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In order to promote the balanced development of regional economy, governments at all levels are constantly introducing regional coordinated development policy (hereinafter referred to as "the Policy"). However, there is an important and interesting issue, namely, with the increasingly severe environmental problems resulted from rapid regional economic growth, what kind of impact will the Policy have on carbon emissions reduction? This is attracting wide attention from relevant stakeholders. Therefore, taking the Beijing–Tianjin–Hebei (BTH) region in China for example and through constructing the difference-in-differences (DID) model, this paper evaluated the effect of the implementation of the Policy on carbon emissions reduction. Results indicated that the Policy significantly reduced the level of regional carbon emissions in the BTH region. After carrying out a series of robustness tests, this paper still found that the above conclusions were reliable. Moreover, the mediation effect test shown that the Policy indirectly lessened carbon emissions by optimizing energy structure and reducing the intensity of carbon emissions, while the expanding of economic scale would lead to an increase in carbon emissions due to the effect from the Policy. Additionally, heterogeneity analysis revealed that the Policy had a more significant effect on carbon emissions reduction in underdeveloped regions with low environmental constraints. Overall, this paper would be beneficial to understanding the environmental effects of the Policy at the urban regional scale, thus providing an important basic theoretical basis for promoting the green and sustainable development of regional economy. [ABSTRACT FROM AUTHOR]

Energy is known as the lifeline of national development, and from the last decade or so, the security of human energy supply has been frequently disturbed by natural disasters due to global warming and frequent geological activities. In this paper, by combing the literature, we found that the past literature on the relationship between energy and natural disasters mainly focused on measuring energy consumption under natural disasters, but less on the integrated evaluation of human economic activities, energy security and natural disasters, and less on the evaluation of the energy governance efficiency of each provincial, municipal, and autonomous region government in preventing and managing exposure to natural disasters from the perspective of Chinese provinces. Therefore, in order to fill the gap in the literature in this field, this paper collects panel data of energy consumption efficiency stages and natural disaster treatment stages from 2013 to 2017 for 30 provinces in China (excluding Hong Kong, Macao and Taiwan as well as Tibet Autonomous Region) and uses the two-stage undesirable dynamic DDF model as a framework to study the relationship between economic, environmental pollution and natural disasters for the sample data and to analyze the phase-by-phase evaluation of energy and natural disaster efficiency and make corresponding policy recommendations. The following conclusions are drawn: (1) The overall efficiency of China's eastern coastal provinces is higher than that of the central and western provinces. (2) The first-stage efficiency of Chinese provinces is better than the second stage, and the difference in efficiency of the first stage of each province is smaller than that of the second stage. (3) In terms of the efficiency of disaster prevention and relief inputs, the efficiency values are generally lower in most regions of China. (4) Finally, the annual efficiency of natural disaster losses is not high in all regions, and the efficiency values are higher in the eastern coastal regions than in the central and western regions. Accordingly, this paper proposes that each province should formulate relevant disaster prevention and economic development strategies according to regional characteristics, while the central government should also propose locally appropriate coordinated governance policies to effectively control carbon dioxide emissions and air pollution, as well as increase disaster prevention publicity and incorporate disaster prevention education-related work into the performance assessment mechanism of local governments to promote the interactive development of the two. [ABSTRACT FROM AUTHOR]

Background: The processes of transport decarbonisation are complicated. In this paper, we adopt the Activity-Modal Share-Energy Intensity-Carbon Intensity of Fuel (ASIF) approach and propose a conceptual framework on the direct and indirect impact of COVID-19 on transport CO2 emissions. In the Chinese context, changes of carbon emissions associated with passenger and freight transport (including urban, rural, and inter-city transport) across different transport modes are estimated. Scenario analysis is then used to estimate the impact of COVID-19 on total transport carbon emissions up to 2030. Four scenarios, from minimal to significant behavioural changes and global recession associated with COVID-19, are generated. Results: Under the pandemic, the transport system in China was estimated to have produced 28% less CO2 emissions (1044.2 Mt) in 2020, when compared to 2019. Compared with the business-as-usual scenario, the estimated total transport carbon emissions in 2030 would drop by 6%, 15%, and 21% and 23% under the minimal-impact, low-impact, moderate-impact, and severe-impact scenarios, respectively. Conclusions: The results suggest that the processes triggered by COVID-19 alone will not be sufficient to meet the ambitious transport decarbonisation targets. To meet China's pledge under the United Nations Framework on Climate Change, the medium-term effects of COVID-19 must be combined with strong transport decarbonisation measures of modal shift and new energy applications. With these additional measures, it may be possible to advance the transport carbon peak before 2030. Lessons are relevant to other developing countries. [ABSTRACT FROM AUTHOR]

Corporate social responsibility (CSR) is becoming increasingly important in the field of corporate sustainability. However, little literature has focused on the relationship between CSR and corporate carbon emissions in developing countries. This paper aims to fill this gap by exploring the relationship between CSR and corporate carbon intensity from the perspective of financing constraints. We examine the mediating effects of financing constraints using a mediating effects model by using Chinese listed companies data from 2011 to 2019. The analysis results of this paper are as follows: (1) CSR can reduce corporate carbon intensity. (2) Financing constraints have a positive mediating role between the two. Namely, CSR can reduce the financing difficulties of enterprises, and enhance carbon–neutral capacity. (3) The carbon emission reduction effect of CSR is different in different life cycles. (4) CSR has a greater impact on the carbon intensity of state-owned enterprises, high-tech enterprises, and heavy polluting enterprises. These facts provide meaningful references for developing countries such as China to promote CSR and carbon governance. [ABSTRACT FROM AUTHOR]

Current studies do not provide a consensus on whether digital technology innovation can reduce enterprise carbon intensity despite the rise of the digital economy. This paper examines the role and influence pathway of digital technology innovation on enterprise carbon intensity using data from A-share listed enterprises in China's manufacturing industry from 2012 to 2021. The findings indicate that (1) digital technology innovation has been found to significantly reduce enterprise carbon intensity, as confirmed by numerous robustness and endogeneity tests. However, its inhibitory effect on carbon intensity shows a marginal decreasing trend. (2) In the heterogeneity analysis, it was found that digital technology innovation significantly reduces the carbon intensity of consuming coal, coke, kerosene, and diesel. From various perspectives, including enterprise, industry, and external environment, there are significant differences in the carbon reduction effects of digital technology innovation. (3) The analysis of impact paths reveals that digital technology innovation can affect enterprise carbon intensity through three paths: improving productivity, enhancing green innovation efficiency, and adjusting energy consumption. (4) Upon further analysis, it was discovered that the spillover effect of digital technology innovation is more pronounced in the industry cohort of enterprises. Additionally, digital technology innovation plays a positive role in enhancing enterprise ESG performance. The paper's findings offer empirical evidence and decision-making references for the government to develop reasonable policies for reducing carbon emissions, promoting green and low-carbon enterprise transformation, and actively and steadily achieving the goal of carbon peaking and carbon neutrality. [ABSTRACT FROM AUTHOR]

