in the scenarios; (2) the demands of electric power and hydrogen energy will reach 54.48–511.90 BkWh and 7.47–10.31 Gt in 2060, respectively; and (3) collaboration with source industries could make 18.3–18.3% of CO 2 emission reduction contributions. All in all, this study could provide scientific support for the low-carbon transformation of China's steel industry. • Carbon and value flows of BF-BOF, Scrap-EAF, DRI-EAF, MOE-EAF routes are analyzed. • CO 2 emission reduction potential with marginal carbon price is determined. • Decarbonization paths during 2021–2060 for China's steel industry are developed. • Quantify the contribution of collaborative carbon reduction with source industries. [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]

Coal mining not only produces, but also consumes a large amount of energy. Coal production has an extremely high energy efficiency potential, and benchmarking is critical to discover this potential. To address problems such as ambiguity of coal production (e.g. underground mining), benchmarking range and absence of both indicators and standards for energy efficiency benchmarking, this paper makes use of product-based and process-based benchmarking. These two techniques are used to construct a benchmarking system for coal production with high energy efficiency, and improve the standards used at the eight coal mines owned by the Yankuang Group. Comparison and analysis of benchmarking in enterprises indicates that energy use during raw coal production could be reduced by 22.77%. Across China energy savings from coal production could reach 15.98–32.98 Mtce, with an equivalent 42–87 Mt of CO 2 emissions saved. Lastly, this paper provides measures to improve coal production energy efficiency. [ABSTRACT FROM AUTHOR]

Emerging economies like China, India, and Mexico are becoming the world's manufacturing leaders through the engagement in offshoring production activities. In achieving this status, however, they have met with difficult environmental issues. This paper features an analysis of industry-level panel data to examine the link between different offshoring tasks in China and carbon dioxide emissions. Through this analysis, the environmental effects of offshored production are addressed. Specifically an input–output model is presented, thereby quantifying offshored production tasks in China. The results show that iron and steel, nonferrous metals (IS) and chemicals (CH) generate the most carbon dioxide during production of processed goods. Additionally, electrical machinery (EM) and general machinery (GM) generate a higher amount of carbon dioxide during production of parts and components. The results also show that those industries characterized by higher energy consumption have higher carbon dioxide (CO 2 ) emissions induced by offshoring. Given these results, it seems that any solutions geared towards reducing the energy consumption of entire manufacturing industries would be useful. Furthermore, the results of the analyses presented here indicate that China would be responsible for working with developed countries to reduce carbon dioxide emissions through cooperative environmental regulation. A globalization perspective is adopted to offer unique insight into the environmental issues faced by China. The results of this paper would provide quantified, actionable information for formulating practical industrial policies geared towards reducing carbon dioxide leakage. [ABSTRACT FROM AUTHOR]

As CO 2 emissions differ in households with different characteristics, mitigation policies still address the contributions of these characteristics and their effects on specific households. Using a representative resident survey in urban China, this paper compares how household characteristics differ in their associations with household embedded carbon emissions (HECEs) at different levels by quantile regression; then, this paper analyzes the contributions of these characteristics by Shapley decomposition. The findings include the following: (i) household income is the most important contributor to the difference of HECEs, and its positive effect increases as HECEs rise; (ii) the use of wealth has different effects on HECEs because household housing ownership and deposits contribute little to HECEs, but the positive effects of household car ownership contribute 25.8%; (iii) young people and children will emit more HECEs than adults; the employed emit more than persons who are unemployed or retired; (iv) education increases HECEs overall but mainly at the low quantiles; the negative effect of the marriage increases as HECEs rise; (v) income, car ownership, marital status, size and constitution of households with high HECEs should be addressed to reduce the inequality of HECEs. Indeed, education on the low-carbon concept is another way forward. [ABSTRACT FROM AUTHOR]

