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With the gradual increase of international willingness to reach the carbon peak and carbon neutrality, this paper decomposes the influencing factors of China's carbon emission changes from 2008 to 2019 using the Logarithmic Mean Divisia Index model (LMDI), and analyzes the contribution amount and rate of each influencing factor. The results found that: for the whole country, the cumulative growth of carbon emissions during the study period is about 416,484.47 (104 tons), among which the economic growth effect plays a major role in promoting, with a cumulative contribution rate of 284.16%; The increase in regulation intensity and the optimization of industrial structure, however, suppress carbon emissions well, with a cumulative contribution rate of about – 199.21% and − 64.75%, respectively, during the study period. For economic regions, the cumulative influence direction of each driver is the same as that of the whole country, while the population size effect in the northeast economic region and the regulation input effect in the eastern coastal economic region act in the opposite direction from other economic regions, and the carbon emission reduction direction of the energy intensity effect varies from one economic region to another. Accordingly, this paper proposes policy recommendations to enhance regulatory intensity, optimize industrial and energy consumption structure, implement localized emission reduction strategies, and promote synergistic emission reduction in economic zones. [ABSTRACT FROM AUTHOR]

Industrial structure low-carbon restructuring is an essential channel to accelerate China's economic growth and fulfilling carbon emission reduction goals. Whether carbon emission trading pilot policy, as an influential carbon reduction instrument, fosters industrial structure low-carbon restructuring is of major significance to green economic development. This paper empirically investigates the shock of the carbon emission trading pilot policy on industrial structure low-carbon restructuring using the differences-in-differences (DID) and synthetic control method (SCM). Statistics reveal that sectors with low carbon productivity, such as electricity, steam, and hot water production and supply, ferrous metal smelting and pressing, etc., and sectors with high carbon productivity, such as electrical equipment and machinery, electronics and telecommunication equipment, etc. The industrial structure did not develop a stable trend of change before the 12th Five-Year Plan, but a stable trend of low-carbon restructuring emerged after such a period. Carbon emission trading pilot policy significantly facilitates industrial structural low-carbon restructuring. Carbon emission trading pilot policy inhibits energy-intensive industries in the industrial sector significantly, which promotes industrial structure low-carbon restructuring. Therefore, policymakers need to develop a nationwide carbon emission trading market that includes more industries to guide production factors to industrial sectors with high carbon productivity for industrial restructuring and dual carbon goals. [ABSTRACT FROM AUTHOR]

The carbon emissions of sectors and households enabled by primary inputs have practical significance in reality. Considering the mutual effect between the industrial sector and the household, this paper firstly constructed an environmentally extended semi-closed Ghosh input–output model with an endogenized household sector to analyze the relationship between carbon emissions and the Chinese economy from the supply-side perspective. The structural decomposition analysis and the hypothetical extraction method were remodified to identify the supply-side driving effects of the changes in carbon emissions and investigate the net carbon linkage. The results show that the electricity, gas, and water supply sector was the key sector with the highest carbon emission intensity enabled by primary inputs. The household sector had an above 93% indirect effect of the enabled intensity, with its enabled intensity dropping significantly by more than 55% from 2007 to 2017. The operating surplus and mixed income caused 3214.67 Gt (34.17%) of the enabled emissions in 2017. The supply-side economic activity, measured by the value added per capita, was the main factor of the carbon emission growth, mainly attributed to the development of the manufacturing sector and the electricity, gas, and water supply sector. The emission intensity and allocation structure both brought a decrease in carbon emissions. The electricity, gas, and water supply sector and the manufacturing sector were the major sources of the supply-induced cross-sectoral input emissions, while the commercial and service sector and the household sector were the top source of supply-induced cross-sectoral output emissions. This paper sheds light on the policies of the carbon emission abatement and the adjustment of the allocation structure from the perspective of supply. [ABSTRACT FROM AUTHOR]

Copyright of China Population Resources & Environment is the property of Shandong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