Agricultural carbon emission reduction is inseparable from discussions about government systems, especially in countries with distinctive institutional arrangements such as China. Environmental regulation may influence the impact of environmental decentralisation on agricultural carbon intensity. Using panel data from 30 provinces in mainland China from 2000 to 2015, this paper depicts the spatiotemporal pattern and dynamic evolution of environmental decentralisation, environmental regulation, and agricultural carbon intensity. It uses the spatial Durbin model to empirically study the internal connections between the three. The empirical results show that the enhancement of environmental decentralisation, environmental administrative decentralisation, environmental supervision decentralisation, and environmental monitoring decentralisation is not conducive to reducing agricultural carbon intensity. The results also show that the enhancement of the intensity of environmental regulation of "terminal governance type" and "front-end governance type" is conducive to reducing agricultural carbon intensity, but this effect has a negative "space spillover" phenomenon. Other findings are as follows: (1) the enhancement of the two types of environmental regulation intensity is conducive to changing the impact of environmental decentralisation on agricultural carbon intensity from a "grabbing-hand" to a "helping-hand"; (2) compared with balanced grain-producing and marketing areas and major grain-marketing areas, environmental decentralisation and two types of environmental regulations have a greater negative impact on the agricultural carbon intensity of major grain-producing areas. Therefore, the central government should change how it evaluates political performance; accelerate the construction of a diversified performance evaluation system; increase the weight of low-carbon, green, and other indicators that reflect the friendly development of agriculture in the system; and encourage local governments to adjust the direction of agricultural production. [ABSTRACT FROM AUTHOR]

The collaborative agglomeration of manufacturing and producer services is an essential tool for the green transformation of China's economic model. This paper explores the impact of industrial collaborative agglomeration on carbon intensity, using the spatial Durbin model (SDM) based on China's provincial panel data from 2012 to 2019. The empirical results indicate that there is an inverted N-shaped relationship between industrial collaborative agglomeration and carbon intensity, with the turning points of 2.5255 and 2.8575. Regional industrial collaborative agglomeration tends to initially reduce carbon intensity, then aggravates to carbon emission, then finally inhibits carbon intensity. There is an obvious heterogeneity in the impact of producer-service subsectors and manufacturing collaborative agglomeration on carbon intensity. When the industrial collaborative agglomeration level exceeds a certain threshold, the clustering of information transmission, software and information technology service, and financial intermediation service have the greatest emission reduction potential. Industrial collaborative agglomeration has obvious spatial spillover effect, and carbon intensity has obvious spatial convergence effect. This paper provides some novelties for research perspectives on carbon intensity reduction and theoretical references for the development and implementation of differentiated industrial collaborative agglomeration policies. [ABSTRACT FROM AUTHOR]

As an emerging technology, industrial intelligence focus on the integration of artificial intelligence and production, which creates a new access to achieve the goal of carbon emissions reduction. Using data on provincial panel data from 2006 to 2019 in China, we empirically analyze the impact and spatial effects of industrial intelligence on industrial carbon intensity from multiple dimensions. Results show an inverse proportionality between industrial intelligence and industrial carbon intensity, and the mechanism is to promote green technology innovation. Our results remain robust after accounting for endogenous issues. Viewed from spatial effect, industrial intelligence can inhibit not only the industrial carbon intensity of the region but also the surrounding areas. More strikingly, the impact of industrial intelligence in the eastern region is more obvious than that in the central and western regions. This paper effectively complements the research on the influencing factors of industrial carbon intensity and provides a reliable empirical basis for industrial intelligence to reduce industrial carbon intensity, as well as a policy reference for the green development of the industrial sector. [ABSTRACT FROM AUTHOR]

China faces tough challenges in the process of low-carbon transformation. To determine whether China can achieve its new 2030 carbon peaking and carbon intensity reduction commitments, accurate prediction of China's CO2 emissions is vital. In this paper, the random forest (RF) model was used to screen 26 carbon emission influencing factors, and seven indicators were selected as key variables for prediction. Subsequently, a three-layer back propagation (BP) neural network was constructed to forecast China's CO2 emissions and intensity from 2020 to 2040 under the 13th Five-Year Plan, 14th Five-Year Plan, energy optimization, technology breakthrough, and dual control scenarios. The results showed that energy structure factors have the most significant impact on China's CO2 emissions, followed by technology level, and economic development factors are no longer the main drivers. Under the 14th Five-Year Plan scenario, China can achieve its carbon peaking on time, reaching 10,434.082 Mt CO2 emissions in 2030. Although the new commitment to intensity reduction (over 65%) under this scenario cannot be achieved, the 14th Five-Year Plan can bring about 73.359 and 539.710 Mt of CO2 reduction in 2030 and 2040 respectively, compared to the 13th Five-Year Plan. Under the technology breakthrough and dual control scenarios, China will meet its new commitments ahead of schedule, with the dual control scenario being the optimal pathway for CO2 emissions to peak at 9860.08 Mt in 2025. It is necessary for Chinese policy makers to adjust their current strategic planning, such as accelerating the transformation of energy structure and increasing investment in R&D to achieve breakthroughs in green technologies. [ABSTRACT FROM AUTHOR]

The world is facing the challenges of climate change and energy structure adjustments. The role of digital finance, a new branch of business that combines digital technology and traditional financial products, in reducing global carbon emissions needs to be studied. This paper uses panel data on 280 cities in China from 2011 to 2019 to empirically examine the efficacy of digital finance for governing carbon emission reductions and the mechanism by which it does so. The results show that (1) digital finance can facilitate carbon emission reductions and help reduce carbon emission intensity within regions; (2) digital finance helps promote the rational allocation of resources and alleviates factor distortions by encouraging firms to rationally use their own factor endowments so as to reduce carbon emission intensity, which holds robustly after considering the endogenous issues such as possibly omitting variables and collinearity; and (3) differences in geographical location, the vitality of regional innovation and entrepreneurship, regional willingness to protect the environment, and environmental protection levels lead to heterogeneity in the effect of digital finance on carbon emission intensity. Therefore, it is necessary to vigorously develop digital finance as a long-term tool for carbon governance. [ABSTRACT FROM AUTHOR]

