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This study aims to construct a monthly carbon emission index based on energy combustion in order to investigate its predictive power for the real GDP growth rate in the United States. Our objective is to evaluate and quantify the predictive performance and the potential impact of carbon-related factors on the GDP growth rate. We define the carbon emission index as the change rate index of monthly carbon dioxide emissions after accounting for seasonal effects, encompassing five sectors of energy consumption (residential, commercial, industrial, transportation, and electric power). Our findings demonstrate the robust and exceptional predictive capability of the newly developed carbon emission indices for GDP growth rates, particularly in relation to the transportation and industrial sectors. Moreover, in addition to popular macroeconomic variables, the carbon emission index contains incremental predictive information. The results obtained under diverse business cycle conditions and during the COVID-19 Pandemic further underscore the significance of our study. The findings of this paper provide more concise and efficient predictors for GDP growth rate forecasts. • This paper examines the relationship between carbon dioxide and economic growth. • This paper constructs a new set of carbon emission indexes (CEI) • These indexes have robust and excellent predictive power for GDP growth rate. • In particular, the carbon emission indices of the transportation sector and the industrial sectors show the strongest predictive power. [ABSTRACT FROM AUTHOR]

Global warming and environmental degradation are essential issues that endanger human survival. The conflict between rising carbon emissions and carbon neutrality goals has prompted an urgent need for China's energy sector to step up efforts to develop clean energy generation. As a significant hydropower country, hydropower generation is China's mainstay of clean energy generation. The work contributing to sustainable hydropower development requires reasonable forecasts of clean energy generation. This paper proposes a seasonal optimized multivariate grey model that optimizes background value and supplements dummy variables to explore hidden factors through an optimization algorithm to the related sequences. The novel model improves the fitting and prediction accuracy through the loop supplementation of dummy variables. The model tests the effect of China's hydropower generation prediction and compares results with other methods. The mean absolute percentage error of the model training and test groups is 3.87 % and 0.83 %. Finally, this paper predicts hydropower generation in China from 2022 to 2025 based on the power generation during China's 13th Five-Year Plan Period. • This paper proposes a novel grey model method based on dummy variable regulation. • This paper uses the Whale Optimization Algorithm to optimize the grey model's initial and background values. • This paper uses the proposed method to solve the grey model's problem of not fitting the fluctuation trend. • This paper uses the proposed model to predict the trend of hydropower generation during the 14th Five-Year Plan. [ABSTRACT FROM AUTHOR]

Driven by the goal of carbon neutrality and carbon peaking, reducing corporate carbon emissions is of great significance. This study quantifies the characteristics of carbon neutrality bond and tests its effects on corporate carbon emissions. Based on methods such as double fixed effect, SYS-GMM, and IV-2SLS, this paper examines the relationship between the two and draws the following conclusions. First, carbon neutrality bond can reduce corporate carbon emissions. Secondly, the higher the scale, duration, and rating of carbon neutrality bond, the more conducive it is to reducing corporate carbon emissions, and publicly offered carbon neutrality bond is also more conducive to reducing corporate carbon emissions. Thirdly, carbon neutrality bond will reduce corporate carbon emissions by promoting environmental responsibility fulfillment, subsidies, internal control quality and information transparency. However, it exacerbates corporate carbon emissions by increasing greenwashing and liquidity risks. Fourthly, carbon neutrality bond has a stronger inhibitory effect on carbon emissions of large-scale firms, central state-owned firms, and mature-period firms. This study overall concludes that carbon neutral bonds have a significant carbon reduction effect, which aims to provide suggestions on low-carbon finance to promote corporate carbon reduction. [Display omitted] • Quantity features of carbon neutrality bond (CNB) • Impact paths of CNB on CAE are prevention, production and governance effects. • CNB exacerbates CAE by increasing green-washing and liquidity risks. • CNB has a stronger inhibition effect on CAE of large-scale firms. [ABSTRACT FROM AUTHOR]

Selection of the right suppliers with a view of overall reduction in the procurement cost as well as carbon emissions is an important task for the buyers to sustain in the fierce competitive environment. The rising concerns about carbon emissions due to severe climatic changes globally have forced supply chain managers to restrategize about controlling their carbon emissions. This paper proposes a dynamic supplier selection model incorporating the carbon emissions under the carbon cap-and-trade scenario. Carbon emissions caused due to ordering, holding the inventory, production and handling and transportation have been considered in the paper. The proposed mathematical model is a mixed-integer-non-linear-program (MINLP). Validation of the proposed MINLP has been done using two randomly generated datasets having the essential parameters of Big Data, i.e. volume, velocity, and variety. • Paper proposes a mixed-integer nonlinear program (MINLP) using Big Data. • MINLP is mapped with the 3Vs of Big Data. • MINLP model optimizes overall costs in Big Data environment. [ABSTRACT FROM AUTHOR]

Low-carbon industrial upgrading is a central means to achieve long-term climate change mitigation and sustainable industrial development. Yet the empirical evidence on the effects of environmental policies on low-carbon industrial upgrading remains relatively rare, and the analysis of channels is unexamined. Based on the panel data of 30 provinces in China from 2000 to 2016, this paper has contributed to the literature by testing the impacts of four distinct environmental policies on low-carbon upgrading and their possible channels. We found that energy-saving goals (ESGs) and new energy subsidies (NESs) promoted low-carbon upgrading, while pollution discharge fees (PDFs) restrained low-carbon upgrading and emission trading schemes (ETSs) had no impact. These conclusions were still tenable after a series of robustness tests. Channel analysis reveals that ESGs realized both low-carbon innovation and high-carbon industry restructuring (especially reflected in manufacturing), NESs were effective, but only in directing innovation. PDFs did not improve low-carbon upgrading, possibly due to their negative effects in low-carbon fields (including two sub-fields: energy efficiency and renewable energy). The restructuring and innovative effects of ETSs were insignificant. Finally, this paper put forward several policy implementations, including the promotion of market mechanisms, more strict law enforcement, and low-carbon industry development. • The impact of four distinct environmental policies on low-carbon industrial upgrading is examined. • The unique data of low-carbon patents and newly formed enterprises enable channel analysis. • Energy-saving goals (ESGs) promote industrial upgrading through restructuring and innovation effects. • New energy subsidies (NESs) advance industrial upgrading through the channel of inducing innovation only. • Emission trading schemes (ETSs) have no impact while pollution discharge fees (PDFs) restrain industrial upgrading. [ABSTRACT FROM AUTHOR]

