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This paper uses the exogenous shock of China's formal implementation of the environmental information disclosure system in 2008 to construct a quasi-natural experiment. Based on the panel data of prefecture-level cities from 2003 to 2019, the propensity score matching and difference in difference (PSM-DID) approach was used to systematically evaluate the impact of environmental information disclosure on energy efficiency. Overcoming the difficulties in measuring environmental information disclosure and the endogenous problem, this paper investigates the energy-saving effect of environmental information disclosure and illustrates its mechanism for the first time. The results show that environmental information disclosure significantly improved energy efficiency, and public participation played an important role in energy conservation, a conclusion that remained true after a series of robustness tests. The test of the impact mechanism shows that environmental information disclosure can achieve the goal of improving energy efficiency by promoting industrial structure upgrading and technological innovation. This paper enriches the discussion on the relationship between environmental information disclosure and energy efficiency, and provides useful policy inspiration for improving the level of energy efficiency and achieving sustainable economic development. [ABSTRACT FROM AUTHOR]

Green consumption has become an important part of an environmentally friendly society. Policy guidance can effectively promote green consumption. Green consumption policies are extensive because of the diversity of green consumption objects. However, the various objects are not completely isolated, and policy must have a certain level of consistency. Therefore, from the perspective of green consumption objects, this paper first uses the text mining method to mine 308 green consumption policies in China, analyzing the objects covered in China's green consumption policies. Then, the evaluation system of green consumption policy consistency was built, seven key policies were selected, and the PMC-index method was used to measure policy consistency. The results show that (i) the main objectives of China's green consumption policy are the promotion of green products and the efficient use of energy. Green services and green recycling have been subject to fewer policy efforts. (ii) In terms of the links involved in green consumption, China pays more attention to the supply and the consumption chain and less attention to the recycling chain. (iii) The quantitative evaluation results of the seven typical policies show that the policy consistency is good but not perfect. The policy shortcomings are mainly reflected in the incentive methods. Therefore, it is recommended to further improve the green consumption objectives and enrich the means and methods of green consumption guidance. [ABSTRACT FROM AUTHOR]

China's green financial pilot policies (GFPPs) are an important start to build a green financial system in China. It is also an important part of achieving the "dual-carbon" goal. This paper calculates China's total factor energy efficiency (TFEE), analyzes the impact of GFPPs on TFEE, and explores the conduction mechanism. The results show that the relationship between GFPPs and TFEE in the pilot areas is statistically significant. The GFPP mainly improves the TFEE through the green innovation effect and the optimization of the energy structure. The GFPP has a significant effect on TFEE enhancement in eastern coastal cities, non-old traditional industrial cities, and non-resource-based cities with high initial energy. China should continue to deepen the pilot work of green finance, formulate differentiated green finance policies, and ensure green technology innovation. This study provides empirical evidence for further optimization of green finance and energy efficiency. [ABSTRACT FROM AUTHOR]

The platform economy is growing fast in the world. Its expansion, exemplified by industry giants like Amazon, Airbnb, and Uber, is reshaping societal lifestyles and commercial businesses. However, its environmental impacts are uncertain. Currently, the relationship between electronic commerce (e‐commerce) activities and environmental pollution has attracted a lot of attention. This paper attempts to construct a comprehensive theoretical model to investigate the nexus between e‐commerce and regional environmental pollution, with a particular focus on the effects of air pollution and waste pollution. Fixed effect models and China's provincial data during the period from 2008 to 2018 are employed to examine the roles of energy efficiency and resource consumption in such a nexus. The findings suggest that the development of e‐commerce is linked to a reduction in regional air pollution through the channel of improving transportation energy efficiency. The results also show that e‐commerce is associated with an increase in regional waste pollution due to the mechanism of resource consumption in the express packaging industry. As a result, the relationship between e‐commerce and environmental pollution is quite complex at the regional level, transcending a binary distinction of solely positive or negative impacts. This paper contributes to a better understanding of the complex environmental impacts of e‐commerce and helps governments design more efficient and targeted policies to reduce regional pollution. [ABSTRACT FROM AUTHOR]