The free flow of factors resulting from regional integration affects not only economic and social activities between cities, but also climate and environmental changes. Under the goal of sustainable development, regional integration as a policy pathway to lower carbon intensity has rarely been clarified. In light of this, using panel data of 279 prefecture-level cities in China from 2006 to 2019, this paper treats city cluster planning as a quasi-natural experiment of regional integration and aims to discuss the impact and mechanism of regional integration on carbon intensity through difference-in-differences (DID) method, mediating effect model and moderating effect model. The following results are reached: (1) The implementation of regional integration policy effectively reduces carbon intensity, and the conclusion still holds after a series of robustness tests. (2) Total factor productivity (TFP) is the mediator of regional integration to reduce carbon intensity, and population density, technological innovation and industrial upgrading are the moderators. (3) The effect of regional integration in reducing carbon intensity varies from city location and city features. The proposed theoretical framework of regional integration affecting carbon intensity, containing mediator and moderators, not only enriches the theoretical research in the field of environment and region, but also provides a new policy path for exploring sustainable development. Therefore, it is necessary to build urban agglomerations integrating the concepts of green, low carbon, intensive and efficient. [ABSTRACT FROM AUTHOR]

The sustainable development of human beings is facing severe challenges in the context of a new era. The effective reduction of carbon emission intensity is essential to achieve the goal of sustainable development. Obviously, green innovation is an important factor in mitigating carbon emission intensity. It is important to measure the effect of green innovation on carbon emission intensity for accelerating industrial transformation and building a circular economy system. Therefore, this paper uses the data of 30 provinces in China from 2000 to 2019, obtained by the State Intellectual Property Office, using fixed effects model quantile regression model and Spatial Durbin Model to empirically verify the theoretical hypothesis. The conclusions are as follows: (1) Green innovation inhibits carbon emission intensity. Instrumental variable model and robustness test support this conclusion. (2) For carbon emission intensity under different quantiles, green innovation has a more significant effect on provinces with high carbon emission intensity through "target accountability system" and "reverse coercive system." (3) There is a significant spatial correlation between green innovation in China's provinces. The reduction of carbon emission intensity in the region will benefit from the improvement of green innovation in surrounding cities. [ABSTRACT FROM AUTHOR]

The increasing carbon emissions have been a major concern for most countries around the world. And as a result, every country is concerned about developing appropriate strategies to curtail it. As a major economy and the largest carbon emitter in the world, China has pledged to reduce the carbon intensity by 60–65% by 2030, compared with 2005 levels, and achieve carbon neutrality before 2060. Therefore, the analysis of the impact of China's carbon intensity is becoming an increasing important topic. Due to the spatial heterogeneity of carbon intensity, various spatial econometric models have been applied in this field. However, the existing literatures failed to consider the cross-products of relevant factors. This paper constructs our dynamic general nesting spatial panel model (GNS) with common factors to deal with the dilemma, and examines the direct and spatial–temporal spillover effects of industrial structure, GDP per capita, investment in anti-pollution projects as percentage of GDP and energy price on carbon intensity in China over the period 2003–2017. Our analysis shows that: (1) China's carbon intensity showed the spatial agglomeration and temporal "inertia" from 2003 to 2017. (2) From the time dimension, the long-term effect of industrial structure first increased and then gradually decreased. (3) From the spatial dimension, industrial structure and investment in anti-pollution projects as percentage of GDP accounted for the main spatial heterogeneity. Furthermore, this paper attempts to provide policy implications to help reduce carbon intensity and achieve carbon neutrality in China. [ABSTRACT FROM AUTHOR]

Commercial department assumes the vital part in energy conservation and carbon dioxide emission mitigation of China. This paper applies the time-series data covering 2001–2015 and introduces the STIRPAT method to research the factors of commercial department's carbon dioxide emissions in China. The combination of STIRPAT method and ridge regression is first adopted to research carbon dioxide emissions of commercial department in China. Potential influencing factors of carbon dioxide emission, including economic growth, level of urbanization, aggregate population, energy intensity, energy structure and foreign direct investment, are selected to establish the extended stochastic impacts by regression on population, affluence and technology (STIRPAT) model, where ridge regression is adopted to eliminate multicollinearity. The estimation consequences show that all forces were positively related to carbon dioxide emissions in China's commercial department except for energy structure. Energy structure is the only negative factor and aggregate population is the maximal influencing factor of carbon dioxide emissions. The economic growth, urbanization level, energy intensity and foreign direct investment all positively contribute to carbon dioxide emissions of commercial department. The findings have significant implications for policy-makers to enact emission reduction policies in commercial sector. Therefore, the paper ought to take into full consideration these different impacts of above influencing factors to abate carbon dioxide emissions of commercial sector. [ABSTRACT FROM AUTHOR]

The carbon quota allocation rules of China's pilot carbon emissions trading (CET) regions are various, which mainly include benchmarking, historical carbon intensity reduction and auctioning. When the allocation rules change, it is unresolved how to achieve the optimal product prices and effectively allocate the carbon emissions reduction profits of CET-covered enterprises in the cooperative supply chain. Thus, this paper uses the Stackelberg game, Nash equilibrium and the Shapley value based on cost modification to investigate these issues. The results indicate that: (1) The increasing carbon prices can always improve the retail prices only under the auctioning rule. Meanwhile, the growing low-carbon awareness of consumer cannot be always conducive to improving the wholesale and retail prices, and the similar product prices of non-CET-covered enterprises have greater impact on the wholesale prices than that on the retail prices. (2) Only under the free carbon quota allocation rules, can the optimal wholesale and retail prices under the Stackelberg game be always higher than those under the Nash equilibrium. Meanwhile, the auctioning rule can better reduce carbon emissions than the free allocation rules. (3) Improving carbon emissions reduction contribution and emission reduction costs can be conducive to increasing the carbon emission reduction profits of the supplier and retailer, while the impact of carbon emission reduction contribution on improving the carbon emission reduction profits is not always greater than that of the carbon emission reduction costs. [ABSTRACT FROM AUTHOR]

To achieve carbon peak targets, realize carbon neutrality vision, and tackle global climate change, China must improve the carbon emission performance at the city level. Based on the carbon emission performance of 191 prefecture-level cities in China from 1997 to 2017, this paper analyses the evolution characteristics of urban carbon emission performance from three aspects: the overall spatial and temporal evolution, the differences according to both region and city size, and the differences among clusters categorized by carbon emission performance at the city level. This paper also reveals the impact of the social and economic transition on China's carbon emission performance. The results show that: (1) The overall level of carbon emission performance of Chinese cities is low, and there is a downward trend during the study period. The differences in carbon emission performance among cities are convergent, but there is a wide gap between high and low values. (2) The carbon emission performance of cities in eastern coastal areas is higher than that in non-coastal areas cities. Large urban agglomerations and economically developed regions, such as provincial capitals, are the agglomeration areas of high urban carbon emission performance values. (3) The carbon emission performance level of cities with similar sizes will converge. At the same time, such changes will enhance the differences among carbon emission performances at the city level within the same region. (4) Cities that belong to high urban carbon emission performance clusters are mainly distributed in the eastern region. Such cities are classified into large cities, supercities, and megacities. Compared with low urban carbon emission performance clusters, cities in high urban carbon emission performance clusters show a higher proportion in the medium-high level and high level of carbon emission performance. Moreover, cities in high urban carbon emission performance clusters are more likely to improve theirurban carbon emission performance. (5) The economic agglomeration effect, industrial structure adjustment and carbon intensity reduction have a significant impact on improving urban carbon emission performance. Population agglomeration has an incremental effect, and the anticipated benefits of environmental regulation have yet to be fully realized. The impacts of different clusters and different regions are variable. Finally, this paper advances policy enlightenment according to its research findings. [ABSTRACT FROM AUTHOR]

