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The serious consequences of climate warming have increasingly become a globe agenda in recent decades. China has been actively participating in various initiatives to address global climate change and has made commitments to reduce carbon emissions. Although the logistics industry is regarded as the "new driving force of national economic development", its carbon intensity is relatively high. Therefore, whether the logistics industry can develop in a green and low-carbon way is very crucial. This paper takes the green logistics efficiency of China's provincial logistics industry as the research object. The Super-SBM model is used to measure the China's green logistics efficiency, then the general dynamic characteristics is depicted by kernel density analysis. With the GML (Global Malmquist-Luenberger) index model, the reasons for the changes in green logistics efficiency are explained. Finally, Moran's I index is used to analyze the spatial correlation of green logistics efficiency in each province. The results show that the green logistics efficiency in China is at a low level, but with an upward trend. China's green logistics efficiency has a significant positive spatial correlation, showing a zonal pattern of high in the east and low in the west, and a polarization phenomenon. In addition, the bottleneck of the overall development of green logistics efficiency in China depends on the level of green technology. Furthermore, the results also imply that green technology advancement is an inherent key factor for green logistics efficiency to achieve growth. [ABSTRACT FROM AUTHOR]

As global climate change becomes increasingly severe, energy technology innovation has become a key means of coping with the climate crisis and realizing green and low-carbon development. However, existing literature rarely examines the effects of carbon emission reduction policies based on the perspective of energy technology progress for both short-term economic fluctuations and long-term equilibrium. This paper introduces the fossil energy technology sector and the renewable energy technology sector into the dynamic stochastic general equilibrium (DSGE) model, and compares the effectiveness of the carbon emission cap policy, the fossil energy technology subsidy policy, and the renewable energy technology subsidy policy under the framework of China's carbon trading market in promoting macroeconomic growth and controlling pollutant emissions. We found that in long-term, the emission reduction effect of the carbon emission cap policy falls short of the other two policies, and subsidizing fossil fuel technologies is more cost-efficient comparatively. The government expenditure shock can all stimulate macroeconomic growth with crowding out of private investment and household consumption, whereas the energy technology research productivity shock leads to a decline in total output and an increase in renewable energy technology demand. In addition, pollutant emissions are pro-cyclical under the impact of total carbon policies and counter-cyclical under the impact of energy technology subsidy policies. This article constructs a multi-technology sectoral dynamic stochastic general equilibrium model, expanding the research perspective and theoretical framework for evaluating carbon emission reduction policies. At the same time, it proves the importance of the government to implement the phased energy technology subsidy policy while implementing the carbon emission cap policy, which provides important enlightenment for the implementation and adjustment of carbon emission reduction policy. [ABSTRACT FROM AUTHOR]

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

The problem of global climate change is a common problem faced by all countries, and developing countries will face heavier pressure to reduce carbon emissions while promoting economic development. China is currently in a period of economic transformation, and the contradiction of industrial structure upgrading is becoming more and more prominent. The unreasonable industrial structure has caused a large consumption of resources, hindering the optimal allocation of resources and affecting carbon emissions. Technological innovation is an important force to cope with environmental changes, promote economic growth, and improve comprehensive competitiveness. Can technological innovation achieve carbon emission reduction under industrial structure upgrading? In this paper, industrial structure upgrading, technological innovation, and carbon emissions are studied together, and the impact of industrial structure upgrading, technological innovation on carbon emissions is theoretically analyzed, as well as how industrial structure upgrading acts on carbon emissions through technological innovation. An empirical test is conducted using 30 provincial panel data in China from 2005 to 2017, and it is found that industrial structure upgrading can reduce carbon emissions. An econometric analysis based on the mediating effect model finds that industrial structure upgrading has both a direct carbon emission reduction effect and a mediating effect of reducing carbon emissions through technological innovation, and the mediating effect of technological innovation in reducing carbon emissions remains significant in the regression analysis of sub-regions. Based on the research of this paper, it is suggested that the advanced development of industrial structure should be promoted, the rationalization of industrial structure should be promoted, the innovation development strategy should be firmly implemented, and the level of technological innovation should be promoted. [ABSTRACT FROM AUTHOR]