• A distribution dynamics approach is employed to examine the converge of TFEE across Chinese PAA level cities. • The findings show a clear convergence in TFEE. • Convergence comes more from efficiency drops in high TFEE cities than from efficiency gains in low TFEE cities. • The environmental protection polices in key cities improved energy efficiency. • Large-sized cities show better performance in energy efficiency than small- and medium-sized cities. Improving energy efficiency is considered the most direct route to reducing carbon emissions on a massive scale. To examine the long-run trend of China's energy efficiency, this paper employs a distribution dynamics approach to analyze the convergence of total-factor energy efficiency (TFEE) across 286 Chinese cities between 2002 and 2014. The result suggests the existence of convergence, which comes more from the efficiency declines in the high TFEE cities rather than the efficiency gains in the low TFEE cities. Despite the fact that a few cities have performed well in energy efficiency, the majority of cities have converged to a low-efficiency point. Further analyses show that the inefficiency was attributed to inefficient energy use in small- and medium-sized cities. Our analysis provides strong scientific support for China's ongoing energy conservation and environmental protection policies. [ABSTRACT FROM AUTHOR]

The rapid economic development leads to excessive consumption of fossil energy, resulting in a large number of carbon emissions, which makes the sustainable development of China's economy and society face great challenges. Under the background of global warming and environmental deterioration, developing low-carbon economy has become an inevitable choice for China to change its development model and improve its international competitiveness. Technological progress is the first driving force to promote economic growth. However, the influence degree and mechanism of technological progress on the development of low-carbon economy are still unclear. Based on this, the paper proposes the concept of low-carbon GDP, which is used to measure the low-carbon economic development of 30 Chinese provinces. Then, the panel fixed effect model is used to study the effect degree and mechanism of technological progress on low-carbon GDP and the moderating effect of other factors on the relationship between them. The results show that, first, economically developed provinces and regions have higher per capita low-carbon GDP and low-carbon GDP index, but the speed and quality of low-carbon economic development are not necessarily higher. Second, technological progress can promote the growth of low-carbon GDP and make greater contributions to resources-poor regions. Third, improving local education can make technological progress more effective in low-carbon economic development. China needs to upgrade technological development by developing new and high-tech technologies, promoting new urbanization and strengthening education in order to promote low-carbon economic development. [ABSTRACT FROM AUTHOR]

The improvement of energy-related efficiency has promoted energy-sustainable development in China; however, it may be inhibited by energy poverty. This paper constructs an index system to measure China's energy poverty. Subsequently, we evaluate energy-related efficiency towards SDG7 comprised of energy production efficiency and energy sustainable utilization efficiency using a dynamic two-stage data envelopment analysis model. Furthermore, we adopt fixed effect models to quantify the impact of energy poverty on improving energy-related efficiency and the underlying mechanism. The findings indicate that: (1) China's energy poverty situation gradually improves from 2011 to 2020. The energy-related system's performance is medium due to the poor performance in its energy production stage in 30 provinces during 2011–2020. Energy-related efficiency is greater in areas with a higher response to SDG7. (2) The impact of energy poverty on improving energy-related efficiency is significantly negative. Addressing energy poverty significantly improves energy-related efficiency in regions characterized by a high energy poverty index and low energy-related efficiency. However, it bears no impact in regions with a low energy poverty index and high energy-related efficiency. (3) The moderating effect of technological innovation effectively improves energy-related efficiency, whereas the marketization level has an inverse effect. Consequently, this paper suggests several policy implications. • Use principal component analysis to measure energy poverty in China. • Evaluate the energy-related system towards SDG7 using a dynamic two-stage DEA model. • Investigate the role of energy poverty in improving energy-related efficiency. • Clarify the moderating effects of technological innovation and marketization level. [ABSTRACT FROM AUTHOR]

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]