China has become the largest energy producer and consumer in the world. Its carbon emissions account for 80% of its total carbon emissions, while the carbon emissions caused by energy consumption in the power industry account for more than 50%. To ensure that the 2030 carbon-peak and 2060 carbon–neutral targets are achieved, it is imperative to carry out low-carbon energy transformation in the power industry. The paper compares and analyzes the technical level of six high-energy-consuming industries: power, steel, cement, aluminum smelting, petrochemical industry, and coal chemical industry in terms of low carbon. The results show that the structural adjustment of China's high-energy-consuming industries has reached the upper limit, and the low-carbon transformation of power and energy has become inevitable. The carbon emissions of China's six regional power grids are statistically analyzed. The background of the power generation proportion of China's thermal power, hydropower, nuclear power, wind power, solar power and other different energy systems from 2018 to 2020 is analyzed, and the development trend is predicted. The low-carbon emission path of power energy is proposed. Based on the EnergyPLAN model, the power energy structure of carbon peaking in different scenarios from 2020 to 2030 is constructed, and the power energy system's carbon dioxide emission reduction paths under different scenarios are obtained. The sustainability impact of different power generation combination scenarios is comprehensively evaluated using the multi-index evaluation method, and the optimal path of the power system to energy scenario is selected. The research conclusion provides a basis for the power sector's renewable energy power generation path selection. [ABSTRACT FROM AUTHOR]

Regarding the goal of "carbon peaking and carbon neutrality," an urgent practical problem is how green finance decreases carbon emissions. This paper uses the dynamic spatial Durbin model and China's provincial panel data to empirically test the impact of green credit on carbon emissions. The results show that green credit effectively curbs carbon emissions, and has significant spatial spillover effects on the carbon emissions. In the short run, the spillover effects of green credit on carbon emissions are greater than the direct effects, but in the long run, the direct effects of green credit on carbon emissions are greater than the spillover effects. The mechanism test finds that upgrading industrial structure is an important transmission channel for green credit to affect carbon emissions, and energy consumption only plays a part of the intermediary role in the direct impact of green credit on carbon emissions. However, green credit has not achieved the goal of carbon emission reduction by promoting low-carbon technology innovation. [ABSTRACT FROM AUTHOR]

Based on mainland China's provincial OFDI and carbon emissions data from 2003 to 2018, this paper applied a panel fixed-effects model and spatial econometric model to empirically test whether China's OFDI can be a powerful tool to achieve the "carbon neutrality" target. The empirical results indicate that China's OFDI significantly increases carbon emissions, but this effect has temporal and spatial differences. After incorporating spatial factors into the analysis, the impact of OFDI on carbon emissions differs when modelled by different spatial weight matrices. The green effect of OFDI has the problem of poor channels. It is impossible to achieve energy savings and emission reduction by promoting green technology innovation, improving the rationalization of the industrial structure or reducing energy consumption. The test results of the moderating effect indicate that the development of green finance can weaken the positive effect of OFDI on emissions. [ABSTRACT FROM AUTHOR]