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

The carbon mitigation response encompasses a variety of strategies aimed at mitigating greenhouse gas emissions resulting from human activities. These measures are crafted to address the challenges posed by climate change and facilitate the transition of businesses towards a low-carbon paradigm. Leveraging the analytical outcomes of the extended STIRPAT model and the PSO-BP prediction model, this paper suggests countermeasures for reducing carbon emissions in China's metal smelting industry. The overarching objective is to contribute to China's attainment of the "dual carbon objectives." The study identifies key factors influencing carbon emissions in the metal smelting industry, ranked in descending order of sensitivity: population, coal consumption, urbanization rate, total metal production, carbon intensity, proportion of secondary industry, and GDP per capita. Results from three established scenarios—namely, low carbon, standard, and high carbon—indicate a consistent decline in carbon emissions from China's metal smelting industry over the next 15 years. This research not only enhances the findings of existing studies on carbon emissions in the metal smelting sector but also introduces an innovative approach to carbon emission reduction within China's metal smelting industry. [ABSTRACT FROM AUTHOR]

China is the largest carbon emitter in the world. Understanding carbon emissions of China, especially at the provincial level, will help identify the critical factors behind carbon emissions and effectively implement carbon emission reduction measures. There are significant achievements in the study of carbon emissions of China's provinces. However, there is a gap for improvement in the study from periods and groups' perspectives using a decomposition-clustering method. This paper adopts the Logarithmic Mean Divisia Index (LMDI) to decompose each province's carbon emissions, introduces the elbow and K-means methods to cluster provinces based on the driving factors of decomposition, and analyzes the driving factors of carbon emissions from the view of groups and periods. By analyzing the carbon emissions data of 28 provinces in China from 1998 to 2018, a breakthrough has been found that economic activities and energy intensity were the main driving factors of carbon emissions. Some possible countermeasures, such as optimizing the industrial structure and the energy structure, significantly increasing clean energy consumption, would receive effective carbon emission reduction feedback. The results provide better decision-making support for emission reduction policies in China and contribute to global climate change issues. [ABSTRACT FROM AUTHOR]

Financial activity plays an important role in the analysis of environmental and ecological implications. Previous research shows that shadow banking activities, informal and less regulated financial activities, have become an important part of financial systems after the 2008 financial crisis. However, the impact of shadow banking activities on carbon dioxide emissions has been ignored in previous research. In this paper, we use the panel annual data of 30 Chinese provinces over the period 2013–2020 to study the effect of shadow banking activities on carbon dioxide emissions. The result shows that shadow banking activities have a positive impact on carbon dioxide emissions, and the result is still robust by using dynamic panel regression with general method of moments (GMM) method. Heterogeneity analysis shows that the impact of shadow banking activities on carbon emissions is more pronounced for the secondary industry, which proves that shadow banking activities support more for environmentally unfriendly businesses. Furthermore, by using difference-in-difference (DiD) method, we examine the causal effect of shadow banking regulation policy on carbon dioxide emission reduction and demonstrate that the shadow banking regulation can reduce carbon dioxide emissions. Our research contributes to environment protection and achieving the goal of low-carbon economy by exploring the role of shadow banking activities and financial regulation in carbon dioxide reduction. [ABSTRACT FROM AUTHOR]

Climate change is a challenge for all of humanity. Should financial be environmentally responsible? This paper uses the Toda–Yamamoto test and the extended Fourier Toda–Yamamoto test re-examine the relationship between financial development and environmental quality in 31 provinces and municipalities in China during the period 2000–2018. We find that financial development in certain regions has effectively reduced the concentration of PM2.5, which indicates that it has a significantly positive effect on environmental quality, though with regional differences. After considering structural shifts, the relationship between financial development and environmental improvement is found to be significant in more regions, indicating that China has undergone structural shifts in these aspects. The aforementioned conclusions are also supported by further robustness tests. China can consequently utilize the positive impact of finance for advocating carbon emission reduction and improving environment quality, therefore contributing to the response to global climate change. [ABSTRACT FROM AUTHOR]