The time-varying dynamics of the transition to renewable energy reflect the effectiveness and efficiency of energy policy. This paper investigates renewable energy transition behavior in China using Markov regime-switching models. Two distinct phases, expansion and contraction, are identified based on the growth rates of renewable energy consumption share. We find that since China started its new-energy national strategy in 2005, there has been an extended period in which it has been in the expansion state, although it occasionally reverts to a contraction state. Intriguingly, we uncover that the timing of transition state changes can be explained by the changes in policy-related, market-based instruments and risk-related indexes. These findings present implications for policymakers in developing more precise and effective policies, that drives investment choices to align with the goal of a sustainable energy system. [Display omitted] [ABSTRACT FROM AUTHOR]

In China, the total energy consumption and greenhouse gas (GHG) emissions will reach considerable levels based on the current speed of urban rail transit system development. Based on the life-cycle assessment theory, this research constructs an urban rail transit system GHG emission assessment method, calculates emission outputs based on resource inputs from actual investigated data and makes a quantitative analysis of GHG emissions. The results show that in recent years, the GHG emission of urban rail transit construction and operation in China is between 2000 × 104 and 4200 × 104 tonnes of carbon dioxide equivalent (tCO2e) per year. The proportions of the construction and operational phases in this emission are 57 and 43%, respectively. In the construction phase, the GHG emission intensity per unit mileage of shield tunnels and per unit area of stations is about 1.3 × 104 tCO2e/km and 3.71 × 104 tCO2e/ha, respectively. In the operational phase, the GHG emission intensity per unit trip is 0.084 kg carbon dioxide equivalent/passenger-km. The entire life-cycle GHG emission per kilometre of urban rail transit systems is 11.69 × 104 tCO2e (with a service life of 50 years) in China. The construction phase and operation phase generated about 18.73 and 81.27% of this emission, respectively. The preliminary conclusions of this study may help shed light on the emission reduction potential of urban rail transit systems and the emission reduction targets in China. [ABSTRACT FROM AUTHOR]

This study aims to analysis the influence of economic growth (EG) and energy consumption (EC) on sulfur dioxide emissions (SE) in China. Accordingly, this study explores the link between EG, EC, and SE for 30 provinces in China over the span of 2000e2019. This study also analyzes cross-sectional dependence tests, panel unit root tests, Westerlund panel cointegration tests, Dumitrescu-Hurlin (D-H) causality tests. According to the test results, there is an inverted U-shaped association between EG and SE, and the assumption of the Environmental Kuznets Curve (EKC) is verified. The signs of EG and EC in the fixed effect (FE) and random effect (RE) methods are in line with those in the dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS) and autoregressive distributed lag (ARDL) estimators. Moreover, the results verified that EC can obviously positive impact the SE. To reduce SE in China, government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency. This requires the comprehensive use of policies, regulations, economic incentives, and public participation to promote sustainable development. [ABSTRACT FROM AUTHOR]

This paper focuses on energy poverty dynamics by answering one question: Does energy poverty trap exist in Chinese cities? For this purpose, we examine the co-evolution between per capita energy consumption and income for 286 prefectural-and-above level cities in China over the period 2002 to 2014. A nonparametric joint-distribution dynamics approach is employed in the analysis. Both static and dynamic distribution analyses demonstrate significant evidence of club convergence in energy consumption across Chinese cities, and there are multiple equilibria between per capita energy consumption and income in the long-run distribution. The results also suggest that considerable cities fall into energy poverty trap, a chronic state with low income and low energy consumption. Therefore, we can argue that energy poverty is not a transitory state for those cities and support the existence of energy poverty trap in China. Our findings highlight the need to tailor policies aimed at reducing energy poverty in low-income cities. • We examine the co-evolution between per capita energy consumption and income in China. • A dataset of China's 286 prefecture-level cities during 2002–2014 is explored. • The results argue club convergence in energy consumption across Chinese cities. • Considerable cities fall into energy poverty trap. • The study supports the existence of energy poverty trap in China. [ABSTRACT FROM AUTHOR]