With the gradual implementation of strategies to achieve the goals of reaching peak carbon emissions and carbon neutrality, the heterogeneous performance of low-carbon technological progress driving carbon emission reduction in different situations has become an important basis for targeted technological carbon reduction. As an important special subject of national energy resource security and carbon emission reduction, whether resource-based cities can reach peak carbon emissions simultaneously is a key to the achievement of the ' dual carbon' goals. This paper reviewed the theoretical literature on low-carbon technology progress and carbon emissions in resource-based cities, and extracted the their driving mechanisms. Based on the panel data of 116 prefecture-level resource-based cities in China from 2005 to 2019, this paper innovatively considered six undesirable outputs with resource-based city characteristics to define the low-carbon technological progress of such cities, and used the DEA-Malmquist index model, STIRPAT model, and threshold model to clarify the current situation of low-carbon technological progress and carbon emissions in resource-based cities. The study also carried out a deep analysis of the driving relationship and threshold effect between low-carbon technological progress and carbon emission reduction, and compared and analyzed their multiple heterogeneity. The study found that during the sample period, the low-carbon technology progress of these 116 prefecture-level resource-based cities showed a phased upward trend, and that carbon emissions had obvious regional heterogeneity and type heterogeneity. The progress of low-carbon technology in resource-based cities had a certain inhibitory effect on carbon emissions and presented type heterogeneity, regional heterogeneity, and a double threshold effect. In different threshold ranges, the driving effects of low-carbon technology on carbon emission reduction effect and carbon emission reduction rebound effect were different. The driving effects of other seven control variables, such as gross domestic product, command-based environmental regulation, market-based environmental regulation, voluntary environmental regulation, industrial structure, energy consumption structure, and foreign direct investment, on carbon emissions were also different. Finally, based on the research conclusions, regarding different regional resource-based cities, different types of resource-based cities, and different levels of low-carbon technology progress in resource-based cities, policy recommendations related to low-carbon technology progress and carbon emission reduction are proposed in a targeted manner, aiming to promote the improvement of low-carbon technology progress in resource-based cities and the simultaneous achievement of carbon emission reduction targets. [ABSTRACT FROM AUTHOR]

China is currently in the process of the middle and late stage of industrialization, and energy-related CO2 emissions have reached 10 Gt. This paper models energy consumption and related CO2 emissions and analyzes the development trends of various driving factors of CO2 emissions, explicitly considering China's economic and social development goals in the medium- and long-term. Different scenarios for 2020–2060 are projected based on the Kaya identity. Energy consumption will peak at 6,200 Mtce in 2035 in the BAU scenario with the energy-related CO2 emissions peaking at 11.1 Gt in 2026–2027 advanced by the rising non-fossil energy share, while energy consumption and CO2 emissions in the accelerated transition scenario would be potentially reduced by 300 Mtce and 300–400 Mt respectively. In the BAU scenario, the net CO2 emissions will remain around 2,000 Mt in 2060, after removing 1,800 Mt by CCS/CCUS, indicating that China needs to enhance its post-2030 policy to deliver the carbon neutrality pledge. Steady energy efficiency improvement, radical industrial and energy restructuring are three key driving forces for carbon neutrality. [ABSTRACT FROM AUTHOR]

To reduce carbon emissions, the Chinese government is considering introducing a differentiated industrial carbon tax on enterprises outside the carbon trading market in the future. An efficient carbon tax must consider not only how carbon taxes impact the current economy but also how the size of the tax should be adjusted across time due to external changes. To calculate the optimal industrial carbon tax for China which is subject to certain constraints, this paper investigates the economic and environmental effects of four possible industrial carbon tax rate models under carbon intensity constraints from 2021 to 2030 by a dynamic input–output optimization model. The results show that the dynamic tax rate model leads to larger fluctuations in GDP growth than the other tax models, with a low initial tax rate in the beginning and a high tax rate exceeding ¥180/t in 2030. Second, a large quantity of capital stock is distributed across the energy-intensive industries, which leads the existing capital investment structure to be path-dependent. This offsets the performance of carbon taxes. Third, indirect energy-intensive industries such as construction and transport are insensitive to the industrial carbon tax. Finally, comparing the impacts of the four tax rate models, the optimal industrial carbon tax for China is found to be a fixed differentiated tax rate, in which energy-intensive sectors are taxed ¥75/t and low-carbon sectors are taxed ¥50/t. [ABSTRACT FROM AUTHOR]