Increasing concern about carbon dioxide (CO 2 ) emission reduction demands knowledge about the production structure of an economy. Information on productive linkages yields insight about forward and backward emission effects associated with sectoral inputs and outputs and serves as an essential starting point to identify the optimised industrial structure under the constraint of CO 2 emission. This paper proposes a combined linkage analysis and multi-objective programming approach to identify the key CO 2 emission sectors and the optimised production structure with respect to emission reduction target. As a demonstration, the proposed approach is applied to data from China in 2007. The result shows that to reduce CO 2 emissions from 5707.16 to 5452.12 million tonnes, China needs to change its industrial structure by focussing on industrial groups as defined by linkage characteristics, which would lead to a subsequent GDP decrease of 82.59 billion Yuan. From a policy standpoint, the analytical techniques described in this paper can provide valuable information for planners and decision makers to formulate feasible and practical industrial polices with implications for CO 2 emissions. [ABSTRACT FROM AUTHOR]

China has adopted cancellation of export tax rebate policies on many occasions to push ahead energy conservation and emission reduction since 2007. By applying a CEEPA (China Energy & Environmental Policy Analysis system) model, this paper simulates the impacts of the cancellation of export rebates on CO 2 emissions and socio-economic consequences in different scenarios so as to figure out whether it works. This paper covers three export rebate scenarios and makes comparisons between the impacts of export rebates on emission reduction effects and that of carbon tax policies. The conclusions are: 1) the current policy which cancels export rebates for key sectors can cut emissions at huge economic cost, yet it is unsustainable; 2) the policy which cancels export rebates for key sectors and meanwhile subsidizes sectoral outputs yields double dividends in the short term, thus can facilitate emission reduction yet the boost is limited; 3) the policy which cancels export rebates and boosts domestic demand helps improving residents' welfare in the short term while it may inflict pronounced social and economic impacts in the long run. So policy of this kind should be adopted with great caution; 4) export rebates generate far more economic costs than carbon tax policies in the long term, and don't contribute to optimizing the energy mix as well as the latter. In summary, canceling export rebates should not be regarded as a priority to encourage emission reduction. [ABSTRACT FROM AUTHOR]

Chinese government has committed to reduce its carbon intensity by 40–45% over the period 2005–2020 at the 2009 Copenhagen Summit. To achieve the target in a cost-effective way, China is signaling strong intentions to establish emissions trading scheme, and presently seven pilots have been established. This paper focuses on the cost-saving effects of carbon emissions trading in China for the 2020 target. First, an interprovincial emissions trading model is constructed. Then, three kinds of policy scenarios, including no carbon emissions trading among provinces (NETS), the carbon emissions trading only covering the pilots (PETS), and the unified carbon emissions trading market (CETS), have been designed. The results show that China needs to reduce its emissions by 819 MtCO 2 for achieving the 42.5% reduction in carbon intensity over the period 2005–2020. The PETS and the CETS, which may result in a carbon price of 99 yuan/tCO 2 and 53 yuan/tCO 2 , could reduce the total abatement costs by 4.50% and 23.67%, respectively. This paper also finds that the carbon emissions trading could yield different impacts on different provinces, and the cost-saving effects of the eastern and western provinces are more pronounced than the central provinces. Necessary sensitivity analysis is also provided at the end of the research. These findings may be useful for promoting the development of carbon emissions trading in China. [ABSTRACT FROM AUTHOR]

Based on semi-structured interviews with key stakeholders in Nanhai, this paper adopts an analytical framework to examine how a combination of infrastructure-pull, supply-push and demand-pull initiatives implemented by a small district government in southern China were able to facilitate socio-technical transitions to the public transport decarbonization through the establishment of hydrogen refuelling infrastructures, the adoption of fuel cell electric vehicles (FCEVs), and the development of production network on FCEVs. With neither massive investment from the central government nor captive linkage with global automakers, Nanhai out-performs other automotive powerhouses in China by accounting for 9.85 percent of FCEVs and 4.59 percent of all operating hydrogen refuelling stations in China, despite its land area only accounting for 0.01 percent of the country. The provision of hydrogen infrastructures and other pro-active local government initiatives (including financial incentives) facilitate the development of a competitive regionalized production network of about 90 (privately-owned) fuel cell electric buses makers and parts suppliers around the Xianhu Hydrogen Valley in Nanhai. This finding enhances our understanding on effects of (local) state policies on the socio-technical transitions to public transport decarbonization and the long-term development of hydrogen economies in other countries. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a carbon emission inventory in Shanghai for the period from 2000 to 2008 covering six sectors of stationary combustion, transportation, industrial processes, waste disposal and treatment, agricultural activities and forestry sink and three greenhouse gases (CO2, CH4, and N2O). The aim is to reflect carbon emissions in Shanghai, and guides policymakers to take effective actions to mitigate carbon emissions. Several results are obtained: (1) the total carbon emissions in Shanghai increased by 48%, from 136TgCO2e in 2000 to 200TgCO2e in 2008; (2) only the sector of agriculture activities saw reduced emissions; (3) the comparisons among Shanghai, China and world average level confirm that during 2000–2008 Shanghai''s carbon emissions per capita are higher than both the world and the China average level, and its carbon emission per GDP is also higher than the world average level, but both of them are lower than the China average level; (4) in 2008, Shanghai''s carbon emission per GDP is around 10tons CO2 per $10,000 and higher than that of Taiwan, Hong Kong, the G7 and the BRIC (Brazil, Russia, India and China) except China and India. In addition, this paper also illustrates the problems about China statistical system in terms of emission inventory establishment, including the classification system, data quality and temporal resolution. [Copyright &y& Elsevier]