This paper investigates the long-term butterfly effect of cloud computing on the low-carbon economy against the dual backdrop of the digital age and carbon neutrality. Utilizing a full-sample and sub-sample approach, the study identifies the complex interrelationship between the China Cloud Computing Index (CCI) and the Low Carbon Index (LCI). The quantitative examination reveals how CCI impacts LCI – both favorably and unfavorably. The positive effects suggest that cloud computing serves as a motivator in the environmentally friendly economy. In case of negative impacts, however, it is not possible to always determine the incentive effects owing to the large amounts of energy consumption generated by cloud computing data centers. Meanwhile, the positive influence of LCI on CCI indicates how the pursuit of low carbon-economy (as a goal) will bring opportunities for the explosive growth of the cloud computing industry. Cloud computing has increasingly prompted the fluctuation of carbon emissions in the whole ecosystem. By exploring this butterfly effect, this study digs deeper into the complex interrelationship between the discussed indexes. It is expected that the study outcomes will offer meaningful recommendations for the two main vectors of economic development - greenization and digitalization. • Discover the butterfly effect of cloud computing on the low carbon economy. • Using full-sample and sub-sample methodologies, this study identifies the interrelationships between Cloud Computing Index and Low Carbon Index [ABSTRACT FROM AUTHOR]

With the growing share of the climate-sensitive renewable energy market supply in China, estimating future energy drought risk (ED) is essential. In this paper, based on CMIP6, energy demand and power generation are estimated from 2023 to 2100 under SSP2-4.5 and SSP5-8.5 climate scenarios, and ED is defined from high demand (HD), low wind-solar generation (LWS), and residual load (RL). The results show that the ED exacerbation is relatively high under the SSP5-8.5. Between 2023 and 2100, the duration and severity of HD and RL notably increase, while LWS changes are relatively weak. We find that HD and RL exhibit high summer risks in the south and high winter risk in the north. The return periods vary significantly and extends over time in most regions. Moreover, there are few ED when the installed power generation capacity (IPGC) is increased. When the IPGC increases by 2%–5%, the LWS will decrease at least 20%–72%. With a 10% increase, the LWS will be mitigated by at least 80%, whereas the mitigation for RL is limited, approximately 3–17% at different rates. This work performs the first evaluation of future ED and provides the useful references for risk mitigation in China based on CMIP6. [ABSTRACT FROM AUTHOR]

As a result of the "Belt and Road" and "Going Global" policies, a growing number of Chinese power companies are expanding overseas, implementing global development strategies, and making investments in the overseas power industry. Several countries are undergoing an energy transition because of the rapid development of the world economy. This is being done to address the climate change issues that are a result of the overuse of fossil fuels. Brazil is also accelerating its pace of power transformation in its position as a major power generating country in Latin America. In addition to being the largest economy in South America, Brazil is also the country in which China has made the most investments. Additionally, Brazil is increasing its development efforts in wind power, photovoltaics, and other renewable energy sources in response to a large demand for renewable energy sources. Brazil's renewable energy sector offers a great deal of potential for investment based on solid foundations for cooperation between China and Brazil. The Grey Prediction Model was used for this research to forecast Brazil's renewable energy generation installed capacity, and the results show a positive trend in Brazil's renewable energy generation. There is a rapid growth in wind and photovoltaic power generation over the next 5 years, with growth rates reaching 50.39% and 182.99%, respectively, suggesting that there is potential for a broad range of development. Following this, the research applies factor analysis to assess investment risks associated with Brazil's renewable energy sector from 2000 to 2020. Based on the results of the study, Chinese power companies investing in Brazil's renewable energy sector face the greatest political risk, while other risks gradually decrease. To avoid political risks when investing, companies should place a high priority on preventing them. [ABSTRACT FROM AUTHOR]