Carbon neutrality is an important policy in the current global response to climate change and has been widely recognized by various industries. In the process of promoting carbon neutrality, new energy plays a pivotal role. In this study, the definition and connotation of new energy and its role and specific operation in the energy transition of carbon neutrality are firstly explained. Promoting new energy development requires significant green and low-carbon investments. Taking China as an example, this paper analyzes the opportunities brought by the carbon neutral process to the field of green finance and analyzes the main features and development trends of green finance in China at present. Then this paper proposes policy recommendations to strengthen the development of green finance in China in terms of improving the green financial policy system, enhancing the supply capacity of green financial services, and optimizing the supporting environment for green financial development. Finally, this paper analyzes the measures and experiences of the United States in promoting low-carbon development and proposes countermeasures for China's low-carbon development on the basis of the five major relationships that need attention in China's carbon-neutral process. That is, strengthen the top-level design and improve the regulatory policy system; optimize the energy structure and increase the proportion of clean energy; optimize the industrial structure and reduce energy consumption in key industries; build a complete low-carbon technology system and promote low-carbon technology research and development and demonstration applications, and encourage local conditions to explore low-carbon development paths. The development of green finance can contribute to the advancement of new energy technologies, thus contributing to the achievement of carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of the Chinese Ceramic Society is the property of Bulletin of the Chinese Ceramic Society Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Whether renewable energy consumption is beneficial to reducing CO 2 emission intensity and carbon emissions in the context of the goal of "carbon peak and carbon neutrality" in China. To prove this conjecture, considering the spatial spillover effect of carbon dioxide, this paper adopts the spatial Dubin model for empirical analysis based on the panel data of China's 30 provinces over the period 2002–2019. This study explores the CO 2 intensity mitigation effect of China's renewable energy consumption and further investigates the mediation role of technological innovation, industrial structure upgrading and optimization, and energy efficiency in the nexus between renewable energy consumption and carbon intensity. The main findings present that: (1) China's carbon emission intensity is characterized by significant spatial correlation; (2) Renewable energy consumption can significantly reduce carbon intensity and per capita carbon emissions; (3) The mediation effect of renewable energy consumption in reducing carbon emission intensity is to promote technological innovation and industrial structure upgrading, as well as improve energy efficiency. Based on the conclusions, this paper offers several policy implications for governments to reduce CO 2 emission intensity. • The impact of renewable energy consumption on CO 2 emission intensity is explored. • Renewable energy consumption can reduce carbon emission intensity and per capita carbon emissions. • Renewable energy consumption reduces CO 2 intensity through the spatial mediation effect. [ABSTRACT FROM AUTHOR]

