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High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]

In recent years, China has proposed the goal of peaking carbon dioxide emissions by 2030 and achieving carbon neutrality by 2060, which will significantly alter its existing coal-based energy mix. Since coal is China's primary source of energy and the largest contributor to carbon emissions, coal reduction is an important measure toward carbon neutrality. In order to guarantee the stable development of economy and society in the process of coal reduction, the path and cost of coal reduction need to be studied in depth. Based on coal use in China, this paper examines and measures the stages and costs of coal reduction. It also gives a definition for coal reduction costs for the first time, including economic cost, environment and ecology cost, and health cost, as well as proposes a framework for analyzing the "full cost, full process, and full scenario". We measure the cost in combination with the KAYA formula, and take into account the time value of the cost. Based on the above measurement framework, we calculate the unit coal reduction cost and estimate the coal reduction cost between CNY 454.38 and 827.1 billion. [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 address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO 2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO 2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO 2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality. • The National E-commerce Demonstration Cities (NEDC) policy reduced CO 2 emissions. • Optimizing industrial structure, enhancing digital finance, and promoting innovation and entrepreneurship are mechanisms. • The effect is more pronounced in cities with high economic levels and high resource dependence. • The NEDC policy substantially enhanced social welfare by reducing CO 2 emissions. [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]

To achieve the carbon peaking and neutrality targets in China, carbon price and technological innovation will play increasingly important roles in recent future. It is widely-known that carbon price and technological innovation can contribute significantly to emission reduction, respectively; but it is still unclear whether the cooperation effects of carbon price and technological innovation would be positive or negative. In this paper, we assume that there are 3 types of emission reduction measures in China's industrial enterprises, which are improvement of energy efficiency, adjustment of energy structure, and substitution of pollution inputs and non-pollution inputs; then we introduce carbon price and technological innovation respectively and simultaneously, and establish 12 scenarios based on the Data Envelopment Analysis models combined with material balance principal (DEA-MBP), and estimate the additional emission reductions and additional production costs of China's industrial enterprises when carbon price and technological innovation exist respectively or simultaneously. The counterfactually estimating results show that there would be significant regional and sectorial heterogeneities in carbon emission reduction characteristics for China's industrial enterprises. If low-carbon technologies in some sectors have the ability to reduce carbon emissions at the expense of high additional production cost, carbon pricing policies would encourage enterprises to adopt new mitigation technologies and increase additional emission reduction by more than 20%, especially technologies focusing on the adjustment of energy structure and the substitution of pollution inputs by non-pollution inputs. However, in some sectors which have already been covered by carbon pricing policies, the additional carbon pricing policy may not have a significant effect on emission reduction, and the emission reduction would decrease by 10%. [Display omitted] • Cooperation effects of carbon price and technological innovation are estimated. • DEA-MBP models and multiple emission reduction measures/scenarios are applied. • Introduction of carbon price would encourage the adopting of new mitigation technologies. • Carbon price and technological innovation would have overlapping effects. • Significant regional and sectorial heterogeneities exist in emission reduction features. [ABSTRACT FROM AUTHOR]

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

China is transforming the growth model and speeding up industrial structural improvement and upgrading now and in the coming years, which means the slowdown of economic growth and more serious environmental costs in economic and social development would be the "New Normal." As the world's largest energy consumer and carbon‐emitting country, China's emissions reduction commitments are crucial to global greenhouse gas emissions mitigation, so there is a profusion of research focused on China's economy‐environment nexus. Among which, the dynamic relationship of carbon emission and economic growth and its evolution combined the national, regional, provincial data have not been discussed thoroughly. This paper analyses the elasticity of economic performance of carbon emissions based on 30 Chinese provincial data from 2000 to 2016; furthermore, a panel vector autoregressive model is constructed to discuss the interactions of variables within environmental economic system. It is concluded that China is experiencing a turning point from weak decoupling to strong decoupling in recent years, and its economic performance of carbon emissions has been gradually improved with larger disparities among provinces though. Regression result confirms the role of the energy mix on carbon emissions, and it also indicates that the impact of most factors influencing that have been discussed in previous studies may not be direct, prominent, and for long term. [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]