Different from the previous studies that mainly focus on the environmental and economic benefits of the total R&D, we specifically focus on the R&D activities in the energy field, namely, energy-saving R&D in this study, and explored the spatial impacts of energy-saving R&D on urban carbon emission performance and its internal transmission mechanisms for the first time. The heterogeneity analysis from the perspectives of different-types of R&D and different urban groups were also conducted. Results indicate that: Energy-saving R&D has obvious promoting effect on the improvement of urban carbon emission performance, among which the utility-type energy-saving R&D plays a more important role than the invention-type R&D. Energy-saving R&D promotes urban carbon performance mainly through the transmission mechanism of technical effects, while structural effect and urbanization effect negatively affects carbon emission performance due to the existence of energy rebound. Furthermore, there exists significant spatial spillover effects of energy-saving R&D on urban carbon emission performance, and economic factors play a more important role in this spatial effect. In addition, the impact of energy-saving R&D on carbon emission performance has obvious urban group heterogeneity. Finally, we proposed several policy suggestions based on the main conclusions of this study. [ABSTRACT FROM AUTHOR]

Energy use between urban and rural areas is very important in the context of the global energy transition and climate change. However, it is difficult to measure the differences and inequalities in energy consumption due to data limitations. In this paper, a dataset distinguishing urban-rural energy consumption has been generated. We construct an energy inequality index (EI) to assess the difference in per capita energy consumption (PEC) between urban and rural areas. We find that the EI has decreased significantly from 10.42 in 2000 to 1.43 in 2020. Western China has a higher EI than the developed coastal areas. We further define 7 urban-rural types and find that the urban center has the highest PEC, while the rural cluster has the lowest. Cluster analysis shows that prefectures have different equalization trends, namely volatile decline, rapid decline, increase before decline, incremental decline. The urban-rural structure plays an important role in the different trends, and 4 modes of urban-rural energy consumption are summarized, namely urban-centered, urban-suburban double-centered, multi-centered and rural-biased. These results are valuable for understanding the energy consumption between urban and rural China. • A dataset distinguishing urban-rural per capita energy consumption (PEC) has been generated. • China's urban-rural energy inequality has decreased from 10.42 in 2000 to 1.43 in 2020. • Western China are facing a more urban-rural energy inequality than the developed coastal areas. • Among the 7 defined types, urban center ranked highest PEC, while rural cluster ranked lowest. • 4 modes of urban-rural energy consumption are summarized. [ABSTRACT FROM AUTHOR]

In this era of global warming the importance of climate risk cannot be understated, and finding ways to reduce climate risk is a topic worthy of study. In this paper, we innovatively examine the role of renewable energy technology innovation on climate risk in China. In addition to their linear relationship, we also investigate the asymmetric and heterogeneous impact, detect the impact channels, and find that (1) increased renewable energy technology innovation can effectively alleviate the climate risk situation. Accordingly, the development of renewable energy technology innovation can make a significant contribution to CR abatement. (2) Pronounced impacts of renewable energy technology innovation on climate risk can be observed in the higher quantiles (75th and 90th) of climate risk. (3) Renewable energy technology innovation is a powerful weapon for eradicating climate risk in provinces with a higher level of government fiscal expenditure. And (4) renewable energy technology innovation has an impact on climate risk by facilitating energy consumption efficiency, which is a necessary mediator. These conclusions inspire us to put forward several corresponding policy implications for better climate risk governance and renewable energy technology innovation development. [ABSTRACT FROM AUTHOR]