This paper explores the global embodied carbon emissions transfer network. To clarify the carbon emissions reduction responsibilities of each country globally, a complex interdependent network structure based on the 2016 World Multi-Regional Input-Output (MRIO) table and the transfer of production factors between industries is constructed. Using input-output and social network analyses, the structural features of the global carbon emissions flow network is uncovered, and then carbon inequality among countries from a multi-regional perspective is revealed. The research findings show that the scale of global embodied carbon transfer expands continuously. The direction of transfer exhibits asymmetry, regionalism, and complexity. Hungary, Romania, Slovenia, Iran, Ethiopia, and Iran are the main carbon-exporting countries, while the United States, Germany, the United Kingdom, Japan, Canada, Spain are the main carbon-importing countries. Furthermore, the block model analysis reveals that the carbon transfer and transmission effects between global regions tend to be centralized clusters, from "demand-driven" to "internalized supply-demand coexistence". There is significant uneven exchange between wealth benefits and environmental burdens among blocks. • Global embodied carbon emissions transfer network is explored. • Carbon inequality among countries from a multi-regional perspective is revealed. • "Middlemen" in the embodied carbon emissions transfer network are discovered. • Significant uneven exchange exists between wealth benefits and environmental burdens. [ABSTRACT FROM AUTHOR]

This paper investigates the relationships between economic growth, energy consumption, exports, tourism, geopolitical risk, and carbon dioxide (hereafter cited as "CO 2 ") emissions in Group of Seven (hereafter cited as "G7") countries from 1990 to 2021. Cross-sectional correlation tests, unit root tests, cointegration analysis, regression analysis, panel data estimation, and Granger causality tests are performed. The empirical results show that energy consumption and geopolitical risk negatively affect environmental quality. In addition, globalization exacerbates the problem of ecological degradation. At the same time, the increase in export levels and emerging tourism development are conducive to reducing CO 2 emissions. It is recommended that policymakers pay attention to the role of the digital economy and technological innovation in shaping the energy consumption patterns, carbon emissions, and geopolitical risks in G7 countries, encourage digital transformation, use technological innovation in energy efficiency to drive economic growth, use the digital economy to promote sustainable tourism, decouple it from high carbon emissions, challenge the traditional Environmental Kuznets Curve (hereafter cited as "EKC") framework, and jointly promote dual sustainable development of the economy and environment. • We examine energy, exports, tourism, and CO2 emissions links in G7 nations from 1990-2021. • We employ correlation, cointegration, regression, and Granger causality techniques to explore these relationships. • We find that energy consumption, geopolitical risk, and globalization negatively affect environmental quality. • We propose harnessing the digital economy, technology, and sustainable tourism to promote environmental well-being. [ABSTRACT FROM AUTHOR]

Treating carbon emission rights as tradable commodities is a major institutional innovation in the carbon market's response to climate change. The level of carbon emissions from production activities is inextricably linked to climate policy adjustments. Thus, this article applies wavelet-based quantile-on-quantile regression to study the impact of climate policy uncertainty (CPU) on the carbon trading price (CTP) in the European Union Emissions Trading System (EU ETS). Short-term results show a mixed effect of CPU on CTP. In the medium to long term, there is a positive correlation between the two at the high quantiles of CPU. The results are supported by the theoretical mechanisms of CPU on CTP. The CTP represents the economic cost of carbon emissions, which can significantly influence the level of carbon emissions and is critical to achieving carbon neutrality. Governments should strive to reduce CPU and manage market expectations to minimise the impact of CPU on CTP. In addition, this paper can also inspire carbon market participants to help them make sound and scientific investment decisions. • Apply wavelet-based quantile-on-quantile regression to study the effect of CPU on the CTP. • The CPU is at different quantiles and time frequencies, the link between CPU and CTP is dynamic • The results are supported by the theoretical mechanisms of CPU on CTP. • The CTP can significantly influence the level of carbon emissions and is critical to achieving carbon neutrality. • Governments should strive to reduce CPU and manage market expectations to minimise the impact of CPU on CTP. [ABSTRACT FROM AUTHOR]

Foreign aid is an essential tool in economic diplomacy tool, yet its significance in global environment governance often goes underestimated. Taking 118 countries that received Chinese foreign aid from 2000 to 2018 as the research objects, this study investigated the impact of foreign aid on the carbon emissions of recipient countries and the mechanism. Firstly, the present study found that Chinese foreign aid increased the overall carbon emission levels of recipient countries during the sample period, with each 1 % increase in Chinese foreign aid being followed by a 0.0148 % increase in the carbon emissions of recipient countries. Secondly, the improvement of the economic growth and technological innovation of recipient countries served a mediating role in the process of Chinese aid affecting the carbon emissions of recipient countries. Thirdly, the threshold test results indicate that Chinese foreign aid helps to reduce the carbon emission levels of recipient countries when their economic growth rates and technology innovation levels are low, noting that this emission reduction effect may weaken as the recipient countries' economic growth rates and technological innovation increase. The findings of this paper expand the literature on the functional theory and non-economic consequences of foreign aid. Moreover, they told significant theoretical and policy implications for promoting cleaner aid practices and fostering low-carbon, green growth in recipient countries. • Chinese foreign aid (CFA) increased the overall CO 2 emission of recipient countries. • The improvement of the economic growth and technological innovation of recipient countries served a mediating role. • CFA helps to reduce the CO 2 emission of recipient countries with low economic growth rates and limited technical innovation. [ABSTRACT FROM AUTHOR]

Based on the expansion of the consumption scale caused by the convenience of mobile payment, this paper constructs a general equilibrium theoretical model for analysing the impact of digital finance development on household carbon dioxide emissions. Then, the form empirically tests the impact of digital finance development on households' carbon dioxide emissions using the microdata from the China Household Tracking Survey (CFPS). It is found that the development of digital finance can significantly increase the carbon dioxide emissions of household consumption, mainly from the increase in developmental consumption. The mechanism analysis also shows that the expansion of the consumption scale and the upgrade of consumption tendency caused by the convenience of payment and wage premium achieve the related effects. Finally, residents' environmental awareness and social and environmental governance factors also actively adjust the impact of digital financial development on carbon dioxide emissions. • Based on the expansion of the consumption scale caused by the convenience of mobile payment,this paper constructs a general equilibrium theoretical for analysing the impact of digital finance development on household carbon dioxide emissions. • We the impact of digital finance development on households' carbon dioxide emissions using the microdata from the China Tracking Survey(CFPS). • It is found that the development of digital finance can significantly increase the carbon dioxide emissions of household consumption, mainly from the increase in developmental Sumptionion. • The mechanism analysis also shows that the expansion of the consumption scale and upgrade of consumption tendency caused by the convenience of payment and wage premium achieve the related effects. [ABSTRACT FROM AUTHOR]