Abstract: The study uses the carbon dioxide emission calculation model published by IPCC to measure carbon dioxide emissions and fuel inputs of the three types of multimodal transport (road-sea, railway-sea, and river-sea) in ports of China. Then, we make a case study on Shanghai port. Combined with carbon taxes launched around 2012 in China, this paper calculates the carbon taxes on the three types of multimodal transport and makes a pairwise comparison between roadway/railway, roadway/waterway and waterway/railway. The results show that increasing the proportion of railway-sea transportation and river-sea transportation to a reasonable level will achieve great energy saving, emission reduction, and economic benefits. According to different transportation network features, this paper applies Cluster analysis to raise separately suggestions for long-term development of coastal container ports in China based on low-carbon thinking. [Copyright &y& Elsevier]

Abstract: Due to increasing energy scarcity and pressures from climate change, Chinese iron & steel (IS) companies have struggled to implement practices to reduce their energy consumption and CO2 emissions. However, it is not clear whether these practices can improve the environmental or economic performance of these companies. The determinants that drive or hinder the implementation of these practices are also not known. Therefore, this paper describes an empirical analysis of a total of 85 questionnaires of various IS companies across China. A regression analysis was applied in this paper to verify the relationship among CO2 reduction practices, determinants and performance as reported by the IS companies. The results show that although some CO2 reduction practices can result in significant environmental performance, their impacts on the improvement of economic performance are less clear. The paper discusses some implications regarding strategies for prompting CO2 reduction practices that have been considered during the discussion about the determinants that impact on the practices. [Copyright &y& Elsevier]

Abstract: The aim of this paper is to study pathways to a low-carbon economy for Inner Mongolia whose economy highly depends on fossil energy. The paper analyzed the industrial and energy structure of the economy and further demonstrated the necessity of developing the low-carbon economy in Inner Mongolia, a typical province in the western China. In addition, the LMDI Decomposition Method is used to analyze the factors that affect the growth in carbon emission and the Grey Relational Analysis (GRA) is applied to examine the relation between the carbon emission and GDP growth. At last, the paper further studied the advantages of developing the low carbon economy in Inner Mongolia and suggested different modes and pathways for Inner Mongolia to achieve the low carbon economy. [Copyright &y& Elsevier]

Abstract The transport sector produced numerous global greenhouse gas emissions in China. It is important to promote low carbon commuting in China. This paper aims to investigate the determinants of intention and behavior of low-carbon commuting through bicycle-sharing (LCB) in China. Theoretical model and hypotheses are put forward by integrating the theory of planning behavior and theories of value and residual effects. Through structural equation model (SEM), the empirical analysis revealed that residual effect has the largest positive impact on intention of LCB for both males and females. Subjective norms positively affected intention of LCB for males. Attitude towards bicycle-sharing, perceived behavioral control positively affected intention of LCB for females. Intention has higher positive effect on females' behavior of LCB than males'. It is better for government to increase financial subsidies for bicycle-sharing users and producers. [ABSTRACT FROM AUTHOR]