With the statement of Chinese government on energy saving in 2020 at the United Nations General Assembly, carbon neutral was widely spread as a new concept. As a big country, China has the responsibility and obligation to make its own contribution to global climate change. This paper aims to explore and find effective ways for China to achieve carbon neutrality by 2060. We identify the main factors affecting carbon emissions by STIRPAT model; combined with the scenario analysis, we divide the year 2020 to 2060 into three stages: year 2020–2030 is carbon peak stage, year 2030–2050 is rapid emission reduction stage, and year 2050–2060 is complete carbon neutralization stage. At each stage, three development models, high, medium, and low level, were established. There are a total of 27 different scenarios in three stages. A system dynamics model was established to simulate the effects of carbon emission factors and changes in carbon sinks in different scenarios. Finally, 8 paths were found which in line with Chinese current goal of achieving carbon neutrality with treating reach carbon peak in 2030 as an additional filter condition. Comparing per capita GDP levels in different scenarios, we eventually find that keeping economic development at a low level in the first stage, a high level in the second stage, and a medium level in the finally stage, the point where net carbon emissions are less than zero for the first time will appear between year 2056 and 2057. By then, the per capita GDP will reach 144,500 yuan (based on year 2000), nearly four times 2000's. In all, these findings are helpful for policymakers to implement reasonable policies to achieve carbon emission peaking and carbon neutral in China. [ABSTRACT FROM AUTHOR]

The Chinese government has established carbon emissions trading schemes (CETS) to cope with climate change and reduce carbon emissions. This paper uses the multi-period difference in difference (DID) model to explore the impact of CETS on cities' GDP and GDP growth rates in China based on data from 285 prefecture-level cities from 2008–2019. We find that CETS increase the level of GDP by 3.4% and the GDP growth rate by 0.004. The mechanism of increasing GDP includes promoting investment and innovation, and the mechanism of increasing the GDP growth rate includes only promoting the investment growth rate. Thus, CETS satisfy both the weak and strong versions of the Porter Hypothesis from the GDP and growth rate perspectives. In the heterogeneity analysis, we find that the impacts of CETS on cities' GDP and GDP growth rates decrease with the increase of the corresponding dependent variable. In the spatial spillover analysis, we find that the establishment of CETS has a positive spillover effect on the GDP of cities around 50 km and 150 km, and a negative spillover effect on the GDP of cities around 200 km, but there is no spatial spillover effect on the GDP growth rate. [ABSTRACT FROM AUTHOR]

In the context of low-carbon economic development, carbon productivity has effectively integrated the two major objectives of carbon reduction and economic growth, and increasing carbon productivity has become the main approach to address global climate change. Using data from China's input–output table for 2002–2017, this study measures the evolutionary characteristics and influencing factors of carbon productivity from the perspective of embodied carbon emission in China's industrial sector. The results indicate that, first, China's industrial sectors' carbon productivity shows an increasing trend from 25.22 to 65.3 million yuan/10,000 tons of CO2 in 2002–2017, but the overall level is low. The energy efficiency factor is a major element affecting improvement in carbon productivity. Second, the carbon productivity of the 28 industrial sectors shows an increasing trend. There is a significant gap in the carbon productivity between different industrial sectors. The energy efficiency factor in all industrial sectors is positive, indicating that energy efficiency is a positive factor in increasing carbon productivity. Third, from largest to smallest in the carbon productivity are the primary, tertiary, and secondary industries. Finally, this paper recommends several approaches to improve carbon productivity from the perspectives of technology, differentiated policies of carbon emission reduction, and industrial structure adjustment. [ABSTRACT FROM AUTHOR]