As a major energy consumption province in China, Jiangsu Province is a key area for carbon emission reduction in China. Grasping the future trends of carbon emission in Jiangsu Province will help to find effective ways to reduce carbon emission. This paper proposes the STIRPAT-IGWO-SVR model, including screening the carbon emission influencing factors based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, optimizing the parameters of the support vector regression (SVR) model using the gray wolf optimization (GWO) algorithm improved by the differential evolution (DE) algorithm, and sets five scenarios to predict and compare the carbon emissions of Jiangsu Province under different scenarios. In addition, the Tapio decoupling model is used to analyze the decoupling relationship of carbon emission and economic growth in each scenario. The results show that the STIRPAT-IGWO-SVR model proposed in this paper shows good performance compared with other models. For Jiangsu Province, improving the energy structure has the strongest inhibitory effect on carbon emission, stronger than reducing energy intensity, and far stronger than optimizing the industrial structure. Compared with a single plan, even if the measures are slightly weakened, the implementation of combined planning measures can more effectively control carbon emission. • Predict and compare carbon emission and its decoupling status under 5 scenarios. • Propose the STIRPAT-IGWO-SVR model. • Use the GWO algorithm improved by the DE algorithm to optimize the SVR model. • The STIRPAT-IGWO-SVR model shows good performance compared with other models. • The combined planning measures can more effectively control carbon emission. [ABSTRACT FROM AUTHOR]

This paper analyses the effects of digital technology transformation on carbon dioxide (CO 2) emission cycles using the listed manufacturing firms in China from 2013 to 2022. It is found that the digital technology transformation of enterprises significantly reduces the level of CO 2 emissions. It is also observed that the impact of digital transformation on corporate CO 2 emissions varies among different property rights sample groups. The findings indicate that the effects of digital transformation on CO 2 emissions are more remarkable in state-owned enterprises. Digital finance also strengthens the impact of digital transformation on corporate CO 2 emission reduction. These results provide theoretical support and empirical evidence for promoting digital transformation to reduce CO 2 emissions in China. • The study focuses on the role of digital technology in aiding carbon reduction efforts within the manufacturing sector. • Digital technology drives energy conservation and low-carbon transformations in manufacturing. • Digital transformations significantly mitigate carbon emission risks through four main avenues. • State-owned enterprises show a pronounced benefit from digital transformations in carbon reductions. • Empirical evidence underscores the need for enhancing digital tech awareness and regulatory support. [ABSTRACT FROM AUTHOR]

With the successful convening of the 26th United Nations Climate Change Conference (COP26) and the constraints of carbon neutrality targets, China faces an increasingly severe task of energy conservation, reducing emissions, and improving carbon emission efficiency (CEE). The development of the Internet economy provides a perfect opportunity for China to realize the coordinated development of the economy and low-carbon society. Based on China's provincial panel data from 2006 to 2017, this paper explores the relationship between the Internet economy and CEE by using the instrumental variable-generalized method of moments (IV-GMM) method. It also investigates the internal mechanism and heterogeneity analysis. The main results show that (1) the Internet economy positively affects CEE in China; in other words, a 1 % increase in Internet economy indicators will contribute to an increase of CEE indicators by 0.141 %; (2) the Internet economy indirectly affects CEE by increasing human capital, clean technological innovation, and the non-coal energy mix; and (3) there is a significant asymmetric relationship between the Internet economy and CEE, with the negative influence of the Internet economy on CEE being more significant in southern China. This paper also proposes some policy implications to help China achieve low-carbon social development. • We investigate the impact of the Internet economy on carbon emissions efficiency (CEE) in China. • The Internet economy positively affects CEE. • The Internet economy indirectly affects CEE by increasing human capital, clean technological innovation, and energy mix. • There is a significant asymmetric relationship between the Internet economy and CEE. • The negative influence of the Internet economy on CEE is more significant in southern China. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the impact of environmental innovation on energy sector-based CO 2 emissions using a large dataset for 32 OECD countries covering the period 1997–2018. To detect the nonlinear relationship between variables, this paper adopts a panel smooth transition regression (PSTR) model, which can estimate both the threshold level endogenously and the smoothness of the transition from one regime to another. The findings indicate that environmental innovation has a reducing effect on CO 2 emissions from the energy sector up to a certain level of innovation is insignificant (1st regime), then it has a reducing effect (2nd regime), and above this level environmental innovation has an increasing effect on carbon emissions (3rd regime), suggesting the existence of a rebound effect. These findings point out that environmental innovations alone are not a solution to struggle environmental problems and should be supported by environmental policies to reveal their environmental reflections. This paper not only makes an important contribution to the empirical literature, but also reveals important policy implications, particularly to achieve climate change targets. • Environmental innovation – energy sector based CO 2 emissions nexus is investigated in 32 OECD countries. • The panel smooth transition regression model is adopted. • The threshold effects of environmental innovation on energy sector-based CO 2 emissions are found. • The results point out that the rebound effects of environmental innovation should be considered in the policy making process. [ABSTRACT FROM AUTHOR]