With the completion of the poverty alleviation task in China, the Chinese economy has made great breakthroughs. Meanwhile, the implementation of Chinese "dual carbon" goal has entered an important window period of both strategic opportunities and difficulties. The emission of carbon dioxide (CO2) leads to the greenhouse effect, which affects the sustainable development of society. Therefore, this paper proposes an improved analytic hierarchy process (AHP) with Slacks-based measure integrating data envelopment analysis (SBMDEA) (AHP-SBMDEA) based efficiency evaluation model for different provincial-level administrative regions in China, which is used to analyze and optimize the Chinese energy structure of different provincial-level administrative regions. With coal, gasoline, petroleum, fuel oil, diesel, crude oil and natural gas as inputs, the per capita Gross Domestic Product (GDP) as the desired output and the CO2 as the undesired output, after linear weighted calculation of the results of the AHP-SP model and the SBMDEA model, the energy efficiency evaluation model of different provincial administrative regions in China is established. The results show that there is a large difference in efficiency between Chinese northern and southern regions, and the overall efficiency of southern regions is higher than that of northern regions. In addition, it is easier to find out the optimal energy efficiency benchmark, which can provide suggestions and help to guide the energy consumption input structure improvement of other inefficient provincial-level administrative regions. Furthermore, the energy structure can also be adjusted through the redundant variable calculated by the SBMDEA model. For example, Sichuan Province can reduce the consumption of the coal, the gasoline, the diesel, the fuel oil, the crude oil and the natural gas by 5269.95 × 10000 tons (WT), 513.01 WT, 59.05 WT, 34.37 WT, 4,73.33 WT and 130.37 billion cubic meters (BCM), respectively. Its CO2 emissions can be reduced by 1925.4 WT, and raise the efficiency of energy utilization in the province. [Display omitted] • Novel economy and CO 2 emissions evolution model based on a AHP-SBMDEA is proposed. • The proposed model can identify the optimal energy efficiency benchmark. • GDP per capita can be increased and CO 2 emissions can be decreased. [ABSTRACT FROM AUTHOR]

This paper constructs a carbon quota allocation index that takes into account equity, efficiency and ecological construction, and calculates carbon emissions and energy consumption data in important periods based on the expected carbon emission targets and economic and social development indicators of the Chinese government. Based on the calculated carbon emissions, the zero-sum game data Envelopment model (ZSG-DEA) is used to discuss the initial allocation of regional quotas and the optimal carbon quota scheme. The results show that:(1) there is a large gap between the optimal carbon quota and the initial carbon quota allocation in Shandong, Guangdong, Jiangsu and other provinces in 2025, and the implementation of emission reduction measures should be accelerated. (2) By 2030, the final allocation of Beijing, Tianjin, Inner Mongolia, Qinghai, Shanghai, Ningxia, Liaoning and Xinjiang will be positive. The provinces with negative final allocation should carry out the work of carbon peak as soon as possible to avoid increasing the pressure of emission reduction in the future. (3) The central region faces greater pressure of emission reduction, while the western region can accept the transfer of carbon emissions from other regions over time. The research conclusions have important policy implications for establishing a fair and effective carbon quota allocation mechanism, achieving the national total carbon emission control target, stimulating the vitality of the unified carbon market, and promoting regional coordinated emission reduction. • There exist differences in carbon quota allocation among provinces in the future. • There are changes in the initial and optimal carbon quotas obtained by each province. • The role of carbon emissions between regions is changing over time. [ABSTRACT FROM AUTHOR]

The development of a city's green infrastructure is increasingly being driven by low-carbon innovation (LCI). However, knowledge of how LCI affects green economic efficiency (GEE) in China is largely unknown. This study investigates the spatial effects of LCI on GEE in 285 Chinese prefecture-level cities. The empirical findings show that LCI exerts significant beneficial effects on its GEE but negative effects on its neighbors. The positive direct effects on GEE are offset by negative indirect effects due to the lack of spatial linkage effect and the existence of the siphon and crowding-out effects among cities. Using a mediating effect model, we have identified three channels of LCI that affect GEE: industrial structure, energy consumption structure, and human capital. A further heterogeneity analysis indicates that the impacts of LCI on GEE differ by region and city development level. Furthermore, LCI in the building, greenhouse gas treatment, transportation, and sewage and pollutant treatment categories could greatly enhance local GEE. The findings herein provide an empirical experience for accurately accessing the spatial effect of LCI on GEE, and offer a critical decision-making reference for implementing a cross-city green linkage development mechanism. [ABSTRACT FROM AUTHOR]