The global level of climate change agreement and the extensive development of China's industrialization process have caused China to face severe pressures regarding energy conservation and emission reduction. Tourism industry plays an important role in promoting steady economic growth and improving ecological environment in China. The agglomeration economic effect it produces can reduce carbon emissions, but the crowding effect may not be conducive to low carbon development. Therefore, how to reduce carbon emissions while promoting the development of tourism industry has become an urgent problem. This paper measures the level of tourism industry agglomeration and carbon emission in 30 regions of China and uses the method of spatial econometrics to analyze the impact of tourism industry agglomeration on carbon emissions. The empirical results prove that tourism industry agglomeration can reduce the carbon emissions of local and neighboring regions in China. However, this does not mean that the larger the scale of tourism industry agglomeration, the more conducive to the reduction of carbon emissions. For developed tourism groups, the impact of agglomeration effect on carbon emissions of local and adjacent areas shows a U-shaped relationship. When the agglomeration level exceeds 1.963, the expansion of agglomeration scale will increase local carbon emissions. For underdeveloped tourism areas, there is an inverted U-shaped relationship between agglomeration level and carbon emissions both in local and adjacent areas. When the agglomeration level reaches 1.883, the expansion of agglomeration scale will reduce local carbon emissions. The conclusions provide a basis for Chinese government to guide the low-carbon development of the tourism industry from another perspective. [ABSTRACT FROM AUTHOR]

The anthropogenic emission of carbon dioxide (CO2) into the atmosphere is recognized as the main contributor to global climate change. To date, scientists have developed various strategies, including CO2 utilization technologies, to reduce global carbon emissions. This paper presents the global scientific landscape of the CO2 utilization research from 1995 to 2019 based on a bibliometric analysis of 1875 publications extracted from Web of Science. The findings indicate a major increase in the number of publications and citations received from 2015 to 2019, denoting a fast-emerging research trend. The dynamics of global CO2 utilization research is partly driven by China's policies and research funding to promote low-carbon economic development. Applied Energy is recognized as a core journal in this research topic. The utilization of CO2 is a multidisciplinary topic that has progressed by multidimensional collaborations at the country and organizations levels, while the formation of co-authorship networks at the individual level is mostly influenced by the authors' affiliations. Keyword co-occurrence analysis reveals a rapid evolution in the CO2 utilization strategies from chemical fixation in carbonates and epoxides to pilot-scale testing of power-to-gas technologies in Europe and the USA. The development of efficient power-to-fuel technologies and biological utilization routes (using microalgae and bacteria) will probably be the next research priorities in CO2 utilization research. [ABSTRACT FROM AUTHOR]

Technical change has a pivotal role to play in low-carbon development. Recent research has offered different insights regarding the effect of technical change on CO2 emissions but ignored the bias of technical changes which lead to changes in CO2 emissions. To fill the gap, this paper uses the 2008 to 2015 provincial-level data on China's 22 industrial sub-sectors to investigate both the effect of directed technical change on CO2 emissions and its heterogeneity. We find that the technical change in most industrial sectors in China was capital-biased, although a labor-biased trend was evident. Labor-biased technical change is conducive to CO2 reduction, while capital-biased technical change has the opposite effect. Moreover, this effect is different by developmental periods, industries, and regions. Therefore, we propose that the government promotes labor-biased technical change based on the differentiated characteristics. [ABSTRACT FROM AUTHOR]

Achievement of national climate targets and the corresponding costs would entirely depend on regional actions within the country. However, because of substantial inequalities and heterogeneities among regions, especially in developing economies, aggressive or uniform actions may exacerbate inequity and induce huge economic losses, which in turn challenges the national climate pledges. Hence, this study extends prior research by proposing economically optimal strategies that can achieve national climate targets and ensure the greatest local and national benefits as well as regional equality. Focusing on the biggest developing country China, we find this strategy can avoid up to 1.54% of cumulative GDP losses for approaching carbon neutrality, and more than 90% of regions would obtain economic gains compared either with existing independently launched targets or with the uniform strategy that all regions achieve peak carbon emissions before 2030. We also provide optimal carbon mitigation pathways to regional peak carbon, carbon intensity and energy consumption. Aggressive or uniform actions on climate targets may exacerbate regional inequality and induce economic losses in China. The proposed collaborative strategy for carbon neutrality can avoid up to 1.54% of GDP losses while 90% of provinces would gain. [ABSTRACT FROM AUTHOR]