• The paper aims to examine the effects of international tourism on carbon emissions in the most visited countries by using panel quantile regression. • We examine moderating effect of eco-friendly innovations on the transportation sector on the relationship between international tourism and carbon emissions. • Empirical results show that international tourism leads to increase carbon emissions at the highest quantiles of carbon emissions. • The effect of improvements in eco-friendly technologies for transportation is significant on carbon emissions at all quantiles. • The effect of improvements in eco-friendly technologies for transportation eliminates the harmful effect of international tourism on environmental quality. The paper aims to examine the effects of international tourism on carbon emissions in the most visited countries using panel quantile regression for the periods 1995-2018. Since the primary source of carbon emissions from international tourism is transportation, we examine the moderating effect of eco-friendly innovations on the transportation sector for the relationship between international tourism and carbon emissions. Empirical results show that while international tourism led to an increase in carbon emissions between the fifth and ninth quantiles of carbon emissions, eco-friendly innovations for the transportation sector play an essential role in the effect of international tourism on carbon emissions. We find that the impact of improvements in eco-friendly technologies for transportation is significant on carbon emissions at all quantiles and that it eliminates the harmful effect of international tourism on environmental quality. These results are important for policy-makers to reduce carbon emissions from tourism because these countries have committed to reducing their carbon emissions according to the Paris Accord and the Sustainable Development Goals. [ABSTRACT FROM AUTHOR]

This paper first researches the influence of carbon emissions trading (CET) on corporate total factor productivity (TFP) from three aspects of innovation effect, factor allocation effect and cost effect, and then uses the data of listed corporations from 2008 to 2021, and empirically analyzes each effect by multi-temporal difference-in-difference-in-difference (DDD) model. We find that CET can suppress the corporate TFP through direct effect (cost effect), and improve corporate TFP through indirect effects (innovation effect and factor allocation effect). Overall, the indirect effects are more effective. Moreover, the CET can significantly improve corporate TFP, and it is still true after a set of robustness checks. Heterogeneity analysis indicates that CET has a different influence on different types of corporate TFP, and there are also certain differences in their mechanisms. • Mechanisms were analyzed from three aspects. • We analyze the effect of CET on TFP. • The CET can significantly improve TFP. • CET has different mechanisms in promoting TFP. [ABSTRACT FROM AUTHOR]

Narrowing carbon inequality is crucial for coordinated and sustainable development. Based on a dataset of 283 Chinese cities for the period 2011–2017, and by employing the instrumental variable-generalized method of moments (IV-GMM) model, we test whether financial inclusion can achieve the dual dividends of inhibiting carbon inequality not only within cities, but also between cities. Further, this paper pays attention to the heterogeneous, direct, and indirect impacts of financial inclusion on carbon inequality. (1) The first finding is that financial inclusion achieves the dual dividends of narrowing carbon inequality within and between cities. (2) The mitigation effect of financial inclusion on carbon inequality is heterogeneous in terms of cities' administrative hierarchy, geographical location, and economic scale. (3) Six aspects of financial inclusion lead directly to the mitigation of carbon inequality. (4) The inhibitory effect of financial inclusion on carbon inequality is caused mainly by reduced intensity of carbon emissions and income inequality, which are two effective mediators. These findings help us devise solutions for eradicating carbon inequality by designing policies related to financial inclusion. • We examine the impact of financial inclusion on carbon inequality. • Financial inclusion achieves the dual dividends of narrowing carbon inequality both within and between cities. • The nexus is heterogeneous at different city levels, geographical locations, and economic scales. • Financial inclusion indirectly affects carbon inequality through carbon emissions intensity and income inequality. [ABSTRACT FROM AUTHOR]

This research paper investigates the various dependence structures across oil prices, emission prices and stock markets for Middle East and Gulf Cooperation Council (GCC) countries. This study enables us to form a judgement on how the phased implementation of Kyoto protocol and COP26 on climate change is likely to be translated into changes in policy multipliers as the changes feed into the real economy through stock market movements. We employ the spillover index developed by Diebold and Yilmaz (2012) and Baruník and Křehlík (2018) to identify the most strongly related stock index to oil price return. Also, we investigate how emission price (which represents the cost of pollution) changes feed into oil price and how that impact on stock markets and what is the short- and long run spillovers between them. It is important to acknowledge some of the limitations of this study. One potential limitation is the focus on a specific geographic region, the Middle East and GCC countries. This may limit the generalizability of the findings to other regions. Additionally, the study focuses on the dependence structure among oil prices, emission prices, and stock markets, and does not consider other factors that may influence the relationship between these variables. Nonetheless, our study provides useful empirical evidence for assessing the impact of energy transition on both oil prices and stock price movements and can inform the development of diversified revenue streams for the region. In terms of future research, it would be worthwhile to extend the analysis to include additional variables, such as renewable energy prices, to gain a more comprehensive understanding of the dynamics at play in the energy markets of the Middle East and GCCs. • Our study investigates dependence structures among oil, emission prices, and stock markets in GCC countries. • We investigate the various dependence structures across oil price, carbon price and stock markets in the GCCs. • We employ spillover index to identify the dependence structure between oil price volatility and emission prices. • We suggest future research on renewable energy prices for a comprehensive understanding. [ABSTRACT FROM AUTHOR]

• The innovative effects of three types of carbon-abatement policies (energy-saving goals (ESGs), new energy subsidies (NESs), and carbon emission trading schemes (ETSs)) were examined. • The contributions of both ESGs and NESs policies were relatively stable in the 11th five-year period (2006–2010), but weakened in the 12th five-year period (2010–2015) that followed. • In terms of synergies between policies, no significant estimates for policy coordination were discovered. • Only administrative regulation had a positive effect on the tendency to pursue technology investment. • With an improvement in enforcement strength, the innovation influences from TIPs were not static, but changed differently, even oppositely, on each side of the threshold. Low-carbon technology innovation is considered to be one of the most effective remedial measures for reducing climate change. Based on panel data from 30 provinces in China which were collected firms in operation between 1999 and 2016, this paper used a difference-in-differences (DID) approach to assess whether China's current carbon-abatement policies (i.e. energy-saving goals (ESGs), new energy subsidies (NESs), and carbon emission trading schemes (ETSs)) can direct innovation activities towards low-carbon technologies; then, this paper analyzed the channels involved from the perspective of investment preferences. In terms of policy-induced effects, the contributions of both ESGs and NESs policies were discovered to be relatively stable in the 11th five-year period (FYP) (2006–2010), but weaker in the following 12th FYP, and the ETSs' effect on innovation was found to be not significant. In particular, the estimates for policy coordination were not significant, and the innovation-inducing effects of NESs were moderated by market performance. For the analysis of channels, only administrative regulation had a reinforcing effect on the propensity to pursue technological investment. As enforcement increases, the innovation influence from technology investment preferences (TIPs) has also changed: it is distinct, and even opposite, on each side of the threshold. [ABSTRACT FROM AUTHOR]