Abstract As a significant basic industry for the national economic development, coal chemical industry is one of the main contributors to energy consumption and CO 2 emission. In this paper, the CO 2 emission in the time series of 2020 and 2030 was calculated and the Logarithmic Mean Divisia Index (LMDI) method was employed to explore the driving forces of CO 2 emission change. According to the industry development, the CO 2 emission in 2020 and 2030 was tentatively predicted. The results show that China's coal chemical industry has experienced a significant increase in CO 2 emission, from 177.87 million ton CO 2 (MtCO 2) to 427.19 MtCO 2 in 2005–2015, with an average annual growth rate of 9.16%. Currently, the coal-to-ammonia industry is the largest contributor. According to the decomposition analysis, the economic growth and energy intensity are the two positive factors and the industry structure is a negative factor to carbon emission change. In 2020, the CO 2 emission will be 617.34 MtCO 2 under slow development scenario and 759.69 MtCO 2 under rapid development scenario. In 2030, the CO 2 emission will reach 1041.90 MtCO 2 and 1440.13 MtCO 2 under slow and fast development scenarios, respectively. The coal-to-olefins industry will take the place of coal-to-ammonia and turn to be the largest one in 2020 and 2030 if no CO 2 capture, utilization and storage (CCUS) technologies are adopted. It is probable that the contribution from coal-to-methanol will also play important role for CO 2 emission due to its rapid development. In addition, by 2030, if coal-to-natural gas industry develops as planned, its CO 2 emission will significantly increase, which has the potential to be equivalent to that of olefins industry. Highlights • The CO 2 emission evolution trend in China's coal chemical industry is analyzed. • The major driving factors of CO 2 emission change are identified and the effect sizes of various factors are evaluated. • The CO 2 emission in 2020 and 2030 is forecasted. • Policy implications to policymakers are provided. [ABSTRACT FROM AUTHOR]

Abstract China is the world's largest producer and consumer of non-ferrous metals, and the non-ferrous metals industry is energy- and emission-intensive. The CO 2 emissions of the industry have increased nearly four times from the level in 2000 to reach 310 million tons in 2014. To cope with the issues of CO 2 emission and other environmental problems under the background of low-carbon development, it is necessary to analyze the CO 2 emission performance of China's non-ferrous metals industry. Based on group heterogeneity, this paper uses data envelopment analysis to calculate the Shephard distance function and then uses the Shephard distance function and non-parametric meta-frontier methods to construct the meta-frontier Malmquist CO 2 emission performance index (MMCPI) of China's non-ferrous metals industry during the period 2006–2014. The index is further decomposed into three parts: technical efficiency change, technological progress change and technological catch-up effect. The results showed that the MMCPI of China's non-ferrous metals industry exhibits an upward trend during the review period. The improvement in CO 2 emission performance is most significant in the central region, followed by the eastern and western regions. Based on the decomposition of MMCPI, the effect of technological progress are significantly different for the different regions, indicating that more targeted policies are need for different regions. [ABSTRACT FROM AUTHOR]

Abstract Theses on China's low-carbon economy focus on the driving forces of carbon emissions, energy–carbon efficiency, and the carbon–economy nexus. Meanwhile, comprehensive frameworks that assess China's green economy and also analyze its driving forces are lacking. This paper constructs a green productivity index based on the Global Malmquist–Luenberger productivity index to evaluate the development of the low-carbon economy in China. A panel vector auto-regression model is adopted to further analyze the endogenous interactions and dynamic relationships among aspects of the green economy and its influencing factors. Empirical results show that China has seen a balanced development of green economic growth in 2000–2016, achieved in a series of clear stages. To maintain the sustainable growth of the low-carbon economy in the future, China must rely more on technological progress. This research also makes some important discoveries that have not been found in previous studies: the impact of China's industrial structure and energy consumption structure on the green economy are short term, having a duration of impact of approximately four years. Finally, we provide an assessment of provincial green economy development and describe the corresponding policy implications. Graphical abstract Image Highlights • A comprehensive analysis of China's green economy. • A slack-based Global Malmquist–Luenberger index is adopted to calculate the Green Productivity Index in China. • The stage characteristics of green economic development are identified. • A panel vector autoregressive model is used to analyze the interactions among aspects of the environmental economic system. • The findings that the impact duration of energy structure, industry structure, and urbanization on the green economy is about four years. [ABSTRACT FROM AUTHOR]

