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

An in-depth investigation into the effect of embedment in global value chain (GVC) on energy conservation and emissions reduction is of great significance for scientifically assessing the environmental impact of GVC participation, and promoting high-quality development in China. This paper incorporates GVC embedment, energy consumption and carbon emissions into the same analysis framework for the first time. Based on the WIOD database, this paper theoretically and empirically examines the impact and mechanism of global value chain embeddedness on carbon emission reduction from two dimensions: energy consumption intensity and energy consumption structure. The study found that GVC embedment significantly reduced the industry's carbon emission intensity; developing economies' embedment in GVC helped reduce their carbon emission intensity, while the effect was not obvious in developed economies. GVC embedment had a significant inhibitory effect on the carbon emissions in both upstream and downstream industries, but not conducive to carbon reduction of low-tech manufacturing. The mechanism test shows that the GVC embedment not only exhibits the dual effects of energy conservation and emissions reduction, but also has a significant impact on carbon emissions by reducing the energy consumption intensity and improving the energy consumption structure. [ABSTRACT FROM AUTHOR]

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]

Facing the double constraints of the "double carbon" target and high-quality economic development, carbon trading policy is an important tool for realizing the emission reduction commitment; based on the perspective of microenterprises, the specific mechanism and spatial effect of carbon trading policy still need to be evaluated. Taking China's carbon emissions trading pilot as a quasi-natural experiment, this paper empirically investigates the impact of carbon trading policy on the carbon emission intensity of pilot enterprises and its mechanism of action, and its impact on the carbon emission intensity of neighboring enterprises, based on the multi-temporal double-difference model, moderating effect model, and spatial Durbin model with the A-sharelisted enterprises in the period of 2009-2019 as the samples. It is found that: 1) Carbon trading policy will reduce the carbon emission intensity of enterprises to different degrees, and there are significant differences under different ownership types, degrees of marketization and the level of digitization. 2) Under the influence of environmental uncertainty, ESG disclosure will weaken the effectiveness of carbon emission reduction in the pre-pilot stage of the policy; with the gradual improvement of the carbon trading policy and ESG disclosure mechanism, ESG ratings will positively regulate the inhibitory effect of the carbon trading policy on the carbon emission intensity of enterprises through multiple paths. 3) Carbon trading policy effectively reduces multiple negative spillovers through the demonstration effect and competition effect of neighboring enterprises, driving the carbon emission reduction behavior of non-pilot enterprise. The research in this paper enriches the research paradigm of carbon emission intensity influencing factors, provides reference suggestions for the government to improve its policies, and better contributes to the realization of the "dual-carbon" vision in China as soon as possible. [ABSTRACT FROM AUTHOR]

With the proposal of "Carbon Peak and Carbon Neutrality" goals, China is facing a more serious carbon emissions reduction situation, and how the booming digital economy effectively helps China's carbon emissions reduction is one of the most urgent things that should be solved. To study the impact of the digital economy on carbon emission intensity, this paper is based on the panel data of 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2011 to 2021, and applies the double-fixed effect model and the threshold effect model to study the impact of the digital economy on carbon emission intensity and the mechanism of its action, as well as to analyze the mechanism of the digital economy's action on carbon emission intensity from the perspective of technological innovation. The results of the study show that: i) The digital economy can reduce the intensity of regional carbon emissions; ii) The carbon emission reduction effect of the digital economy is non-linear, and its carbon emission reduction effect gradually increases with the level of development of the digital economy; iii) In addition to the direct impact of the digital economy on carbon emission intensity, it also has an indirect impact on carbon emissions through technological innovation; iv) There is regional heterogeneity in the carbon emission reduction effect of the digital economy, and the carbon emission reduction effect is more significant in the central and western parts of the country and regions with a high level of human capital development. Based on the conclusions obtained, this paper suggests: i) The rational integration of the digital economy and regional development should be strengthened; ii) Strong provinces in the digital economy should be encouraged to help weaker provinces, to narrow the "digital divide" between provinces; iii) Differentiated development strategies should be formulated in accordance with local conditions, to give full play to the optimal effect of the digital economy in carbon emission reduction. [ABSTRACT FROM AUTHOR]