Making a country's Trade environmentally friendly, aka the Green Trade through environmental restrictions, has long been a popular policy choice, especially for the wealthy and trade-integrated economies. However, the effectiveness of such regulations in terms of improved environmental quality is an essential but less investigated research question. In this paper, we analyze, for G-7 countries, the environmental effects of the two competing policy choices, i.e., imposing environmental restrictions on Trade or investing in green technology and innovation, by following a rigorous econometric approach. Our results are exciting and, to some extent, contrary to mainstream ideas. We find that the increasing share of Green trade in the overall trade portfolio of G-7 countries is futile and more damaging for the environment by causing an increase in consumption-based carbon emissions. On the other hand, the role of Green technology is highly effective in reducing these emissions in the panel of G-7 countries. These results highlight the effectiveness of the two competing policy choices almost every country must make to protect the climate and stop further environmental degradation. • We investigate the environmental impact of two competing policy choices i.e. Green Trade or Green Innovation in G7 economies. • Our results refute the utility of imposing trade restrictions in G7 countries. • The results show that boosting green trade in the trade portfolio harms the environment. • The role of Green technology is highly effective in reducing consumption based emissions. • These findings demonstrate the comparative efficacy of the two policy choices to achieve COP26 targets. [ABSTRACT FROM AUTHOR]

• This paper discusses the impact of participation in global value chains (GVCs) on carbon emissions transferring via trade (CTT). • As the degree of participation in GVCs rises, the CTT would also increase. • This paper establishes an econometric panel data model to investigate the CTT change. On the basis of building the models measuring the degree of participation in global value chains (GVCs), this paper establishes an econometric panel data model to investigate the impact of participation in GVCs on the carbon emissions transferring via trade (CTT) in 39 major economies, and it articulates relevant environmental governance policies that potentially achieve emissions reduction targets. Results indicate that, from a global perspective, as the degree of participation in GVCs rises, the CTT would also increase, and a series of tests showed that the robustness of this argument was not interfered with by endogenous issues. The growth of the CTT from the continuous deepening of participation in GVCs could be partially counterbalanced by reductions in emissions through relevant policies such as the increase of energy intensity, the optimization of industrial structure, and the improvement of residents' awareness of emission reduction. Thus, we should discuss emissions reduction obligation assignments from the perspective of participation in GVCs, and relevant measures on emission reduction should also be placed on optimizing the division of participation in GVCs for each country, so as to lessen local economic dependence on energy intensive products. Overall, this paper could provide more comprehensive insight to enhance our understanding of the determinants driving the changes in the CTT in response to global climate change. [ABSTRACT FROM AUTHOR]

• A review of different methods for measuring carbon emissions and SCC. • SCC model improvement and decision support research are developing in China. • The differences in existing and future research direction were emphasized. With increasing international attention on the coupling system of carbon emission and social economy, governments need to formulate relevant policies and measures to control carbon dioxide and other greenhouse gas emissions. The social cost of carbon (SCC) can form the basis for such steps. To investigate research on SCC, this paper examines relevant literature in China and abroad for different methods to measure carbon emissions. It further reviews research methods for studying SCC, the effects of model parameters on SCC, and the application of SCC to policymaking. The purpose of researching the measurement of carbon emissions is to select the most appropriate, accurate, and precise methods to enhance data support for research on carbon emissions (including the measurement of social costs). Recording different models facilitates the estimation of SCC for more suitable and exact estimation methods. Analyzing the effects of model parameters on SCC clarifies decision-making and exogenous variables regarding estimating SCC, including the impact of equity weight, uncertainty, risk aversion, and discount and time preference rates on the value of SCC. Therefore, this paper reviews existing research on SCC policy to help frame policymaking appropriately, using the social cost of carbon emissions. [ABSTRACT FROM AUTHOR]

Land use carbon emission is one of the main sources of greenhouse gases. In order to achieve carbon reduction, it is crucial to clarify the pathways of land use carbon emission influencing factors. The article takes Chang-Zhu-Tan urban agglomeration as the study area, combines the land use remote sensing data and energy consumption statistics from 1995 to 2018, and uses the STIRPAT extended model to identify the economic, population, energy, technology, policy, land and opening-up level as the latent variables affecting the land use carbon emission in the study area, to establish PLS-SEM to explore the influence of latent variables on dependent variables and the interaction between latent variables. The results show that the seven selected latent variables had good explanatory power on land use carbon emission with R2 reaching 0.983. Economy, population, energy and land — the latent variables in this study — can directly influence land use carbon emission. This study found that land was the most important factor in increasing land use carbon emissions, with a path coefficient of 1.471, while economy played a negative role, with a path coefficient of −1.401. Latent variables other than energy and land all had mediating effects on the dependent variable or the remaining latent variables directly or indirectly. Indirect effects included complete mediation and partial mediation. For example, technology and opening-up level cannot directly influence the dependent variable, but can have a completely indirect effect by affecting energy (complete mediation). The fitness and superiority of the model developed in this paper were extremely high, with values of 0.067 and 0.846 for SRMR and GOF, respectively. This study helps to clarify the influence paths of land use carbon emission and figuratively depicts the path direction and degree of influence among influencing factors, which will help Chang-Zhu-Tan urban agglomeration achieve carbon emission reduction. • Traditional methods to explore influencing factors, such as LMDI, Kaya or STIRPAT model, can only reflect the direct effect of independent variables on dependent variables, thus obtaining the corresponding influenced coefficient. • For instance, Aruhan et al. (2019) used the STIRPAT model to select indicators such as population for linear regression analysis, and explored the influencing factors of land use carbon emission in Toronto, Inner Mongolia. Quan et al. (2020) calculated logistics carbon emissions in China based on panel data. • The study decomposed the data into different factors such as energy intensity by using LMDI decomposition model, and explored their impact on carbon emission alone. Han et al. (2019) established a multivariate linear correlation test model by using Kaya for the construction of new urbanization with independent variables to analyze the influencing factors in China's urbanization construction. • However, the ways in which various factors affect land use carbon emissions are often complex. Factors may affect land use carbon emissions in a direct and/or indirect ways. Indirect effects also mean that there is a mediation effect, which would lead to more detailed and accurate models. • Coincidentally, partial least squares structural equation model (PLS-SEM) can meet this demand, and PLS-SEM can also visualize the action path map, showing the direction and magnitude of the impact on land use carbon emission more straightforwardly. [ABSTRACT FROM AUTHOR]