Abstract Despite the impact of urbanization on carbon emission has been extensively studied in recent years, the mechanisms by which urbanization, real estate investment affect carbon emissions are still unclear. Different from previous studies focused on direct effect, this paper investigated the impact of urbanization and real estate investment on China's carbon emissions with considering of the provincial contribution and spatial spillover effect. Using the multiplicative logarithmic mean Divisia index (M- LMDI) model, spatial panel data model and panel data of 30 provinces in China over the period 1997–2015, the results suggested that the contributions to carbon emissions and their driving mechanisms were significantly different across provinces. The top five provinces in China that contributed the most to the growths of carbon emissions in China were Shandong, Guangdong, Hebei, Jiangsu, and Henan, with cumulative effects of 10.28%, 10.28%, 5.44%, 5.19%, and 5.09% respectively. The direct impact of urbanization on carbon emissions was significantly negative, but its spatial spillover effect was significantly positive, which suggested that the effect of urbanization on carbon emissions shows significant "pollution transfer effect" after introducing the spillover effect. Due to the characteristics of non-movability and long investment period, the impact of real estate investment on carbon emissions was fixed in the local region, and there was no spillover effect to the adjacent regions. Because of the existence of mutual promotion mechanism between urbanization and real estate investment, the interaction between the two had significant positive direct and spillover effects on carbon emissions, which indicated that the interaction between the two created a reduction effect on both local and adjacent regions. The research can effectively identified the provinces that contribute a lot to China's carbon emissions, and made the decomposition and implementation of the national carbon emission reduction targets more targeted. At the same time, urbanization policies should be combined with real estate policies in the process of carbon emission reduction. [ABSTRACT FROM AUTHOR]

Abstract Economic development has promoted urbanization in the Beijing-Tianjin-Hebei (BTH) region. With the improvement of living standards, residential consumption have become an important contributor to regional carbon emissions. Using an input-output model, we calculated direct and indirect carbon emissions from both urban and rural residential consumption in the BTH region from 2002 to 2012, and then explored the main factors contributing to indirect carbon emissions from residential consumption using a structural decomposition analysis. Results showed that direct carbon emissions from residential consumption increased from 47.13 million tons (MtC) in 2002 to 123.34 MtC in 2012 and indirect carbon emissions from residential consumption increased from 210.36 MtC in 2002 to 550.00 MtC in 2012. Carbon emission intensity and residential consumption level were the main factors affecting indirect carbon emissions during 2002–2012, with varying effects in different sub-regions. Carbon emission intensity played negative effects in Beijing (−37.19 MtC) and Tianjin (−55.39 MtC), positive effects in Hebei (92.89 MtC). Residential consumption level played positive effects in the three sub-regions (79.94 MtC in Beijing, 31.91 MtC in Tianjin and 155.52 MtC in Hebei). Increases in intermediate demand, residential consumption level and population size enhanced indirect carbon emissions. Based on the analysis, this paper contributed to carbon emission reduction strategies in the BTH region. Highlights • Direct carbon emissions from residential consumption increased to 123.34 MtC in 2012. • Indirect carbon emissions from residential consumption increased to 550.00 MtC in 2012. • Carbon emission intensity and residential consumption level were the main impact factors. • Intermediate demand, residential consumption level and population size played positive effects. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we give an overview of the situation of CO2 emissions in both Beijing and Tokyo and discuss and compare the causes for their emission changes according to decomposition based on both social activities and fuel varieties. We find that in order to enjoy a sustainable development, Beijing needs to learn from Tokyo especially in energy consumption area. At the end of the paper, the cooperation between these two metropolises is summarized. [Copyright &y& Elsevier]

Abstract: Chinese government committed to reducing carbon dioxide emissions per unit of GDP by 40% to 45% by 2020. As the capital and one of the biggest cites, Beijing expected to both keep higher GDP growth than average and cut unit GDP carbon emission, and has to adjust the relevant energy strategy in near future. The paper analysis the characteristics of energy supply and energy consumption in Beijing, and setups the economic-energy-environment-oriented reference energy system (RES), selects MARKAL as the optimal model and constructs districted multi-period linear programming matrix, which including 15 energy carriers, 4 energy processes, 17 energy conversions, and 18 energy end-use sets. Furthermore, the paper designs 11 scenarios in various pollute emission restrictions, and establishes the total economic cost as the optimize target, the low-carbon emission as main restriction, to obtain the suitable energy supply structure and end-use technology structure. At last, we have the conclusion that Beijing can attach the demands of cutting carbon emissions per unit of GDP by 45% under the scheduled GDP growth. [Copyright &y& Elsevier]

