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Global environmental problems are worsening. Among various regulatory measures, market-oriented approaches are most favored by governments worldwide. Using provincial panel data from 2004 to 2020, a multi-period DID model was hereby constructed to empirically study the pollution reduction effects of the pilot policy for carbon emissions trading in China. Findings of this paper could be listed as follows: (1) The pilot policy has achieved notable reductions in waste gas and solid waste, although its effect on wastewater pollutants has been less pronounced; (2) Pollution reduction in the pilot regions can be achieved by optimizing the energy consumption structure; (3) Significant variations in pollution reduction effects are observed between the Northern and Southern pilot regions, with notably stronger policy effects in the north across various pollutants compared to the south. Overall, this paper offers pertinent policy recommendations to aid the Chinese government in enhancing its carbon market. [ABSTRACT FROM AUTHOR]

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

Being one of the significant conduits linking international and domestic markets, agricultural trade is an area of study that commands attention. While it may bring about transnational carbon emission transfers, it begs the question: does it promote carbon reduction in a country's agricultural sector? Such an inquiry holds profound implications for optimizing agricultural trade and promoting low-carbon agricultural advancement. Utilizing two-way fixed effect model, mediating effect model and dual-fixed spatial Durbin model, this paper examines the impact effects, mechanisms and spatial characteristics of agricultural trade openness (ATO) on agricultural carbon reduction using panel data from Chinese provinces spanning 2000 to 2021. The main findings include: (1) ATO markedly and positively influences the reduction of agricultural carbon emissions (ACE), this conclusion maintains its validity under endogeneity treatment and robustness tests. (2) ATO contributes to reducing ACE through three intermediary channels: scale effect, technological effect, and structural effect. (3) From a spatial perspective, a notable positive spatial spillover effect is observed from agricultural trade openness to agricultural carbon reduction, with the spatial carbon reduction effect being more apparent. (4) The spatial carbon reduction effect of agricultural trade liberalization exhibits heterogeneity across different natural geographical locations and levels of ATO. The study confirms the vital role of ATO in promoting agricultural carbon reduction in typical countries, underscoring the urgency and importance of bolstering cross-border agricultural trade cooperation and domestic agricultural product circulation in the domain of climate change. • The impact of agricultural trade openness (ATO) on agricultural carbon reduction is investigated in China. • The scale, technological, and structural effect of ATO serve as intermediary channels in reducing carbon emissions. • ATO engenders positive spatial spillover effects on agricultural carbon reduction. • Bolstering cross-border agricultural trade cooperation are of importance and urgency in the domain of climate change. [ABSTRACT FROM AUTHOR]

To support high-quality carbon peaking, a scenario analysis of carbon peaking pathways according to an industrial chain perspective considering both material and part production needs exploring. As a critical segment in the aluminum industrial chain, aluminum casting industry was focused on in this paper. A bottom-up scenario analysis approach was proposed for the carbon emission simulation of China's aluminum casting industry, including: (1) a carbon emission assessment model based on material flow analysis and life-cycle assessment, (2) key influence factor selection and variation scenario prediction, (3) static and dynamic scenario analysis, and (4) driving factor decomposition analysis. Key findings are as follows: (1) China's aluminum casting industry accounted for about 1.1% of the national carbon emissions in 2020; (2) the production stage accounted for around 15% of the total carbon emissions of China's aluminum casting industry in 2020; (3) carbon peaking probabilities before 2030 for the static and dynamic scenario analysis are around 60% and 35%, respectively; and (4) the carbon peaking result differences in whether considering the production stage are about 20% for the static simulation and average 40% for the dynamic simulation. These findings effectively support the formulation of a high-quality carbon peaking pathway. • A bottom-up approach of scenario analysis was proposed for carbon peaking pathways. • Carbon emission assessment model was built with corresponding inventory data. • Static and dynamic scenario analyses of carbon emissions were compared. • Decomposition and sensitivity analysis of driving factors were conducted. • Production stage accounted for around 15% of the total carbon emissions. [ABSTRACT FROM AUTHOR]