The nations participating in the Belt and Road Initiative (BRI) are particularly vulnerable to the challenges posed by climate change due to their extensive trading activities. The need to protect the environment and mitigate the adverse impacts of climate change in these countries is of utmost importance. Therefore, this study contributes to the scientific understanding of this issue by examining the relationship between trade openness and environmental sustainability in 89 BRI countries from 1990 to 2020. Additionally, control variables, including economic growth, energy consumption, urbanization, industrialization, and foreign direct investment, are considered to address omitted variable bias issues. The study utilizes the Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) regression estimators, and the findings reveal that trade openness improves environmental sustainability. However, economic growth, energy consumption, urbanization, and industrialization degrade environmental sustainability. Interestingly, the results affirm foreign direct investment as a trivial determinant of environmental sustainability. Regarding causal relationships, reciprocal causalities are observed between trade openness and carbon emissions, energy consumption and carbon emissions, and urbanization and carbon emissions. Furthermore, one-way causalities exist from economic growth to carbon emissions and from carbon emissions to foreign direct investment. Nevertheless, no causal relationship is identified between industrialization and carbon emissions. Based on these significant findings, it is recommended that China, as a prominent player in the BRI, takes further steps to enhance and promote energy-efficient practices in BRI countries. One practical approach is the establishment of energy efficiency standards for the goods and services traded with these countries. [ABSTRACT FROM AUTHOR]

In this study, using data from 2010 to 2021, and by utilizing the stochastic impacts by regression on population, affluence, and technology (STIRPAT) theory, and system generalized method of moments, the effect of green financing and deployment of renewable energy on carbon dioxide emissions in China and its provinces were analyzed. The results show that green financing reduces environmental pollution at the country level. Moreover, with a 1% increase in renewable energy consumption, carbon dioxide emission can be expected to decrease by 0.103%. It also demonstrates that green financing has a statistically significant coefficient only in provinces located in the eastern and western regions. Chinese policymakers should incentive policies for provinces in the eastern region of China in order to have a cleaner environment. The central region should be under supportive and pressure policies to move faster along the path to sustainable development. [ABSTRACT FROM AUTHOR]

This study analyzed the determinants that impact innovation on offshore wind energy (OSW) for a select group of countries, applying mixed-method approaches for a period between 2011 and 2021. The OSW sector witnessed cost reductions in recent years; therefore, this study analyzed how these factors impact technological innovation in the OSW sector. The fixed effects results proved trademark, carbon emissions, offshore wind capacity, and electricity from renewable energy, technical and scientific journals are significant and impact innovation regarding offshore wind energy. The maximum likelihood (MLE) coefficients are more robust than the restricted maximum likelihood (MREL) and better explained the significance of the variables in spurring OSW innovation. Ultimately, the interaction term "cross" came out significant in the analysis. It signified the importance of the interaction variables in scaling innovation. Similarly, the study forecasted OSW capacity additions to grow to more than 28GW by 2036, at a 48.8% growth rate, from the current over 55 G.W. capacity. Additionally, the infrastructure development of the OSW sector via a fitted line between total global offshore capacity and the development projects observed a negative relationship among these dual factors evaluated in the OSW, showing a decreasing trend of capacity additions among countries, as well as the fitted line relationship between total country OSW capacity and operational projects showed that China leads the globe with operational OSW projects. At the same time, Brazil is the new leader in the world regarding OSW capacity. The general analysis of the parameters of the OSW infrastructure plan showed the sector is declining regarding secured projects, development projects, operational projects, and capacities additions in some countries. However, global total capacity additions are on a steady path, declining a bit. This is attributable to the pandemic that slowed the global economy. This study will serve as a reference document for policy formulators regarding scaling up innovation for offshore wind energy. [ABSTRACT FROM AUTHOR]