For machinery manufacturing firms, a rather concerned barrier to arrive at carbon neutrality is the uncertain benefit of carbon emission reduction. To control the increasing cost triggered by carbon pricing mechanism and transition of carbon emission pattern, this paper restructures the whole production process of machinery products from the perspectives of low-carbon management and revaluation of carbon assets of process-flow to unearth the potential of carbon benefit of machinery products. Our theoretical analysis and case study keeping an eye on engineering machinery and port machinery jointly draw following key findings: First, the process management can effectively reduce carbon emissions as similar as the role of green-tech investment, and can arrive at a rather impressive emission reduction performance with less upfront investment. Second, to enhance carbon benefits sustainably, machinery manufacturing firms should control carbon emissions in the whole life-cycle and integrate carbon assets into production costs. Third, both carbon emission reduction and waste recycling can argument the return on carbon assets. Hence one can see that to create the competitive edge in the low-carbon sphere of machinery products, machinery manufacturing firms should remold the value-added process of carbon emission reduction in products' whole-life at the peak of total costs. • Process management effectively reduces carbon emissions as similar as the role of green-tech investment. • Machinery manufacturers should control carbon emissions in the whole life-cycle and integrate carbon assets into the costs. • Carbon emission reduction and waste recycling can argument the return on carbon assets. [ABSTRACT FROM AUTHOR]

China's large-scale inter-provincial population migration has a vast impact on social changes, and significantly altered the energy consumption demand of various provinces, and further affected the spatial distribution of carbon emissions. Nevertheless, less attention has been paid to the impact of population migration on carbon emissions. To make up for the niche, this paper develops an innovative framework by integrating a geographically weighted regression model, a population migration matrix, and an environmentally extended multi-regional input-output model to assess the impact quantitatively based on factual and counterfactual scenarios. The results show that the carbon emissions increased by 78.16 million tonnes (Mt) in 2017 due to population migration, of which direct carbon emissions increased by 6.91 Mt. and indirect carbon emissions increased by 71.25 Mt. It must be emphasized that population migration increases indirect carbon emissions driven by urban consumption and investment in the provinces with net in-migrants. But these provinces transfer more carbon emissions to the regions with net out-migrants, which implies that population migration exacerbates carbon emissions inequality. This especially increases the carbon emission reduction barrier of provinces with net out-migrants. Overall, these empirical discoveries shed light on making regionally coordinated carbon reduction policies. • Integrated an innovative framework for assessing the impact of population migration on carbon emissions. • The impact of population migration on carbon emissions is assessed from the perspective of industrial linkages. • Population migration exacerbates carbon emissions inequality. • Population migration exacerbates carbon emission reduction barrier of provinces with net out-migrants. [ABSTRACT FROM AUTHOR]

High-quality energy development (HED) is conducive to achieving a win-win situation for economic development and carbon emission reduction in the context of the current "carbon neutrality" constraints in China, and the digital economy will likely accelerate the achievement of its goals. To verify the above hypothesis, based on China's provincial panel dataset from 2007 to 2017, this paper uses a dynamic panel model to estimate the nexus between the digital economy and HED and further explores their heterogeneous influence. The main results indicate that: (1) the digital economy positively affects HED in China; in other words, a 1 % increase in the digital economy index will boost HED by an average of 0.191 %; (2) the results of heterogeneity show that the influence of the digital economy on HED is stronger in regions with higher digital economy indexes and higher HED indexes; and (3) the digital economy positively affects HED through the innovation and application sub-indicator and the economic growth and jobs sub-indicator. We also provide policy implications for governments and scholars in related fields for reference. • The impact of the digital economy on high-quality energy development (HED) is explored. • We measure the digital economy indexes and HED indexes in China. • The digital economy has a positive effect on HED in China. • The digital economy positively affects HED through two dimensions: "innovation and application" and "economic growth and jobs." • The effect of the digital economy on HED is heterogeneous. [ABSTRACT FROM AUTHOR]

This paper investigates how oil price, COVID-19, and global energy innovation can affect carbon emissions under time- and frequency-varying perspectives. We contribute to the literature by being the first research to document the relationship between these variables in the short and long run (dynamically) at different frequencies in a multivariate context, thus providing a more detailed picture of the forces driving CO 2 emissions. For this purpose, we use a novel methodology, i.e., the wavelet local multiple correlation (WLMC) recently developed by Polanco-Martínez et al. (2020). The results provide fresh evidence of long-run asymmetric dynamic correlations, highlighting how the oil price plays a key role in the dynamics of CO 2 emissions. Moreover, we find that, during the long period, there is a strong negative co-movement between CO 2 and the global energy innovation index, i.e., more investment in clean energy induces less emission. Supported by our findings, this research suggests crucial policy implications and insights for the governments worldwide in their efforts to revive their economies amidst the pandemic and environmental uncertainties. • Energy innovation, oil price, COVID-19 and carbon emission linkage is examined. • Wavelet Local Multiple Correlation Method is employed. • Oil price plays a crucial role in the dynamics of CO 2 emissions. • Negative co-movement between CO 2 and energy innovation is discovered. [ABSTRACT FROM AUTHOR]

Under the "double carbon" target, renewable energy technologies offer a new low-carbon development path for human society. This paper selects the Yangtze River Economic Belt as the research area, introduces the classification of the renewable energy technologies from the perspective of patents and uses the Super-SBM model, entropy TOPSIS method and spatial Durbin model to empirically analyze the spatial spillover effects of the renewable energy technologies on carbon emission efficiency (CEE) and optimal development range. The analysis conclusions are as follows: First, there are differences in geographical location and geographic distance between the eastern and the western regions. The CEE is spatially correlated, but the permeability is weak, which specifically reflects the stepwise difference in the eastern, central and western regions of the spatial dimension and the path correlation in the time dimension. Then, the effects of the renewable energy technologies on CEE are all positive, showing continuous and effective positive promotion effects, but the performance of technology diffusion is poor, the spillover effect on the adjacent regions is not obvious. And finally, the positive promotion effect of the renewable energy technologies on CEE is affected by the interval of its double threshold effect. • Ultra-efficiency measurement of carbon emissions in the Yangtze River Economic Belt • Renewable energy technology changes from the perspective of patents • Variation characteristics of carbon emissions with basin characteristics • Spatial spillovers and spatial differences of renewable energy technologies • Carbon Reduction Mechanisms for Renewable Energy Technologies [ABSTRACT FROM AUTHOR]