Under the goal of "carbon peaking" and "carbon neutrality" in China, it is significant to explore whether green finance contributes to carbon emission reduction. Therefore, based on the panel data of 30 provinces in China from 2005 to 2020, this paper empirically examines the impact of green finance on carbon emissions and its mechanism using the FE model, GMM model, DID, and the mediating effect model. Results find that green finance can significantly promote carbon emissions reduction, and this promotion remains still after robustness tests. The heterogeneity analysis shows that green finance's carbon emission reduction effect is more significant in developed and western regions. Moreover, the results of policy intervention effects confirm that green finance reform and innovation pilot zones (GFRIs) for carbon emission reduction are more pronounced than in other regions. Finally, the mediating effects reveal that industrial structure and green innovation are the core transmission channels through which green finance influences carbon emission reduction. These findings offer meaningful implications for formulating reasonable carbon emission reduction plans and determining the future development direction of green finance. [ABSTRACT FROM AUTHOR]

Cities produce over 70% of global carbon emissions and are thus crucial in driving climate change. Urban carbon emissions may continue to increase especially in those less-developed countries and regions which are still under rapid urban development. Policymakers need to find ways to effectively control and reduce carbon emissions. Thus, spatial modeling methods to map and predict urban carbon emissions have been developed to meet these needs. This paper examines the progress of the spatial modeling of carbon emissions and the relationship between urban form and carbon emissions in China by reviewing more than 100 peer-reviewed journal articles in the Scopus database. The latest prediction methods and techniques are described in the paper. Their advantages and limitations are then discussed. Urban forms have a significant influence on carbon emissions and have been applied in spatial modeling studies in other countries. However, this review has identified the lack of urban form data and high-resolution inventories from existing studies in China. Future developments in the spatial modeling in China should therefore have a fine spatial resolution and incorporate open and high-quality urban form data, including urban morphology and land use/land cover. • The spatial modeling studies of urban carbon emission in China are reviewed. • The available data and methods are summarized. • The strengths and weaknesses of the methods are compared. • Urban forms can affect urban carbon emissions. • Future developments will require a finer spatial resolution and urban form data. [ABSTRACT FROM AUTHOR]

New Energy Vehicles (NEVs) exert great potential in reducing carbon emissions, improving air quality and reducing the dependence on petroleum products, and are also essential in realizing the social transformation toward a low-carbon society. Since public are the principal users and stakeholders of NEVs, it's vital to understand their acceptance of NEVs and discuss the influencing factors of public acceptance, so as to promote the development of NEVs. Based on the survey data of Gansu Province, this paper analyzes the public perception and acceptance of NEVs in underdeveloped regions, and explores main factors affecting their acceptance by adopting Structural Equation Model. The results show that the public acceptance of NEVs is relatively higher, with only 51.99% residents are willing to accept NEVs. And there are differences of public acceptance of NEVs among different groups. The acceptance of females, young and less educated public are relatively higher, decreases with aging and increases with education attainment. Perceived risk and perceived cost are significantly negative correlated with public acceptance of NEVs, while subjective norm and the quality of NEVs positively correlated with public acceptance. In addition, support policy is significantly positively correlated with perceived cost while perceived cost is positively corelated with perceived risk. Finally, this paper proposes countermeasures and suggestions on improving the public acceptance of NEVs in underdeveloped regions. • We conducted the NEVs acceptance of 1356 residents in Chinese underdeveloped regions. • 51.99% of the public in underdeveloped regions of China were willing to accept NEVs. • Perceived risk, perceived cost, and NEVs' quality are the key influencing factors. • Support policy, knowledge have significant indirect impact on acceptance of NEVs. • Enhancing subsidies and supporting facilities were effective ways. [ABSTRACT FROM AUTHOR]

Strict climate goals require a rapid reduction of carbon emissions across society. It is a considerable challenge to design decarbonization pathways considering co-operation in energy and carbon emissions across multiple sectors simultaneously. In order to obtain the decarbonization pathway for the whole society, this paper establishes a long-term multi-sector low-carbon transition pathway planning model. Besides inter-sectoral energy supply and demand, this study fully considers the allocation of carbon emissions quotas among different sectors by modified-grandfathering method, which takes into account both equity and efficiency principles. The decarbonization targets of different sectors, corresponding mitigation pathways and energy consumption can be calculated. China is taken as a case study. Results show that China's total energy consumption peaks at 5 billion tces around 2030, then falls below 4 billion in 2060, with the proportion of primary electricity and other clean energy reaching over 50 percent. Besides, the realisation of carbon neutralisation in China depends heavily on the improvement of carbon capture and storage (CCS) and end-use electrification rate. Moreover, the study of different quota allocation ways shows that the increase in the contribution rate of power system mitigation leads to the reduction of the total low-carbon transition costs, which also aggravates administrative difficulties. • A multi-sector model is set up to plan the long-term low-carbon transition pathway. • Modified-grandfathering allocation method can consider multiple indicator factors. • The clean energy consumption of China accounts for about 55% in 2060. • The end-use electrification rate in China is close to 70% in 2060. • The transition pathway with lower cost increases administrative difficulties. [ABSTRACT FROM AUTHOR]