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In recent years, there has been a notable increase in the consumption of fossil energy, leading to a significant rise in environmental pollution, particularly in China due to its rapid development. This has resulted in the frequent occurrence of large‐scale fog and haze weather, highlighting the urgent need for environmental protection measures. To gain insights into the atmospheric conditions in China, an analysis was conducted on the wet deposition of polycyclic aromatic hydrocarbons (PAHs) in a remote region of Central South China from 2014 to 2017. The study revealed that the average concentrations and peak values of Ʃ16PAHs in 2014 and 2015 were considerably higher than those observed in 2016 and 2017. Furthermore, it was found that five‐ring PAH species were the predominant components during 2014 and 2015, indicating a shift in the main sources of PAHs. The peaks of Ʃ16PAHs were predominantly detected in samples collected during light rain in the winter, specifically on days without heavy rainfall. This can be attributed to the absence of heavy rain, which would otherwise reduce the concentration of air pollutants. Consequently, contaminants accumulated in the air are easily enriched in rainwater. The concentrations of Ʃ15Alkyl‐PAHs also exhibited a significant correlation with the number of rainfall days. Notably, a much higher annual average concentration of Ʃ15Alkyl‐PAHs was observed in 2017, which experienced fewer rainfall days. Coal combustion, petroleum sources, and vehicular emissions accounted for 58%, 12%, and 30% of the PAHs in the air, respectively. Despite improvements in air quality in China since 2016, it is crucial to address the elevated concentrations of PAHs in the atmosphere, particularly under adverse meteorological conditions characterized by reduced rainfall. [ABSTRACT FROM AUTHOR]

As a result of high energy consumption and pollution from energy-intensive industries, the Chinese government has implemented a series of policies. A comprehensive assessment of these policies is necessary to guide the green transformation and upgrading of the industry, however, little research has been conducted on this issue. This article takes China's economic policy uncertainty (EPU) Index as a comprehensive and continuous policy shock and investigates the impact of EPU on the financial performance of energy-intensive firms. Based on 289 listed energy-intensive companies from 2003 to 2018, we find that EPU negatively affects the financial performance of firms, and the negative effect is robust after replacing the dependent variable and endogenous discussion. Further, the negative impacts are more pronounced for midwestern, non-SOE firms, as well as ferrous metal and chemical product manufacturers. Moreover, our results indicate that the negative impact of EPU on performance is mitigated for firms with high cash holdings and low debt ratios. [ABSTRACT FROM AUTHOR]

The ambitious targets of peaking CO2 emissions before 2030 and reaching carbon neutrality before 2060 (Goal 3060) have emerged as the driving force in the development of China's low-carbon energy policy. Adopting a systematic review approach, this article provides a timely analysis of key Chinese renewable energy and energy efficiency policies under Goal 3060 across five sectors: electricity, industry, transportation, buildings, and local governments. In addition, the review identifies challenges to be addressed and offers policy recommendations. There are five main conclusions: (1) expedite the development of market-based and network-based governance systems; (2) pursue the harmonization of policies by avoiding contradiction and fragmentation; (3) develop new policies, especially in the building and transportation sectors; (4) embrace surveillance technologies to improve implementation and compliance; and (5) ensure just transition by implementing policy to reduce the negative socioeconomic impacts on fossil fuels-based communities and workers. This review serves as a useful guide for scholars interested in China's clean and low-carbon energy transition. [ABSTRACT FROM AUTHOR]