In order to achieve the carbon peaking and carbon neutrality goals, energy-intensive industries in China, as the main sectors of energy consumption and carbon emissions, had huge pressure to reduce emissions. In addition, the reduction of vegetation area led to a decline in carbon sink capacity, which further exacerbated the imbalance of mutual penetration between carbon source and carbon sink. Therefore, this article considered the role of carbon source and carbon sink and defined and calculated the "carbon emission penetration" (CEP) of the six energy-intensive industries from 2001 to 2020. The KAYA formula and the LMDI method were used to decompose the driving factors of CEP in the three aspects of scale, intensity, and structure. The combined model of STIRPAT and the environmental Kuznets curve (EKC) was used to simulate and analyze the equilibrium points of energy-intensive industries in China from the perspective of factor driving. The analysis results indicated that there were differences in the fluctuation trend of CEP in the six energy-intensive industries, which can be divided into three types: "two-stage growth," "steady growth," and "single peak." Secondly, the driving factors from the three aspects of scale, intensity, and structure—emission intensity (CE), energy consumption intensity (EI), industrial structure (IS), economic scale (GP), and carbon sequestration scale (PCA)—had differences in industry and time dimensions. And the realization time of the CEP equilibrium points of six industries showed a three-level gradient feature significantly. This can provide some reference for the low-carbon transformation of six energy-intensive industries and optimization of China's environmental management under the carbon peaking and carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Global warming is evolving into a crisis affecting the future of humanity. As the world' s second largest economy, China is actively involved in global climate governance, proposing to achieve the goals of reaching peak carbon emissions by 2030 and achieving carbon neutrality by 2060, and has successively introduced the corresponding ' 1+N' policy system. This paper attempts to interpret and analyze 23 policy texts relevant to the achievement of the goals with over 160 000 characters from the CPC Central Committee, the State Council, and relevant ministries and provinces through two typical qualitative research methods-ground theory and institutional grammar tool, to outline the elemental structure and functional profile of the pathways of China' s carbon peak and carbon neutrality policies, and to clarify the group structure and regulation intensity of different policy pathways. Based on grounded theory, it is found that these pathways are already very comprehensive and complete. Among them, the policy pathways under the administrative mechanism include: high energy consumption and high emission industrial control; regulations and standards systems; carbon reduction governance in key industries; control over the amount and intensity of energy consumption; and carbon absorption capacity of ecosystems. The policy pathways under the market mechanism include circular economy development; energy transformation development; cap-and-trade system for carbon emissions; green finance development; and green transformation development. The results of institutional grammar tool research show that relevant policy pathways are dominated by ADIC normative condition statements (177, accounting for 52%), followed by AIC strategy statements (130, accounting for 38%), while ADICO rule-based statements are the least, with only 33, accounting for 10%. Given the pressure of time constraints and heavy tasks to achieve the goals, ADICO' s institutional grammar structure is the most desirable policy statement paradigm because it is more intense in its policy regulation, and it is easier to achieve its governance effectiveness. Undoubtedly, policy regulation is an important tool to effectively alleviate the pressure of the governance of the goals and to ensure the effectiveness of such governance. Policy regulation mainly focuses on the industrial sector with high energy consumption and high emissions, relying on top-down hierarchical organization and using political mobilization and administrative decrees as means to promote governance in the high carbon emission sector. By further constructing a theoretical framework of regulation mechanisms, relevant governance paradigms are classified as ' mandatory governance' and ' flexible governance' according to the intensity of regulation. It is found that the underlying logic behind these two paradigms is precisely the mobilization of the administrative mechanism and the allocation of resources under the market mechanism. Simultaneously, with the gradual achievement of the goals and the gradual decoupling of carbon emissions from economic development, the governance logic should gradually shift from ' mandatory governance' to ' flexible governance,' and from ' administrative hierarchical mobilization' to ' balanced allocation of market resources.' [ABSTRACT FROM AUTHOR]

Digital technology is an effective way to realize the carbon neutrality target in China. Therefore, based on panel data at the city level in China from 2006 to 2016, we take the e-commerce pilot policy as a quasi-natural experiment, using the staggered difference-in-differences (DID) method to explore the effect of digital technology development on carbon emissions and its transmission mechanism. The conclusion of this paper shows that (ⅰ) the e-commerce pilot policy has significantly reduced carbon emissions. After a series of robustness tests, this empirical conclusion is still valid. (ⅱ) The inhibitory effect of different waves of e-commerce pilot cities on carbon emissions sequentially decreases. The e-commerce pilot policy has a greater effect on reducing carbon emissions in non-old industrial based cities and non-resource-based cities. (ⅲ) Implementing the e-commerce pilot city policy mainly reduces urban carbon emissions by optimizing resource allocation, reducing energy consumption and upgrading the industrial structure. (ⅳ) In addition, implementing the e-commerce pilot city policy has a significant positive carbon-reducing linkage effect with the carbon trading pilot policy and the low-carbon city pilot policy. The findings of this paper provide empirical evidence for carbon emission reduction, which has implications for upgrading urban construction patterns and promoting green urban development. • The construction of national e-commerce pilot cities has significantly reduced the carbon emission of cities. • The inhibitory effect of different batches of e-commerce pilot cities on carbon emissions sequentially decreases. • Playing more significant effect in non-old industrial based cities and non-resource-based cities. • Reducing urban carbon emissions by optimizing resource allocation and reducing energy consumption. • Having a significant positive carbon-reducing linkage effect with carbon emissions mitigation policies. [ABSTRACT FROM AUTHOR]