[Display omitted] • Exploring the industrial water-land-energy-carbon interaction help promote resource conservation and low-carbon development. • Constructing evaluation indicators and decomposition model to assess the carbon emission effect of industrial water and land use. • Industrial carbon emission intensity of water and land use in China increases, and inter-provincial difference expands. • Industrial matching index of water and land resources in China presenting great spatial agglomeration. • Matching index of water and land resources is the main inhibitory factor for all provinces in China. The industrial production requires the input of water, land and energy, and the water-land-energy interaction generates carbon emissions. Investigating the industrial water-land-energy-carbon nexus and exploring the influencing factors of the carbon emissions help promote the intensive use of water resources, land resources, and energy, as well as the low-carbon development of industry. This paper applied kernel density estimation and spatial auto-correlation analysis to explore the spatio-temporal variation of industrial carbon emission effect of water and land use and the industrial matching status of water and land resources in China, and then analyzes the influencing factors to industrial carbon emissions by introducing water and land resource factor into Kaya identity and Logarithmic Mean Divisia Index (LMDI) model. The main conclusions are: (1) From 2006 to 2020, China's industrial carbon emissions increased by 82.02%. The industrial carbon emission intensity of water use (CEIWU) and the industrial carbon emission intensity of land use (CEILU) increased by 158.02% and 55.53% respectively. The inter-provincial difference of CEIWU and CEILU expanded considerably, and the number of provinces with high CEILU had a large increase. (2) The industrial matching index of water and land resources (MIWL) in China showed a fluctuating downward trend, presenting great spatial clustering, and the provincial MIWL were mainly concentrated in the H-H and L-L regions. (3) The contributing and inhibitory effect of each influencing factor varied on regional and provincial level. The economic output of water use is a contributing factor to all regions and provinces, while the MIWL is an inhibitory factor to all regions and provinces. [ABSTRACT FROM AUTHOR]

Shrinking cities are a category of cities characterized by population loss, and the environmental problems of these cities are often neglected. Using panel data from 2012 to 2019, this paper investigates the spatial and temporal distribution characteristics of carbon emissions in shrinking cities in China and the driving factors. The results find that: (1) From 2012 to 2019, carbon emissions tend to increase in shrinking cities and decrease in non-shrinking cities. Due to earlier industrial development and ecological neglect, shrinking cities in Northeast China have higher carbon emissions than other regions. (2) Population size, industrial structure and public services promote the growth of carbon emissions in shrinking cities. The influence of living environment on carbon emissions in shrinking cities is not significant. There is an environmental Kuznets curve (EKC) relationship between economic level and carbon emission. (3) In shrinking cities, the increase in commuting time and distance due to spatial expansion promotes the growth of carbon emissions. Foreign investment decreases with the loss of population, which reduces carbon emissions. Technological progress gradually declines as investment in science and technology decreases, which makes carbon emissions grow. This paper clarifies the driving factors of carbon emissions in shrinking cities in China, and therefore, the findings of this paper have important reference value for the formulation of carbon reduction policies in shrinking cities in developing countries. • Carbon emissions in shrinking cities tend to grow. • Shrinking cities have higher carbon emissions compared to non-shrinking cities. • The characteristic factors of shrinking cities affect carbon emissions. • Carbon emissions from shrinking cities have spatial effects. [ABSTRACT FROM AUTHOR]

Based on the tightening regulation of carbon emissions, China has launched the pilot carbon emission trading scheme (CETS) since 2013. There is growing empirical evidence of the actual effect of CETS to promote enterprises' productivity which is characterized by total factor productivity (TFP). However, most studies ignored the further analysis of influence mechanisms. This paper aims to explore the impact of CETS on the TFP of enterprises and discuss the mediating role of government participation and carbon trading market efficiency. Using data from A-share listed enterprises from CETS-covered enterprises, this paper employed a combination of the propensity score matching (PSM) and difference-in-differences (DID) strategies and found that the CETS has a statistically significant positive impact on the TFP of enterprises, and the positive effect has been maintained for six years since its inception. The moderation analysis indicated that: (1) two dimensions of government participation in terms of the market incentive and government supervision significantly moderate the positive impact of CETS on TFP of enterprises; (2) two dimensions of carbon trading market efficiency in terms of the market scale and liquidity significantly moderates the positive impact of CETS on TFP of enterprises. In light of Chinese pilots CETS policy, the study highlights the important moderating roles of government participation and high carbon trading market efficiency on enterprise's TFP. [Display omitted] • Chinese pilots CETS significantly improved the TFP of enterprises by 9.48%. • The government participation moderates the positive impact of CETS on enterprises' TFP. • The higher carbon trading market efficiency is, the greater the moderating effect of CETS on TFP is. [ABSTRACT FROM AUTHOR]