In the context of rapid advancement in automation and increasing global warming, understanding the impact of artificial intelligence (AI) on carbon emissions (CES) is a cutting-edge research topic. However, there is limited focus in existing research on the nonlinear carbon reduction effect (CRE) of AI. This paper first theoretically elaborates the dual impact mechanisms of AI on CES and illuminates the nonlinear carbon reduction mechanisms of AI. Then, this study employs panel data encompassing 30 Chinese provinces between 1997 and 2019 to empirically test the net effect of AI on CES and the nonlinear carbon reduction effect of AI through econometric models. The results are as follows: first, although AI can both reduce and increase CES, AI primarily helps decrease CES. This conclusion holds true even after considering robustness, endogeneity, and spatial heterogeneity. Secondly, relative to the central and western regions, AI has significant achievement in reducing carbon intensity and per capita CES in the eastern region. However, there is still room for improvement in terms of reducing the total CES in the eastern region. Thirdly, improving the AI development level (AIDL) can magnify the marginal CRE of AI and lead to a nonlinear CRE of AI. Lastly, even if the AIDL remains constant, improving the level of marketization, human capital, digital infrastructure, economic development, openness, and government intervention can also amplify the marginal CRE of AI and lead to a nonlinear CRE of AI. To fully harness the potential of AI for green development, concerted efforts should be directed towards enhancing the innovation and application of AI technologies with carbon reduction potential. [ABSTRACT FROM AUTHOR]

Reducing carbon emission intensity is crucial for achieving sustainable development. Carbon emission intensity is expressively affected by the issuance of green bonds. Thus, it is imperative to assess the influence of green bond issuance on carbon emissions and examine their correlation. Such research holds great potential to expedite the overhaul and modernization of businesses and to construct a circular economy system. This paper uses the spatial Durbin model to draw empirical conclusions by using data from 26 provinces in China between 2016 and 2021. Firstly, under different spatial matrices, it has been analyzed that an increase of 1% in the issuance of green bonds leads to a reduction of 0.306% or 0.331% in carbon emission intensity. It shows that green bonds have the potential to substantially reduce carbon intensity. Additionally, the intensity of emissions in the current period is driven by the intensity of emissions in the previous period. Secondly, the analysis of mediated transmission suggests that green bonds can ultimately reduce carbon emission intensity by changing the energy consumption structure or improving the efficiency of green technology innovation. Thirdly, the analysis of heterogeneity shows that the inhibitory effect of green bond issuance on carbon emissions is stronger in less economically developed regions than in economically developed regions. There is a significant inhibitory effect of green bond issuance in neighboring provinces on local carbon emission intensity. This effect is present only in provinces in less economically developed regions and not in economically developed regions. [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]

Under the carbon emission pattern of "peak carbon and carbon neutrality", the policy of crop rotation and fallow system (CRFS) is regarded as an important initiative to promote the green, low-carbon, and high-quality development of agriculture. Focusing on balanced panel data from 30 provinces in China from 2010 to 2021, this paper empirically examines the impact of CRFS on agricultural carbon emissions (ACEI) and its internal mechanism using a multi-temporal difference-in-differences model. The benchmark regression results show that CRFS can significantly reduce ACEI, and the results remain robust after validation by multiple methods. Mechanism results show that CRFS is able to reduce ACEI by reducing factor mismatch and promoting the level of agricultural services. Heterogeneity analysis results show that the arable land fallow rotation system is more conducive to promoting the reduction in agricultural carbon emission intensity in the main grain producing areas, main grain marketing areas, high land transfer areas, and plantation areas than in the grain production and marketing balanced areas, low land transfer, and animal husbandry areas. This study demonstrates the effectiveness of the CRFS policy implementation, provides a doctrinal basis for expanding the scope of CRFS implementation, and provides policy recommendations for relevant departments to improve the CRFS policy. [ABSTRACT FROM AUTHOR]