The extensive use of natural gas provides a new approach to low carbonization of the structure of primary energy sources, as well as reduces the peak in carbon emissions before fossil fuels are completely replaced by clean energy. To explore the impact of the West–East Gas Pipeline Project (WEGPP) on energy conservation and emission reduction in Chinese inland areas, the effects of policy intervention on the socio-economic development in Hubei province are preliminary investigated in this paper. The causal inference of multi-bandwidth and multi-core analysis is carried out using regression discontinuity design (RDD), and the core conclusion of the counterfactual analysis is proven to be robust based on the synthetic control method. The results show that the transportation of natural gas from Western China to Hubei province can reduce the intensity of carbon emissions, demonstrating that it is an effective substitution to low-carbon energy. The WEGPP not only can meet the demands of a large number of energy shortages caused by the rise of the manufacturing industry, but also can solve the technique bottleneck of energy consumption in Central and Eastern China. The WEGPP has ensured the coordinated development in Western, Central, and Eastern China, achieving and maintaining a high and stable economic growth rate in China. These results have significant implications for making policies of energy conservation and emission reduction in a considerable number of gas-importing provinces in Central China. [ABSTRACT FROM AUTHOR]

Carbon emissions are important factors causing global warming, which requires global efforts to deal with. In this paper, we investigate the mechanism of financial innovation on reducing carbon emissions in China by constructing a financial innovation development index with factors of green finance as well as fintech development. Empirical results show that financial innovation contributes to reduce carbon intensity by promoting energy structure transition as well as public fiscal expenditure on energy conservation and environmental protection. Moreover, heterogeneity exists in the effect of financial innovation on carbon emission reduction. Financial innovation has a significant role in reducing carbon intensity in eastern regions, but has a relatively small influence on central and western regions. Furthermore, financial innovation has a lag effect on reducing carbon intensity. [ABSTRACT FROM AUTHOR]

Green credit is an important green financial policy tool to promote green development. However, research is needed to explore how green credit reduces carbon emissions, especially with respect to its dynamic spatial interactions and regional disparities. Based on a theoretical analysis, this paper empirically tests the carbon emission reduction effect of green credit and its three mechanisms by combining a Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, dynamic spatial Durbin model (SDM), and the mediation model, including their dynamic spatial interactions and regional disparities. The study concludes that green credit can reduce carbon emission intensity based on strong spatio-temporal interactions in China. Green credit mainly reduces carbon emission intensity through scale and technology mechanisms with different spatio-temporal interactions. The tertiary industry in China does not currently have completely clean production; as such, the upgrading of the industrial structure as stimulated by green credit in the long term cannot yet effectively reduce carbon emissions. In addition, the carbon emission reduction effect of green credit and its three mechanisms have different levels of performance and dynamic spatial interactions in different regions of China. Finally, targeted policy recommendations are proposed to apply green credit to effectively reduce the carbon emission intensity. [ABSTRACT FROM AUTHOR]

This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based CO2 capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availability from agricultural residues and modelling of the techno-environmental performance of the retrofitted power plants. Using a 500-m resolution map of cropland in China, the availability of residual biomass at a radius of 25–100 km from each power plant is estimated. The biomass yield is then matched with the required input for a set of co-firing scenarios, identified by the optimal mix of different co-firing ratios (10%, 25%, and 40%) and increasing % of total plant's capacity to be retrofitted with the chosen BECCS system. Power generation performance and required biomass for the retrofitted plants are modelled in the Integrated Environmental Control Model (IECM). According to the results, the total decarbonization potential of the modelled large-scale implementation of BECCS ranges from 0.3 to 1.8 Gt CO2/yr (15–81% of BAU emissions), depending on the biomass collection radius. The Chinese provinces of Shandong, Jiangsu, Anhui, and Henan have the most potential for BECCS implementation, while coal-rich regions (e.g. Inner Mongolia) or highly developed coastal areas (Guangdong, Zhejiang) are constrained by local biomass availability. Overall, this work demonstrates the significant potential of the sustainable large-scale implementation of BECCS in China and provides suggestions to policymakers to include this technology in the portfolio of solutions towards carbon neutrality. [ABSTRACT FROM AUTHOR]

The digital economy and the pursuit of carbon peak and carbon neutrality have emerged as crucial focal points for China's future development. However, the intricate relationship between the digital economy and carbon intensity remains uncertain. Based on the construction of the digital economy evaluation index system, using panel data for 30 provinces in China from 2011 to 2019, this study estimates the impact of the digital economy development on carbon intensity by adopting the system-generalized method of moments (SYS-GMM) technique. The results show that the digital economy can effectively reduce the carbon intensity. This conclusion was supported by robustness tests. However, the carbon emission reduction effect of the digital economy exhibits heterogeneity with respect to the digital economy dimensions and regions. In addition to digital industrialization and industrial digitization reducing the carbon intensity, the digital economy development carrier has an inverted U-shaped nonlinear relationship with carbon intensity. Additionally, the digital economy has a more obvious inhibitory effect on carbon intensity in the eastern region. Most importantly, besides the mediating effects of technological progress and financial development, this paper finds that the digital economy can increase carbon intensity through human capital accumulation. These conclusions provide a certain scientific basis for the effective implementation of China's digital economy and carbon peak and carbon–neutral development strategy. [ABSTRACT FROM AUTHOR]

This paper explores the nonlinear effect of outward foreign direct investment (ODI) and Export Trade Structure on CO2 emissions in China. A national panel of 30 provinces and two sub-national panels for the time span 2003 to 2016 have been estimated by using SGMM estimator and panel threshold regression model. The results indicate that GDP has a positive and significant impact on carbon emissions and that the scale effect of ODI will increase the CO2 emissions. Additionally, ODI and Export Trade Structure are generally conducive to the reduction of carbon emission intensities, except that the impact of Export Trade Structure is not significant the in northern region. Moreover, GDP, ODI, and Export Trade Structure contribute to the reduction of CO2 emissions via the technical effects of energy efficiency, and ODI will help reduce CO2 emissions even as the output of energy-intensive industries grows. Therefore, regions should develop a more effective opening-up strategy based on their industrial distribution characteristics and development stages against the background of trade protectionism affecting the evolution of global value chains, use the spillover effects generated by various channels to effectively mitigate CO2 emissions, and seek sustainable economic growth accompanied by clean technologies and faster development of energy efficiency. [ABSTRACT FROM AUTHOR]