Abstract Household carbon emissions account for a significant proportion of the national total emissions. Using a unique nation-wide survey data, this paper investigates the impact of different subjective measures of social awareness on household carbon emissions in China. Subjective variables are found to have significant impacts on household carbon emissions. Feeling secure, compliance with rules, and happiness have negative and significant effects on household carbon emissions, whereas the impact of interest in social issues is positive, which indicates the existence of a gap between awareness and behavior. The impacts of consumer lifestyles on the relationship between awareness and household emissions are also explored and are found to play a significant role in the relationship between awareness and emissions. People with a frugal lifestyle not only associate with lower emissions but also reinforce the role of social awareness. Furthermore, substantial differences are found across rural/urban areas and regional and income groups in China. The government should further promote a green lifestyle and give households more incentives to engage in green consumption behavior. Highlights • Household emissions are studied based on China Household Finance Survey. • Subjective factors are found to have significant impacts on household emissions. • Lifestyles matter in the relationship between awareness and household emissions. • Regional and income differences are considered in the analysis. [ABSTRACT FROM AUTHOR]

This study performed an input-output structural decomposition analysis on changes in COD, ammonia nitrogen, SO 2 , NOx, soot and dust, industrial solid waste, and CO 2 emission multipliers for 41 final products over the period 2007–2012 in China. The results show that during the examined period, emission multipliers were, in general, decreasing. The main driver of this was technical effects. The effects that made a significant contribution were concentrated in eight sectors: coal mining and washing; metals mining and quarrying; food and tobacco products; paper printing manufacturing; the chemical industry; non-metallic mineral products; metal smelting and rolling processing; and electricity, heat production, and supply. Moreover, the technical effects presented an obvious spillover. Although the contribution of the structural effects was far less than the technical ones, there were still some structural adjustments that led to significant synergistic mitigation. For example, the decrease in the direct demand of the agriculture products, electricity, and heat for food and tobacco products commonly reduced SO 2 , NOx, and CO 2 . In addition, four technical effects and most of the structural effects with high efficiency made small contributions. More than one third of the structural effects that showed obvious contributions played a positive role. [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]

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]

Low-carbon pilot cities can break the lock-in effect of living carbon emissions, which are an important strategic component of China's response to climate change. Current research on low-carbon pilot cities focuses on the production field. Insufficient attention has been paid to whether low-carbon pilot cities can promote the green transformation of residents' lifestyle. Using panel data of 285 cities in China from 2004 to 2016, this study explores the inducing effect of low-carbon pilot cities on residents' low-carbon choices from holistic and single-dual perspectives based on the difference-in-differences method and the synthetic control method. This study finds that low-carbon pilot cities can promote the green transformation of residents' lifestyle, and this policy has reduced living carbon emissions by approximately 15.3%. The transmission mechanisms are mainly green life consciousness and green habits. The conclusion considers the effects of multi-pilot policies and other living differences during the parallel period and is still valid after robustness testing using propensity score matching difference-in-differences. In addition, the policy has a snowball effect, and is stronger in larger cities. Ultimately, this paper provides useful information for the scientific implementation of carbon emission reduction plans in the field of residents' living and the improvement of the long-term mechanism of pilot cities with both quality and quantity guaranteed. • Low-carbon pilot cities (LCPCs) induce residents to make low-carbon choices. • LCPCs have reduced living carbon emissions by approximately 15.3%. • LCPCs can coexist with other policies to achieve CO 2 reduction. • The mechanisms are mainly green consciousness and green habits. [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]

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]

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]

China has proposed its ambitious cap targets of carbon emissions in both carbon intensity (CO 2 emissions per unit of GDP) and carbon scale (gross carbon emissions). Since mining sector is the foundation of the whole industrial production as well as a carbon intensive sector, it is critical to uncover the key driving factors on inducing corresponding carbon emissions so that appropriate mitigation policies can be raised. Under such a circumstance, this paper aims to fill such a research gap by employing a novel index decomposition method, namely, Generalized Divisia Index Method (GDIM), so that the driving factors of energy-related carbon emissions changes in China’s mining sector and its five sub-sectors over the period of 1999–2013 can be identified. In addition, a scenario analysis approach is applied in order to seek the feasible mitigation pathways on China’s mining sector and its five sub-sectors. The results indicate that output scale effect is the primary contributor of the increase in carbon emissions of both mining sector and its five sub-sectors and energy use effect also plays a positive role, while carbon intensity effect contributes most to the decrease in carbon emissions. All sub-sectors have achieved the target of 45% carbon intensity reduction except the extraction industry of petroleum and natural gas. Nevertheless, more efforts should be made for the whole mining sector in order to achieve the 2030 peak target of carbon scale. [ABSTRACT FROM AUTHOR]