Abstract Carbon emission rights allocation affects the effective operation of carbon trading system, and then the achievement of energy saving and emissions reduction objectives. Reasonable allocation scheme should meet the principle of justice. Carbon emission rights allocation based on energy justice is a novel and worth discussing subject. This paper explores the optimization of carbon emission rights allocation based on energy justice. The justice-based model is built with the aid of Gini coefficient. The way to optimize allocation scheme with constraints of population, ecological productive land, fossil energy resources and GDP is discussed. Results show that fossil energy resources and ecological productive land play more important role in the allocation. The prime example is Inner Mongolia, its quota percentage change reaches up to 150.01%. As the GDP and population growth rate are fixed in a given interval, the quota allocation in eastern China shows some interesting results. When the GDP growth rate is 6.25%, the quotas of eastern China will not change with varying population growth rate. The allocation will enter a relative stable stage as the population growth rate is greater than or equal to 6.4‰. These results can provide China with experience to deal with the new problem appeared in carbon trading system like two-children policy and the new normal of economic growth. Highlights • Energy justice-based carbon emission allocation with multiple constraints is explored. • Provincial allocation results in China are related to location-related factors. • Two-children policy has effect on optimal allocation results in eastern China. • The critical values of population and economic growth rate in this model are found. [ABSTRACT FROM AUTHOR]

Abstract The construction industry is one of the largest energy consumers and CO 2 emitters in China. This paper primarily aimed to explore the driving forces of energy-related CO 2 emissions (ECE) from the construction industry. Adopting a comprehensive decomposition approach, this study decomposes the changes in ECE into eight factors. The main results provide the following findings. (1) Industrial activity was the largest factor pushing the growth of CO 2 emissions, driving up CO 2 emissions in all years and contributing to a 174.65 Mt CO 2 emissions increase in total. (2) In contrast, advances in industrial output technology represented the dominant factor inhibiting CO 2 emissions, cumulatively reducing CO 2 emissions by 99 Mt. (3) The effects of potential energy intensity changes and industrial output technical efficiency fluctuated in different years but exerted positive effects on CO 2 emissions over the entire period. (4) Additionally, changes in spatial structure, energy-saving technology, and energy consumption structure as well as energy usage efficiency all contributed to emissions reductions to varying degrees. The CO 2 emissions of the construction industry increased in all provinces, while emissions changes and their factor effects varied distinctly across provinces. Highlights • Direct and indirect CO 2 emissions in China's construction industry are calculated. • Impacts of driving factors are quantified by combining the PDA and IDA methods. • Industrial activity is mainly responsible for CO 2 emissions increase. • Industrial output technology change is the dominant curbing factor. • Factor effects of China's construction industry vary distinctly across provinces. [ABSTRACT FROM AUTHOR]

China has become the global largest CO 2 emitter, and CO 2 emissions from China’s power industry account for almost half of the total. Therefore, the power sector plays a key role in achieving low-carbon economy. It is imperative to formulate comprehensive policy implications for the power sector from both macro and micro perspectives to achieve the target of emission reduction. This paper selected seven socio-economic and technological factors involved in the whole power industry to investigate the mechanism driving CO 2 emissions based on the extended STIRPAT model. The results show that the order of factors’ absolute elasticity coefficients is GDP per capita (0.245) > power generation efficiency (−0.237) > power consuming efficiency (−0.189) > line loss rate (−0.184) > electricity practitioner population (0.143) > industrial structure (0.082) > generation structure (0.068). Further, it is necessary to discuss how a specific power enterprise responds under the low-carbon generation policy to maximize its own interest. The evolutionary game model between power enterprise and government is established and results indicate that it is critical to slash low-carbon production cost, enhance returns on low-carbon production and strengthen the regulation of power enterprises, and reduce the supervision cost of government. Accordingly, policy recommendations are proposed from both macro and micro perspectives for CO 2 emission reduction of power industry. [ABSTRACT FROM AUTHOR]