Few studies provide direct evidences that agricultural fiscal affects agricultural carbon intensity. This study tries to fill this gap. Using panel data of 30 provinces in China from 2005 to 2019, we conclude that agricultural fiscal expenditures significantly reduce agricultural carbon intensity. The result is still robust after employing the provincial agricultural leaders' birthplace information as an instrumental variable. Further study shows that the negative effect of agricultural fiscal expenditures on agricultural carbon intensity is more pronounced in regions with less corruption and is also more visible in central, western, and inland regions than other areas. For this effect, agricultural technological improvement and structure optimization are possible channels, but not operation scale expansion. Interestingly, although agricultural fiscal expenditures reduce the local agricultural carbon intensity, neighbor regions' carbon intensities are increased due to fiscal rivalry. [ABSTRACT FROM AUTHOR]

Currently, China is moving towards the era of the digital economy, which is gradually becoming a new engine of high-quality development. In the "double carbon" strategy context, the digital economy is characterized by low carbon emissions and high permeability, making it essential for carbon emission reduction. There needs to be more empirical research on the digital economy and carbon emissions. Given this, this study empirically examines the impact of digital economy development on carbon emissions intensity and its mechanisms in a multidimensional way based on the panel data of 30 provincial-level administrative regions in China from 2011 to 2019, utilizing a fixed-effects model, a mediated-effects model, a spatial Durbin model, and other methods. The study results show that (1) the digital economy can significantly reduce carbon emissions intensity. (2) The digital economy can indirectly affect the intensity of carbon emissions through industrial structure, energy structure, and environmental regulation. (3) The development of the local digital economy has a positive spillover effect on the carbon emissions intensity of neighbouring places. However, the overall effect is negative. This paper reveals some new features of the digital economy and carbon emissions intensity, which provides a reference for advancing the country's construction and realizing China's "double carbon" goal. [ABSTRACT FROM AUTHOR]

Based on the panel data of 279 cities in China from 2003 to 2017, this paper regards the new energy demonstration cities (NEDC) construction as a quasi-natural experiment, using the double-fixed effect model and the difference-in-differences (DID) method to test its local carbon emission reduction effect and transmission mechanisms and further explores the impact of NEDC on neighboring carbon emissions. Results show that (1) NEDC reduces carbon emission intensity and per capita carbon emission significantly and shows dynamic sustainability. The policy effect has shown a trend of increasing year by year. Moreover, there is significant heterogeneity in the carbon emission reduction effect of NEDC, which produces more significant policy effect in large-scale and non-resource-based cities. (2) NEDC construction reduces carbon emission through green technology innovation effect, innovative elements agglomeration effect, and total factor productivity improvement effect. In terms of the contribution of reducing carbon emission intensity and per capita carbon emission, total factor productivity accounts for 36.7% and 21.5%, respectively, green technology innovation accounts for 18.6% and 23.9%, respectively, the contribution of R&D personnel agglomeration is 7.5% and 8.3%, respectively, and the contribution of R&D capital agglomeration is 5.9% and 9.5%, respectively. (3) From the perspective of spatial effect, the impact of NEDC on carbon emissions presents a "siphon" effect; that is, although NEDC reduces local carbon emissions, it has produced the phenomenon of transfer to neighboring areas, accelerating the increase in the carbon emission intensity of neighboring areas. [ABSTRACT FROM AUTHOR]

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

As an effective policy instrument to reduce energy consumption and CO emissions, the effects of fuel taxation on income distribution have been the critical factor that determines whether a fuel tax could be acceptable in China. This paper estimates the distributional effects of a fuel tax on households in various income groups by using the input-output model. Results indicate that the total distributional effects of fuel taxes are moderately progressive; that is, high-income households would bear more tax burden compared to low-income households. In addition, the indirect effects are larger than the direct effects. Moreover, the Kakwani and Suits indices show that fuel excise taxes are progressive, implying that a fuel tax could improve the unfair income distribution. In order to reduce the negative impact of fuel taxes on low-income households, it is necessary for the government to design a reasonable redistribution mechanism of tax revenue or adopt compensatory measures such as the transfer payments targeted on low-income groups. [ABSTRACT FROM AUTHOR]

The application of low-carbon alcohols (LCA fuels) in internal combustion engines has become one of the most important topics in road transport decarbonization. This paper aims to identify the trends and characteristics of LCA combustion research for the period 2000–2021 through bibliometric analysis. Citation analysis is used to evaluate the influence of most productive journals, countries/regions, authors, institutions, and relevant literature, while collaborative network between various authors, countries/regions, institutions, and the co-occurrences among different keywords are discussed. A dataset of 2250 publications was extracted from the Web of Science Core database and analyzed with CiteSpace and Biblioshiny. The extracted documents involve 429 journals of publications by 4782 authors from 1434 institutions across 83 countries/regions. The results reveal that the research output in this field has undergone three main stages of development, i.e., initial development (2000–2007), slow development (2008–2015), and rapid development (2016–2021). Currently, the research field is growing at an annual growth rate of 9.24%, with most of the contributions by authors and institutions originating from China. The analysis from relevant keywords and literature suggests that the core of this research field centers on the combustion, performance, and emission characteristics of LCA-fueled engines. The current study helps keep the scientific community informed of the latest paradigms in the LCA combustion research field. [ABSTRACT FROM AUTHOR]

Continual growth of energy-related CO emissions in China has received great attention, both domestically and internationally. In this paper, we evaluated the CO emissions in five major energy consumption sectors which were evaluated from 1991 to 2012. In order to analyze the driving factors of CO emission change in different sectors, the Kaya identity was extended by adding several variables based on specific industrial characteristics and a decomposition analysis model was established according to the LMDI method. The results demonstrated that economic factor was the leading force explaining emission increase in each sector while energy intensity and sector contribution were major contributors to emission mitigation. Meanwhile, CO emission intensity had no significant influence on CO emission in the short term, and energy consumption structure had a small but growing negative impact on the increase of CO emissions. In addition, the future CO emissions of industry from 2013 to 2020 under three scenarios were estimated, and the reduction potential of CO emissions in industry are 335 Mt in 2020 under lower-emission scenario while the CO emission difference between higher-emission scenario and lower-emission scenario is nearly 725 Mt. This paper can offer complementary perspectives on determinants of energy-related CO emission change in different sectors and help to formulate mitigation strategies for CO emissions. [ABSTRACT FROM AUTHOR]