The total factor carbon emission performance has been largely used to investigate the effectiveness of climate policies and to support the design of carbon reduction strategies. Despite the important information that this indicator is providing in relation to historical and cross-country trends, no previous studies have been specifically devoted to analyze the persistent and the transient components of the total factor carbon emission performance. By disaggregating the time-variant and the time-invariant elements of the carbon dioxide emission changes, this paper adopts, for the first time, a new methodological approach to decompose the components of the total factor carbon emission performance indicator. Using panel data for selected 30 Chinese provinces for the time-period 1997–2017, this paper combines the environmental production technology, the Shephard distance function, and the stochastic frontier models to measure and investigate the spatio-temporal evolution of the total factor carbon emission performance and to evaluate the effectiveness of Chinese policies. By providing a better understanding of the total factor carbon dioxide emission performance, the proposed methodology is suitable to be replicated across regions, and provides an important opportunity for international comparisons and for the design of coordinated carbon reduction strategies. ⁃ An innovative approach is presented to decompose the persistent and transient TFCP ⁃ TFCP of China is affected by persistent inefficiency with regional disparities ⁃ The economic determinants of persistent and transient TFCP are investigated ⁃ Industrialisation, FDI, technology progress are key determinants of persistent TFCP [ABSTRACT FROM AUTHOR]

As a basic structural unit of the city, the community plays a crucial role in decreasing carbon emissions and creating a low carbon city. This paper selects a classic and official low carbon community named Min'an Community in Beijing as a case to illustrate the governance mechanism of the low carbon community in China from the perspective of polycentric governance. The paper summarizes the government mechanism, market mechanism, and public participation mechanism in Min'an Community and analyzes the provision, monitoring, and enforcement of each mechanism. We find that unlike the low carbon governance at the city or industry park levels, China's low carbon governance at the community level lacks a dominant mechanism. Even though it involves community-wide governance, the public participation mechanism is also inadequate. For improving low carbon governance at the community level, the government should broaden finance channels to strengthen the incentive mechanisms, make active use of new technologies, such as mobile Internet, encourage innovation of public participation mechanism, and employ various publicity and education measures to cultivate the low carbon culture. [ABSTRACT FROM AUTHOR]

Understanding the causes of growing carbon transfers between developing countries is likely to be the first step in their mitigation. With this in mind, the current paper uses multi-regional input-output analysis to investigate CO 2 emissions and value-added embodied in China-Brazil trade. We propose the use of value-added exports, rather than gross exports, to more accurately estimate the economic benefits of trade. We find enormous increases in both CO 2 emissions and value-added embodied in exports for China and Brazil between 2000 and 2014. During this period, China's position as a net CO 2 emissions and net value-added exporter vis-à-vis Brazil deepens. Major sources of increasing embodied CO 2 exports for China were the basic materials and electricity industries and for Brazil were the basic materials, agriculture and mining industries. Estimates of net carbon intensities reveal advantages for China in electronics and for Brazil in agriculture and mining. Structural decomposition analysis shows that the changing consumption in China and Brazil as well as the changing structure of intermediate exports from China to Brazil were important sources of increasing embodied CO 2 emissions. This latter finding was possible due to the method proposed in this paper of decomposing the production structure into the domestic, export and import production structures. In line with the key findings, various implications and emission abatement policies are discussed. [ABSTRACT FROM AUTHOR]