The Pearl River Basin (PRB) is a significant area for economic development (ED) and ecological protection in China. Studying the relationship between carbon emission (CE) and ED is crucial for China and the world to cope with climate change and achieve CO2 reduction. For 48 cities in the PRB, we used the coupling coordination model and geographically weighted regression model to analyze the coupling coordination degree (CCD) between CE and ED and investigate the main influencing factors. The results suggested that (1) the CCD presents spatial heterogeneity, with the Pearl River Delta having the highest value and the middle reaches having the lowest value; (2) the coupling coordination type between CE and ED changes from incoordination to coordination in general; and (3) the resident income and population size have a positive influence on the CCD of the cities in the lower reaches, while the secondary industry scale has a beneficial impact on the upstream. Finally, we put forward corresponding policy suggestions to achieve sustainable development in terms of reducing economic inequities, enhancing public expenditure and innovation capability, and streamlining the industrial structure. [ABSTRACT FROM AUTHOR]

Intensifying climate change significantly impacts residential electricity consumption, especially in developing countries, such as China, that are experiencing rapid income growth. By combining meteorological and monthly household consumption survey data, this study explores the response function of residential electricity consumption to temperature in China from a micro perspective. Future residential electricity demands and related CO2 emissions are then forecast under different climate scenarios. Overall, the response function is U-shaped, and one additional day above 34 °C will increase monthly residential electricity consumption by 2.11%. Global warming will more likely increase the electricity burden on low-income groups. There will be notable seasonal changes in electricity demand in the future, and the largest increase will occur in August. The total demand for residential electricity caused by temperature change will show a fluctuating growth trend, from 0.8% and 1% in 2025 to 2% and 2.9% in 2060 under the RCP4.5 scenario and RCP8.5 scenario, respectively; meanwhile, this demand will be accompanied by a cumulative increase in carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

Environmental problems caused by carbon emissions have negative impacts on human life and society. It is therefore important to identify potential approaches to carbon emission reduction. In this study, we analyze the impact fiscal expenditure on science and technology has on carbon emissions using a panel dataset from 2007 to 2016 at Chinese provincial levels. An instrumental variable approach is employed to address the potential endogeneity of fiscal expenditure. Our results show that fiscal expenditure on science and technology has a significant and negative effect on carbon emissions by improving green innovation, economic structure upgrade, energy consumption structure, and energy efficiency. A one hundred RMB yuan increase in fiscal expenditure on science and technology would lower carbon emissions by 0.654 tons. Heterogeneity analysis reveals that the carbon reduction effects of fiscal expenditure on science and technology are larger in regions where internet coverage and the share of industry in the economy are high. Our results highlight the significant role of fiscal expenditure on science and technology in carbon reduction. [ABSTRACT FROM AUTHOR]

Full mobilization and effective use of climate aid is of great importance for the low carbon transition of Belt and Road Initiative (BRI) countries. This study utilizes the two-step system generalized method of moments model to evaluate the effects of climate aid on carbon emissions reduction and the impact mechanism through energy structure optimization. The panel data of 93 Belt and Road countries from 2000 to 2018 were used for empirical analysis. Results show that climate aid has a significant reduction effect on the carbon emissions intensity of BRI countries, and the dominant component of climate aid, i.e., mitigation aid, corresponds to better carbon emissions reduction benefits than adaptation aid. The impact mechanism demonstrates that the climate aid has dual carbon emissions reduction effects in BRI countries which have an intermediate energy structure. It indicates that climate aid not only directly reduces carbon emissions by increasing carbon reduction resources, but also indirectly reduces carbon emissions by promoting renewable energy and optimizing the energy structure. The results evidence the theory of environmental Kuznets curve hypothesis and channels of climate aid effects. Practical implications from the current study include that more climate finance support should be provided to BRI countries by developed countries, the effectiveness of climate aid should be improved by investing in projects with significant carbon reduction like renewable energy, data monitoring and performance evaluation of climate aid should be strengthened, and China should take its role and make more contributions to the low carbon transition especially energy transition of BRI countries. [ABSTRACT FROM AUTHOR]