At present, China is in the period of large-scale tax and fee cuts and external pandemic shocks. Local governments' financial pressure has intensified. There is a lack of existing studies on how it will affect local carbon emissions. This paper uses the quasi-natural experiment of the 2010 educational authority reform to measure exogenous changes in financial pressure. It adopts the continuous double differential method to empirically investigate the impact of local financial pressure on carbon emissions. The results of the paper are as follows. First, the financial pressure generated by the educational authority reform has significantly increased local carbon emission intensity. This indicates that local governments will address carbon emissions in other ways when they feel financial pressure. Second, to ease financial pressure, local governments will regulate high energy-consuming enterprises and utilize their high production value and strong tax-generating ability to scale up their production capacity and obtain more tax revenues, which will lead to a large amount of carbon emissions. This study is of important reference significance for how to deal with financial pressure from now on and how to well handle the relationship between local finance and carbon emissions. [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]

The income gap and global warming have always been topics of common concern to scholars worldwide. Internationally, there is no consensus yet about the impact of the income gap on carbon emissions, and there are few studies about that in China. To explore the effect of the income gap on carbon emissions at the provincial level in China, this paper first theoretically and qualitatively analyzes the non-linear impact of the income gap on carbon emissions. Then, the Gini coefficient of the resident income of different regions in China from 2010 to 2019 is calculated. Finally, a threshold regression model is used to quantitatively test the existence of a threshold effect between the income gap and carbon emission intensity in China. The threshold value is the per capita disposable income of residents. The results show that the income gap is positively related to carbon emission intensity in poor regions. In high-income areas, the widening income gap inhibits the increase in carbon emission intensity. Based on this, this paper proposes policy recommendations to narrow the income gap and reduce the intensity of carbon emissions. [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]

Based on the carbon emission data of China's manufacturing industry from 1998 to 2015, this paper examines the impact of carbon emission inclination of the central and local governments' industrial planning on regional carbon emissions. The findings of this study suggest that central industrial planning focuses on the long-term goal of economic development and favors low carbon emission industries, while local governments are more inclined to short-term economic growth and focus more on high-carbon emission industries with high output. The support of local industrial planning for high-carbon emission industries can reduce the intensity of regional carbon emissions, while the influence of central industrial planning is not evident. The mechanism analysis shows that government support for some industries can improve the industrial added value and reduce the carbon emission intensity. As the output value and carbon emission level of high-carbon emission industries are higher, the decline of carbon emissions caused by local government support for high-carbon emission industries will eventually lead to the reduction of carbon emission intensity in the whole region. The research explains the different paths that the central and local governments choose to develop a low-carbon economy and analyses their influences. [ABSTRACT FROM AUTHOR]

As a comprehensive and systematic approach to innovation, green innovation has become an important tool for reducing haze and carbon intensity. Based on balanced panel data at the city level in China, we use the two-way fixed-effects model to explore the impact of urban green innovation on haze pollution and carbon emission intensity. The conclusions are as follows: 1) The influence of green innovation on carbon emissions intensity and haze pollution exhibits a significant inverted U-shaped relationship. 2) We explore the mediating channels through which green innovation affects carbon emissions intensity and haze pollution. Specifically, the inverted U-shaped impacts of green innovation on energy intensity and resource dependence. 3) The inverted U-shaped relationship between green innovation and carbon emissions intensity holds for both resource-based and non-resource-based cities. 4) The U-shaped relationships, whether regarding carbon emissions intensity or haze pollution, are only applicable to non-environmental priority cities. This paper offers valuable insights for the formulation of more effective environmental management measures by governments. [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 development path from attaching importance to environmental protection to the theory of ecological conservation, then to piloting ecological civilization demonstration areas, marks that China’s ecological conservation has gradually moved from theoretical construction to practical exploration, based on the new idea that “lucid waters and lush mountains are invaluable assets.” It is still an ordeal for China’s ecological conservation in the context of global warming how to reduce carbon emission intensity while maintaining sustained economic growth. Under the dual constraints of peaking carbon dioxide emissions before 2030 and achieving carbon neutrality before 2060 (“dual carbon” goals), this paper employs the five national ecological civilization pilot demonstration areas (ECDAs) established in 2014 as quasi-natural experiments based on the panel data of 30 Chinese provincial regions from 2003 to 2019. Based on the analysis of the policy implementation background and the theoretical mechanism of its impact on carbon emission intensity, the synthetic control method and difference in differences method are adopted to test the impact of the construction of ECDAs on carbon emission intensity and examine the spatial spillover effect of the pilot policies. The study shows that the construction of ECDAs has significantly reduced carbon emission intensity as a whole, especially in Fujian, Guizhou, and Yunnan Provinces. Moreover, the conclusions successfully pass the robustness test. The mechanism analysis results demonstrate that the construction of ECDAs can lower carbon emission intensity through the positive incentives from boosting technological progress and developing green finance, and the reversal pressure mechanism of optimizing the energy structure and improving the market segmentation. The analysis results of the spatial spillover effect indicate that the construction of ECDAs plays a significant role in reducing carbon emission intensity in the region and its adjacent areas. Therefore, China should introduce ECDAs and the experience gained to more regions. Meanwhile, China should spare no effort to seek multi-dimensional paths to reduce carbon emissions in view of regional differences in green development, and strengthen cross-regional communications and cooperation to realize the goals of carbon emission reduction. [ABSTRACT FROM AUTHOR]