In this paper, we identify the causal effects of the industrial transfer policy (ITP) on carbon emissions. Specifically, we treat the demonstration zones of undertaking industrial transfer in China as a quasi-natural experiment and evaluation its carbon mitigation effects using the difference-in-differences (DID) and matching DID strategies. Our findings suggest that the ITP exerts a significant negative impact on carbon emissions. In particular, both the DID and matching DID estimates indicate that the ITP leads to mitigate carbon emissions by approximately 4.9 and 4.7 million tons, respectively. We also investigate the heterogeneous carbon mitigation effects of the ITP. Moreover, various checks and falsification tests are also presented to confirm the causal effects, including the placebo test, concurrent events test, alternative measures of the ITP and carbon emissions, alternative estimation method and matching technique. The results indicate that our key conclusion, the carbon mitigation effect of the ITP is robust. These results indicate that policymakers should seize the carbon mitigation dividend of the ITP to achieve the goal of carbon neutrality. Policymakers should also reduce the regional development differences, improve the level of opening to the outside world, strengthen the construction of green demonstration zones for industrial transfer to mitigate carbon emissions. • The carbon mitigation effects of the demonstration zones of undertaking industrial transfer in China are investigated. • The industrial transfer policy leads to mitigate carbon emissions by approximately 4.7 million tons. • The heterogeneous carbon mitigation effects of the industrial transfer policy are examined. • The results are supported by robustness and falsification checks. [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]

[Display omitted] • China's agricultural carbon emission performance (ACEP) has greatly improved. • Technological progress promotes ACEP, but efficiency changes does little. • China's ACEP has an aggregation effect, provinces with lower ACEP are catching up. • China's ACEP is converging and growing at the same time. • China's ACEP will increase further in terms of spatial scope and temporal trends. The spatial characteristics of carbon emissions form the basis for exploring carbon neutrality measures for different regions. As the second largest carbon emission source globally, agricultural carbon emissions should not be ignored. This paper used panel data from 2009 to 2019 to calculate the agricultural carbon emissions of 30 provinces in China, and used the ML index, spatial Morans'I index and three convergence indices to analyze the dynamic changes and spatial pattern of China's agricultural carbon emission performance (ACEP). The results showed that: (i), China's ACEP has increased by 1.5% from 2009 to 2019, following a spatial pattern of eastern (1.041) > western (1.020) > central (0.974);(ii) the contribution of technological progress to China's ACEP was 1.035, exceeding 1, and thus indicating that technological progress can improve ACEP, while the contribution of efficiency changes was only 0.991; (iii) China's ACEP has exhibited a spatial aggregation effect over the last 10 years (P < 0.05), but the value of Moran's I index dropped from 0.265 in 2009 to 0.202 in 2019, which indicates that the spatial aggregation of ACEP is weakening; and (iv) the ML index for 30 provinces in China showed σ convergence, which indicates that the ACEP is improving, while there is absolute β convergence and conditional β convergence, which indicates a "catch-up effect" among regions. The results indicate that China's ACEP is likely to increase further in terms of spatial scope and temporal trends. [ABSTRACT FROM AUTHOR]

• It evaluates the effect of China's ETS on non-fossil energy development. • It analyzes ETS's effects from energy type, pilot, and pilot-energy type aspects. • The ETS has the most significant promoting effect on hydropower and photovoltaics. • Carbon price plays a positive role in moderating the effect of China's ETS. Emissions Trading Scheme (ETS) can internalize the environmental costs of fossil energy consumption and encourage enterprises to consume non-fossil energy, which is crucial for People's Republic of China (PRC) to achieve the contribution target of the Paris Agreement cost-effectively. However, whether the ETS in PRC can promote non-fossil energy development remains to be answered. This paper uses a difference-in-differences model to evaluate the effect of the ETS on non-fossil energy development in PRC. Using provincial monthly panel data from January 2004 to December 2019, we find that (1) the ETS has significantly promoted non-fossil energy development in PRC, increasing the monthly average share of non-fossil energy power generation in total power generation by 2.326 percentage points, which has been verified by a series of robustness tests. (2) The effect of the ETS on non-fossil energy development is heterogeneous by energy type, pilot region, and pilot-energy type. The ETS has significantly increased the share of hydropower and photovoltaic power generation, and has significantly promoted non-fossil energy development in Guangdong; meanwhile, the ETS has significantly increased the share of hydropower and nuclear power in Guangdong, and the share of wind power and photovoltaic power in Hubei. (3) The higher the carbon price, the greater the role of the ETS in promoting non fossil energy development. [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]