China's newly announced carbon neutrality goal manifests its determination to advance green and low-carbon development. The country aims to peak carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. Consequently, guidelines and action plans have been actively deployed and issued. The carbon neutrality commitment (vision) and its detailed deployment (action) would contribute to climate change mitigation and corporate market value. Therefore, we categorize the carbon neutrality-related events and analyze their impacts on the stock market from July 2020 to March 2021. The main findings are as follows: (1) The action event have increased the carbon neutrality-related stocks by 0.04%, while that of the vision event is – 0.003%, indicating that investors' confidence increases when the carbon neutrality commitment is accompanied by specific and detailed guidelines. (2) The impact of carbon neutrality announcement becomes more positive and significant after related events occur repeatedly. (3) Carbon neutrality-related power industry and state-owned enterprises are potential beneficiaries of this decarbonization goal. Our study supplements the literature on climate policy and its economic value, potentially contributing to the next stage of global decarbonization. [ABSTRACT FROM AUTHOR]

Carbon dioxide has a significant impact on global climate change due to its natural greenhouse effect. The objective and credible forecast of carbon emissions is very important for the government to formulate and implement the corresponding emission reduction targets. For controlling the growth of carbon emissions, Chinese government has put forward the low-carbon pilot policy and carbon trading policy. However, the existing grey models cannot measure the impact of policies and their interactions. In order to remedy the defect, a novel grey multivariable model based on dummy variables and their interactions is established. Two kinds of grey multivariable models and back propagation neural network model are chosen as comparison models to highlight that the introduction of dummy variables and their interactions plays an important part in improving the model performance. To verify the effectiveness, these four models are selected to simulate and predict the carbon emissions generated from primary energy consumption in Guangdong Province of China. The empirical results indicate that the mean absolute percentage errors of the novel model are 2.87% and 0.86%, respectively, which is significantly better than these three competing models. Finally, based on the outstanding performance of the novel model, it is chosen to forecast the fluctuating tendency of carbon emissions in the next 5 years. [ABSTRACT FROM AUTHOR]

Clarifying the time-varying spillovers among pilot carbon emission permit trading markets in China is an important foundation for building the national carbon emission trading market. We calculate the dynamic spillover of carbon price return among the pilot carbon emission permit trading markets in China with the time-varying connectedness approach. The dataset is constructed from transaction data from seven pilot carbon markets in China during the period of June 23, 2014, to December 31, 2020. The quantitative analysis suggests that (i) Beijing and Chongqing carbon emission trading markets are the main spillover markets of carbon price returns, with strong pricing power, while the Guangdong and Tianjin markets are the main receivers of the price return spillover in other pilot carbon emission trading markets. (ii) The spillover effect among China's carbon markets has a strong policy orientation. The improvement and development of the carbon market driven by macroeconomic regulation and control policies can effectively improve the spillover ability of the carbon market, and the market trading activity, namely the volatility of the carbon price return rate, can amplify the spillover ability of the carbon market in the short term. (iii) There exist three types of price return spillover among China's pilot carbon emission trading markets, including central divergence, one-way chain transmission, and circular spillover. Along with the improvement of market operation efficiency, the central divergent type of spillover shifts to the pattern of circular spillover. It is necessary for the government to improve market efficiency and ensure the coordinated development of China's pilot carbon emission trading market and national carbon emission trading market. [ABSTRACT FROM AUTHOR]