Our understanding of how net global warming potential (NGWP) and greenhouse gas intensity (GHGI) is affected by management practices aimed at food security with respect to rice agriculture remains limited. In the present study, a 5 year field experiment was conducted in China to evaluate the effects of integrated soil-crop system management (ISSM) on NGWP and GHGI after accounting for carbon dioxide (CO2) emissions from all sources (methane, CH4, and nitrous oxide, N2O, emissions, agrochemical inputs, Ei, and farm operations, Eo) and sinks (i.e., soil organic carbon, SOC, sequestration). For the improvement of rice yield and agronomic nitrogen use efficiency (NUE), four ISSM scenarios consisting of different nitrogen (N) fertilization rates relative to the local farmers' practice (FP) rate were carried out, namely, N1 (25% reduction), N2 (10% reduction), N3 (FP rate) and N4 (25% increase). The results showed that compared with the FP, the four ISSM scenarios, i.e., N1, N2, N3 and N4, significantly increased the rice yields by 10, 16, 28 and 41% and the agronomic NUE by 75, 67, 86 and 82%, respectively. In addition, compared with the FP, the N1 and N2 scenarios significantly reduced the GHGI by 14 and 18%, respectively, despite similar NGWPs. The N3 and N4 scenarios remarkably increased the NGWP and GHGI by an average of 67 and 36%, respectively. In conclusion, the ISSM strategies are promising for both food security and environmental protection, and the ISSM scenario of N2 is the optimal strategy to realize high yields and high NUE together with low environmental impacts for this agricultural rice field. [ABSTRACT FROM AUTHOR]

Climate anomalies are affecting the world. How to reduce carbon emissions has become an important issue for governments and academics. Although previous researchers have discussed the factors of carbon emission reduction from environmental regulation, economic development, and industrial structure, limited studies have explored the carbon emission reduction effect of a city's spatial structure. Based on 108 Chinese cities from the Yangtze River Economic Belt between 2003 and 2017, this paper examines the impact of the city cluster policy on city carbon emissions using the difference-in-differences (DID) method. We find that: (1) The city cluster policy has significantly reduced the cities' carbon emissions by 7.4%. Furthermore, after a series of robust and endogenous tests, such as parallel trend and PSM-DID, the core conclusion still remains. (2) We further identify possible economic channels through this effect, and find that city cluster policy would increase city productivity, city technological innovation, and industrial structure optimization. The conclusions of this paper have important practical significance for China to achieve carbon neutrality and facilitate future deep decarbonization. [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]

This paper presents an empirical investigation into the effects of energy transition and digitization on carbon dioxide emissions, serving as a proxy for environmental sustainability, across 28 Chinese provinces from 2000 to 2021. Utilizing both static and dynamic regression analyses, the study reveals a significant driving effect of the energy transition on environmental sustainability, primarily through a reduction in carbon dioxide emissions. Notably, this influence is more pronounced in the eastern region of China, followed by the central and western regions, indicating regional heterogeneity in the impact of the energy transition. Furthermore, digitization is found to have a substantial moderating effect, enhancing energy conservation and emission reductions. As digitization progresses, its capability to diminish the impact of energy transitions on carbon dioxide emissions becomes more apparent, particularly in the eastern region, while this effect is less marked in central and western China. The study also delves into the nonlinear relationship between energy transitions and carbon dioxide emissions, discovering that increased levels of digitization can exacerbate the negative effects of energy transitions on emissions. These findings offer valuable insights into the dynamics of energy transition and digitalization, highlighting their crucial roles in shaping environmental sustainability in China. [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]