For curbing the global climate crisis, China has set an ambitious target of peak carbon emissions by 2030. Beijing, the capital of China, has implemented a carbon reduction policy since 2012. Using the reduced and generalized forms of the Environmental Kuznets Curve (EKC), we deduce that both the cubic EKC and the genetic algorithm-based EKC have an N-shape. The first turning point of the three-order EKC occurs around 2011, demonstrating the effectiveness of the carbon reduction policy. However, the time series model predicts that Beijing will reach the second turning point around 2026, when the gross domestic product (GDP) is about CNY 5000 billion and carbon emissions will begin to increase again. Interpretable machine learning is proposed to explore the socio-economic drivers in carbon emissions, indicating that total energy consumption and GDP contribute the most. Therefore, we should accelerate the upgrading of energy consumption and adjust the industrial structure, thus facilitating Beijing to its peak carbon emissions and achieving carbon neutrality. [ABSTRACT FROM AUTHOR]

In the coming four-decade, China will face serious challenge while shifting to carbon neutral. Photovoltaic (PV) power, as one of the most promising clean energies, is seen as an important focus for decarbonization of the power sector in China. The novelty of this study is to use life cycle assessment (LCA) methods to analyze the CO 2 emission reduction of the PV generation industry before 2060 base on the amount of energy and resources consumed and PV generation's CO 2 reduction benefits during the whole industrial chain. This paper aims to examine CO 2 emission reduction contribution, we firstly compute the historical emissions and predict future PV waste and new power capacity from 2010 to 2060. Then, considering the change of industrial structure and technological evolution, the yearly life cycle CO 2 emission from producing stage to recycling stage is calculated. The key results show that the unit CO 2 emission of PV system producing will reduce 88.07% from 2010 to 2060. PV generation industry's total CO 2 emission has reached its neutrality between 2014 and 2015, and will reduce 33.03 Giga tons CO 2 -eq till 2060. The findings can offer relevant insights to low-carbon development of China's PV industry and will provide suggestions for policy-making. [Display omitted] • In the context of Carbon Neutrality target of China. • Explores the CO 2 emission reduction effect of photovoltaic industry in China. • Takes energy structure, technology and products structure into consideration. • Photovoltaic industry will help to reduce 33.03 Bt CO 2 till 2060. [ABSTRACT FROM AUTHOR]

The ecological protection and high-quality development of the Yellow River Basin have become major national strategies in China. Therefore, reducing carbon emissions in the Yellow River Basin through efficient industrial agglomeration is necessary for achieving the goals of carbon peak by 2030 and carbon neutrality by 2060. The Yellow River Basin is an important base for energy, chemicals, raw materials, and industry in China, making it important to study the effects of different industrial agglomeration types on carbon productivity from the perspective of agglomeration externalities. Therefore, taking 2009–2019 panel data for prefecture-level cities in the Yellow River Basin, this study uses a spatial Durbin model to investigate the spatial spillover effects of industrial agglomeration (i.e., specialized, diversified, and competitive agglomeration) on carbon productivity. Furthermore, the moderating effects of urbanization level and environmental regulation are analyzed. The results reveal, first, the existence of spatial correlation in carbon productivity across different cities in the Yellow River Basin. Second, diversified and competitive agglomeration significantly increase carbon productivity, although competitive agglomeration has beggar-thy-neighbor spillover effects. Meanwhile, the effect of specialized agglomeration is not significant. Third, the effects of different types of industrial agglomeration differ significantly between cities in different locations and with different resource endowments. Fourth, urbanization level and environmental regulation have different moderating effects in the relationship between different types of industrial agglomeration and carbon productivity. These findings provide evidence for further developing rational industrial agglomeration patterns to enhance carbon productivity in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