China inaugurated its nationwide emissions trading scheme (ETS) in 2021 as a key policy instrument to fulfill its carbon-peak and carbon-neutrality commitments. The allocation scheme of Chinese ETS is based on grandfathering and benchmarking and has been argued as economically inefficient. This paper proposes an alternative emission quota allocation scheme, a prospective zero-sum gain data envelopment analysis (pZSG-DEA) approach, to efficiently allocate CO 2 emission quotas among market participants. We examined the potential economic gains and losses of implementing this scheme in China. Results showed that the proposed quota allocation can potentially lower the country's carbon intensity in 2020 by an additional 6.96 % compared to the 2005 level. The gains and losses vary substantially across 30 provinces. Beijing, Chongqing, and Zhejiang, were identified as potential quota receivers because increasing their emission quotas could lead to large economic gains; while Liaoning, Hebei, and Guizhou could be major quota givers as their emission reduction is associated with low economic losses. This study could be informative for the design of a high-efficiency emission quota allocation scheme for China's nationally unified emission trading market. • Emission quota allocation via prospective zero-sum gain data envelopment analysis • Welfare distribution effect studied using non-radial directional distance function • Long short-term memory is used to make predictions based on time-series data. • Correlation between carbon emission allocation and economic development [ABSTRACT FROM AUTHOR]

• China's technical progress is biased towards ICT capital and fossil energy. • ICT capital is substitute for fossil energy and complementary to non-fossil energy. • Carbon reduction curve of Subs-KiF is N-shaped, but it's the opposite in Subs-KiN. • Carbon reduction potential of ICT are not fully realized for low carbon economy. Information and communications technology (ICT) investment is beneficial for achieving economic growth within a low carbon system, as the substitution or complementation of ICT to energy offset increased carbon emissions. Based on Chinese provincial panel data during 2000-2018, we incorporate ICT capital as a separate factor to the trans-log production function and identify factor substitution to study ICT's carbon reduction effects. The results show that China's technical progress is more biased towards non-ICT capital, ICT capital and fossil energy, deviate from non-fossil energy and labor. The carbon reduction effect of ICT is manifest by its substitution with fossil energy (0.528) and complementation to non-fossil energy (-0.072), which is comprehensive improvement in both energy productivity and energy structure. Besides, the threshold model reveals an "N" curve carbon reduction effect of substitution elasticity between ICT and fossil energy, whereas it is the opposite for non-fossil energy, and the current substitution elasticities are both in the interval that undermines carbon reduction. This paper confirms ICT's potential in carbon reduction, while this potential is not amplified in production modes of most provinces, and future efforts are required for its suitable match with low carbon transformation. [ABSTRACT FROM AUTHOR]

This paper examines carbon emission growth rates in 35 OECD economies from 1970 to 2019. It analyses the effects of trade liberalisation policy on carbon emissions in interaction with democracy. Both variables serve as potential drivers of adopting emission-reducing technologies. It is observed that trade liberalisation increases carbon dioxide emissions; however, democracy reduces the carbon emission growth rates. In addition, the interaction of trade liberalisation with democracy has a positive impact on carbon dioxide emissions. These findings mean that trade liberalisation has a lessened negative effect on carbon dioxide emissions in more democratic countries. These results indicate several policy implications for the climate change crisis, given that policymakers in democracies do a better job of providing policy formation for climate change than autocracies. [ABSTRACT FROM AUTHOR]

• Rethinking developed countries' contributions to carbon reduction through scenario analysis. • An environmental-extended multi regional input output approach was developed. • Global CO2 emissions would increase by 1.53% in the scenario without trades between germany and other countries. • Increase in emissions in developing countries was greater than in developed countries without free trade. • Germany's contributions in carbon emission reduction were underestimated. The pollution paradise hypothesis states that international trade shifts pollution from developed countries to developing countries, ignoring the positive effects that the participation of developed countries in international trade has on the reduction of carbon emissions. To evaluate a country's contribution to carbon reduction comprehensively, this paper constructed a framework for calculating carbon emissions in two trade scenarios using a multi-regional input-output model. It took Germany as an example, analyzing it at global, national, and sectoral levels. The main findings were as follows: firstly, Germany's contributions to the reduction of emissions may have been underestimated. Without Germany, global embodied CO 2 emissions would have increased by 1.53% on average during the research period. Secondly, Germany's participation in international trade contributed to carbon reduction in developing countries, particularly China and Russia. This was due to the lower intensity of Germany's carbon emissions. Finally, at the sectoral level, changes to carbon emissions in different trade scenarios mainly came from "manufacturing" and "electricity, gas and water supplies". As a result, corresponding policy suggestions were proposed. Studying Germany confirmed that trade protectionism did not benefit the environment and free trade was a better choice. However, more evidence is required to see whether this conclusion would be true for other countries. [ABSTRACT FROM AUTHOR]

• We explore the impact mechanism of ETS on CO 2 emissions from the service sector. • SCM is used to estimate the ETS policy effect. • Intermediate approach is used to identify the carbon emission reduction efficiency. • ETS can be an effective tool to control CO 2 emissions from the service sector. • ETS influences CO 2 emissions by carbon emission reduction efficiency. The service sector has a vital role in achieving emissions reduction, but existing studies on emission trading scheme (ETS) seldom consider CO 2 emissions from service sector. Among the seven ETS pilots in China, those in Beijing and Shanghai cover the service sector. This paper focuses on the Beijing and Shanghai pilots and divides the service sector into the transportation sector and the other service sector. After that, it integrates the synthetic control method and the intermediate approach to analyze the impact mechanism of the ETS on the CO 2 emissions from the service sector. The results show that the ETS has a negative effect on CO 2 emissions from the service sector in China, but the abatement effect is heterogeneous by region and sector. Meanwhile, during the sample period, the impact mechanism of the ETS on CO 2 emissions from the service sector is carbon emission reduction efficiency. [ABSTRACT FROM AUTHOR]