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]

In order to achieve sustainable development goals, China has further increased its goal of reducing carbon intensity and has made digitalization an important support for sustainable development. However, the impact of digitalization on carbon intensity reduction is still unclear. In this context, this paper first evaluates the digitalization level of 30 provincial regions in China and then constructs a spatial Durbin model for two stages, 2012–2015 and 2016–2019, so as to explore the spatial spillover effects of carbon intensity in different stages and the important roles of digital infrastructure and digital inputs in carbon intensity reduction. The main findings are as follows: (1) the current digitization level of each province in China is widely disparate, with the region showing a high level in the east and a low level in the west; (2) carbon intensity reduction has a significant spatial spillover effect, as shown by a 1% reduction in local carbon intensity and a 0.21% reduction in neighboring regions; and (3) digitalization has a more significant positive impact on the reduction in carbon intensity in stage 2. The research results are strong demonstration that digitalization drives sustainable development. [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]

Given the spatial heterogeneity of the social-economic situations across different regions in China, the decomposition of emission reduction targets should be designed according to the actual characteristics of the industrial economy. There is concern about the loss of industrial competitiveness and leakage of CO2 emissions if just seven pilot carbon markets operate independently, so the national carbon market of the power sector was established in 2021. In this study, a China two-region CGE model including Guangdong (GD) and the rest of China (ROC) is built on an analysis of the long-term effects of CO2 prices in industrial sectors at the target 2030 peak. Based on this model, we constructed one business-as-usual scenario and six comparison carbon tax scenarios to quantify the CO2 cost impact for a wide range of manufacturing sectors and identify specific economic activities that face relatively high CO2 costs between the two regions. Based on the China two-region CGE model, the risks of leakage and competitiveness distortions in these potentially exposed sectors are qualitatively assessed. The results show that chemical, nonferrous metal, and machinery are GD's competitive sectors, and agriculture, food, textile, paper, cement, construction, and service belong to ROC's competitive industry. Both GD and ROC need to further unify carbon pricing policies at the same time to effectively coordinate the carbon intensity reduction target and industrial development, which is 2.6% and 3.2% of the severe GDP loss compared with BaU when implementing carbon tax policy. The results can support the setting of the carbon tax and industrial competitiveness promotion policy and with a strong reference to support the provincial emission reduction path. [ABSTRACT FROM AUTHOR]

Agricultural ecosystems are major sources of greenhouse gas (GHG) emissions, specifically nitrous oxide (N2O) and carbon dioxide (CO2). An important method of researching GHG emissions in agricultural ecosystems is model simulation. Field measurements quantifying N2O and CO2 fluxes were taken in a summer maize ecosystem in Zhangye City, Gansu Province, in northwestern China in 2010. Observed N2O and CO2 fluxes were used for validating flux predictions by a DeNitrification-DeComposition (DNDC) model. Then the validated DNDC model was used for sensitivity tests on three variables under consideration: climatic factors, soil properties, and agricultural management. Results indicate that: (1) the factors that N2O emissions are most sensitive to nitrogen fertilizer application rate, manure amendment and residue return rate; (2) CO2 emission increases with increasing manure amendment, residue return rate and initial soil organic carbon (SOC); and (3) net global warming potential (GWP) increases with increasing N fertilizer application rate and decreases as manure amendment, residue return rate and precipitation increase. Simulation of the long-term impact on SOC, N2O and net GWP emissions over 100 yr of management led to the conclusion that increasing residue return rate is a more efficient method of mitigating GHG emission than increasing fertilizer N application rate in the study area. [ABSTRACT FROM AUTHOR]