China has played an active and constructive role in the global combat against climate change. Municipalities play a leading role in tackling global climate change. However, despite the global efforts to push for carbon neutrality, the pathway is not yet clear. Using the municipality of Bengbu as a case, this paper explores pathways for achieving carbon emission peak and carbon neutrality in order to reach a CO 2 emission peak before 2030 in four Scenarios and develops a low emission framework taking into consideration the local economy, population, renewable resources, as well as the transport and energy sectors based on the Low Emissions Analysis Platform (LEAP) model. Meanwhile, the energy demand, the structure of the electric power generation, the CO 2 emission, and the total cost in different Scenarios are simulated respectively. The result of this study provides insight on options for energy transformation for the period of 2020–2060. The results show that the industrial sector is the largest energy consumer. The growth rate of energy demand in the primary industry and industrial sector shows downward trends. The increasement of industrial electrification rate and coal generation phasing out are crucial to CO 2 emission reduction. The large-scale deployment of renewable energy and the deployment of thermal power generation with CCUS are important for the electric power industry to achieve carbon reduction goals. Last but not the least, recommendations on energy planning for municipals to realize carbon emission peak and achieve carbon neutrality are provided. • Pathways for achieving carbon reduction targets of the municipality based on the LEAP model are explored. • The coal generation phasing out is prerequisite to CO 2 emission reduction. • The large-scale deployment of renewable energy is crucial for the electric power industry to achieve carbon reduction goals. • The deployment of thermal power with CCUS is necessary for the electric power industry to achieve carbon reduction goals. • Restructuring of industrial energy consumption and increasing the electrification rate are significant. [ABSTRACT FROM AUTHOR]

With the "carbon neutrality" target proposal, China is facing severe pressure on carbon reduction. Industrial economic activities form an essential emission source of carbon dioxide. Therefore, it is necessary to promote industrial sectors' coordinated emission reduction work. This paper uses non-competitive input-output model and structural path decomposition method to analyze the carbon emission changes from three levels of total, production layer and industrial chains, identifying the main paths and driving factors of carbon emission changes in China from 2017 to 2018. The results show that: (1) The first layer presents obvious low-carbon characteristics as a direct emission level, but the change in its carbon emissions accounted for 41.8%. (2) The increased emission of industrial chains is mainly caused by consumer spending and fixed capital formation, and emission reduction is mainly triggered by consumer spending. (3) Demand scale is an essential driving factor of carbon emission increase. The contribution rate of demand structure to emission increase and reduction industry chains is 55.1% and −16.5%, respectively, which is the biggest reason for the difference between them. Finally, targeted policy recommendations are put forward from the perspective of the emission transmission path and driving factors in the industrial chain. • The non-competitive IO model of China's CO 2 emissions is established. • SPD is applied to identify the emission increase and reduction industrial chains. • The driving factors of CO 2 emission changes in industrial chain are explored. • The comparative analysis of increase and reduction industrial chains is conducted. [ABSTRACT FROM AUTHOR]

The analysis of the implementation effect of the supply-side reform (SSR) in the industrial sector of China's provinces and the reasons behind them are of great significance for China to formulate relevant policies in the future. However, this work has not yet been carried out. Industrial development performance is closely related to energy and environmental efficiency (EEE), and the effect of the SSR implementation is directly reflected in EEE. This study fills this gap by analyzing the EEE of 30 provinces in China from 2012 to 2017 using data envelopment analysis and Malmquist index methods. The results show that the positive effect of China's implementation of SSR has emerged. This positive effect is mainly reflected in the implementation of measures such as reducing overcapacity, which has promoted the technological innovation of enterprises. However, the low management level and resource-allocation efficiency hinder the further improvement of the implementation effect of the SSR, which should be paid special attention to in China's future supply-side reform. In addition, we believe that in the context of China's high-quality development and carbon neutrality goals, the SSR should be given more connotations, which are to increase the requirements for strengthening green and low-carbon development. [ABSTRACT FROM AUTHOR]