Reliable energy statistics serve as the foundation and starting point for understanding the climate policies of any country. As the most comprehensive sources of energy data for China, China Energy Statistics Yearbooks (ESY), published by the National Bureau of Statistics (NBS), underwent three major revisions since 2005. This paper analyzes how these three major revisions correspond to data on China's energy use from 1996 to 2012, and theirs impacts on CO 2 emissions, emission intensity and the share of non-fossil energy in total energy consumption, which are key indicators of China's climate policies. Some notable changes include CO 2 emissions for 2012, which increased by 594 Million tons – a figure equivalent to South Korea's annual emissions, which implies that China's emissions at peak level will be higher than previous estimation. Meanwhile, revised emission intensity data show a higher amount and lower decreasing rate, which means that China's achievements in decreasing emission intensity during 2005–2012 have been overestimated, while future difficulties for achieving the goal of 40–45% reduction will be greater. On the share of non-fossil fuel energy in China's total energy mix, the adjustments increased the indicator by 1.26%, reflecting the fact that China's effort in developing non-fossil energy had been underestimated. Discrepancies in reported scattered coal in different statistics versions are the main contributors to these changes. To further enhance the reliability of its energy statistics, and thereby its climate policies, China should remove incentives for misreporting through legal means, and make the technical system for data collection more comprehensive and accurate, with particular emphasis on scattered coal. [ABSTRACT FROM AUTHOR]

Highlights • The input–output model and ecological network analysis (ENA) are integrated. • The control and dependence conditions of economic sectors in China are analyzed. • The key regions and sectors for carbon mitigation of China are identified. Abstract In this paper, multi-regional input–output analysis (MRIO) and ecological network analysis (ENA) are combined to assess carbon flows within China and identify key regions and sectors in the context of spatial heterogeneity for effective carbon mitigation. An interregional carbon network model is established by articulating the directions and magnitudes of carbon flows based on MRIO. ENA is then used to unveil indirect carbon flows and mutual relationships among regions. The results show that the northwest is the largest controller for most regions in China. Most carbon emissions in the rest of China are induced by the east’s final demand and substantial consumption. In addition, at sectoral level, the control and dependence abilities vary by region in China. This study provides an integrated framework to investigate interregional carbon emission structure, identify efficient pathways for coordinated emission mitigation, and reduce global carbon inequality across regions. [ABSTRACT FROM AUTHOR]

The potential relocation of various industrial sectors from China to India and countries of the SE Asian region presents low cost opportunities for manufacturers, but also risks rising for energy demand and CO 2 emissions. A cross-country shift of industrial output would present challenges for controlling emissions since India and SE Asian countries present higher industrial emissions intensity than China. We find that although there is a convergence in emissions intensity in the machinery manufacturing and paper and pulp industries, there are significant variations in all other industrial sectors. Indian emissions intensity is double that of China in the iron and steel and textile and leather industries and almost triple in the cement industry; Indonesian emissions intensity is almost double that of China in the non-metallic minerals and textile and leather industries and 50% higher in the chemical and petrochemical industry. We demonstrate that the expected higher emissions are driven by both a higher carbon fuel mix intensity in the recipient countries and higher energy intensity in their industrial activities. While industrial relocation could benefit certain countries financially, it would impose considerable threats to their energy supply security and capacity to comply with their Paris Agreement commitments. [ABSTRACT FROM AUTHOR]

High-Carbon Consumption Behavior (HCCB) of urban residents is one of the main obstacles to the goals of low carbon development in China with the rapid development of the national economy. Among all the uptrend influences, the one caused by conspicuous consumption is worth more attention. In this paper, a structural equation model was applied to analyze the impact path of conspicuous consumption motivation on HCCB. Multiple group analysis was then used to test the moderating effect of individual face conscious and demographics on the impact. Our data originated from a social study of Xuzhou, Jiangsu province, China (n = 351). The results indicated four leading aspects. First, the raising habitual HCCB is mainly affected by three points, materialistic hedonism, interpersonal mediation and social status demonstration, and the influence is reduced in successively. While communication of belonging to/dissociation from a group and ostentation have little effect on habitual HCCB. The second, purchased HCCB of residents is mainly impacted positively by materialistic hedonism, and other factors have weak influence on it. The third, face consciousness has a significant moderating effect on the relationship between residents’ conspicuous consumption motivation and HCCB. People with strong face consciousness are more affected by the social status demonstration and interpersonal mediation; those with weak face consciousness are only driven by material hedonism. The last, gender, marital status, age, education level, and household monthly disposable income have significant moderating effects on the relationship. Among them, the HCCB from males, young people, married persons, highly educated people, and higher income groups is more affected by materialistic hedonism, interpersonal mediation, and social status demonstration, while from females with lower education, and lower income groups is more likely to be driven by social status demonstration. [ABSTRACT FROM AUTHOR]