The extreme weather caused by the global warming effect has triggered huge losses to agricultural production. A hot issue for governments and scholars is how to effectively reduce carbon emission intensity in agriculture. The agricultural farming practices that are high pollution and high energy cosuming have exacerbated the vulnerability of regional agroecosystems. The sustainable development of agriculture is faced with the two dilemmas of a low utilization rate of green resources and the serious pollution of farmland. Further, environmental and ecological carrying capacities have reached their limits, seriously hindering the high-quality development of low-carbon agriculture in China. Thus, based on the panel data of 282 cities, the Spatial Dubin Model (SDM) is employed to examine the impact of agricultural mechanization on carbon emission intensity in agriculture. It is found that from 1999 to 2019 carbon emission intensity in agriculture showed an overall downward trend; as of 2019, the agricultural field had completed the target of carbon emission reduction, one year ahead of schedule. From a local perspective, approximately 14.89% of agricultural industries in prefecture-level city have still not achieved carbon emission reduction targets, and agricultural carbon emission reduction tasks were better completed in major grain-producing areas than in nonmajor grain-producing areas. Agricultural mechanization has significantly reduced carbon emission intensity in local agriculture production. The impact of agricultural mechanization on carbon emission intensity in agriculture has not only a significant negative spatial spillover effect but also a significant effect on spatial carbon emission reduction. Compared with non-major grain-producing areas, agricultural mechanization plays a greater role in reducing spatial carbon emissions in major grain-producing areas. Further studies find that agricultural mechanization is conducive to overcome difficulties, such as instability of property rights and land fragmentation, and to achieve large-scale agricultural production, thereby reducing agricultural carbon emissions in nearby regions. However, the transfer of rural labor, adjustments to the structure of agricultural cultivation, and the centralized use of rural land restrict the development of the crossregional service market for agricultural machinery, which in turn weaken its contribution to spatial carbon emission reduction. At the end of this paper, it is suggested that Chinese governments at all levels should introduce subsidy policies for the cross-regional operation of agricultural machinery to solve the problem of their service market failure. Efforts should be made to stimulate the market to develop more energy-efficient and environmentally friendly agricultural machinery products while strictly controlling changes in the use of arable land in non-grain-producing areas, which aims to serve further agricultural mechanization and boost the high-quality development of low-carbon agriculture. [ABSTRACT FROM AUTHOR]

China has established and assigned target responsibilities for local officials in energy conservation and created an evaluation indicator, which is a key institutional arrangement that provides local officials with political incentives to promote carbon abatement policies. In this paper, we elaborate on the relationship between China's target responsibility system and CO2 emissions using interprovincial panel data, grouping provinces into Eastern, Central and Western regions to compare China's CO2 emissions convergence between the periods of the 10th Five-year Plan and the 11th Five-year Plan. The analysis indicates that the target responsibility system does not noticeably change local officials' political incentives to engage in carbon abatement because the effect of the target responsibility system for energy conservation seems to be overshadowed by and subject to gross domestic product (GDP) growth targets. Against the backdrop of growing international pressure on climate change issues, this paper argues that China must include in the target responsibility system an indicator of absolute CO2 emissions reduction as a policy objective. [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]

With the increasingly strict regulations for the energy-saving and emission-reduction technology of ships, minimizing fuel cost and thus reducing the carbon intensity index (CII) is one of the most critical issues in the design and operation of merchant ships. More recently, many wind-assisted devices, such as rotors, wind sails, etc., have been investigated and designed to utilize renewable wind energy. With the equipment of wind-assisted rotors, the optimization of ship routes becomes more important because the effect of this wind-assisted device highly depends on the local wind field along the shipping route. In this paper, an improved ship weather routing framework based on the A* algorithm has been proposed to determine the optimal ship route and ship operations with wind-assisted rotors. The proposed framework effectively utilizes different sources of data, including ship design, weather forecasting and historical sailing information, to produce a better estimation of fuel consumption under the effect of sea states. Several improvements on the classic A* algorithm, including directed searching and three-dimensional extension, are proposed to improve the routing effect and efficiency. Finally, the proposed method was applied to test cases of a VLCC operating from China to the Middle East and the results show that the total fuel consumption could be reduced compared to the minimum distance route. [ABSTRACT FROM AUTHOR]