China launched seven emissions trading scheme (ETS) pilots in 2011, and a national ETS, at the end of 2017 in an attempt to reduce its greenhouse gas emissions (GHGs) and drive its extensive energy transition in a cost-effective way. The Hubei province pilot ETS has operated since 2014, and an analysis of its effectiveness can provide lessons for the nascent national system. This paper disaggregates Hubei's industrial carbon dioxide (CO 2) emissions from 2005 to 2018 into economic scale, economic structure, energy efficiency, and energy structure effects using the logarithmic mean Divisia index (LMDI). Difference-in-difference (DID) models then assess the implementation effectiveness of this ETS, and its impact on the main influencing factors of the LMDI. Ten cities each in the Hubei and Hunan provinces are selected as treatment and control groups, respectively, in the DID models. Results show that the change in industrial CO 2 emissions is mainly due to the economic scale and energy efficiency effects. After the ETS implementation, the energy structure effect has a limited impact on emissions, while the economic structure effect makes a negligible contribution. Moreover, the implementation of the ETS has had little demonstrable impact on industrial CO 2 emissions, gross domestic product (GDP), energy consumption intensity, and CO 2 emission intensity. This lacking of impact is caused by the GHG monitoring capacity deficits of the local Development and Reform Commission, and irrational quota allocations. Effective supervision and quota allocation should be developed to increase the impacts of the ETS. [ABSTRACT FROM AUTHOR]

• The potential gains and carbon emissions reduction of carbon trading are detected. • Three scenarios of carbon trading schemes are considered and compared. • Sectoral trading may create potential gains of 268.02 trillion yuan in 2006–2015. • Carbon emissions may decrease by 17.17 billion tonnes under sectoral trading scheme. • Sectoral trading decreases industrial carbon intensity by 19.80% during 2015–2020. Carbon trading is an important market tool in driving growth and carbon dioxide emissions reduction in industrial sectors in China. This paper attempts to assess the impacts of carbon trading on economic output and carbon dioxide emissions reduction in China's industrial sectors by employing the data envelopment analysis (DEA) based optimization models, based on three carbon trading schemes, i.e., no trading (NT), sectoral trading (ST), and sectoral-and-temporal trading (STT) during 2006–2015. Comparing with the no-trading scheme, the results indicate that, (1) the ST and STT schemes may create potential gains of 268.02 and 612.26 trillion yuan in the whole industrial during the study period, i.e., the industrial value-added would be increased by 55.17% and 73.76%, respectively; (2) the ST and STT schemes could reduce 17.17 and 19.22 billion tonnes of carbon dioxide emissions, respectively, accounting for 58.30% and 65.25% of emissions reduction in the whole industry; and (3) if carbon trading were adopted in China since 2006, its carbon intensity of industrial sectors would decrease by 34.89%, 47.44% and 19.80% under the ST scheme, and 58.93%, 31.50% and 10.25% under the STT scheme during the11th, 12th and 13th Five-Year Plan periods, respectively. [ABSTRACT FROM AUTHOR]

China has become the largest carbon-emitting country in the world since 2007. To achieve national environmental goals by 2030, the carbon emissions per unit of gross domestic product (GDP) will need to fall to 60–65% of 2005 levels. Such a dramatic decrease presents a challenge for a nation in adjusting its energy source and usage, but via monitoring of reductions, greater understanding can be gained of how carbon emitters are responding to national goals. We analyzed the change in carbon emissions from China's fossil energy consumption from population, per capita GDP, energy efficiency improvements and energy structure using a Kaya identity model and Logarithmic Mean Divisia Index (LMDI) factor decomposition method from 2006 to 2018. Results suggest that trends in carbon emissions from 2006 to 2018 can be broken down into four periods: a rapid increase period during 2006–2011, a slowdown increase period during 2011–2014, a consecutive decline period during 2014–2016 and a rebound during 2017–2018. Trends in carbon emissions were greatly affected by per capita GDP and energy efficiency. While per capita GDP increased carbon emissions, energy efficiency had a countering effect on carbon emissions. Our results suggests that China's measures in the past decade to reduce carbon emissions (i.e. carrying out carbon emissions trading on a fixed basis, readjusting the economic structure, optimizing the energy structure, improving energy efficiency and increasing forest carbon sinks) have helped to reduce carbon emissions. However, China should continue to actively respond to climate change while striving to achieve of economic sustainable development and social progress. [ABSTRACT FROM AUTHOR]