China is entering a new period characterized by reaching peak and carbon neutralization, and environmental taxes are increasingly crucial for breaking the "carbon curse" of resource-based cities. Accordingly, using the implementation of China's Environmental Protection Tax Law (EPT Law) as a quasi-natural experiment, this study utilizes the DID model to assess this environmental tax reform's effect in terms of reducing carbon emissions. The research results are as follows: (1) The environmental tax reform (ETR) reduced the intensity of carbon emissions; it additionally promoted reducing total carbon emissions from resource-based cities. (2) The carbon abatement effect can also be achieved by upgrading industrial structures and improving innovation in the area of green technology. (3) The ETR has impacted carbon abatement in resource-based cities more significantly in China's eastern region than in the central or western regions. In contrast, it had less effect on resource-based cities in the regenerative stage than on cities in other stages. (4) The spatial spillover effect of the ETR was significantly positive, aggravating the level of carbon emissions in neighboring cities. Thus, the "pollution haven hypothesis" was tested. Overall, this study deepens the knowledge of ETR and carbon emissions and provides theoretical support and policy suggestions for supporting resource-based cities in a green transformation. [ABSTRACT FROM AUTHOR]

Clean energy transition has been considered as an indispensable way to attain sustainable development for China, where the coal-to-gas initiative plays a vital role towards the goal. This paper takes Beijing, China's political and economic center as well as a national pioneer in the energy transition, as a case to systematically analyze the co-mitigation of air pollution (PM2.5) and carbon emissions (CO2) achieved by the policy-driven natural gas-coal consumption substitution. Firstly, a qualitative analysis of the relationship of Beijing's coal-to-gas policies and its air quality has been conducted. Then, VAR and ARDL models are employed to quantitatively analyze the impacts of coal-to-gas policies on PM2.5 and CO2, respectively. Results show that (i) an innovation of natural gas/coal consumption ratio will reduce PM2.5 concentrations, and the effect decreases over time; and (ii) an increase of 1% in natural gas/coal consumption ratio in Beijing will cause a decrease of 0.0784% in CO2 emissions in the long run. Therefore, the coal-to-gas policies do increase the usage of natural gas and improve Beijing's air quality. The assessment methods and conclusions can be regarded as a reference for not only China's policymakers, but also other countries, especially nowadays when air quality is becoming more valued and GHGs are being tightly controlled. [ABSTRACT FROM AUTHOR]

In order to explore the decoupling relationship and its influence factors between economic growth and carbon emissions in China, the decoupling elasticity decomposition quantitative model of carbon emissions based on extended Log-Mean Divisia Index and Tapio decoupling models is established in this paper. The carbon emissions induced by household (HOU) sector ranked fifth among the nine sectors; hence, we analyzed the HOU sector with the production (PRO) sector together. The results show that, first, the carbon emissions increased from 3.95 billion tons in 1996 to 10.49 billion tons in 2012, and the contributions of manufacturing sector and electric power, gas and water production and supply sector to carbon emissions account for approximately 81 %. Second, the economic output effect is the main contributor, and the energy intensity effect is the major inhibitor factor to the carbon emissions in both the PRO sector and HOU sector, respectively. Third, the decoupling state of the PRO sector mainly stayed at weak decoupling, while the decoupling state of HOU sector mainly stayed at strong decoupling. Fourth, the impact factors of the carbon emissions and the decoupling elasticity values are in complete agreement. At the end of this paper, we present some policy recommendations for China's government to realize the decoupling between CO emissions and economic growth in the near future. [ABSTRACT FROM AUTHOR]

This paper proposes an alternative method to decompose carbon emissions changes using distance functions estimated by data envelopment analysis. The proposed approach can measure the effects of technical efficiency change and technical change, the effects of substitution among inputs, and the effects of GDP composition change on the changes in carbon emissions. We apply this method to decompose the carbon emissions at China's provincial levels. For the 30 provinces as a whole during the 11th Five-Year Plan period (2006-2010), empirical results demonstrated that economic growth and the potential carbon factor changes were the largest contributors to carbon emissions increase, while the good output technical changes and energy usage technical changes were the largest components to carbon emissions reduction. The structure effects represented by GDP composition change was a mild contributor to carbon emissions reduction for most provinces. We found that the substitution effects among inputs existed and contributed to carbon emissions increase for most provinces, but their impacts were limited and differed across provinces. The impacts of the good output technical efficiency change and energy usage technical efficiency changes were extremely limited and different across provinces. The empirical results are beneficial to China's central and local governments to make regional adaptive policies to carbon emissions reduction. [ABSTRACT FROM AUTHOR]

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

Agriculture produced the largest methane emissions in China. It is of great importance to investigate effect of fertilizer using intensity on the environmental efficiency of China’s agriculture. This paper mainly investigates the determinants of environmental efficiency of China’s agriculture. First, we estimate environmental efficiency of China’s agriculture of 30 provinces from 1997 to 2014 through metafrontier SBM super efficiency with undesirable outputs, which allow for technology heterogeneity in different regions. Then, we compare environmental efficiency in different regions. Furthermore, we also analyze whether heterogeneity of environmental technology widened or decreased. Last, we also explore the determinants of environmental efficiency of China’s agriculture through bootstrap truncation regression. We find that fertilizer intensity negatively affects environmental efficiency. Urbanization has significant positive (1.454) effect on environmental efficiency under metafrontier in the east. It is significant use more organic fertilizer to decrease CO2 (carbon dioxide) emissions. It is important to enhance environmental innovation for China’s agriculture. [ABSTRACT FROM AUTHOR]

Energy saving and emission reduction are the most concerned issues in the world. Objective and accurate prediction of carbon emissions can provide reference and early warning for the implementation of the government's environmental strategy. Based on the traditional grey Verhulst model, this paper analyzes the main causes of its errors, introduces the extrapolation method to optimize the background value, and uses particle swarm optimization algorithm to optimize its parameters. In order to evaluate the performance of the models, six commonly statistical evaluation indicators are used to compare the new model with other optimization models and grey universal models, and the effect of the new model is basically better than other models. Finally, it is applied to the prediction of carbon dioxide emission of three kinds of coal in China. The results show that the increase of carbon dioxide related to raw coal slows down in 2016–2020, while the increase of carbon dioxide related to clean coal and other washed coal is 12.7097% and 19.2024%, respectively. Therefore, in order to prevent a strong rebound in carbon emissions, China should increase efforts to save energy and reduce emissions, and reduce energy consumption, especially coal consumption. [ABSTRACT FROM AUTHOR]