The allocation mechanism for carbon emissions permit(CEP) is an institutional guarantee for advancing the development of China's unified carbon trading market. The initial allocation of carbon quotas fails to solve new inequalities stemming from subsidizing cleaner production. This paper constructs a theoretical framework that describes China's progressive decline in carbon intensity, calculates the equilibrium solution on the neoclassical saddle point path using the shooting method, and studies the income distribution imbalance caused by cleaner production subsidies and the reallocation mechanism of carbon emissions permit The main conclusion is that the incremental cleaner production subsidy policy meets the goal of maximizing welfare on the saddle point path, but it may lead to over-investment in the clean sector, thus causing the income distribution imbalance among entities. Further research suggests that the amount of carbon emissions permit acquired by the clean sector should be higher than the actual emissions in the trading market and that, as the cleaner support increases, the share of carbon emissions permit acquired by the sector should be constantly increased through reallocation mechanism. This helps achieve the Pareto improvement in all parties' economic benefits. [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]

Based on panel data from 277 cities in China from 2003 to 2019, this paper uses a multi-period difference-in-differences (DID) model to analyze the effect of civilized city construction on urban carbon emission intensity. The findings of the research are as follows: Firstly, the construction of civilized cities is conducive to curbing the carbon emission intensity of cities, and the construction of civilized cities has reduced urban carbon emission intensity by 14.5%. Secondly, this inhibitory effect can be achieved by optimizing the industrial structure, reducing urban energy consumption, and improving technological innovation. Thirdly, the impact of civilized city construction on urban carbon emissions varies significantly depending on urban location, urban administrative level, urban resource endowment, and urban cultural tourism resources. In addition, the construction of civilized cities in China has resulted in a reduction of carbon emission intensity by 13.2% in non-resource-based cities, and tourist cities have witnessed a 16.8% decrease in carbon emission intensity due to the construction of civilized cities. Finally, based on the analysis results, some suggestions are put forward for promoting the construction of civilized cities in China to reduce carbon emission intensity. [ABSTRACT FROM AUTHOR]

This paper discusses the path to achieve carbon neutrality in the construction field, which is divided into five parts: (1) China's carbon peaking and carbon neutrality goals and consensus on the development of the construction industry; (2) The sustainable green building development trend and relevant policies in China; (3) The green building evaluation system and common software in China; (4) Building carbon emission evaluation model and the decarbonizing tools for the whole life cycle of construction projects; (5) Carbon emission reduction technology evaluation framework of autoclaved aerated concrete production in China. Through the discussion of this paper, we will jointly provide intellectual and technical support for the exploration and implementation of building carbon neutralization path. [ABSTRACT FROM AUTHOR]

The development of information technology such as the continuous improvement of mobile Internet infrastructure and the performance of computers has made it easy to process and share information. The huge market demand for location-based information services provides huge impetus to the generation and development of mobile terminal positioning technology. Generally speaking, the main causes of climate change can be summarized into two categories: natural climate fluctuations and the impact of human activities which is a major measure taken by China to actively respond to climate change. This is a successful approach to actively explore the rapid development of China's industrialization and urbanization, which not only develops the economy and improves people's livelihood but also responds to climate change and reduces carbon intensity. Firstly, this paper mainly is aimed at the connotation of regional low-carbon economic development mode, studying the basic mode of regional low-carbon economic development, and analyzing the characteristics and applicable conditions of each mode. Secondly, based on the machine learning algorithm of data mining, the main mode selection of regional low-carbon economic development is discussed. Thirdly and finally, when choosing the regional low-carbon economic development mode, comprehensive consideration should be given to the economic development basis, energy structure, resource characteristics, industrial status, development mode, geographic location, and other factors. This paper studies the basic conditions and applicable conditions of regional economic development models. The conclusion shows that from the perspective of regional economic evolution, low-carbon economy can be regarded as the decarbonization process of economic development. It is an economic form combining its own characteristics and an inevitable requirement for the transformation of regional economy from other economic models to low-carbon economic models. And other factors of Selection of regional economic development foundation, energy structure, resource characteristics, industrial status, development mode, geographical location, were also discussed. [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]