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

The power sector plays a significant role in China's energy transition and emission reduction strategy. Considering that the aggregation of the power sector from different sources in input-output (IO) tables will lead to the "aggregation bias problem", it is vital that we disaggregate the power sector using IO tables when analyzing and comparing the driving forces of embodied carbon emission changes in the power sector. This paper first disaggregates the power sector into seven subsectors; then, it uses structural decomposition analysis (SDA) to analyze the driving forces of embodied carbon emission changes in each subsector and allocates embodied emissions that occur from 2007 to 2015 according to the demand categories. The results show that the embodied carbon emissions from each clean energy sector were relatively lower than those from thermal power during the study period. Consumption volume was the main driving factor for the embodied carbon emission increments. From 2012 to 2015, the production structure was mainly responsible for the embodied emission increases in each clean energy sector, indicating that the embodied carbon emissions caused by power equipment updates or reconstruction processes should receive more attention. In addition, the embodied carbon emission changes induced by urban residential consumption on the thermal power showed a plateaued trend from 2007 to 2015. This paper provides support for the formulation of emission reduction measures and the low-carbon structural transformation of the power sector. [ABSTRACT FROM AUTHOR]

Smart cities have the potential to achieve the goal of carbon neutrality, but empirical evidence regarding the effect of smart city policies on carbon emissions is limited. In this novel study, we investigate the effect of China's smart city policy on household daily consumption and carbon emissions. The empirical analysis is based on a difference-in-differences regression, in which the dependent variable is the household indirect carbon emissions estimated based on the consumer lifestyle approach and a dataset of 201 Chinese cities between 2010 and 2018. The main findings are as follows. First, the smart city policy significantly reduces household indirect carbon emissions, and the reduction is greater when the policy pilot region includes the whole city rather than only certain subareas. Second, the mechanisms through which the smart city influences household indirect carbon emissions are mainly the reductions in transportation- and education-related emissions resulting from developments in smart technology. Third, the above effects last for years, and they are regionally heterogeneous and more significant in the cities of eastern China. The findings in this paper suggest that smart cities can potentially achieve city sustainability by promoting greener consumption behavior. [ABSTRACT FROM AUTHOR]

Agricultural carbon emissions have long attracted scholars' interest. In recent decades, China has gradually explored the path of agricultural specialization without large-scale operation based on agricultural machinery service outsourcing driven by structural transformation. To date, our understanding of the impact of China's unique agricultural specialization on agricultural carbon emissions remains scant. Nevertheless, this issue is important for promoting China's carbon emission reduction and exploring a path of agricultural transformation that is both competitive and sustainable. Based on China's provincial panel data from 2000 to 2019, this paper constructed a mediating model to test empirically the impacts of agricultural specialization on agricultural carbon emissions. The results showed that agricultural specialization exerted a significant positive effect on agricultural carbon emissions by increasing agricultural external inputs. Specifically, in addition to promoting increased mechanization, agricultural specialization caused an even greater, excessive application of chemical fertilizers, which largely follows metabolic rift theory and substitution and remittance effects. The farmland operation scale had no significant effect on agricultural carbon emissions due to the offset of its significant negative effect on chemicalization and significant positive effect on mechanization. This finding demonstrates that, in the context of smallholder farming, the moderate expansion of farm size can reduce agricultural environmental pollution, but it cannot be proved to reduce agricultural carbon emissions. These findings challenge China's current unique path of agricultural specialization from the perspective of carbon emission reduction and demonstrate the applicability of the theory of metabolic rift to the current path of agricultural development in China. Accordingly, corresponding short-term and long-term implications related to agrarian transition and agricultural carbon emissions are provided. [Display omitted] • China's unique agricultural specialization promotes agricultural carbon emissions. • The moderate expansion of farm size can reduce agricultural environmental pollution. • The impact of agricultural specialization on external inputs follows the metabolic rift. • Excessive inputs of chemical fertilizers play a significant mediating effect. [ABSTRACT FROM AUTHOR]

This paper examines the risk spillover effect between the carbon market and the stock market in China and the role of corporate social responsibility (CSR) on this effect. Employing Beijing, Hubei, and Guangdong carbon markets, we apply time-domain and frequency-domain spillover approaches and find that during the Chinese stock market crisis in 2015, risk spillovers from the stock market to the carbon market were more pronounced. Additionally, CSR firms are more dominant as information transmitters than those non-CSR (NCSR) firms in the carbon market. However, plausibly, due to the infancy of carbon trading, our results show that the level of connectedness between the carbon market and the stock market in China is relatively low. [ABSTRACT FROM AUTHOR]