Technological advancement plays a crucial role in CO emissions mitigation and has attracted great attention around the world. A multitude of literatures mainly focused on single technological impact on environmental issues at national level, while comprehensive studies concerning technological factors at regional level are rare. This paper employs environmental learning curve model to investigate the learning effects of different technological channels on CO emissions at the national and regional levels using panel data of China's 29 provinces from 1997 to 2014. The technological advancement is disaggregated into indigenous research and development (R&D), foreign technology import and technological revolution. Furthermore, to comprehend the characteristics of various provinces with regard to CO emissions and emission efficiency, China's 29 provinces are divided into four regions according to the features of 'CO emissions-efficiency'. Empirically results manifest that technical renovation is the paramount driver to mitigate the national CO emissions. The CO learning abilities of indigenous R&D in high emissions regions are greater than those in the low ones, while boosting the investment of foreign technology import in low emission regions has significantly positive impacts on CO emissions, and the technical renovation is effective in abating CO emissions in all regions. The findings not only enrich technology innovation theories, but also deserve special attention from policymakers. [ABSTRACT FROM AUTHOR]

In China, more than 80% electricity comes from coal which dominates the CO2 emissions. Residential electricity demand forecasting plays a significant role in electricity infrastructure planning and energy policy designing, but it is challenging to make an accurate forecast for developing countries. This paper forecasts the provincial residential electricity consumption of China in the 13th Five-Year-Plan (2016-2020) period using panel data. To overcome the limitations of widely used predication models with unreliably prior knowledge on function forms, a robust piecewise linear model in reduced form is utilized to capture the non-deterministic relationship between income and residential electricity consumption. The forecast results suggest that the growth rates of developed provinces will slow down, while the less developed will be still in fast growing. The national residential electricity demand will increase at 6.6% annually during 2016-2020, and populous provinces such as Guangdong will be the main contributors to the increments. [ABSTRACT FROM AUTHOR]

Beijing faces a serious problem of carbon emissions and the economic sectors are the main source of carbon emissions. Previous literatures have extensively focused on estimating the impact of carbon emissions of individual sector. Little attention has been paid to the multisectoral carbon emissions. In this paper, a multisectoral decomposition analysis was reported to explore the carbon emissions in Beijing. The emissions are decomposed into energy structure, energy intensity, economic structure (in industry), economic output, and population scale effects by the method of logarithmic mean Divisia index. Agricultural, industrial, construction, transportation, commercial, and other sectors are taken into consideration. The results show that population scale effect is the main factor for increasing carbon emissions in all sectors. The energy efficiency improvements are primarily responsible for the decrease in emissions in the industrial sector, while it increases emissions in construction, transportation, and commercial sectors. The economic output in agricultural and other sectors exerts a positive effect on emissions. In contrast, the energy structure effect only makes a minor contribution to the emission decrease in industrial, construction, commercial, and other sectors. [ABSTRACT FROM AUTHOR]

Decoupling CO2 emissions from economic growth is an important cornerstone of a country's decarbonization policy. Existing research in this avenue has mainly focused on decoupling the production-based (PB) CO2 emissions from economic growth at the national level, while decoupling the consumption-based (CB) and income-based (IB) CO2 emissions from economic growth, especially at the sectoral level, has received less attention. Using China's Zhejiang province as a case study, we conduct one of the first studies focused on decoupling the PB, CB, and IB CO2 emissions from economic growth at the sectoral level. Our results reveal that (1) during 2002–2017, the sectoral decoupling level varies greatly among the three different perspectives; (2) most of the examined sectors were in unstable decoupling states while some sectors even reverted to coupling states; and (3) the drivers of CO2 emissions at the sectoral level reveal important factors, such as emissions intensity, production structure, and final demand structure, that contribute toward decarbonization. Our study demonstrates to policymakers how utilizing a multi-perspective evaluation of the decoupling of emissions from sectoral economic growth can improve the accuracy of decarbonization policies and identify critical sectors toward CO2 reduction objectives. [ABSTRACT FROM AUTHOR]

In China, the power industry contributes significantly to carbon emissions, reducing carbon emissions in this industry is conducive to China's adaptation and mitigation of climate change. Researches on green and low-carbon power have attracted increasing attention. In this paper, we analyze and compare the carbon emissions from thermal power sector in 30 Chinese provinces, divided into three main regions. Based on the panel data over the period 2002–2016, we use a slacks-based measurement (SBM) model to measure the carbon emission efficiency of China's power sector. The results show that the carbon emission efficiency of the system is relatively low, with marked differences among regions. Based on the Moran's I, we further found spatial heterogeneity in carbon emission efficiency of provincial power sector. Policies for adaptation and mitigation of climate change should have regional differences. Interregional collaboration also plays a key role in adapting to and mitigating climate change. For China, it is an important issue to develop clean coal-fired power generation and vigorously develop renewable energy. From a global perspective, energy transformation needs to be continuously promoted. Promoting low-carbon transformation of global energy system requires deep technical cooperation and synergy. Global mitigation strategy should focus on the orientation of structural reform and constantly optimize the energy structure. [ABSTRACT FROM AUTHOR]

Understanding the intrinsic mechanism behind changes on energy intensity provides insights about reducing carbon emissions and promoting the sustainable development of Beijing-Tianjin-Hebei (BTH) region. Although various studies have found a causal relationship between energy intensity and energy-related carbon emissions, the internal mechanisms are still unclear. This paper presents a comprehensive analysis of the impact of energy intensity on carbon emissions from 2005 to 2015. With an association established between logarithmic mean Divisia index (LMDI) and generalized Fisher index (GFI), two-layer factor decomposition model is proposed to explore the factor analysis in-depth. (1) LMDI method proves that energy intensity is the main contributor that reduces carbon emissions in BTH. (2) GFI model further decomposes energy intensity into five effects, namely energy substitution, technology progress, labor productivity, capital substitution, and labor-capital resources allocation. (3) The results reveal that the effect of capital-energy substitution in declining energy intensity surpasses technology progress. (4) Energy-labor substitution has increased energy intensity, while energy-energy substitution is negligible. For the coordinate development of BTH, the government should aim at energy intensity and attach importance to encouraging entrepreneurship, accelerating the construction of carbon trading market, allocating resources rationally, and guiding the capital flow into energy-efficient direction. [ABSTRACT FROM AUTHOR]

This paper analyses the forces driving energy-related CO emissions based on a threshold STIRPAT dynamic model, using Chinese state-level panel data during the period of 1997 to 2010. In addition to investigating the impact of affluence on CO emissions, this paper studies channels through which affluence could impact on CO emissions across development levels and explores the possibility of reducing CO emissions through greater affluence by analysing panels including all regions, high-income regions and low-income regions. A threshold STIRPAT dynamic model further estimates thresholds for the major determinants of CO emissions: in the long run, affluence is the most important determinant followed by urban population. Variability of affluence impact on CO emissions in high-income regions is explained mostly by trade openness degree, while low-income regions with a higher industrial level are associated with lower CO emissions. Different measures should be adopted for CO reductions in different regions according to local conditions. [ABSTRACT FROM AUTHOR]