With rapid economic development, higher income levels, urbanization and other socio-economic drivers, people's lifestyles in China have changed remarkably over the last 50 years. This paper uses the IPAT model (where I =Impact representing CO2 emissions, P =Population, A =Affluence, and T =emission intensity) to analyze how these main drivers contributed to the growth of CO2 emissions over this time period. Affluence or lifestyle change has been variously recognized as one of the key factors contributing to CO2 emissions. Through comparative analysis of the development of five regions in China, we trace lifestyle changes since the foundation of the People's Republic of China (PRC) in 1949 until 2002. We find that household consumption across the five regions follows similar trajectories, driven by changes in income and the increasing availability of goods and services, although significant differences still exist between and within regions due to differential policies in China and different possibilities for social mobility. There are considerable differences between the southeast and northwest and between urban and rural areas. We also found that technological improvements have not been able to fully compensate for the increase of emissions due to population growth and increasing wealth, which is also in line with results from other studies. Finally, this paper emphasizes that developing countries such as China, which is home to 22% of the world population and a growing middle class, and which is on a fast track to modernization, need to ensure that people's lifestyles are changing towards more sustainable ways of living. China has been investing heavily in infrastructure and thus creating the emissions of tomorrow. Thus investing, for example, in public transport and low energy building today will help reduce emissions in the future and will support more sustainable lifestyles. [Copyright &y& Elsevier]

This paper presents a decomposition analysis of energy-related CO2 emission in China for the period 1991–2006 divided into three equal time intervals. The complete decomposition method developed by Sun is used to analyze the nature of the four factors: CO2 intensity, energy intensity, structural changes and economic activity. The results show that economic activity has the largest positive effect in CO2 emission changes in all the major economic sectors and China has achieved a considerable decrease in CO2 emission mainly due to the improved energy intensity. However, the impact of CO2 intensity and structural changes is relatively small. Structural changes only exhibit positive effect to the CO2 mitigation in agricultural sector, and CO2 intensity also contributes to the decrease of CO2 emission in transportation sector. Moreover, a formula about CO2 mitigation is presented in this paper, which shows that China has made a significant contribution to reducing global CO2 emission. [Copyright &y& Elsevier]

It is estimated that there will be 85,000 tons of End-of-Life (EoL) wind turbine blades in China by 2050. How to disposing discarded blades has become a significant problem restricting the development of wind power industry in China. To this end, a life cycle assessment (LCA) is performed to measure the carbon reduction (CR) potential of four disposal scenarios of EoL LM 37.3 P2 blades. The contribution of each scenario to reduce the carbon emission intensity of a specific wind farm is further evaluated. At the same time, the critical transportation distance to maintain the CR potential of each scenario is estimated. The results show that: firstly, the disposal scenarios with the greatest and smallest CR potential are producing concrete by EoL blades instead of cements and producing concrete by EoL blades instead of aggregates, respectively. The former one is determined as the baseline scenario, which can reduce 4516 kg CO2-eq carbon emissions per functional unit. Secondly, the critical transportation distances for incineration for electricity, co-processing and producing concrete by EoL blades instead of cements are 895 km, 3309 km and 9716 km. Finally, a reasonable recycling strategy can reduce the life-cycle carbon emission intensity of Datang Zhaluteqi 49.5 MW Wind Farm from 12.51 g CO2-eq/kWh to 9.22 g CO2-eq/kWh. This study not only quantifies the CR potential of different scenarios, but also offers important implications to promote blade disposal technology and improve the wind turbine blade recycling management. [Display omitted] • This paper measures the carbon reduction potential of EoL blades based on LCA. • Four disposal scenarios of EoL blades are considered. • The contribution of each scenario for a specific wind farm is further evaluated. [ABSTRACT FROM AUTHOR]