Universities, the important locations for scientific research and education, have the responsibility to lead ecological civilization and low carbon transition. Ecological footprint evaluation (EFE) is usually used to measure sustainability of campuses. Although it can provide guidance and reference for overall campus planning, it lacks effective significance for individual behavior, especially when the reduction of carbon emissions is the aim. On the other hand a possible solution can be represented by machine learning. It can identify the key factors that will influence individual's overall carbon emissions caused by students' daily behavior, it can be used to find effective ways to reduce individual carbon emissions. This paper applied EFE and machine learning to comprehensively evaluate campus sustainability and students' carbon emissions. Huazhong University of Science and Technology (HUST), a "University in the Forest", was used as a study case in China. Even if HUST is endowned with a forest coverage of 72%, here we showed that its Ecological Footprint Index was −12.52, indicating strong unsustainability. This is mainly due to the high energy and food consumption, caused by the large population living in the campus and the lacking of energy saving measures. The per capita ecological footprint was relatively high, compared with other universities in the world, which meant more efforts needed to be done on ecological sustainability. Low carbon emission is a key feature for a sustainable campus. Based on the questionnaire survey delivered to 486 students who live in the campus, their daily active data were collected in terms of students' personal clothing, food, housing, consumption and transportation. And their associated carbon emissions were calculated based on emission intensities of Chinese population. Based on 486 detailed datasets, machine learning was then used to identify the key daily behavior to influence students' total carbon emission. Results showed that making behavior changes in air conditioning, food and electric bicycle were the most effective ways to reduce carbon emissions. Finally, while effective suggestions were proposed based on qualitative and quantitative evaluations, it is concluded that it is imperative for universities in China to formulate effective low-carbon policies, to achieve sustainable development and to confront global climate change. • A review of main initiatives of sustainable campus construction worldwide. • An evaluation combining campus ecological footprint and individual carbon footprint. • The ecological footprint of "China Forest University" reflects unsustainable. • Machine learning identifies internal driving force of campus carbon emissions. • Targeted guidelines on campus low-carbon construction are provided. [ABSTRACT FROM AUTHOR]

An integrated approach is proposed in this paper to incorporate the group heterogeneity into the framework of natural disposability and managerial disposability, which allows evaluating the CO 2 emission performance under different mitigation strategies (scale-oriented strategy and innovation-oriented strategy). It is able to deal with the intertemporal incomparability when adopting a global technology. In the empirical study, we categorized China's 27 manufacturing sectors into five groups and evaluated their emission performance under different mitigation strategies during 2003–2016. According to the empirical results, we found that there is still much potential (about 70%–80%) for improving the CO 2 emission performance considering the entire manufacturing industry. From the perspective of different groups, the global technologies/innovators group shows the highest emission efficiency, while the energy-/resource-intensive commodities' group performed the worst. Besides, different sectors showed significant technology heterogeneity. Finally, the desirable CO 2 mitigation strategies varied with the different groups. For the labor-intensive tradables' group, we found that the desirable strategy is to decrease the input of energy and other production factors, i.e. scale-oriented strategy. For the regional processing group, the innovation-oriented strategy is more efficient. • Modified global meta-frontier non-radial DDF approach is proposed. • Group heterogeneity is incorporated in natural/managerial disposability framework. • CO 2 emissions performance for China's manufacturing sectors is measured. • Global technologies/innovators group performs best, while energy-/resource-intensive commodities group performs worst. • Desirable mitigation strategies varies with respect to technology heterogeneity of different groups. [ABSTRACT FROM AUTHOR]

Understanding the coupling mechanisms between carbon emissions and the eco-environment is essential for building sustainable economies. Based on the coupling coordination model, this paper investigates the coordination degree of carbon emissions and the eco-environment in China from 2009 to 2015. The Logarithmic Mean Divisia Index decomposition method was used to identify the key factors affecting the coordination degree. Furthermore, different scenarios were simulated to show the impact of changes in government priorities on the coordination degree. The results show that the dynamic relationship between carbon emissions and the eco-environment in China has reached a barely balanced stage, but a few provinces are still struggling with imbalances. The coordination level of carbon emissions and the eco-environment becomes the key factor affecting coordinated development, while the interaction intensity has a limited effect. Further analysis indicated that although the carbon emission evaluation value has a positive effect on promoting an increase in the coordination degree, the eco-environment evaluation value determines the trend of coordinated regional development. Moreover, the priorities of government policymakers have a substantial impact on coordinated development, but these impacts gradually diminish as the differences in evaluation values decrease. These findings contribute to the formulation of effective regional sustainable development strategies. [ABSTRACT FROM AUTHOR]