Guangdong is the most economically developed province in China, which is a large CO emitter and hence is faced with severe carbon reduction pressures. In this paper, a cost assessment methodology based on scenario analysis is presented. A CO source and sink database was built at Guangdong after detailed investigations on the point sources and sedimentary basins. Fifteen transport and five storage scenarios were defined and studied, respectively. Cost estimates based on these scenarios show that during its lifetime, the costs of both transport and storage depend on the amount of CO processed. More CO being processed will bring down the unit costs of both transport and storage. However, it was observed that there is a cost inflection point between the storage amount of 35.2 and 52.8 Mt/year, which means that as the storage amount increases, the storage cost will first decrease and then increase. Source region S1 in Guangdong has been recommended for an early chance of CO storage. Preliminary cost comparisons have shown that the results presented in this study are reasonable, but to improve the cost assessment accuracy of offshore CO storage, a methodology based on a CO storage design that can integrate local prices needs to be further developed. [ABSTRACT FROM AUTHOR]

As an emerging technology with the potential to enable large-scale utilization of fossil fuels in a low-carbon manner, carbon capture, utilization and storage (CCUS) is widely considered to be a strategic technology option to help reduce CO emissions and ensure energy security in China. In principle, CCUS can be divided into three categories, namely chemical utilization, biological utilization and geological utilization. Of the three categories, carbon geological utilization and storage (CGUS) technology has obtained the most attention lately due to its ability to utilize underground resources and conditions, to generate further economic benefits, a feature that distinguishes it from other CO reduction technologies. The CGUS technology related in this paper has various types, each with its own potential, difficulties and characteristics. This paper summarizes China's research findings on the various types of CGUS technology, analyzes their research status, development potential, early opportunities and long-term contributions and recommends major geological utilization methods to policy makers and investors based on China's natural resources and industrial characteristics. Besides, this paper analyzes the status, mechanisms and limitations of China's relations with other countries in this field, as a means to promote research cooperation on an international level. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate the carbon dioxide (CO) emissions reduction performance of 30 mainland provinces in China over 2005-2009. First, the log-mean Divisia index (LMDI) technique is used to decompose the changes in CO emissions at the provincial level into 4 effects that are carbon intensity effect, energy mix effect, energy intensity effect and gross domestic product (GDP) effect. Next, two indicators, decoupling index and rescaled decoupling index, are implemented to evaluate the performance of 30 provinces in CO emission reduction from 2005 to 2009. The decomposition result shows that the GDP growth is mainly responsible for the CO emissions increase, while the energy intensity effect is the key factor for the decrease in CO emissions in each province. Moreover, according to the evaluation, the performance of each province in what concerns the CO emission reduction varies significantly. Most provinces in China made significant efforts in emissions reduction during 2005-2009, while some provinces only made weak efforts or even no efforts in decoupling progress. [ABSTRACT FROM AUTHOR]

China's capital-intensive, export-oriented, spectacular economic growth since launching its open-door policy and economic reforms in late 1978 not only has created jobs and has lifted millions of the Chinese people out of poverty, but also has given rise to unprecedented environmental pollution and CO emissions. While estimates of the embedded CO emissions in China's trade differ, both single-country studies for China and global studies show a hefty chunk of China's CO emissions embedded in trade. This portion of CO emissions had helped to turn China into the world's largest carbon emitter, and is further widening its gap with the second largest emitter. This raises the issue of who should be responsible for this portion of emissions and bearing the carbon cost of exports. China certainly wants importers to cover some, if not all, of that costs. While China's stance is understandable, this paper has argued from a broad and balanced perspective that if this is pushed too far, it will not help to find solutions to this issue. On the contrary, it can be to China's disadvantage for a number of reasons. However, aligning this responsibility with China does not necessarily suggest the sole reliance on domestic actions. In that context, the paper recommends specific actions that need to be taken internationally as well as domestically in order to effectively control the embedded CO emissions in China's trade. [ABSTRACT FROM AUTHOR]

This paper examines the issue of ancillary benefits by linking sulfur dioxide (SO) emission to CO emission using a panel of 29 Chinese provinces over the period 1995-2007. In the presence of non-stationarity and cointegrating properties of these two data series, this paper applies the panel cointegration techniques to examine both the long-run and short-run elasticities of SO with respect to CO. The major findings are that: (1) there exhibits a stable long-run equilibrium relationship between the SO and CO emission with the long-run elasticity being 2.15; (2) there exists a short-run relationship between these two emissions with the short-run elasticity being 0.04. In addition, following an exogenous shock that causes a deviation from the long-run equilibrium, it would take approximately 15 years for SO emission to revert toward the long-run equilibrium path with an average annual convergence rate of 6.5%; (3) the derived ancillary benefits that is generated from one metric ton of CO emission reduction, are 11.77 Yuan (approximately US$ 1.7) in the short run and 196.16 Yuan (US$ 30) in the long run. These findings are not only crucial from the econometric modeling perspective, but also have important policy implications. [ABSTRACT FROM AUTHOR]

Preparatory talks to the next round of negotiations seem to indicate that a comprehensive agreement to mitigate climate change will not be easily attainable, despite the intentions of the US administration and the high expectations surrounding the Copenhagen meeting. One key reason is to what extent fast growing economies, and especially China, should take actions to reduce their growth of emissions. This paper argues that a turning point for international negotiations on climate change could be achieved if China were to agree on carbon obligations in the future. Results from modelling work suggest that the optimal investment behaviour is to anticipate the implementation of a climate policy by roughly 10 years, and that thus future commitments—if credible—could lead to significantly earlier steps towards carbon mitigation. If fast growing economies, and foremost China, believe in the long term objective of global stabilization of carbon concentrations, it might be economically rationale to sign on future targets, provided developed countries take on immediate action. Such a provision could be beneficial for both the developing and developed world. [ABSTRACT FROM AUTHOR]

The construction industry plays an important role in energy saving and carbon emissions mitigation of China. Promoting carbon emission efficiency is seen as an efficient way to abate carbon emissions. Using 2005-2016 data, the carbon emission efficiency of the construction sector in 30 provinces is estimated, and the spatial distribution characteristics of the carbon emission efficiency of the construction industry is explored. The spatial Markov transition probability matrix is employed to investigate the influence of the spatial spillover effect on the regional distribution pattern of carbon emission efficiency. The results demonstrate that the carbon emission efficiency of the construction industry exhibits an unbalanced regional distribution, which is high in the east and low in the west. The spatial autocorrelation indicates that the carbon emission efficiency has a spatial dependence and is characterized by spatial agglomeration. Markov Chain results show a significant spatial spillover effect in carbon emission efficiency. The provinces with higher carbon emission efficiency have a positive effect on their neighbors, while the provinces with lower efficiency have a negative effect on neighbors. The findings are of great importance to understand the differences in and interactions of carbon emission efficiency between regions. [ABSTRACT FROM AUTHOR]