• Time-varying impacts of financial development on CO 2 for the G-7 are examined. • Historical data from 1870 to 2014 for each country is analyzed. • Time-varying co-integration and bootstrap rolling window approaches are utilized. • The impact of financial development on CO 2 is M-shaped in Canada, Japan, and the US. • The impact between the variables is an inverted N-shape in France, Italy, and the UK, while it is an inverted M-shape (W-shaped) in Germany. Financial development has been widely proved to be a key driver of economic growth; however, its environmental impact is still inconclusive, especially for G-7 countries (i.e. Canada, France, Germany, Italy, Japan, the United Kingdom (UK), and the United State (US)). This paper, therefore, investigates the time-varying impact of financial development on carbon dioxide (CO 2) emissions for G-7 countries over a long historical period. The study analyzes historical data from 1870 to 2014 for each country using bootstrap time-varying co-integration (TVC) and bootstrap rolling window estimation approaches. In addition, the polynomial trends of the estimated parameters are obtained to observe the relationship between financial development and carbon emissions. The empirical findings reveal that the impact of financial development on CO 2 emissions over a long history is M-shaped in Canada, Japan, and the US; inverted N-shaped in France, Italy, and the UK; and inverted M-shaped (W-shaped) in Germany. This empirical evidence opens new directions for policy makers to design comprehensive economic policy for using the financial sector as an economic tool to keep environmental quality at sustainable levels. [ABSTRACT FROM AUTHOR]

• 2001–2003 and 2013 were turning points for emissions in the three spaces in china. • Increasing the amount of land for various use did not always raise the emissions. • Change of economic structure made various effects on emissions in the three spaces. As the fastest developing and largest energy-emitting nation in the world, China has been seeking measures to reduce carbon emissions and implement more efficient land-use policies. China's carbon reduction experiences can potentially provide a model for a more sustainable path forward, but increased efforts are needed to understand the factors driving the amount and spatial distribution of carbon emissions and how these drivers are changing through time. This paper develops an understanding of how carbon emissions in three industrial land spaces (agriculture, production and living, and transportation spaces) in China varied across space and through time. A set of complementary models including gravity center and hotspot analysis, alongside an analysis of the relationship between land use and carbon emissions, were implemented to reveal the spatiotemporal distribution of the emissions from 1997 to 2016. Results showed that increasing the extent of land dedicated to different land-uses increased carbon emissions in many areas, but this finding was not universal for all provinces and spaces. Various factors including income, population, energy intensity, energy structure, and economic structure helped explain the variation of emissions across the three types of industrial land spaces. The findings offer implications for China's land use and carbon reduction strategy. [ABSTRACT FROM AUTHOR]

• Carbon emissions network of OECD countries presents a typical network structure. • Carbon is transferred among European countries along with the international trade. • The impact of countries on the edge of the network is still small. • Technology spillovers of environmental regulation on carbon emissions network exist. • Environmental regulation has both inhibition and compensation effects of innovation. Spatial association of carbon emissions between countries has more to do with trade activities. This paper applies the social network analysis to give a clear picture on the evolutionary characteristics of carbon emissions network of Organization for Economic Co-operation and Development (OECD) countries and investigates the technology spillovers of environmental regulation on the carbon emissions network. Empirical results show that: First, the carbon emissions network of OECD countries presents a typical network structure with increasing network density, correlation and decreasing network efficiency. Second, carbon is mainly transferred among European countries along with the international trade, and the impact of countries on the edge of the network is still small. Finally, the U -shape relationship between environmental regulation and carbon emissions network is identified. The innovation inhibition effect exists when the environmental regulation is in a low level, and after arriving at the threshold value, the innovation compensation effect begins to appear. Our findings implied that when making policies for carbon emissions reduction, countries should strengthen the cross-regional communication and fully consider the spatial correlation effect. Some international organizations are supposed to play a leading role in reducing global carbon emissions by controlling the carbon transfer. [ABSTRACT FROM AUTHOR]

• This article analyzed the effects of poverty alleviation on carbon emissions reduction. • Carbon emission efficiency of poverty alleviation has obvious spatial and industrial agglomeration characteristics. • The economic growth trend of "rapid rise, fluctuating growth" derived by poverty alleviation was identified. • Carbon reduction effects of poverty alleviation were continuously optimized. The effective coupling of poverty alleviation and carbon emission reduction goals is an important requirement for sustainable economic development in the present day. In this paper, we utilized socioeconomic data to construct a multiregional input-output (MRIO) table for 27 industries in 30 provinces of China. Multiregional input-output analysis and carbon emission intensity analysis were applied to analyze the effects of poverty alleviation investment on carbon emissions. We found that an investment in poverty alleviation has produced an increase in China's economic aggregate growth from 2010 to 2017. During this time period, the fastest economic growth occurred in 2012 and the regions with the greatest economic drivers were Yunnan and Guizhou. Regarding the industry sector, the construction industry and non-metal products industries had the highest contribution to economy. The economic contribution of the agricultural and food processing industries was insufficient. Poverty alleviation in 26 provinces effectively reduced carbon emission intensity, and the effects were continuously optimized from 2010 to 2017. However, this effect in Inner Mongolia and other 3 provinces was weak. In addition, the effect of carbon emission reduction in the energy production and mining industries was not ideal. This study focuses on the effect of poverty alleviation investment on carbon emissions, which can provide policy guidance for poverty alleviation and green economic growth in China. [ABSTRACT FROM AUTHOR]

• Asymmetric duopoly models of competing supply chains are studied. • Financing risk of carbon emission technology upgradation is examined. • Optimal quantities, prices, and expected profits of chains are compared. • Financing risk plays an important role in model of incomplete information. • Policy suggestions on reducing carbon emissions of chains are provided. The major obstacle to reducing carbon emissions is the high cost of adopting clean energy, which reduces the market competitiveness of companies using clean energy. In this paper, we study the asymmetric duopoly models of two competing supply chains with different carbon emission technology. The financing risk of the supply chain's carbon emission technology investment could be available as complete or incomplete information to its competitor. We find that the financing risk of carbon emission technology upgradation does not affect either chain's choices of equilibrium quantities and prices in the complete information case. If this information is incomplete for the traditional supply chain, financing risk plays an important role in determining optimal quantities and optimal prices. To encourage the use of clean energy technology to reduce carbon emissions, government should use the per-product carbon emission tax to encourage the traditional supply chain to upgrade its carbon emission technology, and should encourage financial institutions to provide preferential loans to the supply chain that has carbon emission technology disadvantage in the market. [ABSTRACT FROM AUTHOR]