This study examines the relationship between urbanization, economic growth, industrial transformation, technological change, public services, demographical change, urban and natural environmental changes, and carbon emissions using a dataset of 182 prefecture-level cities in China between 2001 and 2010. Specifically, this paper differs from previous studies in two aspects. First, the extant literature has focused on how economic processes accompanying rapid urbanization affect carbon emissions in urban areas but gives little attention to the other dimensions of urbanization, including social and environmental changes, which may have important effects on carbon emissions. We assessed the effects of 17 key processes accompanying urbanization in a full range of economic, social, and environmental dimensions on carbon dioxide emissions in urban areas. The results showed that social processes accompanied with rapid urbanization had distinct effects on carbon emissions, compared to economic and environmental processes. Specifically, improvement in public services, indicated by education and cultural developments, reduces the increase in carbon emissions during urbanization, while economic growth and urban construction reinforces the growth in carbon emissions. Second, we examined the impact of various urbanization processes on carbon dioxide emissions using a unique dataset of 182 prefecture-level cities that covers a wide span of regions in China. The results of our analyses on the city level have important implications for the formulation of comprehensive policies aimed at reducing carbon dioxide emission in urban areas, focusing on different urbanization processes in economic, social, and environmental phases. [ABSTRACT FROM AUTHOR]

China is a large agricultural country with a high level of agricultural carbon emissions. Whether market prices can be used in agricultural production as a means of agricultural carbon emissions reduction is of great significance to improve the allocation of agricultural production factors and expand large-scale production. This paper applies an autoregressive distributed lag–pooled mean group(ARDL–PMG) model to evaluate the relationship between agricultural production factor prices, food consumption prices, and agricultural carbon emissions, using Chinese provincial panel data from 1994 to 2018. The results show that agricultural carbon emissions and agricultural production factor prices show environmental Kuznets curve (EKC) characteristics; agricultural carbon emissions and food prices show a U-shaped curve; and agricultural production factors are positively correlated with food price in both directions in the long-term. The results of Granger causality tests show that price is the cause of agricultural carbon emissions; the price of agricultural production factors and the price of food consumption are mutually causal. Such results have implications for price, agriculture, and environmental policies. The analysis implies that the market price can be applied to agricultural carbon reduction, which will help policymakers to implement effective price policies in order to reduce agricultural carbon emissions. One implication is that promoting the marketization of agricultural production factors and reducing price distortions will be conducive to carbon emissions reduction in agriculture, which in turn will increase food consumption prices. Therefore, subsidies are needed at the consumption end, which will eventually achieve further carbon emissions reduction at the production and consumption ends. [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]

Considering the enlarging inter-provincial disparities in China as regards carbon emissions and carbon intensity (carbon emissions per unit gross domestic product), this paper is the first study to investigate the inter-provincial carbon imbalance by constructing and employing the Kaya-Zenga index. We use China's panel data of provincial-level carbon emissions over 1995–2016 to quantitatively measure the levels of inter-provincial imbalance and polarization in carbon emissions and carbon intensity. Further, we decompose the Kaya-Zenga index into different contributing factors both regionally and structurally and perform a scenario analysis to identify the corresponding regionally differentiated countermeasures regarding carbon emission reduction. The results show that the imbalance in carbon emissions is mainly caused by imbalances in population scale and income level, while the imbalance in carbon intensity predominantly results from imbalances in energy efficiency and energy mix. In addition, for heavy manufacturing provinces, the respective emission-reduction strategy should aim at lowering energy intensity through local technology improvement and inter-regional technology transfer. For light manufacturing and high technology provinces, carbon emission reduction is harder to be achieved; however, a mix of policies of improving energy efficiency, optimizing energy mix, and industrial upgrading should be implemented. The results of the scenario analysis indicate that reducing imbalance in carbon intensity under different scenarios can lead to a substantial reduction in carbon emissions (up to 10%). • We investigate the inter-provincial carbon imbalance within China. • We construct the Kaya-Zenga index and decompose the index into four contributors. • We use a panel data set of 30 provincial-level regions in China over 1995–2016. • Carbon imbalance is mainly caused by imbalances in population and energy efficiency. • Reducing intra-group imbalance in carbon intensity can abate carbon emissions. [ABSTRACT FROM AUTHOR]

China has promised large cuts in CO2 emissions by 2020, which is likely to have differential effects across regions. We know little about the regional effects of pollution reduction. We make a contribution to filling this gap using a small theoretical model with two regions, features of the Chinese economy and the right to emit CO2 as a factor of production. We find regionally differentiated effects on income, welfare and output and explore government policies designed to reduce these effects. The effects of fiscal policies depend crucially on whether one or both regions respond and on whether output or welfare is targeted. Boosts to productive capacity do better in terms of output but not welfare. [ABSTRACT FROM AUTHOR]