Identifying the research topics of China's energy transition policy and predicting future research trends are crucial for policymakers to make informed decisions and advance the energy transition. This study applied the Latent Dirichlet Allocation (LDA) to extract 26 major research topics from the 13,976 abstracts of Chinese policy research papers in web of science (WOS), conceptualized the five most popular topics and used the ARIMA model to predict trends over the next 36 months. The results show that except for Economic and Environmental Impact of Renewable Energy Consumption (Topic13), which will first experience unanticipated fluctuations and then show strong growth capacity, all other topics will continue to remain positive growth trend. Research and Development (Topic3) is driven by the urgency of China's energy transformation. Economic and Environmental Impact of Renewable Energy Consumption (Topic13) is driven by the potential for the development of renewable energy. Economic Impact of Climate Change (Topic26) is driven by the climate change debate. Economic Growth, Urbanization, and Energy Consumption (Topic7) is driven by a discussion of their relationship and the mechanisms influencing them. Regional Efficiency and Productivity Analysis (Topic19) is driven by regional differences in China's energy policies. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is vital for addressing climate change and reducing carbon emissions in emerging economies. Financial development (FD) is crucial for economic growth, and its environmental impact and the adjustment of the industrial structure (IND) is a crucial lever in China's economic transition period. This study explored the relationship between FD, IND, and China's green total factor productivity (GTFEE) from 2000 to 2020 using the super-efficiency SBM-undesirable model, which estimates China's GTFEE. The ARDL results suggest that FD and IND enhance GTFEE in the long term, with FD promoting GTFEE by facilitating industrial structure adjustments. The Dumitrescu–Hurlin panel causality tests supported this finding. The QRPD panel quantile regression and heterogeneity analysis revealed significant heterogeneity in the effects. With increasing GTFEE, FD exerts a restraining effect, gradually weakening and transitioning into a promoting effect, while the IND consistently plays a promoting role. [ABSTRACT FROM AUTHOR]

China is the largest CO2 emitter in the world and announced that carbon peak and neutral targets will be achieved before 2030 and 2060, respectively. A retrospective analysis of past CO2 emissions and their drivers is important for the actions of peaking CO2 emissions before 2030 in China. CO2 emissions from energy use (coal, oil, and natural gas) and cement production from 2000 to 2020 were calculated first, and their drivers were decomposed into economic and population growth, energy intensity, and emission coefficient by logarithmic mean Divisa index (LMDI) analysis in this study. China's CO2 emissions increased nearly threefold from 3385 in 2000 to 10,788 million tonnes (Mt) in 2020, with a decline from 2013 to 2016. Coal was the major emission sector contributing more than 70% in most years, while natural gas emissions increased nearly 13 times from 53 to 723 Mt in the two decades, although its contribution only accounted for 6.7% in 2020. Economic growth was the major positive driver, while energy intensity reduction was the major negative driver of the emission increments by year and by the Five Year Plan (FYP). Emission coefficient reduction gradually became important due to its negative effect, especially in the 13th FYP, which offset ~ 30% of the emissions induced by economic growth. The projections of CO2 emissions in 2025, 2030, and 2035 could be 11,596 ± 582, 11,774 ± 621, and 11,401 ± 672 Mt, respectively, suggesting that China's carbon emissions could peak around 2030 with an increment of ~ 1000 Mt on the 2020 levels. Under the sustainable growth of the economy and population, it is possible to reduce the carbon peak value or achieve peak time earlier through the additional reduction of energy intensity and emission coefficient by technological progress and energy alternatives such as non-fossil fuels. [ABSTRACT FROM AUTHOR]

Probing the determinants of energy conservation and decoupling energy use from economic growth in the iron and steel (IS) industry are at the forefront of China's environmental concerns. This study first constructed an extended logarithmic mean divisia index model to estimate determinants of the IS industrial energy consumption. The Tapio approach and decomposed decoupling analysis is further utilized to analyze the decoupling relationship between the industry's total energy use and its value creation as well as the decoupling states of the determinants. Finally, grey Verhulst technique is employed to predict the future trend of decoupling state. Empirical results based on statistical data of the IS industry during 2006–2017 demonstrate that: (1) Regulatory effect and scale effect contribute to energy conservation. Growth effect significantly increases energy consumption while technological effect and structural effect exert unstable impacts on energy use. (2) Weak decoupling states between energy use and value creation are mainly observed during the research period. Structural, technological, regulatory, and scale effects are mainly weak decoupling, while the growth effect is mainly expansionary negative decoupling. (3) A weak decoupling state between the two variables is predicted up to 2030 with the help of grey theory. [ABSTRACT FROM AUTHOR]