Engineering and technological breakthroughs in sustainability play a crucial role in reducing carbon emissions. An important aspect of this is the active participation of enterprises in addressing carbon reduction as a systemic approach. In response to government incentives in the People's Republic of China, Chinese enterprises have developed carbon reduction systems to align their organizational goals with national long-term plans. This paper evaluates the carbon reduction schemes employed by six companies as a multi-criteria decision-making (MCDM) problem. To this end, we propose a new hybrid MCDM method called the grey-MEREC-MAIRCA method. This method combines the recently developed method based on the removal effects of criteria (MEREC) for weighting and multi-attribute ideal-real comparative analysis (MAIRCA) based on the grey system theory. The proposed hybrid method provides the additional benefit of accounting for uncertainty in decision making. Notable findings of this research, based on the decision-maker scores, are that the control of direct carbon emissions and energy-saving efficiency are top priorities. In contrast, committing to corporate social responsibility through carbon public welfare and information disclosure are considered lesser priorities. Furthermore, the ranking results obtained using this method are compared with those from the classical weighted sum model and the technique for order preference by similarity to ideal solution (TOPSIS), confirming the selection of the best company. Despite the limitation of the proposed method and the additional steps needed in the evaluation, it opens up opportunities for future research to develop simpler MCDM methods under uncertainty. [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 reduction of carbon emissions in the power industry will play a vital role in global decarbonization. The power industry has three main strategies to achieve this reduction in emissions: to implement lean marketing strategies that effectively target users of power and encourage them to adopt decarbonizing technologies and services; to optimize the efficiency of these users of power; and to improve the efficiency of renewable energy sources. This paper establishes a comprehensive evaluation system of indexed data from power industry customers for the development of lean marketing strategies. This system evaluates indexes derived from customer data on renewable energy sources, carbon emissions, energy efficiency, and customer credit. It adopts the DEMATEL–CRITIC combination weight assignment and VIKOR method for system evaluation and conducts simulation experiments on customer data in a region of Northeastern China to give an example of how this method could be applied in practice to lean marketing. The results show that the evaluation system proposed in this paper can govern the lean marketing decision-making of power sales enterprises. [ABSTRACT FROM AUTHOR]

Comparing and evaluating the Nationally Determined Contribution (NDC) is an important element in global stocktake in the post-Paris climate negotiations, aimed at closing the emissions gap with the Paris Agreement goals. To date, however, there has still been no explicit guideline or method. By applying emissions allowance allocated by 16 schemes as benchmarks, this paper tries to compare and evaluate the NDCs of the top six emitters, which jointly account for about 70% of the world’s CO2 emissions. Results show that the four developed countries’ NDCs lack ambition with respect to most allocations under 2°C and all under 1.5°C, indicating they need to substantially ratchet up their NDCs and lead elevating mitigation. Evaluating cumulative emissions is more likely to clarify the ambition and fairness of China’s NDC. If considering cumulative emissions, China’s NDC is aligned with the median of cumulative allowances under 2°C and within the 1.5°C range. The Paris Agreement invited the Parties to communicate the mid-century low emissions strategies. This paper also tries to explore the mid-century mitigation in the perspective of allocations, which might provide decision-makers with some useful information when envisaging the post-NDC mitigation. [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]

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]

Carbon trading downstream, as a key strategy for decreasing carbon emissions, has the potential to hasten the entire society's decarbonization. Taking the government, household, and carbon trading management center as stakeholders, this paper constructs a tripartite evolutionary game model, examines and stimulates evolutionary stability strategies, and then proposes some policy implications. Findings show that the downstream carbon market faces a complex evolutionary process. The promotion of the policy can be split into two periods: policy promotion and policy stability implementation. And proper household size management is a crucial and effective strategy to encourage downstream carbon trading programs and emission reduction. [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 paper presents an in-depth analysis of the Marginal Abatement Cost Curve (MACC) for CO2 of China's industrial sector. Leveraging comprehensive firm-level panel data spanning the period 2011–2015, we employ a parameterized directional output distance function to estimate the shadow price of CO2. By doing so, we derive the marginal abatement cost for individual firms across different years, which provides crucial insights into two fundamental aspects: first, the variation in shadow prices as indicators of the economic efficiency of existing climate policies; and second, the carbon price levels necessary to achieve CO2 mitigation targets in the future. Furthermore, we conduct scenario simulations to assess the potential industrial output loss resulting from forthcoming carbon policies, such as the European Union's Carbon Border Adjustment Mechanism (CBAM). Our findings underscore the necessity for a considerably higher tax rate to stimulate pollution reduction in order to meet the desired emission targets. [ABSTRACT FROM AUTHOR]