China is the largest source of carbon emissions in the world, and the Chinese iron and steel sector is the main contributor to the growth in greenhouse gas emissions. In addition to excessive greenhouse gas emissions, climate change and global warming have seriously threatened the survival of animals, plants and even humans. To cope with global climate problems, it is our responsibility to establish environment-friendly iron and steel enterprises. In this study, data envelopment analysis (DEA) is used to evaluate the environmental protection performance of China's iron and steel enterprises based on the panel data during 2015–2017. We first establish an environment-related index system for the industry and build a range-adjusted measure model. Then, the global Malmquist productivity index based on DEA is introduced to analyse environmental efficiency and environmental productivity. The results show that most Chinese iron and steel enterprises achieved high environmental efficiency. However, many enterprises exhibited low environmental productivity and especially Shougang Group, HBIS Tangsteel and Anyang Iron and Steel continued to decline from 2015 to 2017. In general, Valin Hengyang and Shaanxi Iron and Steel achieved better performance in environmental protection. Based on the above results, the environmental problems in our country are still very serious. Thus, the government needs to formulate suitable environmental regulations to reduce the gap between the global frontier and contemporaneous frontier over two periods. Furthermore, entrepreneurs should introduce some advanced environmental technologies to improve their technical level and environmental protection level. [ABSTRACT FROM AUTHOR]

Climate change caused by carbon emissions has a strong influence on the economy and human society. Though numerous previous studies have emphasized the importance of low-carbon innovation on curbing or mitigating carbon emissions, not much attention has been given to the reverse effect. We used a panel of 285 Chinese prefecture-level cities from 2005 to 2016 and Cooperative Patent Classification (CPC)-Y02 patents as low-carbon innovation indicators. The results show that the increasing carbon emissions accelerate cities' low-carbon innovation in China, and the predicted effect varies across low-carbon innovation types. As carbon emissions rise, more low-carbon innovation will occur in activities with higher carbon emissions. Besides, we explore environmental awareness as the mediation channel for carbon emissions to impact low-carbon innovation. With the help of media, government, and enterprises, the growing carbon emissions promote public environmental awareness and change consumers' behaviors, motivating companies to speed up low-carbon innovation. [ABSTRACT FROM AUTHOR]

Countries throughout the whole world, including China, are working together to curb the greenhouse effect, but the effects seem very limited in spite of the fact that various low-carbon development strategies have been adopted, particularly in industrial enterprises. Therefore, carbon emissions caused by the public should be taken seriously, and the public should be encouraged to engage in behavior that limits carbon emissions. Therefore, this article introduces a new incentive mechanism called the Carbon Generalized System of Preferences (CGSP), which was first introduced in Guangdong Province, China. It is believed that this new mechanism matches the role of leadership in Guangdong in the urbanization and economic development of China by addressing the small sources of greenhouse gases (GHGs) and by issuing carbon coins. Compared with Chinese Certified Emission Reduction (CCER), the development scope, management level, and novel criteria of CGSP are very different but relatively easy for the public to accept. The CGSP shows that the network platform, reduced carbon emissions, and urban pilots are all compatible with the goals of the nation and city, and they promote the CGSP in different ways. Because of its consistency with ecological civilization in China, the prospect of the CGSP is bright; however, there are some challenges, such as policy and economic factors, combined with pollution control. [ABSTRACT FROM AUTHOR]

To investigate the influences of different factors on spatial heterogeneity of regional carbon emissions, we firstly studied the spatial-temporal dynamics of regional energy-related carbon emissions using global Moran’s I and Getis-Ord Gi and applied geographical detector model to explain the spatial heterogeneity of regional carbon emissions. Some conclusions were drawn. Regional carbon emissions showed significant global and local spatial autocorrelation. The carbon emissions were greater in eastern and northern regions than in western and southern regions. Fixed assets investment and economic output had been the main contributing factors over the study period, and economic output had been decreasing its influence. Industrial structure’s influence showed a decrease trend and became smaller in 2015. The results of the interaction detections in 2015 can be divided into two types: enhance and nonlinear, and enhance and bivariate. The interactive influences between technological level and fixed assets investment, economic output and technological level, population size and technological level, and economic output and economic development were greater than others. Some policy recommendations were proposed. [ABSTRACT FROM AUTHOR]